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-- https://www.phpmyadmin.net/
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/*!40101 SET NAMES utf8mb4 */;

--
-- Database: `gamification_testing`
--

-- --------------------------------------------------------

--
-- Table structure for table `answers`
--

CREATE TABLE `answers` (
  `id` bigint UNSIGNED NOT NULL,
  `question_id` int UNSIGNED DEFAULT NULL,
  `answer` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
  `is_right` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `answers`
--

INSERT INTO `answers` (`id`, `question_id`, `answer`, `is_right`, `created_at`, `updated_at`) VALUES
(17, 24, 'untuk menuliskan output pada baris baru', 'true', '2023-01-30 06:44:49', '2023-01-30 06:44:49'),
(18, 24, 'untuk menuliskan output pada baris yang sama', NULL, '2023-01-30 06:44:49', '2023-01-30 06:44:49'),
(19, 24, 'untuk mengeluarkan output text', NULL, '2023-01-30 06:44:49', '2023-01-30 06:44:49'),
(20, 24, 'untuk membuat input keyboard', NULL, '2023-01-30 06:44:49', '2023-01-30 06:44:49'),
(21, 25, '1', 'true', '2023-02-18 00:47:48', '2023-02-18 00:47:48'),
(22, 25, '2', NULL, '2023-02-18 00:47:48', '2023-02-18 00:47:48'),
(23, 25, '3', NULL, '2023-02-18 00:47:48', '2023-02-18 00:47:48'),
(24, 25, '!z', NULL, '2023-02-18 00:47:48', '2023-02-18 00:47:48');

-- --------------------------------------------------------

--
-- Table structure for table `badge_settings`
--

CREATE TABLE `badge_settings` (
  `id` int UNSIGNED NOT NULL,
  `name` text COLLATE utf8mb4_unicode_ci NOT NULL,
  `file` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
  `min` int NOT NULL,
  `max` int NOT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `badge_settings`
--

INSERT INTO `badge_settings` (`id`, `name`, `file`, `min`, `max`, `created_at`, `updated_at`) VALUES
(1, 'Warrior', '20220728171009.png', 0, 150, NULL, '2023-06-01 20:54:23'),
(2, 'Elite', '20220728172040.png', 151, 300, NULL, '2023-06-01 20:54:52'),
(3, 'Master', '20220728172051.png', 301, 450, '2022-06-01 15:10:34', '2023-06-01 20:54:57'),
(4, 'Grand Master', '20220728172104.png', 451, 600, '2022-06-01 15:10:34', '2023-06-01 20:55:10'),
(5, 'Epic', '20220728172117.png', 601, 750, '2022-06-01 15:11:23', '2023-06-01 20:56:15'),
(6, 'King', '20220728172150.png', 751, 900, '2022-06-01 15:11:23', '2023-06-01 20:56:38'),
(7, 'Divine', '20220728172317.png', 901, 1300, '2022-06-01 15:12:06', '2023-06-01 20:57:01');

-- --------------------------------------------------------

--
-- Table structure for table `code_error_logs`
--

CREATE TABLE `code_error_logs` (
  `id` bigint UNSIGNED NOT NULL,
  `user_id` bigint UNSIGNED NOT NULL,
  `question_id` int UNSIGNED NOT NULL,
  `total_count` int NOT NULL,
  `error_message` longtext COLLATE utf8mb4_unicode_ci NOT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `code_error_logs`
--

INSERT INTO `code_error_logs` (`id`, `user_id`, `question_id`, `total_count`, `error_message`, `created_at`, `updated_at`) VALUES
(7, 34, 12, 1, 'openjdk 11.0.15 2022-04-19\nOpenJDK Runtime Environment (build 11.0.15+10-Ubuntu-0ubuntu0.18.04.1)\nOpenJDK 64-Bit Server VM (build 11.0.15+10-Ubuntu-0ubuntu0.18.04.1, mixed mode, sharing)\nHello, World!JUnit version 4.13.2\n.E\nTime: 0.008\nThere was 1 failure:\n1) isHelloWorld(example_gmail_com.JUnitHelloWorldTest)\norg.junit.ComparisonFailure: Is Hello World expected:<Hello[] World!> but was:<Hello[,] World!>\n	at org.junit.Assert.assertEquals(Assert.java:117)\n	at example_gmail_com.JUnitHelloWorldTest.isHelloWorld(JUnitHelloWorldTest.java:27)\n\nFAILURES!!!\nTests run: 1,  Failures: 1', '2022-07-28 12:13:59', '2022-07-28 12:13:59'),
(8, 34, 13, 1, 'java_files/example_gmail_com/MyClass.java:7: error: incompatible types: possible lossy conversion from double to int\n		double result = x = y;\n		                    ^\n1 error\nTEST FAILED!', '2022-07-28 12:14:47', '2022-07-28 12:14:47'),
(9, 34, 13, 1, 'java_files/example_gmail_com/MyClass.java:7: error: \';\' expected\n		double result = x + y\n		                     ^\n1 error\nTEST FAILED!', '2022-07-28 12:14:56', '2022-07-28 12:14:56'),
(10, 34, 16, 1, 'java_files/example_gmail_com/Order.java:7: error: illegal start of expression\n		if(itemCost <>> 24.00) {\n		             ^\n1 error\nTEST FAILED!', '2022-07-28 12:15:51', '2022-07-28 12:15:51'),
(11, 34, 16, 1, 'java_files/example_gmail_com/Order.java:7: error: bad operand types for binary operator \'>>\'\n		if(itemCost >> 24.00) {\n		            ^\n  first type:  double\n  second type: double\n1 error\nTEST FAILED!', '2022-07-28 12:15:56', '2022-07-28 12:15:56'),
(12, 34, 16, 1, 'java_files/example_gmail_com/Order.java:12: error: unclosed character literal\n		System.out.print(\'order\');\n		                 ^\njava_files/example_gmail_com/Order.java:12: error: unclosed character literal\n		System.out.print(\'order\');\n		                       ^\njava_files/example_gmail_com/Order.java:12: error: not a statement\n		System.out.print(\'order\');\n		                   ^\n3 errors\nTEST FAILED!', '2022-07-28 12:16:19', '2022-07-28 12:16:19'),
(13, 34, 15, 1, 'java_files/example_gmail_com/NewsFeed.java:14: error: cannot find symbol\n		String topicArray = Arrays.toString(topics);\n		                    ^\n  symbol:   variable Arrays\n  location: class NewsFeed\n1 error\nTEST FAILED!', '2022-07-28 12:17:05', '2022-07-28 12:17:05'),
(14, 34, 15, 1, 'java_files/example_gmail_com/NewsFeed.java:14: error: cannot find symbol\n		String topicArray = arrays.toString(topics);\n		                    ^\n  symbol:   variable arrays\n  location: class NewsFeed\n1 error\nTEST FAILED!', '2022-07-28 12:17:18', '2022-07-28 12:17:18'),
(15, 34, 15, 1, 'java_files/example_gmail_com/NewsFeed.java:3: error: \';\' expected\nimport java.util.Arrays\n                       ^\n1 error\nTEST FAILED!', '2022-07-28 12:17:39', '2022-07-28 12:17:39'),
(16, 1, 12, 1, 'openjdk 11.0.15 2022-04-19\nOpenJDK Runtime Environment (build 11.0.15+10-Ubuntu-0ubuntu0.18.04.1)\nOpenJDK 64-Bit Server VM (build 11.0.15+10-Ubuntu-0ubuntu0.18.04.1, mixed mode, sharing)\nHello, World!JUnit version 4.13.2\n.E\nTime: 0.007\nThere was 1 failure:\n1) isHelloWorld(admin_gmail_com.JUnitHelloWorldTest)\norg.junit.ComparisonFailure: Is Hello World expected:<Hello[] World!> but was:<Hello[,] World!>\n	at org.junit.Assert.assertEquals(Assert.java:117)\n	at admin_gmail_com.JUnitHelloWorldTest.isHelloWorld(JUnitHelloWorldTest.java:27)\n\nFAILURES!!!\nTests run: 1,  Failures: 1', '2022-07-29 04:51:19', '2022-07-29 04:51:19'),
(17, 1, 15, 1, 'java_files/admin_gmail_com/NewsFeed.java:3: error: <identifier> expected\nimport java.util.Arrays.\n                        ^\n1 error\nTEST FAILED!', '2022-07-31 08:29:06', '2022-07-31 08:29:06'),
(18, 1, 13, 1, 'openjdk 11.0.15 2022-04-19\nOpenJDK Runtime Environment (build 11.0.15+10-Ubuntu-0ubuntu0.18.04.1)\nOpenJDK 64-Bit Server VM (build 11.0.15+10-Ubuntu-0ubuntu0.18.04.1, mixed mode, sharing)\n35JUnit version 4.13.2\n.E\nTime: 0.008\nThere was 1 failure:\n1) myResultTest(admin_gmail_com.JUnitMyClassTest)\njava.lang.NoClassDefFoundError: admin_gmail_com/MyClass\n	at admin_gmail_com.JUnitMyClassTest.myResultTest(JUnitMyClassTest.java:30)\n	... 34 trimmed\nCaused by: java.lang.ClassNotFoundException: admin_gmail_com.MyClass\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:581)\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:178)\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:522)\n	... 36 more\n\nFAILURES!!!\nTests run: 1,  Failures: 1', '2022-08-03 05:30:42', '2022-08-03 05:30:42'),
(19, 1, 13, 1, 'openjdk 11.0.15 2022-04-19\nOpenJDK Runtime Environment (build 11.0.15+10-Ubuntu-0ubuntu0.18.04.1)\nOpenJDK 64-Bit Server VM (build 11.0.15+10-Ubuntu-0ubuntu0.18.04.1, mixed mode, sharing)\n35JUnit version 4.13.2\n.E\nTime: 0.007\nThere was 1 failure:\n1) myResultTest(admin_gmail_com.JUnitMyClassTest)\norg.junit.ComparisonFailure: MyClass Double Result expected:<35[.5]> but was:<35[]>\n	at org.junit.Assert.assertEquals(Assert.java:117)\n	at admin_gmail_com.JUnitMyClassTest.myResultTest(JUnitMyClassTest.java:31)\n\nFAILURES!!!\nTests run: 1,  Failures: 1', '2022-08-03 05:30:43', '2022-08-03 05:30:43'),
(20, 37, 22, 1, 'java_files\\adminku_gmail_com\\OrderCase.java:44: error: unmappable character (0xA0) for encoding UTF-8\r\n	??}\r\n	^\r\njava_files\\adminku_gmail_com\\OrderCase.java:44: error: unmappable character (0xA0) for encoding UTF-8\r\n	??}\r\n	 ^\r\n2 errors\r\nTEST FAILED!', '2023-01-18 00:52:47', '2023-01-18 00:52:47'),
(21, 38, 12, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHello, World!\r\nJUnit version 4.13.2\r\n.E\r\nTime: 0.017\r\nThere was 1 failure:\r\n1) isHelloWorld(test_gmail_com.JUnitHelloWorldTest)\r\norg.junit.ComparisonFailure: Is Hello World not same expected:<Hello[ World!]> but was:<Hello[, World!\r\n]>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at test_gmail_com.JUnitHelloWorldTest.isHelloWorld(JUnitHelloWorldTest.java:27)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-01-18 00:54:58', '2023-01-18 00:54:58'),
(22, 38, 12, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHello, World!\r\nJUnit version 4.13.2\r\n.E\r\nTime: 0.023\r\nThere was 1 failure:\r\n1) isHelloWorld(test_gmail_com.JUnitHelloWorldTest)\r\norg.junit.ComparisonFailure: Is Hello World not same expected:<Hello[ World!]> but was:<Hello[, World!\r\n]>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at test_gmail_com.JUnitHelloWorldTest.isHelloWorld(JUnitHelloWorldTest.java:27)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-01-18 00:55:21', '2023-01-18 00:55:21'),
(23, 38, 12, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHello, World!JUnit version 4.13.2\r\n.E\r\nTime: 0.019\r\nThere was 1 failure:\r\n1) isHelloWorld(test_gmail_com.JUnitHelloWorldTest)\r\norg.junit.ComparisonFailure: Is Hello World not same expected:<Hello[] World!> but was:<Hello[,] World!>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at test_gmail_com.JUnitHelloWorldTest.isHelloWorld(JUnitHelloWorldTest.java:27)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-01-18 00:55:30', '2023-01-18 00:55:30'),
(24, 37, 21, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\neav\'ns JUnit version 4.13.2\r\n.E\r\nTime: 0.004\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [adminku_gmail_com.JUnitPoetryTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: adminku_gmail_com.JUnitPoetryTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-01-23 06:58:13', '2023-01-23 06:58:13'),
(25, 37, 21, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHeav\'ns JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [adminku_gmail_com.JUnitPoetryTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: adminku_gmail_com.JUnitPoetryTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-01-23 06:59:00', '2023-01-23 06:59:00'),
(26, 39, 13, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n30.5JUnit version 4.13.2\r\n.E\r\nTime: 0.006\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [irul_gmail_com.JUnitMyClasssTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: irul_gmail_com.JUnitMyClasssTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-01-23 07:03:28', '2023-01-23 07:03:28'),
(27, 39, 13, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n30.5JUnit version 4.13.2\r\n.E\r\nTime: 0.005\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [irul_gmail_com.JUnitMyClasssTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: irul_gmail_com.JUnitMyClasssTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-01-23 07:05:49', '2023-01-23 07:05:49'),
(28, 39, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.E\r\nTime: 0.004\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [irul_gmail_com.JUnitOrderTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: irul_gmail_com.JUnitOrderTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-01-23 07:11:59', '2023-01-23 07:11:59'),
(29, 39, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.E\r\nTime: 0.006\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [irul_gmail_com.JUnitOrderTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: irul_gmail_com.JUnitOrderTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-01-23 07:12:56', '2023-01-23 07:12:56'),
(30, 39, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.E\r\nTime: 0.004\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [irul_gmail_com.JUnitOrderTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: irul_gmail_com.JUnitOrderTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-01-23 07:13:36', '2023-01-23 07:13:36'),
(31, 40, 12, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nhello world!JUnit version 4.13.2\r\n.E\r\nTime: 0.035\r\nThere was 1 failure:\r\n1) isHelloWorld(siskanyoba_gmail_com.JUnitHelloWorldTest)\r\norg.junit.ComparisonFailure: Is Hello World not same expected:<[Hello W]orld!> but was:<[hello w]orld!>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at siskanyoba_gmail_com.JUnitHelloWorldTest.isHelloWorld(JUnitHelloWorldTest.java:27)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-01-25 22:01:16', '2023-01-25 22:01:16'),
(32, 41, 13, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n30.5JUnit version 4.13.2\r\n.E\r\nTime: 0.004\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [seli_gmail_com.JUnitMyClasssTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: seli_gmail_com.JUnitMyClasssTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-09 22:25:09', '2023-02-09 22:25:09'),
(33, 41, 13, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n30.5JUnit version 4.13.2\r\n.E\r\nTime: 0.008\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [seli_gmail_com.JUnitMyClasssTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: seli_gmail_com.JUnitMyClasssTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-09 22:26:43', '2023-02-09 22:26:43'),
(34, 41, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.E\r\nTime: 0.004\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [seli_gmail_com.JUnitOrderTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: seli_gmail_com.JUnitOrderTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-09 22:29:41', '2023-02-09 22:29:41'),
(35, 41, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [seli_gmail_com.JUnitOrderTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: seli_gmail_com.JUnitOrderTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-09 22:32:29', '2023-02-09 22:32:29'),
(36, 41, 22, 1, 'java_files\\seli_gmail_com\\OrderCase.java:44: error: unmappable character (0xA0) for encoding UTF-8\r\n	??}\r\n	^\r\njava_files\\seli_gmail_com\\OrderCase.java:44: error: unmappable character (0xA0) for encoding UTF-8\r\n	??}\r\n	 ^\r\n2 errors\r\nTEST FAILED!', '2023-02-09 22:35:00', '2023-02-09 22:35:00'),
(37, 41, 22, 1, 'java_files\\seli_gmail_com\\OrderCase.java:44: error: unmappable character (0xA0) for encoding UTF-8\r\n	??}\r\n	^\r\njava_files\\seli_gmail_com\\OrderCase.java:44: error: unmappable character (0xA0) for encoding UTF-8\r\n	??}\r\n	 ^\r\n2 errors\r\nTEST FAILED!', '2023-02-09 22:36:18', '2023-02-09 22:36:18'),
(38, 43, 13, 1, 'java_files\\riko_gmail_com\\MyClasss.java:3: error: class, interface, enum, or record expected\r\npackage junit;\r\n^\r\n1 error\r\nTEST FAILED!', '2023-02-09 22:40:12', '2023-02-09 22:40:12'),
(39, 43, 13, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n30.5JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [riko_gmail_com.JUnitMyClasssTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: riko_gmail_com.JUnitMyClasssTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-09 22:40:29', '2023-02-09 22:40:29'),
(40, 43, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [riko_gmail_com.JUnitOrderTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: riko_gmail_com.JUnitOrderTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-13 18:53:56', '2023-02-13 18:53:56'),
(41, 43, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.E\r\nTime: 0.005\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [riko_gmail_com.JUnitOrderTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: riko_gmail_com.JUnitOrderTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-13 18:55:37', '2023-02-13 18:55:37'),
(42, 43, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.E\r\nTime: 0.004\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [riko_gmail_com.JUnitOrderTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: riko_gmail_com.JUnitOrderTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-13 18:58:25', '2023-02-13 18:58:25'),
(43, 43, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.E\r\nTime: 0.004\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [riko_gmail_com.JUnitOrderTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: riko_gmail_com.JUnitOrderTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-13 18:58:33', '2023-02-13 18:58:33'),
(44, 43, 22, 1, 'java_files\\riko_gmail_com\\OrderCase.java:44: error: unmappable character (0xA0) for encoding UTF-8\r\n	??}\r\n	^\r\njava_files\\riko_gmail_com\\OrderCase.java:44: error: unmappable character (0xA0) for encoding UTF-8\r\n	??}\r\n	 ^\r\n2 errors\r\nTEST FAILED!', '2023-02-13 19:01:35', '2023-02-13 19:01:35'),
(45, 43, 21, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\neav\'ns JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [riko_gmail_com.JUnitPoetryTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: riko_gmail_com.JUnitPoetryTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-13 19:07:12', '2023-02-13 19:07:12'),
(46, 43, 21, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHeav\'ns JUnit version 4.13.2\r\n.E\r\nTime: 0.005\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [riko_gmail_com.JUnitPoetryTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: riko_gmail_com.JUnitPoetryTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-13 19:07:29', '2023-02-13 19:07:29'),
(47, 43, 21, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHeav\'ns JUnit version 4.13.2\r\n.E\r\nTime: 0.004\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [riko_gmail_com.JUnitPoetryTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: riko_gmail_com.JUnitPoetryTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-13 19:07:35', '2023-02-13 19:07:35'),
(48, 43, 21, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHeav\'ns JUnit version 4.13.2\r\n.E\r\nTime: 0.005\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [riko_gmail_com.JUnitPoetryTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: riko_gmail_com.JUnitPoetryTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-13 19:08:51', '2023-02-13 19:08:51'),
(49, 43, 20, 1, 'java_files\\riko_gmail_com\\Password.java:11: error: \')\' expected\r\n	    System.out.print(password.compareTo(\"correcthorsebatterystaple\");\r\n	                                                                    ^\r\n1 error\r\nTEST FAILED!', '2023-02-13 19:17:56', '2023-02-13 19:17:56'),
(50, 43, 20, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\ntrue0JUnit version 4.13.2\r\n.E\r\nTime: 0.004\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [riko_gmail_com.JUnitPasswordTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: riko_gmail_com.JUnitPasswordTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-13 19:18:15', '2023-02-13 19:18:15'),
(51, 43, 20, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n0trueJUnit version 4.13.2\r\n.E\r\nTime: 0.004\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [riko_gmail_com.JUnitPasswordTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: riko_gmail_com.JUnitPasswordTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-13 19:19:39', '2023-02-13 19:19:39'),
(52, 45, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.E\r\nTime: 0.004\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [gaga_gmail_com.JUnitOrderTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: gaga_gmail_com.JUnitOrderTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-17 22:25:40', '2023-02-17 22:25:40');
INSERT INTO `code_error_logs` (`id`, `user_id`, `question_id`, `total_count`, `error_message`, `created_at`, `updated_at`) VALUES
(53, 45, 18, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.E\r\nTime: 0.005\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [gaga_gmail_com.JUnitLuckyFiveTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: gaga_gmail_com.JUnitLuckyFiveTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-17 22:33:57', '2023-02-17 22:33:57'),
(54, 45, 20, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n0trueJUnit version 4.13.2\r\n.E\r\nTime: 0.007\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [gaga_gmail_com.JUnitPasswordTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: gaga_gmail_com.JUnitPasswordTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-17 22:39:37', '2023-02-17 22:39:37'),
(55, 45, 21, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHeav\'nsJUnit version 4.13.2\r\n.E\r\nTime: 0.002\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [gaga_gmail_com.JUnitPoetryTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: gaga_gmail_com.JUnitPoetryTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 00:18:39', '2023-02-18 00:18:39'),
(56, 45, 21, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHeav\'nsJUnit version 4.13.2\r\n.E\r\nTime: 0.002\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [gaga_gmail_com.JUnitPoetryTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: gaga_gmail_com.JUnitPoetryTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 00:20:56', '2023-02-18 00:20:56'),
(57, 45, 21, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHeav\'nsJUnit version 4.13.2\r\n.E\r\nTime: 0.002\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [gaga_gmail_com.JUnitPoetryTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: gaga_gmail_com.JUnitPoetryTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 00:22:40', '2023-02-18 00:22:40'),
(58, 46, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!\r\nJUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [testing_gmail_com.JUnitOrderTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: testing_gmail_com.JUnitOrderTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 00:28:29', '2023-02-18 00:28:29'),
(59, 46, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!\r\nJUnit version 4.13.2\r\n.E\r\nTime: 0.024\r\nThere was 1 failure:\r\n1) myResultTest(testing_gmail_com.JUnitOrderTest)\r\njava.lang.NoClassDefFoundError: testing_gmail_com/Order\r\n	at testing_gmail_com.JUnitOrderTest.myResultTest(JUnitOrderTest.java:29)\r\n	... 32 trimmed\r\nCaused by: java.lang.ClassNotFoundException: testing_gmail_com.Order\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	... 34 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 00:37:56', '2023-02-18 00:37:56'),
(60, 46, 16, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!\r\nJUnit version 4.13.2\r\n.E\r\nTime: 0.025\r\nThere was 1 failure:\r\n1) myResultTest(testing_gmail_com.JUnitOrderTest)\r\norg.junit.ComparisonFailure: itemCost Condition not same expected:<High Value Item![]> but was:<High Value Item![\r\n]>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at testing_gmail_com.JUnitOrderTest.myResultTest(JUnitOrderTest.java:30)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 00:39:14', '2023-02-18 00:39:14'),
(61, 46, 15, 1, 'java_files\\testing_gmail_com\\NewsFeed.java:15: error: cannot find symbol\r\n		String topicArray = Arrays.toString(topics);\r\n		                    ^\r\n  symbol:   variable Arrays\r\n  location: class NewsFeed\r\n1 error\r\nTEST FAILED!', '2023-02-18 01:01:00', '2023-02-18 01:01:00'),
(62, 46, 15, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.E\r\nTime: 0.002\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [testing_gmail_com.JUnitNewsFeedTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: testing_gmail_com.JUnitNewsFeedTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 01:01:59', '2023-02-18 01:01:59'),
(63, 46, 15, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.E\r\nTime: 0.002\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [testing_gmail_com.JUnitNewsFeedTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: testing_gmail_com.JUnitNewsFeedTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 01:02:26', '2023-02-18 01:02:26'),
(64, 46, 15, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [testing_gmail_com.JUnitNewsFeedTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: testing_gmail_com.JUnitNewsFeedTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 01:02:40', '2023-02-18 01:02:40'),
(65, 46, 15, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [testing_gmail_com.JUnitNewsFeedTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: testing_gmail_com.JUnitNewsFeedTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 01:02:50', '2023-02-18 01:02:50'),
(66, 46, 15, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [testing_gmail_com.JUnitNewsFeedTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: testing_gmail_com.JUnitNewsFeedTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 01:04:21', '2023-02-18 01:04:21'),
(67, 46, 15, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.E\r\nTime: 0.002\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [testing_gmail_com.JUnitNewsFeedTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: testing_gmail_com.JUnitNewsFeedTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 01:06:01', '2023-02-18 01:06:01'),
(68, 46, 15, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [testing_gmail_com.JUnitNewsFeedTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: testing_gmail_com.JUnitNewsFeedTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 01:06:39', '2023-02-18 01:06:39'),
(69, 46, 17, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.E\r\nTime: 0.002\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [testing_gmail_com.JUnitLuckyFiveSecondTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: testing_gmail_com.JUnitLuckyFiveSecondTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-02-18 01:10:00', '2023-02-18 01:10:00'),
(70, 47, 15, 1, 'java_files\\lisa_gmail_com\\NewsFeed.java:14: error: cannot find symbol\r\n		String topicArray = Arrays.toString(topics);\r\n		                    ^\r\n  symbol:   variable Arrays\r\n  location: class NewsFeed\r\n1 error\r\nTEST FAILED!', '2023-02-19 21:10:13', '2023-02-19 21:10:13'),
(71, 47, 17, 1, 'java_files\\lisa_gmail_com\\LuckyFiveSecond.java:15: error: \')\' expected\r\n	      luck.loop(isikan dengan angka);\r\n	                      ^\r\njava_files\\lisa_gmail_com\\LuckyFiveSecond.java:15: error: \';\' expected\r\n	      luck.loop(isikan dengan angka);\r\n	                                   ^\r\n2 errors\r\nTEST FAILED!', '2023-02-19 21:22:56', '2023-02-19 21:22:56'),
(72, 48, 13, 1, 'java_files\\rika_gmail_com\\MyClass.java:3: error: class, interface, enum, or record expected\r\npackage junit;\r\n^\r\n1 error\r\nTEST FAILED!', '2023-03-06 05:21:10', '2023-03-06 05:21:10'),
(73, 48, 18, 1, 'java_files\\rika_gmail_com\\LuckyFive.java:13: error: cannot find symbol\r\n		luck.loop(6);\r\n		^\r\n  symbol:   variable luck\r\n  location: class LuckyFive\r\n1 error\r\nTEST FAILED!', '2023-03-06 06:22:47', '2023-03-06 06:22:47'),
(74, 48, 18, 1, 'java_files\\rika_gmail_com\\LuckyFive.java:12: error: \';\' expected\r\n        classs LuckyFive\r\n                        ^\r\n1 error\r\nTEST FAILED!', '2023-03-06 06:23:03', '2023-03-06 06:23:03'),
(75, 48, 18, 1, 'java_files\\rika_gmail_com\\LuckyFive.java:12: error: \';\' expected\r\n        classs LuckyFive\r\n                        ^\r\n1 error\r\nTEST FAILED!', '2023-03-06 06:23:26', '2023-03-06 06:23:26'),
(76, 48, 20, 1, 'java_files\\rika_gmail_com\\Password.java:16: error: <identifier> expected\r\n	    System.out.print(pass. //equals);\r\n	                          ^\r\n1 error\r\nTEST FAILED!', '2023-03-06 06:26:04', '2023-03-06 06:26:04'),
(77, 48, 20, 1, 'java_files\\rika_gmail_com\\Password.java:16: error: <identifier> expected\r\n	    System.out.print(pass. //equals);\r\n	                          ^\r\n1 error\r\nTEST FAILED!', '2023-03-06 06:26:22', '2023-03-06 06:26:22'),
(78, 48, 21, 1, 'java_files\\rika_gmail_com\\Poetry.java:15: error: no suitable method found for substring(no arguments)\r\n    System.out.print(line.substring());\r\n                         ^\r\n    method String.substring(int) is not applicable\r\n      (actual and formal argument lists differ in length)\r\n    method String.substring(int,int) is not applicable\r\n      (actual and formal argument lists differ in length)\r\n1 error\r\nTEST FAILED!', '2023-03-06 06:42:51', '2023-03-06 06:42:51'),
(79, 48, 21, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n Heav\'nJUnit version 4.13.2\r\n.E\r\nTime: 0.027\r\nThere was 1 failure:\r\n1) isPoetry(rika_gmail_com.JUnitPoetryTest)\r\norg.junit.ComparisonFailure: Poetry not same expected:<[Heav\'ns]> but was:<[ Heav\'n]>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at rika_gmail_com.JUnitPoetryTest.isPoetry(JUnitPoetryTest.java:29)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-03-06 06:43:15', '2023-03-06 06:43:15'),
(80, 48, 21, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\ne Heav\'nsJUnit version 4.13.2\r\n.E\r\nTime: 0.015\r\nThere was 1 failure:\r\n1) isPoetry(rika_gmail_com.JUnitPoetryTest)\r\norg.junit.ComparisonFailure: Poetry not same expected:<[]Heav\'ns> but was:<[e ]Heav\'ns>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at rika_gmail_com.JUnitPoetryTest.isPoetry(JUnitPoetryTest.java:29)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-03-06 06:43:53', '2023-03-06 06:43:53'),
(81, 48, 21, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHeav\'ns JUnit version 4.13.2\r\n.E\r\nTime: 0.016\r\nThere was 1 failure:\r\n1) isPoetry(rika_gmail_com.JUnitPoetryTest)\r\norg.junit.ComparisonFailure: Poetry not same expected:<Heav\'ns[]> but was:<Heav\'ns[ ]>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at rika_gmail_com.JUnitPoetryTest.isPoetry(JUnitPoetryTest.java:29)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-03-06 06:44:25', '2023-03-06 06:44:25'),
(82, 50, 23, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nShipping cost: 7.0JUnit version 4.13.2\r\n.E\r\nTime: 0.042\r\nThere was 1 failure:\r\n1) myOrderCaseResult(test0903_gmail_com.JUnitOrderNestTest)\r\norg.junit.ComparisonFailure: ShippingCost not same expected:<Shipping cost: [0.85]> but was:<Shipping cost: [7.0]>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at test0903_gmail_com.JUnitOrderNestTest.myOrderCaseResult(JUnitOrderNestTest.java:28)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-03-09 21:42:13', '2023-03-09 21:42:13'),
(83, 50, 23, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nShipping cost: 7.0JUnit version 4.13.2\r\n.E\r\nTime: 0.044\r\nThere was 1 failure:\r\n1) myOrderCaseResult(test0903_gmail_com.JUnitOrderNestTest)\r\norg.junit.ComparisonFailure: ShippingCost not same expected:<Shipping cost: [0.85]> but was:<Shipping cost: [7.0]>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at test0903_gmail_com.JUnitOrderNestTest.myOrderCaseResult(JUnitOrderNestTest.java:28)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', '2023-03-09 21:42:48', '2023-03-09 21:42:48');

-- --------------------------------------------------------

--
-- Table structure for table `code_history_logs`
--

CREATE TABLE `code_history_logs` (
  `id` bigint UNSIGNED NOT NULL,
  `user_id` bigint UNSIGNED NOT NULL,
  `question_id` int UNSIGNED NOT NULL,
  `total_count` int NOT NULL,
  `message` longtext COLLATE utf8mb4_unicode_ci NOT NULL,
  `is_error` int NOT NULL DEFAULT '0',
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `code_history_logs`
--

INSERT INTO `code_history_logs` (`id`, `user_id`, `question_id`, `total_count`, `message`, `is_error`, `created_at`, `updated_at`) VALUES
(1, 2, 1, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.031\r\n\r\nOK (1 test)', 0, '2023-06-01 18:47:05', '2023-06-01 18:47:05'),
(2, 2, 2, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2023-06-01 19:32:08', '2023-06-01 19:32:08'),
(3, 2, 3, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.E\r\nTime: 0.012\r\nThere was 1 failure:\r\n1) initializationError(test0106_gmail_com.JUnitOrderTest)\r\norg.junit.runners.model.InvalidTestClassError: Invalid test class \'test0106_gmail_com.JUnitOrderTest\':\n  1. No runnable methods\r\n	at org.junit.runners.ParentRunner.validate(ParentRunner.java:525)\r\n	at org.junit.runners.ParentRunner.<init>(ParentRunner.java:102)\r\n	at org.junit.runners.BlockJUnit4ClassRunner.<init>(BlockJUnit4ClassRunner.java:84)\r\n	at org.junit.runners.JUnit4.<init>(JUnit4.java:23)\r\n	at org.junit.internal.builders.JUnit4Builder.runnerForClass(JUnit4Builder.java:10)\r\n	at org.junit.runners.model.RunnerBuilder.safeRunnerForClass(RunnerBuilder.java:70)\r\n	at org.junit.internal.builders.AllDefaultPossibilitiesBuilder.runnerForClass(AllDefaultPossibilitiesBuilder.java:37)\r\n	at org.junit.runner.Computer.getRunner(Computer.java:50)\r\n	at org.junit.runner.Computer$1.runnerForClass(Computer.java:31)\r\n	at org.junit.runners.model.RunnerBuilder.safeRunnerForClass(RunnerBuilder.java:70)\r\n	at org.junit.runners.model.RunnerBuilder.runners(RunnerBuilder.java:125)\r\n	at org.junit.runners.model.RunnerBuilder.runners(RunnerBuilder.java:111)\r\n	at org.junit.runners.Suite.<init>(Suite.java:81)\r\n	at org.junit.runner.Computer$2.<init>(Computer.java:33)\r\n	at org.junit.runner.Computer.getSuite(Computer.java:28)\r\n	at org.junit.runner.Request.classes(Request.java:77)\r\n	at org.junit.runner.JUnitCommandLineParseResult.createRequest(JUnitCommandLineParseResult.java:116)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:77)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-06-01 19:44:07', '2023-06-01 19:44:07'),
(4, 2, 3, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.022\r\n\r\nOK (1 test)', 0, '2023-06-01 19:44:48', '2023-06-01 19:44:48'),
(5, 2, 4, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.E\r\nTime: 0.009\r\nThere was 1 failure:\r\n1) initializationError(test0106_gmail_com.JUnitOrderCaseTest)\r\norg.junit.runners.model.InvalidTestClassError: Invalid test class \'test0106_gmail_com.JUnitOrderCaseTest\':\n  1. No runnable methods\r\n	at org.junit.runners.ParentRunner.validate(ParentRunner.java:525)\r\n	at org.junit.runners.ParentRunner.<init>(ParentRunner.java:102)\r\n	at org.junit.runners.BlockJUnit4ClassRunner.<init>(BlockJUnit4ClassRunner.java:84)\r\n	at org.junit.runners.JUnit4.<init>(JUnit4.java:23)\r\n	at org.junit.internal.builders.JUnit4Builder.runnerForClass(JUnit4Builder.java:10)\r\n	at org.junit.runners.model.RunnerBuilder.safeRunnerForClass(RunnerBuilder.java:70)\r\n	at org.junit.internal.builders.AllDefaultPossibilitiesBuilder.runnerForClass(AllDefaultPossibilitiesBuilder.java:37)\r\n	at org.junit.runner.Computer.getRunner(Computer.java:50)\r\n	at org.junit.runner.Computer$1.runnerForClass(Computer.java:31)\r\n	at org.junit.runners.model.RunnerBuilder.safeRunnerForClass(RunnerBuilder.java:70)\r\n	at org.junit.runners.model.RunnerBuilder.runners(RunnerBuilder.java:125)\r\n	at org.junit.runners.model.RunnerBuilder.runners(RunnerBuilder.java:111)\r\n	at org.junit.runners.Suite.<init>(Suite.java:81)\r\n	at org.junit.runner.Computer$2.<init>(Computer.java:33)\r\n	at org.junit.runner.Computer.getSuite(Computer.java:28)\r\n	at org.junit.runner.Request.classes(Request.java:77)\r\n	at org.junit.runner.JUnitCommandLineParseResult.createRequest(JUnitCommandLineParseResult.java:116)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:77)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-06-01 20:43:59', '2023-06-01 20:43:59'),
(6, 2, 4, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.03\r\n\r\nOK (1 test)', 0, '2023-06-01 20:46:37', '2023-06-01 20:46:37'),
(7, 2, 5, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [test0106_gmail_com.JUnitBookStoreTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: test0106_gmail_com.JUnitBookStoreTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-06-03 05:15:24', '2023-06-03 05:15:24'),
(8, 2, 5, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.028\r\n\r\nOK (1 test)', 0, '2023-06-03 05:18:32', '2023-06-03 05:18:32'),
(9, 2, 5, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.032\r\n\r\nOK (1 test)', 0, '2023-06-03 05:54:43', '2023-06-03 05:54:43'),
(10, 2, 4, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.033\r\n\r\nOK (1 test)', 0, '2023-06-03 05:58:17', '2023-06-03 05:58:17'),
(11, 2, 6, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.E\r\nTime: 0.009\r\nThere was 1 failure:\r\n1) initializationError(test0106_gmail_com.JUnitLuckyFiveTest)\r\norg.junit.runners.model.InvalidTestClassError: Invalid test class \'test0106_gmail_com.JUnitLuckyFiveTest\':\n  1. No runnable methods\r\n	at org.junit.runners.ParentRunner.validate(ParentRunner.java:525)\r\n	at org.junit.runners.ParentRunner.<init>(ParentRunner.java:102)\r\n	at org.junit.runners.BlockJUnit4ClassRunner.<init>(BlockJUnit4ClassRunner.java:84)\r\n	at org.junit.runners.JUnit4.<init>(JUnit4.java:23)\r\n	at org.junit.internal.builders.JUnit4Builder.runnerForClass(JUnit4Builder.java:10)\r\n	at org.junit.runners.model.RunnerBuilder.safeRunnerForClass(RunnerBuilder.java:70)\r\n	at org.junit.internal.builders.AllDefaultPossibilitiesBuilder.runnerForClass(AllDefaultPossibilitiesBuilder.java:37)\r\n	at org.junit.runner.Computer.getRunner(Computer.java:50)\r\n	at org.junit.runner.Computer$1.runnerForClass(Computer.java:31)\r\n	at org.junit.runners.model.RunnerBuilder.safeRunnerForClass(RunnerBuilder.java:70)\r\n	at org.junit.runners.model.RunnerBuilder.runners(RunnerBuilder.java:125)\r\n	at org.junit.runners.model.RunnerBuilder.runners(RunnerBuilder.java:111)\r\n	at org.junit.runners.Suite.<init>(Suite.java:81)\r\n	at org.junit.runner.Computer$2.<init>(Computer.java:33)\r\n	at org.junit.runner.Computer.getSuite(Computer.java:28)\r\n	at org.junit.runner.Request.classes(Request.java:77)\r\n	at org.junit.runner.JUnitCommandLineParseResult.createRequest(JUnitCommandLineParseResult.java:116)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:77)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-06-03 06:10:57', '2023-06-03 06:10:57'),
(12, 2, 6, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2023-06-03 06:11:30', '2023-06-03 06:11:30'),
(13, 2, 6, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.03\r\n\r\nOK (1 test)', 0, '2023-06-03 06:26:19', '2023-06-03 06:26:19'),
(14, 2, 6, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2023-06-03 06:34:31', '2023-06-03 06:34:31'),
(15, 2, 6, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.031\r\n\r\nOK (1 test)', 0, '2023-06-03 06:39:19', '2023-06-03 06:39:19'),
(16, 2, 6, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.024\r\n\r\nOK (1 test)', 0, '2023-06-03 06:40:22', '2023-06-03 06:40:22'),
(17, 2, 7, 1, 'java_files\\test0106_gmail_com\\LuckyFiveSecond.java:6: error: \';\' expected\r\n	      int number 6;\r\n	                ^\r\n1 error\r\nTEST FAILED!', 1, '2023-06-04 06:26:14', '2023-06-04 06:26:14'),
(18, 2, 7, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.021\r\n\r\nOK (1 test)', 0, '2023-06-04 06:26:46', '2023-06-04 06:26:46'),
(19, 2, 8, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nDeret Fibonnaci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [test0106_gmail_com.JUnitFibonacciTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: test0106_gmail_com.JUnitFibonacciTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-06-04 06:29:11', '2023-06-04 06:29:11'),
(20, 2, 8, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nDeret Fibonnaci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.E\r\nTime: 0.005\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [test0106_gmail_com.JUnitFibonacciTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: test0106_gmail_com.JUnitFibonacciTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-06-04 06:34:29', '2023-06-04 06:34:29'),
(21, 2, 8, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nDeret Fibonnaci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [test0106_gmail_com.JUnitFibonacciTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: test0106_gmail_com.JUnitFibonacciTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-06-04 06:34:37', '2023-06-04 06:34:37'),
(22, 2, 8, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nDeret Fibonnaci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.E\r\nTime: 0.009\r\nThere was 1 failure:\r\n1) initializationError(test0106_gmail_com.JUnitFibonacciTest)\r\norg.junit.runners.model.InvalidTestClassError: Invalid test class \'test0106_gmail_com.JUnitFibonacciTest\':\n  1. No runnable methods\r\n	at org.junit.runners.ParentRunner.validate(ParentRunner.java:525)\r\n	at org.junit.runners.ParentRunner.<init>(ParentRunner.java:102)\r\n	at org.junit.runners.BlockJUnit4ClassRunner.<init>(BlockJUnit4ClassRunner.java:84)\r\n	at org.junit.runners.JUnit4.<init>(JUnit4.java:23)\r\n	at org.junit.internal.builders.JUnit4Builder.runnerForClass(JUnit4Builder.java:10)\r\n	at org.junit.runners.model.RunnerBuilder.safeRunnerForClass(RunnerBuilder.java:70)\r\n	at org.junit.internal.builders.AllDefaultPossibilitiesBuilder.runnerForClass(AllDefaultPossibilitiesBuilder.java:37)\r\n	at org.junit.runner.Computer.getRunner(Computer.java:50)\r\n	at org.junit.runner.Computer$1.runnerForClass(Computer.java:31)\r\n	at org.junit.runners.model.RunnerBuilder.safeRunnerForClass(RunnerBuilder.java:70)\r\n	at org.junit.runners.model.RunnerBuilder.runners(RunnerBuilder.java:125)\r\n	at org.junit.runners.model.RunnerBuilder.runners(RunnerBuilder.java:111)\r\n	at org.junit.runners.Suite.<init>(Suite.java:81)\r\n	at org.junit.runner.Computer$2.<init>(Computer.java:33)\r\n	at org.junit.runner.Computer.getSuite(Computer.java:28)\r\n	at org.junit.runner.Request.classes(Request.java:77)\r\n	at org.junit.runner.JUnitCommandLineParseResult.createRequest(JUnitCommandLineParseResult.java:116)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:77)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-06-04 06:35:26', '2023-06-04 06:35:26'),
(23, 2, 8, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nDeret Fibonnaci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.E\r\nTime: 0.035\r\nThere was 1 failure:\r\n1) isFibonnaci(test0106_gmail_com.JUnitFibonacciTest)\r\norg.junit.ComparisonFailure: Output not the same expected:<Deret Fibon[ac]ci: \n0 1 1 2 3 5 8 1...> but was:<Deret Fibon[na]ci: \n0 1 1 2 3 5 8 1...>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at test0106_gmail_com.JUnitFibonacciTest.isFibonnaci(JUnitFibonacciTest.java:30)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-06-04 06:47:46', '2023-06-04 06:47:46'),
(24, 2, 8, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.034\r\n\r\nOK (1 test)', 0, '2023-06-04 06:48:17', '2023-06-04 06:48:17'),
(25, 2, 9, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2023-06-04 06:57:40', '2023-06-04 06:57:40'),
(26, 2, 10, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.E\r\nTime: 0.006\r\nThere was 1 failure:\r\n1) initializationError(test0106_gmail_com.JUnitNewsFeedTest)\r\norg.junit.runners.model.InvalidTestClassError: Invalid test class \'test0106_gmail_com.JUnitNewsFeedTest\':\n  1. No runnable methods\r\n	at org.junit.runners.ParentRunner.validate(ParentRunner.java:525)\r\n	at org.junit.runners.ParentRunner.<init>(ParentRunner.java:102)\r\n	at org.junit.runners.BlockJUnit4ClassRunner.<init>(BlockJUnit4ClassRunner.java:84)\r\n	at org.junit.runners.JUnit4.<init>(JUnit4.java:23)\r\n	at org.junit.internal.builders.JUnit4Builder.runnerForClass(JUnit4Builder.java:10)\r\n	at org.junit.runners.model.RunnerBuilder.safeRunnerForClass(RunnerBuilder.java:70)\r\n	at org.junit.internal.builders.AllDefaultPossibilitiesBuilder.runnerForClass(AllDefaultPossibilitiesBuilder.java:37)\r\n	at org.junit.runner.Computer.getRunner(Computer.java:50)\r\n	at org.junit.runner.Computer$1.runnerForClass(Computer.java:31)\r\n	at org.junit.runners.model.RunnerBuilder.safeRunnerForClass(RunnerBuilder.java:70)\r\n	at org.junit.runners.model.RunnerBuilder.runners(RunnerBuilder.java:125)\r\n	at org.junit.runners.model.RunnerBuilder.runners(RunnerBuilder.java:111)\r\n	at org.junit.runners.Suite.<init>(Suite.java:81)\r\n	at org.junit.runner.Computer$2.<init>(Computer.java:33)\r\n	at org.junit.runner.Computer.getSuite(Computer.java:28)\r\n	at org.junit.runner.Request.classes(Request.java:77)\r\n	at org.junit.runner.JUnitCommandLineParseResult.createRequest(JUnitCommandLineParseResult.java:116)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:77)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-06-04 06:59:49', '2023-06-04 06:59:49'),
(27, 2, 10, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2023-06-04 07:00:33', '2023-06-04 07:00:33'),
(28, 2, 11, 1, 'java_files\\test0106_gmail_com\\Average.java:10: error: illegal start of expression\r\n                   for([isi iterasi]) {\r\n                       ^\r\njava_files\\test0106_gmail_com\\Average.java:10: error: \';\' expected\r\n                   for([isi iterasi]) {\r\n                                   ^\r\n2 errors\r\nTEST FAILED!', 1, '2023-06-04 07:02:57', '2023-06-04 07:02:57'),
(29, 2, 11, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.028\r\n\r\nOK (1 test)', 0, '2023-06-04 07:03:19', '2023-06-04 07:03:19'),
(30, 2, 12, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.E\r\nTime: 0.003\r\nThere was 1 failure:\r\n1) initializationError(org.junit.runner.JUnitCommandLineParseResult)\r\njava.lang.IllegalArgumentException: Could not find class [test0106_gmail_com.JUnitLingkaranTest]\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:100)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseArgs(JUnitCommandLineParseResult.java:50)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parse(JUnitCommandLineParseResult.java:44)\r\n	at org.junit.runner.JUnitCore.runMain(JUnitCore.java:72)\r\n	at org.junit.runner.JUnitCore.main(JUnitCore.java:36)\r\nCaused by: java.lang.ClassNotFoundException: test0106_gmail_com.JUnitLingkaranTest\r\n	at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:641)\r\n	at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:188)\r\n	at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:521)\r\n	at java.base/java.lang.Class.forName0(Native Method)\r\n	at java.base/java.lang.Class.forName(Class.java:488)\r\n	at java.base/java.lang.Class.forName(Class.java:467)\r\n	at org.junit.internal.Classes.getClass(Classes.java:42)\r\n	at org.junit.internal.Classes.getClass(Classes.java:27)\r\n	at org.junit.runner.JUnitCommandLineParseResult.parseParameters(JUnitCommandLineParseResult.java:98)\r\n	... 4 more\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-06-04 07:11:39', '2023-06-04 07:11:39'),
(31, 2, 12, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.033\r\n\r\nOK (1 test)', 0, '2023-06-04 07:14:44', '2023-06-04 07:14:44'),
(32, 2, 13, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.028\r\n\r\nOK (1 test)', 0, '2023-06-04 07:17:58', '2023-06-04 07:17:58'),
(33, 2, 13, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1402551.7307JUnit version 4.13.2\r\n.E\r\nTime: 0.028\r\nThere was 1 failure:\r\n1) isLingkaran(test0106_gmail_com.JUnitBankTest)\r\norg.junit.ComparisonFailure: Output not same expected:<...g setelah 5 tahun: 1[338225.5776]> but was:<...g setelah 5 tahun: 1[402551.7307]>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at test0106_gmail_com.JUnitBankTest.isLingkaran(JUnitBankTest.java:34)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-06-04 07:18:54', '2023-06-04 07:18:54'),
(34, 2, 13, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.035\r\n\r\nOK (1 test)', 0, '2023-06-04 07:19:18', '2023-06-04 07:19:18'),
(35, 2, 13, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.029\r\n\r\nOK (1 test)', 0, '2023-06-04 07:24:36', '2023-06-04 07:24:36'),
(36, 2, 13, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.033\r\n\r\nOK (1 test)', 0, '2023-06-04 07:27:12', '2023-06-04 07:27:12'),
(37, 2, 13, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.046\r\n\r\nOK (1 test)', 0, '2023-06-04 07:28:45', '2023-06-04 07:28:45'),
(38, 2, 13, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.032\r\n\r\nOK (1 test)', 0, '2023-06-04 07:29:25', '2023-06-04 07:29:25'),
(39, 2, 1, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.032\r\n\r\nOK (1 test)', 0, '2023-06-05 07:24:20', '2023-06-05 07:24:20'),
(40, 2, 10, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.035\r\n\r\nOK (1 test)', 0, '2023-06-06 06:11:33', '2023-06-06 06:11:33'),
(41, 3, 1, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2023-06-07 07:34:30', '2023-06-07 07:34:30'),
(42, 3, 2, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.028\r\n\r\nOK (1 test)', 0, '2023-07-06 19:30:30', '2023-07-06 19:30:30'),
(43, 3, 2, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nSelamat anda lulu!JUnit version 4.13.2\r\n.E\r\nTime: 0.029\r\nThere was 1 failure:\r\n1) isAngka(test0706_gmail_com.JUnitAngkaTest)\r\norg.junit.ComparisonFailure: Output not the same expected:<Selamat anda lulu[s]!> but was:<Selamat anda lulu[]!>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at test0706_gmail_com.JUnitAngkaTest.isAngka(JUnitAngkaTest.java:31)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-07-06 19:30:41', '2023-07-06 19:30:41'),
(44, 3, 2, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.023\r\n\r\nOK (1 test)', 0, '2023-07-06 19:31:54', '2023-07-06 19:31:54'),
(45, 4, 1, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.024\r\n\r\nOK (1 test)', 0, '2023-07-06 20:15:52', '2023-07-06 20:15:52'),
(46, 4, 1, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 272JUnit version 4.13.2\r\n.E\r\nTime: 0.019\r\nThere was 1 failure:\r\n1) isTipeData(test0707_gmail_com.JUnitTipeDataTest)\r\norg.junit.ComparisonFailure: Output not the same expected:<...s permukaan balok = [344]> but was:<...s permukaan balok = [272]>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at test0707_gmail_com.JUnitTipeDataTest.isTipeData(JUnitTipeDataTest.java:31)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-07-06 20:19:05', '2023-07-06 20:19:05'),
(47, 4, 1, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 272JUnit version 4.13.2\r\n.E\r\nTime: 0.019\r\nThere was 1 failure:\r\n1) isTipeData(test0707_gmail_com.JUnitTipeDataTest)\r\norg.junit.ComparisonFailure: Output not the same expected:<...s permukaan balok = [344]> but was:<...s permukaan balok = [272]>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at test0707_gmail_com.JUnitTipeDataTest.isTipeData(JUnitTipeDataTest.java:31)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2023-07-06 20:22:24', '2023-07-06 20:22:24'),
(48, 4, 1, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2023-07-06 20:22:56', '2023-07-06 20:22:56'),
(49, 2, 5, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.04\r\n\r\nOK (1 test)', 0, '2023-08-12 21:17:07', '2023-08-12 21:17:07'),
(50, 2, 1, 1, 'java 18 2022-03-22\r\nJava(TM) SE Runtime Environment (build 18+36-2087)\r\nJava HotSpot(TM) 64-Bit Server VM (build 18+36-2087, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.021\r\n\r\nOK (1 test)', 0, '2023-11-25 00:42:42', '2023-11-25 00:42:42'),
(51, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2023-12-26 19:54:49', '2023-12-26 19:54:49'),
(52, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2023-12-26 19:54:51', '2023-12-26 19:54:51'),
(53, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2023-12-26 19:54:59', '2023-12-26 19:54:59'),
(54, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2023-12-26 19:54:59', '2023-12-26 19:54:59'),
(55, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2023-12-26 19:56:24', '2023-12-26 19:56:24'),
(56, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2023-12-26 19:58:39', '2023-12-26 19:58:39'),
(57, 6, 1, 1, 'java_files\\rossaakmalia66_gmail_com\\TipeData.java:11: error: unmappable character (0x93) for encoding UTF-8\r\n        // volume balok ?panjang * lebar * tinggi?\r\n                        ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:11: error: unmappable character (0x94) for encoding UTF-8\r\n        // volume balok ?panjang * lebar * tinggi?\r\n                                                 ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:14: error: unmappable character (0x93) for encoding UTF-8\r\n        // Luas permukaan balok ?2*(panjang * lebar + panjang * tinggi + lebar * tinggi)?\r\n                                ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:14: error: unmappable character (0x94) for encoding UTF-8\r\n        // Luas permukaan balok ?2*(panjang * lebar + panjang * tinggi + lebar * tinggi)?\r\n                                                                                        ^\r\n4 errors\r\nTEST FAILED!', 1, '2023-12-26 20:02:28', '2023-12-26 20:02:28'),
(58, 6, 1, 1, 'java_files\\rossaakmalia66_gmail_com\\TipeData.java:11: error: unmappable character (0x93) for encoding UTF-8\r\n        // volume balok ?panjang * lebar * tinggi?\r\n                        ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:11: error: unmappable character (0x94) for encoding UTF-8\r\n        // volume balok ?panjang * lebar * tinggi?\r\n                                                 ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:14: error: unmappable character (0x93) for encoding UTF-8\r\n        // Luas permukaan balok ?2*(panjang * lebar + panjang * tinggi + lebar * tinggi)?\r\n                                ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:14: error: unmappable character (0x94) for encoding UTF-8\r\n        // Luas permukaan balok ?2*(panjang * lebar + panjang * tinggi + lebar * tinggi)?\r\n                                                                                        ^\r\n4 errors\r\nTEST FAILED!', 1, '2023-12-26 20:02:29', '2023-12-26 20:02:29'),
(59, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2023-12-26 20:02:54', '2023-12-26 20:02:54'),
(60, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2023-12-26 20:03:46', '2023-12-26 20:03:46'),
(61, 6, 1, 1, 'java_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: unmappable character (0x85) for encoding UTF-8\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n             ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:12: error: unmappable character (0x85) for encoding UTF-8\r\n             vBalok = ??;\r\n                      ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:12: error: unmappable character (0x85) for encoding UTF-8\r\n             vBalok = ??;\r\n                       ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:15: error: unmappable character (0x85) for encoding UTF-8\r\n             lBalok = ?..;\r\n                      ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: not a statement\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n               ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: \';\' expected\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                      ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: not a statement\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                        ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: \';\' expected\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                             ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: not a statement\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                               ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: \';\' expected\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                                     ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: not a statement\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                                       ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: \';\' expected\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                                             ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: not a statement\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                                               ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:15: error: illegal \'.\'\r\n             lBalok = ?..;\r\n                        ^\r\n14 errors\r\nTEST FAILED!', 1, '2023-12-26 20:04:05', '2023-12-26 20:04:05'),
(62, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2023-12-26 20:04:55', '2023-12-26 20:04:55'),
(63, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2024-01-22 20:17:40', '2024-01-22 20:17:40'),
(64, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2024-01-22 20:22:47', '2024-01-22 20:22:47'),
(65, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2024-01-22 20:22:50', '2024-01-22 20:22:50'),
(66, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2024-01-22 20:24:13', '2024-01-22 20:24:13'),
(67, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2024-01-22 20:58:02', '2024-01-22 20:58:02'),
(68, 6, 1, 1, 'Error: Could not find or load main class rossaakmalia66_gmail_com.TipeData\nCaused by: java.lang.ClassNotFoundException: rossaakmalia66_gmail_com.TipeData\r\nnull', 1, '2024-01-22 21:02:28', '2024-01-22 21:02:28'),
(69, 6, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 1080, Luas permukaan balok = 654JUnit version 4.13.2\r\n.E\r\nTime: 0.015\r\nThere was 1 failure:\r\n1) isTipeData(rossaakmalia66_gmail_com.JUnitTipeDataTest)\r\norg.junit.ComparisonFailure: Output not the same expected:<Volume balok = [420, Luas permukaan balok = 34]4> but was:<Volume balok = [1080, Luas permukaan balok = 65]4>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at rossaakmalia66_gmail_com.JUnitTipeDataTest.isTipeData(JUnitTipeDataTest.java:31)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2024-01-22 21:56:38', '2024-01-22 21:56:38'),
(70, 6, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-01-22 21:58:57', '2024-01-22 21:58:57'),
(71, 6, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.005\r\n\r\nOK (1 test)', 0, '2024-01-22 22:49:11', '2024-01-22 22:49:11'),
(72, 6, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-01-30 21:57:30', '2024-01-30 21:57:30'),
(73, 6, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-02-02 04:11:42', '2024-02-02 04:11:42'),
(74, 6, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-02-26 20:22:40', '2024-02-26 20:22:40'),
(75, 6, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.033\r\n\r\nOK (1 test)', 0, '2024-02-26 20:25:44', '2024-02-26 20:25:44'),
(76, 6, 1, 1, 'java_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: unmappable character (0x85) for encoding UTF-8\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n             ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: not a statement\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n               ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: \';\' expected\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                      ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: not a statement\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                        ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: \';\' expected\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                             ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: not a statement\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                               ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: \';\' expected\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                                     ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: not a statement\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                                       ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: \';\' expected\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                                             ^\r\njava_files\\rossaakmalia66_gmail_com\\TipeData.java:5: error: not a statement\r\n             ? panjang, lebar, tinggi, vBalok, lBalok;\r\n                                               ^\r\n10 errors\r\nTEST FAILED!', 1, '2024-02-26 23:47:35', '2024-02-26 23:47:35'),
(77, 6, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-02-26 23:47:54', '2024-02-26 23:47:54'),
(78, 6, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-03-02 01:58:57', '2024-03-02 01:58:57'),
(79, 6, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-03-03 05:07:39', '2024-03-03 05:07:39'),
(80, 6, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-03-03 05:07:40', '2024-03-03 05:07:40'),
(81, 6, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-03-03 10:06:30', '2024-03-03 10:06:30'),
(82, 6, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-03-03 10:10:54', '2024-03-03 10:10:54'),
(83, 6, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-03-03 10:12:37', '2024-03-03 10:12:37'),
(84, 6, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-03-03 10:31:38', '2024-03-03 10:31:38'),
(85, 6, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.023\r\n\r\nOK (1 test)', 0, '2024-03-05 20:52:20', '2024-03-05 20:52:20'),
(86, 7, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-03-08 07:49:22', '2024-03-08 07:49:22'),
(87, 7, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-03-08 08:18:20', '2024-03-08 08:18:20'),
(88, 7, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-03-08 08:29:01', '2024-03-08 08:29:01'),
(89, 7, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-03-08 08:32:41', '2024-03-08 08:32:41'),
(90, 7, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-03-08 08:36:27', '2024-03-08 08:36:27'),
(91, 7, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-03-08 08:39:04', '2024-03-08 08:39:04');
INSERT INTO `code_history_logs` (`id`, `user_id`, `question_id`, `total_count`, `message`, `is_error`, `created_at`, `updated_at`) VALUES
(92, 7, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.027\r\n\r\nOK (1 test)', 0, '2024-03-08 09:12:06', '2024-03-08 09:12:06'),
(93, 9, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.034\r\n\r\nOK (1 test)', 0, '2024-03-11 05:00:23', '2024-03-11 05:00:23'),
(94, 9, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-03-11 05:03:36', '2024-03-11 05:03:36'),
(95, 9, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-03-11 05:07:03', '2024-03-11 05:07:03'),
(96, 9, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-03-11 05:09:42', '2024-03-11 05:09:42'),
(97, 9, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-03-11 05:12:49', '2024-03-11 05:12:49'),
(98, 7, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.026\r\n\r\nOK (1 test)', 0, '2024-03-11 05:18:25', '2024-03-11 05:18:25'),
(99, 10, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.033\r\n\r\nOK (1 test)', 0, '2024-03-11 08:28:57', '2024-03-11 08:28:57'),
(100, 10, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-03-11 08:36:22', '2024-03-11 08:36:22'),
(101, 10, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-03-11 08:40:05', '2024-03-11 08:40:05'),
(102, 10, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-03-11 08:43:37', '2024-03-11 08:43:37'),
(103, 10, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-03-11 08:46:27', '2024-03-11 08:46:27'),
(104, 11, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-03-11 08:55:54', '2024-03-11 08:55:54'),
(105, 11, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-03-11 08:57:14', '2024-03-11 08:57:14'),
(106, 11, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-03-11 08:58:41', '2024-03-11 08:58:41'),
(107, 11, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-03-11 09:00:01', '2024-03-11 09:00:01'),
(108, 11, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-03-11 09:01:34', '2024-03-11 09:01:34'),
(109, 12, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-03-11 09:10:15', '2024-03-11 09:10:15'),
(110, 12, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.026\r\n\r\nOK (1 test)', 0, '2024-03-11 09:11:41', '2024-03-11 09:11:41'),
(111, 12, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-03-11 09:13:05', '2024-03-11 09:13:05'),
(112, 12, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-03-11 09:16:11', '2024-03-11 09:16:11'),
(113, 12, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-03-11 09:17:21', '2024-03-11 09:17:21'),
(114, 13, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-03-11 09:21:12', '2024-03-11 09:21:12'),
(115, 13, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-03-11 09:23:09', '2024-03-11 09:23:09'),
(116, 13, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-03-11 09:24:56', '2024-03-11 09:24:56'),
(117, 13, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.024\r\n\r\nOK (1 test)', 0, '2024-03-11 09:28:02', '2024-03-11 09:28:02'),
(118, 13, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-03-11 09:30:21', '2024-03-11 09:30:21'),
(119, 14, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-03-11 09:40:20', '2024-03-11 09:40:20'),
(120, 14, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-03-11 09:42:18', '2024-03-11 09:42:18'),
(121, 14, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-03-11 09:43:38', '2024-03-11 09:43:38'),
(122, 14, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-03-11 09:45:15', '2024-03-11 09:45:15'),
(123, 14, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-03-11 09:47:08', '2024-03-11 09:47:08'),
(124, 15, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.024\r\n\r\nOK (1 test)', 0, '2024-03-11 09:55:21', '2024-03-11 09:55:21'),
(125, 15, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-03-11 09:56:47', '2024-03-11 09:56:47'),
(126, 15, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-03-11 09:59:33', '2024-03-11 09:59:33'),
(127, 15, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-03-11 10:00:17', '2024-03-11 10:00:17'),
(128, 15, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-03-11 10:01:56', '2024-03-11 10:01:56'),
(129, 16, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.022\r\n\r\nOK (1 test)', 0, '2024-03-11 10:14:24', '2024-03-11 10:14:24'),
(130, 16, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-03-11 10:15:50', '2024-03-11 10:15:50'),
(131, 16, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-03-11 10:17:25', '2024-03-11 10:17:25'),
(132, 16, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-03-11 10:18:44', '2024-03-11 10:18:44'),
(133, 16, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-03-11 10:20:04', '2024-03-11 10:20:04'),
(134, 17, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-03-11 10:23:34', '2024-03-11 10:23:34'),
(135, 17, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-03-11 10:25:12', '2024-03-11 10:25:12'),
(136, 17, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-03-11 10:26:25', '2024-03-11 10:26:25'),
(137, 17, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-03-11 10:27:37', '2024-03-11 10:27:37'),
(138, 17, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-03-11 10:30:03', '2024-03-11 10:30:03'),
(139, 10, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-03-24 00:13:52', '2024-03-24 00:13:52'),
(140, 10, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-03-24 00:16:46', '2024-03-24 00:16:46'),
(141, 10, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.026\r\n\r\nOK (1 test)', 0, '2024-03-24 00:19:42', '2024-03-24 00:19:42'),
(142, 10, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 21 JUnit version 4.13.2\r\n.E\r\nTime: 0.027\r\nThere was 1 failure:\r\n1) isFibonnaci(lower_gmail_com.JUnitFibonacciTest)\r\norg.junit.ComparisonFailure: Output not the same expected:<...: \n0 1 1 2 3 5 8 13 []> but was:<...: \n0 1 1 2 3 5 8 13 [21 ]>\r\n	at org.junit.Assert.assertEquals(Assert.java:117)\r\n	at lower_gmail_com.JUnitFibonacciTest.isFibonnaci(JUnitFibonacciTest.java:30)\r\n\r\nFAILURES!!!\r\nTests run: 1,  Failures: 1', 1, '2024-03-24 00:21:56', '2024-03-24 00:21:56'),
(143, 10, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.023\r\n\r\nOK (1 test)', 0, '2024-03-24 00:22:11', '2024-03-24 00:22:11'),
(144, 10, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-03-24 00:23:34', '2024-03-24 00:23:34'),
(145, 10, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.023\r\n\r\nOK (1 test)', 0, '2024-03-24 00:23:39', '2024-03-24 00:23:39'),
(146, 10, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-03-24 00:23:39', '2024-03-24 00:23:39'),
(147, 10, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.023\r\n\r\nOK (1 test)', 0, '2024-03-24 00:26:31', '2024-03-24 00:26:31'),
(148, 10, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-03-24 00:30:51', '2024-03-24 00:30:51'),
(149, 10, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.025\r\n\r\nOK (1 test)', 0, '2024-03-24 00:33:59', '2024-03-24 00:33:59'),
(150, 10, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.027\r\n\r\nOK (1 test)', 0, '2024-03-24 00:38:13', '2024-03-24 00:38:13'),
(151, 19, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.031\r\n\r\nOK (1 test)', 0, '2024-03-24 00:53:27', '2024-03-24 00:53:27'),
(152, 19, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-03-24 00:55:03', '2024-03-24 00:55:03'),
(153, 19, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-03-24 00:56:27', '2024-03-24 00:56:27'),
(154, 19, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.028\r\n\r\nOK (1 test)', 0, '2024-03-24 00:57:49', '2024-03-24 00:57:49'),
(155, 19, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.033\r\n\r\nOK (1 test)', 0, '2024-03-24 00:59:09', '2024-03-24 00:59:09'),
(156, 19, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-03-24 01:01:20', '2024-03-24 01:01:20'),
(157, 19, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-03-24 01:03:06', '2024-03-24 01:03:06'),
(158, 19, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.03\r\n\r\nOK (1 test)', 0, '2024-03-24 01:04:29', '2024-03-24 01:04:29'),
(159, 19, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-03-24 01:05:49', '2024-03-24 01:05:49'),
(160, 19, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-03-24 01:07:13', '2024-03-24 01:07:13'),
(161, 19, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-03-24 01:09:32', '2024-03-24 01:09:32'),
(162, 19, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.039\r\n\r\nOK (1 test)', 0, '2024-03-24 01:11:01', '2024-03-24 01:11:01'),
(163, 19, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.044\r\n\r\nOK (1 test)', 0, '2024-03-24 01:13:01', '2024-03-24 01:13:01'),
(164, 12, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.03\r\n\r\nOK (1 test)', 0, '2024-03-24 01:16:08', '2024-03-24 01:16:08'),
(165, 12, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-03-24 01:18:08', '2024-03-24 01:18:08'),
(166, 12, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-03-24 01:20:24', '2024-03-24 01:20:24'),
(167, 12, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-03-24 01:21:08', '2024-03-24 01:21:08'),
(168, 12, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.035\r\n\r\nOK (1 test)', 0, '2024-03-24 01:22:00', '2024-03-24 01:22:00'),
(169, 12, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-03-24 01:23:28', '2024-03-24 01:23:28'),
(170, 12, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-03-24 01:24:49', '2024-03-24 01:24:49'),
(171, 12, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-03-24 01:26:18', '2024-03-24 01:26:18'),
(172, 12, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.03\r\n\r\nOK (1 test)', 0, '2024-03-24 01:27:46', '2024-03-24 01:27:46'),
(173, 12, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.025\r\n\r\nOK (1 test)', 0, '2024-03-24 01:29:18', '2024-03-24 01:29:18'),
(174, 13, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-03-24 01:32:01', '2024-03-24 01:32:01'),
(175, 13, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-03-24 01:33:35', '2024-03-24 01:33:35'),
(176, 13, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.023\r\n\r\nOK (1 test)', 0, '2024-03-24 01:34:54', '2024-03-24 01:34:54'),
(177, 13, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-03-24 01:36:11', '2024-03-24 01:36:11'),
(178, 13, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-03-24 01:37:54', '2024-03-24 01:37:54'),
(179, 13, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-03-24 01:39:10', '2024-03-24 01:39:10'),
(180, 13, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-03-24 01:40:12', '2024-03-24 01:40:12'),
(181, 13, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-03-24 01:41:13', '2024-03-24 01:41:13'),
(182, 21, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-03-24 02:56:00', '2024-03-24 02:56:00'),
(183, 21, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.031\r\n\r\nOK (1 test)', 0, '2024-03-24 02:56:03', '2024-03-24 02:56:03'),
(184, 21, 2, 1, 'java_files\\kuncijawaban4_gmail_com\\Angka.java:8: error: unmappable character (0x85) for encoding UTF-8\r\n                   System.out.print(\"?\");\r\n                                     ^\r\n1 error\r\nTEST FAILED!', 1, '2024-03-26 08:55:14', '2024-03-26 08:55:14'),
(185, 21, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-03-28 08:29:01', '2024-03-28 08:29:01'),
(186, 21, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-03-28 08:32:23', '2024-03-28 08:32:23'),
(187, 21, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-03-28 08:33:59', '2024-03-28 08:33:59'),
(188, 21, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-03-28 08:35:56', '2024-03-28 08:35:56'),
(189, 21, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-03-28 08:37:15', '2024-03-28 08:37:15'),
(190, 21, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-03-28 08:38:37', '2024-03-28 08:38:37'),
(191, 21, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-03-28 08:39:48', '2024-03-28 08:39:48'),
(192, 21, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-03-28 08:41:04', '2024-03-28 08:41:04'),
(193, 21, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-03-28 08:42:14', '2024-03-28 08:42:14'),
(194, 21, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-03-28 08:43:37', '2024-03-28 08:43:37'),
(195, 21, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-03-28 08:45:04', '2024-03-28 08:45:04'),
(196, 21, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-03-28 08:46:15', '2024-03-28 08:46:15'),
(197, 21, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.029\r\n\r\nOK (1 test)', 0, '2024-03-28 08:47:20', '2024-03-28 08:47:20'),
(198, 22, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-03-28 08:59:28', '2024-03-28 08:59:28'),
(199, 22, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-03-28 09:03:54', '2024-03-28 09:03:54'),
(200, 22, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-03-28 09:04:49', '2024-03-28 09:04:49'),
(201, 22, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-03-28 09:06:05', '2024-03-28 09:06:05'),
(202, 22, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-03-28 09:07:11', '2024-03-28 09:07:11'),
(203, 22, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-03-28 09:12:22', '2024-03-28 09:12:22'),
(204, 22, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0\r\n\r\nOK (1 test)', 0, '2024-03-28 09:13:32', '2024-03-28 09:13:32'),
(205, 22, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-03-28 09:14:39', '2024-03-28 09:14:39'),
(206, 22, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.002\r\n\r\nOK (1 test)', 0, '2024-03-28 09:15:50', '2024-03-28 09:15:50'),
(207, 22, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-03-28 09:17:06', '2024-03-28 09:17:06'),
(208, 22, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-03-28 09:18:13', '2024-03-28 09:18:13'),
(209, 22, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-03-28 09:19:31', '2024-03-28 09:19:31'),
(210, 22, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-03-28 09:20:39', '2024-03-28 09:20:39'),
(211, 23, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.028\r\n\r\nOK (1 test)', 0, '2024-04-01 04:01:12', '2024-04-01 04:01:12'),
(212, 23, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.024\r\n\r\nOK (1 test)', 0, '2024-04-01 04:02:39', '2024-04-01 04:02:39'),
(213, 23, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-04-01 04:03:51', '2024-04-01 04:03:51'),
(214, 23, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.022\r\n\r\nOK (1 test)', 0, '2024-04-01 04:05:56', '2024-04-01 04:05:56'),
(215, 23, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.027\r\n\r\nOK (1 test)', 0, '2024-04-01 04:08:30', '2024-04-01 04:08:30'),
(216, 23, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-04-01 04:09:59', '2024-04-01 04:09:59'),
(217, 23, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-04-01 04:11:24', '2024-04-01 04:11:24'),
(218, 23, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.032\r\n\r\nOK (1 test)', 0, '2024-04-01 04:12:53', '2024-04-01 04:12:53'),
(219, 23, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-04-01 04:16:13', '2024-04-01 04:16:13'),
(220, 23, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-04-01 04:17:44', '2024-04-01 04:17:44'),
(221, 23, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-04-01 04:20:00', '2024-04-01 04:20:00'),
(222, 23, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.036\r\n\r\nOK (1 test)', 0, '2024-04-01 04:21:26', '2024-04-01 04:21:26'),
(223, 23, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.025\r\n\r\nOK (1 test)', 0, '2024-04-01 04:24:56', '2024-04-01 04:24:56'),
(224, 24, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.034\r\n\r\nOK (1 test)', 0, '2024-04-01 04:38:46', '2024-04-01 04:38:46'),
(225, 24, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-04-01 04:40:21', '2024-04-01 04:40:21'),
(226, 24, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-04-01 04:42:01', '2024-04-01 04:42:01'),
(227, 24, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-01 04:43:28', '2024-04-01 04:43:28'),
(228, 24, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.028\r\n\r\nOK (1 test)', 0, '2024-04-01 04:44:56', '2024-04-01 04:44:56'),
(229, 24, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-01 04:46:13', '2024-04-01 04:46:13'),
(230, 24, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-04-01 04:47:31', '2024-04-01 04:47:31'),
(231, 24, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.025\r\n\r\nOK (1 test)', 0, '2024-04-01 04:50:27', '2024-04-01 04:50:27'),
(232, 24, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-04-01 04:52:05', '2024-04-01 04:52:05'),
(233, 24, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-04-01 04:53:45', '2024-04-01 04:53:45'),
(234, 24, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.023\r\n\r\nOK (1 test)', 0, '2024-04-01 04:56:13', '2024-04-01 04:56:13'),
(235, 24, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.021\r\n\r\nOK (1 test)', 0, '2024-04-01 04:59:45', '2024-04-01 04:59:45'),
(236, 24, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.032\r\n\r\nOK (1 test)', 0, '2024-04-01 05:01:02', '2024-04-01 05:01:02'),
(237, 6, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-04-07 10:36:15', '2024-04-07 10:36:15'),
(238, 25, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-16 17:15:11', '2024-04-16 17:15:11'),
(239, 25, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-04-16 17:17:15', '2024-04-16 17:17:15'),
(240, 25, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-16 17:20:13', '2024-04-16 17:20:13'),
(241, 25, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.031\r\n\r\nOK (1 test)', 0, '2024-04-16 17:24:07', '2024-04-16 17:24:07'),
(242, 25, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0\r\n\r\nOK (1 test)', 0, '2024-04-16 17:26:22', '2024-04-16 17:26:22'),
(243, 25, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-16 17:27:59', '2024-04-16 17:27:59'),
(244, 25, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.03\r\n\r\nOK (1 test)', 0, '2024-04-16 17:30:07', '2024-04-16 17:30:07'),
(245, 25, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-16 17:31:57', '2024-04-16 17:31:57'),
(246, 25, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-04-16 17:46:33', '2024-04-16 17:46:33'),
(247, 25, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-04-16 17:49:47', '2024-04-16 17:49:47'),
(248, 25, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-04-23 18:54:09', '2024-04-23 18:54:09'),
(249, 26, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-04-26 13:26:39', '2024-04-26 13:26:39');
INSERT INTO `code_history_logs` (`id`, `user_id`, `question_id`, `total_count`, `message`, `is_error`, `created_at`, `updated_at`) VALUES
(250, 26, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-04-26 13:49:00', '2024-04-26 13:49:00'),
(251, 26, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-04-26 20:41:12', '2024-04-26 20:41:12'),
(252, 26, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.023\r\n\r\nOK (1 test)', 0, '2024-04-26 20:55:51', '2024-04-26 20:55:51'),
(253, 26, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-04-26 21:14:54', '2024-04-26 21:14:54'),
(254, 26, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-04-26 21:31:09', '2024-04-26 21:31:09'),
(255, 26, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-04-26 21:49:23', '2024-04-26 21:49:23'),
(256, 26, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-04-26 23:18:16', '2024-04-26 23:18:16'),
(257, 26, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-04-26 23:44:21', '2024-04-26 23:44:21'),
(258, 26, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.005\r\n\r\nOK (1 test)', 0, '2024-04-27 00:05:59', '2024-04-27 00:05:59'),
(259, 26, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-04-27 00:33:49', '2024-04-27 00:33:49'),
(260, 26, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-04-27 00:50:49', '2024-04-27 00:50:49'),
(261, 26, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.025\r\n\r\nOK (1 test)', 0, '2024-04-27 01:09:59', '2024-04-27 01:09:59'),
(262, 27, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.025\r\n\r\nOK (1 test)', 0, '2024-04-27 05:49:17', '2024-04-27 05:49:17'),
(263, 27, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-04-27 05:58:30', '2024-04-27 05:58:30'),
(264, 27, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-04-27 06:07:40', '2024-04-27 06:07:40'),
(265, 27, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-04-27 06:16:34', '2024-04-27 06:16:34'),
(266, 27, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.024\r\n\r\nOK (1 test)', 0, '2024-04-27 06:27:10', '2024-04-27 06:27:10'),
(267, 27, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-04-27 06:35:36', '2024-04-27 06:35:36'),
(268, 27, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.028\r\n\r\nOK (1 test)', 0, '2024-04-27 06:46:26', '2024-04-27 06:46:26'),
(269, 27, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.046\r\n\r\nOK (1 test)', 0, '2024-04-27 06:58:11', '2024-04-27 06:58:11'),
(270, 27, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-04-27 07:07:43', '2024-04-27 07:07:43'),
(271, 27, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-04-27 07:18:22', '2024-04-27 07:18:22'),
(272, 27, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-04-27 07:28:47', '2024-04-27 07:28:47'),
(273, 27, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.023\r\n\r\nOK (1 test)', 0, '2024-04-27 07:38:44', '2024-04-27 07:38:44'),
(274, 27, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.032\r\n\r\nOK (1 test)', 0, '2024-04-27 07:47:15', '2024-04-27 07:47:15'),
(275, 28, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-04-27 13:39:47', '2024-04-27 13:39:47'),
(276, 28, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-04-27 13:48:20', '2024-04-27 13:48:20'),
(277, 28, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.006\r\n\r\nOK (1 test)', 0, '2024-04-27 13:56:41', '2024-04-27 13:56:41'),
(278, 28, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-04-27 14:04:40', '2024-04-27 14:04:40'),
(279, 28, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.022\r\n\r\nOK (1 test)', 0, '2024-04-27 14:12:51', '2024-04-27 14:12:51'),
(280, 28, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-04-27 14:21:13', '2024-04-27 14:21:13'),
(281, 28, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.002\r\n\r\nOK (1 test)', 0, '2024-04-27 14:29:18', '2024-04-27 14:29:18'),
(282, 28, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-04-27 14:36:48', '2024-04-27 14:36:48'),
(283, 28, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-04-27 14:45:59', '2024-04-27 14:45:59'),
(284, 28, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-04-27 14:53:51', '2024-04-27 14:53:51'),
(285, 28, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.03\r\n\r\nOK (1 test)', 0, '2024-04-27 15:01:11', '2024-04-27 15:01:11'),
(286, 28, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-04-27 15:08:33', '2024-04-27 15:08:33'),
(287, 28, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-04-27 15:16:13', '2024-04-27 15:16:13'),
(288, 29, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-27 19:24:12', '2024-04-27 19:24:12'),
(289, 29, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-27 19:35:20', '2024-04-27 19:35:20'),
(290, 29, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.057\r\n\r\nOK (1 test)', 0, '2024-04-27 19:45:03', '2024-04-27 19:45:03'),
(291, 29, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.031\r\n\r\nOK (1 test)', 0, '2024-04-27 19:52:50', '2024-04-27 19:52:50'),
(292, 29, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-04-27 20:01:04', '2024-04-27 20:01:04'),
(293, 29, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.027\r\n\r\nOK (1 test)', 0, '2024-04-27 20:09:40', '2024-04-27 20:09:40'),
(294, 29, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-27 20:18:24', '2024-04-27 20:18:24'),
(295, 29, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.03\r\n\r\nOK (1 test)', 0, '2024-04-27 20:27:05', '2024-04-27 20:27:05'),
(296, 29, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-04-27 20:36:21', '2024-04-27 20:36:21'),
(297, 29, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.024\r\n\r\nOK (1 test)', 0, '2024-04-27 20:44:31', '2024-04-27 20:44:31'),
(298, 29, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-27 20:54:14', '2024-04-27 20:54:14'),
(299, 29, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.022\r\n\r\nOK (1 test)', 0, '2024-04-27 20:54:14', '2024-04-27 20:54:14'),
(300, 29, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-27 21:03:29', '2024-04-27 21:03:29'),
(301, 29, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-04-27 21:07:15', '2024-04-27 21:07:15'),
(302, 29, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.031\r\n\r\nOK (1 test)', 0, '2024-04-27 21:16:08', '2024-04-27 21:16:08'),
(303, 30, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.021\r\n\r\nOK (1 test)', 0, '2024-04-28 05:53:39', '2024-04-28 05:53:39'),
(304, 30, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-04-28 06:07:35', '2024-04-28 06:07:35'),
(305, 30, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-04-28 06:15:20', '2024-04-28 06:15:20'),
(306, 30, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-04-28 06:23:22', '2024-04-28 06:23:22'),
(307, 30, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-04-28 06:31:42', '2024-04-28 06:31:42'),
(308, 30, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-04-28 06:41:48', '2024-04-28 06:41:48'),
(309, 30, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-04-28 06:49:53', '2024-04-28 06:49:53'),
(310, 30, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-28 07:02:16', '2024-04-28 07:02:16'),
(311, 30, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-04-28 07:10:46', '2024-04-28 07:10:46'),
(312, 30, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-04-28 07:19:13', '2024-04-28 07:19:13'),
(313, 30, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-04-28 07:33:15', '2024-04-28 07:33:15'),
(314, 30, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-04-28 07:41:15', '2024-04-28 07:41:15'),
(315, 30, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-04-28 07:51:12', '2024-04-28 07:51:12'),
(316, 31, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.03\r\n\r\nOK (1 test)', 0, '2024-04-28 13:55:52', '2024-04-28 13:55:52'),
(317, 31, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-04-28 13:58:47', '2024-04-28 13:58:47'),
(318, 31, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-04-28 13:59:48', '2024-04-28 13:59:48'),
(319, 31, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-04-28 14:02:30', '2024-04-28 14:02:30'),
(320, 31, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.053\r\n\r\nOK (1 test)', 0, '2024-04-28 14:06:00', '2024-04-28 14:06:00'),
(321, 31, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.025\r\n\r\nOK (1 test)', 0, '2024-04-28 14:09:52', '2024-04-28 14:09:52'),
(322, 31, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-04-28 14:13:45', '2024-04-28 14:13:45'),
(323, 31, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.025\r\n\r\nOK (1 test)', 0, '2024-04-28 14:16:55', '2024-04-28 14:16:55'),
(324, 31, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-04-28 14:19:39', '2024-04-28 14:19:39'),
(325, 31, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.032\r\n\r\nOK (1 test)', 0, '2024-04-28 14:23:07', '2024-04-28 14:23:07'),
(326, 31, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-04-28 14:26:54', '2024-04-28 14:26:54'),
(327, 31, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-04-28 14:30:05', '2024-04-28 14:30:05'),
(328, 31, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-04-28 14:32:36', '2024-04-28 14:32:36'),
(329, 31, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-04-28 14:35:14', '2024-04-28 14:35:14'),
(330, 31, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.037\r\n\r\nOK (1 test)', 0, '2024-04-28 14:37:49', '2024-04-28 14:37:49'),
(331, 26, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-04-28 14:46:07', '2024-04-28 14:46:07'),
(332, 26, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-04-28 14:47:10', '2024-04-28 14:47:10'),
(333, 27, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-28 14:48:38', '2024-04-28 14:48:38'),
(334, 27, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-04-28 14:49:34', '2024-04-28 14:49:34'),
(335, 27, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-04-28 14:51:21', '2024-04-28 14:51:21'),
(336, 27, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-04-28 14:52:14', '2024-04-28 14:52:14'),
(337, 28, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-04-28 14:53:36', '2024-04-28 14:53:36'),
(338, 28, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-04-28 14:54:26', '2024-04-28 14:54:26'),
(339, 29, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.024\r\n\r\nOK (1 test)', 0, '2024-04-28 14:55:46', '2024-04-28 14:55:46'),
(340, 29, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-04-28 14:56:35', '2024-04-28 14:56:35'),
(341, 29, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-04-28 14:57:41', '2024-04-28 14:57:41'),
(342, 29, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.021\r\n\r\nOK (1 test)', 0, '2024-04-28 14:58:30', '2024-04-28 14:58:30'),
(343, 29, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-04-28 14:59:41', '2024-04-28 14:59:41'),
(344, 29, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.023\r\n\r\nOK (1 test)', 0, '2024-04-28 15:01:05', '2024-04-28 15:01:05'),
(345, 30, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-04-28 15:02:50', '2024-04-28 15:02:50'),
(346, 30, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-04-28 15:03:52', '2024-04-28 15:03:52'),
(347, 32, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.022\r\n\r\nOK (1 test)', 0, '2024-05-01 19:20:46', '2024-05-01 19:20:46'),
(348, 32, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-05-01 19:39:12', '2024-05-01 19:39:12'),
(349, 32, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-05-01 19:43:06', '2024-05-01 19:43:06'),
(350, 32, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-05-01 19:46:31', '2024-05-01 19:46:31'),
(351, 32, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.005\r\n\r\nOK (1 test)', 0, '2024-05-01 19:47:41', '2024-05-01 19:47:41'),
(352, 32, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-05-01 19:55:48', '2024-05-01 19:55:48'),
(353, 32, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-05-01 19:58:10', '2024-05-01 19:58:10'),
(354, 32, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-05-01 20:01:20', '2024-05-01 20:01:20'),
(355, 32, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-05-01 20:04:21', '2024-05-01 20:04:21'),
(356, 32, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-05-01 20:07:21', '2024-05-01 20:07:21'),
(357, 32, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-05-01 20:18:39', '2024-05-01 20:18:39'),
(358, 32, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-05-01 20:20:43', '2024-05-01 20:20:43'),
(359, 32, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-05-01 20:30:31', '2024-05-01 20:30:31'),
(360, 32, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-05-01 20:38:23', '2024-05-01 20:38:23'),
(361, 33, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-05-01 20:41:03', '2024-05-01 20:41:03'),
(362, 33, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-05-01 20:48:46', '2024-05-01 20:48:46'),
(363, 33, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-05-01 20:53:47', '2024-05-01 20:53:47'),
(364, 10, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0\r\n\r\nOK (1 test)', 0, '2024-05-01 20:57:08', '2024-05-01 20:57:08'),
(365, 10, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-05-01 21:05:06', '2024-05-01 21:05:06'),
(366, 10, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-05-01 21:06:20', '2024-05-01 21:06:20'),
(367, 10, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-05-01 21:10:17', '2024-05-01 21:10:17'),
(368, 10, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-05-01 21:17:35', '2024-05-01 21:17:35'),
(369, 34, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.032\r\n\r\nOK (1 test)', 0, '2024-05-01 21:30:34', '2024-05-01 21:30:34'),
(370, 34, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.031\r\n\r\nOK (1 test)', 0, '2024-05-01 21:36:33', '2024-05-01 21:36:33'),
(371, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-05-01 21:42:08', '2024-05-01 21:42:08'),
(372, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-05-01 21:45:02', '2024-05-01 21:45:02'),
(373, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-05-01 21:48:31', '2024-05-01 21:48:31'),
(374, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-05-01 21:57:37', '2024-05-01 21:57:37'),
(375, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-05-01 21:58:40', '2024-05-01 21:58:40'),
(376, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-05-01 22:03:34', '2024-05-01 22:03:34'),
(377, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.005\r\n\r\nOK (1 test)', 0, '2024-05-01 22:05:53', '2024-05-01 22:05:53'),
(378, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-05-01 22:07:06', '2024-05-01 22:07:06'),
(379, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.026\r\n\r\nOK (1 test)', 0, '2024-05-01 22:08:25', '2024-05-01 22:08:25'),
(380, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.025\r\n\r\nOK (1 test)', 0, '2024-05-01 22:17:04', '2024-05-01 22:17:04'),
(381, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-05-01 22:19:32', '2024-05-01 22:19:32'),
(382, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-05-01 22:22:35', '2024-05-01 22:22:35'),
(383, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-05-01 22:33:49', '2024-05-01 22:33:49'),
(384, 34, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-05-01 22:35:29', '2024-05-01 22:35:29'),
(385, 34, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-05-01 22:38:31', '2024-05-01 22:38:31'),
(386, 34, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-05-01 23:28:05', '2024-05-01 23:28:05'),
(387, 32, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.03\r\n\r\nOK (1 test)', 0, '2024-05-02 14:58:34', '2024-05-02 14:58:34'),
(388, 32, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-05-02 15:00:01', '2024-05-02 15:00:01'),
(389, 32, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-05-02 15:02:05', '2024-05-02 15:02:05'),
(390, 32, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-05-02 15:10:51', '2024-05-02 15:10:51'),
(391, 32, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.024\r\n\r\nOK (1 test)', 0, '2024-05-02 15:19:41', '2024-05-02 15:19:41'),
(392, 32, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-05-02 15:29:04', '2024-05-02 15:29:04'),
(393, 32, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-05-02 15:38:12', '2024-05-02 15:38:12'),
(394, 32, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.037\r\n\r\nOK (1 test)', 0, '2024-05-02 15:46:30', '2024-05-02 15:46:30'),
(395, 32, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-05-02 15:55:38', '2024-05-02 15:55:38'),
(396, 32, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-05-02 16:03:44', '2024-05-02 16:03:44'),
(397, 32, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.033\r\n\r\nOK (1 test)', 0, '2024-05-02 16:12:21', '2024-05-02 16:12:21'),
(398, 32, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.028\r\n\r\nOK (1 test)', 0, '2024-05-02 16:20:55', '2024-05-02 16:20:55'),
(399, 32, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.025\r\n\r\nOK (1 test)', 0, '2024-05-02 16:29:22', '2024-05-02 16:29:22'),
(400, 35, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-05-02 17:20:08', '2024-05-02 17:20:08'),
(401, 35, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-05-02 17:29:20', '2024-05-02 17:29:20'),
(402, 35, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-05-02 17:37:29', '2024-05-02 17:37:29'),
(403, 35, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-05-02 17:46:03', '2024-05-02 17:46:03'),
(404, 35, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-05-02 17:48:26', '2024-05-02 17:48:26'),
(405, 35, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-05-02 17:55:50', '2024-05-02 17:55:50'),
(406, 35, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-05-02 18:03:21', '2024-05-02 18:03:21'),
(407, 35, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-05-02 18:19:27', '2024-05-02 18:19:27');
INSERT INTO `code_history_logs` (`id`, `user_id`, `question_id`, `total_count`, `message`, `is_error`, `created_at`, `updated_at`) VALUES
(408, 35, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-05-02 18:42:47', '2024-05-02 18:42:47'),
(409, 35, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.005\r\n\r\nOK (1 test)', 0, '2024-05-02 18:54:08', '2024-05-02 18:54:08'),
(410, 35, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0\r\n\r\nOK (1 test)', 0, '2024-05-02 19:15:42', '2024-05-02 19:15:42'),
(411, 35, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-05-02 19:26:26', '2024-05-02 19:26:26'),
(412, 35, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-05-02 19:40:34', '2024-05-02 19:40:34'),
(413, 35, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.03\r\n\r\nOK (1 test)', 0, '2024-05-02 19:49:44', '2024-05-02 19:49:44'),
(414, 36, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-05-03 03:11:13', '2024-05-03 03:11:13'),
(415, 36, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-05-03 03:29:00', '2024-05-03 03:29:00'),
(416, 36, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.018\r\n\r\nOK (1 test)', 0, '2024-05-03 03:38:04', '2024-05-03 03:38:04'),
(417, 36, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.022\r\n\r\nOK (1 test)', 0, '2024-05-03 03:53:58', '2024-05-03 03:53:58'),
(418, 36, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-05-03 04:04:07', '2024-05-03 04:04:07'),
(419, 36, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-05-03 04:11:44', '2024-05-03 04:11:44'),
(420, 36, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-05-03 04:30:50', '2024-05-03 04:30:50'),
(421, 36, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.04\r\n\r\nOK (1 test)', 0, '2024-05-03 04:50:26', '2024-05-03 04:50:26'),
(422, 36, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-05-03 05:01:18', '2024-05-03 05:01:18'),
(423, 36, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-05-03 05:23:49', '2024-05-03 05:23:49'),
(424, 36, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.01\r\n\r\nOK (1 test)', 0, '2024-05-03 05:43:20', '2024-05-03 05:43:20'),
(425, 36, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-05-03 05:54:27', '2024-05-03 05:54:27'),
(426, 36, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-05-03 06:04:30', '2024-05-03 06:04:30'),
(427, 37, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-06-03 05:07:29', '2024-06-03 05:07:29'),
(428, 37, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.039\r\n\r\nOK (1 test)', 0, '2024-06-03 05:20:58', '2024-06-03 05:20:58'),
(429, 37, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.026\r\n\r\nOK (1 test)', 0, '2024-06-03 05:26:23', '2024-06-03 05:26:23'),
(430, 37, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-03 05:39:34', '2024-06-03 05:39:34'),
(431, 37, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-06-03 05:49:45', '2024-06-03 05:49:45'),
(432, 37, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-06-03 06:05:46', '2024-06-03 06:05:46'),
(433, 37, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.008\r\n\r\nOK (1 test)', 0, '2024-06-03 06:23:45', '2024-06-03 06:23:45'),
(434, 37, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-06-03 06:39:03', '2024-06-03 06:39:03'),
(435, 37, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-06-03 07:00:48', '2024-06-03 07:00:48'),
(436, 37, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-06-03 07:08:53', '2024-06-03 07:08:53'),
(437, 37, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-06-03 07:24:32', '2024-06-03 07:24:32'),
(438, 37, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-06-03 07:32:32', '2024-06-03 07:32:32'),
(439, 37, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-06-03 07:40:12', '2024-06-03 07:40:12'),
(440, 37, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-03 08:04:24', '2024-06-03 08:04:24'),
(441, 39, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.024\r\n\r\nOK (1 test)', 0, '2024-06-10 01:50:47', '2024-06-10 01:50:47'),
(442, 39, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-10 01:58:04', '2024-06-10 01:58:04'),
(443, 39, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-06-10 02:01:59', '2024-06-10 02:01:59'),
(444, 39, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-10 02:07:56', '2024-06-10 02:07:56'),
(445, 39, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-06-10 02:21:00', '2024-06-10 02:21:00'),
(446, 39, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0\r\n\r\nOK (1 test)', 0, '2024-06-10 02:27:38', '2024-06-10 02:27:38'),
(447, 39, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-06-10 02:34:31', '2024-06-10 02:34:31'),
(448, 39, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.022\r\n\r\nOK (1 test)', 0, '2024-06-10 02:38:19', '2024-06-10 02:38:19'),
(449, 39, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.021\r\n\r\nOK (1 test)', 0, '2024-06-10 02:48:37', '2024-06-10 02:48:37'),
(450, 39, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.031\r\n\r\nOK (1 test)', 0, '2024-06-10 02:54:21', '2024-06-10 02:54:21'),
(451, 40, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.024\r\n\r\nOK (1 test)', 0, '2024-06-10 03:09:56', '2024-06-10 03:09:56'),
(452, 40, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-06-10 03:15:35', '2024-06-10 03:15:35'),
(453, 40, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-06-10 03:17:13', '2024-06-10 03:17:13'),
(454, 40, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-10 03:23:31', '2024-06-10 03:23:31'),
(455, 40, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-06-10 03:30:11', '2024-06-10 03:30:11'),
(456, 40, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-10 03:36:04', '2024-06-10 03:36:04'),
(457, 40, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-10 03:47:11', '2024-06-10 03:47:11'),
(458, 40, 7, 1, 'java_files\\della_gmail_com\\LuckyFiveSecond.java:11: error: reached end of file while parsing\r\n	      }\r\n	       ^\r\n1 error\r\nTEST FAILED!', 1, '2024-06-10 03:52:08', '2024-06-10 03:52:08'),
(459, 40, 7, 1, 'java_files\\della_gmail_com\\LuckyFiveSecond.java:12: error: reached end of file while parsing\r\n}\r\n ^\r\n1 error\r\nTEST FAILED!', 1, '2024-06-10 03:52:14', '2024-06-10 03:52:14'),
(460, 40, 7, 1, 'java_files\\della_gmail_com\\LuckyFiveSecond.java:12: error: reached end of file while parsing\r\n}\r\n ^\r\n1 error\r\nTEST FAILED!', 1, '2024-06-10 03:52:21', '2024-06-10 03:52:21'),
(461, 40, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0\r\n\r\nOK (1 test)', 0, '2024-06-10 03:52:30', '2024-06-10 03:52:30'),
(462, 41, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-10 03:54:56', '2024-06-10 03:54:56'),
(463, 41, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-10 04:01:48', '2024-06-10 04:01:48'),
(464, 41, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-10 04:06:00', '2024-06-10 04:06:00'),
(465, 41, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-10 04:12:52', '2024-06-10 04:12:52'),
(466, 41, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-06-10 04:19:10', '2024-06-10 04:19:10'),
(467, 41, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-10 04:22:47', '2024-06-10 04:22:47'),
(468, 41, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-06-10 04:28:29', '2024-06-10 04:28:29'),
(469, 41, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-06-10 04:31:07', '2024-06-10 04:31:07'),
(470, 41, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-06-10 04:31:50', '2024-06-10 04:31:50'),
(471, 41, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-10 04:35:43', '2024-06-10 04:35:43'),
(472, 41, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-06-10 04:39:28', '2024-06-10 04:39:28'),
(473, 41, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-13 03:18:18', '2024-06-13 03:18:18'),
(474, 41, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-13 03:30:14', '2024-06-13 03:30:14'),
(475, 41, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-06-13 03:38:00', '2024-06-13 03:38:00'),
(476, 41, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.017\r\n\r\nOK (1 test)', 0, '2024-06-13 03:38:02', '2024-06-13 03:38:02'),
(477, 41, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-13 03:43:37', '2024-06-13 03:43:37'),
(478, 41, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-13 03:48:32', '2024-06-13 03:48:32'),
(479, 40, 7, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-13 05:25:10', '2024-06-13 05:25:10'),
(480, 40, 8, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nDeret Fibonacci: \n0 1 1 2 3 5 8 13 JUnit version 4.13.2\r\n.\r\nTime: 0.031\r\n\r\nOK (1 test)', 0, '2024-06-13 05:33:05', '2024-06-13 05:33:05'),
(481, 40, 9, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n*\n**\n***\n****\n*****\nJUnit version 4.13.2\r\n.\r\nTime: 0.015\r\n\r\nOK (1 test)', 0, '2024-06-13 05:39:34', '2024-06-13 05:39:34'),
(482, 40, 10, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n[Opinion, Tech, Science, Health]JUnit version 4.13.2\r\n.\r\nTime: 0.013\r\n\r\nOK (1 test)', 0, '2024-06-13 05:44:33', '2024-06-13 05:44:33'),
(483, 40, 11, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n83.33333333333333JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-06-13 05:48:03', '2024-06-13 05:48:03'),
(484, 40, 12, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nLuas Lingkaran = 615.44\nKeliling Lingkaran = 87.92JUnit version 4.13.2\r\n.\r\nTime: 0.031\r\n\r\nOK (1 test)', 0, '2024-06-13 05:51:56', '2024-06-13 05:51:56'),
(485, 40, 13, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nJumlah uang setelah 5 tahun: 1338225.5776JUnit version 4.13.2\r\n.\r\nTime: 0.032\r\n\r\nOK (1 test)', 0, '2024-06-13 05:54:53', '2024-06-13 05:54:53'),
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(489, 37, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-06-14 18:59:20', '2024-06-14 18:59:20'),
(490, 37, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.006\r\n\r\nOK (1 test)', 0, '2024-06-14 19:01:11', '2024-06-14 19:01:11'),
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(492, 37, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.037\r\n\r\nOK (1 test)', 0, '2024-06-19 08:39:09', '2024-06-19 08:39:09'),
(493, 6, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.022\r\n\r\nOK (1 test)', 0, '2024-06-22 05:32:59', '2024-06-22 05:32:59'),
(494, 6, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.022\r\n\r\nOK (1 test)', 0, '2024-06-22 05:40:20', '2024-06-22 05:40:20'),
(495, 42, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.029\r\n\r\nOK (1 test)', 0, '2024-06-22 05:42:33', '2024-06-22 05:42:33'),
(496, 42, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-06-22 06:46:15', '2024-06-22 06:46:15'),
(497, 43, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-06-23 07:45:02', '2024-06-23 07:45:02'),
(498, 43, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.023\r\n\r\nOK (1 test)', 0, '2024-06-24 00:06:37', '2024-06-24 00:06:37'),
(499, 43, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.02\r\n\r\nOK (1 test)', 0, '2024-06-24 00:48:51', '2024-06-24 00:48:51'),
(500, 44, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-06-24 11:40:01', '2024-06-24 11:40:01'),
(501, 44, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.007\r\n\r\nOK (1 test)', 0, '2024-06-24 11:42:20', '2024-06-24 11:42:20'),
(502, 43, 3, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nHigh Value Item!JUnit version 4.13.2\r\n.\r\nTime: 0.009\r\n\r\nOK (1 test)', 0, '2024-06-25 03:21:34', '2024-06-25 03:21:34'),
(503, 43, 4, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nShipping cost: 1.75JUnit version 4.13.2\r\n.\r\nTime: 0.011\r\n\r\nOK (1 test)', 0, '2024-06-25 03:25:57', '2024-06-25 03:25:57'),
(504, 45, 1, 1, 'java_files\\revisi_gmail_com\\TipeData.java:12: error: cannot find symbol\r\n             vBalok = panjang * lebar * tingg;\r\n                                        ^\r\n  symbol:   variable tingg\r\n  location: class TipeData\r\n1 error\r\nTEST FAILED!', 1, '2024-06-30 10:51:59', '2024-06-30 10:51:59'),
(505, 45, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-06-30 10:52:07', '2024-06-30 10:52:07'),
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(507, 43, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.045\r\n\r\nOK (1 test)', 0, '2024-06-30 10:57:50', '2024-06-30 10:57:50'),
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(509, 43, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-06-30 11:06:01', '2024-06-30 11:06:01'),
(510, 43, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.022\r\n\r\nOK (1 test)', 0, '2024-06-30 11:08:51', '2024-06-30 11:08:51'),
(511, 43, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.014\r\n\r\nOK (1 test)', 0, '2024-06-30 11:16:30', '2024-06-30 11:16:30'),
(512, 43, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.019\r\n\r\nOK (1 test)', 0, '2024-06-30 11:18:51', '2024-06-30 11:18:51'),
(513, 43, 5, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\ndiskon yang didapatkan adalah 20%JUnit version 4.13.2\r\n.\r\nTime: 0.012\r\n\r\nOK (1 test)', 0, '2024-06-30 11:20:08', '2024-06-30 11:20:08'),
(514, 43, 6, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\n12345JUnit version 4.13.2\r\n.\r\nTime: 0.023\r\n\r\nOK (1 test)', 0, '2024-06-30 11:20:45', '2024-06-30 11:20:45'),
(515, 45, 1, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nVolume balok = 420, Luas permukaan balok = 344JUnit version 4.13.2\r\n.\r\nTime: 0.022\r\n\r\nOK (1 test)', 0, '2024-06-30 11:23:22', '2024-06-30 11:23:22'),
(516, 45, 2, 1, 'java 19.0.2 2023-01-17\r\nJava(TM) SE Runtime Environment (build 19.0.2+7-44)\r\nJava HotSpot(TM) 64-Bit Server VM (build 19.0.2+7-44, mixed mode, sharing)\r\nSelamat anda lulus!JUnit version 4.13.2\r\n.\r\nTime: 0.016\r\n\r\nOK (1 test)', 0, '2024-07-02 10:28:27', '2024-07-02 10:28:27');

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(1, 'Tipe Data, Variabel dan Operator', 1, '<p><strong class=\"ql-size-large\">Variabel</strong></p><p>Variabel adalah tempat untuk menyimpan data. Deklarasi variabel adalah sebuah perintah agar komputer menyediakan variabel yang akan kita pakai. Pendeklarasian variabel harus diawali dengan tipe variabel, nama variabel kemudian diakhiri dengan titik-koma ;.</p><p><br></p><p>Bentuk penulisan :</p><pre class=\"ql-syntax\" spellcheck=\"false\"><tipe data> <nama> [=nilai awal]\r\n</pre><p><span style=\"color: rgb(51, 51, 51);\">nilai dalam tanda </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">[]</code><span style=\"color: rgb(51, 51, 51);\"> bersifat optional. Contoh:</span></p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-built_in\">int</span> contVariabel;\r\n\r\n<span class=\"hljs-built_in\">int</span> contohVar = <span class=\"hljs-number\">34</span>;\r\n</pre><p>Variabel dibagi menjadi 2 jenis yaitu</p><ol><li>Variabel lokal: variable yang hanya bisa dikenali pada sub program, pada kesempatan ini seluruhnya masih menggunakan variabel lokal.</li><li>Variabel global: variable yang dapat dikenali pada keseluruhan program. Penggunaan variabel global akan dijelaskan lebih detail pada pertemuan yang akan datang</li></ol><p><br></p><p><span style=\"color: rgb(51, 51, 51);\">Dalam memberi nama variabel ada beberapa aturan yang harus dipenuhi, antara lain:</span></p><ul><li>Diawali dengan huruf atau karakter underscore <code style=\"color: inherit; background-color: rgb(247, 247, 247);\">_</code></li><li>Nama variabel bersifat case sensitive (huruf besar dianggap berbeda dengan huruf kecil)</li><li>Tidak boleh menggunakan spasi (sebagai pengganti dapat digunakan tanda underscore atau penggunaan huruf besar pada awal kata berikutnya)</li><li>Tidak boleh menggunakan karakter khusus seperti <code style=\"color: inherit; background-color: rgb(247, 247, 247);\"><</code>,<code style=\"color: inherit; background-color: rgb(247, 247, 247);\">></code>,<code style=\"color: inherit; background-color: rgb(247, 247, 247);\">*</code>,<code style=\"color: inherit; background-color: rgb(247, 247, 247);\">?</code>,<code style=\"color: inherit; background-color: rgb(247, 247, 247);\">=</code> dan sebagainya.</li><li>Apabila nama variable lebih dari satu kata maka kata yang setelahnya diawali huruf besar.</li></ul><p><span style=\"color: rgb(51, 51, 51);\">Beberapa Keyword yang tidak boleh digunakan sebagai nama variabel:</span></p><pre class=\"ql-syntax\" spellcheck=\"false\">abstract, <span class=\"hljs-keyword\">default</span>, <span class=\"hljs-keyword\">if</span>, private, <span class=\"hljs-variable language_\">this</span>, assert, <span class=\"hljs-keyword\">do</span>, implements, protected, <span class=\"hljs-keyword\">throw</span>, boolean, double, <span class=\"hljs-keyword\">import</span>, public, throws, <span class=\"hljs-keyword\">break</span>, <span class=\"hljs-keyword\">else</span>, <span class=\"hljs-keyword\">instanceof</span>, <span class=\"hljs-keyword\">return</span>, transient, byte, enum, int, short, <span class=\"hljs-keyword\">try</span>, <span class=\"hljs-keyword\">case</span>, <span class=\"hljs-keyword\">extends</span>, interface, <span class=\"hljs-keyword\">static</span>, <span class=\"hljs-keyword\">void</span>, <span class=\"hljs-keyword\">catch</span>, final, long, strictfp, volatile, char, <span class=\"hljs-keyword\">finally</span>, native, <span class=\"hljs-variable language_\">super</span>, <span class=\"hljs-keyword\">while</span>, <span class=\"hljs-keyword\">class</span>, float, <span class=\"hljs-keyword\">new</span>, <span class=\"hljs-keyword\">switch</span>, <span class=\"hljs-keyword\">continue</span>, <span class=\"hljs-keyword\">for</span>, package, synchronized\r\n</pre><p><br></p><p><strong class=\"ql-size-large\">Tipe Data</strong></p><p><span style=\"color: rgb(51, 51, 51);\">Tipe data adalah jenis data yang ingin kita simpan di variabel. Tipe data dapat dikategorikan menjadi dua kelompok, yaitu</span></p><ul><li>Tipe data primitive/build in: tipe data bawaan dari sebuah bahasa pemrograman</li><li>Tipe data non-primitive/referensi: tipe data yang dibuat berdasarkan kebutuhan programmer</li></ul><p>Selengkapnya, tipe data primitive yang bisa dipakai dalam pemrograman Java ada di tabel berikut ini:</p><p><img 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\"></p><p><br></p><p><span style=\"color: rgb(51, 51, 51);\">Selain harus memperhatikan jenis tipe data yang digunakan, tipe data juga mempunyai penulisan nilai yang berbeda. Sebagai contoh penulisan nilai tipe data char harus diapit dengan tanda </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">\'</code><span style=\"color: rgb(51, 51, 51);\"> (petik satu). Variabel String harus menggunakan tanda </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">\"</code><span style=\"color: rgb(51, 51, 51);\"> (petik dua). Dalam penulisan bilangan pecahan digunakan tanda </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">.</code><span style=\"color: rgb(51, 51, 51);\"> (titik) bukan koma.</span></p><p><br></p><p><strong>Deklarasi variabel</strong></p><p><span style=\"color: rgb(51, 51, 51);\">Secara umum, format deklarasi variabel dapat dinyatakan sebagai berikut:</span></p><p><span style=\"color: rgb(51, 51, 51);\">contoh: </span></p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-built_in\">int</span> bilangan;\r\nbyte contohDeklarasiVariabelMenggunakanTipeDataByte;\r\n<span class=\"hljs-built_in\">float</span> volume, luas;\r\n<span class=\"hljs-built_in\">int</span> angka = <span class=\"hljs-number\">1</span>;\r\n<span class=\"hljs-built_in\">float</span> phi = <span class=\"hljs-number\">3.14</span>f;\r\nchar kelas = <span class=\"hljs-string\">\'A\'</span>;\r\nString nama = <span class=\"hljs-string\">\"Joko Sembung\"</span>;\r\n</pre><p><br></p><h4>Mencetak Variabel</h4><p><span style=\"color: rgb(51, 51, 51);\">Contoh penggunaan fungsi untuk menampilkan nilai variabel di layar command prompt adalah sebagai berikut:</span></p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(nilai);\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a);\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(<span class=\"hljs-string\">\"Nilai Anda adalah \"</span>+nilai);\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(<span class=\"hljs-string\">\"Angka adalah \"</span>+a);\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a+<span class=\"hljs-string\">\" angka pertama, \"</span>+b+<span class=\"hljs-string\">\" angkat kedua, \"</span>+c+<span class=\"hljs-string\">\" angka ketiga \"</span>);\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(<span class=\"hljs-title class_\">String</span>.<span class=\"hljs-title function_\">format</span>(<span class=\"hljs-string\">\"%d angka pertama, %d angkat kedua, %d angka ketiga \"</span>,a,b,c));\r\n</pre><p><br></p><p><strong>Casting Tipe Data</strong></p><p><span style=\"color: rgb(51, 51, 51);\">ketika kita ingin memberikan nilai dari tipe data primitive ke tipe data primitive yang lain. Ada 2 bentuk tipe casting tipe data:</span></p><ul><li><span style=\"color: rgb(51, 51, 51);\">Widening casting(otomatis): mengubah tipe data dari yang ukurannya lebih kecil ke tipe data yang lebih besar</span></li></ul><pre class=\"ql-syntax\" spellcheck=\"false\">	byte -> short -> char -> int -> long -> float -> double\r\n</pre><p>contoh:</p><pre class=\"ql-syntax\" spellcheck=\"false\">    	byte umur = <span class=\"hljs-number\">9</span>;\r\n        double myDouble = umur;\r\n        System.out.println(umur); <span class=\"hljs-regexp\">//output</span> 9System.out.println(myDouble); <span class=\"hljs-regexp\">//output</span> <span class=\"hljs-number\">9.0</span>\r\n</pre><p><br></p><ul><li><span style=\"color: rgb(51, 51, 51);\">Narrowing casting(manual): mengubah tipe data dari yang ukurannya lebih besar ke tipe data yang lebih kecil</span></li></ul><pre class=\"ql-syntax\" spellcheck=\"false\">	double -> float -> long -> int -> char -> short -> byte\r\n</pre><p>contoh:</p><pre class=\"ql-syntax\" spellcheck=\"false\">	<span class=\"hljs-comment\">//Contoh tipe data primitive</span>\r\n    int x = <span class=\"hljs-number\">9</span>; <span class=\"hljs-comment\">//hanya ada 1 nilai yang disimpan, yaitu 9</span>\r\n    char hurufKu = <span class=\"hljs-string\">\'N\'</span>; <span class=\"hljs-comment\">//hanya ada 1 nilai yang disimpan, yaitu karakter N</span>\r\n    \r\n    <span class=\"hljs-comment\">//Contoh tipe data non-primitiveString tulisan = \"Aku belajar Java\"; //ada 16 nilai, termasuk spasi</span>\r\n    int[] daftar = { <span class=\"hljs-number\">1</span>, <span class=\"hljs-number\">4</span>, <span class=\"hljs-number\">9</span>, <span class=\"hljs-number\">16</span>, <span class=\"hljs-number\">25</span>, <span class=\"hljs-number\">36</span>, <span class=\"hljs-number\">49</span> }; <span class=\"hljs-comment\">//ada 7 nilai bertipe integer</span>\r\n</pre><h4><br></h4><h4><span class=\"ql-size-large\">﻿Sequence/Statement</span></h4><p><span style=\"color: rgb(51, 51, 51);\">Perintah/statement digunakan untuk memerintahkan komputer untuk melakukan sesuatu. Contoh, pada program menghitung luas persegi panjang diatas, ada beberapa statemen:</span></p><ul><li>Perintah <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">panjang = 10;</code> memerintahkan komputer untuk mengisi variabel panjang dengan nilai 10. Begitu juga dengan perintah <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">lebar = 5;</code></li><li>Perintah <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">luas = panjang * lebar;</code> memerintahkan komputer untuk menghitung hasil perkalian dari panjang dan lebar, lalu menyimpannya kedalam variabel luas.</li><li>Perintah <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">System.out.println(\"Luas persegi panjang: \" + luas);</code> memerintahkan komputer untuk menampilkan isi variabel luas ke layar.</li></ul><p><span style=\"color: rgb(51, 51, 51);\">Setiap statement harus diakhir dengan titik koma </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">;</code><span style=\"color: rgb(51, 51, 51);\">, kecuali statement-statement tertentu seperti </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">if</code><span style=\"color: rgb(51, 51, 51);\">, </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">for</code><span style=\"color: rgb(51, 51, 51);\">, </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">while</code><span style=\"color: rgb(51, 51, 51);\">, </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">class</code><span style=\"color: rgb(51, 51, 51);\"> dan sebagainya.</span></p><p><br></p><p><strong>Keyword Import</strong></p><p><span style=\"color: rgb(51, 51, 51);\">Digunakan untuk memanggil library/fungsi-fungsi yang telah disediakan oleh bahasa Java. Perintah </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">import java.util.Scanner;</code><span style=\"color: rgb(51, 51, 51);\"> digunakan untuk memanggil library </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">Scanner</code><span style=\"color: rgb(51, 51, 51);\"> yang diperlukan untuk menerima input dari keyboard yang akan dibahas di bagian input.</span></p><p><br></p><p><strong style=\"color: rgb(51, 51, 51);\">Kurung Kurawal</strong></p><p><span style=\"color: rgb(51, 51, 51);\">Kurung kurawal berfungsi untuk memberitahu komputer bahwa perintah-perintah di dalamnya merupakan satu kesatuan. Singkatnya, kurung kurawal digunakan untuk membuat sekumpulan perintah (compount statement/block).</span></p><p><br></p><p><strong class=\"ql-size-large\" style=\"color: rgb(51, 51, 51);\">Output</strong></p><p><span style=\"color: rgb(51, 51, 51);\">Setiap program pasti menghasilkan output. Salah satu cara untuk menampilkan output adalah dengan menampilkannya ke layar. Untuk menampilkan ke layar, ada beberapa cara:</span></p><ol><li><code style=\"color: inherit; background-color: rgb(247, 247, 247);\">System.out.print(“Hello world”);</code> Perintah ini akan menampilkan kata Hello world ke layar, atau apapun yang kita tuliskan didalam tanda petik.</li><li><code style=\"background-color: rgb(247, 247, 247); color: inherit;\">System.out.println(“Hello world”);</code> Perintah ini akan menampilkan kata Hello world ke layar, atau apapun yang kita tuliskan didalam tanda petik, sekaligus memberi perintah ganti baris di akhir kata/kalimat.</li><li><code style=\"background-color: rgb(247, 247, 247); color: inherit;\">System.out.println(panjang);</code> Perintah ini akan menampilkan isi variabel panjang ke layar. Perhatikan bahwa untuk menampilkan isi variabel, tidak perlu menggunakan tanda petik ( “ ).</li><li><code style=\"background-color: rgb(247, 247, 247); color: inherit;\">System.out.println(“Panjang segi empat: “ + panjang);</code> Perintah ini akan menampilkan kalimat “Panjang segi empat: “ kemudian disambung dengan isi variabel panjang ke layar. Perhatikan untuk menyambung kalimat dengan isi variabel, digunakan tanda plus ( + ).</li></ol><p>contoh:</p><ul><li>Menggunakan System.out.print()</li></ul><pre class=\"ql-syntax\" spellcheck=\"false\">      System.out.<span class=\"hljs-built_in\">print</span>(<span class=\"hljs-string\">\"Hello World!\"</span>);\r\n      System.out.<span class=\"hljs-built_in\">print</span>(<span class=\"hljs-string\">\"Nama saya Jack\"</span>);\r\n</pre><p>Hasil</p><pre class=\"ql-syntax\" spellcheck=\"false\">      Hello World!Nama saya Jack\r\n</pre><ul><li>Menggunakan System.out.println()</li></ul><pre class=\"ql-syntax\" spellcheck=\"false\">      <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(<span class=\"hljs-string\">\"Hello World!\"</span>);\r\n      <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(<span class=\"hljs-string\">\"Nama saya Jack\"</span>);\r\n</pre><p>Hasil</p><pre class=\"ql-syntax\" spellcheck=\"false\">      Hello World!\r\n      Nama saya Jack\r\n</pre><ul><li>Menampilkan isi variabel panjang</li></ul><pre class=\"ql-syntax\" spellcheck=\"false\">      <span class=\"hljs-built_in\">int</span> panjang = <span class=\"hljs-number\">10</span>;\r\n      System.out.println(panjang);\r\n</pre><p>Hasil</p><pre class=\"ql-syntax\" spellcheck=\"false\">      10\r\n</pre><ul><li>Menampilkan kalimat \"Panjang segi empat\" dan disambung dengan isi variabel panjang</li></ul><pre class=\"ql-syntax\" spellcheck=\"false\">      <span class=\"hljs-built_in\">int</span> panjang = <span class=\"hljs-number\">10</span>;\r\n      System.out.println(<span class=\"hljs-string\">\"Panjang segi empat: \"</span> + panjang);\r\n</pre><p>Hasil</p><pre class=\"ql-syntax\" spellcheck=\"false\">      Panjang segi empat: 10\r\n</pre><p><span style=\"color: rgb(51, 51, 51);\">Pada output program terdapat beberapa karakter khusus. Karakter-karakter ini dikenal dengan istilah escape sequence. Karakter-karakter yang umum digunakan dapat dilihat pada tabel berikut ini:</span></p><p><img src=\"data:image/png;base64,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\"></p><p><br></p><p><strong class=\"ql-size-large\">Input</strong></p><p><span style=\"color: rgb(51, 51, 51);\">Untuk membaca input dari keyboard, pertama-tama kita pastikan bahwa library Scanner sudah kita sertakan. Caranya adalah dengan menuliskan perintah </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">import java.util.Scanner;</code><span style=\"color: rgb(51, 51, 51);\"> di baris paling atas dari kode program kita. Selanjutnya kita tuliskan perintah deklarasi scanner berikut ini didalam fungsi main():</span></p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-title class_\">Scanner</span> sc = <span class=\"hljs-keyword\">new</span> <span class=\"hljs-title class_\">Scanner</span>(<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">in</span>);\r\n</pre><p>Selanjutnya, tergantung dari jenis input yang akan kita masukkan, berupa bilangan bulat (int), bilangan koma (float/double), atau karakter (String).</p><ol><li>Jika input berupa bilangan bulat, maka perintahnya adalah: <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">nextInt();</code></li><li>Jika input berupa bilangan koma, maka perintahnya adalah: <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">nextFloat();</code></li><li>Jika input berupa teks, maka perintahnya adalah: <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">nextLine();</code></li></ol><p><strong>Contoh</strong>:</p><ul><li>Input berupa bilangan bulat:</li></ul><pre class=\"ql-syntax\" spellcheck=\"false\">    <span class=\"hljs-keyword\">import</span> java.<span class=\"hljs-property\">util</span>.<span class=\"hljs-property\">Scanner</span>;\r\n    \r\n    <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">Hello</span> {\r\n     public <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span>(<span class=\"hljs-params\"><span class=\"hljs-built_in\">String</span> args[]</span>) {\r\n       <span class=\"hljs-title class_\">Scanner</span> sc = <span class=\"hljs-keyword\">new</span> <span class=\"hljs-title class_\">Scanner</span>(<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">in</span>);\r\n       int usia;\r\n       <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Masukkan usia anda: \"</span>);\r\n       usia = sc.<span class=\"hljs-title function_\">nextInt</span>();\r\n       <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Usia anda adalah: \"</span> + usia);\r\n     }\r\n    }\r\n</pre><p>Hasil</p><pre class=\"ql-syntax\" spellcheck=\"false\">    Masukkan usia anda: 20\r\n    Usia anda adalah 20\r\n</pre><ul><li>Input berupa dua buah <span class=\"hljs-attr\">bilangan</span>:</li></ul><pre class=\"ql-syntax\" spellcheck=\"false\">    <span class=\"hljs-keyword\">import</span> java.<span class=\"hljs-property\">util</span>.<span class=\"hljs-property\">Scanner</span>;\r\n    \r\n    <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">Hello</span> {\r\n     public <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span>(<span class=\"hljs-params\"><span class=\"hljs-built_in\">String</span> args[]</span>) {\r\n       <span class=\"hljs-title class_\">Scanner</span> sc = <span class=\"hljs-keyword\">new</span> <span class=\"hljs-title class_\">Scanner</span>(<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">in</span>);\r\n       int panjang, lebar;\r\n       <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Masukkan panjang: \"</span>);\r\n       panjang = sc.<span class=\"hljs-title function_\">nextInt</span>();\r\n       <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Masukkan lebar: \"</span>);\r\n       lebar = sc.<span class=\"hljs-title function_\">nextInt</span>();\r\n       <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Nilai dari panjang: \"</span> + panjang);\r\n       <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Nilai dari lebar: \"</span> + lebar);\r\n     }\r\n    }\r\n</pre><p>Hasil</p><pre class=\"ql-syntax\" spellcheck=\"false\">    Masukkan panjang: 15\r\n    Masukkan lebar: 7\r\n    Nilai dari panjang: 15\r\n    Nilai dari lebar: 7\r\n</pre><p><br></p><p><strong class=\"ql-size-large\">Operator</strong></p><p>Operator merupakan simbol yang biasa digunakan dalam menulis suatu penyataan (statement) dalam bahasa pemrograman apapun. Operator akan melakukan suatu operasi terhadap operand sesuai dengan fungsinya. Jenis-jenis operator adalah sebagai berikut</p><ul><li>Operator Aritmatika</li><li>Operator Increment dan Decrement</li><li>Operator Assignment</li><li>Operator Relasi</li><li>Operator Logika</li><li>Operator Bitwise</li></ul><h5><br></h5><p><strong>Operator Aritmatika</strong></p><p>Arithmatic operator (operator aritmatika) adalah operator yang berfungsi untuk operasi aritmatika.</p><p><img 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\"></p><p>Contoh penggunaan:</p><pre class=\"ql-syntax\" spellcheck=\"false\">int a = <span class=\"hljs-number\">10</span>, b = <span class=\"hljs-number\">5</span>\r\n\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a+b); <span class=\"hljs-comment\">//hasilnya 15</span>\r\n\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a-b); <span class=\"hljs-comment\">//hasilnya 5</span>\r\n\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a*b); <span class=\"hljs-comment\">//hasilnya 50</span>\r\n\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a/b); <span class=\"hljs-comment\">//hasilnya 2</span>\r\n\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a%b); <span class=\"hljs-comment\">//hasilnya 0</span>\r\n</pre><h5><br></h5><p><strong>Operator Increment dan Decrement</strong></p><p><span style=\"color: rgb(51, 51, 51);\">Digunakan untuk menaikan atau menurunkan suatu nilai integer (bilangan bulat) sebanyak satu satuan, dan hanya dapat digunakan pada variabel</span></p><p><img 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\"></p><p>Contoh penggunaan:</p><pre class=\"ql-syntax\" spellcheck=\"false\">int a = <span class=\"hljs-number\">6</span>;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a++); <span class=\"hljs-comment\">//hasilnya 6</span>\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(++a); <span class=\"hljs-comment\">//hasilnya 8</span>\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a--); <span class=\"hljs-comment\">//hasilnya 8</span>\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(--a); <span class=\"hljs-comment\">//hasilnya 6</span>\r\n</pre><p><br></p><p><strong>Operator Assignment</strong></p><p><span style=\"color: rgb(51, 51, 51);\">Operator assignment dalam Java digunakan untuk memberikan sebuah nilai ke sebuah variabel. Operator assignment hanya berupa </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">=</code><span style=\"color: rgb(51, 51, 51);\">.</span></p><p><img 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\"></p><p>Contoh penggunaan:</p><pre class=\"ql-syntax\" spellcheck=\"false\">int a, b;\r\na = <span class=\"hljs-number\">6</span>;\r\nb = <span class=\"hljs-number\">3</span>;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a); <span class=\"hljs-comment\">//hasilnya 6</span>\r\na += b;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a); <span class=\"hljs-comment\">//hasilnya 9</span>\r\na -= b;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a); <span class=\"hljs-comment\">//hasilnya 6</span>\r\na *= b;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a); <span class=\"hljs-comment\">//hasilnya 18</span>\r\na /= b;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a); <span class=\"hljs-comment\">//hasilnya 6</span>\r\na %= b;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a); <span class=\"hljs-comment\">//hasilnya 0</span>\r\n</pre><p><br></p><p><strong>Operator Relasi</strong></p><p><span style=\"color: rgb(51, 51, 51);\">Operator relasi dalam Java digunakan untuk menghasilkan nilai boolean yang sering digunakan untuk mengatur alur jalannya sebuah program. Nilai yang dihasilkan dari operator ini adalah </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">true</code><span style=\"color: rgb(51, 51, 51);\"> atau </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">false</code><span style=\"color: rgb(51, 51, 51);\">.</span></p><p><img src=\"data:image/png;base64,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\"></p><p>Contoh penggunaan:</p><pre class=\"ql-syntax\" spellcheck=\"false\">int a = <span class=\"hljs-number\">6</span>, b = <span class=\"hljs-number\">3</span>;\r\nSystem.out.println(a > b); <span class=\"hljs-regexp\">//hasilnya</span> <span class=\"hljs-literal\">true</span>\r\nSystem.out.println(a < b); <span class=\"hljs-regexp\">//hasilnya</span> <span class=\"hljs-literal\">false</span>\r\nSystem.out.println(a == b); <span class=\"hljs-regexp\">//hasilnya</span> <span class=\"hljs-literal\">false</span>\r\nSystem.out.println(a != b); <span class=\"hljs-regexp\">//hasilnya</span> <span class=\"hljs-literal\">true</span>\r\nSystem.out.println(a >= b); <span class=\"hljs-regexp\">//hasilnya</span> <span class=\"hljs-literal\">true</span>\r\nSystem.out.println(a <= b); <span class=\"hljs-regexp\">//hasilnya</span> <span class=\"hljs-literal\">false</span>\r\n</pre><p><br></p><p>Operator Logika</p><p><span style=\"color: rgb(51, 51, 51);\">Operator ini digunakan untuk ekspresi logik yang menghasilkan nilai boolean, </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">true atau false</code><span style=\"color: rgb(51, 51, 51);\">.</span></p><p><img 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\"></p><p>Contoh penggunaan:</p><pre class=\"ql-syntax\" spellcheck=\"false\">boolean a = <span class=\"hljs-literal\">true</span>, b = <span class=\"hljs-literal\">false</span>;\r\nSystem.out.println(a && b); <span class=\"hljs-regexp\">//hasilnya</span> <span class=\"hljs-literal\">false</span>\r\nSystem.out.println(a || b); <span class=\"hljs-regexp\">//hasilnya</span> <span class=\"hljs-literal\">true</span>\r\nSystem.out.println(!a); <span class=\"hljs-regexp\">//hasilnya</span> <span class=\"hljs-literal\">false</span>\r\n</pre><p><br></p><p><strong>Operator Bitwise</strong></p><p><span style=\"color: rgb(51, 51, 51);\">Operator ini digunakan untuk melakukan manipulasi bit dari sebuah bilangan.</span></p><p><img src=\"data:image/png;base64,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\"></p><p>Contoh penggunaan:</p><pre class=\"ql-syntax\" spellcheck=\"false\">int a = <span class=\"hljs-number\">60</span>; <span class=\"hljs-comment\">//ubah ke biner 00111100</span>\r\nint b = <span class=\"hljs-number\">13</span>; <span class=\"hljs-comment\">//ubah ke biner 00001101</span>\r\nint c = <span class=\"hljs-number\">0</span>;\r\n\r\n<span class=\"hljs-comment\">/*      00111100\r\n        00001101\r\na & b = 00001100*/</span>\r\n\r\nc = a & b;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(c); <span class=\"hljs-comment\">//hasilnya 12</span>\r\n\r\n<span class=\"hljs-comment\">/*      00111100\r\n        00001101\r\na | b = 00111101*/</span>\r\n\r\nc = a | b;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(c); <span class=\"hljs-comment\">//hasilnya 61</span>\r\n\r\n<span class=\"hljs-comment\">/*      00111100\r\n        00001101\r\na ^ b = 00110001*/</span>\r\n\r\nc = a ^ b;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(c); <span class=\"hljs-comment\">//hasilnya 49</span>\r\n\r\n<span class=\"hljs-comment\">/*   00111100\r\n!a = 11000011*/</span>\r\n\r\nc = ~a;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(c); <span class=\"hljs-comment\">//hasilnya -61</span>\r\n\r\n<span class=\"hljs-comment\">/*       00111100\r\na << 2 = 11110000*/</span>\r\n\r\nc = a << <span class=\"hljs-number\">2</span>;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(c); <span class=\"hljs-comment\">//hasilnya 240</span>\r\n\r\n<span class=\"hljs-comment\">/*       00111100\r\na << 2 = 00001111*/</span>\r\n\r\nc = a >> <span class=\"hljs-number\">2</span>;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(c); <span class=\"hljs-comment\">//hasilnya 15</span>\r\nc = a >>> <span class=\"hljs-number\">2</span>;\r\n<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(a >>> <span class=\"hljs-number\">2</span>); <span class=\"hljs-comment\">//hasilnya 15</span>\r\n</pre><p><br></p><p><strong class=\"ql-size-large\">Flowchart</strong></p><p>Flowchart merupakan sebuah bagan dengan symbol-symbol tertentu yang digunakan untuk menjelaskan urutan proses dan hubungan antar proses lainnya pada sebuah program.</p><p><br></p><p><strong>Simbol-simbol flowchart</strong></p><p><img src=\"data:image/png;base64,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\"></p><h5>Contoh flowchart</h5><p>Flowchart untuk menghitung luas dan keliling bangun datar, persegi panjang.</p><p><img src=\"data:image/png;base64,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\"></p>', 'https://www.youtube.com/embed/IecFYqIGO-w', 1, '2023-06-01 05:41:16', '2023-06-01 07:14:10', NULL);
INSERT INTO `contents` (`id`, `title`, `lesson_id`, `description`, `url_video`, `published`, `created_at`, `updated_at`, `deleted_at`) VALUES
(2, 'Sintaks Pemilihan IF-ELSE', 2, '<p><strong class=\"ql-size-large\">Sintaks Pemilihan IF</strong></p><p><br></p><p>Pada kehidupan sehari-hari kita selalu mengambil keputusan dengan mempertimbangkan berbagai hal/kondisi-kondisi. Sintaks pemilihan adalah statement pemilihan yang digunakan untuk mengatur kapan suatu perintah akan dijalankan. Dengan statement ini kita bisa mengatur kapan suatu perintah akan dijalankan, yaitu ketika telah dipenuhinya suatu syarat tertentu. Misalnya:</p><blockquote>Jika <strong>nilai lebih dari 70</strong> maka <strong>Diterima</strong></blockquote><p>Pernyataan di atas mengandung sebab akibat. Bila dilihat, keterangan <strong>nilai lebih dari 70</strong> adalah merupakan suatu syarat, sedangkan <strong>DITERIMA</strong> ini akan dilakukan apabila syaratnya terpenuhi atau <strong>nilai lebih dari 70</strong>. Dalam dunia logika, istilah <strong>terpenuhinya syarat</strong> dapat dikatakan <strong>syarat tersebut bernilai benar atau TRUE</strong>. Selanjutnya pernyataan <strong>jika...maka...</strong> dapat diadopsi dalam <em>programming</em>. Untuk pernyataan tersebut dalam programming, maka dapat digunakan statement sintaks pemilihan. Pada pembahasan di materi sintaks pemilihan 1 ini akan dipelajari tiga macam sintaks pemilihan yaitu <code style=\"color: inherit; background-color: rgb(247, 247, 247);\">if</code>, <code style=\"color: inherit; background-color: rgb(247, 247, 247);\">if else</code>, <code style=\"color: inherit; background-color: rgb(247, 247, 247);\">if else if else</code> dan <code style=\"color: inherit; background-color: rgb(247, 247, 247);\">switch case</code>.</p><p>Bentuk umum:</p><pre class=\"ql-syntax\" spellcheck=\"false\">if (kondisi)  {\r\n  pernyataan;\r\n  pernyataan;\r\n  ...\r\n}\r\n</pre><p>Bentuk flowchart:</p><p><img 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\"></p><ul><li>Apabila kondisi bernilai benar, maka pernyataan akan dilaksanakan.</li><li>Apabila kondisi bernilai salah, maka pernyataan tidak akan dilaksanakan.</li></ul><p>Pada sintaks pemilihan 1 ini, kita akan menggunakan operator hubungan (<em>relational operator</em>). Berikut ini operator hubungan dalam bahasa pemrograman Java:</p><p><img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAooAAAEQCAYAAAA3YVU0AAAgAElEQVR4nO3dX2gbZ7438K/De9HrCkxTb3skt5dGGKyC5XG7OqJgSIyMFwqVUdzgBHzSuLYhXnoUVr6wD9F7qEts4zRrSETqmmhhX97UwikEgo+29USGCuoK3W3XmjdFTSuqvQq7YXep3ouZ0TwzGv1xosiO8/2AaS3Nn9/zjCz99HueZ9L28OHD0rFjx6D/tLW1mX4AlP9LRERERM+PYwcdABEREREdTkwUiYiIiMgWE0UiIiIissVEkYiIiIhs/a9qT+zt7XExCxEREdER09nZ2fC2VRNF8UBMFIkas7e3t68/QCIiolba29vb1/YceiYiIiIiW0wUiYiIiMgWE0UiIiIissVEkYiIiIhsMVEkIiIiIltMFImIiIjIFhNFIiIiIrLFRJGIiIiIbDFRJCIiIiJbTBSJiIiIyBYTRSIiIiKydWQTxcyyBx6P8bO4a3oWix4PPJ5FZJpwDvOxn95xiokpU5uace7mK2JjcgobhYOOg4gaob+vTCWK4qPYmNTeZyY3UKy6t/3xzMciomfZkUwUi4kpjK2ZH1s/KyZVbkyn00inp+FudXCPKbPswcCcXPH4+lkPPMtPku42UxEbkwOYv3fQcRDR4xP+jvsiuLM8BEejeyambN+niOjZdQQTxSK278oAJES+SCOdTuPOrAQAWP9ST6isFUX92/MUNhKL5Wqd+q1Y+GZdrQJ5fwNTnhrb7C6aqoD7/ra9u6glvkab0uk00tdC6vNr14UKntG2DbECWZFM6tvZPW8cY3HZ8rylLeY+1JNEGfMnzO00V3itFcca5yOiFqqfJJr/lo33OzFJlOcGTJXIavvo+3k8HkwtL2rvo/r7g+U9yjKCYlRCN4TtKkczxJGYxV39/VyMQXyPr3yPbvQ8REfVEUwUHXC9DgAy5v9LfaNyBJbUxGqyXv1QxvzcuvHb3BymTBWydYzZJDDrc/MwvkOvY0wcqtldhOfsuml7eW5gX4lQ5kt1/9C1JQy1C090T2tJsIz5P1iPt4558Zv92pjw5pfBomcMpqhMzxvHWNcqs6G33EBhA1OWtlTrE1P8yx5LhVdNJCuHzS3nI6IWyjeUJJr/li3vdzYa3UdeW1ffR/v86G8vYmPS8h4FYP1s5RdxeW5e2M543wcA7C6aKpzrZ+ewVRFf5SiIPDdXkQjWPA/REXYEE0XA/ZZWabs3j4F9VvGk2TtIp9OIjQKADBkR3BGrd9/lKt8cRmNalS+GEADc28J2AQCK2IjpSV7avI2pClhLEbnvAECC6+XKZx29fkhV9iyfU4tdvrutxr67hXWhren0HUT6AHnus4o3Yf0Y090A2oewlBYqml9E1HN/l0MRDgwtq8fRK59LAQdQ2MD1NQAIIWaphK7HKt9oTecjopaR58aMhKn8HibKYGsNahKZFkZr7s3js131C7k+eiPN3kF6eQiOOvuY6NssD8EBB4aWhfeatP7ekkPOGpe+n/5+dC+HPADx/bf8XnfNBdmSFLonxfMY7/25Hxo9D9HRdiQTRXRPG3/MmsaqeBL8vep36A6n9ob3dr/6rfplV5WETELkXb365YZffJMpbGNL+3Z+qpz4uHFKqwJWvBE1k3jO7lPqm6z2xla8nwOg9YnHA49H/0ZtfRMOwW+bsGlDQifESqq94s4WZADS7CljPqglnvrnI6KWGI0ZoxTWilkhhxxg+gKuV+ty96t8Ed/HPuX3Wgt12Lr63Ofyfu398PeJz+SRuwcAIZwJaEfW33ts6EPM1vnt9c9DdLQdzUQRMFW/9G+5WNt6olXO9mokfO0uuJ74+MZQut159ESswmN9262TvBa0uZiTOZwSv1nX4Hj1yXuAiFpgNIb0pBuOwKz2RW4ecw2OxMjKY7zb1NzHmDeee1esKDafPn/ys1eXhIoiEemOYKJYeesbR+AMQk/xjOIimS1t0Yk6TNwBl/aGawyzZPDZnIxqQ8l29KH09bOWCdTC/JvKOX3r2NLPufuZNu/IhQ4YyZsx9Gz81BryLVcH9W/WP+TqVhT1SqxpWNsSDxEdPMmp/zU6MDSmTVcR/271L77CMHL5p9r878fZBxBGY/zobweM6uB+aO+/WMd1PeHV33vK9PdsfTRDn+pDRLr/ddABNJ86/Lu+to4xj2Uq9Kj/6dwOZ20MHnG4ovzmpr7hzt9bx/pZj3li9ugZ88KUWrqnERtdx9iaughk3vr8aMw2wbOes5zgdfsRwjrW5wbgmRPjbuxWGLJ1v8ot1DhHY0hPDuHM6Dxkm+sRGmv8thtE1ELdpxDpW8f8vXWMLfu1pE5/b53HgEd8F5IQ+cK80E59jwghlp5ueB9b96z77Yfx/mu8Z0mQ+lAxTxGw+bwgIgBHsqKoTk6uGD7QhlWehtCsOAQbQkxMtrqnjYUwGmn2zr5jcU8KQ+jiua9V+2YeQkTcfjSmLi5Rj4ZpfVFNtbhtlIekhHPHRiFMfDcqEdbYzddDXezCBStEh5UDQ7/T3tfWxsp3KLB7bxXvxmA3elNvH1vtQ5i1vH+p76Mytnb2sda4fGcIQH3fmYXfHB2mxffnvgjuaFNqjJEioudb28OHD0vHjh2D/tPW1oa2tjbkcjm89tpr6kZtbQccJjVOv/WN+m2eN5lprb29PXR2dh50GEQE4dY85UIB3x+J9vs5dQSHnomIiPS7V8iV04Oe1jQkoiPoSA49ExEROQJLldOQ+iK485SmIREdRRx6JmoiDj0TEdFhtt/PKVYUiYiIiMgWE0UiIiIissVEkYiIiIhsMVEkIiIiIltMFImIiIjIFhNFIiIiIrLFRJGIiIiIbDFRJCIiIiJbTBSJiIiIyFbNf+t5b28PAP9lFqL90P9uiIiInnU1E0X9n3hhokjUGP4TfkREdJjtt5jBoWciIiIissVEkYiIiIhsMVEkIiIiIltMFImIiIjIFhNFIiIiIrLFRJGIiIiIbDFRJCIiIiJbTBSJiIiIyFbNG27vx6NHj5p1qLpeeOGFlp2LiIiI6HnFiiIRERER2WKiSERERES2mCgSERERkS0mikSHwe4iPB6P8DOFjcJBB1VfZtkDz3LmoMNoisyyB1OJovgIFk3X5ICuT2EDU5MbKD7u84JiYsrSRiKi2pq2mIWIHtPuIjxngVg6Dbf42AkPctfSmO4+yOCeE7uLGEMM6YDDeKyQQw4SIl8sYaj94ELDDznIr/vhqPJ05g/zwNt3qj4vcgRm4Z+cw0bvAbeJiJ4ZrCgSHbDMl+vAqN9IEgGgexqxUWD9S7FaV8TGpLmyJVaH1IpYRthGrXpllu231/cxVcrqVQcLG5gqb7+IrYoNLDFaKl1qjBumSt3irqU/TPGq24rb1Iy5sIEpzyI2ElNVY6hUxEYsh8i7bvOjO1uQ+/zor5dQidXg5QyKiamKeE1tLGxgylSRtFQuLfEW7+cgOTvs4570YGwNkOcGhGtruQama+rA0JgL8//VWAWSiAgPHz4s/e1vfys9evSo9I9//KP0z3/+s/Svf/2r9Oc//7n0yy+/lH755ZdSI/7+97+37IfosPrLX/6y731+3pgs9fRMlj7/qeZWpc8/6Cn1LH1bdb9vl3psfu8pTW78rD7wzeVST8/lkn6Eb5d6Sj0ffF76WT/gN5dLPT09pcvfVAnhp89Lk+Lz2vZGTGqM5fPp5xBitsaotsGIyfq73gb9nHVj1mI0zvlt6XKPOaYK31w2H7NK7FX3rXEN1D6xXFvT+dT4jD6378Pa18Tor8r2Vh5P3abe642Ijqr9fk61pqJY2MRv+/vRL/7MbOKvAJBZMT/e34/+T7ItCYvoMHAElhAblTF/olZlz4Gh5TTSk0bVy9Hrh2Q92OiZ8pCi+60QgBDO6MOp3X6EkENOq2S5J9NILw8ZQ5bdfoRqxKlW2CI4pQ+Fa1XPst3PMI8IZoXhW/dkDKG16+b5fEKMahv0mIrYvisjdG26XF11vxsxtbGxmCWhOuiGfxSQlXz1dt3PAa+7LEO3ReS+A7A2ZjM/cREZbZuN2Dqk2VlLn7vgKlch88jdE3+3ns+N6bQ4vcAB1+tivBlsrYXgrzb94Icc5D4X9HpjMXEd633iNXCg/20J8t1toYLYAVefjK0d1hSJqL7WzFFsH8RH24P2z7knsL090ZIwiA4r92Qa6UlAHTYcwPzaGDxrQMhmjmJmWR1uVEnw1zqwkERUU0xMYWBOLv9eLVnMKzLw+hlTQtXhlABFO879HHBvHQOeecueEiJ1YtDOgNw9Ca7fCQ+1u+B6gpgbOqsiQ3LOmh8sbGPrXp35ido2/t8JPfKyC1IfjD7f3cL6qB/TRuTYvitDels4X2EDUyfmYbQGkGa1IxRyyNW4hpkv14HXY9o1MY4tXiPHq9YeFJPRRmY2EtHzrDWJYmETv/3N/0ZKfKz3P5FYGMSLmRX0v/8H8/Yjv8f2+10tCY3ocFErh0PQkqHYBk5pFbRygtgXwZ30EByFDUydqJwl2Cgj2Qohll6CGxksesaeLPy+CO6IFb8ma37MWuXQaXn4hxxkuHCm1vxEu20sC08q5xfmkbsHuMbULdRrGkIsncaS+ojanlcdtsezi116Wz+++djlre7nAEu6LSb4RES1sKJIdKC0xMCmcuh41QXcy0Gt+2SwtdbMFbj6MG/jq6o7nBJwN4ci3OXEJa/IAM7YxPs41CHR3A8A9DYWcjDSnP3HXJ9aXbMq3s8Bff661VirzJfrCL1l1A/zigzXW0Jv7G5hHSHEugF1WBmmoXZ9pbX/ZSMO+4UsgF6BNVU0KyPCZ3MypFlzlVG8bkREtXDVM9GBcuPUrIT1s9b78unz304Jq6G1JAoAkMGiZbjyceTuiytlx7BeY1tH4AxC9+bxmb6Cd3dRGAIH0H0Kkb51jInzK3cXhTl99ajz6dbPGttn/lDZxv3E3IgOp1Qxh1EdZrfOW7To9iOEdVzXVhsXE1MYW5PgelnfQKtW6nYX4Tm7LkwH6ICrT2yPfk31OY1FbN8F/L1VotCSaIM6H3M9ZqxoziyPWeYsGnFVT0CJiAy8jyLRAXMElpB+Vb1voji7L3QtjaVy5cyN6WsheM56tMRIQuSLGEInxrC1U8RQYL81PAeGfhfB1okBeOb0891BBAOY/zKD6W63zT5uTH8RwdQJDzwA0BdBZBRCzA4MLceQ86jzK7WjIpaeht3RbKMKLCGmeDDm0Vo5G0EIW1ry9TgxN3DOV12WSqla6QPEdghGY9qiIv2aqPGoseaEhSsODI0J12w0hjuzOQwoegJqbY+EyLUIpLN6+qcuhPFXqyC3u+CCjPkTU4BWaXZPphFb9hjzRG2nAjRSiSQiUrU9fPiwdOzYMeg/bW1taGtrQy6Xw2uvvaZu1NZW90CPHj162rGWvfDCCy07F9F+7O3tobOz86DDOEIyWPRch+up3vRaXUCUG3vCIe3CBqb+C5h9inM0m2J3EZ4v/aYV9ET0/Njv5xSHnonokFBvFC3eFFy93UsDN71+Imrlz3xz88fwQw5yveHqA2d/c3EiomqYKBLRIaEOxWJuoHzPwoG7/qe6irqsexoxjD3Rv4Nce+HJ4VBMzGHr7Vn+831E1DAOPRM1EYeeiYjoMOPQMxERERE1RdNWPbPKR0RERHS0sKJIRERERLaYKBIRERGRLSaKRERERGSLiSIRERER2WKiSERERES2mCgSERERka2at8fZ29sD0NgNt4lIpf/dEBERPetqJoodHeo/R8VEkagx+Xy+/HdDRER02OTz+X1tz6FnIiIiIrLFRJGIiIiIbDFRJCIiIiJbTBSJiIiIyBYTRSIiIiKyxUSRiIiIiGwxUSQiIiIiW0wUiYiIiMhWzRtu70epVGrWocp4o28iIiKig8OKIhERERHZYqJIRERERLaYKBIRERGRLSaKRIdBZgWSJAk/M9gsHHRQ9WWvSJCuZA86jKbIXpEwc7tY+URhEzMHdW0Km5i5sAmbqJ5I9oqElUz5N6xIK3haV9F8LiJ61jBRJDpomRVI54BVWYas/1x1IjrMD9iWyaxgHKtYOOkwPZy9IkEaTsJ362CuTfaPUcDvhaP+po0rbOLGzSB8bv13BUqvE8ebeQ5B1/lV4NzTS0SJ6OlqWaKY/aQfv73911adjuiZkf0qDoz40CU+6J7A6ggQ/0r8eC1i84JkqjyKFTC1IpYVtlErX9kr9tvr+5gqmfWqg6bq2gqSFRtYYrRUw9QYN7EinNOacJnjVbcVt6kZc2ETM9IKNm/PVI2hUhGbnyoIv9NlfjizgvGbQazKCxhsFx53TyBx0Yv4p8Zx1apZVmuXkRSZYrWJoyjGaWqn2o/jN4HUpYBx3SzVTXPfFbF5YQabGW0bu3ZnViANR5FCHON6nD8qSHU6ASEW6zWpHidQrkiKsZnO3YXgRQXjR6TyTPS8aVmi2PV+Ar/+nwCTRSKL404vcPNGxXBm13kZ8nk9eSli80IA0c7VcmUrcdGL1KWoab/UpRvAh+rzqyMpRIcl3HAmtEpYEKlLcVMSM74XRqJcKQsCN8erV8oKm5gZjsJ5Vd8eiN8UN1BjTPoT5RhXO6MIWBKE1KUknLeMNsSFalPx9oyWnKnPn1aiiAv7NhZzHFHltBbDKoI7UUTthpR1mTii8MErJoMoYvPTOIJXJ9Bls4vj5ALkjwe1Sl8Ryp4XyqdJ+GQZsjyBLj3Rw2rVvijenkFgy2dqi9EXDgx+GIYXal8snHRoSZ5Q3bwVhnJOHAZ/AAVA8lMgLMtCfALtC4j3YkKLU/2i4t27gSjCxjURkuDacUKtSCKO8f/Wzqv1eVy4Jo43fPDeTLKqSPQMauHQ84sYXNjGe/8vgP5P+HZBpHOcXCgnddUrew4MfiwmjtqHr/VgI6fL1a+uN4MAgjitD6e6fQhCgaIlFl3nLcmE24dgjTiLXyeR6g0jqA9ZaklHWSaOKMIIC8O3XedXEbQmwUKMahv0mIpIbaVMyVnXO2FTGxuL2StUB7vgGwFSyoPq7fpeATqd5qSqkEJyRxierekBlJ0UnO8JSWUmjuhOEKvC9ep6MwgIyZI52QTwklPoC6iVvvKQsJq4ei+Gjepmuxe+3hSSX+vVRgXKDuD70CZBNFoLZQ9wvuIw/Q5/uGLYXddYnGEk7BJTXbsTTsSR5FQKomdO02643aiu97fx+0/60T/zn0gsDOLFVgdAdAip1UOgXDm8OQ7pJhC8KmPCkqxkr6hDkiovfLUO3MDcs+LtGQQupcq/V0sWHygpoPO0KRk47vQCinac7xVgJ46AFLXs6UW4TgzaGaDseOH8UHio3QnnE8Tc0FmVFLxOS4RakmY8msWKNG6qbpavTUGB0htGWLhO2a/ULcclcY/KSM3XUn3+dLtwjM5Vtb8LKSR3gNROANIl8xG9fiHmkdNYaEd1hRSSO174yn38AMpOEKc/Nq6q3XWuF6fXnzC2LyhQ4IXvJXH743D2Asnvi4C7qTMuiegpa3mimP2kH/+B32N7wW5Ah+h5p1YOB6ElQ59uIqhVasof1r1hJORBOAqbmBmunCXYKCPZUufhdWnJ0BOpV1l6Qs2PWauo2WWjOwoeAFpbujAhy5gAtCH4JJx6IvSjglSnT2izekzvxUTVKp0+jI+LCciyw2jbllFBVPYAr/+4cQ4EsSrbD4UDaqLuddb5WvCjghSc5SQPmSTiIz61XXbnbShOL3zvOKqfAwDggLOzdmhEdDi1cOj5r9ic6cen/5bA9vtMEolU2YrFGjrHK85ysgJkkbzpRfhWlbln+6YP88rluWr1HHd6gT3FtEDigWJU9czxPo7jcPamoPwoPFRQ9ILlY8VcX5UExjq8KtISIaeWCDWUoFnow/jiML1aydOHwNXqqu+Nxq/0AyUlDClXOe/3imnhVGXsD6DsGEPTjcVp9EX5HBWVbC0hJ6JnTgtXPQfwp39P4KOTHGwmMnQheNGL+Dnrvfn0OWlBISESk6gsVoajSOHJKN+Xlyxg84J5aNXKcfK0eZFCZsU8HOkOItwbN69uzayYVgHX5oDXb17ckv1jZRv3E3Mjjju9lXMY2wdxeiSF6LAl9sImZs7FTYlQZYKmtkNcOKSvVta/EFiTanURD4ykzZQgQ5uLGccNyyp3Y3WxWtlzmoZ7K4mJvW3smSTiMOZmNhSnJSl8oKTgrbiljzkBJaJnR8uGnrve38ZHrToZ0TPEcXIB8isrkIYliLP7gldlLJTnvXVh4moQ0jlJS4y8CN9aRXB4HMmvixisNsRZ/awY/DCM5LAx5y14NYEwAoh+lcWE265e14WJW2HMDEuQAKA3jPAIhJgdGPx4FYqkzq/UjlpzuLQiqpMLWFWk8tw+78UwgtCHeR8n5gbO+YoT2FJQRJcpuek6LyPhnEFAkkzbey8mIJ8UF4ME4Ttfux3q9ZKNhSjuCayOCM+PrGJ1JIUb+gHanXAihejwDHBrAYPtet8LcxRHViF/rLf5ART4EKw1PxFaVfjSOCSsQj5/XE0u3zGeV6uBPiPxqxdnlWF355uW12NBgYIgTje0OIiIDpO2hw8flo4dOwb9p62tDW1tbcjlcvjVr36lbtTWVvdApVKp+cE1cF6iwySfz6Ojo+OgwzhCsliRbsB5y3Ivw6ZSFxAp71UuHKLmKN6eQRTVV1YTUevk83l0djY+aZj/MgsRHRLqvQfFm4IXb99AvNd6j8Nmc2DwvaDl5ubUPFnELzmN2zQR0TOFiSIRHRLq0DIuBcr3kwxs+Z7qKuoy9wRWMW7/bz3TE8leGQeq3LiciA4/Dj0TNRGHnomI6DDj0DMRERERNUXTVj2z+kdERER0tLCiSERERES2mCgSERERkS0mikRERERki4kiEREREdliokhEREREtpgoEhEREZEtJopEREREZKvmfRTz+TwA3iORaD/0vxsiIqJnXc1EUf8nXpgoEjVmb29vX/80EhERUSvt7e3ta3sOPRMRERGRLSaKRERERGSLiSIRERER2WKiSERERES2mCgSERERkS0mikRERERki4kiEREREdliokhEREREtmrecHs/Hj161KxDlb3wwgtNPyYRERERNYYVRSIiIiKyxUSRiIiIiGwxUSQ6DHYX4fF4hJ8pbBQOOqj6MsseeJYzBx1GU2SWPZhKFMVHsOjxYHH3wEIyySybY7H+/jTPRUTPLyaKRAdtdxGes0AsnUZa/7nmwvwJfli3zO4ixhDDUsBhPFbIIQcJrpcPLqyywgaur4Xg79YfKCL33dOLzT0ZA84u4mh8BSCiJ8FEkeiAZb5cB0b9cIsPdk8jNgqsfyl+VBexMekxVR7FCphaEcsI26hVycyy/fb6PqZKZr3qYGEDU+XtF7FVsYElxskNmGp0yx5MJTawKJzTmgyb492oqOrVjLmwgSnPIjYSU1VjqFTERiyHyLtu86M7W5D7/Ohvr7HfZK2+y5jaaX2+KMZYq4K8uwjPiXnIWMeYR0/e8sjdc8EF4XrUPL61nzNY9CwiI15PUz+5cWo2h7EjUi0moifw8OHD0t/+9rfSo0ePSv/4xz9K//znP0v/+te/Sn/+859Lv/zyS+mXX34pNeLvf/97gz/50h/PT5T++P/qb0v0rPnLX/6y731+3pgs9fRMlj7/qeZWpc8/6Cn1LH1bdb9vl3psfu8pTW78rD7wzeVST8/lkn6Eb5d6Sj0ffF76WT/gN5dLPT09pcvfVAnhp89Lk+Lz2vZGTGqM5fPp5xBitsaotsGIyfq73gb9nHVj1mI0zvlt6XKPOaYK31w2H7NK7JZnLce1tt36u2V7y7WwtrvibEuWNnxzudTzwWRpUo/7p89Lk9Z+regn4fh6P5W3UeMzXfufPi9N1oiJiJ5N+/2canFFMYuV/gD+9O9hDFb9lk70fHEElhAblTF/olZ1yoGh5TTSk0bVy9Hrh2Q92OgZDGl/W+63QgBCOKMPp3b7EUIOOa1y5Z5MI708hPJga7cfoRpxqhW2CE7pw59a1bNs9zPMI4JZYfjWPRlDaO26uVomxKi2QY+piO27MkLXpsvVVfe7EVMbG4tZEqqDbvhHAVnJV2/X/RzwugsO86PIfQdIzg77fRLXsd4nttWB/rclyHe3TdVLeW5Oa7sb0+m0eWgb6+WKnSOwhHR62lxVtsTietXYt3g/B8CPWbEvBI7AkrmfXnYJ/QzghxzkvgjuVNkfANDuggvr2OL0B6LnWgsTxSxW+v8D+GQbH518sXWnJXoGuCf1+Yl3EOkDsDZmOywLCEOvJ+Yh1ztwnwv2qY7BGKIcw3qN7fKKXJFQdTiNNK54Pwfcm8eAaVFO7WNazoDcPcu8u3YXXE8Qc0NnVeTKhLCwja175uRMODu278oVbR2YE6+GA0PLMYSgfQGwDn93T+POrFTzOptjMfdLXpERGhOSvB9ykOGCS/gCbhqiPzFvej7z5Tqkt/uN/W3nY3bA1Qfk7tceuCeio61pN9yuqbCJ3/7mT/j1/91mJZGoJrVyOAQ1GRqIbeCUVvXJLHswtgagL4I76SE4ChuYOlE5S7BRxcSUltyEEEsvwY0MFj1jTxZ+vSrVE2p+zGq1Dk7Lwz/kICOEM912++SRuweErqUxbfu8Tq0iThc2MHViHgOTMPWNI7CEdEC7rmc9QLXjaUngmfJ7ZwZbayH4J4VW3M8BfX71S4F2PszeQTqtnq2YmMLAXf1Lg7oQxv+uo8Y5AMAB1+u12kdEz4PWVBTbB/HR9ntQftOPFc6NJhJUvwWL41UXcC+HvLbd1pqEyBeWodfHpg/zpmsMeZp1OCXgu5ypMpZXjCqaOd7H0QFXn4zcD8JDhRxyTxBzffbJkJp41a/G2lMXuZSvafsQlq6FjL7ZXTRVGN2TahW5WuWueD9nXuxUyCFniU2s9upTBMQpAOZqsLYQRkgK7durJdFE9Fxr4dBzFya2fw+834/f3v5r605LdKi5cWpWwvpZ66rXIjZi65BmT8gnv9QAACAASURBVAkJkZhEZbDYyNBzHUZyUsTGZO1hXEfgDEL35vGZngDtLqoVTl33KUT61s0rZXcX4fE0epsVdZ7funBblswfKtu4n5gb0eGUKuYw2g2zG9R5j+sxYTh5d1FYuawmn+LzpkTsZRcksR+1CqX9MLc5GQegVv9MsWWwtQaE3lJfKdaEvZiYwtiaMN+ySqJpGopuIC4iej60Zui5rAsT2wlszkSx+cZHHIYmgjYE+eoiPCc8mBceD11LY6k8FOnG9LUQPGc9WmIkIfJFDKETY9jaKWIosN8PcweGfhfB1okBeOb0891BBAOY/zKD6W67ep0b019EMHXCAw8A9EUQGYUQszovL+cZg6ecQIYQ20f1zxFYQkzxYMyjtXI2ghC2tLlzjxNzA+d81QXczaEIt5YoqYkXILZDMxpDetKtVgEnBzDg0VuvD4WrKp4Xh+Tbh7B0LSdcy9rD2B1OCZgbgwfquYv3c+Y5ldr8Qr8+v7B7GrFRow8xGkNsVMZ1ffsfcpBf9wtJobZY5i3La6iQQ67q8DsRPS/aHj58WDp27Bj0n7a2NrS1tSGXy+G1115TN2prq3ugR48eNT24F154oenHJHqa9vb20NnZedBhHCEZLHquw/XFUnmldPMVsTE5gNxYvTmHz5diYgpzmLWs1CaiZ91+P6d4w20iOiTUuX3iTcHV29DUuul1MzgwNBay3Nz8eZfBZ3Mu49ZKRPTcYqJIRIeEOrSMuQHjljN3/U91FXVZ9zRiGKv4l2ueV5nlMeBasxYMEdGzjEPPRE3EoWciIjrMOPRMRERERE3BRJGIiIiIbDXt9jgcJiYiIiI6WlhRJCIiIiJbTBSJiIiIyBYTRSIiIiKyxUSRiIiIiGwxUSQiIiIiW0wUiYiIiMhWzdvj7O3tAWjsX2YhIpX+d0NERPSsq5kodnR0AGCiSNSofD5f/rshIiI6bPL5/L6259AzEREREdliokhEREREtpgoEhEREZEtJopEREREZIuJIhERERHZYqJIRERERLaYKBIRERGRLSaKRERERGSr5g2396NUKjXrUHXxBuBERERETx8rikRERERki4kiEREREdliokh0GGRWIEmS8DODzcJBB1Vf9ooE6Ur2oMNoiuwVCTO3i5VPFDYxc1DXprCJmQubsInqiWSvSFjJlH/DirSCZ/EqFm/PWP5uhJ8Wvi7N/bn/54Utn9lrQUdX0+YoEtFjyqxAOgesyjK6xMeGJShXZUy4DzK450RmBeNYhXzSYXo4e0XC+E0vwrdkLLQb27bq2mT/GAX8CTjqb9q4wiZu3Azi9Hn9dwVKrxPHm3mOFnmgpICRVcjnu+pv/NQUoex54XynytPW/q6pCxNXk5CuZA+4TUQGVhSJDlj2qzgw4oPpY8E9gdURIP6VWFsoYvOCuWoiVsDUilhW2EatfGWv2G+v77OvKoypuraCZMUGlhgt1TA1xk2sCOe0VlrM8arbitvUjLmwiRlpBZtipaluRa6IzU8VhN+xfDBnVjB+M4hVeQGD7cLj7gkkLnoR/9Q4rloxymrtMipCplht4rBWxIx2qv04fhNIXQoY181S3TT3XRGbF2awmdG2sWt3ZgXScBQpxDGux/mjglSnExBisV6T6nEC5SqYGFsjfX6h+uuuWn+aZZG8CQTfrJdQFS1/E1msiPHZVG2tlfLa7X8AZccJp/ga0dn1t/54tQq1O4jw3niDFUiip69liWL2k3789vZfW3U6omfGcacXuHmjYjiz67wsVBWK2LwQQLRzFbIsQ5ZlJC56kboUNe2XunQD+FB9fnUkheiwhBvOhLrP1SBSl+KmJGZ8L4yEdjz5ahC4WeMDqrCJmeEonFf17YH4TXEDNcakP1GOcbUzioAlCUhdSsJ5y2hD/JzxAVq8PaMlZ+rzp5Uo4sK+jcUcR1Q5rcWwiuBOFFG7IWVdJo4ofPCaPuiL2Pw0juDVCdilIY6TC5A/HtQqfWpFSfk0CZ8sQ5Yn0KUnelit2hfF2zMIbPlMbTH6woHBD8PwQu2LhZMOLelIwqf1nXwrDOWcmGQ8gAIg+SkQlmUhPoH2BcR7MaHFqX5R8e7dQBRh45oISXDtOKFWJBHH+H9r59X6PF410cliRRJfJwmE98aFLzF2/WmjoECBF86Xqp1HPZbp7+aWD8nhccQ7nUbfaImyQ9hH2TMS0IbaX60ia9Pfxdsz5REE9XhORIfFZNgBr99r+ZJIdHBalih2vZ/Ar/8nwGSRyMJxcqGc1FWv7Dkw+LFsGo5yvOGD13qwkdPl6lfXm0EAQZzWh1PdPgShQNESi67zlmTC7UOwRpzFr5NI9YYR1IdbtQ/BskwcUYQRFoZvu86vImhNgoUY1TboMRWR2kqZkrOud8KmNjYWs1eoDnbBNwKklAfV2/W9ApgSBQCFFJI7QfgaGlp+AGUnBed7QkKTiSO6E8SqcL263gwCN5PlhMCcbAJ4ySn0BdQEppyAqImr92LYqG62e+HrTSH5tV5tVKDsAL4PbRJEo7VQ9gDnKw7T7/CH1WTURmNxhpGwS0ztIrh9A/Fe8XWiJkaprZSWnNr0p50fFaRg+buxVs6t16HdC18v4HUaaV3xe8X0u3p+IwGt1/7i10nA763Sdmt/ZxG/ZH6Nq6/hOJJCYu14xWl6rRAdpBbOUXwRgwvbcH7Sj/5Pfo/t97U/k8wK+t//g3nTEeF5oueAWj0EyhWQm+OQbgJBm3lw6rw5/TcvfLUO3MDcs+LtGQQupcq/V0sWHygpoPO06QPxuNMLKNpxvleAnTgCUtSypxfhOjFoZ1A/oD8UHmp3wvkEMTd0ViUFr9MSoZakGY9msSKNm6qb5WtTUKD0hhEWrlP2K3XLcUncozJS87VUnz/dLhyjc1Xt70IKyR0gtROAdMl8RK9fiHnktDGX0k4hheSOF75yHz+AshPE6Y+Nq2p3nevF6RXnUWqVPp9tpU/9MuD1h03Hd7wiXGWb/rSjTtmoPT9R30b4egVnpzlRTm0Bvg+FaDJJxOHEqtCPtdr/QEnB+WaVFNna35kk4ghi1dS243D2lv+MVC854UUSSgHoqnU9iVqg5YtZut7fxu8/6Uf/zH8isTCIF90T2N6eaHUYRIeUWjkchJYMfbqJoFbNKH9Y9YaRkAfhKGxiZrhylmCjjGRLnYfXpSVDT2QflaXH0fyYtYqaXTa6o+ABoLWlCxOyjAlAG4JPGkOePypIdfoqhi69FxNVq3T6MD4uJiDLDqNtW0YFUdkDvP7jxjkQxGq1YVjYVcZs/KggBWc5yUEmifiID8Y7sOW8DcXphe8dR/VzmDyAsgM43zP3S/F7BeWLUNGftq01x9nwNtaFJ+r8Qp8Qa/F7Bej1qe1rsP1VF7JY+sJ07DK1T/Ce8FCVL0hEB6Hli1myn/TjP/B7bC8M4kVArSj295t/PmHBnZ4X2YrFGjrHK85ysqJO3FdX39rOPds3fZi3xhwwi+NOL7CnmCb9P1CMqp453sdxHM7eFJQfhYcKilBp2X/M9akVpgrW4VWR9uHvFD786yZoFvowvjhMr1by9CFwtbrqe6PxK/1ASQmVsirn/V4xLZyyH3Y1Km6NxWleyKEmQ/tZRa0Ox3q14dvG+tMcZ8MKKSTF+agV8wv1iqcWy2O0X2Ttb9ttbt9AHJZpDqbXPdHBamGi+FdszvTj039LmIeV3RPY3t42/3DYmZ4bXQhe9CJ+znpvPn1OWlD4kBGTqCxWhqNI4cko3xsLCDYvmIdWrRwnT5sXKWRWzMNx7iDCvXGMi/MrMys1Vq1WnEGdxC8sFMj+sbKN+4m5Eced3so5jO2DOD2SsiwygFphOhc3JUKVCZo2505YOKSvVta/EFiTanURjzB3zpooaPPYblhWuRuri7XKVs2FHebE3jZ2bWhUT1oaitOSFD5QjESrkjpn1LxifNw0Z7GRhLexhSzW66D9zVgXspS316Z9CAlo3fZrFdlqn1jW/na84YNX/BsqbCJqnbNYjqt6AkrUSi0bes5+EsCf/j2Bj06+2KpTEj0THCcXIL+i3ptPnN0XvCpjoVxl6MLE1SCkc5KWGHkRvrWK4PA4kl8XMVhtiLP6WTH4YRjJYWPOW/BqAmEEEP0qiwm33UdfFyZuhTEzLEECgN4wwiMQYnZg8ONVKJI6v1I7as3h0oqoTi5gVZHKc/u8F8MIQh/mfZyYGzjnK05gS0ERXabkpuu8jIRzBgFJMm3vvZgQ7rdYhLIXhM9yjzxrO9TrJRsLUdwTWB0Rnh9ZxepICjf0A7Q74UQK0eEZ4NYCBtv1vhfmKI6sQv5Yb/MDKPAhWCexOO70ApfGIWEV8vnjFcOmFUOj9eKsMuxedc4e1H5dvSIZc1lN0xXs+9Oq+HUSKaSQsvzNqLwI31JvaeQ4GUZ4K6DFH0T4ohdeMa11BxFGQItF/5u6YSSgddpfr/pp7u8uoH0QC7dg/A3Bfh6yWok83aSqOdGTaXv48GHp2LFj0H/a2trQ1taGXC6HX/3qV+pGbW11D1QqlZ52rGWNxEN0EPL5PDo6Og46jCMkixXpBpy3LPcybCq1kqS8x5ubH3XZKxKSbx7261zE5oUo8OHTfM3T8yyfz6Oz027OjT3ecJuIDgn13oPiTcHVW6lY73HYbA4MvhfkfeuOvMaG5w9cJo5o52kmiXRoMFEkokNCHVrGpUD5fniBLd9TXUVd5p7AKsbt/61nOiJqLzw5HLJYOQfT/TeJDhqHnomaiEPPRER0mHHomYiIiIiagokiEREREdlq2u1xOBxMREREdLSwokhEREREtpgoEhEREZEtJopEREREZIuJIhERERHZYqJIRERERLaYKBIRERGRrZq3x8nn8wB46xui/dD/boiIiJ51NRNF/Z94YaJI1Ji9vb19/dNIRERErbS3t7ev7Tn0TERERES2mCgSERERkS0mikRERERki4kiEREREdliokhEREREtpgoEhEREZEtJopEREREZIuJIhERERHZqnnD7f149OhRsw5V1wsvvNCycxERERE9r1hRJCIiIiJbTBSJiIiIyBYTRSIiIiKyxUSR6DDYXYTH4xF+prBROOig6ssse+BZzhx0GE2RWfZgKlEUH8Gix4PF3QMLySSzbI7F+vuzopiYsrzWhZ8Wvpbq9t/uYoPxZLDoWcTR+CsgqtS0xSxE9Jh2F+E5C8TSabjFx054kLuWxnT3QQb3nNhdxBhiSAccxmOFHHKQ4H/54MIqK2zg+loIZyb1B4rIfSfB9e5BBvV48ooMjMaQnnTX3/ipqdd/RWzE1hEam27gWG5MX9uCZzlzwG0iejoOoKL4V2zO/Babz0C1hKgVMl+uA6N+mD5iuqcRGwXWvxTrFEVsTJorMGIFTK2IZYRt1KpkZtl+e32ffVV0ChuYKm+/iK2KDSwxTm7AVKNb9mAqsYFF4ZzWqo453o2Kql7NmAsbmPIsYkOsWlliqFTERiyHyLvmD/nizhbkPj/622vsN1mr7zKmdlqfN1fWalSQdxfhOTEPGesYK1eu8sjdc8EF4XrUPL61n7UqmHg96/aTpe9tru3irt7mahW2DLbWgNBb9RKqouV1nMGieL7CBqZszm/qA0uV3vza1/rP9tpmsOgZwPw9YP2s0G+m41muV/cpRL4beyYrvER1PXz4sPS3v/2t9OjRo9I//vGP0j//+c/Sv/71r9Kf//zn0i+//FL65ZdfSo34+9//3sDP16WPenpKE/8n3+D29j9Eh9Vf/vKXfe/z88ZkqadnsvT5TzW3Kn3+QU+pZ+nbqvt9u9Rj83tPaXLjZ/WBby6Xenoul/QjfLvUU+r54PPSz/oBv7lc6unpKV3+pkoIP31emhSf17Y3YlJjLJ9PP4cQszVGtQ1GTNbf9Tbo56wbsxajcc5vS5d7zDFV+Oay+ZhVYrc8azmute3W3y3bW66Ftd0VZ1uytOGby6WeDyZLk3rcP31emrT2a0U/CcfX+6m8jRpf1Wtv8/oz98/Ppc8/mCxNflC9DcZ59/lar7imWntM10bdx/zatLZXOO9Pnxt9Z8fymqi4Ptbj69tUfb0QHR77/ZxqYUUxi5X+/wA+2cZHJ180Hs6soL+/3/zzSbZ1YREdMEdgCbFRGfMnalWnHBhaTpuGthy9fkjWg42ewZBWJXG/FQIQwhl9OLXbjxByyGmVEPdkGunlIZQHW7v9CNWIU62wRXBKHwrXqp5lu59hHhHMCsO37skYQmvXzdUXIUa1DXpMRWzflRG6Nl2urrrfjZja2FjMklAddMM/CshKvnq77ueA111wmB9F7jtAcnbY75O4jvU+sa0O9L8tQb67bapyyXNzWtvdmE6nsSQObWMdY9p1dgSWkE5Pw77OpsbietXYt3g/B8CPWbEvBI7AkrmfXnYJ/QzghxzkvgjuVNm/wu5nmL8XQkx4/bnfCgFrW0KFU4ZrrFobhPPC8lq3Vvys52rvh7/PfC2K93OWa5NH7p4Elz5NoHva3J/tLrggI/eDtv/OFvB2f9W2m18TGXw2Z35dqq+7dWwJFUTHqy6hP4iOjtbMUSxs4re/+RN+/X+3MWgt9bsnsL090ZIwiA4r92Qa6UlAHXIbwPzaGDxrQMhmjmJm2YOxNf03Cf5aB+5zwT7VMRQTUxiYk8u/V0sW84oMvH7G9OHa4ZQARTvO/Rxwbx0DnnnLnhIidWLQzqB+2P9OeKjdBdcTxNzQWRUZknPW/GBhG1v3ANeYXSqhJrS4J1e2tU+/Gg4MLceQ84xh/oQH89akrHsad2ZzGJirfp3NsUjwC/2SV2SExpaM4/2QgwwXzgjvr+bXCQCEys9nvlyH9PYdY/868zHV6RExcxKoJZ/l/fsimK0zn1Y/Tq25fJXncsD1upgoF7F9F/D/Trg2u1tYhwsxof3W1wggIaK1L6/IcL1VNU3E9l0Z0tuzwrFDiJna1gFXH/TWq152QcIWcgXAXXW6AtGzpzUVxfZBfLT9HpTf9GOlYhoPK4pEBq1ymE7jzqyE9ZgxD0ufHzb2XQR30mmkv4hUVhT3QZ/DNjDnQiydRjode6KECwDQp8Vm+lkqVxCfVPNjVqt1FX7IQUYIftvEJ4/cPTW5S1vbaqrQqVXE9BcRSPfmMWCZU6dWEdPqXNSzNVbgakmgMZ8ug601c2zF+znjS4E27/C68045rjuzkvClQV3I4e911DhHZR9VVFd/yEEW/7+iKtvgcepuoy08KSexlfMLTe3X5oYOKGeM63ItBJTbZz2elXp99cTUfGzzNiZVvtQQPetaOPTchYnt3wPv9+O3t/9qPOyewPb2tvnn/a7WhUV0oKrfgsXxqgu4l0Ne225rTULkC2sy8rj0Yd50jSFPsw6nBHyXMyU7ecWo2JjjfRwdcPUZw4MAtErX48dcn1qtsrJPDhqlLsQoX9P2ISxdCxl9s7toWgjinryDSB+Qu2+/lKR4P2de7FTIIWeJTa32qomaPkVAnAIgPl8/0WqwjTFjEVblULAdcwLWsMI2tiAsKqpov14B1IaS9QqgULU0t6/WQhbt+FW/JGjHS1zHunUb02uV6Oho8arnLkxsJ/Dr/4ly1TMRAMCNU7MS1s9aV72qH8TS7CkhIRKTqAwWT8xDHFh7HEZyUsTG5BjWa2zrCJxB6N48PhNWgZqGNrtPIdJnzLvTt6m+ArbiDOh/W8L6WWP7zB8q27ifmBvR4ZQq5jCaEysrdd6jWO1V26lfQzX5FJ83JSovuyCJ/VgngRKTcQA21TvzSmJrwl5MTGFsTajSVUk0papz9rT5l3Ofla9LMTFnmkeYV+T6CaA2vF29kmd3Lu11LrZXrGTqUzXE/rPOx9xdVIeg9WPsbmHdepcBken42jxa8XoVNjBnnbNY3q9GAkr0jDqA+yi+iMGFj1p/WqJDyhFYQvpV9b6J4oy30LU0lsoVCzemr4XgOevREiMJkS9iCJ0Yw9ZOEUOB/dYYHRj6XQRbJwbgmdPPdwcRDGD+ywymu+0+Rt2Y/iKCqRMeeACgL4LIKISYjXl5nnICGUJsH9U/R2AJMcWDMY/WytkIQtjSkovHibmBc77qAu7mUIS7vHhhaw0AxHZotPl17sk7iEwOCHMUQ4ill4xFONbnxTmK7UNYupYTrmXtOYodTgmYG4MH6rkrqnfW+YXd04iNGn2I0RhiozKu69v/kIP8ul9ICrXFMlXn7KnX5Q6mMODxCO3Vr2sRue9C8E9W3V3damcLMmTIlte5SkLkC3WKgiMwi8jdAS3+ECKzEiQxre0+hQj0vtX/Dq4bCWj7EGZntzCgn6cvgtishDFhLm3N6ufLLkiYx5gHahvbh7D0BYzXPeyvl1r5PdOkSjfR4dH28OHD0rFjx6D/tLW1oa2tDblcDq+99pq6UVtb3QM9evToacda9sILL7TsXET7sbe3h87OzoMO4wjJYNFzHa4vmjfPsZJalcqN8ebmh1Fm2YOttw77tSliY3IO+N3TfJ0SNcd+P6f4T/gR0SGhzu0Tb4ys3oam1k2vm8GBobGQ5ebmdDjUW3hySOx+hvnXzzBJpCOJiSIRHRLq0DLmBsr31hu462/8Xn9PonsaMYxV/Ms1dNDqLDw5FDJYPAvT4hmio4RDz0RNxKFnIiI6zDj0TERERERN0bRVz6zyERERER0trCgSERERkS0mikRERERki4kiEREREdliokhEREREtpgoEhEREZEtJopEREREZKvm7XH29vYANHbDbSJS6X83REREz7qaiWJHRwcAJopEjcrn8+W/GyIiosMmn8/va3sOPRMRERGRLSaKRERERGSLiSIRERER2WKiSERERES2mCgSERERkS0mikRERERki4kiEREREdliokhEREREtmrecHs/SqVSsw5VF28ATkRERPT0saJIRERERLaYKBIRERGRLSaKRERERGSLiSLRQcqsQJKkqj8zt4tAYRMz0gw2C1WOUe95i+LtGUgXNlFsWiMOmX32x2FWvD0D6UpWfASbFyRI0gqy1o0zK/aPVz86Ni/U7qfi7Znqr88rjZ/pSWWvSFjJPP7zwpZY2VcfEVHTFrM0JLOC/jUnEguDeLGlJyY6pNwTkOUJ7ZcsVqQbcN5awGC7uNEgFuTBAwiODlRhE9EtHxIfdwkPPoCy44W3N45kZgJdbuOZ4vcK0OvD8UaPn4kjCh8S7dU3eaCkgJFVyOe7qm/01BWh7HnhfKfK04VN3LgZxOnzjRyrCxNXk5CuZA+4TUTPDlYUiQ47mwpZ9opQdfyjYtlBrzpZKpNVqMeqXlkyV5UqtxNjqag0FTYxI60gK1ZOr2S1x/V9LBWeiipr/QpQ7f6oPKZYfVKrdpumPqvoL3H/C5vYvGLXTqlqP2WvSJi5vYmVKjHYtumPUTjfG4TDFEcScThx+r0g4l+Ze+WBkgI6ncb2lpgq2nwuDuxEEahaXc4ieRMIvlkvoRJfbzPYLGSxIhyzeHvG0p9ZrNjFU7VvHkDZccJpl9BmViANR5FCHOPi68R0vS2vWXcQ4b3xBiuQRNTaRPElJ7wtPSHR0ZO9ImF8L4yELEOWE/DtxZEqP1vE5oUAop2rkGUZsiwjcdGL1KWobSJoHMtaxdRkVhC45MSqdiz5qhPRYeMD2RyLDPlqELhp/RCOY/wrn/r8rTC8N8chDSs4rcUf7o3jhp5IZFYgnVMQvqUdT15FEHGM1xjmrN0f+jFhtOFWGMo5S/JwMwrlPaMNpv4qbGLmXBzBq9rz7ymI3hT2LWxiZjgKp/68nEC4N4Xof5sTsNSlJJy3jGsSP1cjAdaqZD63+WG1aujEcbcPwZs3hDYUoewJSV1mBdJwEr5b9m12nAwj3Au1TR9bktFyDAoUeOF8qVqQ6nlNr7dbPiSHxxEXEtYHSgrOV4QzFBQoMNpWvD2DwJbP9Boy9U1BgdLrtK+UuiewOgJ4LyYgyxPogp4Eo+prFnDA6/dWJNpEZO/gK4qZFfT395t/PuEfMJE9rcpTrjQ5MPhhWPgC5sDgx7JpWM3xhs/2C9qD2zMYvxnEarVEwY42VK4fveu8JdFw+xCs2MmL8DvaHu1e+HoB78Wgdgz1QzulPBCOLyatXfCN1AqoXn8UsflpHMGrRsxoH0T4IhD9o/A+0xtGUE/K3D4EkYLyo3aEr5NIjaxiovx8EOFeIYT2QSzIsvG81qYKI6fL7VKviQKl2vzAHxWkbJIjo2rYBd9ICsmvtVS0kEJyR0/q1DZ7L4aNfmz3wtcrbK8NYddMAn9UkEIK0eEqc2cBdfh6J4jV85br69Qj14aNX7IcV2ib4+SC+TX0ktPUN8Wvk4DfW+U1qibIRiKaRfxSyny93T4EEUdS+PLieMUJ3ExyriJRA1o7RxEAOp3m+YnuCWxvT1TbmohEWpXHJ37wtjvhtNk0e0XCeLny5YVPfHInivEdACOnUXNg0R1EuDeAcSkOQK1ATbgrNyvenkHgklHHq0wWzUwVJjtala58xGrJYt3+eABlB4jvSIhb9x05XSdK7QhKCl5nWHjEAWen3ZZZrEjjxnl6fXYbNaT4vQJ0+izJkZYUX1WvWNebQaQ+TaF4chCOHxWk4MTpdpSTRt+H4t6WmLUh7NUa8xOzX8Xrzk/UtxG+lsDZKVzfQgpJ+BBut+zTuWpqm/m1CgBBtS3QKpJvVnm9lNsqtiuIVdNr9DicvYBpQsJLTniRhFIAumr0ARG1uqLYPoiP3re86bCiSNRU+ny98nDsrbBNRTGIVXkVwYphYiutQinLWB0B4ufMc770uWXG8PRq3SSxJn1enTCUu1qzotiY8rCx+NO0xQxZbe7hOJSLifLQ8pN4oKQqH7QOBbuDCCOJVEFLLEd8asKmJY3mOX1q5a38mz6EXTUCdXujMtjoNpYK4o8KUuK8Ses+2vW+4UyYpkoYsdlUJEWWttq3S/2yYFLlyxURVWptophZQX+/ZV6OewLb29vmH2syEsi41gAABE1JREFUSUSqdiecwrAoAC2B0GWRvOlV5/jVGlLudeI4uhCsN1dO0HXemH+nDmEWkdpKaUnYRO3KZIP0YV5Ztq9cVqjbH1o16fvHvxnQcacwNK5GaUq6kEki3qsm5QsnGx7Er3vOChUJoANeP5D8uqhVPWskdZk4ojte+N5Q43ugpOCtOpwL6MlV3cqvlVZB9AqJmykuvQKoxVH8OolUbxhhod/Mi3JqLGSBJUGuonj7BuKwzPc0vUaIqJaDn6NIRPugJXef6gslitj876h58YYpccpiZdj6vEFd1FBjsYj13nyWD3pATMKK2LwwXjnEu197imnFrHlI0qpefzgw+J5lcYq2SrfWSnCR4w0fvGLlNRNH1Fqh2lFQTiUzK6Zh+MfheMVp6gfAPilyvOEDtqK4cVNI6rQ5eeUFQshi5Zw4Z9GS6NppaCGLNr/0Ulx7fWivNctCFuOY+nQCI/FzvOI09Z1+vcvJZSaJeI1E0Fp5dbzhg3cnirh+rQqbiFrnLAJVqq5EZKe1cxTdE9jebukZiY4cx8kFrCoSAlIUABC8GIZ3J6k924WJq0FI5/Q5eV6Eb60iODyO5NdFDFZUvNTFH8nhcay8aVPFc09gdUQqz1EE1GFcNeHQ9w1AuqQ/l0AYAUS/ymLCvf8ao+NkGOGtQLltGFlF4iIQuJRE9nyXbcJQuz/UNiQuziAwLEE7KrwXE41X/9oHsXBVMfq0N4zwCJDUkxlrH/WGkbgaROBcEqnCoP1q8npecsKrJVBa7Q2prRS8/rB5u3YvfIgiapqn2YUJeRUrknFdzO1V5xGmLgUwA/t+KH6dRAoppIQ+M3gR1u71qV8vte1BhC964RUGfrveCQP660Pvl0+FoWFr342sYnUkhRt6HNaKpMVxpxe4NA4J2lzK9kEs3AJmhiVI2jZ282rVpLvO/FwiAgC0PXz4sHTs2DHoP21tbWhra0Mul8OvfvUrdaO2troHKpVKTzvWskbiIToI+XweHR0dBx0GPWXZK+q8umYNNR/UOZote0VC0u4Lx6FSxOaFKPBhlVtCER1x+XwenZ22K/JsceiZiKiGin/ysLCJGzfNw+9PQ9c7YWAr9Qz9U4t1Fp4cFpk4op2nmSQSNYiJIhFRDY6TYYQRRUC/j+BwEr6Kf2bxKWgfRNifRKCF/6byk6m98ORwyGLlHIz7PhJRXRx6JmoiDj0TEdFhxqFnIiIiImqKpq16ZpWPiIiI6GhhRZGIiIiIbDFRJCIiIiJbTBSJiIiIyBYTRSIiIiKyxUSRiIiIiGwxUSQiIiIiW0wUiYiIiMhWzfso5vN5ALxHItF+6H83REREz7qq/4Sf/gMwUSQiIiJ6HnHomYiIiIhsMVEkIiIiIltMFImIiIjIFhNFIiIiIrLFRJGIiIiIbDFRJCIiIiJbTBSJiIiIyBYTRSIiIiKyxUSRiIiIiGwxUSQiIiIiW0wUiYiIiMjW/wftn2pMp6vN+QAAAABJRU5ErkJggg==\"></p><p><span style=\"color: rgb(51, 51, 51);\">Implementasi atau penggunaan operator hubungan pada sintaks pemilihan adalah sebagai berikut:</span></p><p><img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAnwAAAE2CAYAAAD7xk/BAAAgAElEQVR4nOzdeXxU9bn48c+smSXbZN8TkhAChCXsCIiAKGhlF9G6a6u1inpvK/1d9dqq19pa9d5Lt2vtLSpWZVNBkE2wIhAIe4CwhYSEkH2dzL79/qA51wgqyDJDeN7/5JWTM2eemTmZ85znu6l8Pl9ApVIB0PlTCCGEEEJ0H+pgByCEEEIIIS4tSfiEEEIIIbo57Tf9we/309DQwLFjx7Db7ZczJiGEEEII8S1UKhVJSUnk5ORgNBq/c/9vTPiqqqp49dVX2bhxoyR8QgghhBAhRKVSkZKSwr333st99933neMwvjHh27t3L6tWraKsrOyiBymEEEIIIS5MeXk5cXFxTJkyhbi4uG/d9xsTPrvdjtvtVn5Xq9VotVoZySuEEEIIESR+vx+v10sgEMDv92O323G5XN/5uG9M+L4qIiKChx56iMGDB0vCJ4QQQggRJG1tbSxZsoR169ad1+POKeELCwvjuuuu46abbpKETwghhBAiSOrr69m3b995J3wyLYsQQgghRDcnCZ8QQgghRDcnCZ8QQgghRDcnCZ8QQgghRDcnCZ8QQgghRDcnCZ8QQgghRDcnCZ8QQgghRDd3TvPwXS2sViulpaW0tbUFO5SgM5lM5OXlERcXF5JzLwYCARwOB62trbS1tdHW1obb7cZoNBIdHU1UVBRRUVGEhYVdtpiam5s5cuQIVqv1sj1nqAsLCyMnJ4fU1NRghyKEEFc1Sfj+6dSpU/z617/m008/xePxBDucoNNqtQwfPpwXX3yR7OzsoMbi8/lob2+nvr6eo0ePsnPnTnbv3s2JEyfwer14PB48Hg9+vx+NRoNOp0On02EymcjOzmbIkCEMHDiQnJwcYmJiMJvNqNUXt7h95MgRXnjhBbZs2YLX672ox76SaTQa8vLyePrppxkzZkywwxFCiKuWJHycrhZVVVXx2WefUVZWFuxwQobP52PHjh1BS/i8Xi/l5eVs3ryZzZs3s2vXLqqrq3E4HDgcju9MzFUqFXv27OHTTz8lPDycrKwshg0bxpgxYxgxYgSJiYkXrXpZWlrKqlWraG5uvijH605qamoYO3asJHxCCBFEkvD9k8PhOKfFh68mbrebjo6OoDx3XV0d77//Ph9//DElJSW0trbi8/kIBALnfIxAIIDL5cLlctHa2sqpU6coLi5m8eLFDB48mNmzZ3PzzTcTGRl5wfE6HI6gvVehzul0SjO3EEIEmSR8ZxEREcG0adO4+eabgx3KZbd//35eeeUVJfk9nwTrQgUCAerq6li3bh0LFixgz549tLa24vf7gdPNzOHh4VgsFlJTU+nRowfx8fHExsYSExODwWDAarXS3NxMU1MTtbW1HD9+nLq6OlpbW7Hb7bhcLqqqqpTkb/ny5dx///0MHz6ciIiIi1LxM5lM3HXXXYwbN+6Cj3WlKi0t5fe//z1NTU3A5T2PhBBCnEkSvrMwGo0MHz6c6dOnBzuUyyoQCBAVFcXrr79+2audbrebPXv28Oabb7J69WpqamqUvnB6vZ78/HxGjBjBwIED6devHxkZGZhMJrRaLRqNBo1Gg1qtxu/34/V68fl8eL1erFYrx44dY9++fezevZuioiJOnDiBz+fj1KlTfPTRR+zZs4dZs2Zx1113kZeXd8GvJTo6mrFjx151589Xpaens2zZMiXhE0IIEVzdNuHz+/00NzdTVVWFWq0mJSWF+Pj4c3qsSqVCp9Oh1+svcZShR6fTXfbndLlcrFu3jl/96lfs378fl8tFIBBAq9XSq1cv7rrrLsaPH0/Pnj0xm81Kcncu4uPjycrKYty4cbS0tFBSUsLy5ctZtGgRtbW1OJ1ODh8+zPz58zl8+DBPP/00AwYMuKDXo9FoCAsLuyrPn056vR6NRnNRjuXxeKiurqapqQmz2UxmZiZGo/GiHFsIIa4Wlzzhs9vtNDc34/F4CAsLU5rezsbj8XD06FGKioo4dOgQjY2NREVFMXToUCZOnHjOCRtAeXk5v/zlLykqKkKlUnHdddfx6quvEhERcbFemrgIPB4Pa9eu5YUXXmDXrl34/X60Wi1paWnMmjWLOXPmkJ+fj9ls/t7PoVarUavVJCQkMG7cOAoLC5kyZQpvv/02a9asob6+nra2NlasWIHD4eDZZ59l8ODBFy1hERfm888/59e//jWVlZWYTCYefPBBHnjggQs6J4QQ4mpzSRM+u93O3//+d5YuXUpLSwvJycnccccdTJ8+Ha2261PbbDbWrFnDH/7wB0pKSnA4HHi9XjQaDYsXL+a1117j1ltvPec+Vps3b2bjxo1UV1djMBjQaDRSFQgxHo+HTZs28Zvf/IY9e/bg9/sxmUyMHz+ehx56iJEjRxIdHX1REy+1Wk1MTAxjx44lLy+PUaNG8cYbb7B3716cTicbNmzAZDLxzDPP0K9fv4v2vOL7i4mJoaOjg7KyMtRqNcuXL2fy5Mn07Nkz2KEJIcQV45ImfJWVlXzwwQds2LCBQCCgNJP+4Ac/6JLwBQIBSktLefHFF9m7d6/SSb+TzWajsbFRmWftu7S3t7Nhwwbq6uqA0xeMa6+99owkUwSP3+9nz549PPvss2zfvl1J7qdNm8ZTTz1FQUHBJa2wdVYR77rrLnr27Mkvf/lLNm/ejN1uZ9WqVURGRvLCCy+QlJR0yWIQ5yY3N5cBAwawd+9e3G43paWlfPHFF5LwCSHEebikS6vZ7XasVit+v59AIIDX66Wjo+OMEXs2m40NGzZQWlqqJHsmk4mBAwcyZswYCgoKiIuLO+d+W9u3b2fr1q1Kp/+ePXsycODAi/vixAWpqKjg97//vZLsGQwGpk2bxrx58y55stdJpVJhNBoZPXo0//Zv/8aQIUNQq9V0dHSwZMkS/vznP9PS0nLJ4xDfzmw2M3r0aKKiogCor69n7dq1MuehEEKch0ua8CUlJZGfn68sbxUdHc3AgQPPqLTZ7XYOHDiA2+0GTnd6nzhxIgsWLOC9995j8eLFjB8//pyac202G1u2bKG8vBw4fVEfNGgQiYmJF/nVie/L6XSyePFiVq9ejdfrJSwsjOuvv55nnnmGPn36XPa+czqdjjFjxjBv3jz69u2LSqWira2NhQsXsnr1auW8FMGh0Wjo378/aWlpwOkJuffu3cvOnTuDHJkQQlw5LmkbZ1JSEvPmzWPSpElYrVYSEhIoLCw8YySox+Ohvr5eqfyZzWaGDx9O//79UalUBAKBc+67V11dzebNm5VVGPR6PQUFBUp1QATftm3bWLhwIQ0NDQD07t2buXPnMmDAgKCt22symZg0aRItLS388pe/pKqqioqKCt555x2GDRtGTk5OUOISp2/aEhISKCgoYPfu3QCcOHGC4uJirrvuuqCMLBdCiCvNJa3wqdVqevfuza233sq9997LLbfcQkZGxhkXdY/HQ1tbm5LwhYWFER0drex3rkmA3++nvLyc4uJiZVtGRgbZ2dky4jJEVFdX89Zbb3H48GFl3r97772XkSNHBi3Z62Q0GpkyZQozZszAZDLh8/koLi5m2bJlsj5ukFksFgYMGKB063A6nezZs4eampogRyaEEFeGS1rhCwQCHDx4kL179+JwOIiOjqawsJAePXoApy/+27dvp7q6Wqn2wOlJeHfv3s0HH3ygLL7er1+/70wI7HY7+/fvp7W1VdnWs2dPMjMzL80LFOfF4/Gwbds2PvnkEzweDzqdjkmTJjFt2rSQmWIjJiaG2267TekH2tzczIoVK7jxxhvp379/sMO7ahmNRvLy8oiJiaGxsRE4vSpMVVUVGRkZQY5OCCFC3yVN+BwOB3/7299YsGABbrebmJgYHnvsMebOnYvP52PdunU899xz2Gw22tvblcdZrVbef/99PvroI9RqNbNnz+bFF1/8zjVP7XY7R44c6TIoJC0tTUZahoiWlhbWrl2rXLB79OjBPffcQ3p6etCre53UajX9+/dn1qxZ7Ny5U7n5WLduHb1795bmwyBRqVQkJiaSlpamnD81NTVUV1fj9/vPeUCXEEJcrS7pt6TX66WhoYGmpiasVitNTU00NjYSCATw+Xw0NjZSV1dHc3NzlyYzv9+P1WqloaGBuro66urqzmmpL7vdTkVFhfK70WgkJSXlGyd6DkVWq5UjR47Q3Nzc7dYfraqqori4mEAgQFhYGMOHD2fs2LEhd7E2mUyMGzeOwYMHA9DR0cHWrVuprq4OcmTnpvPGp66u7owpjq5kMTExpKamKr+73W4qKysv+zKAQghxJQralVar1ZKamkpiYiLR0dFdRu6qVCrMZjMxMTEkJiaSlZV1Tk1+LS0t1NbWKr9HRUWFVPXo69xuN+vXr+fjjz9WmqGLioq4//77lWbP83Hs2DHeeecd9u/fH5IX+gMHDiifT3R0NNdeey0mkynIUZ1JpVKRl5fH6NGjleXRSkpKqKysDHJkZwoEAhQVFbFkyRJl3smDBw9y33338dZbb9HR0XFex6uuruZvf/sbRUVFITc6OSYmhpSUFOV3r9fLiRMnJOETQohzELSZiPV6PRMnTiQ1NZXKykpeeuklDh06BJxOBu6++25uvvlmtFrtOa+d2dDQgM1mU343m80hPR1Lc3Mzf/jDH6ivryclJYWhQ4fS1tbG0aNHaWpqOq+kzePxsHHjRp577jkef/xxcnNzQ66yeezYMdra2gCIjY0N6bkRzWYzAwYMIC4ujlOnTlFXV0dVVRVerzekJvB2Op0sXLiQTZs28bvf/Y6JEydis9k4fPgwdXV15zXYxOfzsWPHDp588knuvvtucnJyzms5w0stMjKySzx+v5/a2tqQS0yFECIUBe3KpVKpiI+PZ+zYsRw/frzLtCl6vZ4+ffowceLE8zqmzWbrUhULCwsLmcEAZxMZGcmsWbPo6OjoMrAkEAicd3OuVqtlyJAhPProo4wZMybk+pr5fD5qampwOBwApKamYrFYghzVt8vMzFQSPq/XS01NDR6PJ6QSvrCwMCZPnkxeXh69evXq8rfzPYc6R9U/8cQTDBs2LOTWndZqtRiNRjQaDT6fD7/fT0dHR0hWs4UQItSEzpXrIrDZbF0qGjqdLuhNhoFAAJfLhVarPSNRMBqNzJgxA7/ff04VzEAggNPpxOv1Yjabu/R9U6lUFBQUkJubS1hYWMhNQ+NyubDZbMrFOTY2VpmQO1RZLBbCw8OB/+tX6vP5LnscgUAAt9uNSqVSmpg7qdVqJkyYwHXXXXfOFV2Xy4Xb7cZkMnU5T1QqFdnZ2fzLv/wLYWFhZzxXKAgLC0On0+Hz+QgEAtjt9qB8JkIIcaXpVgmfw+Ho8uWv0+nOKZG6mKqqqvj9739Pv379KCws5P3332ffvn3ExcUxffp0brrppi5zif31r3+lpaWFhx56iISEhLMe0+12s3fvXpYuXUppaSkul4vExESmT5/O5MmTlcRp165dvP3220yfPp1x48aFVNIXCAS6VGJ0Ol3IDdb4Op1O1+U9vFyJRVtbG//zP/9DeHg4N910E0uXLmXz5s0YDAZuvvlmZs2a1SVZ/uijjygpKeFHP/oRWVlZZz2mz+fj0KFDLFmyhL1792K324mMjGTy5MlMnz6d6OhoAI4cOcKrr77KDTfcwJQpUy77/8936Uz4nE4ngUDgjP95IYQQZ9etEr6vD87w+/2Xvbmnra2N1atXs2PHDj788EPq6+vR6XSUlpaya9cu3G43U6dORaPR4PF42Lx5M3V1ddx2221nTfgCgQAlJSU899xzdHR0kJycjNlsZt++fezfvx+Hw8GcOXNQqVRUVFTw8ccf07dvX6699tqQSviuRMEa7ON0Ovniiy9obm5m69atHD9+HKPRyKFDh9i7dy82m437779fqRjv2rWLjRs3Mm3atG9M+Kqqqvjtb3/LsWPHSEpKIi4ujqNHj/LKK6/Q1tbG3LlzUavV1NbWsnTpUhITE5k0aVLIJXxf7+6gUqlCdlCWEEKEkm6V8BkMhi5JjtfrVfqMXS6dU86UlJRw++238//+3/8jOTmZVatW8fzzz7N69WpGjx6tJHedTVPf1t8qLi6Ou+66i4KCApKSklCpVBQVFfH000+zdu1apkyZgtlsxu/3K8cLNV+/MHu93pCM86s8Hk+X6tHlrEj6/X4OHDhATk4O//Ef/0GvXr3Yvn07//7v/86qVauYNGmSMuFw543Nt72f4eHhTJs2jczMTNLS0lCr1ZSVlTFv3jzWrVvHvffeS3R0dJdzKBQ/H5fLpfTTValUGAyGkK8UCyFEKOhWCZ/JZOrST87j8Vz2hK9TYWEhDz74IH379kWtVjNq1CiysrKorKykubn5G5tvv06lUpGRkaFcpDuTpqFDh5KcnExtbS3Nzc0hPTgFTifjJpMJtVqN3++npaUl5KfTaG1txW63A6c/h/Dw8MtaNc3Ly+Phhx9mxIgRaDQaRowYQe/evTl+/Dg1NTXntcJEbGwsU6dO7ZJ4WywWevbsyf79+6mvr1eadUOZ0+nskvB9vR+iEEKIs+tWCZ/ZbO4yOtXlcmG1WoMSS2xsLLGxsUr1wWg0EhMTQ3Nz83knOoFAgJaWFg4dOsThw4epra2lqamJsrIysrKyznu+vmBQq9UkJSVhMBiw2+2cPHmSlpaWYIf1rSorK5VVHXQ6HcnJyZd19LPFYiEpKUlJaHQ6HTExMRw8eFBJRM9He3s7R48e5eDBg9TU1GC1Wtm9ezcqleqKmNrE7XZjt9uVbhpqtZrw8HCp8AkhxDnoVglfQkJCl1G5Vqu1y0TMl9PX+xWpVCo0Gs159ykMBAIcP36c+fPnU1xcTFZWFomJiUqTaKg2vZ1Nbm4ukZGR2O12GhsbKSkpUVazCDUOh4OSkhJljef4+HjS09ODOiVL5zn0fT7zuro6/vKXv7By5UpSU1NJS0tDr9fj9/uVY4a6trY2ZXJp+L+biFAcTSyEEKGmWyV8FouFxMRESkpKgNMXiKqqKgKBwBXbsbtzNY7ly5dz55138sADDxATE0NbWxvHjx+/IioznQoKCoiPj6e2tpaWlha++OILfvjDH160qllZWRnvv/8+EyZMYMSIERd0rGPHjvHll18q1dg+ffqQnp5+McIMim3btrFkyRJGjhzJv/7rvxIfH49Op6O9vZ09e/YEO7xz0tLSQk1NjfK7VqslIyMj5Kf3EUKIUNCt2kJMJlOXUYput5vq6urzXl4qlHg8HioqKlCr1fTt25fMzEzCw8Npb2/HarVeEZWZThkZGQwbNgw43dy+bds2vvjii4vyGgKBAI2NjWzYsOGCl0Cz2+18/vnn7NixAzjdVWDkyJGkpaVdcJzB0rnmbJ8+fcjNzSUqKgqbzUZra+sVcw41NTV1Wc9Yp9ORkZEhFT4hhDgH3arCZzKZzlhtoKqqipqampBbNeBc6XQ60tPT6ejo4KOPPkKr1eJ0Olm1ahVHjx6loKAg2CGeM4vFwsSJE1m2bBktLS2UlZXxzjvvkJ+fT2pq6gUfPxAIXPDo30AgQGlpKUuWLMFutysTWk+cOPGKriSlpaURCARYuXKlMmBo48aNFBUVkZSUFOTovlvnMmpVVVXKtuTkZFJSUmTQhhBCnINLWuHT6/VER0crTXadnc6/3ryq1+uxWCzKdpPJRGxs7Hk/n8lkoqCgoMtowyNHjnDixIkLeBXnR61Wo9VqUavVZ6yEodFouoy0Bc7YV61Wo9Fo0Gg0ysoKkyZNYtq0aaxfv565c+fywgsvEBERwejRo7tMRfPV5w7FJmy9Xs8111zD5MmTgdNVvuXLl7Ny5UqcTmeQozuto6ODRYsWsXPnTgCioqK46aab6N+//2WNo/Nc+fo5dLZz6+v7fv0cArjmmmuYPXs2u3fv5oknnuDZZ5/F7XZzww03EBUVpfRNDNVzyG63c+jQIWUtZoC+ffue10hlIYS4ml3SCl9YWBhPPfUUc+bMweVyER4eTmZm5hkd3xMTE5k/fz41NTX4/X4sFss3TiD7bdRqNT169GDIkCGsX78egJqaGo4dO8bYsWMvS9NPdnY2CxcuxGg0EhcXp2xPTk7m17/+NW63mx49egCnmwpfeOEFPB6PcuEaN24cq1atIiUlBb1ej0qlIisri+eff57777+ftrY24uPjSU1Nxel04nQ6SUlJAWDixImsWLGClJSUkFrv9atSUlK4++672bNnD6WlpbS0tPC3v/2NvLw8xo4dG9Qkw+l08tFHH7F06VLsdjsajYahQ4cya9asyzo6NyYmhtdeew2/39+l8hkREcGTTz7J/fffr5xDAI899hh33323sq2wsJDVq1cTGxtLZGQkcHrQyZNPPsn06dNpbGwkOjqajIwMAoEA7e3tylrOQ4cO5bPPPiMhIUFZVi4UNDc3d+lraDAYKCwsJDk5OYhRCSHEleOSZgUqlYrU1FSSk5MJBALfWDXQ6XTk5uaSnZ39rfudi7S0NEaPHs0//vEPPB4PXq+X/fv3K4nSpWY0Gunbty/QdaSuXq8nJyeny3aNRkN2dnaXbRaLhejo6C6P1Wg0JCYmEh8fr4yq7Pz7VwekxMTEdKmUhiKNRsPo0aOZM2cOr7/+Oi0tLezdu5f58+eTmJhI7969v9dxVSoVSUlJ3HrrreTl5Z33410uFxs3buQ///M/qaioIBAIkJqayg9/+EPlc7tcOv8fgDPOg84k7avbU1NTSU1NVbaFh4czcODALo9Xq9XK+eHz+bpUBDsn84bTSWVhYeEZzx1MgUCAuro6Dhw4oGzLyMhgyJAh0n9PCCHO0WUZtNHZxPRdF5Bz3e/bmM1mRo8erSRSgUCAHTt2dJnO4VL7puWezrb9m7adTWdz21f/fq6PDSVms5nbbruNCRMmAKenQFm9ejXPP/88x44d+97HzczM5OGHH2bAgAHn9Ti/309xcTEvvfQSe/bswefzYTKZuO2227jllluC0nfv25YMO9dz6JvOwc4m2/M5XjB5vV52796tjNDVaDQMGDCA4cOHBzkyIYS4cnSrUbqdhgwZwqhRo5S7/6qqKoqLi4Mclfiq7OxsHn30UYYPH45Go8Fut7N8+XJefvllDhw48L0GXpwtmfkuLpeLzZs389JLL7F9+3b8fj8mk4kZM2bwyCOPYLFYzjsOcXF1dHSwefNmZRL1pKQkJk+eTFRUVJAjE0KIK0e3TPgiIyOZOHGiMhqxubmZTZs2XVFz1nV3Wq2W4cOH89xzz1FYWKgkfUuWLOHZZ59l/fr132s1ifPR2NjI3//+d37xi1+wceNG3G43Op2OG264gSeeeIKMjIyQqnRdrUpLSykpKcHj8aDRaCgoKGDMmDHy2QghxHnolgmfSqXimmuuYcKECRgMBlQqFTabLWjr6oqzMxgMXH/99fziF7+gZ8+ewOnJslesWMFPfvITfv3rX1NRUXHOx6uqquLNN99UJt7+Jn6/n927dzNv3jyefvpptm7ditPpVM6bn//85wwYMECW7AoRbW1tuN1uNBoNSUlJTJ8+/aJM4yOEEFeT0BzKeRGkpKTw0ksv8a//+q/A6ek1QmnUoTits6Lm9Xr5zW9+w4EDB3C73ZSVlTF//nw2bNjA9OnTmTBhAtnZ2d/YjBcIBKitrWXp0qVYLBb69evX5e8+n4/m5mZKS0tZsWIFq1atory8XLkJiIiIYMKECTz11FMMGTIkZEc5X41Gjx7NsmXLcDqd6PV6kpOTMRgMwQ5LCCGuKN32qqbVaklJSVGmLBGhKzw8nFtuuYWUlBT++te/8sknn9DU1ERbWxvbtm3jwIEDLFq0iOHDh1NYWEh+fj49e/YkLi6uS7Oez+fDbrfj9XqB0539a2trOXToEKWlpezcuZPt27dTVVWFzWZT+glmZGRw++23c+edd5Kfny/JXoiJiIi4YidOF0KIUCFXtrNob29n/fr1XebRu1rs27dPSZguF5VKhclkYvTo0eTk5DB27Fjmz5/P3r178fl8tLW1sWPHDnbt2kV4eDhJSUkkJSWRmppKQkICCQkJxMXFUVNTQ21tLYsWLWLTpk3U1tZSXV1NbW0tDQ0N2O32LoNBTCYTEyZM4JFHHmHEiBFERUVdlH5hDQ0NrF279oKPcyXbt28fx48fD3YYQggh/kkSvrNwOp2sXLmSL7/8MtihXHZutztog1tUKhUpKSnMmTOHESNGsHLlSpYvX87BgwdpaWlRkr+2tjaOHDmCRqNBr9ej1+vRarX4/X6sVquy/Jbb7cbn83V5Dp1OR0JCAgMHDmTmzJmMHz+e1NTUi1rVczqdvPfeeyxfvvyiHfNK43Q6aW9vD3YYQggh/kkSvn8yGAzKRT8QCGC32y/5KNFQp9VqMZlMl/15jUYj+fn5pKenc9NNN7Flyxa2bt3Kzp07OXz4ME6nU1k31+v1nvE5eTyeLr+rVCqioqIoKChQpuwZOnQoiYmJhIWFXZSqnl6vx2AwKMlye3u7JDz/pNfrg3IeCSGE+D+S8HE6IUhPT2f06NGUlZWdURW6Gmm1Wvr168fQoUOD8vwqlYrw8HD69OlDfn4+M2bMoLq6muPHj7Nr1y527tzJkSNHqK6uxuFwdGmqValUREZGkpmZSX5+PkOGDGHAgAH06NGD5ORkTCbTRR+BW1BQwNixY/n0008ve5N4KFOr1fTv359x48YFOxQhhLiqScL3T0lJSTz//PPcdddd2Gy2YIcTdAaDgaysrO+1pvHF1rksWExMDH369GHcuHFYrVbsdjtOp1Opxno8HsLCwjCZTJhMJoxGIyaTifDw8EuS5H1VdnY2//3f/015eflVXxn+Kr1eT1pamrLyjRBCiOCQhO+fNBoNKSkpJCUl4ff7gx1O0HWutRpqk9tqNBoiIyOJjIxUtvn9fgKBgLLGbDDi1mq1ZGZmkp6eLufPV6hUqgteLlEIIcSFk4TvKzovThqNJtihiPPQWbmrr69n27Zt9PjhfWEAACAASURBVOnTh5ycnMseh5w/QgghQpUsJSC6hUAgcM4rbQghhBBXG0n4RLfh8XhobW3F5XIFOxQhhBAipEjCJ4QQQgjRzUnCJ4QQQgjRzUnCJ7oFlUqFxWJhxIgRJCcnBzscIYQQIqTIKF3RbfTo0YOf/exnmM3mYIcihBBChBRJ+ES3odfriY+PD3YYQgghRMiRJl0hhBBCiG5OEj7RbbS2trJ9+3Zqa2uDHYoQQggRUiThE91CIBDg+PHj/Pa3v2X79u3BDkcIIYQIKZLwiW7D7XbT0NCAw+EIdihCCCFESJGETwghhBCim5OETwghhBCim5OET3Qb4eHh5OfnExMTE+xQhBBCiJAi8/CJbkGlUpGbm8szzzxDdHR0sMMRQgghQookfKLbMBgMpKenBzsMIYQQIuRIk64QQgghRDcnCZ/oNpxOJ5WVlbS3twc7FCGEECKkSMInuoVAIMChQ4eYN28eX3zxRbDDEUIIIUKKJHyi23A6nZw6dQqbzRbsUIQQQoiQIgmfEEIIIUQ3JwmfEEIIIUQ3Jwmf6DbCwsJISkrCZDIFOxQhhBAipMg8fKJbUKlU5OXl8eKLLxIXFxfscIQQQoiQIgmf6DbMZjM9e/YMdhhCCCFEyJEmXSGEEEKIbk4SPtFt+P1+XC4XPp8v2KEIIYQQIUUSPtFt7N+/nx//+MesXbs22KEIIYQQIUUSPtEtBAIBHA4HJ06coK2tLdjhCCGEECFFEj7RbahUKgKBQLDDEEIIIUKOJHyi25GkTwghhOhKEj5xxWlsbGT9+vXU19cr21QqFWq1Gp1Oh1rd9bRuaWnhs88+o6Ki4nKHKoQQQoQESfjEFae2tpbXXnuNd999F7fbrWzv1asXr7/+OuPHj1e2+Xw+Nm7cyOuvv86RI0eCEa4QQggRdJLwiStOSkoKw4YNY+nSpRQXF+P3+wGIiIigX79+xMfHK/tWV1fz8ccfk56ezpAhQ4IVshBCCBFUkvCJK050dDRTp07FbDazbNkyWltbz7qfy+Vi5cqVVFdXc+utt2KxWC5zpEIIIURokIRPXHHUajUFBQXcdttt7Ny5k+3btwNdJ14OBAKUlJTw97//neHDhzN48GBUKlWQIxdCCCGCQxI+cUXS6XRMnjyZ3NxclixZQn19PUePHuWpp55i48aNNDU1sXjxYrRaLVOnTiUyMjLYIQshhBBBIwmfuGIlJCQwZcoUjhw5wkcffURTUxP79u2jrq6O7du3s23bNmbOnEm/fv2kuieEEOKqJgmfuGJpNBpGjhzJkCFDePfddzl48CA+n4/m5mY+/PBDUlNTue222zAajcEOVQghhAgqSfjEFS02NpaZM2fi9/v5+OOPaWpqYtWqVVRUVHDrrbcSFxcX7BCFEEKIoJOET1zR1Go1AwcOZNasWZSUlFBeXs7WrVspKChg1KhR0pQrhBBCIAmf6AbMZjMzZsygf//+uN1uMjIymDZtGrGxscEOTQghhAgJ2mAHIMTFkJyczOzZsykvL2fmzJkMHjz4jCXWhBBCiKuVJHyiW9BqtYwbNw6NRsOIESMIDw8PdkhCCCFEyJCET3QbycnJzJgxA71eH+xQhPhODoeD+vp64uLiMJlM0t9UCHFJScInug21Wk1YWFiwwxDinFRWVvLb3/4Wn8/HnDlzGD58uCz/J4S4ZKSTkxBCBEFqaiozZ84kEAjwq1/9ihdffJG9e/fi8/mCHZoQohuSCp/owuv14nK58Pv9qNVq9Ho9Op0u2GF9bz6fj61bt9Le3s5NN910Xo/1er1s3rwZh8PBpEmTLlGE4moVHh7OjTfeyKBBg/jkk0946623+PLLL7nrrru49dZbiY+Pl4FHQoiLRhI+oaiqqmLVqlXs2bMHl8uFRqMhNzeXWbNm0aNHj8t28fF4PJSVlREWFkZGRgYajeZ7H8vv97Nz505qa2u/V8K3fft2WltbJeETl4RGoyEpKYk77riDQYMGsWzZMj788EO2bNnCrFmzGD16NPHx8VdN/75AIIBKpaKlpYW2tjbS0tLQai/OZcrn81FbWwucrq6eD6/XS21tLSqV6rwfG0q8Xi81NTVEREQQHR19wcez2WzU1taSkJBARETERYjwtKamJjo6OkhPT7+g607n+WS1WmloaCA5Ofk7V17qfEx3JLePAgC73c57773HP/7xD8aNG8c999zDhAkTKC4u5o9//CMNDQ2XLRabzca7777LypUrcbvdF3SsQCCAy+XC6XR+r8e63W5cLtcFxSDEdzGZTAwcOJCf//znPP3008TExPDCCy/wzDPPsGnTJvx+/wUdv7y8nLfeeovPPvvsjP8Fj8fDli1beOuttygvL7+g57kQ27dv56233qK9vZ3i4mLeeustrFbrRTu+3W5XEurzZbPZWLx4MR9//PFFiycYrFYrCxcupLi4+KIc7/jx4/zhD3/gyJEjF+V4nbZs2cLChQsv6Lu3tLSUN954g8rKSg4fPswbb7zByZMnv/UxGzZs4L333rvg/7dQJRU+AcCePXv4/PPPuffee5k5cyYajQav14tWq+XPf/4zhw4dwmazsWvXLiIjI9m8eTMqlYrJkyczZMgQNBoNNpuNLVu28I9//IOwsDAmTJjAsGHDaGpqYv369RgMBvbv3092djYzZsygvLyclStXUlNTQ3p6OtOmTSM+Pp5PPvmENWvWEBERgd1u5wc/+AE5OTns27ePVatWYbPZKCgo4Ac/+AEWi4Wamho2btxIWFgYe/fupV+/fkybNq3LaF273c7q1av54osvyMrKYvr06cTHx1NVVcVnn33G6NGjyc3NpaOjgzVr1pCXl0dubi6BQICOjg4++ugjtm7dSnZ2NrfccgthYWGsXbuW7Oxshg8fjtfrZd26dYSFhTFmzBgOHTrEsWPHiIyM5PPPP8disTBjxgyysrLw+/0cO3aMFStWcPLkSfR6PRaLhVtuuYXMzEw2bdrEpk2bcDgcjBw5khtuuIHo6Gh2797NiRMniIiIYOPGjcTHxzNz5kzS0tIu6bnh9Xo5deoUTU1NXbYnJCSQlJSERqPB5/NRX1+vVFA6xcTEkJqailarxe/309TUdMaXblRUFOnp6eh0OgKBAC0tLZw4caLLPmazmaysLOUzbWtro7KyEq/Xq+xjNBrJysrCYDAA0NHRQWVlZZeLhsFgID09XZm2x+FwUFVVhc1mU/bR6/WkpqYqFRC3283Jkydpa2tT9tFqtSQlJREfHw+crh6dPHmS5uZmZR+1Wk1CQgLJycnKtpMnT55x8xQXF6dUMqKiosjPz2fatGlERUXxwQcfsGHDBm655RYef/xxMjIyzrviEQgE2LFjB6+88grp6elER0czePBg5e/Hjh3jtdde4+jRo4SHh9OjR4/zOv7F4nQ6aW1txe/309zczIkTJ7p8vhfK5/NRXV39vSpGXq+XkydPXvHrcrvdbsrLy8nKyroox+vo6KCsrOyiJuZwusJ34sSJC0q8PB4Pzc3NeL1e2tvbKS8vx+FwfOtjbDYbbW1t3bbCJwmfAE5XAAKBAL1791aaULVaLf369SMuLo6qqioAFixYQGxsLIMGDaKyspL58+czb948cnJyWLx4MevWrWP06NGcOnWKl19+mccff5zExESWLFmCw+Fg0KBBREZGYrVa2bVrF2FhYfTr14+ioiJ+97vfMW/ePCIjIzEajYSHhxMXF4fBYODzzz9n4cKF5Ofnk5aWxrp169izZw/z5s2joaGBDz74AJ/PR2FhIeHh4QQCAeW1+Xw+du7cSUREBBaLhU8++YSWlhbmzp1LbW0tK1asIDMzk9zcXGw2G59//jkqlYrc3Fx8Ph/FxcVER0cTFxfHunXrKC8vZ8aMGaxZs4YxY8YoCd/WrVsJDw9n5MiRHDp0iDfffJPc3FyysrLYuXMnNTU1/Pu//zuNjY3813/9F+Hh4WRmZvLxxx+TmZnJjBkzOHHiBAcOHKBHjx44nU4WL16MSqVixowZHDhwgLfffpvevXuTkpLC1q1bqa2t5emnn76k8w52dHSwdOlSPvnkE2WbSqVi9uzZ3HHHHYSHh+NwOPj000959913lX3UajU33ngjDz74INHR0Xg8Hr744gv++Mc/dtln5MiRzJ07V1n3ePfu3bz00ktdnqtv374888wzSoJVWlrKb37zG9rb25X9cnJyePrpp8nMzAROn9OvvfYalZWVyj4ZGRk88cQTDBgwAIBTp07xhz/8gf379yv7JCUl8eMf/5ixY8cC0NLSwt/+9je2bNmi7GOxWLj77ruZMmUKAC6Xi/fff5+1a9cq+xiNRm699VbuueceZdvHH3/MRx991OVCNmXKFObOnatcZNavX8+iRYtobm6mpaWF5uZm3nnnHaKionjssce+1woyDoeDmJgYtFotRUVF9O3bF4PBgMvlYvv27bS3t5OUlKRU/6xWK+Xl5VitVpKSksjIyECn0+F2u6mpqUGn09HR0UFTUxNpaWnExsZSXl5OW1sbWVlZJCUloVarlST/+PHjqFQq0tPTSU5OxuVyUVNTg1qtpqWlBZ1OR1ZWFhEREWckVS6Xi6qqKkwmEykpKUqS0RlzdnY2Xq+XqqoqJbasrCwSExPPeuH2+XycOHGCmpoa4uLiyMzMRKfT0d7eTn19PSkpKZhMJhwOB6dOnVLOuc7HlpWVUV9fT3x8PBkZGcpzx8fHExMTg9/vp6qqCqPRSEJCAg0NDTidTnQ6nXLDlpub2+Xm5fjx49hsNnQ6nXLjYjKZOHnyJKdOnSIQCJCZmUlycjJqtZr6+no8Hg9qtZqqqiqioqLIzs4+65RUdrud8vJyOjo6MBgMyndjc3MzbW1tpKamotfrsVqt1NTUkJaWhtFopKWlhfLycux2OzExMWRnZ5814Q0EArS3t7Nz5058Ph9ZWVnEx8fj9/upqakBIC0tjUAgQF1dHXa7XbnBqa2tpaqqCq/XS2pqKmlpaUqf8UAgQH19PQ0NDZhMJnJycro8v9frpa6uDpVKhdvtpra2VvlMdDodKSkpTJw4kdjYWCoqKs74f6isrKShoYGwsDAl5oKCAjIzMyXhE92X3++nra0NjUajVEc6hYeHYzQasVqteL1e/H4/U6dO5cYbb6SiooLnn3+eL7/8EovFwqZNmxg0aBC33HILdXV1HD58mKKiIiZMmEBLSwvjx4/n4YcfJioqCo1Gw9SpU5Wqjtls5s9//jOtra0MGzaM3r17k5yczLRp0zCZTPz1r38lNTWVxx57DLVaTXp6Oq+99hqlpaVERUXR3t7OzTffzP333094eHiXLz6VSkXPnj155JFHiIqKQq/Xs2PHDhobG/F6vdjtdmVkpN/vx+l04vF4lMf27t2bn/zkJ8TExJCYmMjbb79NYWEhDodD2e+rzb+BQACPx4PZbOaee+4hPz+fTz75hA8++ICTJ08qF9Mnn3ySAQMGUFtbi8vlIj4+HqPRyIMPPkhYWBhut5vKykoOHTqE1+vF7XYTGRnJAw88QGZmJsuWLWPZsmWcOnWKvLy8S3Z+mEwmJk2aREFBQZftmZmZyvliMBgYO3Ys6enpXfbpvHjC6RuIIUOG8Itf/KLLPvHx8V36//Tp0+eMfaKjo7vsk5OTw+OPP668/wARERFK0ginLzI/+tGPulTvzGYzGRkZyu8JCQnceeedtLa2KtsMBkOX9zMqKoqZM2dy7bXXKtv0ej05OTldfr/55psZNGiQsk2j0SjJZ6frr7+eXr16dbkhSUtL63KBGT16NGazmeXLl1NWVkbfvn2ZM2cOU6dOJSoqiu8rLS2Nfv36sWvXLqZOnUpaWhoNDQ0UFxczbNgw5eLc1tbGwoUL2b9/P1qtFpvNxuzZs5k0aRItLS288847nDhxAp1OR319PeHh4fTs2ZMTJ07Q2tpKeno6//Iv/0JKSgqHDx9mwYIFWK1WXC4XZrOZhx9+mOjoaBYsWMDx48fxer3069ePnj17UlJS0uU98/v9bNiwgdWrV3PHHXdgsVhYsmQJW7duJTY2lqioKB588EH27t3LihUrUKvVNDc3k5yczNy5c0lKSuryHvj9frZv347dbqe5uRmXy8XcuXOVqvyiRYt44IEH6N27NzU1Nbz55ptMnz6dnJwcfD4fmzdvxmq10t7ejs1m48EHHyQzM5P58+czffp0brjhBtxuN++99x45OTnceuutfP7553z22WcYDAZaWlqw2WzccccdTJ8+nYaGBhYsWEBZWRler5ejR48yePBgfvrTn9La2sr777+Pz+fDarViMpn46U9/Sm5uLuvXr+eLL75Qjmm327nnnnv4wQ9+0OVcstlsLFq0iDVr1mAwGPD7/VRWVjJ+/Hh27NjBl19+yWOPPUZcXByHDx/mnXfe4eGHHyYmJoa3336b8vJyNBoN9fX1TJ06lZkzZ54x9VVnM7HFYqG1tZWcnBweffRRoqKi+PDDD1GpVDz66KP4fD4+++wzDh48yOOPP05DQwNvv/02TqcTh8OB3+/noYceYsiQIQQCAY4ePcrvfvc77HY7VquVGTNmMGfOHKVCa7PZWLp0KSUlJRgMBuXzfOKJJxg1ahTl5eUsXryYBx544Iz/hQ0bNrB27Vp0Oh0NDQ1kZ2fz5JNPsm3bNsrLy+nfv//3/j8LZZLwCVQqFWFhYXi93jOaUDqTmsjISFQqldK0ZjabiY+PJyoqitraWtra2jh8+DD79u1jw4YN+Hw+Tp06xcCBA/H7/eh0OvLy8khISABO350dO3aM9957j/Lyck6ePKkkSjqdDo1Gg06nIywsDKfTSXNzMwMHDiQyMhJAadpqamoiKioKg8FAr169zlr9UKvVSiXA5/ORlJSEzWbD5XJ9551cZ6f6zotQRkaGckf7Xe+pxWIhJyeHiIgIkpKScLvd2Gw2jEYjfr+ff/zjH9jtdo4ePcq1116L2WzG4/Gwdu1a1qxZQ0NDAydOnODmm29WOhLHxsYqd7qJiYk4HI7vbKa4UHq9nt69e9O7d+9v3Eer1ZKTk9MlCfq6zgTo60nQV6lUKpKTk7s0g55NfHw811133bfuY7FYuOaaa751n4iICIYOHfqt+xgMBgYOHPit+2i1WgoKCs5Iir+uV69e9OrV66x/6zz/Gxoa+PTTT9m+fTs333wzDz74IIWFhRfcnBgWFsaoUaPYv38/Bw8eJDU1ldLSUjo6Opg9e7ZSnd28eTNFRUXcd999pKen8/bbb7Ns2TJGjhyJ2+3m0KFDNDY28rOf/Qyn08nLL79Me3s7jz/+OF6vlzfeeIMdO3Zw4403smLFCmw2m3KBnz9/PkuXLmXWrFkcPHiQpqYmfvazn1FQUMCmTZuUag+crqZt2bKFv//970ycOJG+fftis9koKipSum34fD4iIiLIzs7mvvvuw2KxUFZWxp///Gd2797N5MmTu7wHPp8Pt9vNhAkTSE5OZv78+Xz66acMGDDgjGY/p9NJZWWl0lzp8/nw+XzcdNNNpKWl8Ze//IVFixYxe/Zsjh07ptw0dH73dSbnNTU1HDhwgIceeoiCggLeffddlixZwjXXXMORI0dYv349jz76KElJSbz88stERUUpLRs//OEPiYmJobW1lddee41t27aRk5NDdXU1Bw8e5Kc//Sl5eXksWLCADz/8kBEjRnSpSB44cID33nuPqVOnMn78eNavX09ZWRlwunJdWVmp3DR1dHRQUVGBzWYjLS2N66+/nvDwcDQaDQsXLmTFihWMHj26yw0TnG46TUtL4/7776empoY//elPbNiwgSlTpnDq1CklQfP7/TQ2NirPGRsby+zZs4mNjcXpdPLqq6+yadMmBgwYgN/vx+12M2DAAEaMGMHSpUtZvnw5Y8eOVQbNdFZbDx06xFNPPUV8fDz/+Z//ydq1a+nfv7/yes7Wfzs/P5+MjAyio6PZt28f//u//0tJSQmNjY1UV1d/33+xkCcJn0ClUpGWlobH46GiooJevXqhVqvxer2UlJTQ2tpKZmYmHo8Hr9er/AN5PB7cbjcRERHo9XoSEhIYO3Zsl9GwMTExVFdXo1KpuiRXJ0+e5H/+539ITU3lF7/4Bbt37+att95S/q5Wq/H5fAQCAXQ6HWq1uks/EYfDQSAQUKpHXz/+t71WlUpFIBAgEAgozdedX3oOh6PLQJHOip/L5UKv12O321GpVMrKCJ0VPZfLhcPhwGw2n/V5O7/0AoEAdrsdnU5HU1MTmzZtYvz48UyZMgWtVsuqVatYtGgRs2bNok+fPrz55ptn7XOkUqm6HFNc2dxuN6WlpSxfvpzPP/+c+Ph4nnvuOcaOHUt8fPxFG6man59Peno6X375JaNGjaK4uJjs7Gxyc3OB0xfR/fv3U11dzf79+6moqKClpYXa2lql+Uun03HNNdcwduxYamtrycnJoW/fvgwdOhS3243FYqGurg6Hw8HBgweVxK3z5qSqqoqOjg7UajXjxo1jwoQJ6PX6M0bjl5eX86c//Ylhw4Yxffp0zGYzfr+fpKQkioqKSEpKYtiwYWi1WhITE7Farezbt49Tp05htVppbGw84/VrtVqGDx+uJIL9+/fn8OHD2O3273zvtFotI0eO5Prrr0en0zFmzBjefffdLtXhs1Gr1eTn5zNz5kx0Oh2FhYXs3r2btrY2vF4vDocDjUZDZGSk0u3EYDBgMpno6OigtLSUlpYW2tvblX60arWavn37MnXqVLRaLQMHDuTDDz+kvb1dSfgCgQCVlZX4fD5GjRpF7969MZlM7Ny58ztfq9lsViq0TU1NNDU10dbWdtb3KTo6mhtuuIG+ffuSkpJCSkrKOQ3iiIuLw2azcfToUVpbW7FarTQ3NytTguXl5TFjxgwsFgvHjx+nqKiI5ubmLqOktVotw4YN44YbbiAQCNC/f39OnDjxnTfBiYmJHDt2jP3793P8+HFlFG93JwmfAKCwsJBevXqxYMECZeqB0tJSFixYQL9+/ejVqxcHDhygtraW999/H5PJxL59+2hqamLw4MFER0eTkZHB3r17ueGGG4iLi+P48ePodLqzJmJ2u51Tp05RWFiIxWLp0kE7LCwMs9nM0aNHKSsrIy0tjczMTLZt20ZRURGRkZF88sknxMfH07NnzwvqMGyxWAgPD2fbtm0kJSWxcuVKjh49qvy9swlo4cKF9O/fn08//VR53ri4OHbu3ElxcTF79uxhy5YtTJ069VufrzM5tFqtqNVqYmJilP5CXq+X+vp6WltbSUtLw263U1lZSZ8+fb736xOhr7GxkcWLF7Ns2TI8Hg+zZ89m4sSJZGZmXvRlAo1GozL9y5o1aygrK+P2229X+k35/X7sdjsajQatVotWq2XQoEFMmDCBuLg4rFYrKpUKo9GITqdTqvBGo1F5TOcgns5uCCaTCY1Gg9ls5pZbbiEnJwez2awkOd/0Go1GI1FRUVRVVSk3WuHh4dx1111s2LCBFStW8OWXX/Lkk09y4MABVqxYQY8ePdBoNPj9/rN2+O+MPSwsDJ/Ph9FoVLqqdH5PfdMNlFqtxmAwKPEajUaln+K3PU6lUqHX65XKvsFgwOv14vP5MBgMeDwefv/73xMZGYnJZGLUqFHo9XqKiopYuHAhycnJxMXFdXlNna0yncc0Go14PJ4uk3b7/X4cDgdarbZL14vO+L964/t1tbW1/OlPf6K1tZVevXopA5/O9p52dgVSqVRoNBrlvf3qc5zN/v37eeONN4iNjSUtLQ2v16vs+9X3rPN976ywfv29NRgMZ3ye33UTvHr1atavX09mZiaBQOAbz5fuRhI+AZxuInvkkUf4y1/+wksvvaRUz0aNGsV9992n9I0yGo3U1NTw5JNPolKpmDp1KsOHDycsLIw777yT+fPn89Of/hSdTkdkZCRPPPEEMTExWCyWLn0/kpKSGDlyJAsWLGDNmjVER0fTq1cvdDodJpOJMWPG8Morr/DCCy8wd+5cpk+fTm1tLT//+c/R6XRkZGTws5/9jKysLEpLS4mOjj7rsmqdzdBf7f9lMBiIiopCq9WSmprKtGnT+Otf/8rmzZspLCxU7oQ7m1Dz8/PZsGGDMmBl7ty59O/fn+nTp/Pb3/6Wp556ioEDBzJkyBAiIiKUL6HOZnAAnU6n9B/srFp6PB5cLhfr1q1jzZo1PPPMM4wYMYINGzbw7LPPkpqaSlRUlDIPm9FoVI4Pp5tao6KiruiJsa9mLpeLL7/8kj/+8Y8cO3aMiRMncs8999CzZ88z+tJeLCqVigEDBrB48WJefvllCgsLyc/PV/6u1WqV0dc33XQTGRkZSqW9s2P/uTIYDMTGxpKYmMicOXOURFClUp1Ts1lycjK33347b775Jh988AGPPPIIRqORtLQ07rzzTvr378/rr7/Ojh072LVrF+Hh4dx77710dHSwb9++835vOpOn9vZ23G43FRUVXV5v52j1uro6IiIiqKioQKvVYrFY0Gq1tLS0KM3A9fX139gFovP/t/N4cXFx3H333URHR5OWlkaPHj3wer1s2rQJp9PJD3/4QywWCwcPHjyvwQQajYbo6Gg6Ojqoq6sjOzubqqoqWlpalO8Tt9uN1WrFbrdTUVGhtFiUl5dTXFzMI488wvjx41myZIkycO/r7HY7J0+exOFw0NbWRlNTE4MGDVIm7q+vr8dmsylN5nC6RWXbtm2cOnWKhx9+mOzs7DNG5p/tPfsu57Kf0+lky5YtJCcn89BDD1FdXc2ePXuuipYSSfgE8H+DE5599lmam5txOp2YzWbi4uK6JC4Wi4Uf//jHJCYmotfru3TKHzBgAL/5zW9oaGjA6/USHR1NYmIiGo2GV199Vel/B6ebAR555BGmTp2KRqNR+rvExMQoTT15eXl4PB5lcMC//du/UVdXh9/vJzY2VmnqysvL45VXXjnrRKJarZbbb79dqR6q1WomTpzIiBEjHlL4FwAAIABJREFUSExMRKfTMXXqVIYNG4bH4yEhIQGv14vZbP7/7d15eFX1gf/x992T3CQ3+0YCWchCgCRAwiJBUTAUl4IKVKu2arVKFztOO50Z25920elil7G1tdZa0S7juLRuDxUQQUHZggHZQoCAIYQkZLnZl7v9/uDJGUISREuA3n5ez5PnMfec8z3fcxLhw3fF4XBw8803s2TJEvr6+nC73URHR5OYmGiMh3riiSfo6uoiNjYWs9ls/Gt6/vz5zJo1C5fLhclkYsqUKTzyyCNERETw/PPPExcXx9e//nXi4uLYtGkTv/71r2loaGDOnDn85Cc/oaWlhcjISBwOBw6HA7vdzsKFC5k7d67xr+kZM2Ywfvx4EhMTR/vXQ0ZBbW0tL774IhEREXz/+99n1qxZxMXFjcoMwYEyB8ZITpkyhfXr1/OFL3yB+Ph42tvbjWECpaWl7Ny5k1/+8pfk5+fT1dVFUlISS5cuNYZEnFre6cMpBr4fmMjz4osv8uMf/5jExETcbjclJSXGTMjTn/XUci0WC5MnT+bmm2/mueeeY82aNZSUlPDaa69hMploaWnB6XSSkZFBbW0t69ev5/nnn6e+vp66urph3+Nw9xv4ysjIIDU1laeffpotW7Zw4MABOjs7B/2jbe/evfzwhz/E6XRSXl7OokWLKCgoYObMmfztb38zWujr6+uNIRenDr84ldlsJjIyktraWl577TUSExMJBAIUFxdz1VVXkZKSwttvv81LL72Ex+OhqqrKGCN7pnd3qvz8fCZMmMDvf/97I2A1NzdjMpnIyckhJCSERx99lLS0NHbt2oXX68VkMhnjoletWsWRI0d49913R+ytCQQCvPjii1RXVxvdonPnzsXhcFBQUMBvfvMbHnroISwWC7t27TIW009KSjKWvAoNDaWiomLQeNqzeb6P+uz039OBn2NsbCw7duzghRde4ODBg8Y7OduhQf+oLA8++OB3Tn0pA3bv3s2aNWtob28nLCyMxYsXk52dHdQv45+d2WwmLCyM2NhYEhISiImJMcIFwJEjRygvL6esrIzCwkJjYPEAi8VCeHi40UIQHR2NzWbDarUa4WXAwL8w4+PjjVAZERFhjFWy2WzExMQQHx+P3W436hYfH09CQgKRkZGDlo8ZqWto4D6njq0baH0buN5utxv3cjqdhIeH43A4jGvDw8ON8BoVFWXU0Wq1EhUVZcwydTqdhIaGGt0t4eHhxh/0Ay18FouFhoYG3nzzTfbt28fOnTvZuHEjqampXHXVVca7SEhIIDo62limYuAv0PDw8CEtfOdqfJecXwMTXa699lqKiooGtd6eaw6Hg3HjxpGVlUVISAiJiYlMmDCB+fPnExcXZ4SPCRMmkJ2dbazT1tbWRkREBHl5eYwZMwaz2Ux0dLSxNNCpawcmJydjsViIiIggNzeX5ORkY6mNnp4e+vr6SExMJD8/n7i4OGJiYsjPzzdm0jocDtLS0hg/fjxhYWGMHTuWnJwc0tPTiYuLw+VyMW7cOLq6ujhx4gQREREsWLCAoqIiUlNTiYiIoK+vj7y8PGbPns2kSZMGzdo2mUxERESQk5NDWlqa8f9pZmYm2dnZREVFGetBhoWFMW/ePIqLi8nPzycqKoro6GhmzZpFQkICJpOJefPmsWDBAhITE8nIyCAiIgKHw0FpaSmXXHIJ+fn5JCQk4HA4yMjIMN7pQA9FdnY25eXltLW1cccdd1BUVERnZydr1qyhsLCQwsJCYmJi8Hg8ZGZmUlpaSmFhIYmJiYSGhpKZmWmUabfbGTdunLHczoDIyEiys7Ox2+1G3WbOnEl+fj7p6emMGTMGk8lETEwM8+fPZ8qUKUyaNInExERjzVCXy8Xs2bOZMWMGOTk5gyYPDSyBM23aNLxeL4mJiSxatIhJkyZht9tJTEwkKSkJk8lEXl4eZWVlTJo0iZycHMaMGUNycjIej4e0tDRKS0uZMmWKsSzMuHHjyMzMNCbwjRkzhsmTJw8atx0ZGUlubu6gn2dWVpbxO5SSkkJubi4ul4vk5GTy8vIIDw83Gira2tqYMmUKpaWlTJw4keTk5EE/q4tVV1cXb7/9trGA9vjx41m0aNGgRpXhmHw+X2C4wPfcc8/xzW9+k6NHjxIXF8eKFSu46qqrFPj+idXV1bFr1y6mTp06aCaYfDxdXV3s2bOHqqoqPB4PycnJTJ482VjEWGQ0nLpl1KljpYY7DifHa3m9XiwWy6Dfy9OvHe770/+e8Pl8+P1+LBbLkMlGI9Xh9HIGvh+YzTzQon5qfQfucXq5Z1v3U8uxWq3DvrOBMV+n/0NrpOuGey6A9vZ2Hn30USoqKvj+979PQkICK1eu5I033uA73/kOeXl5BAIBfD7fsM/0UT/P0+s2MEnt9LoNjIsb7thAi9+prZUjvdOBck5/LwPPYDabOT1r/L3P93F+F4f7/fZ4PIPGNA533sWosbGR733ve/zqV78CYMGCBcbSZWeipgE5a0lJScTGxmrM2N/J6XRSXFxsLD8w0AoqMpqG6+oa6ThgjMH6qPPOpuvt9NB4NnU4U3fvcPUym80fuYvG2dT11HJG6h4cqYt2pGA0XDnh4eFcddVVtLS08Ktf/QqHw4HZbOazn/2ssfSJyWQa8c+Gj/p5nl63kc499edy+rGz+XNp4Joz1fOTHhupXiN9fjbvfYDZbB5x3Hew0t8yctZG+h9EPj69S5F/bhaLhaKiIjIzM40t5VwulzG5S+RcU+ATERG5AKxWKzExMcTExFzoqsg/gY+/i7SIiIiI/ENR4BMREREJcgp8IiIiIkFOgU9EREQkyCnwiYiIiAQ5BT4RERGRIKfAJyIiIhLkFPhEREREgpwCn4iIiEiQU+ATERERCXIKfCIiIiJBToFPREREJMgp8ImIiIgEOQU+ERERkSCnwCciIiIS5BT4RERERIKcAp+IiIhIkFPgExEREQlyCnwiIiIiQU6BT0RERCTIKfCJiIiIBDkFPhEREZEgp8AnIiIiEuQU+ERERESCnAKfiIiISJBT4BMREREJctYLXYF/JL29vbS0tOD3+4mJiSEsLOxCV0lERETkI52XwOf3+3G73Xz44YecOHGC3t5e4uPjGT9+PHFxcZhMpvNRjb+L3++nvLychx56CLfbzbe+9S2uuuoqLBbLha6aiIiIyBmNeuDzeDxs3ryZJ598ksrKSpqbm+nr6yMmJoZp06axfPlypk+fPqp1aGtro7a2ltDQUFJTU7Hb7Z+onKamJvbs2UNzczMNDQ34/X4FPhEREbnojWrg8/l8vPbaa/zwhz9kx44dWCwWIiMjsVqt1NbWUl1dTUJCAiUlJaPWyhcIBHjuued48skniY2N5aGHHqKkpOQTl+X3+/H7/QQCgXNcUxEREZHRMaqBr6qqiieffJKKigpiYmK48cYbmT9/PtHR0Rw8eJC1a9cSFRU15Lr+/n7cbjd+v5+oqChCQkIGHQ8EAvT39wPgcDgIBAJ0dHTQ29uLy+XC4XAY5/p8Purr66mqqiI+Ph63243X68VisQwJmf39/bS2tgIQFRU1qJzhDHRVezweXC7XJ245FBERERlNoxb4Ojs7ef3119mwYQM2m43rrruO//zP/yQuLg6z2cz06dNZsGABHo/HCF79/f2sXLmSlStXUldXh9/vJz4+nssvv5zFixcb4bCyspLf/va3WK1WbrjhBj744APWrFlDT08P2dnZ3H777RQUFFBbW8tTTz3FSy+9RG9vL42Njfzwhz/khRdeYMmSJZSVlQHQ09PDq6++yurVq6mvrwcgISGBK6+8kmuvvZaIiIghz9fY2Mivf/1r3nnnHbxeL3l5edxxxx1MmDABOBkG9+3bx5o1a0hOTqasrIzo6OjRet0iIiIiIxq1wNfS0sL7779PV1cXubm53HDDDSQlJRnH7XY7ycnJxvdNTU08+eST/Pa3v6WhoYHQ0FD8fj89PT288cYb7N+/n6997WskJSVx7NgxXn/9dXp6eigvL+fgwYM0NzfT39/P2rVrOXLkCP/1X/+F1+tl7dq1VFZW4vV68Xq9vPvuu+zevZuJEydSVlZGQ0MDv/rVr1ixYgVNTU2Ehobi8/no6elhzZo1HDp0iC9/+cuDWiI9Hg9PPfUUXV1dtLe34/F4WLt2LXV1dXzve98jKyuL/v5+XnjhBR5//HFiY2NJTExk7ty5o/W6RUREREY0aoGvo6ODo0ePAhATE0NeXt6I5/b39/POO+/wm9/8hqamJhYsWMDixYvp7e3l5ZdfZvXq1bz44ouUlJRw3XXXGePn6uvr6evr49JLL6WwsJB33nmHjRs3snbtWrZv305ZWRn33HMPDoeDDRs24HQ6uf7665k0aRKXXXYZvb29vPnmm/z2t7+lu7ubRYsWcfXVV9PW1sZLL73E+vXref7555kxYwbz58836uv3++no6GDevHnk5uby1ltvsWXLFt566y2WLVtGRkYGAN3d3XR0dGCz2fB4PKP1qkVERETOaNQCX1dXl9E9GhoaisvlGvHczs5O1q9fT11dHbm5udx7772Ulpbi8/lISkpi+/bt1NfXs3nzZhYtWmRc5/P5WLhwIffffz8ZGRlMmDCBAwcOcPToUY4dO0Z4eDhLliyhqqqKLVu24HK5WLp0KXPnzsVqtdLQ0MCbb75JY2MjxcXF3HfffUyZMgWv10tsbCwVFRXU1tayefPmQYHParWyZMkS/u3f/o2kpCTS09PZv38/bW1t1NXV4fV6sdlsLFu2jJiYGOLj4ykoKBitVy0iIiJyRqMW+KxWK6GhocDJFrzu7m4iIyOHPbe3t5fDhw/j8/nIyMhg3Lhx2Gw2bDYb6enppKens2PHDurq6oZcO3nyZNLT03E4HIwdOxan00kgEKC7uxufz0doaKgxQcNkMmGz2YzJFd3d3Rw+fBiTyURWVhapqanGfbOyshg7diz79+/n2LFjg+5psVgoLCw0zh83bhwhISF0dHTQ2dmJz+fDbrczdepUJkyYgNVq/cgJICIiIiKjZdS2VgsPDyclJQUAt9vN4cOHRzzX5/PR2dlJIBAgJCRk0Np2VquVkJAQAoEAXq93yLVms9mY9GG1Wo3/DgQCH7l0ysB9gWHv63A48Pv9w9731Fm+I93XbDbjdDoV9kREROSCGrXAFxUVxfjx4wGoqalh1apVxlIqA3w+H319fVitVlwuFyaTiaamJnp6eoxzOjs7qa+vx2azERcX95H3PdN6fn6/H5/PZ3w/cN9AIEBTUxN9fX3Gsfb2dhoaGnA4HMTHx5/1c4uIiIhcbEatSzc2NpaFCxeyatUqqqur+f3vf4/T6eSqq67C6XRy/PhxXnnlFVwuF3fddRfZ2dlYLBaqqqp45513iI6ONiZVHD16lKioKAoLCz/RAs0D3brNzc0cPHiQCRMmEBERQXh4ODk5Oaxbt469e/eyceNGrrzySjo6Oli9ejXHjx8nJSWFwsLCj31Pr9fLqlWrePbZZ0lLS+NLX/oSmZmZH7scERERkb/XqAU+i8VCaWkpt956K48//jjHjh3jBz/4gRH8mpubcbvd3HzzzYSHh7Nw4UL+9re/sX//fn70ox+xevVqent7qaiowOfzMWfOHObOnYvZ/PEaJU0mE+PGjSM8PJza2lp+8pOf8PLLL3PTTTfx2c9+lmuuuYY1a9ZQU1PDd77zHV5++WU6Ojp4//33sVgsXH755cyePftjP7/H42H9+vWsXLkSl8tFWVmZAp+IiIhcEKO600ZUVBRf/OIXSU5O5ne/+x27d+9m//79ALhcLq644gpuvPFGQkJCmD59Oj/60Y949NFH2bhxIzU1NcDJlsIvfOEL3HPPPaSnpwNgs9mwWCxYLBbsdvugsXQD4+lsNpsRDmfMmMHChQtZsWIF1dXVdHZ2smTJEmw2G5deeimPPPIIjz76KJs3bzYmccTHx3PPPfdw5513GmMRT72vzWYb8b4mkwmz2WxMUomIiDAmsIiIiIicb6Ma+ACSk5O59dZbmTdvHo2NjRw/fhy/309qaippaWnGYszh4eGUlZUxadIkampqqKurIzQ0lLS0NFJTU4mLizMC1rRp0/if//kfuru7GT9+PDabDYCcnByeeeYZOjo6yMjIICwsDIAxY8bw4IMPctNNN3HixAliY2ONbtqIiAiuvvpqCgsLqa2tpa6ujoiICFJTU0lNTSUmJsa4b2lpKX/5y1/weDxGF7TJZKKgoIAXXniB3t5eMjMzcTgcmEwmvvCFLzB79mwiIyONHThEREREzrdRD3xwcgxdVlYWmZmZxgLEVqt1SPfswBInaWlpeL1eTCbToBmwAyIiIigqKgIGT9IIDQ011rs79XOLxUJKSgqJiYn4fD6jlW6A3W4nMzOT9PR0vF4vZrN52L12o6KimDZt2pDyw8PDmTJlypDPk5OTSUxMNFr8RERERC6E8xL4BphMJmMNvDMxm80fed5IkzfONKnj9KA32vc1mUxnvJ+IiIjI+aBmJxEREZEgp8AnIiIiEuQU+ERERESCnAKfiIiISJBT4BMREREJcgp8IiIiIkFOgU9EREQkyCnwiYiIiAQ5BT4RERGRIKfAJyIiIhLkFPhEREREgpwCn4iIiEiQU+ATERERCXIKfCIiIiJBToFPREREJMgp8ImIiIgEOQU+ERERkSCnwCciIiIS5BT4RERERIKcAp+IiIhIkFPgExEREQlyCnwiIiIiQU6BT0RERCTIKfCJiIiIBDkFPhEREZEgp8AnIiIiEuQU+ERERESCnAKfiIiISJCzXugKBAIBTCbTGc/p7e2loaEBq9VKUlISFovlPNXuzDweDydOnKC/v5+kpCRCQkIudJVEREREhhi1Fr5AIIDb7Wbbtm1UV1fj9/uNYz6fj3Xr1nHvvfeyZMkSHn74YY4fPz5iOevXr+f222/ngQceoL6+frSq/LF9+OGHPPjggyxfvpw33njjQldHREREZFij1sLX2trKY489xooVKygsLORnP/sZGRkZ+Hw+3njjDb71rW9x4MABAA4dOsSCBQtITk4eUk59fT0vvvgi7777LnFxcURHRw86HggEqKys5Omnn6alpQWXy8WnP/1pLr300o9sORxJc3Mz//u//8v+/fuHHIuOjua6666jsLCQyMhI/H4/b7/9NmlpaXzqU59SK5+IiIhcdEYt8Pl8PtxuN8eOHSMtLQ2v1wtAS0sLq1evZvfu3YwbN45bbrmFxMREkpKShpTh9/uprKxk9erVOJ1OiouLhwSqrq4uVq1axeOPP47P58NisdDW1sbEiROJi4v7RHU/ceIETz/9NHv37h1yLDExkezsbAoLC4mNjaW4uJi//vWvvP/+++zatYuSkpJPdE8RERGR0TJqgS86OpovfelLXHHFFcTHxzNu3DgA2traqK6uxmQyUVRUxNe//nXCw8OHbY3r6emhoqKC48ePM3bsWEpKSjCbB/dCu91u3n77bTo7OzGbzQQCAd577z0qKyspLS0ddN6BAwfIyMj4yCDo8/no7Oykv7+f0tJS0tPTjWPx8fFMnDgRAIvFQlFREenp6ezfv5+3336bqVOnXjRjDEVERERgFAOfyWTCarUSEhKC3W4HoLGxkYqKCurq6gDo7Oxk69atjBs3jvT0dGw226AyOjo6KC8vx+fzkZOTQ1pa2pD7VFVVUVlZidPpZPr06ezZs4dDhw6xY8cOSkpKcDgcABw/fpyHH36Y/v5+li5dyhVXXEFycrJRt+HYbDZuvfVWrrnmGuMzq9VKRESE8X1ubi5ZWVl88MEHbN26lbq6umHrKSIiInKhjNqkjc7OTv74xz9yyy238OCDD9LU1MSaNWt48MEH2b17Nz6fjw0bNnDLLbfwy1/+kubm5iFltLW1cfjwYQKBAKmpqYSHhw86HggE2LJlC8ePHycvL4+bbrqJsWPH0t/fz+bNmweVGRoaSkREBBs3buT+++9n+fLl/O53v+PQoUMjPoPZbCYyMpKEhATjKyYmZlAwDQsLIyUlBZvNxtGjR2lqajoHb09ERETk3BnVMXwtLS00NDRw4sQJPB4PsbGxJCUlcfToUTwejxGWkpKShm1pq6uro7W1FTjZRXz6+L2mpibKy8vp6upi6tSpzJs3j23btlFeXk5FRQU1NTWkpKQAMGbMGB544AGKiop49tlneeONN9i8eTPPP/88N954I0uWLBnS1dvf389TTz3F22+/TVxcHIWFhcydO5eoqCjjHLPZTHR0NFarlaamJtrb28/1qxQRERH5u5y3dfgCgQBz5szB4XBw//33s337di699FJ+8IMfEBcXNyhEDWhtbaWvrw+AqKgoo3t2wI4dO9i1axcJCQmUlpaSkpLCzJkzWbFiBQ0NDWzevJmZM2cCJ7tns7OzufvuuykrK2Pt2rW88sor7Nu3jwceeIDXX3+d5cuXc/XVV2MymYxWvHfffZcNGzZgsVhwuVxccsklfOMb32Dq1KmYzWZMJpPR6tfa2qrAJyIiIhed87rwstPpJCkpidDQUEwmExEREaSnpw8JcgO6u7vxeDyYTCaioqIGtQJ2dXWxefNmampqKC4uNsLkpEmTyMnJoaqqik2bNnHnnXcO6goODw9n4sSJZGZmMm/ePFasWMHvf/971q1bx7hx47j66qtJSEjgy1/+Mg0NDVgsFtxuN5s2bWL79u28+uqrREdHk5qaSlJSklE3q9VKd3c3ra2teL1erNYLvqa1iIiICHAR7LRxJn6/n0AgQCAQMFrTBhw9epT169cbu1089thjxpIs/f39eDwe9u7dy44dOwbN1oWTE0paW1t55ZVXWL9+Pb29vYSEhBAfHw9AXFwcd911l3G+x+OhvLycf/3Xf2Xr1q1s3bqVmpoaI/AN1M3v99PX10cgEDg/L0hERETkLFzUgS8kJMRoKRsIciEhIXi9XiorKykvL8fv93P48GGeeOIJ47qBbuAjR46wfv16ZsyYgdVqpbOzk3379vHGG2/w6quvcuTIEUJDQ1mwYAGf+cxnmDt3rlHGqcu/OBwOJk6caIwH7O7uNu7h9/txu914vV5MJhMhISFDlo4RERERuZAu6sB36ri9gfF8ISEhdHR0sHnzZjo7O0lLS+Oqq64iJibGuK69vZ2VK1dy5MgRNm3axNGjR4mMjOSZZ57hz3/+M4cOHSIkJISFCxdy9dVXM3v2bBISErDb7QQCAZqamjCZTMYkjkAgQFVVFbW1tQAkJSUZO34EAgFaW1vxeDw4HA4iIiIU+EREROSiclEHvpSUFJxOJ3By4eSBVrWmpiY2bdqE3++ntLSU+++/n9TUVOO6np4eOjo6qKmpYfv27ezZs4eMjAz++te/cuDAAT71qU9x2223MW3aNOLi4gYtlOzz+XjppZf429/+Rk5ODmPGjKGpqYk333yT3bt343Q6mTNnDhkZGcDgwJeSkkJMTMwn3tJNREREZDSM6sLLA0FqYJzb6f/9US1hUVFRpKWlsXPnTo4fP05XVxcAe/fupaamBrvdTklJCfHx8YPKcjqdlJSUsHLlSpqamti5cyfjx49n8eLF3HvvvVxyySUkJyePuCNGX18f27dvZ+3atTgcDjweD729vSQkJHDNNddwxx13GEG0r6+P+vp6PB4P48aNIyEh4e97cSIiIiLn2KgFvtDQUObPnw9AVlaWsexKfHw8n/3sZykuLmb69OlnnM0aERHBlClTWLlyJQcOHKCuro6MjAxSUlL4/Oc/j8lkoqysbMj6fABXXnklnZ2dnDhxgoKCAlJTU7n77rux2+3Y7fYRW+HMZjMLFy7EarWyb98+3G43DoeDxMREioqKmD17NsnJycb51dXVxlZxEydOHNTSKCIiInIxGLXAFxISwpVXXskVV1yB2Ww2WtNiY2O57bbb8Pl8WCyWM7byhYeHU1xcTFhYGCdOnGDHjh3MmjWL4uJiioqKjO3bhpOTk8M3vvEN/H4/Vqv1rMfVmUwmcnJyGD9+PL29vfT09GC1WnE6nVgsliFBcefOnVRXV5OYmEhJScmQ3UBERERELrRRnV1gNpux2WxDuk4HPv+oEGaxWJg4cSLz5s2jo6ODbdu2Gevy2Wy2M7YODoRBu93+iSZRmM1mwsLCiI2NxeVyYbVah4Q9t9vN9u3bcbvdTJkyhTlz5nzs+4iIiIiMtot+OmlqairLli0jJyeH7u5u3G73ha6SoaWlhebmZvLz81m0aJGxbIuIiIjIxeSinqULYLfbueaaa5g0aRJWq3XYLdgulOTkZL797W/j9XoZO3aslmMRERGRi9JFH/jg5OSNyZMnX+hqDBEaGsqECRMudDVEREREzkhNUiIiIiJBToFPREREJMgp8ImIiIgEOQU+ERERkSCnwCciIiIS5EZ1lm5/fz8dHR04HA6cTqexcHEgEKCxsZGjR4/S3d1NbGwsmZmZhIaGDlvO4cOHeeutt3C5XCxYsICIiIjRrPao6OrqYtOmTVRWVjJ9+nSmTJmCzWa70NUSERGRfwKjFvi6u7tZtWoVr776Krm5uXzxi18kJiYGgKqqKn7+85/zzjvv4Ha7mTx5Mj/72c+YOHHikHI6Ozt54YUX+OlPf8oll1zCFVdcMeSc1tZWtm3bRnt7O+Hh4UyePJkxY8aM1qMNcvz4cfbt20dPTw8AVquViIgIkpOTGTNmDHa7HYDe3l7eeustnnjiCRYvXsyPfvQj4uLizksdRURE5J/bqAW+1tZWXnnlFZ555hkKCwspKysjJiaGrq4u/vKXv7BixQoCgQDJycl0dXUZgel01dXVvPTSS3R1dZGeno7L5Rp03OPxsG7dOu677z56e3txOBzcfffdfPOb3xz1FjSfz8dLL73ET3/6UzweD3BySza73U5UVBRXXnkly5cvZ+zYsbhcLvLy8ujq6mLr1q0cPHhQgU9ERETOi1ELfC4KPDH+AAAVeklEQVSXi8suu4z6+noKCgoYO3YsAM3NzXzwwQd4PB7mzJnDz3/+c6Kjo0lMTBxSRn9/P7t27WL37t1ERUUxffr0IbtZtLW1sW7dOmpqaowu47Vr13LDDTeQl5c3Wo8HnAx8dXV1HDlyBKfTSVZWFmFhYTQ3N7N7924OHz5Mf38/Dz74IJGRkUyYMIGJEydy5MgR1q1bN+zziIiIiJxroxb4nE4nS5Ys4bLLLsPpdBITE0MgEKCjo4MTJ05gsVhISkoiMzOT8PBwLBbLkDI6OzvZtm0bvb29pKWlkZ+fb4S6AXV1dZSXl2OxWEhNTaW5uZmdO3eya9cucnJyRjVQBQIB47/T09P53ve+x6RJkzhw4ACPPPII69atY+PGjRw4cIBp06aRlZVFcXExH3zwAe+99x719fXaf1dERERG3ailoe7ubp577jluu+02vv/979PS0sKqVav4+te/Tnl5OT6fj/Xr13PNNdfw05/+lJaWliFldHZ2smvXLgKBAFlZWcTGxg45p6Kigg8//JCUlBSWLl1KUlISLS0txpi+U/n9/jN+DQS4QCBwVuedym63k5SURFZWFvPmzWPGjBkEAgE6Oztxu90AREdHk5eXh8Ph4PDhw1RVVZ2LVy0iIiJyRqPWwtfX18f+/fvZsGEDXq+X7u5umpqaOHz4MF1dXfj9ftxuN3v37qWwsJD+/v4hZTQ2NtLU1EQgECA2NnbILN7e3l62bNlCS0sLZWVlXHvttVRWVnLw4EG2bt3K8ePHiYqKAmDPnj08/PDDHD16dNj6ulwubr75ZpYtW8ZTTz3Fiy++OOK4woKCAu677z7S0tKMz7xeLy0tLUYX7wcffIDNZiM3N5ecnBwATCYTMTExhIeH09raSkNDwyd6tyIiIiIfx6guy+L3+4H/azGbPXs2X/rSl3j88cc5dOgQ06ZN47bbbmPy5MlGMDtVQ0MDXV1dwMnWsYEZrwOqqqrYsWMHDoeDmTNnMnnyZGbOnMnrr79OdXU1u3fvZsKECcDJyR1NTU0jhqy+vj66urqMbueGhoYRA19zc7MxSWNAbW0t//3f/43L5aKmpoY9e/ZQUFDAbbfdNqjbNioqCqfTaYRZERERkdE2qoHvdBkZGZSVlfHKK69w+PBhxo8fz+c+9zkcDsew53d0dBgtf1FRUYSEhBjH/H4/27dvZ8+ePaSlpXHppZficrkoLi4mJiaG5uZmNmzYwNKlSwHIzc3lscceGzHEWa1WEhMTsVgs3HrrrZSVlRmB9XTh4eFDln1pbW3lzTffHPTZsWPHeOuttyguLjZCn8vlIiwszGjx9Pl8w45fFBERETlXzmvg+7j6+/vx+XyYTCbCwsKwWv+vug0NDbzzzjt0dnbicrnw+/3s2LGDjo4O0tPTqaioYMeOHVRXV5OZmYnVaiUmJoa+vr5h72WxWAgLCzPuFRcXN2LgCwkJwWaz4fV6jc8yMjK4++67yczMpLGxkdWrV/PWW2/xzDPPEBMTw3333UdERARhYWE4HA78fj/t7e309vbidDrP7YsTEREROcVFHfisVitms5lAIEBPTw9erxebzUYgEODQoUO8/fbbBAIB9u7dy1e+8hVMJhMej4e6ujoCgQAHDhxgw4YNZGZmUl1dzS9+8YsRu3TDw8NZvHgx1157LS+//DIrV64cdlwhQE5ODnfdddegrlqXy0VpaSklJSX4fD6mTp1KfX09W7du5b333uMzn/kMubm59PT0GOWazeYhs45FREREzrWLOvCd2qrndrvp6+vDZrPR09PDjh07qKmpAU5uW1ZZWTnoWpPJxIkTJ9iwYQOLFi2iqamJN954w7jmdC6Xi5ycHK655hp27tzJa6+9Rm9v77DnFhcXc8MNNwwKfCaTCavVaowzTExMNFru+vv7jdbAtrY2Y1xiWFjYkHGJIiIiIufaRR34Tg1NA4FvYIbrxo0b8fv9lJaW8u1vf5vU1FTjutbWVr7zne+wdu1atm3bxr59+ygoKOCPf/wjbW1tw97LbreTnZ2NxWJh+fLlLFiwYFCX7ani4uKGLOrc3d3N/v37sVqtxrZye/fuxWq1kpOTQ3x8vPEc3d3dREREkJCQMKibWkRERGQ0XNRpIzEx0dh/t7m52WhxG5iBGwgEmDlzJtOnTx80y9fn8zF9+nQ2bdrEgQMH2LlzJ1OnTmX69OnDrqE3wGKxYDKZyMjIMHYGGY7JZMJisQwaD1hTU8NDDz1EWFgYXV1dNDY20tfXx+zZs7nllluMbdRaWlro7OwkISHhjPcQEREROVdGbeFli8WC0+nE4XAQFhZm7Gtrs9kGfX6mMWwRERHk5eVhNps5ePCgsYDx4cOH6ejoICkpienTpxMZGTnk3pdccgkpKSn4fD4OHTpEV1cXFosFq9U64tdAXQa6Z0f6GphVa7fbSUtLIzY2Fp/Px4cffsj+/ftxu93k5eXxH//xHzz22GPMmjULs9lMe3s7hw4doru7m7S0tFHf+k1EREQERrGFLyIigq985SvccMMNREREGHvljh07ll/+8pe43W7i4+ONIDhSGSUlJTz77LMcPXqUyspK8vPzueaaaygqKsJisTBu3Lhht0+77LLLeOWVV+ju7iYpKQmXy3XOn9FkMnHTTTdxxRVX4PP5jM8tFgshISFERUURERFh1O/QoUOUl5djt9uZOHEi6enp57xOIiIiIqcbtcBnNptJTEwkISEBwGg9s9vtpKenEwgEPnKGqsPhoKioiNzcXKqrq9m2bRuLFy8mJiaG6OjoQeWeLjw83GhBG82ZsFFRUcMuGn06r9dLZWUle/bsITExkblz554x7IqIiIicK6PWpTvAZDING7jOJoSZTCby8vL49Kc/TX9/Pzt27DD2xx2p3LO594XQ1tbG9u3b6enpoaCggJkzZ17oKomIiMg/iYt60gacbKlbunQpfr+fqKioERdDvthZLBYmT57M8uXLKSsrM1o+RUREREbbRR/4TCYT+fn5/Od//idwcu26f0SRkZEsXbqU6667jpCQEK2/JyIiIufNRR/44OSOG+Hh4Re6Gn8Xs9n8DxtWRURE5B/bqI/hExEREZELS4FPREREJMgp8ImIiIgEOQU+ERERkSB3wSdtnM0CzD09PRw7dgyr1UpaWpqxtdnFLBAI4Ha7OX78ONHR0SQmJg67I4iIiIjIaBu1BBIIBGhoaGDdunXs2bNn0NZj/f39vP7669x+++2UlZVx//33U1tbO2w5fr+f1atXc/PNN/Otb32L+vr6Ye/V399PX18f/f39I67VFwgEWLVqFV/72tf4f//v/3HgwIFP9Fwej4f+/n7jy+Px4PP5CAQCxnler5eXX36Z22+/nQceeIAPP/zwY99LRERE5FwYtRa+lpYWHnvsMVasWEFhYSGPPvooWVlZeL1eXn/9db797W9z5MgRrFYrzc3NXH/99aSmpg4pp66ujhdffJGdO3eSlZVFTEzMoON+v59du3bx+OOP43a7iYyM5Prrr6esrGxIi1ogEOC9997jT3/6E2FhYcyaNYvs7OyzfqZAIMDevXt56qmnaGtrA06uExgREUFSUhIFBQVMmzaN+Ph4zGYzsbGxHDt2jLq6Oq699lrGjh37D9E6KSIiIsFlVLt0e3t7aWpqoqury+i2bWlpYe3atVRVVTF+/HiWL19OQkLCsGHP7/ezb98+1q5di9PppKSkBIfDMeicrq4uVq1axbPPPovP58NsNtPb28vUqVOH3c3C5/PR29uLxWL52Lt2+P1+du/ezRNPPDGoxdJsNmOxWEhISOCWW27hq1/9KnFxcWRnZ5OVlcXWrVvZtGkTc+fOJTIy8mPdU0REROTvNWqBLyoqinvvvZerr76a2NhYxo4dC5zcU/bDDz/EZDIxefJk7rzzTpxO57BldHd38/7779PY2EhmZibTpk0b0mrX2trKhg0b6OnpwWaz0d/fz5YtW9i7d++wgc9ms2E2m7FarR+7tS0QCNDX10d3dzexsbF87nOfY86cOVRVVfGnP/2JXbt28cILLzBnzhzmz59PQkICM2bMYOPGjbz33nucOHFCgU9ERETOu1Edw9fe3k59fT1NTU14vV5qampYv369MZ7txIkTvPbaa1RUVNDX1zekjI6ODt5//338fj85OTmMGTNmyDn79u2jqqqKyMhII2QdPnyYiooKent7B51rMpmwWq2YTCZsNhtW6yfPuw6Hg4KCAq699lruvvtuPv/5zwMnA+jhw4eBk6G3qKiIkJAQampq2Llz5ye+n4iIiMgnNWotfJ2dnTz//PP84he/YMaMGTz11FOsX7+eH//4xxw5cgSv18umTZvYuXMnN954Iw888ADJycmDynC73Rw5coRAIEBKSsqQ7dUCgQBbtmzh+PHj5Ofnc+ONN9LS0kJ9fT2bN29m6dKlQ7qKT23hGwh8+/fvZ/Xq1bS3tw/7LHFxcZSVlZGWljbo84FyHA6HsTeu3W4nOjoaAIvFQmJiInFxcXR0dFBdXf3JX6iIiIjIJzRqgc/v99PR0YHb7aatrQ2Px8OYMWPIzc2lqamJ9vZ2oqOjyc3NJScnh9DQ0CFl1NXV4Xa7AYiOjh4yfq+hoYHt27cbY/Yuu+wytmzZwpYtW9i5cydHjhw5Y+Ab6NLdvn07jzzyCC0tLcM+y9ixY0lKShoU+Pr6+tixYwcul4v9+/fz5z//GZvNxiWXXML06dON88LDw4mOjqapqYnGxsZP9jJFRERE/g7ndR2+Sy65BLvdzr//+79TXl5OaWkpP/7xj4mJiRl2bJvb7Ta6ek8PfIFAgPfff59du3aRlJTEnDlzSEpKMloTT5w4waZNmygtLR1Ups1mM7p0BwLfpEmTuPPOO42Zt6dLSEggLy9vSN2efvppnnvuOXp7e2lvbycxMZFJkyYZrX3wf4Gvr6+PxsZG/H6/1uMTERGR8+q8Br7Q0FDi4uIICQnBZDLhdDoZM2bMkJa7Ad3d3Xi9XkwmEy6Xa9B5nZ2dbNmyhdraWmbNmkVpaSkOh4OJEyeSl5fHnj172LRpE+3t7YPCpNVqHdKlm5+fT1ZW1oizds1mMyEhIYPW2QsJCWHKlClkZ2fjdrv54IMPOHjwIL/73e+w2Wz8y7/8C3a7HafTSXR0ND6fD7fbTUdHBy6X61y8ThEREZGzcsF32jgbpwatATU1Naxbtw6fz8exY8d4+OGHMZvNdHR00NHRgdfrpbKyku3bt3P55Zcb19ntdmw2Gw6HA5vNBpycPFJRUUFnZ+ew93e5XBQXFw8KapGRkXzmM59h2bJlRvfud7/7XbZs2cJf//pXysrKKCoqGlR/j8eDx+M5Z+9FRERE5Gxc1IEvJCTE6HZta2ujr6+P0NBQPB4P+/bto6KiAr/fz4cffsgf/vAH4P92wgCMWcGzZ8/GbrdjMpmYMmUKd9xxBwkJCaSkpACwceNGHnzwwRHH8KWlpfHd736XsrIy4zOTyURoaKgxQWPGjBkUFRWxefNmY+IInFwncGAcot1uH3asooiIiMhouqgDX3R0NCEhIcDJ5U4GAl9HRwebNm2iq6uLzMxMli1bNmjNvdbWVp5//nmqqqrYvHkzR44cIScnB4CwsDCSk5OJiYkxWvhycnJYtmzZiGP44uPjyczMHLGefr+fmpoaqqqqAHA6ncaOIJ2dnbS2tmKxWHC5XAp8IiIict5d1IEvOTnZWIrl1AkcjY2NbNmyhUAgwOzZs/nqV79qtNbByR0+6urqOHToEO+//z579uwxtlD7y1/+wmOPPUZERARxcXHMnz+fyZMnk52dPWj3jFNZLBZCQkIGjfFra2vjD3/4A9u2baO9vZ19+/axa9cunE4ns2bNYuLEicD/Bb6wsDDS0tI0YUNERETOu1ELfKcucmw2m42gM7AN2cDnZxIVFcW4ceOoqKigtraWzs5OEhMT2bt3L7W1tYSEhFBSUkJsbOyg6wY+f+2112hubuaDDz5g/vz5OJ1OOjs7jWViBhZmNpvNhIWFndVzhYaGEhoaSnd3N++88w6bNm3CZDJht9vJyspi/vz5fPGLX8TpdOLz+WhsbKSpqYmYmBijlVFERETkfBq1wOd0Ovn0pz9NXFwcaWlpRhdnYmIi99xzDwsWLKCgoOCMu11ERkYydepUXn31VQ4ePEhtbS1ZWVlkZ2fz9a9/HZPJxMKFCwctgzJgwYIFmEwmmpubmT59urEcy6JFi3A6nURGRhqTKs6W2WxmxowZPProo8YEj4ElXiIjI0lPTyc3N5e4uDjgZCvgjh076OnpISEhgcLCwo91PxEREZFzYdQCn91uZ/bs2cyaNWtQa15UVBTXX3+9sR6dyWQasQyn08m0adNwuVw0NTVRUVHBnDlzmDRpEvn5+WdsJUxPT+fOO+/E7/cbLYoAJSUlFBYWYjabjTF8H8fYsWO56667zurcEydOsHnzZqxWK5MnTx7U7SwiIiJyvozqgDKTyYTFYhkSygY+P1PYg5Mtavn5+Vx55ZV0dXVRXl5OX1/fiOUOd/1At/Kp9z51SZbR4vP5OHDgANXV1bhcLi6//PJhF5cWERERGW0X9aQNgDFjxrBs2TIOHTqE1+ulra3tH2Kmq9/vp6mpidjYWAoKCoxdRkRERETOt4s+8FmtVhYsWMCkSZMwm83GWMCLndVq5eqrr6akpASXy0VSUtKFrpKIiIj8k7roAx+cHMv3jzbD1WQyER8fT3x8/IWuioiIiPyT06JwIiIiIkFOgU9EREQkyCnwiYiIiAQ5BT4RERGRIKfAJyIiIhLkFPhEREREgpwCn4iIiEiQU+ATERERCXIKfCIiIiJBToFPREREJMgp8ImIiIgEOQU+ERERkSCnwCciIiIS5BT4RERERIKcAp+IiIhIkFPgExEREQlyCnwiIiIiQU6BT0RERCTIKfCJiIiIBDnr2ZzU1tbGN77xDR566CFMJtNo10lEREREhuHxeKitrf3Y140Y+EwmkxHuPB4PlZWVn7x2IiIiInLOnZrXzmTELt0xY8YQFRV1TislIiIiIueG3W4/67xm8vl8gYFkeGpC7OzsZO3ataxevZrW1tZRq6yIiIiIfDwWi4W8vDwWL17MxIkTP/L8EQMfQF9fH11dXXi93lGprIiIiIh8fCaTCYfDQXh4OGbzR8/BPWPgExEREZF/fFqWRURERCTIKfCJiIiIBDkFPhEREZEgp8AnIiIiEuQU+ERERESCnAKfiIiISJBT4BMREREJcgp8IiIiIkFOgU9EREQkyCnwiYiIiAQ5BT4RERGRIKfAJyIiIhLkFPhEREREgpwCn4iIiEiQU+ATERERCXIKfCIiIiJB7v8D3pKYD906Z8wAAAAASUVORK5CYII=\"></p><p>Contoh program:</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">import</span> java.<span class=\"hljs-property\">util</span>.<span class=\"hljs-property\">Scanner</span>;\r\n\r\npublic <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">Contoh</span> {\r\n  public <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span>(<span class=\"hljs-params\"><span class=\"hljs-built_in\">String</span>[] args</span>) {\r\n    <span class=\"hljs-title class_\">Scanner</span> input = <span class=\"hljs-keyword\">new</span> <span class=\"hljs-title class_\">Scanner</span>(<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">in</span>);\r\n\r\n    int angka;\r\n\r\n    <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Masukkan angka: \"</span>);\r\n    angka = input.<span class=\"hljs-title function_\">nextInt</span>();\r\n\r\n    <span class=\"hljs-keyword\">if</span> (angka > <span class=\"hljs-number\">70</span>) {\r\n      <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(<span class=\"hljs-string\">\"Selamat anda dinyatakan diterima\"</span>);\r\n    }\r\n\r\n  }\r\n}\r\n</pre><p>Ketika program di atas dijalankan kemudian dimasukkan angka 80 maka akan keluar tampilan <strong>Selamat anda dinyatakan diterima</strong>. Hal ini disebabkan karena terdapat sebuah kondisi yang menyatakan bahwa jika nilai lebih dari 70 (<code style=\"color: inherit; background-color: rgb(247, 247, 247);\">angka > 70</code>) maka akan tampil <strong>Selamat anda dinyatakan diterima</strong>, sedangkan jika dimasukkan angka 70 atau kurang dari 70 maka tidak akan terdapat tampilan apapun.</p><p><br></p><p><strong class=\"ql-size-large\">Sintaks Pemilihan IF-ELSE</strong></p><p><br></p><p>Bentuk umum:</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">if</span> (kondisi) {\r\n  pernyataan1;\r\n} <span class=\"hljs-keyword\">else</span> {\r\n  pernyataan2;\r\n}\r\n</pre><p>Bentuk flowchart:</p><p><img src=\"data:image/png;base64,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\"></p><p>Struktur ini minimal memiliki 2 pernyataan. Jika kondisi yang diperiksa bernilai benar atau terpenuhi maka pernyataan pertama yang akan dilaksanakan dan jika kondisi yang diperiksa bernilai salah maka pernyataan kedua yang akan dilaksanakan.</p><p>Contoh program:</p><pre class=\"ql-syntax\" spellcheck=\"false\">import java.util.Scanner;\r\n\r\npublic class Contoh {\r\n  public static void main(String[] args) {\r\n    Scanner input = new Scanner(System.in);\r\n\r\n    int angka;\r\n\r\n    System.out.print(\"Masukkan angka: \");\r\n    angka = input.nextInt();\r\n\r\n    if (angka > 70) {\r\n      System.out.println(\"Selamat anda dinyatakan diterima\");\r\n    } else {\r\n      System.out.println(\"Silahkan coba tes lagi tahun depan\");\r\n    }\r\n\r\n  }\r\n}\r\n</pre><p>Pada contoh program <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">if else</code> di atas ditambahkan kode program.</p><pre class=\"ql-syntax\" spellcheck=\"false\">else {\r\n  System.out.println(\"Silahkan coba tes lagi tahun depan\");\r\n}\r\n</pre><p>Sehingga ketika angka yang dimasukkan nilainya 70 atau kurang dari 70 maka akan muncul tampilan <strong>Silahkan coba tes lagi tahun depan</strong>.</p>', 'https://www.youtube.com/embed/492A2poEoow', 1, '2023-06-01 06:22:29', '2023-06-01 07:15:29', NULL);
INSERT INTO `contents` (`id`, `title`, `lesson_id`, `description`, `url_video`, `published`, `created_at`, `updated_at`, `deleted_at`) VALUES
(3, 'Sintaks Pemilihan IF-ELSE IF-ELSE', 2, '<p><strong class=\"ql-size-large\">Sintaks Pemilihan IF-ELSE IF-ELSE</strong></p><p><br></p><p>Bentuk Umum:</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">if</span> (kondisi1) {\r\n  pernyataan-<span class=\"hljs-number\">1</span>;\r\n} <span class=\"hljs-keyword\">else</span> <span class=\"hljs-keyword\">if</span> (kondisi2) {\r\n  pernyataan-<span class=\"hljs-number\">2</span>;\r\n} <span class=\"hljs-keyword\">else</span> <span class=\"hljs-keyword\">if</span> (kondisix) {\r\n  pernyataan-x;\r\n} <span class=\"hljs-keyword\">else</span> {\r\n  pernyataan-<span class=\"hljs-keyword\">else</span>;\r\n}\r\n</pre><p><span style=\"color: rgb(51, 51, 51);\">Bentuk Flowchart:</span></p><p><img src=\"data:image/png;base64,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\"></p><p>Pada bentuk <code style=\"color: inherit; background-color: rgb(247, 247, 247);\">if else if else</code> di atas, pernyataan 1 akan dijalankan apabila <code style=\"color: inherit; background-color: rgb(247, 247, 247);\">kondisi1</code> bernilai benar. Jika <code style=\"color: inherit; background-color: rgb(247, 247, 247);\">kondisi1</code> bernilai salah, maka akan dicek <code style=\"color: inherit; background-color: rgb(247, 247, 247);\">kondisi2</code>. Jika <code style=\"color: inherit; background-color: rgb(247, 247, 247);\">kondisi2</code> benar maka akan dijalankan pernyataan2, begitu seterusnya. Dan apabila tidak ada satupun syarat yang terpenuhi, barulah pernyataan-else akan dikerjakan.</p><p>Contoh program:</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">import</span> java.<span class=\"hljs-property\">util</span>.<span class=\"hljs-property\">Scanner</span>;\r\n\r\npublic <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">Contoh</span> {\r\n  public <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span>(<span class=\"hljs-params\"><span class=\"hljs-built_in\">String</span>[] args</span>) {\r\n    <span class=\"hljs-title class_\">Scanner</span> input = <span class=\"hljs-keyword\">new</span> <span class=\"hljs-title class_\">Scanner</span>(<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">in</span>);\r\n\r\n    int bayar;\r\n\r\n    <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Masukkan total belanja anda: \"</span>);\r\n    bayar = input.<span class=\"hljs-title function_\">nextInt</span>();\r\n\r\n    <span class=\"hljs-keyword\">if</span> (bayar >= <span class=\"hljs-number\">2000000</span>) {\r\n      <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(<span class=\"hljs-string\">\"Selamat anda mendapatkan hadiah kompor gas\"</span>);\r\n    } <span class=\"hljs-keyword\">else</span> <span class=\"hljs-keyword\">if</span> (bayar >= <span class=\"hljs-number\">1000000</span>) {\r\n      <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(<span class=\"hljs-string\">\"Selamat anda mendapatkan hadiah teflon\"</span>);\r\n    } <span class=\"hljs-keyword\">else</span> <span class=\"hljs-keyword\">if</span> (bayar >= <span class=\"hljs-number\">500000</span>) {\r\n      <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(<span class=\"hljs-string\">\"Selamat anda mendapatkan hadiah piring\"</span>);\r\n    } <span class=\"hljs-keyword\">else</span> {\r\n      <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(<span class=\"hljs-string\">\"Maaf anda belum beruntung, tingkatkan belanja anda!\"</span>);\r\n    }\r\n\r\n  }\r\n}\r\n</pre><p><br></p>', 'https://www.youtube.com/embed/yGrD2uZnvQo', 1, '2023-06-01 06:31:47', '2023-06-01 07:16:03', NULL),
(4, 'Sintaks Pemilihan switch-case', 2, '<p>Sintaks pemilihan ini digunakan untuk penyelesaian kondisi dengan kemungkinan yang terjadi cukup banyak. Struktur ini akan melaksanakan salah satu dari beberapa pernyataan <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">case</code> tergantung nilai kondisi yang ada di dalam <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">switch</code>. Selanjutnya proses diteruskan hingga ditemukan pernyataan <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">break</code>. Jika tidak ada nilai pada case yang sesuai dengan nilai kondisi, maka proses akan diteruskan kepada pernyataan yang ada di bawah <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">default</code>. Bentuk <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">switch case</code> pada umumnya digunakan untuk menggantikan pernyataan <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">if else if else</code> yang berdasarkan nilai konstanta.</p><p>Bentuk umum:</p><pre class=\"ql-syntax\" spellcheck=\"false\">switch (kondisi) {\r\ncase konstanta-1:\r\n  pernyataan-1;\r\n  break;\r\ncase konstanta-2:\r\n  pernyataan-2;\r\n  break;\r\n  ...\r\n  ...\r\ncase konstanta-x:\r\n  pernyataan-x;\r\n  break;\r\ndefault:\r\n  pernyataan;\r\n}\r\n</pre><p>Contoh program:</p><pre class=\"ql-syntax\" spellcheck=\"false\">import java.util.Scanner;\r\n\r\npublic class Contoh {\r\n  public static void main(String[] args) {\r\n    Scanner input = new Scanner(System.in);\r\n\r\n    int angka;\r\n\r\n    System.out.print(\"Masukkan kode kelas anda: \");\r\n    angka = input.nextInt();\r\n\r\n    switch(angka) {\r\n      case 1:\r\n        System.out.println(\"Kelas 1\");\r\n        break;\r\n      case 2:\r\n        System.out.println(\"Kelas 2\");\r\n        break;\r\n      case 3:\r\n        System.out.println(\"Kelas 3\");\r\n        break;\r\n      case 4:\r\n        System.out.println(\"Kelas 4\");\r\n        break;\r\n      default:\r\n        System.out.println(\"Kode yang anda masukkan salah\");\r\n    }\r\n\r\n  }\r\n}\r\n</pre><p>Pada contoh program <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">switch case</code> di atas jika dimasukkan angka <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">1</code> maka outputnya <strong>Kelas 1</strong> dan seterusnya sampai angka <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">4</code>. Jika inputan selain angka <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">1</code> s/d <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">4</code> maka outputnya adalah <strong>Kode yang anda masukkan salah</strong>.</p>', 'https://www.youtube.com/embed/_OwCDThM3EI', 1, '2023-06-01 06:48:22', '2023-06-01 07:16:43', NULL);
INSERT INTO `contents` (`id`, `title`, `lesson_id`, `description`, `url_video`, `published`, `created_at`, `updated_at`, `deleted_at`) VALUES
(5, 'Sintaks Pemilihan Bersarang', 3, '<p><strong class=\"ql-size-large\">Sintaks Pemilihan Bersarang</strong></p><p><br></p><p>Kita telah mempelajari penggunaan pernyataan IF untuk memilih sebuah tidak, pernyataan IF-ELSE untuk memilih antara dua tindakan, serta pernyataan IF-ELSE IF-ELSE dan SWITCH-CASE untuk memilih beberapa tindakan (3 atau lebih). Terkadang kita membutuhkan pengambilan keputusan dalam bentuk level (bertingkat) sehingga di dalam suatu pernyataan IF (atau IF-ELSE) bisa saja terdapat pernyataan IF (atau IF-ELSE) yang lain. Jenis percabangan seperti ini disebut NESTED IF (percabangan bersarang). Secara umum, bentuk penulisan pernyataan NESTED IF adalah sebagai berikut:</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">if</span> (kondisi <span class=\"hljs-number\">1</span>){\r\n  <span class=\"hljs-keyword\">if</span> (kondisi <span class=\"hljs-number\">2</span>){\r\n    pernyataan <span class=\"hljs-number\">1</span>;\r\n    …\r\n    …\r\n    <span class=\"hljs-keyword\">if</span> (kondisi n){\r\n      pernyataan <span class=\"hljs-number\">2</span>;\r\n    } <span class=\"hljs-keyword\">else</span> {\r\n      pernyataan <span class=\"hljs-number\">3</span>;\r\n    }\r\n    } <span class=\"hljs-keyword\">else</span> {\r\n    pernyataan n;\r\n    }\r\n} <span class=\"hljs-keyword\">else</span> {\r\n  pernyataan x;\r\n}\r\n</pre><p>Pada bentuk penulisan pernyataan NESTED-IF tersebut, kondisi yang akan diseleksi pertama kali adalah kondisi IF yang berada di posisi terluar (kondisi 1).</p><ul><li>Jika kondisi 1 bernilai salah, maka pernyataan ELSE terluar (pasangan dari IF yang bersangkutan) yang akan diproses. Namun, jika pernyataan ELSE (pasangan dari IF) tidak ditulis, maka penyeleksian kondisi akan dihentikan.</li><li>Jika ternyata kondisi 1 bernilai benar, maka kondisi berikutnya yang lebih dalam (kondisi 2) akan diseleksi. Jika kondisi 2 bernilai salah, maka pernyataan ELSE (pasangan dari IF yang bersangkutan) yang akan diproses. Namun, jika pernyataan ELSE (pasangan dari IF) tidak ditulis, maka penyeleksian kondisi akan dihentikan.</li></ul><p>Dengan cara yang sama, penyeleksian kondisi akan dilakukan sampai dengan kondisi n, jika kondisi-kondisi sebelumnya bernilai benar.</p><p><img 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OXOGSZMmYTAYiI+Pp1OnTuVy7qrIx8eH+fPns3LlSj744AN+/vlnhg0bhq+vr4Tbh6DVaqlVq5ZlTTF7e3tq1aqFvb09arWawYMHc+rUKYYPH079+vVp2rQpjRs3Jj09nWnTpqHVaqlXrx4eHh7Y2tri5eWFh4cH/fr1IzMzky1bttChQwcZD1kFycKwQoi/zGQyYTKZ0Gj+/3c6g8GATqezdA9aWVmV+YD+rKwskpKS+OSTT2jSpAnTp0+nZs2aZXrOR4VOpyMpKYlly5bh5+fHM888Q8uWLWVA+f9gNpsxGo2W1//vf4Zf3yuFhYVotVrLJvYqlYqCggJsbW3RaDSW95fRaESlUqFWqzGbzRgMhkq78b347ySQCSEqHYPBQGpqKvHx8Rw7doz+/fsTGxsrswNLmdls5qeffmLp0qVcv36dmJgYIiMjcXZ2Vro0IaocCWRCiEqlsLCQffv2sWbNGqysrHj66afp0qWLtBqUoRs3brB27Vo2bdpE9+7diY6OlvXchChlEsiEEJXG7du3WbduHTt27CAkJIRhw4YRGBj4QNepKBvFxcV8++23rFixAq1WS2xsLOHh4dKFKUQpkUAmhKgUrl27xnvvvcelS5eIioqib9++1KhRo0zHqZlMJgwGA1ZWVpbgUVRUhK2tbakMcD906BAZGRm0bdvWsq3R7+/XbDZz+/ZtioqK8Pb2/tMAZDAYKCkpKfPtoP59T9CjR48yfPhwnnzySZycnMr0vEI8CmQvSyFEhXfkyBFiY2MpLi7mzTffpHv37lSvXr1Mw5jZbCY1NZWFCxdiNBrx8/Nj+/btTJkyhebNm1OjRo1/fI6vvvqKpKQk0tLSSElJoVWrVmi12gf+jV6vJy4ujs2bNxMWFoadnd0Dx48dO8aECRPYt28fHTp0+MPx0qRSqfDw8CAkJAS1Ws2qVau4fv06wcHBEsqE+IeknV8IUWGZzWY++eQTXn/9daKiopg+fTpubm7ltvxCUVER169f5+7duxw/fpw5c+bQv39//P39S+X+dTodVlZWjBo1Cnt7+z8dLG9tbU10dDRFRUVUr179gWPbtm3j3Xffxd3dnWvXrmEwGEqlrv9GpVLh6enJqFGjCAgIYObMmZw5c4Y5c+bQoEEDRbbKEqIqkEAmhKhwzGYzt27d4o033mDLli189NFHDB8+XLF6MjIy2LRpE61atbLs9ajX60lJSSEuLo709HRatWpFTEwMKSkpliB36NAhunbtyrPPPou7uzsFBQV8/vnnfPnll/j4+ODk5IROp+PAgQOYzWYGDRqETqdjzZo1bN26lerVq/Pmm29y/fp10tPTGTFixAPdkq1atSI5OZkvvviCzZs3l+tzYmtrS48ePahXrx6vvfYaAwYMYOHChXTu3FnGlQnxN0ggE6ISKCwspKCgoFxXv1eKyWTi4sWLzJ8/n7y8PLZt20arVq0Uq+f+/fusXbuWhg0bMmbMGBwdHTGbzZw4cYK3336bdu3a0a9fPzZs2MAHH3yA0Wjk22+/JSYmhieffJKEhATc3NwYMWIEmzZtYt26dQwcOBCdTseCBQsICgri/Pnz6PV6HnvsMXbs2MGuXbt44YUXMJlMlJSUcPHiRU6fPs2QIUMeCGReXl6KPS+/CQgIsCwiGxsbS2xsLE899ZQsQVJJqFQqNBoNLi4usvCvwiSQCVEJrF+/nk2bNuHq6qp0KWXu7t27HDt2jMDAQBYvXkxwcLCi9eh0OgoLC7Gzs7NsWWMymUhJSaFatWqMGzcOLy8vrKysWLZsGdbW1oSHhzN16lQKCgq4dOkSN27c4O7du5w6dYp27doxePBgXFxcyMvLIyUl5YHz2dnZYWNjw61bt2jfvj2+vr788MMPSjz0h+bs7MyMGTNwdXXl5ZdfZt26dTRp0kTpssRDMJlMODo68uabb1KrVi2ly3mkSSATohLYuXMnGRkZREZGKl1KmSssLMTFxYXs7Gz2799PjRo18PDwUKye6tWrM2jQIFJTU9mwYQMTJkzA0dGRvLw87O3t0Wq1qFQqnJycUKlUGI1GHB0d0Wg0WFlZYWtri9FoRK/XW8aBaTQaVCoVjo6OD4y5UqvVdOrUidzcXHbs2MGOHTuIiYmp8C2jer2e48ePc+7cOdq2bUvnzp3x9fVVuizxEPLz81mzZg2//PKLBDKFSSATohJQqVT07duX5557TulSykVubi5fffUVX375JRcuXOCZZ56hUaNGitSiUqlo1KgRLVq0YPHixfj5+REVFYWnpyf79+8nIyMDrVbL5cuXcXBw+I/3Y2NjQ7Vq1bh+/Tr37t2jqKiIkydPPhC2zGYzKpWKp556ioiICJ5//nk2btxIYGBgeTzUv+Xu3bskJyezdu1avL29+fjjjxXtYhZ/TVZWFl988UWFD/2PAglkQogKx93d3bIa/PLly5k4cSLjxo2jT58+5boIrEqlsoyxiYiI4MqVKyxfvpygoCDatm3Lnj17mD59Ou7u7mRlZREREcG5c+fQ6/UP3Af82hXZqVMnFi9ezBtvvIGdnR137tyxtJb91rp28OBB9u7di8lk4t69e/zrX/+iuLj4T2cvpqSksH79ek6cOEFaWhozZsygX79+dOnSpVyepytXrhAfH8+PP/5IREQEQ4YMkb1EhfibJJAJISokW1tbunTpQu3atUlISODdd98lNTWV0aNHl8tYOpVKRb169Xj++efx8vLC2dmZ6OhogoKC8Pb2xsPDg1dffZXz58+j0+nw9vamSZMmZGZmWhaTdXR0JCoqCvg1kIWFheHk5ERaWhouLi54eXmh0+lwdnbGZDLh4OBAo0aNMJvN5OXl0a1bN1q0aMHdu3cJDw//Qwucj48P3bt3p2vXrsCvrXB169Yt88HZRqOR48eP89FHH1FQUMDo0aPp3r277HEpxD8gK/ULUQk8+eSTBAYGMmvWLKVLUUR+fj67du1i7ty5NGzYkClTptCgQYNyOfdv3Yj//jP8/5Yvo9GIyWSytHT9/vif/fxbYFOr1Q90FT3sfSpJr9eTnJxsWXds/PjxBAcHY2trq3Rp4m/IysqiZ8+eLFiwgM6dOytdziNN5rgKISo8Z2dn+vXrx9KlS7l9+zbPPPMMu3fvtsx6LEu/D0G/dS/+xsrKCmtra8ttvz/+Zz9bW1tbWrF+O/5X7lMpZrOZ999/nxdffJEePXrw/vvv06xZMwljQpQCCWRCiEpBo9HQrFkzli1bRqtWrRgzZgxr1qyhsLBQ6dKqPLPZTHZ2NpGRkSxbtoz58+fz5ptvluuuCUJUdTKGTAhRqXh5eTFz5kwCAgJYsGABqampjB8/npo1a1aIVqSqprCwkAMHDvDGG2/g7OzMnj17CAgIULosIaoc+WojhKh0HBwcGDt2LHPmzOHo0aM899xzHD58mOLiYqVLqzJMJhMZGRksW7aMN998k4iICLZt2yZhTIgyIi1kQohKSaVS0b17d+rWrcu8efOYMGECo0ePpk+fPhViS6HKTKfTcfr0aVavXs3PP//Mc889x6BBg9BqtUqXJkSVJYFMCFGpBQQE8P7777NmzRo+++wzzp07R3R0NE2aNJHxTX9DQUGBZcNyJycnpk6dSqtWrWRvSiHKmAQyIUSl5+TkxNixYwkMDGTt2rXMmDGDkSNHEhERgZ2dndLlVRq5ubl88skn7Nu3j7CwMIYMGUK9evUk2ApRDiSQCSGqBLVaTdeuXalVqxbr169nwYIFpKWlMWTIENzc3JQur8JLTU1l5syZZGdn8+yzzxIRESHPmxDlSL72CCGqDCsrKxo0aMALL7zAsGHD2LhxI1OnTuXq1auyV99/YDabSUxMJCoqCqPRyIcffshjjz0mYUyIciaBTAhRpahUKtzc3BgyZAizZ8/mypUrDBkyhFOnTildWoVTUFDA9OnTeemll4iKimLZsmU0adJEFnoVQgESyIQQVZKNjQ3t2rUjISGB+vXr07VrVz7//HNpKfs/aWlpPPPMM6xfv54VK1YwZcoUqlevLmu5CaEQCWRCiCrN1dWVlStXMm3aNF588UUmTpzIzZs3MRqNSpemiOLiYnbu3Mmzzz7L/fv3SUxMJCIiQoKYEAqTQCaEqPLUajXPP/88Gzdu5NSpU4wbN44ff/zxkdp2yWw2k5mZyerVq5k5cyYtWrRg8eLFsjyIEBWEzLIUooIxGo1kZGSQkZFhue3WrVtcv36dgwcPAr8GDC8vL+rUqaNUmZVSWFgYK1euZO7cubz77rs88cQT9O3bFw8PjyrfQnTq1CnWrl3L8ePHGTFiBAMHDqRatWpKlyWE+D8SyISoYIxGIykpKSxYsMDSgnPlyhXOnj3LyZMnAXBzcyM2NpbatWtX+SBR2urWrcv06dNZv349mzdv5ueffyY6Opr69etjZWWldHmlTqfTsWPHDj799FPs7e15/fXXCQ8PR6ORy78QFYm8I4WoYGxsbPDz80OtVnPixIkHjmVlZaFWqwkLC6Np06YSxv4md3d3YmJiqF+/PmvWrGHGjBnExMTQuXPnKhVUbt68SXx8PJs3b6Znz54MGzaM+vXrK12WEOJPVJ0rjxBVSHBwMD179uTEiRPcu3fvgWPOzs706dNHNnn+hxwdHenevTu1atWyjKtKTU0lNjYWa2trpcv7x44ePcqiRYu4fv06L7/8Mj169JAuSiEqMBnJKUQFZG9vT8+ePWnatOkDt6tUKurUqcPgwYOrZPdaedNoNDRq1IhXXnmF6OhoVqxYQWxsLJmZmUqX9reVlJSwadMmJk+ejFqt5r333uPxxx+XMCZEBSeBTIgKqlmzZnTu3BknJyfLbdbW1gwfPpyaNWsqWFnVolKp8PDwYOjQoaxatYrU1FQGDBhgmUBRmdy9e5dFixYxffp0IiIimDFjBs2bN69S3bBCVFUSyISooKytrRk0aNADY348PT0ZPXq0jB0rA7a2toSGhrJr1y6aNGnCk08+yapVqzAYDEqX9lCysrJ4+eWXWb58Oa+++iqTJ0/G19dXlrQQopKQr01CVGBNmzalW7duXLhwgaKiIqZMmfJAi5koffb29ixYsIDmzZszb948Ll26xNixY/Hx8amQ3cQlJSWcPn2al19+GWtra+Lj42nTpo3SZQkh/iL56iREBaZSqXj66aepU6cOgYGBjBgxQumSHgl2dnaMHDmSuXPncvToUd544w0OHTqETqdTurQHZGdnk5CQwIgRI2jUqBGrV6+WMCZEJSUtZEJUcAEBATRt2pS6detiZ2endDmPDBsbG3r06IGPjw+LFi1i1qxZDBs2jN69e1O9enVFazMYDJw/f54VK1Zw8OBBxo0bR0xMjGwKLkQlJoFMiArs1q1bbN++nevXr5OdnU1iYiKRkZE4ODgoXdojQaVS0aRJE6ZPn05CQgIrVqwgNTWV6OhoxZYduXfvHrt372b16tVotVrmzJlDeHi4IrUIIUqPBDIhKiCz2czly5eJj4/nyJEj9OjRA4PBwPz58zl//jwjRoygdu3aSpf5yPDy8mLcuHEEBgYSFxfHK6+8wpgxY4iIiCjXcWU3btzgs88+Y9euXbRq1Yro6Gjq1atXbucXQpQdCWRCVDB6vZ6UlBQWL16M0Whk3LhxdOvWDYDQ0FDi4uK4ePEi48ePp23btjLjspzY2dnRp08f6tatS3x8PDNmzODSpUsMHz4cZ2fnMj23yWTi/PnzLFy4kIyMDKKioujTpw+urq7y9xeiirCaNm3aNKWLEEL8qqioiMTERObMmUPdunV54YUXaNeuHXZ2dtjY2FC/fn2Cg4M5e/Ysn3/+OXZ2dvj7+1eJleUrg9/WLGvevDmOjo7Ex8dz8eJFGjRogIuLS5mc02g0smfPHt58801sbGx44YUX6N69O87OzhLGxD9WWFjIunXr6NWrF35+fkqX80iTQCZEBVFcXMyMGTNYuXIlUVFRTJgwAT8/vwcW9VSr1Xh6etKiRQuKi4tZunQp9+7do1GjRjLgvxzZ29sTFB0ZeNAAACAASURBVBREUFAQW7du5euvv8bf3x8fH59SDUlms5mFCxcybdo0unbtytSpU2nYsCE2Njaldg7xaJNAVnGozGazWekihHjUZWZm8tRTT5GZmcmiRYuIiIj4nwt6GgwGkpKSmDp1Ko0bN2b+/Pl4e3uXU8UCfg1MV69e5Z133mH//v3MmjWLvn37lkpgysvLIzY2ll27dvHxxx8TFRUli7yKUpeVlUXPnj1ZsGABnTt3VrqcR5q8u4VQUFFREdu3byc8PBw7Ozt27dpF9+7dH+qDV6PR0L9/fxISEsjPz+exxx7j0KFDlJSUlEPlAv7/3qLz5s1j5MiRvP7668yZM4dbt27xd7/r6nQ6Dh48SGRkJGlpaezfv58hQ4ZIGBOiipN3uBAKMBqNZGRkMH/+fF577TWioqLYunUrtWrV+sv31axZM9asWUNYWJhlg+ysrKy/HQjEX+fo6MikSZN4//33SUpKYuzYsZw5c+YvhWOz2Uxubi6rV6/mxRdfJCQkhG+++YagoKAyrFwIUVHILEshyllxcTEnT55kxYoVXL16lbfeeovHHnvsH20A7e7uzty5c2natCnLly/n1KlTjBkzhkaNGsmA/3KiVqvp378/gYGBvPvuu8TGxvLCCy/QrVs33Nzc/uvv6vV6Ll68yJo1azh69CgjR45k2LBhODo6llP1QgilyRgyIcrR3bt32b59O4mJibi6uhIbG0tISMg/CmO/d+jQIRYvXsy9e/d4+umniYiIoFq1aqV2/+J/y8vLY+nSpXzzzTd07NiRoUOHEhgY+KcD/ouKiti9ezefffYZBoOBUaNG0aFDB7RarQKVi0eNjCGrOGSWpRDlwGw2c+PGDZYtW8b27dtp164d48aNIygoqNQXFvX19aVFixZkZWWxbds2cnJyqFOnjiyTUI60Wi1t2rTB1dWVPXv28OOPP+Li4oKPj88D4Ts/P59PP/2UhIQEAgICeP7552ndurW0aopyI7MsKw4JZEKUgxMnTjB9+nR++eUXYmJiGDRoEN7e3mUSkFQqFdWrV6dZs2bY2dmxc+dOjhw5gp+fHzVq1JDB4eXEysqKgIAAGjRowOXLl9m8eTMmk4l69eqh1Wr55ZdfePvttzlw4ACDBw8mOjqaunXrSmgW5UoCWcUhXZZClCGTycT69euZP38+ISEhvPDCC+W6jlRRURGnTp1i6dKlXLt2jYkTJxIZGSmhrByZTCaysrJITEzkyy+/pHXr1jRu3JgVK1bg6urKq6++SkhIiKwjJxQhXZYVhwQyIcpIXl4e77zzDhs3buTFF19k6NChimx1YzQaycnJYdmyZaxfv57o6GheffXVct2DUcD9+/c5cOAAM2fO5Pz584wePZoJEyZIq6VQlASyikNmWQpRBi5cuMDkyZP55ZdfWLduHW3atFEsAFlZWeHl5cXUqVNp0aIFzz77LIcPHyYuLg5PT09FanoU2dvbExERQUhICPn5+dSqVUtW3BdCWEgLmRClSKfT8e233zJr1ixq1qzJnDlz8PPzq1DjgtLT03n66acpLCxkzpw5hIWFSTAQ4hFx/fp1kpKSyM3NxWw2U1hYSHx8PJGRkZYxZG5ubgwcOBAPDw+Fq320SCATohSYTCYyMzP54osv2LBhA7169WLcuHEV9oKWn5/PjBkz2Lt3L08//TRPPfUU7u7u0nUmRBVXWFjIsGHDSEpKwmAw/OG4Wq0mNjaWadOmVdjrV1UlsyyF+IdMJhPHjx9nyZIl/PDDD8TGxjJq1ChcXFyULu0/srW1JSwsDAcHB7788ksuXbqEt7c3rq6uMrZMiCrMxsYGBwcHvv32WwoLC/9wvFatWrz00ks0bdq0QrXsPwqkhUyIf6CoqIjk5GRWr16Ns7MzsbGxtG/fvtKEmpKSEn788Ufi4uIwmUxERUXRo0cPmfEnRBVWVFREVFQU27Zte2CLNSsrK0aNGsXbb7+Nj4+PghU+miSQCfE3Xbt2jfj4eL7++msiIyMZNmwYdevWVbqsv8xsNnPhwgXWrl3LTz/9RI8ePYiJianQLXxCiH/mu+++o0+fPhQXF1tu8/f35/333+fxxx+X4QsKkEAmxF9kNps5dOgQS5YsITs7m9GjR9OjRw+cnJyULu0fyc3NJTk5mVWrVlGnTh0mT55McHCw0mUJIcqATqdj8ODBbNq0CQCNRsPQoUOZPXs2Xl5eClf3aJIILMRfUFRUxIYNG3j99ddxdHTkvffe4/HHH6/0YQx+3aD8ySefZPbs2RQWFvLss8+yadMmTCaT0qUJIUqZra0tU6dOxdbWFoDatWsTGRkpS+EoSAb1C/GQcnJy+Pjjj1m1ahUDBw5k/Pjx1K9fv0o17Ws0Gnx8fAgPD6egoICPPvqIvLw8QkJCLBduIUTV4OHhweXLlzl37hxdu3blxRdflPGjCpIuS1Fh6HQ69Ho9jo6OwK9dgzqdDvj125ySM37S0tJ47bXXuHTpEtOmTaNHjx5VPqDodDp27tzJa6+9RosWLZg2bVqlHCMnhPjPTp48ycCBA3nvvfcYOHCg0uU80so8kF24cIGPP/6YnJycKtWS8KjQ6/UMGjSIqKioMj/Xtm3beO6550hMTKRFixacP3+eOXPmEBoayjPPPIO9vX2Z1/B7er2elJQUJk6ciKenJ++88w5NmzYt9zqUYjabOXXqFFOmTKGkpIRp06bRrl07rK2tlS5NiHKh1+t59dVXuXbtWpX8DDMajWRkZODr61tpZof/FSaTiVatWjF8+PAKPzauzLdOunz5Mp9//jldunSRneQroS+++AK9Xl8ugSw8PJymTZuyZs0a/P39OXLkCDqdjnbt2qHT6cjJycFoNOLs7Iyrq2uZXxxzc3NJTEzko48+IjIykilTplCjRo0yPWdFo1KpaNasGcuXL2f+/PlMnjyZMWPG0K9fP9zc3JQuT4gyd+fOHVauXEmHDh1o3Lix0uWUCX9/f6VLKDPnz58nKSmJjh07SiBTq9W0bduWGTNmEBQUVNanE6VMo9Fw9uzZcjmXs7MzY8eOZdq0aXzzzTccPHiQ0NBQ3Nzc+OKLLzh69Cj5+fm4urry6quvUrt27TKpQ6/Xk5qayuLFi0lJSWHSpEkMHz78kW4Vql27NtOnTychIYEVK1Zw4cIFoqOjadiwoSweKR4Js2bNIiQkROkyxF+UnJzMmjVrlC7jocjm4qJCCQ8PJygoiGXLluHl5UVERAQ2NjbUrFmT5s2bU1RUxPjx42ndujUjRowo9fPn5eXx/fffs3LlSpycnFi6dClt2rQp9fNURs7OzowePRp/f3+WLFnClClTGDt2LJ07d5aBwEII8Q9JIBMVioODAwMHDuTll18mIiKChg0bWmb+HT9+nJycHEpKSsjOzi71c6enp/PZZ5+xZ88e2rVrx6hRo6hZs2apn6cys7KyokePHvj5+bFy5UreffddUlNTiYqKwtvbW+nyhBCi0pJAJiqcwMBA6tSpQ2BgIFqtlpSUFBISEvD19cXLywsHBwdKcy6K0Wjk5MmTLF26lFu3bjF8+HD69OlDtWrVSu0cVU1gYCBvvPEGmzdvZv369Vy4cIHY2FhCQkKkC1MIIf6GqjdlRFR6arUajUaDRqPBZDJx4cIFsrKy6NGjB506dSrVMFZSUkJSUhKvvfYaAJMnT+aJJ56QMPYQnJ2diYqK4o033kCn0/HGG2/w9ddfW5YqEUII8fCkhUxUOCqVyjKDUq1WExQUxJdffsn48eNxcnJCo9GUyvRso9HI3Llz+fzzz3niiScYNWoUXl5eVXLqd1mxsbGhffv21KxZk/j4eGbMmEFaWhrR0dE4OzsrXZ4QQlQaEshEhVO3bl0SEhKwt7dHrVbTokULEhISuHPnDs7OzqjVamxsbP7ROXJzcxk5cqRlrbPIyMgqv9BrWbGyssLPz49XXnkFf39/Zs+ezalTp5g9e7YsjSGEEA9JuixFhWNlZUX16tUtocvKyopq1arh5+eHq6sr1atX/9uLxBoMBvbt20enTp3Izs5m586dPP744xLG/iGVSoW9vT3Dhw9n1apVnDt3jt69e5OamorRaFS6PCGEqPAkkIlHgslk4tatWyxZsoTx48fTs2dP9u7dS7169ZQurcpp3bo1iYmJBAcH07t3b0vrphBCiP9MuixFlVdSUkJqaiorV67k5MmTTJo0iaioKGkVK0NeXl588sknLF26lI8++oiTJ09a1jDTaOSyI4QQvyctZKJKKygoYMeOHbz33nvk5OQwY8YMhgwZImGsHFhbWzNhwgTmzp1Leno6b731Ft999x0FBQVKlyaEEBVOlfiqajQaMZlMaDSaR2oNpJKSElQqleJb+qSlpVFSUkKDBg0UreP3cnJyWLt2Lbt27SI0NJTo6GgCAgLKfA9Mg8GASqWyzNbU6/WoVKpSaRm6ffs2J0+epEmTJpZxW3+2Sr7BYODu3bvY2dnh4ODwwDGz2cy9e/cwm804OzuX+XsmPDwcX19fVqxYwcKFC7l06RKDBg3C09OzTM8rRGViNpst4y2lFfnRVOn/6mlpaSxYsID79+9ja2tLUFAQvXv3pk6dOuUezm7fvk1mZiYNGjQo06UTDAYDBw4c4KuvvqJjx44MGDCgzEPGn7l69SrJycns2LGDbt26VahAlpqayrx580hPT2fIkCFERkaWy8bg+fn5JCcn4+DgQEREBHfu3GHZsmV07NiRbt26/ePX5LVr11iyZAnDhw/n5MmThIeH06FDhz/8/TMzM/n0009p2bIlvXr1shy/du0a8fHxXLhwAY1GQ1hYGAMGDMDV1fUf1fXfqNVq6tevz6RJk9i8eTPbtm3j0qVLjBs3jvr16yvy2hWiIikpKSExMZH9+/ej1+txdHSkU6dO9OzZ829PYPq7zGYzmZmZ6PV6fH19ZRmgclTpr4TXr18nOTmZ0NBQmjRpwp49e/jss88UGUR88OBBPvjggzLtkikpKWHNmjXExcXx3XffcfTo0VJdKPVhZGVlsXz5cstG4Fu3bq0wg7bNZjObNm0iJiaG/Px8pk2bxlNPPVUuYQzg/v37HD58mBMnTpCbm8uSJUs4ceIEtWrVKpX7Ly4u5ubNmzg5OdGhQwdq1679pyHP2dmZjh07EhAQ8MDxrKwsrKys6N+/P35+fqxdu5YffvgBk8lUKvX9JyqVCg8PD4YOHcpLL71EVlYWL7/8Mnv37i3T8wpRGej1evbt28edO3eIjIzE3d2dJUuWsGvXrnK/vptMJnbu3Mlnn30mwwvKWaVvITOZTNjZ2dG5c2d8fX25c+cOqamp5Obm4uTkRHJyMlu3bkWr1dK/f3/at2/PsWPHSE9PJy0tDWtra5566ik2bdpEo0aN2LVrF1ZWVvTq1YucnBxcXFwICwtDq9Vy8OBBzp49S0REBN9++y1HjhzB0dGRgQMHolarWb58OYcOHcLZ2ZnevXvTqVMnfvrpJ5KSksjOzqZFixYMGzYMrVbLli1b2L17NyqVip49e9K9e3eysrLYv38/bm5uJCUl4ebmRnR0NIGBgZbHq1arCQkJoVWrVkybNq1cWwELCgr46quvWL16NWfOnOH27dsVakmDe/fusWDBAtavX8/QoUMZOXIkPj4+inRj6/V6Pv/8c44dO8Ybb7xh+RvevHmTxMREjh8/jpeXF4MGDaJ27dp89tlnBAcHs2PHDoxGI0888QStW7dGrVZz4sQJNmzYwL1792jatCkAOp2OO3fuWILmlStXWLt2LRcvXqRdu3b069fPEtz+XXBwMAEBATg7O1O/fn1+/PFHrl27Vm4XfQcHBzp27EjdunVZtGgR48ePZ8yYMTz33HPSUiYeWWazGZPJRL169YiMjKRNmzacPHmSI0eOWD6LvvrqK44fP069evUYNWoU1apVY+vWrRQXF3Pp0iWaN29O9erVyc/P59atWxw4cIDGjRvTq1cvjhw5QmhoKE2bNuXevXskJiYSEhKCRqNhw4YNXL9+neDgYB5//HEyMzMtt6WnpxMTE0NgYCBbtmzhhx9+wNramj59+hAeHo5Op2PTpk3s27cPW1tb+vTpQ+fOnTl+/DhZWVncuHGDs2fP0q5dO4YMGWJZyig/P5/vv/8ea2trOnfuTE5ODomJiQwdOhQvLy+F/xrKqfSB7N+pVCoMBgPW1tZoNBo+//xzVqxYwdixY7lz5w5z5sxh/PjxXLx4kaVLl9KmTRu6du1KYWEhy5Ytw9HRkQEDBpCamsonn3yCq6srRqOR+vXrW2aNubi44O/vz9WrV+nSpQsHDx5k0aJFxMTEULNmTRwcHAgODsbb25ucnBxOnjxp2ZdxxYoV2NvbEx4ezqFDh+jQoQNXrlxh9erVODk5oVarmTt3Lq6urgwePJjk5GRmz57Nhx9+iIuLC/Dr2IKQkBAMBsM/Xhz1Yf3W6vTBBx9w+vRpioqK/tCikpGRwU8//VQu9fyZzMxM4uLi+Pnnn/nwww+JiIhQbOC+2WzmwIED6PV6Jk6caAlWubm5zJkzh7S0NCIjI0lJSWHq1KlMnDiRlStXUlJSwuDBg/nll1+YN28es2bNAuDtt9/G29ubRo0asWjRIlQqFTk5OezZswdHR0dq167NRx99RElJCUOGDOHq1atkZmaya9cuTCYTzZs3t4RSe3t77O3tMZlM3Lt3D71ej6enZ7mGVo1Gg5+fHzNnziQ0NJSXXnqJ/fv3M3bs2Edmdf9atWrh4eHxSI15FQ9PrVZTXFyMvb09OTk5fPzxx5bWs6SkJCZNmsTs2bPZsGEDqamp9OzZk2rVqnHy5EmWL19Oy5Yt6dChA8uXL+fatWvodDpu3rxJYGAgp0+fZuPGjQQEBLB3717c3NwIDg5m69at5Ofn069fPzw8PCgpKSE4OBg3NzeuXr3KqVOn6NSpE+fOnSMuLo7q1auj0+m4ePEi/fr1IzU1lQ8//BCtVsuJEyeIi4ujS5cueHt788477+Du7k6fPn0A0Gq1FBQUWBpLkpOTKSwspHr16go/88qqEoHs1q1bLFu2jLy8PFJTUxk3bhwODg4kJyfTt29fHnvsMfLy8jh//jyHDh3C0dGRtm3b8uabb9KwYUNLC8HkyZMZNGgQO3fuZP369Xh5eZGSkkJaWhrFxcUcPnyYjz76iM6dO9OxY0eMRiPu7u4sX74cZ2dnWrduzfHjxxk0aJBlhfJx48ZhMBgoLi4mJSWFixcvEhMTw9y5czEajZw/f5709HRu3ryJh4cH1apVY+7cubRo0QIfHx+WL19uaan7TXm3JPzyyy8MHjwYvV7/H7u2VqxYwapVq8q1rt8zGAysXbtW0TD2Wx2nT58mODjYssyD2Wzm559/5ty5c0yaNIlu3brRoUMHXn75Zc6cOYPBYGDy5MkMHz6cAwcOsGTJEq5du0ZmZiY2NjZMnDiRBg0aEBQUxNSpUzGZTBgMBsv/5+Xl4erqSps2bejRowfp6emW43+moKCAxMREvLy8CAsLU6R1ys7OjqioKPLz83n++efZtm1budegBKPRSNeuXdm8efOfTsgQjyaz2czhw4eZNWsWhw8fpqioiL59+/Lzzz+TlZXFU089RefOnfHy8mL06NFcu3YNa2trHn/8cd566y1sbGxITU2lWbNmvPPOO9SqVYusrCzOnj1L69atOX36NOnp6Rw+fBhvb28aNGhAWFgYBoOB+/fvc/fuXU6dOoWnpyeNGjXC2dmZwYMHWz7L3nvvPYxGI8ePH+fatWtkZ2cTGRlJWFgYRqORxo0bc+TIEcvnadeuXZkyZQoeHh6cOXOGn376icjISMtOK127dmX//v289dZb6PV6PvnkE7RarcJ/BWVViUBmMpkoLi6mWbNmPP/88zRr1ozc3Fyys7NZunQpGzduBLB0WxYXF+Pp6flAd85vq8OrVCq0Wi0ajYagoCAuX77MTz/9hFarpUaNGoSGhnLx4kU+/fRTjh49SmZmJlZWVn/a5ZOXl8f27dvZtGkTN27c4PLlywwePNgSIPfv3092djbFxcV07NjRUqOjoyOAZXac0t2C/v7+rFu3jnnz5rFz505u3779hw2kX3nlFSZNmqRQhb8+18uWLWPWrFnk5uYydOjQMh2o/t9YW1vzxBNPkJGRwSeffMLbb7+Nm5sb+fn5mEwm3N3dAXBxccHe3p78/HxUKhUuLi6oVCpsbW2xtrZGr9dz584dnJycsLe3R6VS4ezs/IdZtdWqVePZZ59l1qxZ9OrVi6effppOnTr9x/qKiopYvXo1p0+fZtasWXh7e5fp8/FnTCYTubm5LF68mLi4OKZOncqYMWMeieVIli1bxr59+8p9bJCo2MxmMzqdjpKSEp588kl69+6Np6cn27dvt3RfOjs7Yzab8fX1xcbGBq1Wi4+PD7a2tpbXk6OjI7a2tqjVapycnLC2tiY4OJgTJ07www8/cObMGdq0aYO9vT3JycnEx8dz48YNsrOzad269Z++LjMyMoiLi+PHH38kKysLo9HIgAEDSE9PZ+XKlaSkpHD37l0KCgro3bs3arUaBwcHS2+Vg4MDer3+gfv28PAgLCyM7777joiICOrWrVtuz3VFVSUCWY0aNXjxxRcJDg623GZra4ubmxsRERFMmjQJjUaDXq+nsLCQTz/99KHu183NjZYtW7J7927y8/OJjIzEzs6OrVu3cuXKFRYvXkxaWhqffPIJ8GvLlcFgsCzDcebMGTZt2kSfPn3417/+xWuvvYZGo+Hbb79ly5YtLF26FCsrKz766KMK33XRtGlTli9fzuHDh1m9ejX79+/n2rVrFBcXA7+2dvx7K155c3FxYebMmTRq1IiFCxdy7NgxXnrpJRo2bKjIsiDe3t707duXOXPmkJCQQGxsLA4ODpjNZssFLTs7G51Oh5ub25+2UKlUKpycnMjPzyc/Px+9Xs/169cxGAwP/Duz2UyzZs3YuHEjW7ZsYerUqf8x2Ny7d4+EhAQ2bdrE66+/TsuWLTGbzeX6+isqKuL06dMsWLCAa9eusWLFCiIjI8vt/EpzcXGRmWviD9RqNZ06deKtt96yvH/NZjMODg40atSIIUOG0KNHD6ysrCguLqawsPCh77devXp4e3uzZcsWbGxsaNq0KXl5ebz22muMGDGC6OhoEhISOH36NPDrtee3HhGz2cyOHTvYt28fCxYsoLCwkEWLFmEymVi3bh3Hjx9n9erV3L9/n8mTJz9UTWazmYyMDI4dO0ZAQABnzpzh1KlTdOzYscJ/FpalKhHI/uwP6OTkROfOndm+fTtr1qzB2dkZo9FIgwYNHuqb6W/rRoWFhbFhwwZu3rzJ3LlzUavVaLVaSkpK2L9/PxcvXiQvLw+VSoWXl5elK6h9+/ZoNBpsbGy4fPkymzdv5vLly7Rq1crSAnLkyBFu377NjRs3/uuL8N+PGY1Gjh49SmpqKunp6dy/f59t27bRqlUrfH19/94T+JBsbGzo2LEjoaGh/PjjjyQmJvLDDz9w8eLFMj3vw7K2tmb48OE0bNiQDz74gJdeeokxY8YQERFRbmMTVCqV5X+tWrVi5MiRLFy4kPr169OkSRMCAgL48ssvuXHjBufOncPDw4Pg4OA/fECrVCrUajVNmjQhKSmJhIQEAgIC2L17N0aj8YHXxL1799i1axdGo5G7d+9Sq1atP6w9Br9eBPfu3cusWbMIDw/n2rVrJCQkUK9ePVq0aFEu3We5ubns2LGDDRs24OXlxfLlywkKCirz8wpR0f123fj9bb+Fqe3bt3Pnzh3UajXW1ta0b9/+f97Hb//t5uZGUFAQmzdvpmvXrtSuXdvSK3Tjxg2SkpI4fPgwWq0WtVqNp6cnu3fvJjExkR49eqDValGpVBw6dMjSmqZSqXB0dLSMmb1y5Qp37tx5qEB1//59du3axf3795kyZQpfffUVcXFxNGrUyNJF+iiymjZt2rSyPMHly5c5cuQIPXr0KJOlB8xmM1qtlrZt2z7wIWRlZYWfnx/w65pU2dnZmM1m6tevj4uLCz4+PgQGBj7wTaRt27a4ublhMplwdHQkKCgIT09P9u7dS61atRg5ciRarRYXFxcKCwvJzs7G29ubZs2a0bx5c2rXro3JZCIjIwMfHx8aNWqEVqslKysLg8Fg+Xft27fHZDJZZsGFhIQQGhpKjRo1cHBwoHnz5jg4OGAymXBwcCAkJMTy2EwmE0ePHuXUqVPUqVOHGjVqoNPpqFOnDm5ubqX+7eL7778nJyeHqKgoy202Njb4+/vTqVMngoKCqFatGg0bNiQkJKRUz/13+fr60rlzZ3Jzc9m4cSM5OTnUrFnT0iVd1lQqFXXr1iUgIIDAwEBLMG/evDm1atUiJyeHK1euUL16dQYNGkTDhg1Rq9W0atUKd3d3y2v6txmRLi4upKWlcefOHTp37kzjxo0JCQmxXGRdXFxITU3l7Nmz3Lp1i8jISDp16oRWqyUoKAhvb2/L4/7tNefs7Mzt27e5ffs2Dg4O+Pv7l2l3oclk4ueffyYuLo6dO3cSHh7OxIkT8fPze+S+Ef/0009cvHiRQYMGKb6os/jfCgsLWbhwISNGjCjTGYBGo5GAgAD8/f0faDF3cnLCy8uLW7duceXKFXJzcy3vfbVaTVBQkGVZHaPRiKenJ0FBQdja2mIwGPDy8qJZs2YUFBRw7tw5unXrRps2bSz3e/36dXQ6HQH/j737Dqu6/v8/fj+DcQDZS0FQWaKiOHJmKaYopoKZaGrL9GPmTC1XjtwDS3OmuEehlh8zzczK/JjlHjkBCRTFRAHZHM45vz/6cn7iaAKH8bxdl9clZ7zfz3M4nPM4r+nrS7NmzYyfe9nZ2Vy/fh0/Pz8aNGhAQUEBKSkpODg4EBwcTNOmTalXrx55eXlcv34dGxsbmjdvTqNGjXB1daVGjRr4+flhYWGBVqslICDAuAxPXl4ed+7coWHDuhOi3QAAIABJREFUhrRq1QofHx8yMzOpX7/+IzPD/624uDjOnj1Ly5Yt8fT0LNFjlzSFoZQHMuzbt49ly5axYMGCUvsmrNPp/rALoGhWYNE4nKKH/HDLU9ExHnxK4uLiGDVqFJGRkQwYMMB4n6IB00UrKhd9M9HpdOTl5aHRaFAqlRgMBrRaLSqVqljriV6vR6vVGt+Qi45rMBiK/THq9XqTLgcwefJkLly4wOeff/7E26Snp5OdnV3qLXR/V3Z2Nnv27GH79u1Uq1aNwYMH06xZs1L/EHz49WUwGIr9XgsLCykoKMDMzMxYy8O/Z71eb3ytFI0tKRpfVnTbh2/zYPfxw8cwpcLCQn7++WdWrVpFXl4effv2pUOHDlVmRuXDVq5cyZ49e4iJiSnzRT/F3/fbb7/h7+/P999/X6pfOv/s77Xos8XMzMw4w/7h+zzpvUen0/H555+zZ88e3nzzTVq0aGF8vyna8aVo8lHR5VqtFq1Wi0ajMX62Fa1iUHSOos+y/Px8LC0tHxn+UPT/xz22hy/7s8/xf2rfvn1s3LiRkSNH0rJlyxI/fkmqFF2Wf/ZLfLgr5nEv+AeP8eCLOSMjg2bNmj3St/2krS1UKlWxljqFQvHY5SmUSuVjWyQerq0irM1kb29fLqcrW1tbExERQe3atdmwYQPTp0/ntddeo1u3bqX6Qfi4boeHXzsPv34e/j0/+HPRRJOHr3v4Ng+/zsvDa8dgMLB582Y2bNhA/fr1efvtt6lXr16ZLdkiREXxZ3+vD3+2PO4+T3rvycvLQ6VS0bZt20d2x3jwb/HB+z/4hbHo/I/7rFUqlcb3nieFycc9tocvk3GVlSSQlRaFQkG9evWoVatWuQwc4s+Zm5vTtGlTPDw82LJlC1FRUVy6dImxY8caZ7OK0pGRkcGkSZP47rvvGDJkCL1795a1t4QwAUtLS5577jmAEu8SFCVHAtmfKFpIU1RcKpUKDw8PRowYQWBgIFOmTOHEiRNER0fLBtel5JdffmHYsGGkpqayZs0amjRpUiWWtBCiPFIqldjZ2Zm6DPEnTN+nIUQZsbS0pFu3buzatYvs7GwaN27MoUOHSn0fx6pEp9OxY8cOwsPDcXFx4ejRo7Rq1UrCmBBC/AkJZKLK8fb25quvvqJ///68/vrrREVFce/ePQlm/4JOp+PWrVvMmTOHGTNmMHjwYOOWYEIIIf6cdFmKKsnCwoJ58+bRtGlTli5dSlxcHEOHDqVu3brSmvM3FRQUcObMGaKjo4mLi2PatGl06dKlym+DIoQQf4e0kIkqS6FQ0KtXL6KiosjJyWHGjBl8+eWXZGRkmLq0CiMzM5Ndu3Yxa9YsCgoKmDt3Lt27d5cwJoQQf5O0kIkqTaVS8dRTT/H++++zfv16YytPv379qFGjhswI/AM3btxg/fr1fPvttzz33HP069cPb29vU5clhBAVkgQyUeUVraw/YsQI47Y+RV2Y5WX3gfLm8OHDLF++nLS0NIYOHUpoaKiMFxNCiH9BuiyF+D9OTk688MILTJo0iYKCAkaNGkVMTMxf2vu0qsjNzWXt2rVMmDABe3t75syZQ0REhIQxIYT4l6SFTIgHWFpa0qJFCzw9Pdm8eTOTJ0/m3LlzvPPOO1V2q58iN2/eZMmSJRw8eJCBAwcSEREh67gJIUQJKfVAptfrOXjwIP369Sv3G3uKR/3000/lfv+vkqZQKPD09GTkyJE0b96cUaNGcenSJebMmYO/v7+pyzOJs2fPMm3aNO7du8ecOXNo06bNI1s1CVEZFW3x07dvX/z8/ExcTcnT6XTcuXMHJyenSrnZ/c2bN437WJd3pR7IgoODWbBgASkpKaV9KpP46aefuHv3Lm3btq2ULSgNGzYkLCzM1GWYhEajISQkhD179hi3/pk/fz4dO3asEH/cJaGwsJCDBw8ybtw4AgMDiY6OxtfX19RlCVFmnJ2dmTdvHtevXzd1KaUiKyuL48ePU7duXby8vExdTolr2LAhwcHBBAYGmrqUP6UwyACZfyUqKoorV64wdepUPDw8TF2OKCV37tzhww8/ZO/evQwcOJA+ffrg5ORUqYNZamoqW7Zs4eOPP6ZXr16MGDECJycnU5dV4a1cuZI9e/YQExPzr7dl0+l0GAyGRzarB9BqteTl5WFlZfXYjZvz8/MpKCh44vWiakhJSaFTp04sW7aMtm3bmrqcKk3GkAnxF7i4uDBx4kT8/f1Zs2YNCQkJvPbaawQGBla6D7PCwkJiY2OJiori/PnzTJgwgcjIyErZnVER5OXlcenSJfLy8opdbmlpSVpaGkqlkmefffaRLwenT59m7969vP7664+0fOj1eg4dOsTJkyfp27cvtWrVKvXHIYT4YxLIhPiLrK2t6d+/P15eXixbtowpU6YwaNAg2rdvX2kWQs3IyOC7775j8eLFODs789FHH9G8eXNTl1Wlpaens3btWhITE4mLi0Ov1+Pv74+Xlxc2NjbY2try9NNPP9JKdvfuXc6fP092djYGg6FYYDMYDPz2229cuXKF3NzcR64XQpQ9CWRC/A0qlYr27dvj6enJ2rVrmTVrFpcvX6ZPnz5Ur17d1OX9K9euXeOTTz7h66+/pl27dgwZMgR3d3dTl1Xlubu7s3jxYu7evcvSpUvJy8tjzJgxODk5ce7cOQoLC1GpVBgMBu7evcvZs2fJzc3lxo0b6PV69Ho9V65c4cqVKxQWFlK7dm0CAgKKnePevXucOnWK4OBgXFxcTPRIhajaJJAJ8Q/4+fkxfvx4AgMDWbduHRcvXmTw4ME0a9aswrU0aLVajh07RnR0NGlpaQwZMoTw8PBK0+pXGSiVSlQqFQqFAoVCYewm//rrr8nOzqZJkyZkZmaydetWfv75Z5ydnUlISCAtLY309HQOHjxIQUEBubm57Nu3j/79+6PX64Hfw9iOHTu4ceMG9erVM+XDFKJKk4VhhfiH7Ozs6NevH7Nnz0av1zN58mR27NjxyFif8iwrK4udO3cyc+ZMrKysGD9+PC+88IKEsQqgqNvx1q1b6PV6EhMTOXToEG3btmXw4ME0bdoUCwsLNBoNXbp04Y033qBfv34YDAZOnjxJYWEh2dnZrFu3jgsXLjBgwABpERXChKSFTIh/QaVS0bJlS6pXr86nn37KokWLiI+PZ+DAgeW+6+fevXssWbKEb775hh49etCnTx9q1KhR6SYpVAUGg4HU1FTy8/Np1qwZ9evXJyEhgbNnz2JhYUFycjJr167l+vXr3LhxA29vb+zs7Lh27Rq3bt1i6tSptGzZUn73QpiQBDIh/iWFQoG3tzdDhw7Fx8eHRYsWcenSJaZMmYKPj4+py3usGzduMHz4cFJSUhg/fjwdO3ZEo9FUuO5WUZzBYDBu9aVUKlEoFBw/fpwlS5Ywfvx4/Pz8iI6ORqFQYDAYqFOnDt7e3mzfvp0uXbpUynWohKgopMtSiBKgUCioVq0aL7zwAsuXL+f27dtERkZy/Phx41id8uLHH3+kTZs2ZGdns2XLFrp3715hVrIWj6dQKHB1dQXgxIkTJCYmsmvXLpKTk0lOTiY/P58WLVpgYWHBzZs3jaHN2tqakSNHYmFhwfjx48nJyTHlwxCiSpNAJkQJUigUBAcHs3HjRlq1akW/fv3YtGkTWVlZJq3LYDBw//59Fi5cSEREBC+++CL//e9/qVOnjgSxCkKpVFKtWjXs7OyM2/nY2tpib2+PUqnEx8eH8PBwli5dSteuXcnLyyMgIIBnn30WPz8/QkNDGThwIEqlEgcHB6ytrbG3t6dGjRrMnTuXq1evsmvXLmStcCFMQ7oshSgFrq6uREVFUa9ePebNm8eJEycYNWoU3t7ej11VvTQVFBRw9epVPvjgA86dO8dHH31E7969y7QG8e/Z29szevRoDAaDcazX5MmTUSgUKJVKrKyseOONN3jppZcwGAxoNBrjbVu3bk16ejrVqlUzhjmFQkFkZKSxa/Po0aPGmZxCiLInLWRClBJzc3PefPNNVq1axbVr1xg5ciTffPMNmZmZZVZDeno6X375JZMnTyYnJ4dVq1bx4osvltn5RckqWv6iiEqlMgYs+D1kWVtbY2Njg0qlQq1WGwObo6MjZmZmqFQq4/0eDGBmZmbFjiWEKFvSQiZEKWvbti21atXio48+IioqisuXL9OrVy88PT1L7Zx6vZ7k5GS2bdvGoUOHaNq0KQMHDsTLy0taQIQQohySQCZEGahZsyYTJ05k586d7N69m/j4eF5//XWCgoJKvAtTr9dz5swZPv74Y1JSUujbty9hYWE4OjqW6HmEEEKUHGmfFqKM2Nvb89JLLzF69Giys7OZNm0aX331Ffn5+SV2DoPBwI4dO5gwYQL5+fm8++679OrVS8KYEEKUc9JCJkQZ0mg0PP3009SsWZP169cb98IcNmzYv14dPzMzk3nz5vHf//6Xvn370r9/fzw9PWVckBBCVAASyIQoY2q1mjp16vDOO+8QGBjI3LlzOXnyJMuWLfvHLVmxsbGMGzeO2NhYPvjgA9q0aYO1tXUJVy6EEKK0yFdnIUygaCHZPn36EBMTQ3x8PC1btuT48eN/+1j79u2jZ8+eaLVavvnmGzp27ChhTAghKhgJZEKYkFKppG7duhw6dIiQkBAiIyNZuXIlWVlZf7hAp8Fg4N69e3z44YeMHTuWHj16sHXrVqpXry6zKIUQogKSLkshygGNRsPSpUvZsGEDK1eu5MqVK7z55pvUrl0bMzOzYrctLCzk8uXLREdHc/z4cSZMmEBERIS0igkhRAUmgUyIckKtVvPyyy/j4+PDkiVLmDZtGq+88gpPP/20MWzl5uby/fffGzeInj17Nm3atCm2WKgQQoiKRwKZEOWImZkZzzzzDO7u7qxevZolS5YQHx/Piy++iE6nIyYmhs8//5yWLVvy+uuv4+fnZ+qShRBClAAJZEKUM0Xjyt555x0+//xzdu3axZkzZ8jPzycpKYlXXnmFHj164ODgYOpShRBClBAJZEKUU25ubrz88sv4+/uzbt06zMzMmDlzJi1atCjzDcqFEEKULnlXF6Ics7Kyol27dvj5+aFSqahRo4apSxJCCFEKJJAJUc4plUpq1qxp6jKEEEKUIlmHTAghhBDCxCSQCSGEEEKYmAQyIYQQQggTk0AmhBBCCGFiEsiEEEIIIUxMApkQQgghhIlJIBNCCCGEMDEJZEIIIYQQJiaBTAghhBDCxCSQCSGEEEKYmAQyIYQQQggTk0AmhBBCCGFiEsiEEEIIIUxMApkQQgghhIlJIBNCCCGEMDEJZEIIIYQQJiaBTAghhBDCxCSQCSGEEEKYmAQyIYQQQggTU5u6gIomISGB7777DoPBAMCxY8dISUlh27ZtODg4AODo6Eh4eDgKhcKUpQohTMxgMJCUlMS3336LXq8H4MiRIyQlJbFhwwbMzc0BcHNzo127dtjY2JiyXCGECUkg+5sUCgWzZs3i2rVrxS7/4YcfAFCpVEyePJmIiAhTlCeEKEcUCgX379/n448/5qeffip23dChQwHQaDQMGjSIsLAwU5QohCgnpMvyb3J1dWXgwIGo1Y/PstWrV2fQoEFlXJUQoryqXbs2PXv2RKPRPPb6mjVr8vLLL6NUytuxEFWZvAP8TRqNhrCwMOrVq/fY64cPH46Hh0cZVyWEKK9sbGxo3749TZs2feQ6tVpN586dady4sQkqE0KUJxLI/iaFQkGdOnV48cUXsbCwKHZdQEAAr732mokqE0KUV4GBgYSGhmJra1vscjc3NwYPHiytY0IICWT/RLVq1ejQoQNBQUHFLh82bBguLi4mqkoIUV5ZW1sTGhpKgwYNil3+0ksvPbG1XQhRtUgg+wcUCgUNGjSgS5cuWFpaAtC4cWN69Ohh4sqEEOVVUFAQISEhxlYyNzc3hg0bJrOxhRCABLJ/zMbGho4dOxIUFIRCoWDw4MG4ubmZuiwhRDllaWnJCy+8gK+vL/D7LMuaNWuauCohRHkhy178QwqFgubNm/PMM89gZWVFSEiIcU0hIYR4nKCgIDp27EhWVhb/+c9/pHVMCGEkgexfUKvVNGjQAFdXV+zs7ExdjhCVQkJCAjt37uTXX3+tlIElLS2N2rVr8/7771fKwfx6vZ62bdvSp08fU5ciRIUigewf0Ov1pKamsm3bNtauXctvv/3G+fPnee+99/Dx8UGlUpm6RCEqrJMnT7J69Wq8vLyoUaOGqcspcSqVCjc3N7KyskxdSqnYt28fhw4dkkAmxN8kgexvKiws5MKFC6xfv57Tp08zduxY6tSpw5IlSxg4cCATJkzg6aeffmR6uxDir3vqqacYO3YswcHBpi5F/E1r1qxh2bJlpi5DiApHAtnfkJ+fz9dff8369esxMzNj+vTptGnTBrVajb+/Px999BFTpkyhZ8+eREZG4uPjY+qShRBCCFEBSCD7i1JSUti8eTNffPEFbdu25ZVXXsHPz894vYuLC++99x7169dn06ZNXL16lYEDB9KiRQsZ7C+EEEKIPySB7C84duwYK1asICEhgcGDB9O1a1fs7e0fuZ2ZmRm9e/fGx8eHjRs3MnfuXCIjI+nevftjby+EEEIIARLI/lB+fj67du3i448/platWixYsIDGjRs/cWNx+H05jCZNmuDu7s727duNrWVDhgzB09OzDKsXQgghREVR+eZcl5A7d+6wYMECoqKiCAsLY/r06Tz11FN/GMaKKJVKPDw8eOONNxg5ciSnT59m1KhRnD9/Hr1eXwbVCyGEEKIikUD2GLGxsbz99tvs2bOHSZMm/aPWLYVCQbVq1ejcuTOLFi3C0tKSvn378vXXX5dS1UIIIYSoqCSQPUCn03H06FH69evHvXv3WL16NT169MDa2vofH1OtVhMQEEB0dDS9evXixRdf5P3336ewsLAEKxdCCCFERSaB7P9kZGSwceNG3njjDdq0aUN0dDRBQUEldnwLCwumTZvGtm3b2LRpE3369OHKlStotdoSO4cQQgghKqYqH8h0Oh1Xrlxh0qRJLFmyhBEjRjB37lzc3d1L5XzPP/88+/btA+Ctt95iz549pKenl8q5hBBCCFExVOlZlpmZmRw+fJilS5eiVCpZvHgxzzzzTKmf19fXl5UrV7J06VKWLVvGlStX6NOnD15eXpVybzshhBBC/LEqG8iuX7/O9u3b2bt3L0899RTDhg3Dw8OjzM7v7OzMmDFj8Pf3Z/v27SQmJvLKK6/QpEkTWUhWCCGEqGKqXCDT6XScPXuWNWvWcPPmTQYMGEBERIRJ9p6sVq0aL7zwArVr12b9+vXMmTOHyMhIevXqJaFMiFKSk5PD7t27+fnnn4Hfvxx17NiR4ODgMv+7MxgMpKamUlBQQPXq1aWFXIgqrEr99efl5bF3716mTp1KQUEBb7/9NpGRkSbdCNzCwoIWLVowYcIEWrduzfLly5k2bRoZGRkmq0mIyiwnJ4cffviBW7duERQUxPXr11myZAlxcXEYDIYyrUWn07Fv3z62bNlCXl5emZ5bCFG+VJkWspycHJYvX87OnTsJDQ3l1VdfxdPT8y8t9FralEoltWrVYsiQIQQFBTFjxgzOnTvH3LlzadCgganLE6LSUalU1K9fnz59+lC7dm1mzpxJfHw8AQEBpKamsmnTJhISEmjcuDHdunWjsLCQo0ePGpfGKWrFjouLIz8/nwsXLtCqVSs8PT25cOEC4eHhODo6cvfuXb755ht8fHzIy8vj66+/5u7duzRt2pTevXvz008/sXbtWtLS0tBqtfTo0QMHBwf27t3L6dOnsbGxoU+fPgQHB3P79m327dvH6dOnsbe3p2fPntSvX5+9e/dibm5OQkICCQkJtG/fnpCQEDQajfHxnj9/nlOnTmFjY8OPP/5IYGAg3bt3x9XV1YS/BSHEg6pEC1l6ejoDBw5k06ZNjBgxgnHjxuHt7V0uwtiD7Ozs6NSpE59++ilWVlb07t2bHTt2lPm3diGqCpVKBfy+kLOFhQUZGRkMGzaMq1ev0qpVK3788UfWrFnDpUuXWLp0KfPnzzeuS/jTTz/x3nvvcejQIQoLC1m+fDlHjhxhw4YNnDx5Er1ez4ULF4iJiSEpKYkTJ07g5OREYGAgq1atYs+ePTg4OODo6Ei1atXw8PDA0tKSY8eOkZKSwtNPP839+/cZO3YsycnJXLp0iWvXrtGkSRNu3rzJ4sWLuXnzJnv37mXYsGFcuHDBWMePP/5Y7H3j0qVLTJw4kS1btqDRaIiJieGzzz6TVjkhypHylUhKwalTp+jZsyeurq58+umn1K1b19Ql/SG1Wo2Xlxdbt24lKiqKESNGcPHiRd5++21sbGxMXZ4QlUJeXh6HDx/m/v37HDp0iHr16lG/fn2OHz/O5cuX2b17N56enpibm/PNN99QvXp1FAoF48aNo1evXgCcOHGCRo0aMXv2bPR6PVOnTkWhUODu7s7evXtp27Ytx44dw87OjpCQEOzt7QHIzc3l1KlT/PLLL/Ts2ZNmzZqRlJTECy+8QLVq1fD19SUiIgKABg0a0K9fP1JTUwkJCSEkJAQAd3d3Vq9ebWxZa9u2LVFRUSQlJREVFUVCQgJardY4Jk6n0+Hm5kZUVBT29vYsWbKExMREsrKysLS0NMFvQAjxsEoZyAwGA1lZWWzevJkFCxYQGhpKVFRUhQo0arWa0aNHU7duXWbMmEFSUhKjR48mICCg3LXsCVHR6PV67t+/D8Do0aPp2LEjTk5OHDhwgNjYWLp3746ZmRk6nY7mzZtjbm6Ora0tHh4eKJVK9Ho9SqUSGxsbNBoNhYWFWFpaYmZmRmhoKKtWreLKlSscO3aM0NBQFAoFn376KTt27OD69evExcXxxhtvPFKXwWDgwoULbNiwgRMnTpCamkpaWho6nY7Lly+zbt06jh07xs2bN7GysjLujevo6Ii5uTkWFhZoNBp0Ot0jLevW1tZYW1ujVquxsrIiJydH9tYVohypdJ/sWq2W+Ph4Vq5cydGjR5k0aRIDBw40dVn/iLm5Od26dcPDw4N58+Yxfvx4hgwZwrPPPluhwqUQ5Y2VlRVdu3bl3XffLTaz0sHBAR8fH3bs2EFAQAA6nQ69Xs/Jkyf/8rHbtGnD2rVrWbduHWlpabRs2ZKzZ8+yc+dOwsPD6dSpE2PHji3WXVp0nszMTNatW0deXh6bNm3i1q1bvPrqq2RmZrJ//35SUlJYs2YNFy5cYM2aNSgUihJ/boQQplGpAllWVhaHDx9m48aNaLVaFi5cSKtWrUxd1r+iVCpp1qwZCxYsYPXq1SxcuJD4+Hh69epFjRo1TF2eEBXW48JMcHAw3t7erFu3jjZt2qDVanF1df3TLc4UCoXxeO7u7oSEhLB06VL69u1LrVq1yMjIwNzcnOvXr7N3714SEhKMrW1OTk589913fP3119SvXx9LS0vu37/Pjz/+yMWLFyksLEShUGBubo5Wq+Wnn37izJkzZGVl/eFj+aPH+2C9QojyQTVt2rRppi7i3zIYDNy5c4fNmzezbds2fH19GTduHMHBwcZvoRWdvb09zZo1w8LCgh07dvDLL7/g5uZGjRo15I1VVCoXL17k8uXLtG7dulS2MDMYDBQWFlK7dm18fHyKrf1la2tLnTp1uHr1KrGxsaSmpuLq6krNmjWxtLSkYcOGODo6olAoKCgowNnZmaCgINRqNVqtFl9fX2rVqkVhYSFffPEFI0aMICgoCBsbGxQKBQkJCeTk5FC/fn2aNGlCQEAANjY2pKamcufOHXx9fQkICOD27dskJSXh7OxMw4YNadu2LZ6enqSmpnLjxg1cXFwICgqiWbNmqNVqfHx8qFu3LgaDAYPBQJ06dahZs6bxsRUUFGBjY0OLFi0wNzensLAQd3d3/P39S3zttVOnTnH8+HGGDBlSoscVpSMrK4tNmzbRtWtXvL29TV1OlaYwVIIpfJcvX2bFihXExsYSERFBjx49Ku107qLp90UL277++uuEh4cXm+IuREW2Y8cOdu3axdixYwkODi6VcxSNnXrSQqw6nY6cnBwsLCwwNzc3Bp0HW5aKLis6hl6vR6FQYDAYWLFiBZ988gmffPKJcQcQvV5PQUEBarUapVJpPJbBYECr1aLT6bC0tDSGPb1ej6WlJTqdzvjFUqvVotfrMTMzM9ZfdN6iuh7+uahWvV5vPE7R235pfJlbs2YNy5Yt4/Tp0yV+bFHyUlJS6NSpE8uWLaNt27amLqdKq/Bdll9++SUfffQR9vb2vPPOOzRv3hwrKytTl1Vq1Go1bdu2xcvLi5iYGJYuXcrVq1cZNGhQuevCLGqJeNzA4fv372MwGHB2dn7kQ/HGjRscPXqUDh064Ojo+Mh9L1y4wNmzZwkPD6/Uv2tRev5sRXyVSkW1atWMPz+ui+/hyx5sjcrNzeXll1/Gzc2t2PWPm9FY1B35oAd/frCVvyiI/dFjedxjUygUxY4jrepClD8VNpDl5OSwZMkS1q1bx4svvsjAgQPx9vauMluPeHt78+abbxIQEGAMZUUtCuXhzdZgMPC///2P5cuXk5iYaLxcoVDg5uaGt7c3Li4uDB8+vNgHH0BSUhJbt241dg897MKFC2zZsoVOnTpJIBPljpmZGf3790ej0ciMaCHEX1Yh3y1+/fVXpkyZwsmTJ1mwYAEhISFVctahjY0NYWFheHt7s2jRIt566y0mTpxIaGjoY79JlyWFQkHTpk1ZuHAhaWlpjBkzhqCgIN566y3UajU6nQ6lUmlcZPNBhYWFZGZmotPpHnvs/Px8MjMzZcFcUS4plcpSGfsmhKjcKlxz0uHDh+nTpw/Xr1/n888/p1u3blUyjBVRq9U0atSIRYsW8dxzzzFixAhWrlxJdna2qUvDysoKDw8PvLy8sLKywt7eHm9vbxwcHDhx4gRHjx41jpU5dOgQvXv3pmv58g1ZAAAgAElEQVTXrhw9ehS9Xs+1a9eYMmUKISEhREZGcvjwYQoLC43HLxpPN2vWLM6ePSsBTQghRIVVIQKZwWAgIyODtWvXMmLECFq0aMG2bdvw9/cvF91z5YGTkxPvvfce06dPZ9WqVYwePZqbN2+Wy4Uf8/PzOXfuHOfOnUOr1XLmzBmmTJlC7dq16dOnD9u2bePevXskJydjZ2fHO++8g4uLCx9++CG3b98Gfh90ffLkSRYuXIiZmRm1a9eW14IQQogKq9x3Wer1euLj49m4cSPffPMNgwcPpl+/ftja2pq6tHLHzMyMAQMG4Ofnx7Rp0+jbty8zZsygadOmj+0aLA8MBgMnT57E1dWVoUOH4u3tjZOTE/Pnz6d58+a4uLiQnp5OYGAgsbGxxrWXbt++zbJly2jcuDH/+c9/5PUghBCiQivXgUyr1XLkyBE+/vhjMjMzmTJlCs8995zJx0eVdy1btmTdunXMmzePt99+m1deeYWIiAg8PT1NXdojilYnt7a2xsLCAvh9bJzBYODEiROcP3+ezMxMkpOTycjIMHZL5uTkkJmZia2trXRVCiGEqPDKbZdlamoqa9euZerUqbi6ujJ37ly6dOkiYewvql69OvPnz2fo0KHs2bOHOXPmcPz48T9dcbysKRQKnJycuHv3LqmpqeTl5XHu3DnS09M5cuQIBQUFTJs2jVdffdW4OTOAl5cX/fv358cff+Srr74iNzfXhI9CCCGE+HfKZQvZuXPnWLNmDadPn6Z///706tULJycnU5dV4Zibm/PKK6/g6+vLxo0bmT17Nv3796dTp06PLDVR2h5es6no56Ktofbt28f8+fOpXr06169fx9LSEgcHB2JjY1m5ciW3bt0iPz/feD8LCwvat29PVlYWu3fvxsvLixYtWlSanRmEEEJULeUqkGm1Wvbv38+qVauwtbVlxowZtGnTRlrF/gWVSkWbNm3w8PBg27ZtrFq1iqtXr/L6668XW7SyNGk0GoYPH46zszMKhQIbGxsiIiIwGAxoNBr8/f0ZO3YsZ86cwczMjB49epCTk4O7uzuXL18mPz+fZ555BqVSSfXq1WndujXOzs54eXnx0ksvERwcjLu7uwzqF0IIUWGVm0CWlpbGxo0biYmJoWPHjvTr1w9fX1/5kC0BKpWKOnXq8NZbb+Hj48O6deu4fPky7733Hj4+PqX+HJuZmdGuXTsAY+tWo0aNjD8DNGvWjEaNGqFQKFCr1cZtagIDA4H/v/q4QqHA1tbWOKtSo9FQvXr1YscSQgghKppyEciSkpKYO3cup06dYtiwYTz//PPY2dnJB2wJUigUODg40LNnT+rWrcvMmTPp27cvixYtKpP9yx637czDHmwJLbr+SV2QD3d/isrl+PHjTJw4kZo1a5q6lBKXlZVFTk4OLi4ulfK1+9///leGmAjxD5g0kBkMBs6fP8/w4cNRKpV8+OGHNG/evMpsf2QKFhYWBAcHs2HDBqZOnUpYWBjvv/8+I0eOlOddlAvBwcG8/PLLJCQkPHG3hoosMTGRpKQkQkJCKuXWSmFhYTz77LOmLkOICsdk7wa5ubns27ePiRMn0qZNG6ZPn14ul2WojIrGcUVFRdG8eXPj+K2ZM2dSo0YNGRgvTMrX15dJkyaZuoxSs3LlSvbs2cPy5ctlL1YhhFGZN4no9XquX7/O+++/z4QJE3jjjTdYunRpmYQxg8FQbM0qvV5fYmtYZWVlcevWLQoKCsjNzX3icQsLC8nJySk3a2dFRkby5Zdfcvv2bQYPHsy3335rXHxVCCGEEGWjTANZTk4Ohw8fZuTIkfz8888sWbKEsWPHotFoSv3cBQUFnDlzhl9++QW9Xs/du3c5fPgwSUlJJbK9UNGeij///DMxMTHk5OQ89naXLl1iw4YN5Sr0BAUFER0dTb169Zg3bx7r16/n1q1b5XLbJSGEEKIyKrNAlpKSwpYtW5g1axYeHh6sXr2a0NDQsjo92dnZrFu3jk8//ZTU1FS2b9/OihUrSExMLJHWqtTUVC5evEhKSgrXrl174gKsd+/eJTY2tlwt0KpQKPDw8GDy5MlERkayb98+Fi5cyPnz54tt5i2EEEKI0lHqY8j0ej2XL182LrXQvXt3+vbta7JZOHl5eXz//ff873//o3v37jRt2hSVSkVmZiY//PADycnJODk50axZM3Q6Hffu3SM7O5u4uDhcXFwICQnBxsYGnU7Hr7/+yokTJzAYDNy4cQODwUCdOnWwsbFBo9FQWFhIXFwcJ06cQKfT0bp1a7y9vWnbtm2xsSMGg4GEhATjuWJjY3F3d6ddu3bY2NiU2XPj4OBA//79qVOnDuvXr2fWrFn069eP559/XsaVCSGEEKWo1ANZbGws06dPR6vVMnToUJ599lmTDWTV6XRcvHiRO3fu0Lx5c0JDQ7G2tiYnJ4eFCxcSHx+Pn58fx48f59ixYzg7O3PkyBFcXFxwcXFh06ZNpKWlMWDAAJKSkli9ejW3b9/G0dGRkydPkpeXxy+//MI333xDixYtSEtLY/PmzRQUFODo6EhSUhLZ2dlER0fTtm1bLC0tgd8D2bFjx9i2bRtubm44OzuzdetW0tPTeemll8p09qNGo6F9+/Z4eHiwdu1a5syZw+7duyv14OMOHToQHh5u6jKEEEJUYaUeyFQqFXl5efz2229oNBrMzc1L+5RPVDSOrEmTJrRo0QJHR0fg962aYmJiWLBgAU899RTHjh1j48aNxMbGkpeXR7du3WjcuDFZWVkcOHCA8PBwzp8/T2JiIv379ycwMJA1a9bwww8/kJWVRUpKCjqdjjt37hAXF0enTp0IDQ3FysqKAwcOcOvWrWLT+Q0GA1lZWRQUFBAeHk7Dhg3JzMzk4MGD9OzZs8zDkFKpxN7enoyMDOLi4ggICCjzrZbKgsFgYPfu3WRkZEggE0IIYVKlHshq1arF3LlzWbZsGe+++y6jR48mIiICCwuL0j71I4rW4DI3N+e7774jICAAe3t7YmNjMTMzo1mzZri5uVG3bl3s7OyIj4+nZs2aBAYG4unpib+/PwcOHCA/P5/U1FQ0Gg0BAQHUqVOH+vXrc/To0WLnq1OnDkFBQaxcuZIzZ84wbNiwP6zP3d2dwMBAPDw88PX15fDhwyYZw3X27FlmzpzJ7du32bJlC02aNDFpkC4tRbNu4+PjTV2KEEKIKq7UA5laraZu3brMnTuXVatWMX78eM6dO8f06dPLfI9KhUJBUFAQ9erVY+vWrQQGBhIWFoZarSY/P9/YaqXVatHr9ajVapRKZbGNsB88lk6nM97ncZtnOzs7M27cOJ5//nlmz57N3LlzadOmzRPre9K5ykphYSH79+9nypQp+Pv7Ex0djY+PT6VdMNZgMFCtWrVKuVq6EEKIiqVMPmmLFiIdM2YMK1euZNeuXXTt2pXExMQyXYlboVBgZmZG586dad68ORs2bODKlSsEBQWh0+n47LPPuHXrFkePHuX+/fvUqVPnsWHEzMwMT09P0tPTOX78OCdPnmTLli1kZ2cbA5Ver+f27dtcuXIFNzc34ySB8rqURFpaGitWrGDs2LF07dqVjz76CD8/v0obxoQQQojypMxX6u/cuTMBAQGMGjWKiIgIpk6dSrt27bCzsyvV86rVamrUqIG1tTUODg688sorLFy4kJ9//pm+ffsyZ84cFi1axLp163B1deW1114D4OLFi8buVScnJ7y9vTEzM6Np06Y8++yzLF26FAsLC5566ikyMjJwcnKidu3aqFQqkpKSWLx4MdeuXcPKyorhw4djZmaGr69vsS1TFAoFjo6OeHp6GrsGnZ2d8fLyKvVApNfriY+P54MPPjDuH9i7d2+TdCkLIYQQVZXCYKIl43Nzc5k/fz5fffUVYWFh9O/fHy8vr1JdXqGodaoo5BS1zhWds6CggMzMTKytrbG0tHzk9gaDAZ1OZwxTer2e7OxsVCqV8fZKpdLY3Vl0zKysLKysrLC0tHzkGE+qTa/XFztOacjKyuLHH39kwYIF2NjYMHbs2D/sUq1sDAYDs2fP5uzZs8TExJi6HFFFFG2dFBMTU6lnL4uKISUlhU6dOrFs2TLatm1r6nKqNJPtZanRaJg4cSINGjRg48aNJCYm8uqrr9KsWTPjchAl7eHWpofDn7m5ebH10R6+vUKhKBaQlEplsdmHRbd/8H7m5ubG2ZyPO8aTzqVUKku1dSwxMZGdO3cSExNDu3btGDZsmOwlKoQQQpiIyQIZ/D4Wq3v37tSqVYu1a9cSFRVFeHg44eHhpd6FWVUVFhZy4sQJ1q5dS3JyMkOHDqV3796lFoKFEEII8edMPmLbzMyMxo0b8+6779KmTRu2bdvG/PnzuXXrlqlLq3SysrL47LPPmDlzJiqVikmTJtG/f38JY0IIIYSJmTyQwe/dc15eXgwaNIi33nqL06dPM3ToUM6dO2fq0iqN3377jcWLF7N8+XKefvpp3n33XVq2bCmzKIUQQohyoFx9GtvZ2dG5c2c+/PBD7Ozs6NWrF1u3bi2Rzb+rKoPBwLVr1xg1ahQHDhxg2LBhDB06FG9vbwljQgghRDlR7j6RzczM8PPzY8WKFQwbNozRo0czbtw4srKyTF1ahfTzzz8THh5OZmYmS5cuJSIiAltbW1kMVQghhChHyl0gg99nImo0GkaMGMHOnTvZv38/AwYM4OLFi2W6kGxFZTAYyM/P56OPPqJr166EhISwbds2GjRoUKrLigghhBDinymXgexBbdq04bPPPsPCwoJhw4axe/duMjMzpRvzCbRaLXFxcQwdOpSlS5eyePFiPvjgA2xsbExdmhBCCCGewKTLXvwVCoUCPz8/PvzwQz7++GMWL15MfHw8vXv3xtPTU8ZBPSAjI4MjR46wYsUK1Go1n376KcHBwaYuSwghhBB/otwHsiLu7u6MHj0aPz8/Nm/eTEJCAgMGDKBFixZVfjyUwWAgOTmZ7du3s3//fho3bsxbb72Fh4eHqUsTQgghxF9QYQIZQLVq1XjxxRfx9vYmOjqa999/n/79+9OzZ88qu5ZWYWEh58+fZ+3atSQlJREZGUl4eDgODg6mLk0IIYQQf1GFCmTw+ybhrVu3pkaNGmzfvp0PPviACxcu8Oabb1a5rX90Oh1ffPEFGzZswMHBgTFjxvDUU0+h0WhMXZoQQggh/oYKF8iK1KpVizfffJOgoCAWLVrElStXGDNmDK1atTJ1aWUiNzeXqKgo9uzZQ5cuXRgwYADe3t4yi1IIIYSogCr0iHgbGxs6derEkiVLcHFx4e2332br1q3k5+eburRSlZCQQP/+/YmJieHdd99l1KhR1KlTR8KYEEIIUUFV6EAGv2+7FBAQwMyZM+nduzczZ85k/vz53Lt3z9SllYqvv/6aHj16kJmZyRdffEH37t1lI3YhhBCigqvwgQx+XxrDycmJ4cOHM3fuXHbu3MmIESO4du0aer3e1OX9awaDgaysLBYvXsx//vMfunbtyu7du6WLUgghhKgkKkUgK6JWq+nevTvr1q0jOzub1157jUOHDpGbm2vq0v6xwsJCrl69yuTJk9m8eTMzZsxgypQpVXZWqRBCCFEZVapAVqRx48asWLGCli1bMmbMGNauXUtycrKpy/rbcnNz+fbbb3nvvfdITEwkKiqKPn36yCxKIYQQopKpsLMs/4y7uzvvv/8+gYGBrF69mrNnzzJo0CAaN26MWl3+H3Zqaio7duxg586dNGrUiMGDB+Pv72/qsoQQQghRCsp/MvkXLCwsePXVVwkMDGTVqlVMnz6dAQMG0Llz53I9EP7cuXOsWbOGCxcuEBkZyQsvvICTk5OpyxJCCCFEKanUgaxIixYtqFGjBlu3bmXt2rXExsYa1+0qT7RaLV988QUff/wx9vb2TJ48mTZt2mBubm7q0oQQQghRiqpEIAOoWbMmQ4YMwcfHh82bNxMbG8vIkSNp1KhRuZipmJqaSnR0NLt27aJr16707dsXHx8fU5clhBBCiDJQKQf1P4mdnR3dunXjvffeQ61WM2rUKPbt24dWqzVpXZcvX+bdd9/lyy+/ZOzYsQwfPlzCmBBCCFGFVKlABr+PK2vcuDHz5s2jQ4cOjBw5kqioKAwGQ5nXotPp+P777xk8eDBpaWl8+OGH9OjRo1yPbxNCCCFEyatygQx+X93f2dmZqVOnsmDBApYuXUqPHj1ITU0ts2CWk5PD5s2bGTRoEE2bNmXFihU0adKkQswAFUIIIUTJqpKB7EE9e/bk4MGDZGRkEBYWxrfffktOTk6pnU+v13Pr1i1jGHz77beZPXs2bm5upXZO8f8ZDAb0er3xX1EAf9xlQgghRFmR5hggICCAvXv3Mm3aNCZNmkSfPn2IjIzEzc0NpbLkMmtubi6nTp1i1qxZFBQUsHjxYjp06FBixxd/Lj4+nsTERAoLCzEYDMTFxZGSksKBAweMtwkICKBmzZrlYrKHEEKIqkEC2f+xtrZmxowZxMTEsG3bNq5du8arr75KgwYNSmTZiVu3brFnzx7WrVtHcHAw48aNo3bt2iVQufg7jhw5wvjx40lJSSl2eefOnQFwdHRk2bJleHh4SCATQghRZqp8l+WDLC0t6dOnD5MmTSIzM5N58+bxxRdfkJ2d/Y+PqdPpOHv2LPPnz2fHjh0MGDCAhQsXShgzkbCwMBo3bvzEsBUSEkLz5s0xMzMr48qEEEJUZdJC9hBzc3Nat26Nm5sbW7ZsYfXq1cTGxjJo0KC/vVp+Tk4O3333HevXr8fa2pqxY8fSrl07+bA3IRcXFwYMGMCRI0e4f/9+sevc3NwICwvD09PTRNUJIYSoqqSF7DGUSiV+fn4MGzaMV199lYMHDzJ69GhiY2P/8jHS0tJYvXo1H3zwAXXr1mXChAm0b99ewlg5EBYWRrNmzR65vFWrVjzzzDOyM4IQQogyJ4HsDzg7OxMREcGCBQvIy8ujd+/e/Pe///3T+928eZPx48fz2Wef0b9/f0aNGoW/v78saVFO2NnZMWrUqGKXubu7ExoaWu620xJCCFE1SCD7ExYWFjRq1IjVq1fTq1cvhg8fzowZM564NMa5c+fo2bMnCQkJLFiwgJdeegknJycUCkUZVy7+SOfOnXnmmWeMPzds2JCwsDAJzUIIIUxCAtlfoFAosLOzY+LEiaxevZoNGzbwxhtv8OuvvxZbx2r9+vW0bt2awMBAduzYQfPmzaX7q5wyMzNj1qxZKBQKXFxceP755/Hy8jJ1WUIIIaooaQ74GxQKBR07duSzzz5j0qRJDB48mLFjx+Lr68vixYvZvXs3UVFRDB48uNK0iBkMBvLz801dRqlo0qQJHTt2JCMjg65du5KXl2fqkkqcQqFArVbLEh5CCFHOSSD7m5RKJQ0bNmT58uUsWbKEMWPGkJOTQ+3atdmyZQutW7c2dYklKj4+nq+++orCwkJTl1IqatWqxa+//sru3btNXUqpsLCwoHXr1jRq1MjUpQghhPgDEsj+oZo1azJp0iTy8/M5duwYCxYsIDg42NRllbjNmzcTHR1Ny5YtTV1KqbG1teXIkSOmLqPEFRQUcOnSJW7fvk1QUFCJ7johhBCiZEkg+xfs7e3x9vYmLy8PV1fXStNN+aDCwkIaN27Mtm3bTF2K+Jvu3r3L7NmzMRgMsj+nEEKUcxLIxJ9SqVQy+7ACUqvV0iomhBAVhLxbCyGEEEKYmAQyIYQQQggTk0AmhBBCCGFiEsiEEEIIIUxMApkQQgghhIlJIBNCCCGEMDEJZEIIIYQQJiaBTAghhBDCxCSQCSGEEEKYmAQyIYQQQggTq5KBTK/Xo9fri12m1Wplvz9RZvLy8khNTSU/P9/UpQghhCgHqlwgy87OZtWqVYwbN45r164BcPnyZdq3b88PP/xg4uqqFoPBwJEjRwgLC6NOnTr4+voSGRnJxYsXTVJLSkoKFy5cICsrq9TOk5mZSXR0NO3ataNly5Y899xzfPfdd+h0ulI7pxBCiPKvygUyKysr6tatS1xcHCdPniQvL48tW7Zgbm5OcHCwqcurcjIyMrCxsWHz5s3s37+f7Oxs3n77bdLS0sq0DoPBwOHDh1m8eDEJCQml1lqq0+moVasWq1ev5tChQ9SsWZNNmzaRm5tbKucTQghRMahNXUBZUygUBAcHExgYyA8//ICDgwMHDhxgwoQJaLVaFi1axA8//IBKpSIiIoJu3bphZ2dn6rIrNYVCgVqtpnbt2gwYMIAZM2Zw9+5dVCoV+/fv5/PPPyc/P5/w8HAiIiI4deoUe/fuRa1Wk56eTo8ePbh27Rp5eXmcOXOGtLQ0Xn31VS5evEi9evXo3r07mZmZbN++HVdXVxo2bMgnn3zC4cOHMTMzo1u3btStW5dPPvmEU6dOkZyczBtvvEHXrl05evQoGzZs4NatW9SrV49XXnkFDw8Pdu3axVdffUVWVhbt2rVjyJAhpKens3v3bvLz8zl//jwGg4EhQ4bQokULVCoVAPb29oSEhKDX68nKysLV1ZWsrCzpLhdClDiDwUBubi4WFhbG9yBRflW5FjL4/UOxY8eOJCUlsXTpUmrVqkVISAh3795Fr9fz5ptv0qJFC3bs2MH58+cfGW8mSlZhYSF3794lKSmJU6dO4eHhgUaj4cCBA3zyySd06dKFF198kfXr1/PDDz+QmJjIxx9/zPXr1+nYsSMqlYqvvvqKzz77jNatW+Pl5cX48eNJTU1l+/bt3Lt3j7i4OA4fPoxOpyM5ORlzc3PGjx9P586d2bhxIzdv3iQ4OBhfX1+6dOlCw4YNMRgM/PLLL3To0IHhw4fz22+/8cknnxAXF4dWq2XgwIG8/vrrREdHc+DAAdLT09m1axcHDx6kVatWaLVaPvroIzIyMoo93rS0NH788UeWL1/O8ePHad++PRqNxkTPvhCissrOzmbhwoXs3buXmzdvotVqTV2S+ANVroUMfm+RadKkCd7e3uzatYtFixZRrVo1fHx8CA8PJzk5GSsrK/R6PRkZGej1epTKKpldy0RqaioxMTFYW1sTGxvLm2++iYWFBadPn0ahUKDRaFCpVJibm3Px4kXc3Nzw9vbmvffew9fXl0uXLlGtWjW6d+9O3759uXLlCl988QV+fn5cuHCBs2fPkpycjEajwd/fHz8/P1xcXIy/ZzMzM/R6PQEBASQmJvLMM89Qp04dFAoFL730ErGxsdy+fRtbW1syMjKoUaMG7u7uXL9+Ha1Wi62tLTdu3MDf3x83Nze6du1KZGQkTk5OrF+/nqysLBwdHYHfv7HevHmTL7/8kosXL1KtWjWysrLIz89Hra6Sf45CiFKi1Wr58ssv+eCDDwgNDeWFF16gefPmeHh4yPtNOVRlfyN2dnYEBwdz5coV49ixX375hTVr1mBhYUFGRoYxjInSZWFhgbe3N/Xq1WPYsGH4+/uTmprK/fv3SU5O5ujRo5ibmxMUFESjRo1ISUnB1ta2WFeyWq1Go9GgVCqxsrJCpVLh6emJl5cX+/btQ6VSUatWLapXr87x48fZvHkztra25OTkPHEQf05ODqtXr+batWvY2tqSkJBAzZo1uXz5Mt9//z15eXmYmZmRkZFh7HI0MzPD0tISpVKJpaUlQLHuSIVCQYMGDZg7dy5ZWVksX76c1atX8+yzz1K3bt1SfJaFEFVVeno6n376Kd9//z0dOnSgS5cutG3bFm9vb1OXJh5QZQMZgLm5OZaWlsZvCkePHiU+Pp7Fixdz/fp1VqxYgUKhMHGVlZ+DgwNhYWE0a9bM2BJpYWGBh4cHubm5DB8+nFq1apGZmYlarWbHjh1/6bi2trY0b96cVatWUbNmTV577TWsrKw4cOAAKSkpzJgxg6SkJGJjYwFQKpUUFBRQUFCAwWDg7t27rF+/nnHjxhEWFsaKFStISUnh+PHjXL16lQkTJuDm5sahQ4f+8mPNysri9u3buLq6YmFhgY2NDQaDQYJ/FfPbb78RHx+PlZWVqUsRlVhGRkaxpXVu377N1q1b+e6773j66acJDQ2VyWzlSJUOZA+HLS8vLzIzM5kzZw5arZb09HTpqixlCoXisaHX2tqaNm3a8MsvvzBhwgQcHBxQKpUMGjTosfd5+DKFQoGFhQWNGjVCrVZjbm5O3bp1MTc3x8/Pj/379zN16lSysrIoKChAqVRSo0YN7t+/z8yZM3n99ddp2bIlgYGBxMTEcOzYMRISEvD19aVmzZocPXqUJUuWYG5uTl5envHcD9bxuDrT09PZunUrly9fRqlUkpycTPfu3fHw8Cjpp1aUU3Z2dty8eZMRI0ZIt5EoVVqtloSEhEcuv3XrFtu3b+d///sfjRs3li+E5USVfTdQKpV06NCBBg0a4O7uDsAzzzyDo6MjGRkZ2NvbY2Zmhre3t8xOKSUKhcI4nqFWrVrFwq9araZp06ZMnDiRxMRECgsLcXR0xNvbG1dXV+rWrYu9vT3we5AeM2YMTk5OmJmZ4enpybp166hXrx537tzBz8+PunXrUqNGDZRKJV27dsXLy4v79+/j7OyMubk5Hh4eWFtbM2nSJG7dukX9+vVxdHRk7ty5xMXFYWlpiY2NDba2tri4uFCvXj1+++037O3tGTRoEG5ubjg6OjJu3DhcXFxQKpW0bNkSDw8P3NzcjI/L2dmZXr168euvv5KXl4ezszMBAQHY2tqW+fMvTKNjx45s3rxZFgUWpS4rK4tJkyZx//79R66zsrKiU6dOhIaGMnv2bBNUJx5WZQMZgLu7O25ubsZWjGrVqtGyZctig/ily7J0OTk54ejo+NjnWaPREBgYiL+/P/B7iFYoFNjb2+Pu7m68j7W1NYGBgcaf/1979xocVX3/cfxz9r7ZLMkmITFAEkoCuTSBKDHINBBuhoShVh07JdiOWtEi0tZ21GoHHnS0lsHOtA9wbB1bpk/sWFsZi4Nap9VoxPZ/5pkAABLXSURBVNZyH5IariKYRBISIYRkN9k9/wf/skMEFS2bn9m8XzMM7CHs+SabgTfnnP0dv9+vr33ta4rFYtq1a5fOnj2ra6+9Nn56KD09XTU1NYrFYnI6nbJtO/5nq6qq4q+/ZVmaPn26CgsL4/s//7GhUOiS3ydlZWXxX2dlZSkzM3PE5+bz+VRaWqri4uL4/vkeG1+ysrJUW1tregyMA729vRct2+Tz+fSNb3xDa9euVVlZmQYHB/WLX/zC0IS40LgOMuni4LIsiyNio+yzguRSr8elXrePP7ZtWykpKbr55pt17bXXjjgCd+Hr/PFTnR/f38f/3Cd93OXMdeFzcjp8/CLCMRou/D7zeDxasmSJHn74Yc2ePVs+n0+WZamzs9PghLjQuA8yJC+Xy6Xq6mpVV1ebHgUARp1lWQoGg1q0aJHuv/9+LVq0SF6v1/RY+AQEGQAASSglJUU///nPNXPmTBafHgMIMgAAkpDH49GcOXNMj4HLxEUsAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhrHsBT6V0+nUyy+/rE2bNpkeJSH6+vo0ODioiRMnmh7liuvp6VFzc7OWL19uehQAwGcgyPCprrvuOlVVVem5554zPUpCvP/+++rv71dpaanpUa64WCymUCik8vJybtMEAF9yBBk+VUNDgxoaGkyPkRC2beuxxx7T3r179ac//cn0OACAcYz/NgMAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABhGkAEAABjmMj3AWHP8+HG98cYb8ce7du1SR0eHtmzZolAoJEkKhUJqaGiQZVmmxgQAAGMIQfY5RaNR/epXv1JHR4ck6ezZsxoeHlZra6ucTqccDodWr16tZcuWGZ4UAACMFQTZ55SZmanFixdr48aNI7afO3dOkhQIBNTY2GhiNAAAMEZxDdnnFAwGdcstt2jKlCmX/P27775b06ZNG+WpAADAWEaQfQGFhYVauXKlnE7niO2hUEg/+clPDE0FAADGKoLsCwiFQlq6dKkKCwvj2yzL0r333qucnByDkwEAgLGIIPsCLMtSRUWFli1bJo/HI0maOnWqbrvtNsOTAQDw/2zb1tDQkOkxcJkIsi8oKytLdXV1KioqksPh0B133PGJ15UBADDawuGwnnvuOW3fvl39/f2mx8Fn4F2WX5BlWaqurlZtba38fr+WL18ur9dreiwAACRJAwMDeuqppxQOh7V48WItX75cs2bNkt/vNz0aLiHhQXbixAm98MIL6unpSfSujOjo6NCECRP07LPP6sUXXzQ9TkLMmzdPCxYsMD0GAOBzGhgY0DvvvKP9+/frlVde0aJFi7RixQpVVFTI5eKYzJdJwl+Nd999V7/85S9VUlKivLy8RO9u1GVkZCgjI0M9PT1JGZ0vvfSSDh8+TJABwBh29uxZ7dixQ21tbdq6dasaGhq0Zs0aBQIB06PhvxIeZENDQyoqKtL69etVWlqa6N3hCvP7/Tp27JjpMRImGo3qrbfe0h133GF6FAC4oiKRiI4cOTJiW19fn/7zn//ovffe0x//+EctXbpUsVjM0IS40Kgcr/R6vQqFQvF7PWLsCAaDSXtPTsuydNNNN6mjo0O2bZseBwCuuE/6+3tgYECS5PP5RnMcfApOIGNcq6io0JNPPml6DAC44np7e9Xa2qqurq74Np/Pp8zMTDU2Nur++++Xbduqq6szOCXOI8gAAEhilmUpJSVF+fn5qq+v11133aXi4mI5HA51dnaaHg//RZABAJCkUlJSdM0116i2tlaNjY2aNWuW3G636bFwCQQZAABJyOfz6dvf/rZKSko0e/Zsrhf7kiPIAABIQn6/X7fffrucTqfpUXAZuHUSAABJihgbOwgyAAAAwwgyAAAAwwgyAAAAwwgyAAAAw5IiyGzbViwWG1e3v4lGoxocHOQeZAAAJIExv+xFb2+v3nzzTUUiEXm9XmVnZ2vGjBlKT08f9XswDgwMqK+vT1lZWXI4EtO6w8PDamtrU0tLi7q7u1VQUKCqqiplZ2cn7T0nAQBIdmM+yFpbW7VmzRrNmzdPbrdbfX19uvnmm3XTTTcpNTV1VGfZs2eP/vGPf+i+++5TIBBIyD76+/v1wgsv6MiRI4rFYtq8ebNWrFihNWvWyO/3J2SfAAAgscZ8kA0PDyszM1Pr1q1TRkaGfv3rX6upqUk1NTXy+/3au3evdu3aJZfLpaqqKs2YMUNHjx5Vd3e3urq65HQ6dd1112nHjh2aMmWK9u/fL4fDoZkzZ6qvr08pKSkqLi6W2+3WwYMHdeLECZWXl2v//v06fPiwfD6fqqurZVmWnnnmGW3btk3Z2dmaM2eOSkpKdPToUe3evVtnzpzR1KlTVVNTI7fbrZ07d6q1tVWWZWnmzJkqLy/X6dOn1dbWptTUVO3evVvBYFA1NTXKzc2Nf74ej0c33HCD8vPz5XA49OCDD6q5uVnf+c53CDIAAMaoMR9k51mWpdTUVGVkZKi7u1vRaFRvvPGGNm/erLKyMg0ODurtt9/W7bffrn379unPf/6zcnNzVVlZqcLCQm3YsEG5ubnKz89Xe3u7duzYIbfbLZfLpTVr1igrK0t/+MMfNDQ0JJ/Pp9dee01+v1+HDx/Wvn37dP3116u3t1fhcFgdHR3q6+tTT0+P3nrrLZ04cULRaFRbt27V8PCwZs2apRdffFGBQEAnT57Uv/71L911110Kh8PasGGDMjMzNXXqVLW0tKitrU333Xdf/Gif3+9XeXm5pP8/Rep0OhUIBLg3GQAAY1hSBNmZM2e0detWRSIRNTc3q6GhQSkpKXr++eeVl5enVatWqbe3Vxs3btTrr78uSXK73WpsbFRlZaXC4bA++OAD1dfXa8WKFWpqatLf/vY3TZs2TS0tLXr//fc1NDSkV155RT/60Y9UUlKinJwcBYNBvf7663r22WcVCAQ0d+5ctbW16Vvf+pamTJkip9Opuro6ORwOxWIxPfTQQ/r3v/+thQsX6rbbblN6erreffdd/e53v9OhQ4eUkZGhrq4urVy5UgsXLtTWrVu1bds2dXV1XfL0a2trq/bs2aNVq1YpGAyO9pcdAABcIUkRZAMDA9q9e7cKCgr0ve99T7W1tYpEIjpw4IAOHTqk1157TdFoVOfOndPkyZPl8/k0ffp0lZeXKzc3V8ePH5fL5dLMmTNVUFCg/Px8eb1elZSU6NChQ9q7d6+OHj2qWCymmpoaRSIR/fWvf9Wrr76qY8eOyel0yuFwKDU1VW63W1lZWQoEAgqHwzp48KCeeeYZHThwQG1tbfGL799++21t2bJFx44d0+DgoBYtWiTbtpWamqqrr75aV111lQoLCxWNRhUOhy/6nNvb27V+/XrNnj1bN9xwg1yupHgpAQAYl5LiX/Hs7Gz99Kc/VWlpaTyOTp48KZ/Ppx//+Me688474x8bDof19NNPxz/uPMuy4vf8Ov9uxdzcXFVUVGj79u3q7+/XggULFAqFtHnzZr355pt69NFHderUKf32t7+9aCbbtrVnzx499dRTqq2t1SOPPKJHHnlELpdLL7/8sjZt2qTHH39caWlpevLJJ+P7dDgc8V+f//njy3l0dXXp3nvvVXp6utavX69QKHQFv5oAAGC0JcU6ZJZlyeVyye12xyMrLS1NX/3qV/X3v/9dHR0d6u/vV3t7u06dOnVZy0NYliWv16v58+dr3759am5u1o033ijLsnT69GlNmDBBPp9Pra2t6u7uliQFAgGdPn1a7e3tOnv2rM6dOyfbtpWVlaWOjg4dOHBA0WhU3d3d8vv9ysjI0JEjR3Ts2LHLXkPto48+0kMPPaQzZ85o3bp1Ghoa0qlTpxSJRL74FxAAABg15o+QBYNBFRcXy+fzjdju9Xq1evVqPfbYY1qxYoX8fr+ys7N1zz33KCsrS7Ztxy+E93g8Kikp0YQJE+JvDsjLy1MgEFBeXp7y8/OVkZGhWbNmye/3a+HChdq5c6dWr16tSZMmqbCwUKmpqaqurlZhYaHuvvtuffe739WyZctUVlamTZs2KTU1VRMnTlR+fr6uv/56vfrqq7rnnnuUnZ2tvLw8TZw4UcFgUIWFhfL5fLIsS8FgUF/5yldGfG7t7e3q6enRqVOntHLlSklSfn6+HnjgAdXU1LAWGQAAY5BlJ3h5+5deeklPPPGEHn/8cZWWliZkH8PDw596DdVHH32kaDSqUCgUv8Be0ohTlhc+x/mV/x0Ohzo6OvSDH/xANTU1+uEPfxgPnkgkouHhYXm93vhzWZaloaEh9fX1KS0tTU6nU7FYTAMDA3K73XI6nbIsSw6HQ9FoVAMDA/H4Ov8jGo1eNMf5U6kmrFu3Ti0tLdqyZYuxGQAAidHZ2am6ujo98cQTmjdvnulxxrUxf4RM0mde0J6enj7i8aVW0b/wOS68nqy9vV1paWlasGDBiKNPHo9HHo/noudxu93KyMgYsa9LLRLrdDov+c7JT5oDAAAkr6S4hixRbNvW5MmTtXbtWhUXF5seBwAAJKmkOEKWKJZlKTc3d8RK+QAAAFcaR8gAAAAMI8gAAAAMI8gAAAAMI8gAAAAMI8gAAAAMI8gAAAAMI8gAAAAMS/g6ZLZt6+DBg9q8ebPy8vISvbtRNzQ0pFgsJo/Hk5T3kdy+fbuCwaDpMQAASGoJD7KCggLNnz9fnZ2d6u3tTfTuRt3+/ft15swZVVZWKiUlxfQ4V1xOTo7q6upMjwEAQFJLeJBNnz5dP/vZzxQOhxO9KyOefvppHTlyRN///veVk5NjepyEyMrKMj0CAABJLeFB5vF4NGnSpETvxpiMjAx1dXUpLy9PkydPNj0OAAAYg7ioHwAAwDCCDAAAwDCCDAAAwDCCDAAAwDCCDAAAwDCCDAAAwDCCDAAAwDCCDAAAwDCCDAAAwDCCDAAAwDCCDAAAwDCCDAAAwDCCDACAJGXbtukRcJkIMgAAklAkEtH27dv13nvvKRqNmh4Hn8FlegAAAHDlnTt3Ths2bFBaWpqWLl2q+fPnKy8vTw4Hx2K+jAgyAACSkG3bOnnypLZt26ampibNnTtXDQ0NamhoUE5OjizLMj0iLkCQAQCQxGKxmE6cOKHnn39e//znP/WXv/xFt9xyi775zW+aHg0XIMj+R7Ztq6mpSb/5zW+Uk5NjehwAACRJAwMD+vDDD+OPo9Gojh8/rg8++EA7d+7U73//e914441c+P8lQZD9j8rLy1VcXKympiY5nU7T4wAAIEkaHh5WT0/PRdtjsZg6Ozv14Ycfyuv1EmRfEgTZ/6i+vl719fWmxwAAYITe3l7V19frnXfeiW+zLEsOh0M1NTV69NFHVVRUpLq6OoNT4jyCDACAJOdyuRQMBlVVVaW1a9eqvr5eHo9HnZ2dpkfDfxFkAAAkKafTqUmTJunqq6/WrbfeqmXLliktLc30WLgEggwAgCTkdru1ePFiFRUVqaGhQdnZ2aZHwqcgyAAASEKBQEAPPviggsGg6VFwGViuFwCAJGRZFjE2hhBkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhhFkAAAAhlm2bdumhwAAAIl34MABbdy4UUePHpUkRSIR7d69W8XFxUpPT5ckzZgxQw8//LDy8/NNjjruuEwPAAAARse0adNk27aam5sViUTi23ft2iVJcrvdqq2tVVpamqkRxy1OWQIAME64XC7deeeduuqqqy75+2VlZVqyZAlBZgBBBgDAODJnzhzV1dXJsqwR2/1+v5YvX66ysjJDk41vBBkAAOOI0+nU2rVr49eMnVdSUqIlS5ZctB2jgyADAGCcqaioUGNjY/xxSkqKFi5cqGuuucbgVOMbQQYAwDjjcDj0wAMPKDMzU5JUVFSkr3/965owYYLhycYvggwAgHGooKBAq1atkt/vV01NjebOnWt6pHGNIAMAYByyLEurV69WZWWlbr31Vnm9XtMjjWssDAsAwDgViUTU0tKiysrKi951idFFkAEAABjGKUsAAADDCDIAAADDCDIAAADDCDIAAADDCDIAAADDCDIAAADDCDIAAADDCDIAAADDCDIAAADDCDIAAADDCDIAAADDCDIAAADDCDIAAADD/g/uuT7meQ0FYAAAAABJRU5ErkJggg==\"></p><p>Berikut ini adalah contoh penggunaan NESTED IF ketika seseorang akan melakukan pembayaran di kasir. Kasir akan memberikan pertanyaan sebagai berikut:</p><ul><li>Apakah pelanggan mempunyai kartu anggota?</li><li class=\"ql-indent-1\">TRUE: Pelanggan mempunyai kartu anggota</li><li class=\"ql-indent-2\">Apakah total harga barang belanjaan lebih dari Rp 500.000?</li><li class=\"ql-indent-3\">TRUE: Total harga barang belanjaan lebih dari Rp 500.000, pelanggan mendapatkan diskon Rp 50.000</li><li class=\"ql-indent-3\">FALSE: Total harga barang belanjaan tidak lebih dari Rp 500.000, pelanggan mendapatkan diskon Rp 25.000</li><li class=\"ql-indent-1\">FALSE: Pelanggan tidak mempunyai kartu anggota</li><li class=\"ql-indent-2\">Apakah total harga barang belanjaan lebih dari Rp 200.000?</li><li class=\"ql-indent-3\">TRUE: Total harga barang belanjaan lebih dari Rp 200.000, pelanggan mendapatkan diskon Rp 10.000</li><li class=\"ql-indent-3\">FALSE: Total harga barang belanjaan tidak lebih dari Rp 200.000, pelanggan tidak mendapatkan diskon</li></ul><p>Untuk lebih memperjelas alur percabangan pada contoh kasus tersebut, perhatikan flowchart berikut</p><p><img src=\"data:image/png;base64,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\"></p><p>berikut adalah <span style=\"color: rgb(51, 51, 51);\">kode program untuk penggunaan NESTED IF pada contoh kasus pembayaran di kasir.</span></p><p><img src=\"data:image/png;base64,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\"></p><p><span style=\"color: rgb(51, 51, 51);\">Pada kode program tersebut, kasir diminta untuk memasukkan input, apakah pelanggan mempunyai kartu anggota atau tidak. Selanjutnya kasir juga perlu memasukkan total harga barang belanjaan. Kondisi yang akan diseleksi pertama kali adalah nilai dari variabel “kartu”. Jika pengguna memasukkan input “y”, maka seleksi kondisi ini bernilai benar, dan selanjutnya dilakukan penyeleksian total harga barang belanjaan untuk menentukan diskon yang diperoleh. Berikut adalah hasil keluaran program ketika dijalankan:</span></p><p><img src=\"data:image/png;base64,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\"></p><p>Kondisi di dalam pernyataan IF-ELSE dapat berupa ekspresi boolean yang kompleks, dimana operator logika seperti <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">&&</code>, <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">||</code>, dan <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">!</code> dapat digunakan. Operator yang diterapkan pada sub-ekspresi akan dievaluasi dari kiri ke kanan.</p><ul><li>Ketika mengevaluasi (<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">e1 && e2</code>), jika <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">e1</code> menghasilkan FALSE, maka <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">e2</code> tidak akan dievaluasi. Dengan demikian, nilai seluruh ekspresi (<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">e1 && e2</code>) akan dianggap salah. Namun, jika <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">e1</code> menghasilkan TRUE, maka selanjutnya <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">e2</code> akan dievaluasi untuk menentukan nilai seluruh ekspresi</li><li>Ketika mengevaluasi (e1 || e2), jika e1 menghasilkan TRUE, maka e2 tidak akan dievaluasi. Dengan demikian, nilai seluruh ekspresi (e1 || e2) akan dianggap benar. Namun, jika e1 menghasilkan FALSE, maka selanjutnya e2 akan dievaluasi untuk menentukan nilai seluruh ekspresi</li></ul><p><br></p>', 'https://www.youtube.com/embed/yrGPuZB1SsA', 1, '2023-06-01 06:57:49', '2023-06-01 07:17:15', NULL);
INSERT INTO `contents` (`id`, `title`, `lesson_id`, `description`, `url_video`, `published`, `created_at`, `updated_at`, `deleted_at`) VALUES
(6, 'Perulangan dengan for', 4, '<p><strong class=\"ql-size-large\">Perulangan dengan For</strong></p><p><br></p><p>Loop adalah suatu blok atau kelompok instruksi yang dilaksanakan secara berulang-ulang. Perulangan yang disebut juga repetition akan membuat efisiensi proses dibandingkan jika dioperasikan secara manual. Perulangan yang dijelaskan pada jobsheet ini adalah:</p><ul><li>Perulangan dengan&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">for</code></li><li>Perulangan dengan&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">while</code></li><li>Perulangan dengan&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">do-while</code></li></ul><h3><code style=\"background-color: rgb(247, 247, 247); color: inherit;\">for</code></h3><p><code style=\"background-color: rgb(247, 247, 247); color: inherit;\">for</code>&nbsp;adalah kode yang digunakan untuk menjalankan serangkaian kode secara berulang-ulang. Pada kode for ini terdapat beberapa komponen yang dicantumkan, antara lain:&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">(1) inisialisasi, (2) kondisi, (3) perubahan nilai, (4) statement yang diulang</code>. Berikut ini format sintaks untuk kode&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">for</code>.</p><pre class=\"ql-syntax\" spellcheck=\"false\">    for(inisialisasi; kondisi; perubahan_nilai){\r\n        statement;\r\n        ...\r\n    }\r\n</pre><p>Berikut ini adalah contoh skrip untuk mencetak tulisan&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">“Hello dasar pemrograman”</code>&nbsp;sebanyak 10 kali.</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">for</span> (<span class=\"hljs-built_in\">int</span> a = <span class=\"hljs-number\">0</span>; a &lt; <span class=\"hljs-number\">10</span>; a++) {\r\n    System.out.println(“Hello dasar pemrograman”);\r\n}\r\n</pre><p><br></p>', 'https://www.youtube.com/embed/OAiZZqiSzxo', 1, '2023-06-01 07:23:07', '2023-06-01 07:23:07', NULL),
(7, 'Perulangan dengan While', 4, '<p><strong class=\"ql-size-large\">Perulangan dengan While</strong></p><p><br></p><p>Kode&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">while</code>&nbsp;merupakan kode alternatif untuk melakukan perulangan selain&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">for</code>. Cara kerjanya sama, namun sintaks (aturan penulisan) yang berbeda. Berikut sintaks while</p><pre class=\"ql-syntax\" spellcheck=\"false\">while(kondisi) {\r\n  statement;\r\n  perubahan nilai;\r\n}\r\n</pre><p>Berikut ini adalah contoh skrip untuk mencetak tulisan&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">“Hello dasar pemrograman”</code>&nbsp;sebanyak 10 kali.</p><pre class=\"ql-syntax\" spellcheck=\"false\">int a = 0;\r\nwhile (a &lt; 10) {\r\n    System.out.println(“Hello dasar pemrograman”);\r\n}\r\n</pre><p><br></p>', 'https://www.youtube.com/embed/KcsFEZerRDk', 1, '2023-06-01 07:24:51', '2023-06-01 07:24:51', NULL);
INSERT INTO `contents` (`id`, `title`, `lesson_id`, `description`, `url_video`, `published`, `created_at`, `updated_at`, `deleted_at`) VALUES
(8, 'Perulangan dengan Do-While', 4, '<p><strong class=\"ql-size-large\">Perulangan dengan Do-While</strong></p><p><br></p><p>Kode <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">do-while</code> merupakan kode <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">while-do</code> dengan sintaks yang berbeda. Cara kerja <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">do-while</code> relatif sama dengan <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">while</code>. Berikut sintaks untuk <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">do-while</code>.</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">do</span> {\r\n    statement;\r\n    perubahan_nilai;\r\n} <span class=\"hljs-keyword\">while</span> (kondisi);\r\n</pre><p>Berikut ini adalah contoh skrip untuk mencetak tulisan <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">“Hello dasar pemrograman”</code> sebanyak 10 kali.</p><pre class=\"ql-syntax\" spellcheck=\"false\">int a = <span class=\"hljs-number\">0</span>;\r\n<span class=\"hljs-keyword\">do</span> {\r\n    <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>(“<span class=\"hljs-title class_\">Hello</span>”);\r\n    a++;\r\n} <span class=\"hljs-keyword\">while</span> (a < <span class=\"hljs-number\">10</span>);\r\n</pre><p>Ketiga jenis <em>loop</em> tersebut sama-sama memiliki kondisi yang merupakan batasan suatu perulangan dilakukan. Cara kerja <em>loop</em> menggunakan <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">for</code> dan <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">while</code> dijelaskan pada Gambar 1. Batasan yang menjadi kondisi suatu perulangan didefinisikan dulu di awal, kemudian dilanjutkan dengan statement yang harus di-looping. Berbeda dengan <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">for</code> dan <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">while</code>, Gambar 2 menjelaskan tentang alur perulangan menggunakan <code style=\"background-color: rgb(247, 247, 247); color: inherit;\">do-while</code>. Setelah inisialisasi dilakukan, akan di proses dulu statement yang harus dijalankan, baru kemudian dilakukan pembatasan <em>looping</em> dalam penulisan kondisi.</p><p><img src=\"data:image/png;base64,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\"></p><p><br></p><p><code style=\"background-color: rgb(247, 247, 247); color: rgb(51, 51, 51);\">Break</code><span style=\"color: rgb(51, 51, 51);\"> dan </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">continue</code><span style=\"color: rgb(51, 51, 51);\"> tergolong ke dalam keyword di bahasa pemrograman java, yang keduanya digunakan pada suatu kondisi tertentu , pada perulangan seperti </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">while</code><span style=\"color: rgb(51, 51, 51);\"> ,</span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">do while</code><span style=\"color: rgb(51, 51, 51);\"> dan </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">for</code><span style=\"color: rgb(51, 51, 51);\">. Jika fungsi break digunakan untuk menghentikan suatu pernyataan (statement), dan jika fungsi </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">continue</code><span style=\"color: rgb(51, 51, 51);\"> digunakan untuk mengabaikan ,lalu melanjutkan suatu pernyataan pada perulangan. Keyword </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">break</code><span style=\"color: rgb(51, 51, 51);\"> dan </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">continue</code><span style=\"color: rgb(51, 51, 51);\"> juga biasa digunakan, bersamaan dengan Control Flow seperti </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">if else</code><span style=\"color: rgb(51, 51, 51);\">, dan </span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">switch case</code><span style=\"color: rgb(51, 51, 51);\"> di dalam program java</span></p>', 'https://www.youtube.com/embed/E9khhPRn8aQ', 1, '2023-06-01 07:28:33', '2023-06-01 18:43:55', NULL);
INSERT INTO `contents` (`id`, `title`, `lesson_id`, `description`, `url_video`, `published`, `created_at`, `updated_at`, `deleted_at`) VALUES
(9, 'Perulangan Bersarang', 5, '<h3>Pengertian Perulangan Bersarang (Nested Loop)</h3><p><br></p><p>Pada bahasan sebelumnya, telah dibahas tentang konsep dasar perulangan. Pada bahasan tersebut disebutkan bahwa logika perulangan digunakan untuk melakukan beberapa proses atau statement program secara berulang-ulang, dengan suatu pola tertentu. Pada perulangan, proses atau satetement akan terus dilakukan atau akan terus diulang, selama kondisi perulangan bernilai benar/true. Dan sebaliknya, perulangan akan berhenti dan proses atau statement tidak akan dieksekusi lagi ketika kondisi perulangan bernilai salah/false. Jadi, dalam logika perulangan, suatu kondisi perulangan diperlukan untuk menentukan apakah suatu perulangan masih akan akan berlangsung lagi atau harus berhenti.</p><p>Perulangan bersarang (nested loop) adalah struktur perulangan yang berada di dalam perulangan lainnya. Pada umumnya, struktur perulangan yang berada di dalam perulangan lainnya tersebut memiliki hubungan yang saling terkait dalam menyesuaikan sebuah kasus. Pada dasarnya tidak ada batasan dalam jumlah perulangan bersarang. Tetapi sebaiknya tidak terlalu dalam, untuk menghindari kompleksitas yang tinggi serta alur program menjadi lebih sukar untuk dipahami.</p><p>Sebagai ilustrasi sederhana tentang cara kerja perulangan bersarang, misalkan ada seorang mahasiswa yang hendak mensosialisasikan organisasi kemahasiswaan kepada mahasiswa-mahasiswa yang saat itu sedang ada di ruang kelas di lantai 1 dan lantai 2. Di lantai 1 ada 3 ruang dan demikian juga di lantai 2. Dan tentu saja, mahasiswa tersebut harus pergi ke lantai 1 dan lantai 2. Dan misalkan ada lantai 3, 4 dan seterusnya, maka mahasiswa tersebut juga harus mengunjungi setiap lantai selanjutnya, yaitu lantai 3 dan lanai 4 juga bukan? Hal tersebut menggambarkan suatu proses perulangan untuk berkunjung ke setiap lantai, dan kita sebut saja perulangan luar (outer loop). Kemudian, setelah dia sampai di lantai 1, apa yang selanjutnya dilakukan? Tentu saja ia mulai masuk mulai ruangan 1.1, 1.2 dan selanjutnya 1.3. Dan hal tersebut juga menggambarkan suatu proses perulangan yang lain bukan? Kita sebut saja sebagai perulangan dalam (inner loop), dimana inner loop ini berada di dalam outer loop. Setelah semua ruang di lantai 1 telah selesai dikunjungi (inner loop telah selesai dilakukan/dijalankan), maka ia melanjutkan ke lantai 2 (melanjutkan lagi pada tahap perulangan selanjutnya untuk outer loop). Dan setelah sampai di lantai 2, maka ia mulai lagi untuk masuk ke ruangan satu persatu mulai 2.1, 2.2 dan 2.3 (mulai lagi untuk menjalankan inner loop, persis seperti yang sebelumnya telah dilakukan).</p><p><img 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\"></p><p><span style=\"color: rgb(51, 51, 51);\">Jika digambarkan dalam flowchart maka ilustrasi di atas akan tampak seperti Gambar 2. Area yang bergaris merah disebut dengan inner loop, sedangkan area yang bergaris hijau adalah outer loop.</span></p><p><img 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\"></p><h3>Bentuk Umum</h3><p>Secara umum dan sederhana flowchart perulangan bersarang ditunjukan pada Gambar</p><ol><li>Pada gambar tersebut terlihat terdapat perulangan dalam yang berada di dalam perulangan luar. Tiap perulangan memiliki kondisi sendiri-sendiri dan statement masing-masing.</li></ol><p><br></p><p><img 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\"></p><p>Dan apa dituliskan dalam pseudocode yang sangat sederhana, maka bentuk dasar dari perulangan bersarang bisa dituliskan sebagai berikut:</p><pre class=\"ql-syntax\" spellcheck=\"false\">loop-<span class=\"hljs-number\">1</span> {\r\n    loop-<span class=\"hljs-number\">2</span> {\r\n    <span class=\"hljs-comment\">// another statement</span>\r\n    loop-n {\r\n    <span class=\"hljs-comment\">// statement</span>\r\n    }\r\n  }\r\n}\r\n</pre><h3><br></h3><h3>Sintaks</h3><p>Semua sintaks perulangan yang telah dibahas sebelumnya, seperti for, while dan do-while, semuanya bisa digunakan untuk kasus perulangan bersarang. Dan tidak ada aturan yang mengharuskan menggunakan sintaks yang sama antara perulangan luar dan perulangan yang ada di dalamnya. Misalkan, perulangan luar menggunakan for, dan perulangan yang dalam menggunakan while, hal tersebut bisa dilakukan.</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">for</span>(<span class=\"hljs-built_in\">int</span> i=<span class=\"hljs-number\">0</span>; i&lt;<span class=\"hljs-number\">2</span>; i++)  {\r\n  <span class=\"hljs-keyword\">for</span>(<span class=\"hljs-built_in\">int</span> j=<span class=\"hljs-number\">1</span>; j&lt;=<span class=\"hljs-number\">5</span>; j++) {\r\n    //statement\r\n  }\r\n}\r\n</pre><p><br></p>', 'https://www.youtube.com/embed/5BTDCPuC8EI', 1, '2023-06-01 07:33:14', '2023-06-01 07:33:14', NULL);
INSERT INTO `contents` (`id`, `title`, `lesson_id`, `description`, `url_video`, `published`, `created_at`, `updated_at`, `deleted_at`) VALUES
(10, 'Array Satu Dimensi', 6, '<p><strong class=\"ql-size-large\">Array Satu Dimensi</strong></p><p><br></p><p>Array adalah sekumpulan tempat penyimpanan data yang bertipe sama dan memiliki index. Array dapat diibaratkan sebagai sekumpulan variabel yang bertipe sama dan bernama sama. Array biasanya digunakan untuk menyimpan deret angka. Kemudian untuk membedakan nilai/isi dari variabel tersebut, digunakan index. Ada dua tipe array:</p><ul><li>Array satu dimensi</li><li>Array multi dimensi</li></ul><p><img 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\"></p><p><span style=\"color: rgb(51, 51, 51);\">Ilustrasi diatas adalah variabel bertipe integer yang bernama bilanganBulat dan berisi nilai 17. Satu buah variabel hanya dapat menyimpan satu buah nilai. Sekarang amati ilustrasi tentang array berikut ini:</span></p><p><img src=\"data:image/png;base64,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\"></p><p><span style=\"color: rgb(51, 51, 51);\">Ilustrasi diatas adalah&nbsp;</span><strong style=\"color: rgb(51, 51, 51);\">array</strong><span style=\"color: rgb(51, 51, 51);\">&nbsp;bertipe&nbsp;</span><strong style=\"color: rgb(51, 51, 51);\">integer</strong><span style=\"color: rgb(51, 51, 51);\">&nbsp;bernama&nbsp;</span><strong style=\"color: rgb(51, 51, 51);\">arrayInteger</strong><span style=\"color: rgb(51, 51, 51);\">&nbsp;dan memiliki kapasitas 5 buah bilangan integer. Sebuah array dapat menyimpan lebih dari satu nilai (tergantung dari kapasitasnya). Meskipun begitu, nilai-nilai yang disimpan di sebuah array harus bertipe sama. Tiap elemen pada array dinomori dengan index array.&nbsp;</span><strong style=\"color: rgb(51, 51, 51);\">Index array</strong><span style=\"color: rgb(51, 51, 51);\">&nbsp;selalu dimulai dari 0 (nol).</span></p><p><br></p><h3>Cara Mendeklarasikan Array</h3><p>Secara umum, cara mendeklarasikan array adalah sebagai berikut:</p><pre class=\"ql-syntax\" spellcheck=\"false\">tipe[] namaArray = <span class=\"hljs-keyword\">new</span> tipe[kapasitas];\r\n</pre><ul><li>Tipe adalah tipe data dari array yang akan dibuat.</li><li>namaArray adalah nama dari array yang akan dibuat.</li><li>Kapasitas adalah banyaknya nilai yang dapat disimpan didalam array yang akan dibuat.</li></ul><p>Untuk mengakses (mengisi/membaca) sebuah elemen dari array, kita hanya perlu menuliskan nama array tersebut, kemudian diikuti dengan index yang dituju didalam tanda kurung kotak [ ].</p><p>Contoh program berikut ini membuat array bernama bil, bertipe integer, jumlah elemen 4, kemudian mengisinya dengan beberapa nilai, kemudian menampilkan isi elemennya ke layar.</p><p><img 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\"></p><p>Ada beberapa alternatif cara untuk mendeklarasikan array.</p><ul><li>Deklarasi array tanpa mengalokasikan jumlah elemennya:</li></ul><p>			<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">int[] myArray;</code></p><ul><li>Deklarasi array dengan mengalokasikan 10 elemen:</li></ul><p>			<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">int[] myArray = new int[10];</code></p><ul><li>Mengubah jumlah elemen array dengan 50:</li></ul><p>			<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">myArray = new int[50];</code></p><ul><li>Deklarasi array dan mengisinya secara langsung:</li></ul><pre class=\"ql-syntax\" spellcheck=\"false\">    int[] myArray = {<span class=\"hljs-number\">10</span>, <span class=\"hljs-number\">20</span>, <span class=\"hljs-number\">30</span>, <span class=\"hljs-number\">40</span>};\r\n    <span class=\"hljs-title class_\">String</span>[] myArray2 = {<span class=\"hljs-string\">\"Malang\"</span>, <span class=\"hljs-string\">\"Surabaya\"</span>};\r\n</pre><ul><li>Mengetahui jumlah elemen array:</li></ul><p>			<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">myArray.length;</code></p><p><br></p><h3>Menggunakan Perulangan Pada Array Satu Dimensi</h3><p>Untuk mengakses (mengisi/membaca) nilai dari sebuah array, kita dapat menggunakan perulangan.</p><p><img src=\"data:image/png;base64,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\"></p><p><span style=\"color: rgb(51, 51, 51);\">Kita juga bisa menggunakan perulangan untuk menerima input dan menyimpannya kedalam array. Contoh, program yang meminta input sebanyak 5 bilangan kemudian menampilkan kembali 5 bilangan tersebut.</span></p><p><img 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d4IYekwQwtwcn33ii1D0GVYVIc85dNdh7rnnPrx4ooLsXCb6QDbo89BXvkQznGLDMU49+4oFynFNLxq9mMhVCRLYf+shRikyt2sHdR5I83NMY0Ucr7F71w7Ksk8o+uT9Be5/6LMsLO2YXX1jflyxOIlceP84l9eHNHlJVfTJFrdBgrkGFseJ0mVkxYC1y0PuvvteDj/4ECfePsbc3BKvvfQ6RfIsL2xjunKZbDiiTMr6iVPMTRqWyj6yskbPIKsiF996h/OvvcHzf/YXVGfOcu++A5x79U30wiXmqpp3nvo++foGhSqfeegzPP74T+Ocw/swK4br6Ojo6LheXPMagCwZvQSNtgU0213Bp3fewpG5nfQk8JX5kpfPvM+b5ZD1ec+ol9jYE9gxmbB3qOy/ZZ4vHvkUa33h3XOnOJZGrPlz3LJ3P48fPkSzMeGZ118js8S5omG06IhrxihE5hthrom8kq9y+O7b+Nn+bt6+cJr3Vs4y8TBNQq83xxBlbJ7JfJ+IcM/cIu+8+BIZF+Hlv+LRX/sGnz9yF+fPnOPMu8egN4SNyJ6+sHDXHr79nW/hR2O8e57bvnAX//CXf5Fnnn2eYnERMWGaFdz7qXsYDPq8+uaLjKcTFlZf4+jcnTzwC7/Ka6+/iWSBE15hfIb0zgv8+jd+mZWVx/kX//yfs7pyGZPzLI7e4ouPfpa/2LjE6VPPM9h4lVu33cl/84/+O779nb/i+9//AVbAwq4BD33uU1y6fI53RpfZd+gQX/r5n8MXOdV4wlPf/UtWXnsBEeHcW6/w9//Lv08Va771rW/y2nMvc/6lb/EPfvMbHDt+nMGJl1gfjzgYJlw+d57VuM7hgTJ8/016WcH2uM57l86gC/Psduu8uLaKjcbE99/g13/5F6nqKa+99CpPfneV/dsdP3jjdYqmJljExazt93XCkXvu4Wtf+xovvvgCFy9eIoSPpxylo6Ojo+OjEbvG1Rf/0//w3/NP/sd/QuWNmBILFliuHP1RgyBMSs+aj/QimBcmzmhSZNmVLKfAI0cf5Mlnnma9ENZcZFp6nBo5jhxBkpFSpMHwvYJpikQvDHOjiMYgOsKkoScBvGPilKFTqtK1Kl/JaFxgx/5bmIqn7PW5/76jPPvkdxlfOIvXmmGWEb1vhX9cIE1rMnHkrv1Zqhu8CE3hiU3EZxlNU9Mre9RNg2oiCxkptapiPnhiTIDhZhKXqm2/fFGUNHUNQAiB8WRMrywZT6bMDwZETcQmkpcFqYkYhneOpAoGPnhSTIQskJq41X0xcgkXPBkOqxoK53HiaDRRmULukcwjw4pB2aOpG5ImirygbmqykDGtKso8p0kJzCjKgrqu24K9WeeuF0cdG4IP4GFcj5kbzDEeDpkvesSqIROH13ZdYjA33+crP/NVHn74Yf7xP/5vCSG0hZldtVVHR8cngN/+r36H3/7t//pGL+PH5ppvu6JA7ZTaC40T1lNEg6M3J5gTNrLERgZFpbjcMxUDHxg2ibUk+OYC7y0YG1liXDj6lRKc0GikSkIIvu3rd47KKVNLmPeICA3aOh6FozFDQisyFJ0D78g8QCKZMihz9u/aQ9Ef8M5rr1INN0ipJhPoqVHXkSx4UpwyX+TEOqHVmDwUeAyP4JLiVXFNQyGeOB5TOtcKADUNTpU8yyEpQbXtMZLWcLPZ+jWZMAiBqq6xqmI+z5CYmPceV9V4TRQ+kCZTvLRaCbFqCDJTlIsNQTypmdDLcprYtHoKTlvN/tnavBqmkQBkDuqqgRjp+QDTKQWCIOi0IjPFJ2UgQN2QzcLzaTKhJ65tjdRZm5QlemJIjKQE81kPndQMfI42CT+bG7CJCezavYeUEr/3e7+Hc44YU2f8Ozo6Oq4z114ICPAJggecR4AmKBIcycE4a7X651y7a87KHMNINDQeXj/+PrU3UhEgb9XoGjWCtbvvJkbMQZPa4TxW+FaBThWfBerNIkMBF4StHh4zYmxwMVKWPc6dPMbpk6dJAqmuyZ2ReUE0kcXIIOtTVVMKcdRra5RlDwkeTTX5ZstdU5N5R9PUOOcoQiDGhpDl7c5YlTgZ0zQ1ZVkSfNgydiELWDKm1YRM+hRFjiYlxhpVIw8eU6MMjqauEYzgAylFelnRihg1EUPQ2NDLM6aTMYMyJ6bW+GvTkDmPVlXbfukc0Yw882QI08kUIeDEUIUsC+19kiFAngU0QdKImCNpxPv2LZPnOWZK3TQIjhQjeZFTNQltIs57BCPPc2IT25eANgrw1ttv8c57b5PnGSnp7OWxrhOgo6Oj4zpyzR2AYEIRwauRPDiEXFvJXDWlUMOSo2zaCYGaapz36DQRJOIU+llAGkObmtoJDiMpRKStWnQC3reiszPlrpAUMW3lgPPQCtRoKx3szCApzpSQBTQlYh3xeTt4IPdCU00Y9EvqSYNTUJ2QuVYtv9/LSRrBOULuqZuaKlWgRggFeeZpmqYNyTshVhMajBAyitwz6M1RNc1MFEdQVWLd4L0nzzyQqKdVW7DohSy06Qo1xepWXTHPc+q6xokR47SV26WNAvjcISTyzFFXE0LIyBCiKS4ZwQvOWsng4IymifjgGRQ5TluFxBgjWKKaTnFO8CGjmk4wVbIsB5dIVUXwjpRiKz2cEnmeI2JIEOrpBO8DZZGTUkScp5qM2vz+ph9G65N57xiNxoQQttTwuk6Ajo6OjuvHNXcATNoiL1wrAuStnfTjDApxBBWKaK3OfObb+wuQZdTMQtwkooB4Rz6TCBZpx93OxO9wzIxGaofalOaJSYli7RAdmA0aMoIJQbK2bU4bRCD3Dm0agnOYKWWWMRmPybxHnLT99M4RU8I7j3pQS0QUy9tFO6DWBhDIHQ1p1uLoETOiJQDqFJHNMDptMly8oLMLo0TMGxIc0dohROJmIX7aeoFxnIIY4hym7UhlAaKmVl3PDO894lpVQDNrn8dsSI+aza6jtNecBCbtijUioc3r+5DB5nGDgLXPSwDfz2k0QRDMFPGO2ho0Gd47fNZ2e1jTzPL9idxnbSukbDpr7evSNJEQAiLyiZj+1dHR0fG3jWvuAFQehjmtkbPZnHlt9f3bAG9ryBtnqNuaKwcB4qywzGZG3oA8bR5ZPtCzaO2cn1Z3n/YcXtqTytXTBRG8zSISzsD5dgahgRe7Ik2rhvdZ2zrYWsr2RN7TbE5smxnxTZVDBcTJVmgbWuOa2DS0mz+dHdOYuThXwuHmZGtb3P7fbf2yHZZEa/Q3/y8g4q8MKA2ydT+lPY7JlfO00/quej5X3ceuur15wM21XjnnlefX/pwP/LzdzrevhzMhXDXHe2vkzawIYHP9V2RWP3i7o6Ojo+P6cc0dgCTQ+NbwiNAq2M0MpxizoTCbu/itQX6tAdvaIV513w8df9PwfXiESis6ZBgOMcMJW8VnJkYSIUk7UKg9fjuGmK0xtjOnQ2QmZdw+2NmV82wd76o1XP3933v7Q70WHz7mD93PPvp+8qGff/h+W7dn69a/xrY6+9D9P2INHz7Xf2gNQBvV2PzxX2vXO4Pf0dHRcaO59joACv3miuFMAsm13QE4traq7ax5a+fSW2t4N3fWou1xvEHlP2ght4yKfdCMNGH24FmEYWbXQaCRNiVh4lAEZzpzLASxNlagwuzLEUzbUbl80EB/kszW5rIdVxviq2IVH+E4/LioaBtluYq/znn4ZF3Njo6Ojr99XHMHII8wX13ZYTYeqsBWmHgzLVCFmeHXdie+6SiYgJv1jKO25RhsbYyvihJc/T3OZgvLLGqwGTlI8sGUQhu69mA/XHBm+Nl9HF7th84j+kGz9ZM80n4rxE973XWWxtiMrlxtmK/V02gcqL96EVeiPB0dHR0dP1lccweg8caw+OFP/PAhe5sltuYF6CwH7NVwKGIGJJIHsfyDBuojjYmRx83drQMLYK0lCpsPEtqdv23mpN0sbbCZq3eztIDDaYWQrjKiguIw78Ba98IQcDXwyapc34yKfDwIIf0Ee0UdHR0dHVvcOP1Vs60w/GbGfSu6L4KY50cfxC1bBr/d0sb268rJ2Ax/2ywPYVfFpGV2TmZiOEjCPmDY5coxJNGWFrqtOoGOjo6Ojo5PGjfMAdisY7dZe9qs5I5NN8BE/prd/kchYNnMOCeQZnb7iuEHwVQQwqxYcDOEv2nYr6rQlw+XGNrM2M9aErbW5vkYt9MdHR0dHR0fGzfMAZArfXFXWtXsKuNrbma607//QFeOOPuaOQHE2XcHhFnoHmg74z/isbZ1LiNrz7/ZSSCbTXbWFgJsFhuY/6EjdXR0dHR0fBK4gSPYHDbL9zsESwnnIJnHpM2zK4L/UR2Ard3/VfXv5oGAkGPqMRLmI6Yg4tGkW/Kzm3UHiGLiZoWCgs30B8x05iAkZtUL1/ZydHR0dHR0XEdumAMwiUpZFDgSToxmWuN9W50v1rbl2Q+pAPx1GLiKrXC+hTZHb21BoFmGczlRR2A1ZgJ4TB3Otxr87c6+1RCIYjhHK81LwPlAbBoED5ZAEg6lq3fr6Ojo6PikcuNSAOWAcYoEA28JJ63+PU5m4fqrFIL+gxjQsLXrt4Cqx/tASgnnEjENcVmD+EhqWn195wKmbUdAm5IQBEPCEBXD8Kg2xMpTZCWWWifB2ayuoOtv6+jo6Oj4hHLDxq81vmB+eS/3PPgQZDkS/KwyX2dV/K0m/o/OppxfBpbTFugZJmOKuTG79ydcsQJ+zLblnKJUQqYkq2YdA+0EAUExP2Zxp7Gww8h7FQ0bqEwwqdtUg7TpAOm6ADo6Ojo6PqHcMAdAQ8HS7n3M79yF5AXRNlvzNr828+0/Ko7W6Acg4J0nxiFFf8reg/Bb/8UX2X9rxrZdJf/wt3+T/bcsUad1xNUINSINQg1SI9mEX/3NL/OFL92HLxrKfk20Ydv3LzXQfKjNsKOjo6Oj45PFx5ICEEBNWuld5zDn2LG8ncX5OYgN58+c4UJsmF9eZnV8megmKIL4QJScPbccwhWGSGB07Bgb44ql3XsZzC+ARtYunmNj9TJlf8D2vQdxeYaMz3P2zCrazIbqWMRnSh2HZP2MYXOG3pJn14GdvHP8NfqLcODQgMsXlfG6UhSRnbsWOX9myL5bFpjUE6rYsH1P4PzJRNFTMh/ZuWMZsZoL59cYTo35xZLgHQvzfeqq5uzJCgWWdy0yt5SRbIPz7w3xmWNuqeTC+SmmgeVdMN0wJqPU1ing+Js5PB0dHR0dHf/xXPMIgJgippgEatdnwy+w64FHuOWnvkh56+0s7NtLyDyhzNm5bzfr49MMq5OE3hyT3iJ3f/k3WHr0l/GfepRP/Wf/Ob1+n2LvAY7+/K+hd30au/UwzfwSqSjYd/9n2P/5r6O3Psxg9w5SpkhmQI0jgrbjeSM5x86O6W9fYHFXxvvn3iHm6zzy1b3c/9itpMJ48ImD3P+l7VRF4tM/dT9Pfu8VVtenbLvNMWzg4NEFvv6bRzlwf8Y9jy9yzxNz1Nsv8PAvLPHY35nnlgenPP4LC+zYv4NsKePAg4ss3BN5+Fdz7n1wwPZ9GzzxKzvI9jb4bYEv/nKPHfsahDFeBLEenaZAR0dHR8f14po7AM451NowvheYG/S57+gRnn/mB3z/e9/j+089xfrGBinl7F7YTriY2GX7qeM6d975ELdsX+ap//tfc/yZdzn13jFWVi7h8kC5OKAR5eypk1y6cJ7kDNcvyPoFVax5/bVXiU0kxprNubOmDsjoF4tcXqlYnFtm5dwUjZ4slDz15BscuuMgu/Yn7r3/Nr79l88zv6Ts2Gm89dbbrK0f4+67SryL5K7k0pkxf/nvXuWv/vQ0qydzgjl06nnhe6f4s3/zPs8/dRpNI+AcVXUOVJBYsLg0x5mTIzZWHbv3Fey/NWe8XnLuZAQNJJ2lFTo6Ojo6Oq4T19wBUAxxm0NnlB0L8/SCp5lMiNUUMcOLkA2WmHjhTN3Q33cnlMLC4k7eO3uM2E8cvv8BxpdXGDvj3Jkz/PG//kMmq5f43LamOosAACAASURBVOc/x8LyNlJV8c4LL/LUd/6Sg4f284Wf+jyujf3Pqv8V7wqC9HAMaCaOH3z3LV569jRx4hD1nHxvg9On3+WRx/fx0svPs3ousXdfH1HlG7/0OJ+6/wGOHPoU2xYLvPYYrQpSz3HpZMHrz42xKYRmG7axhyLdwuvPXeLiudM8+tgh7rh9mbXzl0jDPt5DMy15/pkTHDg4xwOf3s0zf3WaZrRIFgaoVhiRv4H0YUdHR0dHx4/FNa8BSKogghchpcjG6kXq8ZCvfekJnDa89vT3uPD++2gzxfVKPvv1r7B28hTnvv8+Fy+c4t4nHoddPXbs6HPizbfoJc+nP/dZsj37KOfnmZw9i22M2LdnDw8+9gTTbIGSxPsnTmBJcQRSjIj3qBrOCoqwRJxMuXxeESuohyX9eQex4MypYzx860G+9ScnyWSJbYvzfPuP3+bEe+uYeurRAzz+yGMce/80GhwB0JQjolgMSNXDxkvItCAvKtTGrF64yC237ebI7UcJdcZ4OMb7HmdPr/PZn95LM9rg3DHFNwMS6+Ac4uxHH33Q0dHR0dHxY3LNHQBxrYRuaiKIZ7qxzv/7f/0hxaCHNhOypkLMaIZn+cP/9fdwOiSPG9jQcWLyLKdOv880GSFMoEnsJOfVp5+hmXsdc0JaX6cXG9bW13jyj/+MseSY84TRMTwes5lU72wyYGyE555+FXURSQXe93jj1RNEXcO7Asw4c3yDerhAMxV+8OS7eNvG+PIyeQl/9m9eQVNCzGNWtRfNRSBCgj//d9+Eahd5WKaaCoSMN14+y7F3V6iaQNMIPc1QrSnziFbCs0+9i0vLOBwiDicZSRucdNLCHR0dHR3Xh2vuAJgYyRTvBa/gzBBNNKMNxCIpRQqBOUbkl2vmmpogY6YsUqcRfkVZUI+6IdF5mpQTYoK6IToQSThVyijo2gY+ZEyDkGmbdnBO2imCBkg7/Kep2pkAXgosGo3C0tJejtx7kOXdkeeefYvp6jx5URNHi6jOUQQPWlGPS5AJog6RVmFQtHUutM4AQWRCTJfwXjDrkabbGFYJsxwEYhpw6M6Cux/ay/G3z3LxpIJmiBtjmtoIgHQFgB0dHR0d149r7wDATCTPcKRWY18dWeZpGsXTFgoWqcIRSb4dquOYEiyhbkzjhGBKkYQQHdOQUKcEM8rG8ArJCVGUTBvy2lB3VTmDaDvpb1PdTz3gZuJCSsAz3qh56fkXQWrq8QKZ62M6wcVFcApuOJsvAKLFTGGw16oUWgEGXieYRKABN24HCFmAtNiKCs3WoVpw8uQZTq2cJNYFabxERo1z1Ux+yGOinbBgR0dHR8d142PRAdgcs+swxBRVZbQ+pNfvEURIdY3PhDokphLIYkmhFYmccdHQuESvLpivhHHWDuPJU8IkUQdw6sjUk6kSvRJFceZmQkLtuVsp4SuTBQVBRFAD1VY2uJ4qGudwDIjpEtC0jgobmKsR2xQHLmbaAhliAZUEeLwFBD+bLSAoAXPpqsmDbUNC0ikSS5ga1bgkaI7IcLbMnK1Jg10bYEdHR0fHdeJjiQDYrJrdzaraMoTlpSX2H9jHcG2N1fPnqUkU0eFTQDRDvaEi5NEoDPKYISZEJ4jY1rQ/A8wJrdF0rTHeHM171ehemxlU2TKqDlOPE8GF2bE0R9ICeMWXK1hcQHWI+TQT5mknAoqWmNSIgKHg1hHL2vNpDmQYgmGYG7cRBAOxtg3RZxVN3SfFksxliI1xboTE+dn6Np/DDRNm7Ojo6Oi4ybjmDkAQRzYrxpuiOAkUZcFXv/o1du1c5rvf+SZrF86DOpwJzgBpMGkHAPskeGv309ELjtQa3dkEP4cg5kgibLbNicmHdv9cZfgBsdkxZrUB2qr+CwFcxIiIloDHJOKs3dW3A4LatWzJE0sCBBNF8Virezj73h51FgKB2c+UdsaRmIJOgZpkBerkiqNi3e6/o6Ojo+P6ce3bAJuENq1BzMqCSdXggHuOHuVf/v7v8+47r5OJIJKRREihzcvDlQB4Eq7k39kcuvfBCvkr5nJz12xX/eajjKnNHIHNY/n2tmsr+03nrhzbNo8wO6Y0V44BbQ3A5qrlyvrb3/kfWiuWIZIQJltLVMrZSTbHEH/Ekjs6Ojo6Oj4mrr0SoAhZliEixJTIQiDPcpqmNaJ5ls9y8Z3F6+jo6OjouFFccwfAzGiaBhGhaRp27FjmZ372Zzl58iSrKys0TcR1bW8dHR0dHR03lGvuAGR5TpYFnECeZ5y/cJ4nn3ySo0fvYXFpCYCqqjoHoKOjo6Oj4wZy7WsAYiTGiJrgnEcwVlYusbExBMB7j3PQWNf21tHR0dHRcaP4WPrORATvHKoJmdUEqCreO9QU1W7ufUdHR0dHx43kujSeDzeGpJQ4fPgwsYl4n+Fc1/Pe0dHR0dFxo7guVlhE+IM/+H0OHjjIz/zsz+C9I6UuCtDR0dHR0XGj+FikgD+MauL06TP80//5nxJcOxxIJKNrBOzo6Ojo6LgxXPs2QAQzwczwwFyZ48VwIiCOhCdJjsmPdmpvip+N+I0OkhdcCNTJIMK2OrB7XQgRhhbBO8w5knOoRsa5x4XAYKJsmzq8Cpdy4/y8Q3xgUMGgFgbJ40NAkxGnkW1asDQSRALrOVyYd5ycU9Z7gosNvmnYkgAywWs7kTBrQCcN3hyCQ81wzlMJTHJPHVw7pdB5Kg9Tb2id6DVCXhvzlpE30MSE9nKmmWNMInOBgS+Yy/v0xrB7XUA8p+bhcgGalJR7zg2US3lk4isaX9P4isZXRF8RXQW+IVETCjCr6GmNmSI2j489jEhZtrONks4z9otMegPW5xoYRbxGeoxw41XWSsflQca0TMQEIWb08Uid4+J2vO6lnswh9KjrGpEGdEqMEwQlU8+APplV+GyV2p0hhou44hIpnSVzfZpU4wTKtANrRqzkq/jgUB0wyXIW/BqZJOregNRkLMcF+uvCfC30o1K5RBJHngKNmxKIJCJFgqw2RBxFI6gzxjol9zkN2zkddlL5hKaK5DN02mOp6lPGIbU5nIGv1+h7yFKBDxNUepDmgYiEETRG4xKWEmW2g8YG5Iwo3Coq4NQTNBEdVOrIYkleKJIiUuUMfY3L7mTi5pi6jJhKzI+Y6pgFPUylOU2RSC6wkk+p0hzj6SoxRBKLpGnCQonTIVpkpF6JUdFgFFYR6KJwHR03M9fcAZAP3RaRLUV+mQ3nsb9BC+A0QD1bZVBwUamnNeSBSeE5lyUu9QWPMFeUuAQkJUfoS0keE8UkcWhuJ31z5OKZi8LShtIfJ+6d38P95TL9iaIbU0IWyOf6hEa5o9zO0hQGNWwbKvsnge0To0cg5Dmtid8U/AUVIPNkZYGZIQbBearUkJuwNErsqQL9RkiayFRYspwQMkY5TDw0TYM6GKhj+0To1UaZF6SkjKop00vrPHTLnSyUA0RhcajsnjoGSUhNw8JE2R0zeuZxZjO5ZcGZbyWUTVATNjYmmGQ04nFFYGJrVKHGwoCVtYow75GyJgXh1ruO0O/36Q0GBJfTKPQWFgl+wIE770AQ5ssezoG6CnEV6kZEWaOcT0SG9Bc8iLbXt+yjkpPUMZ2OEfpoGjAYbOeeo0fJswX62TJNrElEQsio6g3KXsBLICp4X3D49iP84i/9HeaWlkjjCt8fsNIP2OED1Pu3M+7nBF/gywE2P0dOBgmCZDgXEJdh6hDnEXUs9ObZGE/YcetB7jx6N84DWUaDIj3HBKPJA0qE4MiKHnWCiRpVahAc/flFHvupn+KLX/g8B289iHiHYRw6dAdf/epXeeCB+3HSTsy4olkpZHkgFhOa0QaFg6xfk2nNaLqGpA3mCyOjplBjIPPYeERPFDdNuDH0CMy5ht2Lu5BK8Kkmd+BVyVxGUzX82jf+Lp//whfp9+a2hLk6OjpuXq59DYCw1eNv1goD2Y+h+tc4SK41sN4gMyH3nhCVEofzjhiEoFBbQ4VrhYbqmlB7fKxZ8CVHtu9nUR2ZGou1Y0E9UQyLkUODHewp5ihCxjQAdWR7MWBxbp4QMooI22rH0tgYVAIx0aCE2c4f2vHEjRhTbaMQziBXyCM47/FN4kAseGx+P/smnlIdXoGqwcSoM0EzgeAxg1114Mu77mJ/LChGkeiMlDvmQs4gK9FBDiIs1kI5jgQV+o2wXAfySWyHKiVHntrJiU49jgzVgM8GhHIe8yURoZomyp4nyZRYO8pigXFco0lTyqxk/559bC+XGE6nxFhSZ31WxbEw2M99n/kMA18gVYURqZNCUCRMqfQ80V1EiiHTOGzPFXOq5KlMsQwsb4haktIOvF9geXkPRVimnvSIfkoojEkzgX7NxDZY8AtUSdi7dw//6B/8Dm+/e4aV4RiPkO9d5pavfYGlB+9h+z13E3dsY0LAti9z95d+mn6YQ3yBqWcjKpUPJHPEkCHmSdNE3p9jcdd2Du5YQKYNWEaTprgiMfaJkQRKMaIZE8lR36Pu9yErcD5nYecyn/ncw2xcuETVRNSMPMuYTqfs3LmTn/+5nyPP8w++yU3QGuqQKDSnUGh0nbkEczKi7ytsfImeTfAmeIW8WCXTij6Bwhp6MSFpFaugZxm5Xiazimy6jks5PUq+952nue+Bx9izvBNxYeaCdHR03Kx8DDUAwgc3+D9epr/X0DoVgM722q6O7IiBxUaROlH2egxD4hzr9LWgRyKmml6zCE4R7yinxo7asaaR1DScnIe4WPDm+ir7BtvIp5GqTIxSZOeKkuc1r668z4UFobIGwxPUGLiMwkI748AJKoI5Ibl2/HDwnmY4oa+OOQI0iaYPPTyLlrFzBKOhsBJr1rYV1C4RamUwjpTiKUJAIxy4rNyf5jg9ElDj2A7BJ2NRSt55/U3Ol4kqJHwZqJyyNDV6l6ek+ZwLPSN3nhANFTf78qh4XBZYm04p+3M0Tc1CFull+1jbWKffE5IYKTXt47NlLg/hL/7037JYOrJeD2GRaSaMpGaht5u16YQsFFhcb6c0ZgOiVTRpnWK+YVyPMDN65TxWK71ikQuj0/TmjEk1pMxrcluiqTzD6Sp/+d0/Iq92kocBsTfFZTXNeoRMkHJEujwgH+zly1/5Ii/+1Td55ZV3aBolm19g34P3curCBc4+8yqLzrFqEyocfmkb9fbtrEfFej1Gown59kU2mkjPBTbilDIGtKlwRclTzz9HOV3jYFYyjDn9gWd9dIne3EEqE7anisvmaUKO1MJKDkvOUa2PWQ7C+cuXeP2Fl1kPCzSSEBc4fuIU2987xuGDd2CmH3iPOydk5tmIgo+JgUtY5tE6Me8ust40lC4R6hUuuQzJ1hhNDWGOZhrZNqgZuojzOdM6UjhjoUzE6LAqMZYSiYm1i5c5f2GDzz30EP/PyXep1Topjo6Om5hr7gDI1r/GpvE3s/9o5b/QpvpnM/MMceCdZycFj+07xCAvmaaIU6UavsinslvJs5qnV9/hyOLB/5+9N4+SLKvvOz93eUssGblUVta+d1X1Sq9Ub9ANiF1qECAZELLOMEYjj2GA8ZmZcySNPfhge86cwbKEwBpZsi3RkkAYMJsaA70AjZreq/el9qysysrKPTMyIt5yl/njRi7V3ZJadDUgiO85LyPi5Xv33Xff8vvd3/L9MeA1R+dKBhPJ8KbdbG9ErMsE35p4lrGlgmoJcempFbAujqjngpt372aPbjDfanHb3BGmKoLNqsplwxsYURUK7TnYmuBocxYnwAofCgD64KJYn/Zxzfa9DLkI2874wdJpqkJzWd8W9usBRgaGSCpt7ps6ge10uGrjLnbXhxmQCU8eeppmn+Y1jQ1c5PpY2nkRx0SbpZlj9OmYm9ZtY2dlkLsmDnOPmCEvCi7U6zmwboT6poSTSc6XF49Q5gWqK/yNUBgpSRoN3vy2X+TOv76HsTNnecs7387k6YM8frjFgde/iQu2pMj+YZ54+H4OP/h99lx1E3uvvIG5sfv4wVe/inGe2voRrn31q9mxbzva7ePp8W+xVOZUlMeKUFnRqxb1gZx3vPsmqv2OajXi9KkmkVvPlz73HS66qp8rr7uQkYEK8zPH+frnjrNu3XZ+4T1voFZb4It/ch/zpxfoH4l5/ZtupmqGSfv7ODZ+L3d/7mlckrJjz0a+8O/+hNZimz6ZsJQVFJ2cC3ftZ/BMxsKxE4ikwqWvu5ntN16PrMRc+sF+HjtxlEcffpSr3vBanJZsSOukAzUO3v4d5s6c4bo330K0fiN33PqHNM+cxa/bzC/+2ls5euxxNmw/QK7h7t//JEn/ENde9you2LiLctM6Oicf4I6/+C5RmlBaSyOtMFc6okRjc0tZ5ngf7t3nPwslQpwl9TUGBtvcfOlW0k37SOuKi2LHf/jK7Vx71aVs1J4zephNOxSP/OAgh5+a4dprL2bDcErfSJ3mouCLX/9rBvsrvPKaS0krm8nmF7ntwTFmZtsszExz5MQot7zmYuJUUnZcLxC3hx5+hnHeFQDvPc6FGY6UAiEkUgp+WC9AoUJ1wMhBbIOfXUiB8Y4iljw7e4rRbIE39u3gEltnsISOdCjjKI2Bakw9KyDS/GDhOE/PLfLGdXsZqfQxVkyB0ixFnrG6Z7YCBY7vTR1jPEvYNbKJpbpiwedcratU2obvzz/DeFriASMkVoQ+OYKyElloSEW97bCTU3SaS0w0mjjrUPNt3NA2Hp48wSP9BUoqdnqNXOgwNj+Grq9j//BW/mT6McrmLIN7+/jvp57imaSDVIpWWfKd5hHeuv0V1Eooa5I4l2zsG+TgwiTPtheQ7YyioZFSYlxwn5QCSikxzrJkLTaOSAYbpAP9zDxUcP3r38L06UP819vvId7yCt719rcy/ehBHn30fk7Ml7xipIKXMVoL9lx9JeOL43z9P36Tfftvod4/TduUwb+vKnhXwQuJLT1ppc7BR77Pvgu38fgTx7jqshtJa4CQPHtolDOp5LpXbqZ/YJFTY01u/dO/4k1vuhhJDS0jlBbUByy3ffav8Drmdb+wFUSLJImwtk1eniGN+4kKQatjOPHYUxQXw6ZXXcHuy/bx4G138OAd32cxSlhcajL3ve/RUlBPKmyNGpyeGOf2797Grgv3MNg2tKcWueuLX2f/G96MKBU2l/RXhohVjVOjkzz06J3c9OafwxSaSy4/wEQr544/+3O2X3slW6IZljotBo1BSUFZ5uCrOOtAaLTWCBEyYp77KAjviawCUeXaqzcyoBzf+MpdbLugxrad+zALOUOVOqK5xG33P832XTWGh/awY28fWa751m2H2bqnQjw4TLNYx6ZaH4o2Tz5xkPHjo8zn/SASlJJ08kUGBmoobVmuRNlDDz38bOJH8PS/tDmGWMMYLD04PKUMq7RxLGUtFnxOuhR8/bo0DMuUoTYMWoFQmjIWFMLgOzl1K1myBaUG6T01J1knUxpootzhnSNPJVGa0JdDNfMI44i9JPYSVxrKvMSXFitcCPzruiiUg8iD7WSMHj5C3mqxa+Nm9lfWoRx4IaigwDhK4UnaJddGI1yth+nvQNosqZcCrwSLdcVsxbOUClw9oeoksRfgIXHQyICipBrFVAqHLAyFd5DGeOcwzmEkGBmO6wRkZc7oqePU+6vs3L2d8bOnWOiUbNi7k8cOP0vLeDbs3MX43DzTC02WWguM7N3OYidH6hhQFNJy/OQxKlpx4aUXUCwsUtoQlGmdxbsC7w3WGYwpWVhcwmOYmWvjxRJDIwmvuvkiqlVBa6mkyNtAC520kbrEK4vQHRayGZQsKfMW8/Oz+EKgUfjUU+RLaC0xkUVHnkx5msowPT/Hgw/cyx0P38O6/dtIh6qImqZ/ZIDmzFkMFoSn0lelr5py9JmnKcuMxx5+mEcefYh2tkRaTUiqdSaX2oi+GrKe8sSRoxw9PY2u1pian8NUa8j+Acamp8mVYNeeC1hcXETHMa4oQjlpHRHrFO88eEesNc57rHUvEBMjiJRA6RZDjZTDh4+RJCU3XLWLo2eaaB1RrQjuvu9Z8k7BiSMnueeeR+ivCppnRylmlrhwUwXXbiOxnDg5zqNPnGBoWPPqn7ueal+EVRYRC9JY0G4vIb2D57gieuihh58tnP8YACEQQnSD/1hZfljUC0ErCg2UEjItUUIQZZYNS4KL5SCDQ8PIosLjrTEGneXSeDO7RrYxNNDHYb/AiT7DzqhkX7yOXVpQSM0j5SJRFLMxGqDesVxs6xQ4Jk3JsIvZLKv0RxX2iyFsZljstMgG6+zqH2HEZix5wzN0Qk0DJ1jWU6yATIFe30+z45iwGcMiYdQLWqbAec8FjfU0k4xsaZFYabwxJM4jIsVsbNGlpyUsz5bzrF83TNmao503qVUrbK32kZaC4cYAF+qSM515luhwcW09aglmU4ehRUt4HEGBEsKGbAVjKZqLXLR/HzPz89x957epac3Zo4e5/MKrqJVLbNo1yDe/9heI0lGp16mWHYb6E3bv2M7ZQ2dJIstFe7czHO9ja0NzeH6JulRIC0IphDQIIYhlDZfXifwAeTOlnkS4IqJoazSSsm1Y3+9IaCAwDK6LGNm2hUajwc49m7CZg1JjWzXKXCCLGN+qUyBwzUUOP3OCd77vg/zRH/5n2mmdTRfvQ0ZVEmJ27dzGiQcfYnz2NAvViGZrlp27t9NShsOHjxD1p8zMTjI3M0nHdIi1xytBR5TUXQfdbnLFK6+hc+Jp+uqC6fHTuFbJyKaI9tmTLBVtFtttNm7dzNWXXc7mkY0cmZsly9vUkgRKS+EdtigREQgErXYba8xKqey1cF7SsjFeG5odxba9r6BmW1Srgxw8dYhkqMbxqQXG2o4MQ553cCrGuA5bt1XZtanCvh3reeTkGB2m2L97O9KXZKVkLpe0sg45NaTWXLh/Dw8dfJLWQgul6pgf/tHsoYce/oFDfexjH/vY+WzwgQfu44EH7mfZax9FEcZ0I/l+CFSMx2i6+wtyHXzuW9qay6ojLJg2J6Ocx1oTjKWGJe1p+pxCwtjiNE+LJovCUJgC4TydsuBpM89JlRFLTZ+KaWUdOpFgNnEsmYJ1SR3nPWdNm0VRYvKcadvhTFTSkY6KUEzbjDYuJDgKWLZ0OAS6kmAiSZloxosmT7dnKCJB4S1NSjqRoHSWRZNxyreZ0CVLGkbzBZ6UTWbIaCnHRNEKOfBGMO9yqCXoSDPZaTLu2+TWsGA6NG1OYQ1EmsUqtDrtFbuL9CHWW3mPwtFpNukszHH06ScRZYYuc6aOjLKh1iBfnOXpH9yFmD1LRShUZiimpxBFi6nRMdoLJbOLkziWaE1Ocui+R5mfPkNfniFyj0fjXIlSCUUhmZ8tOHl8humzJROnMuYmPNPjBRPjs0RKsTBhePKhSeanHXHSIE5qTJ5pk7cURRvmpjOmz7ZZmiuQecz02TlONw0VnzB+qsmb3/4+fDbBs6fGqSV9DKR9xJmhfWKMQ488jNUOJTzl9Dw6L4iFpTU5A9ayMHoKO7eAtAUDXmDLDrH0yGYL33G0Oh2mDj+EyjrMnJkgzSXpQsb8xCGkF9ikSqtoUxQFFSE59vS9+AyGGwPs2baep556BFwVpz3COqK4wZbt27hg+yD33X8PmYm7XBGWQkaUYggBnB2fxVNlfHqBxw9NcLbVx3xhODWdM5fXWdJ1rIjI4oSq8PiioF22SGSD+44tMi09fQODJD6hKDV3HzyM95pM9bF9z8W84sL9fOtbd+FabaxQuBfJx9FDDz2s4sCBazlw4LofdzdeMl5mJkC/Ygn4Yav/5lpQSh/M6y64AUotaSeC06nhYLbA3bJFNCBo5IIyzxm1Bc46YgFZLqnnjgm1wLHIs6Qd7YqiZoDFJUa15SnlGI9KlNbEkeS4m2FAR9QWyjCrj2CxImipFomx1JxnckCwuanQjmXdBCcFLlLM2oy5dgeNwOA5vc6zpSmQWnJQLSIErF8CE0ueqhZ4tcBQJiDLaDuNiAVOQuYyzGyHupOU0tIs20z6JayKKBJPmnuUEjSlYZR5rPA4oUhjT2JDTIIHnPd4IdECbHOR6U4L5R0JAuMk2kzz7ON3UaiIeg6pE3REE2VmKSfbHJ6rkxQlUtTIZiaZazYRWclA0cBrQ9V5ciMoY0dWzKHiBsJFHDs8jo6rjJ/MwKecbi8hbMTUeMbp0UlSP4DPKsi4wmyWc3ZqDhAkWmA7OZGqcOpomzQewWWW00czfP8AoiiZmezwf3/iVj7wjgt57Okx5h4dZb4yxaKyeOUg9iTCMbxgUbPjzKSTdOKSSikws3N0SqgDuIKG1CA8Ls/QZcb44aeY66tTFR0W58dwug+bxeTNDNW/SGYqXL5nF9VNw2zoH+Svv347zcV5qvEAwjheedWVXLRvG7d/40G+df93sM7xT97/a1z2yqtZmHjoefe4E9BREX1GsCAEB48dIxWWJRWDE1itKTJDpFKkqyPNMDKeYfOGChetjxhMazxz7xmacy1cnHDoyDwNYzFlhzwdQosSK1Ouu/E1PPbww0xNtej3CbIXAthDDz/TEP6lJOm/AD71qd/j9z/1e0AIAqxUqnQ67R/aDSC8xgsDokT4kNYmRQUKRyWOyG2LQlkEMcKG2a7WmrIskSK84oT3ICReeJzweATSh/VSSBweK/wKYVHYp7t0LReuu68AJAIrgs9/eftlLH8XghXfh5Uhd1t4gQuNIl3Qimxw66/0x63hUcB7lBfdFMjQh9A5gRfL/VvJtVjVsrokRGuVrufmfHvvkTIwFYY2wg6i2w8vutkbSBAybOHpRo34LtNjGFPhujkaAry3CBHokbz3CBk+Q/NipTfdq0A4keV1q2Pn3XLmSGhbeBH2kt3ricIjqVUUeVHiSrcyLivjgUd2k1G8XHXThPsqpKs675Cwsp/whNROIRHedLeXeMLYIB3WQVypEMcJCGg3W3gfiICUVDTqVZRStNsZ6TUTRgAAIABJREFUnawDeBp9A+g4Is/atFut518PIcE7pACcD31bPo0VXg2PECp0Vjpi5UljjRSKdivDeI8XYuU8wK+Qbnkk1VqNIsux1iK8C5krPfTQw98bH/rgh/nQhz7y4+7GS8aPpBbAS1ExPIJlaeeFRwpw1iK1IsMgtEQ7h7UOISVCCIw1SLk6v/FiVUzKtW89IVhOhFJr1os1X5bFknjONsov9+9crGzhV38pt9wPv+ItWH4xy7UNCLEsX1dac2u7u+JuWH7Brz2mOGe/c36+AJbjNFYE4podlvu2KrDdcvdWthEEgbz2XMI26pxj4M/t9+rezz+RtWO3euyuAOtuJ1bG1SFwtDtdL/aagVt7Jf0q3d45XfCie2WFwJ2zvmvQ8edGyAuWtS2BEmCzjE6WrbS7rDo6a5hfWORcCBabC+f8fi5ENyDPLyt4L7BpGJNVrbMwUBhDSJQV52h84VY9ZyTotJae8/8eeujhZxk/EibA8wlrLd47oiimLA3eg3XLnOYhBTFM+Hu+zR566KGHHnr4m/AyEAGdXybA50JJhXeKPM+J45gDB67gpptexYMPPsLtt98R8t9NmBX+sORDPfTQQw899PDTjpfFBbA66fdrPs+PMF4mGtI6JklibrjxBm6/43YefOBRlJI459Far5AR9dBDDz300EMPz8d5t5M7vzbyPzABivOZaiRCTJpzDiUlUgg6nTZCCJx76dTDPfTQQw899PCzgJepFsBarNYEOF9HUFKjdcxll13G/PwCU1PT57H9HnrooYceevjpx8sQBCieEwT40rIAng+PdQbnHFIpKpUKURSdzwP00EMPPfTQw089XpZQ+WD6D99DFsD50wAEAikkRVHw6KOPkKQJfX3189Z+Dz300EMPPfws4LwrAIH/Zk1u90v2xbtu8rcEZLAodK0AAM56tI5XjrVMcPNS0g99120hfCCSWcmGF6zk5QcSHssySY30Ho9COh3KFiOQXiJwqK4StLadwA0Q9g35/hInwne7Jm89kA91CYxWKiOtEup0uf66ywqVDi826PKF9ggljsPn6hH9Sl8CvXD4VD6sN3J1bJxYTe9facOzQnok/PJ5e7wIfV8e6zDeHsQyQ8Py0UV3BMU5vV3+G4iCuiPvxcpYLu8brkcgIDIybKmdZ5mUyHQZg5QP4xzGevX/Kwrtcq/Wch+cE+y6vEX375pruTwmfs24sLLev4hl7ZX6267v2vtj+d5Yuy9hzIXAe7EmXueF+tFDDz38tOK8KwD+nCDA1UDAHxqim+PvdVhQKCUIVn9HlhVs2rQNrXVgOBNQliVKqb+l0b/jHJZJhwgUxNILHAIrwgKgvUBQ4lAIr1BYvE9QNkXgEB6UixCURNYFEqA1wjKxQVApL8BLCikwQoKXGClXmAGNDILKSI+VvktZtzyeDoTpLpYVce0DE9+LO9fwqRwryo4RUKpQfImushLZc4WiFUEBiGzoV6mCAiK8oJQC5cL5GRmEjnaCUgXBrJxCeAk4vChAlCgckZVoJ7vjVHbJeiQejUd1lzBGy0qE6I6H9EFBBIlyEodEOoknfBdOoJ3HS08rDgpHaoJw98KTRUEpiKzDCYvHrtwHxpY4PA4HXQXTWrNGRPruyLuV8enSJGG6gl560N4jfSAnst1FeFYUxBezhPFYXZaxdjyCciVBuHPvDa/Bq/BdWJz1SKmJdIy1JdaVeMruPmsVyh566OGnES8rW84yEdD5IwMK0sqYUHFudnaGr3zlK9z06pt497vfTRxHaB2htaIsix++32tmv+FFuHz4NTN5391GOKx0mK6wsDJU4bMyCO1APxzaXBbiXrggTLA4YUFYhLAob1HeobxDeHfOK1562RWaf/vYrOLFpUEKgoIjPWgb2A61B92tvaCcRzuIbViMhFYErdjTioKiUClhsAO1AqQLLInKB8VBudCWcqH9yJ5D/kd3KIOgFss0vMvzeo/AIrwNYty7YHVZUXaCFSZYYsL/pXcgHMpbRHedxgaBLBTeS/AaLyROKBwyFMTxQcEAhXKyO96hr9W0gi1NUGSFQGq1yrr3AnrWC6leL2a+/vdBOO/Va+yfO6jPsxI9H0orTGmw1iKlJk2TH6InPfTQwz9UvKzlgF8eCKw1aJ2gdcSpU2P89m//NgBKqZV0QKV++FNz3Ze7E8sUr6wI/YCuWV4Czq/UCZCupFQCIYLp1QiLEAIpgzheJbcNtm7RFfAe0E4QuWAR0C7UG8AJlPVda8KqQXsNa/7q4te88MWLE/5A13TfFcFeYFlVWEL9AUmhPO2oOyaEIkNxIbp0yCKYzQmUwEIEJWC5d6o76xXd/VbsMsuUu0EFwQqJlWF26ljm7V826q81Yy9fB7Ei2pR3eBGUmDAUgsgF5Ut1N/KARXXHmpXZeaBA9ki3vI1/nrwsCoPWUdf9BGVZIKXsytbQX4kLloZuB1ev7IsV7y92u795Zu5F10L0Yq0/zqOUwpgSHUuyLEPKXvpsDz38rOBlSQNcLeIC4M97Xr7Wmr6+PiYnz9Jo9JPnGc75NcfmJSkhRoQXuZSrHohzX7qhWA5d378TrivQLE52hZwHLy2B3V8E0y9dodblK9Bd068XQThqH7ZTPpi5g1ALgmTZP+7Fc2Z7K4JfnNO/FwMPFKrbLqFgkRNg5YqMha5C0NGQWoG2kJhgDbACCg2lFBi5LIxDAZpSrh7DytUjWiEQMvj3hQfpBE4ojFA4oUB4hAgiNZxmd2y9Y/mu8oRiPasxAQ4n/Er1QyuDpcF2zyHIRYHwCumDO0N0TfGyq7wsV5pErKlT0EVZllSqKXkRrEoq0sF83lVKnFBIV2JkhOzGfBghgjXiedfmb8KL2Wb1mLBii1oZ59DMc8sM/c1w3qOkROuE0nafIcF5fVZ76KGHn1y8TC6AZfNswPl8n4QZvmNxcZEkSVhaWgqkQEphnaMsS6Iowlr7dzcGrA6B7L74uv74KMLpCKckQqnw2u3OcB3h5SmtRhFm7cJFIdTM+1DBkG4hGqdQXiFNqDyIA+0UHoF0AikU2G6RIiHDrFRoSiGwIpiljVAIuzpbBbpK1XLVPbGybnnsZbcK37lK0PMVg2WzfGpDCeGKFVQMJMaTWoitJzagreia9IOUtQJyDZkWdKTDCYGTAtOVyaX0lDpYUwrhyTXYrmKwvE0YL4n3CiMkJo4plMZLhRA6xF2sKD3BUuG9X6nWVyKwQuOkxHqH6bpujPMrPnZL+G4EoBzSWRLrEMJiZXAfKCyxdQjhMcKF49KtrCcEKtIIIXnrW97KFZdf0VVEPFoIYimQKgh+J5ZjFcB27ysBeO+QUq1cp7XXI1ynVeuNc27Vu3COIt29vr7rzvDB7bEahdD1+yMRUjKyfj1bt25dicdhjUK8wpLpPddddx3v/ZX3kiQJSRI/T/j3dIEeevjpxXm3AASq3q4CIFlhAjxfLoEg+KBWq9FsLqK1AoJSILsFgIwxK99fXJvLAhPAM7hhE3v2X0RSOGRe8MwTT1BkbXw3I8ERBIoUKaXLkTJCeIWRJpTIVQl50SFSCiPj0GffNUF7kEKTU5CgMNZRah0EihIUEpTQuEhjTZjVlsKSAkI4vHfdcscGkDgXXB/WWpRSeB/C1Xw32EvK4BZ5oTERhNlw5AVRKZAuRIYrJSlEt5Sv9SRCoLIg+BMRlKGmNFitQQiKPGM4iXG5wWhQQmCEwFuHVorMlYgowhUGoVXXXeK6lodQbtiqiD0XX0qjUSP2BdnsJIcPHaHIcxCq6/P2WO9BKgya0guk0igPkVTkzqGUpCwNNtIIG0reGmeJhAxxcd0SyzkerwWRFxhr0V5glaQUdGMtJFIH8zgerrr6Gnbu3MEjjzxMe2mJC/ZdyNWvuJi0kjDbETz70Hc5dLaDxuJNiao2cFmGVFFwS3iPEKszbCE864aGufGaA9z5zW9jXKjoFwIMuxazrlK4/PxIQAmLkpCVFiEFKzrhmriVOIq44YYbGRiq8pnP/Ce8Fzi7/Hx4rLFEkcI4OHjwIPsv3MsbXv8Gvvb1rwSrl5AYY1HyR1IstIceevgx4WXiAVj763wGAb4cWC7DGoRrHCe86vVvYrqd8dBTz3B49DST800KF+aKxitkWoE4AVXDxBWIqzgqtOKI3EBHppRpDR+lZLpKR4DVEYXWmLhCLjR5WqctE7K0jxkjKdMGi15R1hpkOiVPayxJRSEVNolBKwpThEBDZ85Jd1weX60jjDE4ZyiKvGsh8MRxjJTieQqABzIFbe3pRJ4iUdhqTFMZWhEsxbCYeNqxwCuFjzRp2zGcKTapOo02jGSKdWkD38zoywVDRtNoGtJ2SdI21DNPPzFR6RkUCYkJQnjZO74sbPuH17P/iss5PDbGo089w8lTpzFCk6MQaRWrNCJJcTqhIMKnNZacINdV2ioi95qOiljyirQ6wLxSuKhKGVcoKzVyFbMkFR2pcSrB1fpoak2uE3KdYKOUJS8oaxUKraGS0jQFpfegFe9933t58MEHmRgfZ7B/gGuuvgatNA/cex/33Hsfc1OTQdhLQRxHWOfRSuO9xxiDUrobm6IoiwKlFI1Gg0suuYQ4ihFCoXWCFJo4isELlApKoHMe76Be70MJQVnkSAGRFkFJEw6kwHqH8wLn4c677uQvP/eXxHHcDfKTITNGCKrVKnlRoJWm1Wrx3e98j6uuuoparQqspjwmSS8osIcefprxsgQBsmwk9SsW6594CAHeByGpqnXWbd3O6JGTnJqcpdG/Dq0kuy7Yyet+7rU0KhXuuftu7vruk9S3r+OWN7yF/VsuYm444+5bv8Apozhw/dX0WcPGvZdx53/9DE8//gRveMctCCSX77+E41OTfO3PvsBikXPNG9/M9VdfxfZN6/jUH/8xJ585wS//6j9mauIsV+7axciWdXzyX/xLEu0wLu/muXuKokRKzetf90Y+8OsfIK1EfP2vvsqtt/4peMktt7yN97znvTQXF7n1z25dqZa4cs4e1rWhoWLqQuPyksKUjPT3M5e1sFrg0Rjn6UQCX4m4QA6xvz5Csy9ioNHg6CNP8sjiBBds3MaVW3bhJXRmF3n09FEuu+Jynjh4kLl2Rkt7XrF9JxPNOcaKRXJhVjIQPJKk2mB481Z0vY+FqQk6C7P4uMHAxq1cffnlvObV15N3Onzid34XESVceeBGbnjtG6n29XHk6ON87U9u5ea3vpG+Wo1LN2znWbHEN/7gM4xs38gNr30NFSfYtHc33/rCV3jwju8h1jW45d3v56pd+xg9Mcptn/sifX0Jb//ld5BPTrFzx3amJ87w1S9+kV1bN5FUqzz+xBNEOiLvtKlUKwz3DfKIgE5eUnOOTTu28s/e/z4+/f9+nPm245++//08e/woDz/wML/5z/83rrnmAItLTX7rY/8nu/fu5SP/y4cZqvfxmhtezVNHj/Lxj3+cLMv46Ec/yk033cyxY0f5xCc+wa5du3jLW97Mrp3bOTP2LBddcin/8z/7IEePnaC0Hqk1Qni0jqjU6rz9F97G//Q/vJ8vf/XzfPpTv4vWmne985e49JKr2LlzB1u2jvCRj36Qxx55hiSpcvLkKDMzs1x44YU89NCDgGPPnj189CP/nD/+o//EE08+8WN7LnvooYeXDy97EOCqX/on1ZnYzUfvEtNkWYc7b7+DzRddwht//haOPfwYx589xNYd29m2azef+vQfhOAuY4j693DgTa/ltu/ezZfO3s6ud13JqfFxdt70elppwre+9FcMH5tgqF4hGR5g3e4d3POD+/j6t7/DzW9/G25gkIsu3M/whfv4/De/ze5NI+y78momp1rIvn7UUpv/8ud/wVXXXs6evRfw5KMP4HxJGkVIJXHO0ejrZ/3IBj772c/y7KGnGD8zRpa1ufbAjezatYsPfOADzM/Pr1gMzoEAqRXVao2haoNYSIx3THWaOCPIvVsJOIxKyCNLXSfI3HLo1FE29A2wS9ZZoM7lYgD95CnO5PPsHN7CDqqkE4vsoM6WgUHO5i02uYRW0xBJSx6vjVhXnBwf5xvfvp3LrriCysX7eOjbt7FoYl7zxrdw4shh/sXH/w2KkJVw5RVX46KUj/8//479+/cR1wWFkfRv3sKTjz3ON//8y1z0a7eQNgbZuHMPeZLw3/7iSwzvvYD1tSFqm3byul99F4dPn+De73+e6298FcnwFjraoodH+P4dt/PFr36Z9/zSOzFCUO1r0M46GGvABb/7N77xDW669ko+/KEPcc/TJzlyz23cfXycs2fPcukll8CZFiMjI3zpa19lZP16hJD863/1r5iYmeToyVGeOXKYp558kl/95ffwqX//eyx0MiqVCu9973upVmv81m/9Jtdffz2/8Ru/wR133MHs7Bx33n47r33VFfzgr7/PlVdeydFjo1QqFUpnsd7jjKVcXOTzn/887fl5Nm9dj/MeYR1JkqC15qMf/SjveOcvcMUVV/D0U0cpyxIpod1u098/gFIK5xxzs7N8+cv/jcmpsz/Sp7GHHnr40eH8EwFxLhFQEDo/GcJf+DDjXCVLCRH1IUjMI2KNVYK5sXEeuv0OxsaOseOS3RSxY92mTTzz1GEiIoo8w/gCt2WQHMnpySnWXbqbvr4Kc84z3Eh49t57mZlaYGBLg4XFaaL6Ohamxjny2EF00kcaF9iixTVXv4Kjzz5Ov5a0zp7l3m98k7pw9PuSB+/4Ju3Zszz6ve9y7Jmnibwk9gpbeqwTxEow18q463t3sbg4yyVXXM2vvucf0Vets3PnLqamppmbmwN4QWIk4aFWCtbbmC0mZlsWsT2L2WpS+kqJlJJ2JFhKBF4LqpmlklkW24uctS06yiG9peEluhIzGzua9Yjj7VkmVMF8q8mGWoMRWWG37iMuLNbZkIvvNIUBH8UhWt84jjz+FN/71p1s27qdDVu2s254A3FU5a+/fx/eh+2jtEZtaJBDY8fxtYjhXZvx7QXyisIVCxx94iBLaZXBqiBrFmzctJ6H7r+TpdlJtm3exszCHP0bh9CuYOnsGer1iPvu/S7HJ46zccsIp559momnn0QsLPDtL32JYn6O9vw8fZUqWmmEUhTGsthc5Kvf/Db/9hP/nqzd5NJrbqCu4YEf/ICNm7byvl98Gw/d+wBz07NMTJzlK1/7KvWBAd7zK+/jiiuuIJYaLYJJ3gpBFGmMNWzespmzZ88wNDTI2NhJ7rzzDqwznDhxnKzImJxtUlhJXjgQCmMMWiikD3RJmBJcicdRlgatUjyKoig4ceIYs3PTzM7OoVRM6UBpjcBSr0QszM/hvULoCtNzC3z3e99ldnLiR/iE9tBDDz9KvAxMgDzP5/+TklYUTM6rjHcr2fRSUDpLu8xxSpBWIiLl2TzUYO7saZoLM8hUs3XvBRRKkFYS6rEkGkipeMH+nRdw7Y2vRC8soLxk2JW0n3mWfhkzmAo6M5NUk36WTo2Rdlps6B9GL80gmnPMjB6lVrY5/cSjTB8+SnbqNBuqMVOHnqIzPkriMtz8PLaToZ2gpmKkF5SlJ2s1KYWik3W45wff5+ATTzLUqNPf6OP+++/numuvZe/eC2g0+mi32y8YGJnnOVOzMxwfPcGRo0cZPTHK7MwMZScjdoLIgkKQaY82FiccbQ00EvKqJEsVHeU4bhcZrVqOZHMcLec5bBeZ14b12zbTKXI29g8R1ao0KbFaESVV4kadxaKDlZ7BRh8xgs0jI6RxwskzZ8htSbVeZe++fegoptZoMDUzjcOT1hJ+/m1vYteuLbiFaUa2b6Q1eRIzN8Xgls3o1jyR8TRSxcSRx6nYkk21GuPHDmPMEkm2RPPYYU4++RCTJ55FiIxNfSnzR44StdpUTUk2NY0uCk4fO46wjh3bd9DuZPQNDGG8ozo4xPEzEwz0VZldyujMTzF9doLdu/dz0c5t3HX7nUgvMGXJQ48c5MFHHmJ+foEd27aD9SwtLhEnMVu2b0FHEqUkd911J7v37OSJJ5/gv3/zNu7+/t0hQBVLo7+BiCoUVhCnVdJKlde//o3cd9/9vPbm11BLU/JWi0atRr1epZJWqdX6kEJTrdZIUoWUHu8dSVxB6oi8LNiwfh3rBgY4eugwpXE0WzkXXnwZf/j//QGvuuHAj/AJ7aGHHn6UUB/72Mc+dj4bfOCB+3jggfu6v0Q3Yr08n4cAPEmSUhT5ynFeDFaJZ1Z+4HzIwxeAjiIuvvhidl56Ebv27GHy2UOMPfo4iVScmZ0hGqxzwYV72Fiv0D51itnpFkMettUaPHbPPeTzZ3EzbfTcHM2xCWIV024vsHBylL50gNnxYzSnZqjXhjhz8jCdqXnOjE+we+sWLty6nc0bRhg/NUY1iVmYnWF+dgYlQ+73MimOx2IcqDghkhA3hrj68ku56dU3MrR+A7ff9hVOjY8zM7fA6OhJrrvuevbu3YdzjsnJyXOVMQHtimK+Amdiy1jdcWoAxpKSdlWBlMRtQ+IFWSwQWtN2JbMuo608S6ZgynSYdjmzRZtqo87IumHSJGWGnLyTsdRuc2pplgVXMJYvMFo26WhB4UqcLVBasm5kPRdddhl79l5ANYm4/a++ytLMWVplzszCLLt3bGHXzi0szk4TCU97cZE9O3YwcfIkRx9/jHJyglhrFs6cJptfolptMH/mBHY+Z6k1w9TYKP26RtYpmT9zhubkJCLPuWjnTi7YsROXZbRm5xmoVDj6+OOQd865b9rtFo1Ggx07tjM+fppms8nVB17JDTfeyLWvPMDJkyf5/t13B0IhIbj6qqu46867GBsbw3jPzl27edvb3sbevRdw7NhR7rjjDsrSkGUZWdbhmmteyfbt2xgdHeX06dD+ddddy5VXXon3npMnT7CwsMixY0eZm5tjbOwkJ06MMjFxBmMszcUmDx98mLNnJ+jrq/Pa176W/v4B8jxny5bNTE6eZW5unhMnRpmenkIgGT8zzvjEFFGkePPrX0en3eLhRx8FqUkqVRYW5nntTa9i8sxpnj187KU+sD308FOFAweu5cCB637c3XjJEP48h+h/6tOf5NOf/r2uFUBQqVTodDp/535/H3jvaDT6aTYXu2tenAIQ+PWXTf/LeeUClAApKW23wFAOcZxgKRDSY6wjjerY3BApiXdtpCjJbB9JorFZiZKSvJLh85hhBFlekKVVWjKn7i2ZTUhVgXSOTNRBdIidpNQJxlkSHLa0qEjh8GgtMNYESuAuLbDyHmctMkoD1703lEkDYTp4W+BUTNW1MdZhvEZH8Ura5AtZZgCUpWuKhhJPrhyFEjjvSZDEZXDpNCNHokMqX4wgRlNKRy48qRWkBlTpAt++EMz1SdISKiakp0kHHelYTAQaScMrys4SUaRwMqLjNLrSR5a1qEiHNjlLkcJIQSQEFAUahXAeqWJKC1InGGdIZU7LGmItkWgyKxDKkliNkSVKOigVpayilABbIrxFK4mxBqkVpfUhRbEoiKU7Z4yEgL6+Bu94xzu47757OXlyjGanFbY3DmcNkdJcdsmlvP51r2N6coqvfvkrdLIMi6eTF6RpspIF4JwJHAhy2S3jcc7inO9mcpSElMCgpfouodAya59SoRpmmqYYY1bu/5UUzqIMKYI+rNNa4ZxfSRUNWQkKKxN279jOz7/xZr7ypS8wMT2DEzEyqfDLv/RONq8f4Gtf/DyHR3tugB56WIsPffDDfOhDH/lxd+Ml42UJAlw1sPuVNLWfBDfAciiiW9MVqQKHgDGGJIkpjSFp1NFaYoyhyFtY48ilQqUJHVOQpII8L0llTkFO0hdTLrYorCHSAu80uS7pRBmxEMjcUZUGYcNY1CKDMYJYe6QtUd6TSCBWoZCRBJNbnDPEkUZ0C7NYQTc3W1CaApylNE28K0iTCGxJ6RxKSNIkod3JQtpZWRJFzyd58cBS5MEWJEYQSUUVRSzAqu6VlA5ROAYLTxwLOh4ipdClQ2uBVALZKajJJFhXhCeXDpMVtKUErQOVsQxENcoYOr7Ex5qopnHekBUFIqnTzudJo4isyOivRihfstRu4XRMohU60pSFwfoCVCD/Cantnrrw2ELiJdRkhncJjiZ1keKswmCIhSFvZ6RJTHNpkaiaEtGlYfYgnINIUdhzFQApFadPn+azn/0slUrK4uIiFo/Jc/rqdUSkccby2GOPMnr8BMJ7Wp0WcZxQFgWVSoqUkrLs4L0N3BhS0Gw2qVTSQMmrNXEsuxwaQWjneRDyICjLciVLBbqpfHmgJJZSdsl9PPPzCwwMDACEgkUeiqKkWq1SFAVFUVCtVkO6qHWcPjPOH/3RHyOcoZNleBVYEm+77RtI26E5Mwmqet6fxR566OHHj/NPBMTqTFMIgezWBvhJwdo5sPDgrQMhiLXGlgYJmE5OaUoqypF2eeod0MkyEi2RuaVqJZGCHM9S2SFJBFqnCOfpZG1kJcKSEZtQzU4Ki5eiG0SeI6QkNwXOeeI4pSgKEhV1i9gIlBSIKMFYE7j/u24K64JLINIaZEosBM5rjC1ReLwKpEJFURB1LQBpWukyI56bjSGAWCiklCGn3IPzDmM81gHOodFEWuOw2G5GQCE8i7IglhHaC4g1TR+q/HgpyCOBVzGFBGMdsRNgDFJIEhWhpcQ5g/QO5RxVIbBlSapSXFmSSEU5t0g9jYi9JtUpeZ5jsw5JFOGcxQuHkgpjLcZ5Ui3wIglKgXAUuUWmJVnhUKIPqTVlsUQca5wv6OuvdcckWFq8dwgXsgyeGxnjnKPRaFAUBa1WiziOibqMkGVRhnu8a/HKi4IiL4i0pt3JkFpSFDlaa6IoxjnPcihGo9EXcvS1xDmLMQ7v6Va2DAppUWQrOfzWBoVHSkW73UFrfQ7JkxCSgYGBbmR/UCaWWTE7nQ5KStI03GtdckCKPEdbgxaeSqWCQWOFYHp6Ck1JRWleLKdmDz308A8L558IaE05YGCFPvehjlwjAAAgAElEQVQnAcuUsqtYrhMP2FC0RgIujhBJikShLCQypEY5SSCkQRF5jbIC6TQWBUKiC0VcWBIREzlBzTgaLhQNthiIFVYrpBYgDaWUqAi8zxFaYDF4Efz9iY4o2hlKCKSQ5HmJFxIhNbHWeGvJjcM70xUqGiU8xnqcd+cQBLkuw98LuUqEC2V9pfNIG8ofJ0KSekkFTexAOo9PNLn2oVSwhrwWYSKBcB6roZVAlko6ytGWgenPWYtXEumCohEhiEqHcIEtERUFV4ZUSBEsLgJBUVqSNEU5TeJjfCHwXiNUTOnBKYXQkk7eQscKEcXYKMaSIGWF3Dik1iAcIolwKqG0ArTBK4MRBoPDKxmuaSi9gBOOF6ohtXYsoygKv50H50P5n27hBCklRVmAhNJZhJah+JDW3XYC3XBoz2GtYdn8v3I9BMFFIMA5u1LgKqRxhmtorSWKojXr5Uo/l0l/gC6roF357qFbMjso5suGuuV2fLfake9SFEshcf5ca0gPPfTw04OXlQlwtRzwy3GU84/ATCeYx8PIel73j97FwK4dTJucLInI0gjfV2NRQDuOyK1AUiGuDuCTKipPqRiN8Jr3vuvdfOGP/gu/9cGP0hhch3dw5TVX8fv/4T/yyd/9fbZt3wAyDZwCLuuWEA4c9Nt27OCf/PoHGBocxBSGWCfESYrSMSMjG/m9T36S6w68Eh0lVJOI9/+P7+czt36GX3n3uxBSopVCqb/70npCkZ+OElgZSvjGNuT8S+PwzpHZktwZXFEinUArjTSeSttSyRxR6ZGFC4V7TPhd8YKhXNLIodK21MtQQCgxUC2htJBu3sLPv+9X2XjRPhaEJ0sUeSWmnUZklYjFSLEQRSymNRbilGJwHdNK06pWaacR7/n19/PHn/tT/ulHPkhfY4iFHKSs0V9dT71vhDhNEBac1Hzk//jf+fxffp4Pf/hDJGmM9RYnBJ2iICvLFRY94yzuRdeQWIkj/QlJcu2hhx56+PvhZWUC/IeAIPTPXddvE2TbMzo9y1lhydOEeikYKjVmvkW1XqPlc/JalUJXufGtb+D0qWOcufsIpcuhUqWN4Hd+53c49PhhFpSm4iMeuv8BHnrwST7xL/8vhgeqHDuZId08SlgKLyCOQvGZJGFk4yaarTZaJ2RZGYrTeItxjmeefpIzZ8axzrEwO8Otn/kMs3PzrEsDN35ZLCFkEoox/B3nHjuPdMH8byQ4GSr85QJEpLGlJxWaehmIgVoRpIVnUxGKH83EFikEiVAUlIg0opQOUVriakQbQ2EhV6ESYOTBqhjT8UydnqFYMsTEYCTGhVLHaVyl7DQxukIpNNe/6kakVtz3g3swWZt6rFgXN/j4//qbLEzNklEnrY/wputuISktc/IsM1OjnHxylkU0/+bf/g5vOHAdN968G2ctkY6wHqIkRQqBKy1SKOI4Chkrz6dMeOHxW8MlsRZrrUzPvbd66KGHHn5S8CNhAvxJCQKE8LIW/m/uiwD69u1mcONGDp84xMKZWVKdkg4M43XKrs1bSaXg5KFDnEaw/+rrSfbuRlU8e91Gpg7fz0S7Sd5Xo6NhUVi0TIgMmLLAK4+0ClfkSCtR1pHEgo7TWO8oTAlSoXTMZa+4nJ3bd/LI449x6swZBtYNcflllzF6cozW0hIgSOMI60PhHinAueA+sH/LOa4911oetrMSOlFQAqT3rCs1O1wf6/9/9t48SJLrvu/8/N57mVlVfc/03AcwAGYADM4ZgIBwESAJEgQpUpREkRZlUZK9Zni93HWE7D/W69UG1xHa/cO7YUsRFuVdybJi17a8XJIWT5kiJUorEQQJHgBx3xgM5p7p7unqqsrM995v/3hZ3T0gJFImRpoh84sodHdNVuX18v3O9/2WwmRWcExKDvfPUE8Ku90Ud/fmOVOu8GBcoGMsXe1w2vfp1zWzMz22FY7Dw7PkhUkyw06oHIQIczu2M7/rch555jlOHD2Gc46JqRl2bN+NirBhZppnnnqcRSnYc/X1bL3xAMtLC+yNgUNPPkZYWsDmBRIU6ogg+NpQLpc8+50neW7wLOgZZn3KqFhX4DQjMwYnhip6YgjceOAAIDz28LcTJXGduvmrv+KYStLCraVv0aLFxYXzQASUJE3XmADHy5kuHKjo6gsDtSaVuiCBuc0b2TqZY0yHy6+/C2sdg+5W5m+4k/f90s8ROpF69z42Xb+fTr+PGQ0pwpClJx/BHD9FMTiNrUq8VdQqU7XFaElpAmI6OIHaebz0MLKAd46hdjEqxKHQtRNYMnZfcil33nU3OPjgL/4cMKIaLrF40vOBD/wDNmzrkEtJdA6pZsjI8N3jWLNC1B6BLK12UCEPwlQp7PFd3jl/Jb+w+UY+NHMdf3/qOrbZHpVTahPJQuIaqK2yWzv8xNzlXLVxG4sd4fqNu5kpHXeVc9ySbeV4rChmZrirs5PpkeWaDTu5ZtFx44nI7SvTXDq1kQkv5GoYSAAjmBCZn5tj1+YNzG3azqU33QMiLLsZtt78Zt7zcz/LzPbN+F1Xc/AtbyEbrDBaPMvmSzZy+MWHKV5aYsOZw7hYs+QiZdeTiUXzFXJfUhRT3HLn/bzvvl9k54bLKG2XnAxbC5WFmA+oGRJjJHcd3nT3Pbz9rW8mUlFrSW2U8D2yJn/hOFoH0bXXhYzUcOqJYvCNlLGg2BiwqoAhSP43fZgtWrQ4T/hr0PuUC7oHIMSIsRaVpLp2+sxpXl5cZuv1E1jbSV3cCEWny8Nf/xqPfuMhLrljO93o6SIsnzrJyUMvcfSZJxkdmmSys0jWmUViWgaZBRAiwTgMqckwEIhYoEKtwQeDQejlHUL01JXn8MuH+Ve/8RtMTnW4867b2bJlC4cPH+Lhb38HxGIdxFBSV57CWkLtUamwVqmrJItLjKslDgFGw5IXnnue05WwwRTEqmY0WxGTCBw2puxIBGJdQ4g89uKzvDAVuaa7mSxz7O7NMektAx/JRp5OELrGYarAZXNbmZzs8dLSKZarEpfnVNUQ7VrECFIrS2cWWVp+mL0zuxmoJTPKSBxzGzbx+KPf4RsPPMDee7Yz11UYDIiDIYtnTvHMY99m5lBBV87gZrcQRfHGo17x1iDUfOGPPkXme2zfsoE3vvFePv+l32ewsoyzijcDovGNwm5aF//R3/hX+FDiQ910x3v4EWp6k7ESJnKOhKdZ48gkth0OLVr80OL1bwKUNerfv4h85kJEXddNNzQIgct37yCOVpjsdiiMkmnkleefp2MMs3lGeeY0ooHJboeyv4LWEZelqVM0rkrehu97/lTquk7RaZ4nPXZnmJycIvjI0tIS1jqcM4Tg8T5ijCXLMoxJneDdzhTDQUnmHDVKbYTaQOlSer+azOhdspWJvbvQHRvJLtmC6eSrkeq4aqBAbYW6l3FseBZjHT2bMaxKFrVKZmNpheGpRY6dOcVIA5lPLs0ZKmTDBCt4Kkmd9tLU2S0mlddDYNvmOQaLp5me6NErHJunJ3n0oa/jYuDq3Tt46lvfIjPChtkpwnBEORghloa1URs6ZyGa1OpQxxFKhZqSQXmWQdlH0s6ImgidjHFjegpCCFyxdy/79++nKAp87XE2W+2ab9GiRYsfdpyHDMCrl/1d2A6AMbLK0Oa9R5v18mG0zM3X7+fJs8+x8vICEwRePHWKInim1XPi5ClGoxHLi2e47s5r2f/+D3D4T57n2SePJX07VURNWjv//fRECuSZY1QOWV4+S9Ep+JVf+RXKcsgX/vALlGXJjTce5M13v5fp6Zyf/+Av8vGP/QFPP/UsH/zABzlw8EpM70U+/A+28R9/7z/TX15Am2Y2S6q9R1/x6NFDdD1MiMMEZaUHktEs/0rHYZ2lcsIxPyBMdaissuBHDKdynixP09s2y+zUpagqCwsnOTk6RWkSTfGhlbNsvmw3i68ssFQNcVNd6uixRtA6oKrYwlKeXeCuNxzkSH6Gp48s4coBp18+xEyekQ+X6R85Ql0OOfbyy7xx6m4+8L738+KXnuDQMy+BjjUdDMFEAgOKosvB/bcwP7WNIqt5+LEvs7jyMmotuZ1HoyN6ATVY5zAm4+CBg7zjHW/lF37pb4OA954syxpSnRYtWrT44cZfAxMgXMhywDGmNdmqSbdANUWy337wAR78sz8nXzlOZXp89Yt/QNefxYTAt/+/L6PLx8ldwclXXuFTv/cxsnrIzMoEiVomKbMVeRfbLVBKIDkZnaLz3aI8mtZ8RyqstRw/fpR/9s8+gjFCCDXD4QjvPU8+8STPP/Ob/Ov/49cw2RnqMmM4HPLv/t3/zb//jyNs5xj1qMdwxTATDfhAkLS8MKIMJVD2LEOE08FjEPJ1Ne/VDECMLPghD77wBINCOMWIzy48xdEZKIYDRoefoBeEKLBilVfykj9dfonJYU1t4KUXBiz7Ero5ZfRojFgs1jokKj56HvzTP6aKX2ZydJIVzfncx/4DbjQi1hVf+Pj/Q7W4QOE6nD52lN/96G/iyj7dBQcm1amdKp18grqocZIRguexJ/8cqznqa6qwgko3rbtnSKfrEckRcdR1IHM5ZVVy5NiRtEZeU+R/kSSsWrRo0eIHxuvPBKhjgzpuADSrqfULESKCiF0tVYybF8uzC6n+qZFcA7EaINGjwRP6i3RQvERsrKnODiFUjGpFoqDB019Y5M33vIV9Wy/nY1/4DIOViquvvIK7776b4XDY6COsrZQwJjHQhRDwPtDv18QYGn53SwjKYFAy5DQhVJhsBWIOYugPFoAKGZZEL4h2KJWUModVJsFMbNOcpqSugySGtL5sM25eKy2ckoo6c3grnIoloyjEQjjsQkNLqFgFdZbluiIUiWa59kOCM0SbCGastdAs8QMgCnV/KdXifU0mhjBaxkWP+kjtT9GxghLpmMjozAJ5rHCxoMgKqqri+OFXeN9738/hJw/xuS9/meX+CiujM1gsBkNUJapic8M73vk2rtp/OS+++CTO5qCea6+9lrnZaX733/4Og0GfzHWIYhLBz4Xpq7Zo0aLF64rz0gR4oRr7vwyrBlASM6CLoclbCCYmiuCk9mZw1IxNq1VPERSrBhWPWIcTwx986jP8oQZMrZQukucdHnvsMZ566ims8fg4TMI+xjZOCAQNzdL9c5dOhhDWscnVGKOk/H6j8iOJUU5DgZCEfYooGL/WhxAFokl/RyNpmaAk5j8Y52wSpa2Nijcw6BiCCQSEmAlFBBc1cQZIKi1YFfKg1EbpZ0lrMWJSZ7xqantMjRHJ/GvaJtdADBEQrIZEiNQIFzmtERKjodOACTGxNYqnjiBG+E8f+zixLskCeKcgDpEi7ZuAOI/BU1aez37ms3z604EQlsizCcDy+OOP8/Aj38CHdUJVKoi1qPrzNcxatGjR4oLBeSECWqMWvbiYAMcQBBvHy7sMSQkgifGICIJfbe6zMWBFm6Y/n3jTg8dZC1iC8Zimv8DYrGGaO1fdLTPj2/B91J6l4fTX9bdu/F7O2JQ3vW7N+TTdnprS9qnW3zgHRlPA2wS+RsHGhhdA0rXIAklnIK2axMa1IDmulneUSCL7WR9Ay7pzSs6Hrl5fIxEwJKnjmFZiAEJNaI7Tqm9WJ4CKp/SB3Fi0DnTyLqPhENGsSV3UaVlecykVQ1FM4OvkNFnJ8R4ylzMcjrCZYq1BVfEhkJk8qUO2aNGixY8AzksGYD0RUMKF2wPwmmiiVKNpXbiMHYCGT90QUrQcFYsisTFuEgFLrCskxpTiFvAhYCVrXIn1vO+CtUndL4b4PdZkNNdv1QGw0JhLms4DNAOJQGSYgUpi+JOYDLiJglXIaISQSKl+lbW7Y1SQCLXVRA8coBeUTlAGWdo+E+jUUFtYyVLPw0SdCHFG9pyjXUWU5ioKWDVJf0CVIBYhOUVBUuYgdSwYRJMOgRlrGkgEsUljIHjEZc12XaBEzQA1Ho0Z6CQaMqpQY10EqXCuQ12D96m0Mua9FyM4sWjTi/FXoAJo0aJFi4sWr/tU9+qJ/2LMAKTLMq6eN0sax1G1pN+DkSQ2o4qJKXJO7elJyS+JtqaI2ybNWlQjLsuIITYyrhYRg6/992ZK1EaxRpVk8NMeEsZRtl3t5FvtvSRtNo6+o6T0fWWgbqh/U91/rX3TNH0AsXlDSJ8ZZOmlQNeDi2l54dkive/PocCV1dc4GzEWY1pzB9P1Hf9bEBpXKxKMJFEaQso4jE/IulQmMI4YImoUlbK5RgXELpAhtsLlJXkBqoYQMuraY41dJahSjYgRrLGNUE7EvJYaUIsWLVr8EOL8NAHGlBhO0qUGI3KBLwZ8FSSsGnzTGFfBYOM4VHZIaIykgCbrjyBoDIi1yZBpWI2oARSfZHCtEKMdtwAi9vugkpVx5qBxBFaj/3Q8jZluMgCCGxvM5mvHW756P3a8SlHGRwOoYOOaI1AZQQy4kDICCiwVybmZrLRJ1TfOxGvsZ5xNMeMdaGB8KYXQlCBMMxgNkGGaREcUSacryW2w6kGEaCHEtJJBmqxKajtoDiIC1ARSFsSIae5p+jwKIgaiS9LHSOqtoK3/t2jR4kcD56cJcP3vqheX8Qe+u3wBybyP/zy3zr1WNpZzl/y/uh5+jlGU1d+QcdX++8FrZQrG5YG1evv3S0P7mtuJrjIIwjhqb2STG/gmd2Tj2vH8ZbuU19ggmfR111fP2XptO1m3jay/vq++E6/ej5z7YzXLsr7Tf10STEB/hJgAW7Ro8aON884E2KJFixYtWrS48HAeiIDkVU2ArRfQokWLFi1aXGg4z/3OTQNgmwpo0aJFixYtLiicZznghgnw1dS3LVq0aNGiRYu/UZwXy/zqFW0XiyJgixYtWrRo8aOC89AEmBZ3AReVHHCLFi1atGjxo4TzQgQ05raHsQPQOgEtWrRo0aLFhYTzVJxft959XUbgQkRiKtRzmPiMGCgDU7VhegjdOr3vreAlrSE3UQkhydyaoIncxgpqOngiaoTcFFy1Ywcd10Ul4vEEyQh0wFoQ3xDhJHGeAGQmAIFIhncdRk5QiUQd0+GtOVRJ8W7MngcaI0ZANLLKnTM+TxI1cJRErhME1skdrfvexCYomqPB4sRhguAiGE3HqiqNJoJFQ6ISVJOORxrCnqiCYhKToigQsQaI6doEk8iDigCJXDmRLZnmu40qQt0QIJlEc6wZOtYh0IgVh6jFqKAx9Z4gEDUm8h9dx2WwXh1BDIohoo12QBizCAGypgyZNiaizXVrOB8U8qLHrksvxblEVZwoGNK9UwzomOK4dX5btGhxYeI8NQHqqqyuiHxvmtu/QVjrGqW9RNXrvScXx0Y63L15H++5/Gb2b9yBKIyMUmfJoOWqFFOTxApmbA9iTd+PGPkCckdthXvuegv333ITps6IeOg5ZrZezrt/5u8xu3kTQYaAR4wD16WKgvOLiFZ4nWDFzrKUG2xusEYghuRojJUKrSEaS6c3wU/+1E/yvve9D9STScCpJmPaUPFGETxKrRGvESXpEBht+IAJqNSoOoIqTmbRqkvPzDJpNzChOT1rkkqQZFhn0Sg46WEMVKFGrQGJ6f6TUXnYsm07H/r7f48dO7bg6xGFtdSieFEKL3Qrg6qhVENmC6SKZFHIao/EEVCRGHoKJHaw9LB0yWUKEyZwvocLghHIOgXayCdbTU6LHRt1FGuEEBQfDCbr8LZ3vJ2ffv97qOIQYxI9swbFGJccK1UCildFM4s3QlBFgyK2x11vvpdbb7sRrStycYjURPEoDtEMQ7XKUtiiRYsWFxrOK/H5mhrghRsFxRjwvkZEyLIc54TsbMnB7fuQ5REPPPM0g9mMTgRxhuVqRFQAy9GVZTbbgtFghaJXMCeWUNVUKmzYuZWb7/0xPvk7v8FKLLGZY6USlkMgdiy9yQkWFyZYKQWCIhow0iHPkoiNSpf9N97C5IaSR7/wWfxyRbfTIThlGANoMlQmQlXVqCpTk1NJbdCaZKjWEeEZVawKmcmxCloHfFWiuQMrICWYAFqQOUesLNdefTsHr7uBWAUe+86f8NiLf0bWnWdQR0I5oJNZYu0IXsld3uQTYjquLCNWIMbQ7Xbp9gpEIHpPLkKmggtwtgOjTBBxjLxnThwbQk5f4KzJKPEgAzA1xB7EOa649HpuPngLimc0Os0DD3yKU/1T9AcDgirdvFi9v+u4/6i9x5gc43KGgyFFVrBhZo5ellMNBnSyqeQ4qFB5xeYZfQkQwAwDOYI1jlGhnC1X+OMv/zEf/Zf/C7/8wj/k8MtHaLQSSTmZMVXzhev8tmjR4kcb500O+GJKfTqXYYwQYyTLMq7tzHOln+CsDMi3bmQxrDC1DJfYLp18jlEoeUn7bMi67CgN08ahWReplOXRgBO2w90HbuOZhx/imRdfwrsuRbBsnN9JZ8dOPvnFT6PHnwEcbsMOZiYnyKwhTk6ycuJR6hXo7djD1gPXsHTqSTZfcxULzx2lv7KMNQZLY9DqmqLosnPnDo4ePcY3v/YQzjk0BtQagqbYVxScCtYrHQOm8uRRsFJwhkiJBe2kTECcIcTAtvkd7Ny5nc9+/uNsmNrCG2+9m+PLz3JkYcjM3Db2XXk1Lzz7TfqLJaF24AQ01UpUoSwrpqdn2L5tO1/84h9y9Oix1UxQF4tqZJBDZZXCJ3mD3MPeyU1szyf4Sv9lqqiNoMQAZAQoRgqMrXjk0Yd49NFHMGaEMUsM4ojuZJcdO3dhEV5+9oVz7rExgiBJmRHYf9VVnDh6jEe+8VVMUHpZQSYW62Hv5DxLgwUOUzGlkdoa5m2PK2SCZwdnOJZ51BkOvfgK/+e//r+477638rv/9neofYaII3kMNenxapfAtmjR4sLEeWsCHONCbwJMXAWphhxCwDnLXG3Z5B3OwwBPb1BzvZ3jmo07MapcPrGBO90WNvWF6yc2c/PmXWyMOVdObmVnnjPDFFdtu4xDj3wTUwne1MxMzHLlFTew68qruOqm/WTOYrJpLrvhdn78Z/822y+7jEuuO8Cem27Gu4LQ7bJz3z4WFhcZEsmyAmOzFNnrmsiStZYsy7j11lu58647ALDWUqlPNWuSxG8WYa6Y4Oqtu7n1imu4Y991HNx5Bb08AzyYKmUBpCTPLfMbt7NwOlANZ9i753YmeruYnpnDWMuuXXv4H/7pP2XfVduJcQjkEA3GJOnjGFPaO8TAzOws7/rxd7Fp8yY0Kt57vBOGWaomZFHIgjK9WHPf/F52SI/nzxxjOYxQUwEBYgFhAmKHqq4RA/uvuokff/t/xdWX3UeRTeGspcgL3vGOd/Dud7/ru+6zauoDKIqC4D3OOg4eOMCb774Hq0km2UWYUcveMMGeFceGkbBhJEyPYHtpORBm2DlyTFRKZhTE8Edf/HM2bdrI1HSBRstYkllNBbqmztiiRYsWFxrOu/apiKz2A1yICCEQYyTPM5xY+v0VnlsYcuXsNk7VKxwKZ9lSRS6dnuPp48d53CwQRkPutzt4PgzJfeTscIFnTh0jbM2pJw0Dm0M3R7XGIJjMsHB6iVf+/CGu3DhH7YdU5YDoptmwbRdHT53ia1/9Kgfe8m5mpjaiZWTpxAL904s89a1HqFdOMn/WIUQkT1J3qkpUpd/v88wzz/LS/qvYMD2DquJDwLg8iQY3ujcmwvDsWU4MPWdWajoKFkM9XUMOSSAnAJGyHCFimZ3dzE+95/184ytPkJuc3uQEUeGxx57kve/9Kaw5Tqe7hbNnAkUnY1Au0is6xJARsVRlyQMPfIU33HwtVVlirCGzOafDCJtnTJVJvygYuHX3PrYvRZ4+dYLDU0PqGBCrKC5lJzRvyh6Bp599lMe/c4g42sZ9976drPcCX/vOn9Jf6fPRj34UQiQ7J/WeBH5q71GtsabD0089xd7Ld7Fr+yYkKhLgsiv2sK+7mRvKHqOpTWyYqHnp1FF2XL6HjacrbogzdHZvxg9f5uGFo0QVyjKgRMQEjLGk/EJoXuMSwIXrALdo0eJHF+dFDjjGNOEasy7CvkDnQGMMxhhiKuxjrWV5ynEi8ywXsFAYSmrOFspUlaLCvOtYcpHKKAMHy9Fzctay5E9RyTJnej1e8cu4menUeR8CzmXkOWycm+HJJx9nenqaWnM2Tk/wja9+CR88e6/ex5c+81uUvmLX9s0srywyKAfkRojOoGJQSU6FqmKbY08d+Yl1MYSYbuq4+b6BCmRFh6npGSZnHF01BF9j/emxfQQsxCmsgX5/ic3X5nzus79NJrOo3chLLx8CUTrdjKv2X8/hl79K/2RJtzNFXQ/p5DkheFBHJEJQsqxDjJGiSD8jkY51hKh4w+r6g8dfeQGTbWB++1a2hzP0RyepVRCalLoMkregkYjicqUMnoXBI9R+kBr/XMb8pk3MTE7x4pNPj+/w6qqBoiiIQVCNiJG0iiIGjLVoDDz//PMcH74AGy/l9JFjPJL1UWd4fPEYe6SHMM8D/Vd4fLKk6jpElc2b5wkhUNcxOStNJ8Sa4b9APd8WLVr8yOO8ZABE1uj/tUlZX0woNC0RGxHoVEo0wnODM/zY7A72VhsJHctDy0cYiGeEUhpDtDDIIjU5Zd3nheef4+D+m3j6q08wUodqiZiSTvS88eBtHNGKo8cXmZQhp156ns0bN2AInDxyCCuR/uIpdu/Ywjt/4n6ee/ghjjz8EmodGgJzvR5lVVPWNVu2bue+t72VN951J728wJcDPveZT3F8cRljUrdAlCTfO9LIieEyJ0c1RRSsGKo8pvV4MkxNgAJR4ejxF3jh+W3ccet9aMg5cuRZziydRPIZ5jZO8U/+yX/PJ//f3+T3f++PsC7ggyf4gEhaRmnFcvMtt3DvW97ItddewWSv4A8++3m++eA3mfCGIEJpoXaQBzjWU/rhDFcOKq6c3cgJW3J8ZYC1ulr/J3aIfobdO25g3+XXIziWlo5y4sRxrLMYY3jTm97EO99+Py3LkZEAACAASURBVP/13/m71KPUk2CMQQVM6rdkfn4jb3vbW7njjjcwPZmj3vP5T3+Wk8cWySYmeDwsMuzUnJwwSISqgOgrJuqzHJ5U+h1DEEPPWn783W/j6JHjrPQrUgNgDRgk5kC8cFNfLVq0+JHHeWkCHEc/F5vhH+NYXvOZ5efp52kJWGEt33YDnhk9y8TpAV1rOTSlWJvz0uJpJIwoXKCWCqlz5o3n0T/7Cj/9of+G2669jj988lkqW2LdgC9+8hPkWUGnPAJa8Ynf/jW0jiydNnzsf/815kMfqYQzD32b3z3yq2BOMVWNmA5Npzw1o9GQ2ke6vR4vvvQSH//4J/jkJz5OJoLGilCNKKzDN9r2UZTaCHXweCArhBECMeLFpA487STLH7ogJUEHPPD1T7Nprkv/bIkxltoPyTtTnF0+ifcVXbcBQ45xFdFXOJcTYk1d12AMD3zlAR5++CE6HYFQsnK2T247jOqaAstUJSx1lOU8ZYpGoxo7WuDMy4v4CShsjqcmpSgCSE1eCEeOP8GJU09jrUfjCnU1YuRLOpllub9Mt9vBWouXuhmPivfJYcpcjyNHj/KfPvNpPvn7H6MoBBM9y4vLuKJg0ZcsxhGhSNeszEh8AaHkG8ZTilKLYsSy57JL+In3vI1f/Fs/S4wOMR40oupS/V9GNAWYv7Gx3KJFixZ/Ec6DHDDnrAK4kJcA/kUY9jJiXZIPhSkxlAUshwpvDYONGVEjlYFhodSjigkUsQoSyUyP2i9yYnHAv//8F7jnwH6+8txRynoBXy8hvqDuB1zmwS/RNTVBC4KbYjDs05GKoIZtM5s5tXQGJgf4YUmtBRprxAoIWGOo65qJXo+qKjEoVYgIHieKhoAV1xDYKNEoagyBgKgB9agojpy1dHUysmJr6qqPdZHFs0tYySjrisnJLm6iy11338Y3v/VNvvTFr6DBEeqVtN5dM0DIstQDEFQZDUeUo5IYSiaKHn5U4zuOWpWpEiZLwRdCyMBYy7CjHM0DaATKJp3UAXXJUbElQfsp2+DBigGFXrfHjl272LxpM7/+67/OcDiEqKhJpERGLHnHAhZM6vUQW9MfDiEGenmXsoypHACItUgMFE0EbwtLPwRshIkautPTHLzpRv7RP/4wS0t9hBy1I1Sk6VewICtpfy1atGhxAeL17wFgLe0vkpZfXWyoYiQXS1F7vJZ4Z+ipQSpF85wylmRRERMoM0g2qOF9syUxBjJn+dYTj3Do+W8x9IaIRaKhQwkSkAjGdBLrXozAiNwJNTm1KMRlssziPdTGEQtLbJb0ETX1VaA4a9LafxGCRjJrUxOgtUQFFV1rQ2vS+2J0THqXGAbXN6lJiUaPdVVD6GNRI6iD2gthMODrD3yFP/rCZ/HDgGAxGIzNCRGQtMRPJGBRYvRghDzrMSo91tj0vQZqC7lXOiFQAZkYaonUTsmUhp2PppveJUIjDah4jAiqjohBTQ0ox44c5ZOf+ARLZ85gRDDWEEXRmM5RoxA1YIzgo8egGHFgLHVQsAaNY/6/ZvlkJPW0uMSlYESwavDDPp//1O9TDs6gmGacG4SmSVMg4hITYosWLVpcgHj9SwDriH9S8CTNSoCLJxOQZwVVVWKLSI7S1cAoRIItqEPEIhiFSZ+i5iAALhlaGWAxWK/AkDNV+k6hiw2QotoSVFB6eAADBk8OlORNxthj1WO9ITatcoampb9JKYsCIaR/VU1NgAoYl/r61nUBmuSZpT9W74U0nf8AFtFxtJoRqRMDL6SGPmOAglB7zpw8tfpxdYGm7XBduVtBawQSgyGWGEBMRgTyhicniDLMkrFNlMDJcDokRdJpeUI6xuY4I4AxzfkFwphpT5VyNKIcpbR7JGU+xgdmSIyIIunYXOMVjc959dLIGs2ymJT+xyTPafwd3iiEIcPldK2wibwZsuaSp+NVMlq0aNHiQsV5kgM+Vw3wYjL+AFVVYYxh67ZtdDodik5x0Z1DixYtWrRo8ZfhPMkBX+TNzyIcOHiQn/mZ97J33z6qMjkELVq0aNGixQ8LzjMT4Dj6v7iiZ2sN1113Hc888yxPPPE4ZVle3A5NixYtWrRo8Sq8/mqArO/8H+sCXNjWc0xeZG1TA9dECDQYDKjrmhBCkghu0aJFixYtfkhwXpsAx0yA64mBLjSoarNawRJCYGZmmqtvvAXnLIcOHQKEzLmLLIfRokWLFi1a/OU4Lz0A43T5WhPg676X1w3jDMW4VFHXnpV+n7m5DeR5TgiNsE1odd1btGjRosUPD87TKgBz0dTMV5XrQhJzGY1GPPzwwywtLbFt2zastRhrzlE4bNGiRYsWLS52nJcmwPW40JcBiph1vAVCCJ7RqMQai7OJ1KZsVwG0aNGiRYsfMrz+TYCqqMZVJsDUA3DhRs/GyOrL+xoRoZcbThx9mU1btzEzvw3JeiiCqGI0YpSGqOb7g6ic82paJZv/YpKTVbDRrhLNeKNEwESLCw6j0tDtGtCMIIo3kWA8guKiwcXEXheMXyW0+d5QnNYImhQDtaSWHEm8g3iTIUSMBhRNksRAxKICog3bnoxXeyROxNVtNVEYiQoRSxSDNj+9jQRT460nEjFBcNHhYwSJiOYEEYJA4S29uqZmgkBB4R0TZQcbkjrgKoWvsatOp8aYnLgYMRrJBCQaiBaoUGrQIhEzmSFChRCa4xZEEzlSOue6efnm30j3TmqgIkpNCB4xGV4Tw6LaiMcnr9gLlkSVHEzAW79676wKSAXim/s7VhVsGJPwiVtJM1BDgVJrQYgWowJq8JJh8KgEoiGpW2qOhgxVizFgTKJ/1GgRyRtnff1YNM3PMdL+o8TmvSQXLSoYSowKRmssI5zWIBXBeFzIEE0CTHkweDtqmBUNgsE25EtBIh5F1SIhI5MivW8DSkjMi6vP3PqXNvsWvLo0rhQ0CkKOxG4SjoqOQCRImcZG8xlIYyrK2nui8pp9PtYaYkwiV0oAfBq74ghN+XB8XCqx+U5D7l0imdKx3uX4fiqJmDKD2IU4meilNKIRtBmfoq4ZfzKmnyKaGjEKajGaYdQiGhA8NkuEXT6G1TlXhFVl1hYtXgvnJaxdH/BfyMYfxisA1ku4AtHz5S99kTNnFpjfso06QmwexIaDDsXwV13doLDOMGt6sKUxdmjjHDRThSgqglGD0cTkp2N5WTVpG6OoCelolDS5iaISz5nGvxeSwU4wzQQnqxyAaw6LrE5ka6ee3l0/ea5dS9H1V7X5rIKNppl0FZE0eYqCVYMEpZMVpOk2UrlA7ZJhE6mprKV0QpTmOrnE1FdVdXMvfdqbRpxzVOWQPDOJG1ADThzOFFgbmyaVvDmduHr8a8bQNj8FldBc1/H5No+OjO8hDf1yJMvzJDMsYJ0hxEDuHBIilmQYo0msh6y7t9+1X4nNK40FmtJarCuwDpflWInNPTcNGXVyPqwDIxbnCowYYqxRPBBRjcTE27xuDLz6lzWMzzcNz3X3F5qnQBuHMR2rVZucvMZpjqahm1YhqEKISaHRSHIiEXKX4yufbgnj8SvnHMVrHaBzDh8CIkqeGYgeUYXG2Rg/D+s/FVGiCEHkHEf5tZ7mEALOWULwZJlt6LN1dRysjh2JDfvkeOzL2vhY/ebmadDmTptxg3Qjn944D8kJtOdsTzPevU9CVAaLaEzPEIpGsLZAJPV1J8MvaWXTBZyBbfE3i/MkByyrzX8Xcvp/PdY7KiEE+v0+n/vcZxst+yJFdz/oUsC/JCrXdf8fTyBpEomrD38Uk6ZV9UnlXmEsNpOmpGZC0u/fOUlmeW35o2oy/usnN4VVZqexsoDRkAyCJCrixrYjibC4oUVujLyGlKUYrw5RgwlNNCbpWK04wGCsoRwNCFSYriOaEoh4G4jUBFuhUjPMIlGUyniih15RoCi+rjGNBkXth42BDojxjMqazOWJ718CzmQEP464JWUDAIxfE09YNXNjmuTx3831biZqiYYYItYpoSrJs4IYaoIErLF4X5IZRx0DYgSJFtX132tJj6NZtw9psgJpH6qKmEhWGBRPWY0wVGDz1bEjappSVkmoPd3OFKrJwdMYMEYpsg5VGRs9iPVOQERV1o0cs+7YBBivhhEgQ4kYUkZqdTypa+LcdPzReMY6DmpAsIiJVN4TbUyS1eoJPmKNYp2hCgFrCmIwq3tTWYtkRZPhFhXK0ZCpiZwYh5SjZfKsQ6g91uRp/GGJMVv9zKqRbpyv0AiXjZ+3V2fOxgGCMSaVBm3SfdA4fkKUICZ9rnGQoii1U1QCaw6TJWVQlLywIBHvl4gaELUYcal3yozt9ZpDmsZmym5YlxF8pK6H9HoWJOWnBmWNSI6VjBjLNP7riizLL3JWthbnE69/D8B3MQFeHA4ArJUsOp2Cfr+PiMFal9T2foAeAF1Nkb/GPpsXq9uYxvBLmpAlpWCD0HDuRyx1E3NLSvOOo8VxtKCW9dP49zjrJuocOxkO00xUKT0dSKbBNHOmTdGLJkGjKGE1JZvmv5ShSFGtRZEmayIYAqbJNogKLqaJzaiB0CTZRciygjzP0bokj4FOCGQxaQt0fIVrBIzGpRNnHLWPeB9AoOjkTE51sE4R4wlxSIgjikmH2gqxNVAi1FiN6ezHUZc60FdfO3nVa20sSEwOhFVDllmMhiQBJJocAmsoOpYYR4jUGGmuldom2pM1o9qoKcI4OleS0TBpXBglEqhDiTGRIjc4mxQgU5mmGTciiAl0euDjCiIRDYrLhKhDKr+Mda96MlXWfQfNvtN+0XQfVR1g01jTJtIUSyRrxqZBNMOPI34gSGjKAeOclEmOgzE4lzXnWiNSYqQi+pIiK4gxOZDaGLg0Rs267Fj62S1yynIFXy0zO+0wLJNnI4yUiAaIBoPDJvEIQpN1MDFlXqIkJ0Bo9DJeBWMMMUaMSSqX1lpiGJdukhOw+h0qZCkhQ23G9665lyqrjmaIFcPyNDZfweZLOGfXgqYmm4CMyz9jWFRtk5GA7oSh8mepQx/vh1hr6RQTTE3NrWY0rXVNhuHimYNb/PXivGoBwHgJ4MUxANPqBcH7QFEUq3U057IfKIumr3qt7o8mQNVkhlOUk6KFcQpRxhOBCFHyZiqsME3qD82aaCs2MakiTa34+0UQsxrxBzHYJo2eJsV0TEFsqntLSqta6qYXIknkjh0Og0HFIiheLNGkyd/LWgRd2/SKYvDGErAEl8PkBPtuOkA+MUFtk85gXmd0a0ceDGhO1wtFnWFijlOLCxlWsiYiEyYnJ/ngB3+eK664nBhr8sLw5jffzd4rL+Xet93BxJQgZgVrRsAKRkYYUiRtCOl6S1g3AY8n8fHdG6d2m3p0Y5hsFMQo1+y/go2zE9T1iG5WoDEwt2GaN7zhetDh2r0bOwCyPlI0zb6TumEaGPVqNkI1Nk9soKr77LpkCzt2bkKkBvVIUx+3wP6r93Hrjx3A+xUE2LBhEz/xrndy//33MNGzWNFG7XF9vF42zlwg9ZsIKskpME0xCFVE/GpqvXETiU0mQxTUhGYsR6Lx2NWqUTKSSWgpZUy6Rc4b3nADM7M51no01JgmC5UEoOKrMmfjcZ3uU/AVG+amueeeO8hz5Y7bb2Lz/CTWBDTWECKirnFIkx22CkWAPLBqwOG1HYBer8f999/Plq1b8d43oltgiNjmFqXnx+CioVMLWdTV8s2qomXjOCbnLPKOd76ZK6/eydvuv43eRA8RIcbQlLDWj7fm2gmkbL4n6pCr91/CHXfeyFX7d3PtDXuJWmItvP3++7jlljcQQljlN2n7AFr8RTgvTYAxjpsABWPMD546P89IZECyWjeGc8sYPygiIM5x191387/983/Ov/gX/5IPfehD9Ho9nLGE2uOMoaorjHWIOIxkaAzEWCM2Gd7OxCz/8B//MtMTGbaJKnxtsdaholRVjTUGQzKIqk1/gKH5Pb7qlaqt2JyoqSYZMMmwGYNoJBMlKgQs6j0Tk1N8+L/7MFvnZ7EYMB4JioZEqGTF4gOAEqzDW0cZIj7v4hWCcfQtjHKDzywDZyiNw7ucMD3Jpn2Xk09NUgrUrkPMZhiUltp2GLgpam/IJjfylvf8DL7oEm0XHyJ5XuCc495738Ls7DSPPfYYxgjWGm6//Ta27djKG++9lenZjEsv3cxH/ud/xM4d08xvzPif/sdf5tpr9yBmiHM1ohVQp6i9afzLrECM1NWIonCIeDKn+HqUjEoMqK3Yf80eNs52yHJQX4EqW7fOc/Cmq3G2xlCRmSQBbSQStUSlRKRqSiklIkMET10OsTYkaWMM3pfEEFBV8sKw+5KtXHLpNuq6jxGPxhpnDFZg586tXHX1brIs1YeHKyUPPfR1tm3fyOyGDiHWKIEsF9AKg8eaIUYCwa+QZzEJQFJjTY0zEWtq0CGiNXW1TLeTIQRcBiHUgMfoiDqUQEVmA8YpRpND42xG9DVihNhkK4pOzm23HaDbVUSGFLmAV4xRQhwgpkKMJ6pviMU0pc0lIiYSY6TX7XDLLTeBeA4cvI5NmzcQg2+ae5u+Ce/BGIwxdIIwMVImK8g1PefWWoyCyJrBDCHS6/W4+eabmZudI3OukbJucmEx9d1oozaZVZFZb8kGNdlqBgfWHMfUmKpac/fdd7Jj52buefPtTE1ONUykgrE0GYCw5gA17pmPQ5QSYz1XXX0JNx68ih275tm7bzdFoQzLJR566EE+/OH/lk2b5ptlzUOKIj+nxDnuOWjR4rz0AHw3LuwMwLqExeteLhvXz/dcvoe/9bM/y//6q7/KKy8fQgQya5mZnmYwGDAYrjAx2aM7OcOpM8sUWca27ZtQP+DM0hKjyjI/v5Wt8zPsv/JSnj865MTyMhXTKAts2bYFGyboj05xZhE2bd6MMT4ZDBTvA8vLy69KByoilioomzZuotcpGNaewalXiJKxcX6WxdMnsK5DZ2YDxVKgOz3D5i2b2L19K1BytCxxw1TLrqgJUVGXEXSE6U0iEpibn+KMn0TxVAHyTXPUgz5zrofPFL9QonmHssj4z3/2p5gTJ4iZsJx3Edtl88bNhFiy7CMdLeltnEd27iC/ZAfx7FlkaZG6HLFlyyYuv/wKfu8//B5VVad+hAhHjx7n7HKfV44cYVQN2Dg3Q2/CsPeK7SyezJmeNkxMgM1SFLVhfhpCxrHjCxgxOCfMzU0Dwkp/RL/fpzMJsS6ZnphkBWHCZpSmj7FDOlmFD2fZMreTk6MVssISwggjFTNTs9RSEIcBMTAzP4WRklE15OyZAROTqQ6euwk6nQmOnnyG6KdwVug4h9oUrYfg8X5Ibir27d3FqaUISyVV9HQ6k3znkW/x4NdPEbXGquAr5dTJk5TVcuPUCMYKlT/LlvlNmGiIsc/yUsn8hi6VKpPTE6gt6J84QwiQF5HZ+Wk0GGweWVioQEuK3LFlfhuD6gTlyoizQ2Xj3BSqJdLZgK4s0R/CSr/PVK+LD+X4yQNNnfVTU46Tx4ZsmN/MwrJlFBaYm7PkeYdyGBmNAr6uEBEym5wAVCnyglFZcfTYScBx4sQiw2EgjisYKEpNlucM6worGZO1sKe3gaWVPoPhEDuRUdcBF1O5y1pLjNDtdgD47d/6LU6dPp06YwRCDBhcyrs10b1EmAqWG7bu5tnjr/ByOaTMU4kn5eHjWvIIy+HDRzi7NODEsQXq2qf8jxG6nQ4isLKykq6PABpTYEVJr9vB132OHTtO0REGKytARuVLIOeZZ5/gT/7ky/z0T7+Xf/NvfjtJhIfI5OQk1loWFs6sZgUu9AbtFucf9iMf+chHXs8v/NrXv8bXv/5g85fgnKOu/eu5C0Apig5VtW4i+S/GONWearHp4X/9PGQB1KUsyMGDB9m5YwdnTp/m9OlTFFnG+3/mfczNzPD8C89z2513cMcd9/DUU8/z/ve9j907trB58zSD0ZBTZ0tuuOl27r7takanDzMzu4uF5bMsLzvue/sb2XfFTnZtv4JrrruS48f6/NLf+Xmuv/5q7rzrTrbv2M41117Lk089QV3X5xyfV+GaGw/yk+9+F71uwdve+R6kXERch/f99E/xrYe+ytzWnbz7vR/guW8/xNUHb+WOO25idPIIs3O7OF2dJJyq8Sp4lxqaKleQW8/Vt7+F6w4eoCgyLj1wJ9VwieVSufntb+XSS7azZXqWPddfw8LxRZCcPQeuZ99V+yhfPsrSyiITuy/ntre9m42b5pnbtRWzfRcLLx9m25VXseOafdRxhW63ixkOGfaX2bPnUjZu2MCDDz6Y6rZiqX3k5UOvcPjIER57+gkWT/fZvnkrnTww6K8wN72VY8de4Gx/gYWFPnfc/mNsmp/hLW+6h3LYZ3HhFPe99W62bJ5lfuMs1aikrkquuvYStsxPc+rEKfZccxV7t8xzePlF9u/byXDxNDfcehPbNmzhzGCFbs9x6a5NDJZPccsbbkHJOHHqDJddsZsr9u7gkks2c9ut1/L80y9z/Q27ede73sxUd5Zbb72RUXmS08dqYiWIDUQclpraGvZdsZ3rr74U75Wr919DoZ7jJ06zc/cl3H3PbWzePMEzT72E0RnQDllRsv/aHbz04ousLDnUKPuu2sa+vVew97I93HTzJbzw7BGuvvYS7n/XW+n15rj9jTdTLh1ncLbPvW+9me1bp7nu2ht5w617eOGZYxSF4brr9rJr56Vcc+12MlPx3KET/N1f+Ckuu2QzWW8j9919A08/dQR8hoYSNUqU1FfQ6QhvOLiPF557lAM3XM+eS/Zx5vSQ6Q3CPW86wNzsNDcfPEjwNadOHseKIJoaBkU9ZF1GwwGvHDlM/+wKL710nFOnV6i9Q8WgJhLFoxXE3JEF2FJa9nc3YYY1Z42nb2JyyMUSmjKcMYbZ2RluvfVW3nrvvbxy5AiLi4vpmTHpuc5DU5BzhiIatpSWA3M7KFdWWKxWGGWpZ2Jc6xOJGKuEUPPyyy9z5JXjPPbo/8/emwbZcZ1nms9ZcrlbFVDYF4IgSHBfRVLiLokSJcoyLcmWLC9tT3umNWGPNLanO2LsHo/9Y8KOjpj+4fC0PBPTDksty7a89nihKLJFkeImLiIJAuAOgNhRWGq9e2aeZX6cvFUFkLJJEbAAKd+IW7cqMyvzZOa9+X3nW953F/PTJqQivOX977+dK6+6nF2vv75QyU/Z1udEgfChI2lups2+vfs5dPAIRw4fp7ACbzVKafbtfYO77rqLHTt2MBwOSZKEe+65h9tuu42nnnp6oabh3T03f7Tx3ve+j/e+96Yf9DDeNc5YDcC55Fye7Amf3miFB6xz9Ad9fu/3fo/de/bwv//Wb/Hrv/ZrAOzcuYO77rqLDRs28HM/+7M8t+0F0rTBLTffzP4D+3j00Uc4cuQwUkc889xLHD00ydNPPcY373+Aw4cPs2zZCq688mqee+45duzYycTEci68cCtj42Nse+F5lJbs2LGDdevWkKbpkqKDULU8vmycX/jFf82zzz/Hww8/zF/+9V/zr372ZxhfNs7EiuWYPDxA1m7cRK87YNsLL3Bk8hDPPv0k/+0bD3Bocj+xjtBShtCskjgp6GV9ZKPB8U6Xp3fs5JWDk2y+/CpM2qK5ag37Dh5k+7btWOuZaE3Qnprn+ee244ynpVPGdUqiEmpJk+effp5dr77Oxs0XEHnDkX37mTp2lNd2buOl55/l2NFJtNI0mk2stQwHeXgNDdYIOu0BxVDQaXu8q5NEY0wenmXl8jW0ak2cy1m5YoJef8iuXS/xykvPMj11kCsuu5BGKrhoy3piZdn5wlNMnzjM3PQkrbGIRlPiXUajGbNsvIb1fVatTvncv/lppmeP8NQT32Z6eoq0lnDDDdfysbvv5PHHvsWrr+wACg4d3suOF5/m9T0vMLFcsWZVg2Xjkvm5A3z7ofs4NrmPKy+7gEgKIqEQzi4UViI83hn27n2DF7Y/yd69r7P5/PU4l3Fg/34OHjjAxIpxrAthbTHqdChbBb0PhYKzc8fZseMpXtj+FKvWpIy1NCtW1On3p/jmg1/ntdde4Kb3XsbyVspVl2/k4Yce59lnHqMwR5mfmWLQn2PXa9t47OFvMX1iP+vWpoyPNVBk7Nj+HE88+h1adc/ysTG0EKGPIFS9lq2N0Bqr8Su/8ksoWfDA/d/g2NFjXHv1VpRo8/KLT7Fzx5Pc8/EPUYslt91yI//X7/9Hfue3fpM7br2Jbq+HjCIOHTkBssV82zIcSLxIsF7gpMOpgkaziVSSLRvP54PXvo8b1m/hQ1dcz/Vbr2BifBk6jilMjlIK7yHLBhw/fpwHHnhgQSgsy4ZorU5qUpSEgtaNq9Zx02XX8p7zLubWrVdyy2VXkegaofo/1Og4X2BMTqPR4sC+o/Tagqmjhl5viLUhJffcc8/y4IPfxNhi8VnkR10AOhQS2hrz05bjRwYMuhHteYsrIqSKsc4zGAxxzhFFEUkSk2UZ33rwQf7sz/607Ax4dzVNFX54cNpTAKfa/REpy9kabjpVqOh0Fy2O6vnn5uaJdcSD33yQbc8+z//273+Diy68mFdffY2jk0e59dZbeeGFbXz3mafQqsWv/eqv8+/+7f/Ij919BztffZU/+tN7qccFuTEIEZXEMxaJ4LrrrqLV+EU6U4Le8DgnTpwgiRKKvFgIAVrrFh68Y2NjeG/ptLtkRY7UivZ8m26nQ9rp4cvQar1WR8uIRr2J8JY4SRgMhzgPhbWhHcp4sjyDKGFiYgJySXfoiGt1dK3G9Nw0nSyjlmWodBwnJVmeMz0zTdFu842/v5fxIiWN6/RyQ6o1zljMIKNlIe4b7Mw8goSol9PMCnrtNuOA6nSpGUuSRBRZTjbM0SomSZLQteEd3jnyoaVwAutAyZQoaiBdxss7dtFvK9Zf1MDLmBuuv5YP3HEzs9NH2LLlYg7tP8r87DRf/cqXuOeeT/BzP/NZ9u8/zP33fRspPEiPN0HhVQAAIABJREFUcAVJqvB5gbOebqfNSy+9yNZLtjD58iRHp3qYImfP7l3Mz89x6SVbefzpV6jXG3zmZ38SqftE0ZCNG9ZQ5F20Xk6e9RkOuvS7XVatWYYpLNZk1OsxeVH20ntBYXI6pk+73WUwHJDWE+JE0xv2kQKKvCCJJKIAJWXp9wV+BiksSS3i7o/dzrJGC200GzekxImgKPrMzJygsEOQYVu8oZbARz9yGYnewsH9ezFFxpWXbeWW226gGI6zan3Oqy8+jzMDBI5hf4AtcuZmpom1xuQ5WjqCUVz8js3MzXJ43yHOO/88JlYe4sSUZOXK5Wy+YBOt5kq8jXj5xR0Ib3nqicd5/JFHUDq0YsbJOIOsIE1bdDpD4qiB0DGyZPWkDNt3+z2MhiMHD/Ld2UPEY+dxbG6aV+IO8w2LU4JEa/Ii8Ek0Gk2ybBiKgm0oClZKk2U5Kl3SQuFBeM+xI0d5qXuCdWuH7Jk6wMt2mmKsFhTRGI0jFKp2u10ajeXkuSHSMVFdYV2Oc47hcICKBEJ4/AJpWIAUGmc1+IhIJziT4WyOlIEnwhaCOIqJIx2Izayh1x8Q6Yj+YEiSxKRpDWvMOTVBq3DmcNodgKVMgIF97Ozm0R9xFYyiFqHd7+Qv3ruDQFlYv3YjN918Mx5Ba2ycPXsPc2RqlvlBwXee387H776Lv/6LP0G4DmMrWtxw4zXs2vMqqydWUYuapMIhskn2TU5z2yd+iY17J9m+YzvHT+zlgQe+Ac7QnuvT6XeZ7hzDFDnehhmHsylOCrwCHbf4+Z//73Bmnj/+o68x73L+8f6/4xOfuodrL72EDevO4777H2Xvnn04p/nsz/8bWmPjbEzBRwKT9Xhj1ySf/MVf5ZWXXmPbi9/l6KEZdL3FL3zmp1guHb/7/3yJblSjsJb1F27ByDtYPjbOazuepznssNwNEdIia4rW0FE4w8SWtWy+4hLGN65n3c3XULzsGdoeIulRJAYh68SqIBMRmSg4MXWCm27+CEfmj3F87046xzKOTZ9gbHwZKyZWcnTqKCDxBQgbMabrFK7PQEtcPceheX37JE5pmpsvoTW2jJVxm0TkTB7toJODeJ2TNsa58KIrmZ7t0M9y4kYNQ0xntuC977mSmBZbr7qMA8+/jDQ1hv1lPLLzJerrV/CJT3+Cr9//bVTumJvOefjb2/noRz+Ki5axa/cbrF7e4PXXD+C9YVVrLVJrTF5n2K+jozqCJsPuSqSEuCHpdnuodAxkCnkPQcyFl16Cri1jbNkEO15/g6EseN+t13PN1ReTporbb3kf27ftZmKiwaWX3ciF519O8T7Bi41dHJ2fZu26Dex9/TWkcUxMbCEvDNBCigm8SzB5E2NrWKmYnsu44MIrsXmT196YRClPLa1jC8nePbtxcoxhlqBcH2MERaFpxhLUBuAwxnWIag28kwhnAomRSbC2xaNPvcG6tWv46Kd+gge/9QjPPL+DuH4TBw8PMabLoQPHGBiB8wqhE5wPFN5SeBAKbz1RXCMUtubB0ZEgnAYn8bFEe0/uLfvrHjHep6st08WIkEdgpEeWnUB5nrFlyxZuvPEGLrnkMgaDISB4+ZWXESakCIcawKOdo1CWfS3DQ/UZ2hOOEz0VOBAELLYChsetFGBNWRTpHNY7pAKtJTfdciONVo1v3PcNjCnK1tAQbxCu5J9QFi+GOB14G0ZdBgKHyzI+9ZnPMjN1nPl2lwKNjuvc8v47+dhH7uQ3/u2voYXFLPZ1VPgRhvCnuUn0i1/8A/7TF/8ACEUtaVpjMBiczkPgvWNsbJxOp10ueXcf5NDaEx4ocRxTlLOA0wWTW5z3rF27jnqjjnGe3qDPzMwMQnguueRiPvT+2/nrP/8v9ExOZgWbNp3HoNMlQjM3M03aHGdy6gT1ZpP1a9cyHA5pz88xHA6ppTXGx5ZTGIvSMTMzM6xfsZLZuSM0x1vMzXnqyyQzs8cpBhHr164C12Z2qqCvPalWbFm9ETPI8NZx+PgkupayYmKCREU4k2FMnwPHptC1MayDLZvPoz1znGG/R+YEmddsXDHGmO/z8uEpsrE13PwTnySTnmeeeRyd9zFTczStpLmqxYnZY0TdnKZIMTJBrFjDMNbEiUQPO0SDNr2+JZqY4Mi+A6xbthKzvI44OE0/1bhEs2liPW16ZO1DuF5GQp2f+uRPsWnzBn73P/wfqEiR6JRENsg6PZQoMGNNdGuecSuxU5ocRz5eoOM6aT7NeK1O5hPyvI9WCfNzc6ycWEcUJSAdx0/MUxSOtA5pJMBAphRp7pmVBYmXkOW0GXLBujXMTvVACuI4ptPpMD4+hlKCTrdNrZZSr9fo9XqkacrU1Cyt5hhSKI4enWLVyrWkaZOjR48TRSlFbimkDlX3rkutoWi2Eubm5lmxYoKZ6TmmpubYfN5aYuVp1ptkuWPqxAyRjhgba+EwKOkZZAWHp6fYuGkt2AIySzONOH50BhU30LVxpucGJPUmK9Muy5ev5PobL+Ghh7+JJOWnfvpunn1qD7te3421ivGxCbr5FINehkcQRynOCWan26xZu4Fep8dgmOG9xMcRRVGQpBFgmFgxTq83T2Ey6vWEwhb0ez1azRb1egvnPKaAEydm0CoGFItMeW/zOy7CTD3VCcUwo2RFxniPiBRegjGBAEqOugXSlImJiTIi0GDv3r3h2UBoYwQWoipSCLw1oR3WgxKSQr09Pk4hFFneR0rDipXLiCLJ1FQoasRH5UuW7ZCLewzPqMBTEMcxxhjO37Ca//M//C7/7n/99xw4Oo2qNRkOMz5y14f5X77wK3zuX/883dlpjNCYN/FdVHi7+MLnf5UvfOHXftDDeNc4/V0AZcHK2S4D/C+JJI2J4ojpmRPMzIrAdS+h0Whw1dVXcs011/LSyztpd3tkDmScsnvPAbSzxHiUlExPHaOWNiiyjEOHDmJNaA9z1pLnBceOHQsEIFKBh8nJSYzr0RsO8L5J73gPhCNNYmZnpnGuC65G4iTKeHbv3k2kFMSaoqbpuiHzU5PIwpIKgXYFOgozFqVjdu/aRSPVFHmGcRJdSzh64jjTRZtacwW5NRQzs/SLIYPJSVTRZ0xpMJ72wQ4tLVAIIhzCFnQPH0GmNTKXk5kuzRQSpylOHGdtEhMPephhl5aI0MZgnWVu3x5y7VBuQKoThPU88uBDfP7XP89H7/4I337sYTIzxHhBlGoirxkWjt7skNwKGn4CqwTDwuNyS2YF2bCL8R5sird1ZJxzdHoOV8RIpVCihU4HdHttCpXSqDfo9IYURpBJDVKVpEiaI4c6IGKM8+gheF9nejZQ8goR0R8UzM2Hfu3ZuT5C1piezYnjlLS+gpm5Ic7nRLqGcQKkRKAp8hypEga9gl6vTa1W48jBeZRMWDVxPvNzA5wdMp/AYJChdUJhBJ3eHEorjM3QWtFsrObY0QyNQztL1xUI0aDfB5/lCJEy6DuOd+dptFbRGl/DqtWbGWtN0OlaJo/Ncmyqi9aKdsdR+AKtIrwQtDsFcZzgqHFiuhfC1yXTHbgFNj3nHFMnZjEmR0iPdwXGWqSo0esa2vMzSBkxGAxo1JsEVe6lEbq3Z8SklCG15AxSK4T3IUVQMgE6D0JKFIGnAGAwGHDkyBGcs1jrSNPAFKm0flOhsHM20O46AmGTH+kn/PPjk1KTxDWUcrTnuzhnEFKXxFQlGdP3jEp6okiXxEqaD3zgg3z5S1/myOQkQsbk+YC1a9ex5YLz+du//VumpqeJvMVJCQvcHBV+VHFGagCEOJ0h9DOPM1kECGCcIe9lRJEGAZEUWGvBWwbDAQ8/8jAH3tgNUqBUinHgiUiTBIoO3jpiLbHO4YwlVgKHQ6kI7zWFMeAFWmmcteFhZx1RlGK9Cf3EPjgSpsgI3GrBUfDOY71FRRojocBSaIlxgkiq8mEoQChs6bgURU4Ux1iTo6TAekeRZ0gVKqQjQDvP/p0vkhUDxq3BW0vkPVqo8Ei0FistAxXGUBMpkfBkzqBqEQPXJVAEaTyWwksSochEgRQqsOzFishaEhnjbRjjbLvNF//wi8jIoPEYb5Dale1aCuEcadxCC0FuJdYLvI0ITGsNcpcBCaaoE8d1CjfAkZHUG5g8wgLD/gCta1ifcGyqR9xsYkuO/cKARqFjickLBFG4vjIKIV08ECGFBOnLfD5Y54lUhMOQFSJwZyiNkuG6CyFxJae9LK+hUgpjFTbXKKnxTlHkGu9rCBWRFwKpY2zJRaN0gvUOHdUoTI7tK5RKcNbglce6HDFiHRQJtnAIrfCqzoHDJ7j3Gw8zNtZkvm+4975HOX6si0oaWAs6qoGpMcwLojhBSBc+Q0kazlFInDCokshISokxNnBYOIeUCQIoch/47KXEmkCbbApHLR3DWcoinaVshW/PAbDGoMr2N+8cSkiE1gjvQutqSTbk8EgZVECtXayWj+O4bJ0DZ0O74MIoSr7/cJ5+VGrzthFqdaCwDqk0cqRQ6hUh2jEqNzy1O0ksEJc559Fa8a2HHmJu+jhCysD/YS1FPuThhx/i8IG9RDpCuKoDoELAGeYB8D/yRYAQxENUpEs9AY+zBhVFDAZddux4AesgUh7lw0PTy/DFN8YgbEYsa2S2wPkkMBT6HFEKuljnSNIarowISKFwRQFSYz04B1HkMHkwgpHWFLkjimKsFyQyFGfFUURREoQ449BItPHERhAjcEoGURmCcQqkNAWxDkQrSgq8lPgopjCGmIj25GFiBakdIqUD4/DOglAUwmNSSY5FeUliHK4YIrVnKAx5KpDOoUxBVNMU1iGsI3eWSEQ4LchkMIjKCYwHtMR4x3BmCuWHRMLR1EkI2zqJ1KAKi88FyAgfBSMTiSTwJbgIHccMB54oTukXM0idIpSgM+xQi1biXJcoSrAOjHO0xifoDvogFVpq8IFbzxYOITRCCHQcl1GfQNoEvjRuQXdCKYVQgrywCKkQUpTdIxZXFGgtEVJgnUNLgRQeYw3eQBTFDAYZkU7CTD+3KK2xzoewNCFUrCMdiKKUorCeOGmSFR5rPLFOAuGUiPHeIZTGOkuURMHp9DGDzHHw0Az4KQpjiCKNIwYf4bygsKHIMorrQSyn7JePY00+GASCLeEoSgKkxShhmcuXulTJC98+YzxRlOC8I46CuI0tC0+/HwhCiF8AWqnA72gtQpUdS36koBeKB6VURFFU3h+JMWahVkAg3pwiFOW9lBLrR07A22uykjIURUZxSp4PFhhJQ93A99b1kFKUkQhfjtsyefQYzuTIKC4JpCyd+Xl68/OYvI+SAuX9OyEKrfBDjNPuALiSCRBGUrtyIb9+NmIk9qGUOkNFgISHuhCktTrO5hTOBCdAaiyCJElIIg/DDkUeuMrHWyupyQxbdLGZxmUZQsXU4ph6GtMfFvSGOR4oCkuaJiRKMT87TRprcmdo1ZehI0GWd/A+wlqHczlKaZxVZcjVEgmJKCyJEDhXNi55jzaOmlMICW3hkVEUQtEiFDJFsUY4Gx6oglJdTQW1N+GoC4GwORobnJ8owcqgFKdVROEzHA4tBODKh7AMLIYmzBoRkmyYE0UJQniSWooxBSqKKIxBSYGRkswrcukRSqGtQBqF9gKXWRKdUmDJXRYkgUWN3MsgRhMBeYH2gTymyCWtsTqrVo+xZ/8kzqesWLmJieU19u15Han6+CJGigi0J3dDoMAqH9TZCLqComxxc4ToS/A0KSvTgdI4L7I0huxNUOsDhEcqkMoDJQWtoiyw9eVyMNYGlToM1nqkkqXD7RaD5NKXhgxGVfFFkSHQKAXOF0H/QQSWO0/gyLXOBKpfocsoSsmApyOcD4I2DgVSEW6Xx/qSZ0KEAj1j+kQRjOiNQ0t8MGjBGQo58CBCJBeYuIRgIdxvXWgdDIaS8rv5zr6fQdcj/G5HC5UsawMWDls6I2HDEVnOSAworB8d/80YSVIjxUjA7x0hOBnfKyz/5mMuFi+PHJKgMih0kMR2tvxu2RxPiBCCC3TeVQSgAmcsBXDqrPrsNP4BoeUGzszsP3wtNWNjY/zY3XfxwH3/yFw2LMN8oZ1uxdpV3HP3B3j4G39Ldtih4pj3XH0jF2waY3Z2J489tA0ZRziR8rG7P0YjGbJn/yGee+FF7DBDK81H7voIzXrC3/zF1/CmIIprXHXNdVx26UW0O5Pc+/f3gQ1iMqGXXOOEoa8MSgtiK1A+RAm8CoItNgq0vt4YPBJjHSMZXK0jvCkWUgtZUSCERKMD01hRlPUgQSZV6YTMC4RM8FZC4dBYakmEMx7pBElcIy+GREIReQ1ovBdolUAR1NiF8WidsGb1eo4eO0ZmCqwEF2k2XXIJtWaDxGa4mRmO7dmDcQVCRBRKYenSiGOcjdHNJvUVCVNHjpAYQazAigTnFR/+4K043ePAkd0M85yxsVX85Kd+nH+894/Y9fJrKJEERxeHs4ZIQSFyolLAxgmBdnIkzhv0Bbxc8sxdEoJ9U7psqXHzJxd+eRHSOSdtL0AsDQ1bRuQxi+xzbnHbk16mHIXHibfgnx+N0eswDq/LMdlQmCbyhQp0GFHXLj3eKYY6CAWwSD/yVkbobZXNvY1tTvmPUunPi3J0ZfG8LA110Ll45/tbGLE45WwFCxoI//zO3nztlxyIkXP8NnfGSNnh5P/wS9ZXqBBw+gNBYvHhdu7IAS9+Vc7EcK0TjI1PcNllV9CoN/DW40woLFo2voLp6Tm+850n6cwcp64jXG544dkX2L3rAFsu2oJXcSmsk3DR1kt47tmneWHbNgaDPsNhBkLywvbtPPXkk5gsQwtwOLZvf5E9u/eyadP6krAEFnXvg2xrpqCIFEQq5JxjjdWCYSyZS+BoVNBtagp8MHreY5xdoC7NC4N3liTS+LxAGUeEpJYkyEiRYygkZEqSeU2vEPREjI3q1JIxXM+hjGSQWwZaMtQah6Ih6igXMzQSTwo+JVcp3kQ0V6zh5g/dzXzP4qIargi1Ed3hkDXnn8/4+g2c6PcZqog8aTBMavTrdYb1On2l6bmUeMU6Nl93LR3h8TrBIRg6waYLL2TLBevYuWMbJhd4n7Pr9Vd55OHH+eD7P0yrPoE3BRKHFJIoTqjpKIhGOY/0IS2hXRC+kfhSEtmdJPy00JPvQntX2GbJci+CtK9TCKcRTiN9SSrj9ZJXmSMe9YyXzoDwslQdXGLyR8dwEuEk0nvA4nE4EcSZnFAlS99IilcsGiFgIRftRznp0nAJi8AgfFAmHJ3vSCVyJAQ0Uix8sxEvxz4SYlrKh3+SgzPC95fHHplZJxZNoi+T9uJtGtkFoa7R9kuM/+hWvLMC+6WCU281Yvc9rsFbbV0SLJVRzFDvs1T/Q4ziMO9kgBV+SHHGiwDPBQfgZKGM0zteISRSRXR7Q6xxrF61huWtFsM8542DR+j1Blx+9XUIM42wA/LhAK8ls9PzZMOCTq+DcR6kQKiEXm9Ir92h257HyJhWc5yVq1YzsXyC9sxxGo0aeb9L7qGwPYrCEmkR8pfhDAmhwiDvuyqT1J0gGlq0cag4ou0NvRiKekQPQVEYmmlMb2hpLR9n9erVaFOgXZ+ZY0eZ73RIx1ps2Xw+rSRhZrbNoSNHKbwNeXnpKbzH6ZgoGmP55i10Bh3qWMYGy5man8WNa/LxcVqNJlG/T//wYWSzzqYLt/DazpdZMbaMxvoVmEPT9OoNuq0GV9z5AQ4fO0Rr8ijH223mpmYYFobjx6Y4OtfGG8/qDRvpeEG9VSfWBdO79rN81SZWXHA5rU0rWXvpZTSmHN0T+7A+5aobrufokf0c2juNoB6uXeT57nNPct3Vv8S6VRewv/0y3kt02uT6669lx1NPB65/BL6UFZZOlfnikcIjLFRzO7H4++IHj5P9cXHK++K9e2vjVz7gR3LQXocIjB8dvxSV8UG3AS9LxT6/ZPn3MgqlMV4YY7kvYcpCtWCkxMJUeFTAVpr+pdPihbe3MmgL5vmU6/BW4xotf2e03QtGutyF461VAL8fjIy+5506AKN79E/9k/tn1i/FaLvvdWKV8a8QcIaKAJeEEc/S4r8RTk1XhOGePifAl0VhcZqwcvUarrn2WuZmprjyyqv5yp//JTPdIRvP28xN193Jn3/xVTIjKYCoFuFxpFFKkFdXIDVpLQGCUQdJkedMLJ/gxz/+4xw9uI+vfun/JVISHyVkphQvsaNQ5YhbHPAW4WHZQLCx1mTF8iaRAythyvQ50J+jP3RoIXEC8mGBFhEXXbCZD955Jy+/sA0zmGfq+HGSWp077rid9WvXcOzQIaK4wYnZLsNeu3ych04DpzRj46u5/WMfYfe+V5CdLlsu2My9//UfWHflpSzbsJ724Um2bFpPdvAQr7x6gHXXXIdYv5YxNDZyvHjoKOs3rYWVLXrKs3xiAjk9gx4a3DCnMJZCKqyR6KTORe+5lhWbzuPVV3dxyRWX8mr9GWYP5OhGgqzVWNaaQJmCuWMamTbYcN4GXnv0OwgbIZTDWcWgmKdRG6ffhVZzOQDOeTau3cBnPv1Z8rk2T7+0bcGqBLNfGlSvyqDr0gf8klnwYqKekx/M8uR4cjmjW+wsHzkLI6M5SjH4cgRiMe3gl+6jFKgZzQS9QiyEhRfHuHQkYpRWWDheGfL3gZgGXxaindSbf6pBO8XJPumx4E95X3qcU7+L4s2bvAMEFsTSbRgFLzx44d92BOBN8KeMbBQ0+X528laRke+57s0QLH2eVeH+Cv80zggToAs9V6V859IilbMPpxYBioUH8ekbb2YyCl9w5Phh7v/mA3Tbc1x25VVsOG8jbzy9jccef5JLz19JpDS5z8miiNz28NIRm4TUCAoR0zMFWTFPo+FRylIYR6QTXtrxKpdeeCkrl9WC8TcDJOM4Z8nyIVI0gq2RoxkbIIaAZE4bnO0y1R/g84LcGmjVmVcWKwUoCc6htCaONN3ZE9QUvP+O23j1lZd5fvtL6FrCZVdcwd/93V9x4OAb5HkNoVroqIGgh7FDVJTQ8wobjVP02hx45mFyo6lfsZUkXcmF193MyonlUFuFPH+colbn24++wuEHHufWn/84em6G1//uXlR/ngO7X+TS917GrhefY9lsQc6A8ShBOYXTitxJ0oEGDSaC6UNvsOeJx0hrYzSXr+LItic4sHdIbflV7H16GxmwxqQgFDKR2DxHyT7GJwiZADHeSwrfRsag4hq5sex64zV+53d+i363TeTByJIj3ntybfAihOEXP0lvYeje0hBCmHUvXXfqZ/J7z/K8sEtm96fuf5SrH4WIw37U6JhvCQk+Xvz/hfx/VA4l0Pu6N53L206Cn/L+duDfkZUd5etLGgLeqtTOv839nbrdgqvzVn7M28I/lYl95+F68Ra/vfX6Cj/qOKNtgKEw1Z+1xj9ALKkAPhMpAIiUJIkjkiSh3mhgi4xOp830zAxYRxKHvvBmaxw1PY9SinotIY4jhFTEaUTW7hE3FI1mg7m5NsYa0rRGp5/RbC4vIwOQ1Gvk/Zx+XtBojBFHEdZ68jzHB7aTcmQhOtDSCZuWr+S8FaupxwkW2DN5ED87RT/P8N5ggCLyzPcHZFnOH/3n/4xSis985tPcfMvNPProYyFN0GqhdYSOGnR7wdA0azHnn7+V3YeO0O0OkTYj9gVuOET4lJbSaO8x7Xme3LaN6ZdeYS4ZErd7jI2tpLVxLavjmF5RcN6GdUxmfbLhEDvXZe34BNncMaI4ouj20XoMJTz1NKZIU4a2j7QFw8482hhUMUBbhygyRJZRE7C81aTvPHZqgMkVM9NTjE2sxEuFkCXfgIxIk5Q0iUuO/jYirTM+PsYFF1zA4UMHmJ06UTq6i/d+acD+3eOtjPk72f6drj8VldmoUOGHDWeMCXChBuC0H+D040xmKUpuEPq9DsePHePmm2/B5hmvv76L/fv2ctXVV7D1sitpjo9z0+0foC93cnCuzY3v/QBbz1vH8nHBbXfczj9860GGRUaeZXih0SphOBwEydbbbmLdujXUY8nNN9/Cc08/zqArGGaD0C/ufegNt3ZJAVAIJx+XGXNzR3h1+gjSOJACGymG0uFrCussmiAkU6+nnH/+Zq6++mriOGF6eobdu3fR63b57nef5cYb3suVV1zOwcNzPPPd7Qy6bbZeeBE//ZmP8ydf+xq9XccQeZvO5GSoN5CWuV27scMOL3z729xw/XvYLC4ji3JO7DtAkWmu2bqFR//iL2ilEdddfBGzJw4j2nMcffk1brvuBmZWTfLGwdcwA8PWy7cyNtakoSLMxRfy2q6X8J0OYjAgdg7aHbIsI/aW/swUdn6em667jgOz05zov0Fuhzz/7HN87MYr+M7zLzHbDj3Z3lo2bFhLvRYxeeQgWoc0frPZ5Pd///f5k698mT/7k68syrdWqFChwjmAM1YEuDiTPr3zoDODM1cECB4pYHpqii//8R8jcWgpGQyGDHLDKy+/yN79B3iw6NKUPdpZTM/DE489wnPCEdsurhB0Ol3qqyYwxlBvjDN5vIvSNfI856nvPMGTjz9Kqx6T9eYw+QAvGmiliJMIIQSRjsiG2ZJoa5mdlwLvQ/+/Lz0h61zgCDAW5R1aBq70oijYv38/J05MlQxkhsGgRxzHPPnkk+zY8TxaS3KjyXKLEJ6XX9rJf9yzk6woIFf0Zo/wxINHMP05hIx56ZHHGHQKhvMneOLIIVpJjJMG0+8zMPD4vZO4rM8Jm/Ho5EGG2YDYCfZ9dzsnXtlPtxggyWhEsHPnC3TeeAUcrOl4XD5g+5NPoZwlMpY3tj2PdZam9Aw7XZ755kOM+4iu8kRZjtCSl7Zv546rL+XW2+/k//v7exFasWrVcj79k5/g0YcepN/rYE2BjDxFYeh2u0En/iyvdalQoUKFU3GGmQDh+23X+ZfC0iLAkSLgqXGLQA4ivu8WQYnHG0ev20NLgTGBjEdLiTeG9twM2mfBzoQCAAAgAElEQVQ4WTAwBq9Tuu0Zht4RY9BSouMITM7MzAz/w+c+z+439vNXf/MPdLoZg0EP8Ji8Tz7okESKpBbzMz/3r7jisot5cec28sxw8r0Ijpm2Du0kyji0F0ghKTxIW5IiWYE3FptG5bVwtNtzgUzIWbTWQZCoVqPf7yMAg8J5SSRBCsGgN8DjqeuIvu1jukH21zhHMTODjhMaViBdQTbskA/6jI21KLD4bkY9K0jrmvagg4hjdN/Q8Iq5yUncsjraDRkMDSZNyNp96lGNIjdEgBzkRFqhnaXodZFKYI1DewdojDVkPkdJjfYS6+DrD3yLO+/8MEJGOOe56KIt7Hr9NZ797jNgC5I0pbVigk995tN8+ctf4r777gskLpUTUKFChXMIp10N8D998Q/44hI1wFqtzmDQP6399adbDVAAiEXWwjzPS5rNIG2sdaAE/X47GpxQ4B2yNLpiIT0iFl4Sh/I2sOkR44ULPeVeIoTB+RgnNJIhkhyPJBD6LFaPiyV9v5YIjwyin94jyz7jUQ90eAkyLZEOYhuIS7wIfP6jYLZyb5/QZOQ7WSFwIjg+kTNobxAejFQUUqFcSTokQq97IUGVFdhOgHbhPdOeWgGNwjHQjvlUYoWglQlqRRh7J4HIFsQOcinItEA5QSsLpVW5tjg8sQXpJZkC5eVCTEp56EV+4Tz96H5B2SrpEdhQ1+9DRAQ8VkRYoZDel+vcwj11Qi68h/XnQiKsQoUKbxc/LGqAp50IKKQAFv8+21UBR5wZzjmKoiDP85JX2yGlxFpHkiTv6hjSL73Q4hQXwAUaVgSWaKGFaIGaFYUrxUakD3SqjghPaLkSb9pjMFxeeBYZxsr2r1MiAAKHch7lyzGOGqTLLi1RLn/b7VELRC8eLxxOuEAuQ4z3cem0uJKNTTPq45a+JJEpVcpDS1mophe48gxE6TgssrdJ79AuRC58eR0i69FudAIO6cL4XcmL7qWnUMFYa7t4rk4GQ6+cBy+D44VDeLtwbZ2QGCGxQpVtfhUqVKhw7uKMFAEuFJmdxYZ/hMXw/ygFILnggs3U63XeeGMv3vsFp+D7hfD+lNahcl8jA10SrFihkdhA0eNtadaDoQxM6ba0zyPyFXgrhbC3vOxelB0AJ28f2SCmE/nSWMpAcToiSFEelPeYJS3r3/M8R2e24HwILBKJDBS5OLywGCRKqNCaKByyJCgObHEeI0tWNi+wAnIV3qUPHWwhShFoXZXzaBfW40N7l/YutKSV/e5OhHManYeVAuVCRKCQHif8gvuk8BiCFoLHLWm+KzkUhSqdDVnN7CtUqHBO4wxFAJa21r2TfuAfJMSCCteaNWu5/fY7uPPOD6K1Di1078qbKUlG/OivxYI7cIgyND8y7GGGO1oug4ESCyaoNFOLhC1iSc+1F6fGA04+x1PTJYtLBE6GHudRisCKxXTB2zn7xThDKDB0hFmzFRFOaJxQWCGwS2bRRoXtnfTY0kmyMqQnBBIjROkASJSTKFd2o0uPFxbtHMqJ0iCHKIFwsoyCBN55L0RIa5TpjUIKPCMCHIn3EivCOFRJ5xsiE4vXMNwziZUSK4O2fYUKFSqcyzj9REAshv1Hs+qzuQgQwjhDvj+oaz397DaOnZjlQx+4jUSBlTYIiaBKw1HOEN8ucQijmfEpC4PJGv1R5utHIiPBiCEMoqRfXdrCd/K+lxCplKukX8JLIvyCw7DAe87ibrzwWEY5+NF8twyNv4NbF8z+KHWwmGcPXPOhAmGRP72Mv3vKOobwgfELpxd464HSMRDlNQrnMFJkX3Se/ALvPZRRjIULEKILTkiUF3gXtrfl5VI+iBGBDORHnJK3H32WvV+Y94f6jKW1HG92CMRIFrZChQoVzkKc/hTAEuKfxbD62csECGWv/pIQf24VVkRBO5ucRBcUXlN4iUOUIiv2HQh0+aXmZIlRkAvLg8HNAYkTFojKLXJwErALs06xKGh60j5O3vfJvztx8pEWjeWp60MR3vcDV0YPIMzUy6WMhEwkBFrjJeMPTHmqXD4yyOH/Tr68Jw9qFOkAcGrkQI3W+ZPedRkg8SgSA0mIIZCXn/7IjY6gwqXGvfmalukFSgGdkxHSDJzyP1WKoEKFCmczzkgcc2RMR/K6Z7Px/144fuI47XabT37ikxSFwdolBuidE31XqFChQoUKZxXOkBzwklrzc9BWOmdZNj5Oo9HgscceoxbXkXKp0MnJv1aoUKFChQrnGs5YEeAobnruFAEuwntLq9UEPHNzsxjrcDbk5Rdz8N9Lv7tChQoVKlQ4+3HaHYCFIkAW8//n2nQ5jiPyIgPvcdaTZTlKRSyWxo0cgAoVKlSoUOHcxOl3AEZFgAv99YJ30UL/A8HGjeu5+eb30e13EUKgVYR3gqB/XqKqA6hQoUKFCucwTr8YkGCBX38kr3uu1QGsXLWS/fv38vJzz9Dp9lA6Duew4Mmce2mNChUqVKhQYSnOgBhQINQ5l0Pkzz/3PIXJSL1BC0Wr2WSmk5VrPZUDUKFChQoVznWckSLApfD+3GsDLMyQNIlQSmKtpdfrE7RelkYAqiLAChUqVKhw7uLMFQGW7GlSynfFo/+DQCQkzlisAxmnZM4jI1ky25dsfYyKAitUqFChQoVzD2eUCXCEUU3AuQIF4DwIFTjfBHjvFhTyStb4H+AIK1SoUKFChXeHM84EeC4WAVaoUKFChQo/7Dj9NQDnWLi/QoUKFSpU+FHEGYsAiCVMgOdaEWCFChUqVKjww44zQgTknFtQ2JNSImWlnV6hQoUKFSqcTagsc4UKFSpUqPAjiDOgBvhWRYBVCqBChQoVKlQ4m3CGmACX/FkZ/woVKlSoUOGswxliAlziAQhxzkUAQv2CXOD7E4AsT8EvObWwqIx2EBQQ8RIpBF6AFeCFK9f4crugKCi9R3qPGF0rAQ4PWIQPZEMCWXIPOKQvx/DPyiv775OeaOl+fThRL5CiHEM5tkUOBAE4xOIZsaiUOLouS9UTy5f3iPJcFnQVBTgpcCLwLKiFizz6P0H4qC79uJbXzktEWW/iT7kuS3Uo/ZKfLIyacMAlwk6e8h77xb+dWLzvi/sr9+59ube3uifn1ue+QoUKP1o4w0WAi4WAZzf8EhEjj/OgZYRzgkwKlIE08wjnyRQ4HM5bnBfgFViBl4Zce5RvoaxjiKcfJbhogIsdQgxxWDISHDE1k5HaDCkV1nusgJ70pEmfOkMil2JdHfAktqBuBLGTYO2C3HIwmhIvFR6QQiC8Rboc5TyyNOLBiAmcWDR8wgukE0inEF6BsHiZ45F44cDFRKKOsgJVQESGZwYrNIUdx3qNkgO0Nyjj0CQIr/EYQFIYgUVjEVhvUNqBy4kExB4S60lsGNNAK9qRItMabQWNzCOcxYkMsOAjcDWESzCFQWAQziFchLY1tFMkOsY6h8XjvUN5gXag3OgOe6QA58CLiMIJChxOWrw0eHKkCNfTSImwHukEhYSe8lgtUVagrcB5jxEaL2PwoGxBhEN4hwOsEDjhEKWDVKFChQpnI86sZfajH2fvQ9C5YCGkkMFpAZSxpJ2C8waK87qSVZmkGaf4SIF1NAwsc5pWoZgQCU0raIkYhw8GqPA0ZcTG+hif+/BPsCxp4pwjSyJ6Y03aYzW6Y5pODEOtULqGUBG5jumT03U5HSno1erMxTCnLVN5j14ksEmElGGKaozBerDWYV1wDKSASCm0kguzbFgy0xajWa7HCxClccXpIHfsFVIqhFAUec6w3yeJUqRLiLWmyA1RHGN9gbFBIEmqiDzP8XicM3jv0VGMjmKiOKZWr+GcRSmJt462sswnIZjRzAXKCeLcM5FJlIV2XSC0QjgNSBAG5BBETqNWR8sIgce7IVIOsMUQYwxxkiCUREi1MLEXowjCQoRFoHSE91Cr1ZEyOE1RafQ1Em09La9p5lCzEu1AekEqFIkTpIVg9fKVfPyee2g0GkRK4p1ZSH2dHE+oUKFChbMTZ6AIUCwWAbIoC3y2IkQnBHlRBGdACJbrOpfUJrjz/Cu56crraKyeoJsNwFikFOQScmvoS08vGyCcxWceZwV5UjCMYkSa8FOfvJuoD0wNGPM1GHhWrV7PL3zul1l7/gVYr3AZuL4lziLiLEYVKXE8Rk5Ec9VqxtetRzWbJONjFFAa2ZCYiHSElJJGs8Ev//Kv8Ju/+Rs45ylMjivMEiNISDmUhmyUTpAeEDmIIcgchAUkeQaSFhPLLuDqy+9g7corqavzwdRJkwjneghRIGWEtRqERqUSlEHrqIwAeXrdHmvXrOW3f/u32br1IqwxRFFEoQWDCIwMM/TEQh2NyA2xkGgvUQ4UCcEBGILoA448S4nFZjatu4WLLriJtasvpNVahvOOLBtijcUa86b7LATgPUor8mGGVopPf/JT/Prn/2cSoRDGop1HOY+ynsiLhVSFUophkeO8xyuJiBTtTptIR3zhC59Ha42U8pxLdVWoUOFHG2ekBmCRCGiEs/nBGAyqUgopJc45Wn3LFjVGfniKZ3dsY+9gDhFpJjLJqoEk9QITS+brGqOg6QW1TLAyj0myHrmscfF7rqc2pnjg0cfIvcQ7RUpK/3iHh//+QWYPTBOTInQNG9cwMiH2DaSrYYzGqxqXv+cGNm7ZinEebyD2As3I0PhgkLynKAq+/vWv85d/8VcIWcoxK4Ur74H0AuUFsYXEeGqFoJ4LGjlIb0vD7wkfB41WdWrJBNdedSveNlkxtoVb3/MTpGoZ2AIphkhVAKBUjUFeYMgxPiMqjaEQAqkU0zPTfPWrX+Xw4cPoKGKYZdSRpAas9PTi4KQ4azFaMCETbhnfyETSwNmR4uJojAJvE7ZsuoZNG64hH9Twro73giLPiKMYpRVKvVmnwXuwC9EeQawinnj8cb7+D/8IhUFaj3YCbTyrai0i65lLgvfqpMApyYROybWgrz2DouD+++9n2bLlfPCDH8R7X7FgVqhQ4ZzCGegCWIoREyCcrc9GISRCWJRSWGtZsWIFt68+j2vUCjKTk7Q2cv+u59BecdHyVVyyciOdXpunp/cx5+CysVVcUECttRJfSHZM7mD/siZXXXw5Lz33KEeHPaZaYyTCcOlV13PVzXfx1OOPMJsZCi0Zv2gLF11+MTWdsmndxTz54FdpdzJu/chPs/byrRTDTdxw3SV8579+i0MHDiCtDeVwUmKsZWx8nB//sY9xx+23ct8/3sue3a+glCTHgtQhDeAhcuEVG4ht+F14KGQNMyrqEx68Bgxr166l3Zlj3/49bFihuPmqD/PdV1fQ7x3mgq2b+aX//tN89b98lT2vzIEoML5ASoexBRDjvefSSy7lf/r855ieOsxXvvRH9Dt9lNSoAmQZjs+0JymgaSUTRnPd+vPpdeaZ68xBGpd3SRP0mB06zin8ceY6HQ4deZVIOZwfECc1hFZ88ifuoZnW+dpX/vTN97qcpdcbDT7705/lhuuv4lv/7V72vfoqqUqwmWEibnJNfQ2TM4eZTArqHQuZZ1k8xvvUah7tHWJIhlQRg8GAP/zD/5tf+OyneOw7TzDXG/xLfWwrVKhQ4V3jtDsAzvvFvLpcZAI8W8OjYeYmsdYCMDc3xysn+qxcdSFTgw6P9w7RTDWXNlchRMS3d2/nvKTJR9U6JgeTbK2Psw7PM2/s4cLl57G6uYxdsWTZqglef2yaoYZMwPj4OO1swM7XX2XF+vXsftFhlWTz5RdzxXuv52/+7K+Y7jrOv/Jy/uHv7+Pw/ffxC1t+ma995U8Rh/ez/P9n773D7LrKe//PKnvvU6aoy7Itq9iybAvcKza4gI3BxqaHDgHChYQQUkl4bhIguTdcUknIL5fcUFIIEAhgExfcbcm9yEWyJFvd6pqRNHPmlF3Weu8fa58zI2GuDUj8JJhXj56Rzpy99urv9+3tiJoLznwqisgLj1KKkX0jXHfd9Sg8M6ZPJ45jcDneaLwC44XIK4zAoK1w4ty5TNEJlUKBK7ijsZq0aOPJEQyKPvCWWmUmhgFOWHA+R0+bTyfNGRycylBzJ51O2quQ6FxBFEc41URrcHkpCWvFuvXr+OyffZYPfOCd2CgO5hYJERKeYIqIXYiDOE5qXDpjHsO7hljR2ooftIgaQ2FAaqWfQgw6odkQjl9yBsfPfTVj+/bx9Lqvs2V4HdV6haJwZFlW+ugrvBDAgxpf71azxTe+/nWGh7ZxzFGzA5gqCgb6pzKv6OMlrSpJPEguGS3VZGGWsNgNMj+q0Mj6WFWP2ZS1kcgyPDyEtYZKksBYe7JC9CRN0iQdMXTQAcDEwK8uHa7M//lIRNibOEb6DMPeszlS9MeaPhUzMrSPYZ0h0uJMmcYsiWGkw5ZsjC1JzsjYFloVx95KTEsXIBajYWrHofIRtoyu5ZyTzmDr9i3kWoiUYt7UGay49R5GNjzHrNMvZM+mZ6l44Zj+qbhde8m27mJGJuiRJrW4QsMXqHqMUmC0QSlNp9Mmy3Lq/TXyvCDSqheWODFArcgyhnbuouM1VWcQV5BFESgDqsu8FNoKebGPxScuYM2KLTy+8h4G+l9BqzNCVnie27KT3/3dT1KNDNCH0THKQeEdiYoARVF4jDW0O228CxqWoiioxQmdZockjnAKcgWiFc7ASKeFtpZ6lLCzaEIEoEMUAKbUNDTYsmuYnbvX0h6tc+H5FzNr9nSeG1pL2ulw3XXXYQAtHq00RiscCnC9mdDG0Ol0guMkgFEoZRCtsNYSKU1sLZnO0MYQaUusLVVlSKIYR4oqI1viOMYVATxOMv9JmqRJOpLokGQC5IBMgEcadQykFU1mFYWBPZFnd1wwa2AaCxuKo02NdZWUSpqT6IgxBY2qZ4vtMCyavLWP1q4hFs48nr4sJ/EOl3dI6gl2oMKO5jBzTpjLwIwB6rWYzc+sxvqcY+bNYfOW9SjJ6K/FxAa09mSSofsSRlWOi4O2QgRQijzPMdaAgko1psjzsAReSifAAAScgsxoXDXG9VVo1wz5QBWshm7GAxXU7M6n7B0ZQpuc7Ts3Uql7Rjqb2LprHSqKOProRXzm059lyZLFKDKKbIxIRyS2hpeCPM+xUbDDR9aitMa5vNQACPUooZKD9QqnhULBRptyU2MDI1MSlsyey4CPsBKFyAR86axYoMqY/TzLqdYs9f6IZrMRGHcUcdVVV/GB978frQ3eeZyT0idFE9kIYwziPbaSgFZgNE4rCiWMtlusaw6zUjd4Jh9hXWcvO3XKymwPT8dNVjLKU53dbCka+CSMb86co/EitFotJhHAJE3SJB1JZD71qU996mA2+PDDD/Hwww+W/1NEkaV4Hq/sn46EJKmQZWnvPQeT4kwwNmJ70WTEZZBmdFxOtb/O/MGZ1G3MstY2RtMUVUnYrVO2qgZ5YqCoEpkOOsu59MLLWb3mEfYVDm08rbxgYMosTjtxEfmODeSNJlFc5anHH6d/oA8TR6x//F5s5um0FUfPPZaTFx9D2hxh165hXM1QiA/e/FqTZjlz5hzN61//ek456SRqlSpLTjmZ9evWkqUFxpfOmCqYDnLlGW6PMdQeY0/eYlenQdtkeC2ITkH5EBaoPO2msHdomLPPPp2BgTqr1t7HWL6LwvejVD8f/fUP0R7byaoVK/HOo7Ahxl4c1iY4rzj99DN461vfwuBAjSWnnIwvHBvXbwoRAEaROEXkFYVWjFhHu2IYHhmmGieIEvalBWIsqBRUikLwLmb+3CWcd86lLJh/AmvXPs2u3WtJfQeHcMYZZ/COt72d73/3u4gLgX9iwHtBiZBlBdNnzuaaa69hyUtOZsq0fk5YdAKbtzxHs53RQtjhmuxzHTIlNKzQrmqG8xZb01GaVcNeleNEM6Xez//8k09x/Xf/k42bN5VR/xpRqvsv6CVImqRJmqSfFzr33PM499zz///uxk9Nh8YJcD+h/8i7/NrG82RjG6OxoBJLMpKyR3W4p/Ec1WZOX6EY7lcUg4bH8iHEehoqx5iIihJM4Vi9bi1PLdnCJW+6hq//+/VIO2PAC8/edhfrfMGAH0UUPLzrNvqtJhse5oHvXc8047BFRLFvhBu+8hV01CCWlMREpLnDaoMWcF6oJgm7du7ka//2b+AdkTG4IsUq0GJLuV4hSoKkLYJKNAXQdA6DwhCXWf+KXrpDkRznR9kxNMatd6whzzOiJMWpgjixLFw4n53bd7Jy5WqyPCeKKnRyQRuDYPDeoxQ8vvxRnnj8Ebx0MMpjMGhjaCUGLz44/2VCrsEqhctzRmJ4qLGVgRysreGkAJ0GDYDkKKvZ/NxanntuI+BQKgVJ8Xhmz5xNvV7j3vvuo5WmeFegzHiGQpGgkRge2s2/f+1roHNEciKrydOcxNbIjZDrnEQLVa/IFLS9o201uRYSAeOEvr4ar33NlSy7dxmPPPoY3hM0CtDzPzgS9/4kTdIk/eLQoXECLNX+WndDAo+sdMDNqgLlsChUlkLV4gRwnrGKYVQLnhBC58oZnCJ1yEDFLbSyFGNtbr7+Pznl5JNRypCZGCiwjIKBMRMetJJBDgZIFBS+QmEA2UNdE7LvErzhk+A918v6J84RaUonNxXC3HREASXvGZ/zwNtVLymD1sEiXhDC+RQ2ZMRVGUYp0GO48vWqAm3nieNpVJOC+XMtf/G5P+XZZ58FquQO0GGNFVGZdycLLxYwWJByKBr6OiECoBMJnQigoJbT+74YxYgBKL3qJQaJw2iUx9tGb1zee6LYQu6YNjiFLRs38bV//ldyX4AtvVG8oEt5HDxGl+kBPUCE5GC1wXkfeLgIaQQpIU9B3wSvlhxHVVuqONY9s5KnnnoK58Fj0OhgUwv2mTJl8iRN0iRN0uFJh8QJsEtyBGQCfD4ypZNYJYpRWuMLF0LIXsSz4j2590RRRKs5xiOPPHLI+3uoyXtB6+DE12q1g6OdOcQRpC+SJkaYrF69hjVr1mBtdMjfOzY2xuOPL8c5TxzHKOWPKJA7SZM0SZN0SDMBwuGfCfD5yDlHtVoNArMXoih+4Yd6FJzOiqLA9RLZHNnUrecg4imKvAQD+Qs/+DMgpSgTOdng4CeQpukLP3gQ3isSogCyLCv9XI78tZ6kSZqkXxw6xJkApZe17kgiay3GGq666ipOP+MMWq0mRr84da7WJhSjMYZKJcG5nw/JMMuyMluiIYoivD88xtQDmGX+CWst1h561bvIuHnLGIO1lkmb/yRN0iQdSXTwqwEyMfRvf23A4Umhr10/Ba0VWZZx1VVXM3PGDHbt2kkUxb3kRi/YWplW2HtHnhcYY46AOXhhiiJbhh8K7XaLJPlxtCKHlrpZEYPmJX/Ra/XTkirDMOHIDHedpEmapF9sOiTlgCem/+3GYB/OFPobmEaW5TjnOOqo2azfsJHt27cH9e6L5OHdAkg/b9JgWM+wjiFt8s+Gyb4YEpFS/S9lauefzX6bzP8/SZM0SUcyHXInwC4gONypKApqtTpFkWOTBISeNBnF8RHnx3BoaZLpTdIkTdIkHel08F25j7CwP+8Fay0iQlEUDA5O4fwLX4aI8NxzzwEK50KZ2yNlTJM0SZM0SZM0SS9EP4NywIe3BkBrjXNFT43caIyybNlSlNbMnTsXa2xIK/szsitP0iRN0iRN0iT9LOigawAmOgGqCQ52hzOF+vVCp9PG2ojRkVGKLCOOY0QJnbRNrVbHTfB8//HyvD0fAHq+p+VHfl5WV8BP+LUqS/eOP+OApGzGvci+TQQ26oCf46TxE4oLqd6n4+WGBCXdHHjdyA+Z0PuQIhfpPiuIdmXJItCiURLwqCiPICgUxpfVA5VgvCI3gimn06mQ4Gjc5VTQIoDBlTmQlYTPRUnvXQfSxNEqUWEcyiOqnBvpZhNUKEK9BIEwnhdscSJ15+OAdVahZsP4sy+0s7pzG+Y1xKuqXi2H/3cfDuzngd87EOhKaFfU+Pe786HKGhLdcy4HyhPja71/ewKiEdX9PNSmnni6frit52lJ9ZJX8vxnbGIfuu35sq9qv/+jyooYKuyZiY/3Vka6rewf2dS97cbf1/3rD/js+QfkFSiVl3vPIMqVZ8agKMraHjFOC6p33ieWXAt1POR55+3536tE9VoQdcD6lD8V3XUqT7Qan4fxZ8NPM6GJcdmvu0f2b/nFkxzw007Y5y70RxRaNGFlfJi7sk+hFLrBq/Eba3zdQ7vd//6om/fnnQ6+CWCCzV9pVTplHd4mga7TnjG2zGYXKufFURzCvOIYVzIRGD8AL5bUD10W5acTz3CPkZbf3u+wCUp8uFKUx2uHEgO+htItkCikntUdpOgjHIb0xYEA5Rjf/hMud+j9W+HRFIgCh0WUwmPC78SjQwLg0AeJUDjGiwuBoPHokJQfE+5/5fDK4XW4+LSLMT606XVBoXOUaKwHp6FQUHHQikHnoYe5UcQuXKCihMg7IhG8aHIT4TFEIigcgsfr7kx3r+xwSetyzZUotNcY0aA8TvtxwCMWLZQjcRRa4dC9MY4vcPdy1vt/1GMafgKIU731trhyvicsfnc9VJfJlsmoVDdHow77QLqJj3JUD6jZ/YBYmPOJ71SEUsu9q7xsY+L7uv3Py3dZEBveiUJKBic67CEjXTR24DjK8XcBgzgQiydC8OF5leOVBzEIERpVgrn9SZXlpMdHNpH9jl/0+4sgACZ0AR32s0gPGIYHBKfAaYNxgaGViTdxumRyPvztgo7uunoVQOd+4oEoVA8uqAnfV/sxISVhHxs9hnUG5WNEZwgKLxWMyjDeo30/hc5B5aHt7l5RLoAn1UEwCDG6t6bPAzwkhMgaKUJKcaXxqP32ZNjZHoVHiaYgVOv0JeAy0gWsCtfbolIy3PEk2N1CZN0+ePWjIPiBNGEVu3tdTHiRWEJhsBynyuybXqG9xekCp3O8DvtXeYX1tnc/dJdal3MX+hNKhXvhFzJv5yFJ57Y/wz+8TQDPR3CErOwAACAASURBVFprnnzySd7xjnciItx0001lfvufDiMeOAvjlzL0pDjK7S8HPKfGMxFqCcg8XCTdy7g88Gpconnx9GKkzq6UObH5UPCme816pfYfjxpnLoIDCf0MeN2DFGXVwlIaUeFm76J3ELyWcAFrcCbUNZCy3DG995WgAo1T4ULWZRFglKDEYZAJjpzd2SollPAwogRfpjQWBV4HWBPa14iAlyjs7+5qTNBo7E+ltK8mSoIAOmgtFMhEjUnJVH+YaU5kxl0mGsDAxD0zzhK7C9TVooTPveq+aSLY8wcse0/W3X88YkuGE/aXHLBVupofr9yENe+2N4EZKR/eOXHuVJmCWhRaSQAzkiCqwKsCNQGcdYH3RIE1N88z9QdS2YWJs9ubj/0YH0QO7AQm75WUsCp0N9cQuQjtddmgDxKEmrg2bgIPGz8zZa7t8V6UvzNiUL4L5MbvAN0VCBR4lROk/+c5qaJQlM/2ANiPkGl7Wq0SoCsDSgNR2Q4ESTuMpdCCKyfc+MD8I9fbtQFEdMGSCn0WyvVSar8eHLCrfjT1VA0wfna6gGfiPp8AtHuCzIFjD0B5/xcfCNpfTKd+PumQOAF26UjMAggBwCxduozHHlteOgYOMDo6+hOnv5X/h6uFelHzM878e6piKTd6ieh7jEIV5WcvduInHJgfutm7B0UQ6UoJvSu097sesyNI6uFiHb/oxsFCgRJdSneupz0IF0bZ2oQuiPI96SsUNOoymlLyVKFPIgYrIfd+pgPS1xLUgV3VshZB9zB+yZS76XvVuCowfKbxqqtZUGVq/9Cu8QpFPK7l6M1Fl9HLAYs6ke1MmJP9eO/EioETpXEO+LcPTKCnpemChvFLUkotQ1l5oQQwaoI2dhyw7Q8uJu7R/a9t5SvsD0YmVvcMmh0FeD2eDTFc9lLuhXGkGzBeCarQJdMJ6xLu9hjlI5xxvf023l/KtR3nt4WeyCDUD+36AK4ESg1aD5p016gXMhokWOu7Em7ZaqluKEyYUafBeI3GUqLGEkC6Ces+0aQxfr5UF91OQNECmHIOlNietkBJ0Pp197sy7WCG64KE/bR7GiQJWrrunbDfHpzI8LrAVAgQ0U+4n7rAkB7YKlSOlOY3KxLAURdDqHFAlnXPKePgpQsEfnxHsy5TTwmzbhjf60X5WbevXWCag9L03ibdPdc9mxPGf5ibpH+WdEjCANVEyU8mbosjg5xz9PX1AZSJgUL625+WxuWrH8Wcn1+a7KqhAwvzGFGI6HKGu8zel4z/x0xJeyDTf551EsApU369q+KTUqqaaF+beLa60m35HemqCF3ZjqAIpY2Dkl5ThMQRqPI53X25CoxXAOvH32d8V7IEJCgtMyNocdSKADAKHXQOAXhQXktd+6bvXYT0fAR8UH+qCF0q/FVX7YpCKYuWoE7u9UR1L/lu9aYuAxYggv2Ax/jydIFRWIPuNdmVHp/PN0PQZIiKQGJEJgCA/Zh5eTH2bLe9N9HdNd2CRfuT3v/57qdiA6NQAHnPN6LHQ1FoUfguU6Q7l+VOn2AWkfKP6sq3KkjMiizI2apAqzyskXRXq8uwA+DbDwSUrY3DjQPP2fjpodszFbRV3d3Q8w5QCrTCie8xLiOlfduHKfEQqlPSmbA2z3OGpHsyJkjBPoy3Cw26JoTIdxAxeLHlOH25VwNzDtqoVmC+rhJU1xNMT0E7EqFUWBvf21MTN9qBoHK8dHUg15OiNYJSLsytsigURgQTcA1e0wPIXu3XZKnZGgcHmiA8qAnfeWHqnqeyTz4GKVmVKsJel67mwoTvkRO0GBYRTylmlCCi+73uGTkQ9D7/vfuLQIcgE+DEREAhh/zhzfylTOgSmFcUWZRSeO97iWXSNEXrn2wMAhSiEG1Q2vSS6HjvUHhcnhKV2sQ0y0q/CYVRYHV5SSnInOBNhHcFiTGlGaBAk+BFo7RB6xh8sM6LdygVxhWiHFzvQhz/68t1MuS5K3P8u3LNxr+jtAYT4ZTCe0G8JzLBlireIeJAwmGPRaEKjxUV7hNPuDEcxMpA4XAi5FoonKCUCVeOjcgUENnyUhLECVZbcBApi9aWmkmQPNj3YrHgghRjMYiJyWyFzAYVplaOjJxCKZSOSfMcXzIOazRGKxbMn8fZZ56JAqIkIktHidQYMW0q2qPzFiobJdFNtBulpnMiycDlGCXkWQeNKsdJADUqvBvJUXqcGSKgfLABawlWYy0Oox1Wh/l0RUYSG7QKsCiOdFjzKMYXOVqlWHyQVssah9aC9ylKhaqQXgSjNK7waBUh3uIKjTEJCovBIM5jlMUVglYRWlkoJVtNhDgwOkKhg5nG+8CQJZjCvDi8OCIjiGtjVY4mAYnIc9A6QmsLaIoCvDOIM4i3AbQqXZ6vAnQbbcaI4jHieBT0ENp3sF71VPFOKzLlyTW4yJBaSC2lFimQMRFeKQoJZjxfVnfUIqXmrHQGVRLOmTHl+Qd8OHe58uSRpmU9bSvkppTSPUS+ZIJ6FDG7MMkINmkhNHGS0mMgpa9EXO0nywWtYnAG5UJlTJc5rIkpITAV3UYVLmjljcf5HPEZiSq/rwTiPPgDYEvFXIHgEClQOCKVoHyGJiW2Bu9ytAKlHEZ3zSsOo8NbnWi8xIjYEp8VwYdINUDvxcYjiNqNocC6cc2IV5Aa6MSKTgSFCR42RgSKYA4RBGV0iWsVeVEQlaHWxpiybkYQtKy1vToj3eixsHcitAlAxNoYV3T5iMMY8F6FfSoa5xwmKgCPMXEQ1pQGLKbrnag0s2bN5qwzzySOLc4VAeB4sDZGKdMreCbiQ7XUI1F9/WOS+dSnPvWpg9nggw89yEMPPQAEABBFUW/BDx4JSVIhy7pFX346gBFSAIdrxNoI58bVa9187z8pKRWYv/cOAaZNncrsWTOpJAntVpMkioLyUhtstQ7icXmGUeDyHFRE7qA+OI2s8Mw/ajpje3agdQJak7vgTe2Vo9PMqNYSpFBoGw6VcwVJkiBlrvwDx6JUOECDg1Not9skSUKeZ1hret8vvCf3UKnU8M5xzDFzGN69m9gGVJ1050zAKE21UsWjyAtPVKmjdUQcxfjCBx1GvULLF8Q2wjvBaUvTwfRj5nLNG69laPc2GnuGiG0Fk9TIXXiukaZIDjquYOMEa2JcuT4211x+zZu45n3vQbRi55rViBQw2A+mSmcsJ6onxFGECLTbLebNO46PfPjD3PiDmxlrNqj31/niP/w1FVp85EMf4d577kPjmHvsDPqqMHv6IC7NyVoZ1XqFdtEmSWIUiiiy2EhjreZNb7qGSy57OQ8//ABOTFDvlirqAO4UR82ezq988H2sXbuKTrtBlnviWIHyDAzW+LWP/jd27tzOpk2bmD59Ou9+93v48Ic/yMzpimef2UDa0YhXOJ+BznCSorQAllhrKHKqlWoAdMYSJwlFmoLLkSKjXokpCk+lUsNoQ555KpVKCRbDRZ4XgYkkJdijaxZBsNZQq8acuGg+Lz3lBHbtfI6RMUUSx0SRpSgyvHPl3CRYHWFtjNEG73OsNvgix5iCd7z99Vx8ydkcN38mp516EmvXr8bnBiUxUNrACdI5CHmeUYmSIF/naQC5Iog1oCwCpHnGlIF+3v32t/PG11/LXXfdHaTTUmB3IhR5jvKKSBtU4YnQREqTiSMzKpifRLDo0ss9SPXv+eXX8NqrL2DatCnMm3csu4eHydKC4Ghow080zU5KnFSwxuDzglqlQrvVpFqt0MkyvBYuvuxirnzZEp564llUXKeZjzA4EGF8Qdp0LFi4mE/+ySe5+PLT2bluPaN7YgIed+Q+I7KAd0RS56KLTmHhiUezbccevMvxPiPttDEm5DLRZclwrTVaJSXz79qGClApb37zVVz7ukuZM6fGJZeezaOPbUA7gy3LkBcWskjR9AXGWiIHiQtmjFgbImvx3lOUYdNKwUB/Px/91V9jpDHC9h07GBwcDGtYqRJFlt///T8AYPXqVfT19fGrv/rrfOITv8fCE2Zy3/33kGcR1Xga73zn2/irz/8pp53+Eh55aCUjYy2SuM61V13J+97/Bh566Cn2jnSo91f5rd/8Xf7w9/+YCy54Cfc/+BiddsaUKQNcdtklbNu6hUZjNOwnrSmcJ88LtBaiEpCkaUYU/ejcL+eeex7nnnv+T8wXDhc6+HkA1Lga+MjIBDjO4Lv9PdjkBWbMmsPHP/5bXHPttZx/wfksWrSIShIj3lHkKc4VNBoNhFBcRrwjiiJQgjaG0cYYlf4BPvyRD7HwuKPROERyoqiGMkE6rtenUOQOoyNK8yFaa/I8D6j8ebQYIgH0jIw0sDaANa1DNcM4iUizNnEcgY7IndDXP8D7f/n9nLBwAeIdiMM7hxdB2xDC1Eo7ZF7Q1TrNwtMWzWihaOuYjokYFU1WrdFSERLXyFWMrvazp93m/iceY2h0L9VqQkc0O1s5RaWfloqRvqlI3Ifun8rVb3s3UhlgzCmUDnbJG2++lf+6625GxaNtjFea0bxgb+agOkBbKRpFQa4VfVOm8dqrrmHpsnsZHh4utT6OHTu2MzraoDXWxuqYyMbMnzeXyy+/hLe/402ceeZLiSNLqzmC1TnW5HjfocjbSFGQdVosf+wR7r93KeJDCFc3jGpc65LjJSWKHJFJMapNJRaKvIk1Oc3Gbu6842ZG9u1msL9Oq9HkH//3P/K5P/ssImPg21jliIwisopOZ5Q48Sjj0NrjizaJyaBogLQQ3yRLR7A2I44cic0gH8XgKLKULG1hVE6RjwUpU6fEcUYSZxjTRlwDpVIUDoXBe01RCO12k3rdECcd8nyYvlqEuBRxbWLjsDonsgUuG8MXHbL2GD5vkRiH5E2SSEAy9u3bzVizwchIg6iS0E4dXk30e1FYL1Scoq/QzJSEGbll6ljQRBmty3weghNB6WBLTzspDz/0ILfcfCP7q37D3Z/YmFhZbKGoiGHQWeZmMdNTQ82XhihrcBO81xXCyMgIY80GY81R4jhhz/AeVM9GTe89UaJB5aT5GErnFHmDetXgXIsocWiTUfgWiRlD48jzNpWqZqw5DL6gXo3ZsOE5fvN3fpsVa5aDT3EdjzhPJ21gI0FUirUFedoBaWJNi7HR3SSxI4o8/f0xWhVUYoNWHqNCrID3EkweE64EBTSbDUZHR9m7dx9jjcZ4xAOUUUDhb6wNtUyY2dbMzRNqOZjMoVKHRRObriZVGB1rkFQTvA+ls4eHh/FeaLfbANx0002sWbOaOE7Isoy/+au/54/+8NPlfES9Pddqd/jMZ/6Y3/u932bnjl1YG9Pp5Kx8+mluuPF7ZHmHenWAZrPN5z73F7zlLW9nbGxvEHK8sH3bdlavXsWb3/JGotiESqLOk8QVqtVaz1jTE5p+AXK/HIIogC5DPZyZ/v60v1R8cPsdPMoVU6dOY/Hik/jLv/hfrF2zGqOhEluuufZ1PLF8OZue286C+Qu48MLzuOn665g3dwHXXHMNqYOlDz7Go0+u4rVXX8OJLzmJX3rrGxhrRdx4x+2s3dBk9szZXH3tldTiQR66/06eeHQVV191BbX+CnmeoxQ0my1uvfVWnJuojVGIg6RS5cpXX8JJJy+m2Wzw5S9/ib7+Oueffz633XYrfQODvPycl7Ns6T1ce+21nHrqqbz/l9/Hzh3buP/++1n++JMoFTIFFAjeanKlOHbhQvqnTmfGrFkkUcztt9yKNYZjFx5LoR1nLljEyOZtPPb4UwzMms0ZF11Ac3SI9asex+cptRlHc8z8RdTrdebOPIoHVz3JvvVbOPOiVzB78Slc9BqhkY6y6bH7SDc12Jt7Wh5ia8k9aBsz76RTqNePZuHUuahKm6W33UFr7x6OmjmdganTue+b30ArjRNFljm+//0b2blxLa3W7QztbSFaWPbgIzTzRYw0Gix74D5yV6VvoMqZ57+Ueccdz1gj5e67lzG0ew8XveICTjxxAcsffwitFa57c47POAqHSIZWKWeecRKzZr+CVc/s4JFHHmbmrOlcdtnFjDWbrF//LNZqOrkPKmPxON8M9lklRJHljNNP4ZwLXsKzm1azbNkj7NubcvEFZzJrUDN7zrE8u2krdy27j7QoeNkFL+MlixeRt0ZpN0f4wZ2PkDnF1VddQ6Uas2LlkzzxxHJOOH4es2fPYM6cOURxxG3X3caefWNAHaViFAZjPFoViKQ4L9g45ZSTTmCgv85Dj9xHHGsuufSVDPQNsGLFah5fvpLCe2r1PtJ8FGssCk9sNWtWP8umTZZGo8HmTftwroaXqOeKr1FEXpEUgm3lLJh+FDOrfewc2sKqqMCJoE2CUiFqI2T3jLnoogs567QlLH/owfGzXfoSdKMKIjSRQCSaObaP0+wgD+xci8IyWtfk3vU0B6IEpxQrnnqW5zZqdu9uENsRtKrjfVfyh24+BqVTqrUqr7rkVcyeMpX1z6zhwQcfADIWn3wSZ51/NkfNPRqz4X6U5AxOrXLhlRcxbSBi/eOrefS+Z9B2ACcKr7PSU8aS+w7TZk7hyqtfjTWeFcufZM3yfUCLGTOn8K73vJlOmnL3XUtpjLawkWHJKSdjTMyjjy4PdTzK0M2ux0bQUsWsfWYrO7ZsZ+/QdrZvGsaVfhdd2UGUYERRFUv/SIeToukc1zeNe0Y30VCeTDwGhSs1RtoYEA9G84qLL+bK176GtWvXceONN9DfP8B73vNu9u0bYfv2baEnXojjCmmakxcped5B6ymlxkIwVsiLFBsNYuKEK175ak4/+ThWrLke5x2BZ2u8h77+QUq7HEgwjT3++HLe+uY3sGD+fJ5duwGtLNVqjYte8QqefuoxNm/e2BOarO1GQ/z80iHJBDgRCR/uGoADtfuhqwevv93iNE+vWsXTq1bx5S9/lXe+850MDAxSOMec2Ufx2iuvpHA5r3zV5UydOpW+/j4+8P4P8K3/+DZ/94UvcM899zDWanH7HXezbtUqrvvut/mHf/h7Nm3cQLVa5YMf/CB3330PX/qnf+Ztb3sHJ5+8hFe/+koWLlzA6153NXGcsGTJKQwODvzQYCuVhHe9611ceOFFfP7zf0scJ/zRH/0hC+Yv4PLLX0mjMUq1VuPsc87Be/judd9jzerVfPkrX+KrX/kKTz3xBCBEscUpT248qRFa2nHSuWdx6kUv476nnmKfFxaddTajSvGyK67gvEtfxU133MWJS07j2IWL2Da0h5vvvBNbrXDM3GODp3+9xmVvfAOuWuOxtetYfP55NLTmB0uX8fAza/je7XfwvdtvY+2GtTTHmtgogaiC2BgdxeTOM3/xKVzwyit46PGnkChh8UtfijcRcxcuZPfuYZqtNkUhiGjGGk0eXf40O4ZbPLR8JRlVTDJAK4NGmqErNSRKEB2zcNFC+uoR//HNf+W6732bxsheqhXL3XfcydpnnuGlS5YQWYM2ZoL0WO4t5YGcadP6mDGrn1tuuY2rXns5xx47iw3rn+U73/kGg/0VrIlAPNYYIhuRZylG5WjlSDsdjp4zm8bYCP/yr/+I822uuOISlIErX3sJAwOOr371f/PKV53NrKP6uOD8l3D5q87jP775r5x22nx279qAK5q8+oqXs3TpLdx++/W8771vYtasfhYeP4e3v/NqHnz4Tqr1jPPOPQWtc8ATRQlgyTPw3uN9Sl9fzmteey5nnX4iDz90B3uGtvChD76Vdc8u5z+++SUuueRMTjrxaGbPqNJuDVGvCVP6Y9L2KFna4aknV7NixQa2bG3w+BNbUXIUKukjtwqng1wWO6ilwjG2zuyWYm4nYl4ror/WD4DvFYIa97O58847eW7zZo6bOxc5IHzRe0+RphTtFDJH3VSYrhIWNBQLiypTUoWMtinSLHxfQa4VhYEVKzfz2MMb2LGlw9pndmHopxIPAqZ0pCtAZThaLHnpQp5a+SBf/ucv8JZfei3zFkznrHNO5JfedhX/8m//xN3LbsfaHGvgrHNPZ9m9d3HLrTfzpjddy8IF88AL2ljSvI1SGXEUgM75F5zD9d//DvcsvYPLr7iEGTOmIL7DKafM57bb/otWc4Rzzz4NrQq867Dk5JNYcvIpGBU0JkIBKg+RMijAID5h1YpNLH94HcM7PE8/uZPUKZwKobg9h780R4+0mKf7mN+OWNCJOao2wEBSxQoYNBaFy3MKXxBFMTNmzgQFn//833LFFVewZMkS9uzZw9e+9u9EkaVarWKMxXlPs9VGa0W9XiNJYjrtlE6n9LVB0CY4qY6ONLj5ppu56+7bOfvsU4msJstCBVZXFIyOjOJ8QZ7nJEkVrRRDQ0Ns3bqF0884E601WZFRrda55OKLmTt3LnmW45zv+SX8vNOhzQSoFFof3iWBu2r/bh9VL3zt4IAA8SF0q2IjvvD5v+X673yH11z5aj75B/+dv/vbz3PDzbfz/l9+Hxecew5nLz6az/z5X9NIPfc9sYpLLr+Cfbt3sG79Zh54YjXNRou2NzScItUeXEE1yTl6zizOOPV0lixSbN68lShOGG00WLp0KdVqlaefXsmiRScwDszGPaCTSsLikxbzr//yz4h4/v3fv87/+B9/ShQljI216e+fgtWGqtXknTGqfTWKwlEU0M6C5BUZQ+EcRoQEj1cRNRWxZ7Rgw85VDO/ezdObnuO8xYtZ9dQq2iMj3HHr97HtBg/eeSujIy2UK2i32iiTsKfRBlslsjEb163j3mX3cOyMozDikSynb/oAg9UavtPBoDC1fpxTeFJs0UEJjDmDTQZQSvPovXeya8dGdu+djzcxXivaaZsoVsGRUjxaKZSpkKc5hbFIoTC2Qpa3qSQWq4Uib4F3VJKYoZ17WbBgJhdccAZ5nrJ69XqGd4/SV6sT2xhfpLiihaIerP+l8Tl4oStEa3btHeb7P7iNsbFRNm7awIwZgwwMVkizFC8FtbphZF+G955OR0jiwfC8cZiqo5HtYvGCo5g7dzFHzaywY8c2EpuxacPTPPzoozhj2L55PbWkj7g/o9nayLxjBln/3Bp0nqBwbNr+BCctmUNfZYCRkdVUY49WLW694wds2raPNRu2cuqxc7GqQMhwRYbCok1Emnt0VOW0s85hypSYv//rb5FlI8yaVaNSheOPP4ZZM6eya8c2osiyZ3iYN7zxzagootMpWLr0PkZHW/T11wGFKyCJk1CES4oyQiBkfEyNotqfUBmYAaaK6p9KPRIw29BFkPyUdygpEIHEmGCq6RTMmDkbjJQmmeD4Z7XBVkI8fxQlVAanUk2mYsYi+qcJkexFFYK1Cp8HRqBLK0KlMhCyUnrBRhF54Sl86wBhQmN1TntsB8fPm8FJc2ezbevj1BPPFZedxy03fwcjDispqatgoxbtfas46+SjqSY1Gu0tuGgMZ/cSKU8f09FSJZNNVKuW3Tuf5dxzFpFENSrVFs32OpLkaO5d+hhDu5ts3zbEnDnHIGiUgq9/8xtBOpaQ8EyH1FM9UKpEo1Ak1ToGaBcFOu5HK4X2oL10/ViRikUnEXFtGjqrQ98gmg6+LRSNlByHR5HECc57Oq0Wu3buZOnSZYgI99x9N3OPncuKFStoNEYpiuAMCMFkWakIQkanpfF5HW2Eel3w5Iiv4PIYYz01naB8ROEh8w5lgq9RlreoxBHVagWTGMRqMh+qvCZxBQh+T7n3JLU6m7Zt5bd+57epZPuYWq/Rzj1eW5x0wXs3lVk3ydbhXd32x6GDP5IJ5YADqR+Ssg8v2l9DcbD7qpQiUhrJc7QI27Zs4zv/+V1q9QH6BqaxZdtunlzxDK++/FXcfsN/0BzZS6PjuP7m27n51jtQRcpVl11IgsMoaDvLzHnHI3FELoIyKfv27mbX9h088cQjXHfdDWx8bhNKjzs3dh0AQahUKlx++au49NJLUQryPGNo9y5OWXIyxhjOPvtstm/fQaPRYuqU6SRxnRMWLmLW1AGseKQIzozTZ81BRwmdXPAYkkqdV132Sl73yivQhaFSaLyPUGIxRcH02UfR3jNElDtq3tGfjxG1Rti5djWt4V3E3hOXcVYmqlB4jRFPVGRUvMfmKXWlSHwB7TbSGGXu9OnoPCcTkFqEIqVapFQ8ZFg6EqELoerbxL5JyI4XnBt37dxKrRYzONAXQpzEYMQSmRqeBNERWmmsUeAyqrFGuRwtHp859uwe5d6lD7N54zqmzaxx4uJjSBJN2skAU3o8qyDB9cKgSnCpDV5pcjE4bagPTmFwcJCRkdHSu15KiRa0UUSxRZcmZkUFURHeOE48ZQGDU6ps3vgMiXZUY3B5m8gYnCQ4VUM6CnEVKn0GV+zluGOO5sk1q1n11DqmTJnK5a+5mEZjLyN7RxkcUOjC4nJQqkqe13EMYo0gLicyUORtwJPlGUmlj6zQPPzoar717R9wycUvZ86cWRRFTmN0jH17G6xbu4m777qXDeu20F+fxvXX3863v3sH/3XTPYyMFYiOcWJwokFpnM9ROsPgsVL6fStIrTAkHVbu2crqzhBPtneybPc6hsda5KWDmpICI45YC0YJRe5wGLyKcbgydM6FCBmEQhwZnn15h3VD21kxtIUn82EeHtrExvZeWsbj1ISww/Lq916HyB40hTiU8SjdDaODEJdvUYXmlZdegsty9uzey/SpFZTP2bZ1M8fPn8+MKUdz+kvOBjuLKVMHueLSs+ns20NndIz+qVU60kLFDaTTIm5OxbsaonYzdZrh1Vdcwu6d22nsbVBJBB01STNPkddRqoZQxbmIwlnQMUteeiqnnn4aXnlcCZKUhKRUYWzBbOHFk4vH6WDGQ0IUhZHx5EipOPaS8tSerSxvbefxzi5WDm1ha3MfbR3ydQhS7n2oJgl5FjQpaZqy+KTF7Nm7l6IoqFSqGGN6ZmMRj5MWNvIYNUDWiYkig2MEbRxKqmhqCDlaHC53iNIU3ZTF3hNrjRQOrYVMcrCGzDtMFFGtVpk7GagX+AAAIABJREFU9zhWPb0KUGRFwcC0aVx19Ws4dfF8SMcwvgAvZVRJcOhUqDI3w+Grzf5J6JBmAhx3AjwUbzlYtD9AOfh9FdrtFuecfQ5/+Ed/VIa5aL74xS+ybt060jRlxcoVXHDWyTz51CqsjTnuqGP5yK99jPNOO5HRbRv58v/5ImhhZHSIW2+5lT/4+O+S5wX/5x//ifsfeIgbb7yBD33oI8yeNYdnnlnL3/3dF0jTDnmelzkMNK1Wqwd0LrzwIlqtJnfddTetVot//pev8olP/AHvfe97Wb9+PZ/4xB/QHBtjy5ZtfOtb32T16tXs2LGdOI5pt5vcdNMP+Ou/+iu279jOl770FZYtu4coirn45S9HA9+952GKTsZgvcLLLzybN152HvesWsP93/wmlaSf0aHdSFGQZx36k34K8Vx68UVc9JrXoK3i0jOXcM/3r+PZTduRTpuqFozPcWMN+hLL3sY+nn16Bb/y3nfRJufWG7/L0/c/yvs//BGmLlqEiatccsIpfOOb/8bYnt1UERKrSUf30J9Y+isJWzY/R6VS5cQTF3P/0J7gUNTOgnOQBEfMkb37mDdvNh/5yK9w/PEzMcYwb85ZfOUfv8Ox8+fyrve/AWubbNu1iYce/A77Gh3+9NN/ybFzj6FSzVh0yvF86Z+uZ/NzQ0z0thKvaIy2qSR9/M8/+Ry7dm/n+9++hbVrn+O8Cy7kve99F9ZGXPyKK/j+929m2dKH+dAHf42FC47DRNuZv+hS/vsf/yVDwx2uvPxqrnzVK9m0eQNPr36CgcFjGW0oirwGXtHJEpSusX3rTt529ZWcvCDGDMJdlYe44c6H2b6lw7vf+auko46VT92DYgCjptBqaMQl4Krs3t1C6Qp5ASKOKAYTxyidkucw1nA8/MBKBuL5XHX1L/H3/98/cPfdy3nDG17PMcfMZeP6HXzta9/iqSdWM2X6DPKfwLlKoIx68Qw3G2SdjGKi311J1hqKwuN9zt/8zec59dRTATj33FP5X3/+OZ5+eiX12iDNZgtrg5Nt1zYw2h5jTWeMViQQWZQv0N6FRD0/wb2QJFNZt3Y3b33r+8mbKQ/c/1/kRR833vgAv/7xj3PiyVfwyPJHGPCOoX0FW3ak/MqHfpMtW/awauUzQD/nnvUS3vnudzNQnc5l57+c2+64ga9/4zts2rSX3/j1T7Jz+wg7t69FqAKDOF8ndxAndbSJQ4gwhhMWnYTWhuWPr0AZg3j1opScXgcn5m4IvxVIVGCIOZ6hThPvPbl2PyROOudIkpg8D9VU/+Iv/hyF4tOf+Qz33XcvV1zxaj7+G79BFMe88Y1v5Hvf+x433HADH/vYxzjttNMwxnDiiYv59Kc/xcaNG0Op9jKcMEtTjjrqKD7xO5/krHNegqo+xymLLuP3fuuz7B0dQSlNXnRwheCKAsHjCscpS05j3959rF27nsI5okoVEcfLX3Exm/pg9bMbUNaEO7PTwkQJ4w6kh7Uk+xORkoNsoP/C3/8tX/jC53tq9Wq12vP2PFgk4hkYGAyhHMDBWJguaInjiDwvDqrfglYhfWyWhdCSNE2JogitNfPmzeOkk06iv6K5+5br2dkoSG0dpQ2RdIiLMcTluLiPtulHuZT+KJQu9j5480ZRHOLzJSBgpTUiecmwQ2ifc0Vw1PMeY4KdNE3TkNimDFMM8wABFOny/4JzHqU01hryPAcURZETRWFcadqhUqmgsg5xbNknVWIxnPG619Nuj/Lw3bcwYhSzCo8vFKqqML5FUnhsAZlEtG2FptaghJiUms9xEpNisNpgUGRaiFOHqsSkecZAUmNfa4SK8VRDxDKtKDgAxqkLccQJkKWYQpEmfSiXY32OcSlnn34q1159DV/96r+wecsOMBGegoIOVtfREqFUCoxgVFb6kPWRt6tU6gmp7MOYDrlvo8Si6AcXgxK8NMBkKOlHJCZIhd1URAXaeIQULxnWalxbo40iTjRFnuLF47ynEtcQH5GlnkoSo1STdh6hK1PJ0g6JzqhFGWnaQXSVnDqRdygRvO1HF/soTI0PfOwKNqx5iE2rt1GbFnPl+Vfzla/dzt7mPowYiranUh8la/bjTQaRpWAKhW8zU7fp5EKBxduYwkOBR3xOYhVKcpQUKAZC7gntKYoUNFgV4TwoEpSy4WKW/IXPo6gyvHXcA92goHDEXmEKIVaaRrI/H+veOyKqTLoDWmmEtIw1D9oZrWwvFXM3m1zkhFonoxUrOhWN0yH+PclDDHxuhNSqMiPkC5/7ZpYyZaCCzzOKVsrggKLVDIxSJwlOauSSUxPBF4KyGYXPMSbBSRvnamht8V7AWyLp4MmI4346+RjaApKgVYo4Dd6FkGOd4IoCXZ5zX4b+TQxvppRsX4hSE8ZeKcJc5FrIIo1Xgs2EeiokXjFaDWGTvebLe0TKcKRuCKK1ttcPpRTOuV5+AGN0T2CZyHC11kSR5U1vejNZlvLggw+yZctWFDG+qIBu4cxWtJ9OYmaQFvuYPWs2s2Ycwy//tyv5zJ99kb172/RVIt7yhmt49KEHePyJJ6nW++gUwrHzF/KuX3oLK++9hbuX3kuhIlKvkTKaJOh6golTELzSfPTXPsZHP/obL7wJDnM6xJkAx8MAD1c/AKX2l/oPthMggPPB894YHZKnxCF1al9/neNPWICNDMuWLWN0LMeYSsiVrwScA6VR1lL4AqXSkM/KK4oiHJoQVhYSVwTPVVMy+3C4jDGlCSDYM7tJjnyZhEMkVNHS2pSgx5cHUlMUIQNiSIoBWZb2MiIG00IYX1TG1psoIi3y/8veewVNdlx3nr+Tee8t83nX3ju0AxoE0A00Gt6QACkaSRRFShRjVxqtUUzsvszORmzExr7Nw86MZmekCM0+rDTiclajkShKBClSggfhG66BhutGe+/781/VvZm5D5m3qtqAapBfA2wifxHVXV+Za/LeynPy5Mn/IckEl8OxfbspimlSm9ObCElRIKQ0phqoDEyzQSWtoIwloaDqEkRAWwMmJ1GJzwpWgjW+469ooTEzRQYUM5N0Jwopcv8jVZDmXimxkihwDin8uWZJis1nSJQDV1BNU959+13qlW7q3T2o5AzNwqJTjXc3LNYZL6ykMy+FbIVEqn7qo2koRJFWe8gnvFiJuATrNFqFQi4qxZmLFSQVErTWTWHQSYIrQOkUsDSboaKjOKqVhEYzR4lDpynNwgIZOu1mbLJBtVLFOaHRBJEUQ0KzEERXfL6ES2j4LAl+/MNn2LRxOStWj5BWLH/3wycYHc8x1s+JihKKooHoOkpp8iKowolmeiYBrVs546JBrCVLMx/mlRQlUNgqgqPZmKJS6aYwXoTJiUKJpjAOdaEG8k/F14hoyzQbnE9Hz1Ka001fG+bi74i0HF3fDZWZ/ypU/RSKoqxZAK2VAc7L/Y53afJQE0I5UIUNxXXATwJc+XCju2uA6cYMCRkqSZhuGqyCJNXkBT67XypMGZ+DoqhgpYmX1HAolXnFT2tJdEphCpROmM4NSdbDzMw0aVrBWY1zgk4SwJAXBVlWxTmHsQ5n/fSKKL9Cwv+er+wsbFgpaMOZayfowhfWcqmioaGZtwttlbigAy+qlNKW0PZF6zoBLf2VPM/Jsi6ca7b6n/aybEej0eS9995j/fr1XHfddZw4cTKIl3nlQy0pCDTzaSrVjOUrlrFo4XKee24701M+d6er1s2bb77JvgMHqVar/lissHL5Mra//DJvbn+D3DhIvAKsCXdXOX13SRXPXwJmPwLwx/+eP/rjfw/4RqzV6kxPT81qaP1qRADClr2oTJIyMT5OV3dXSxnPGPMzOzGlA3RxVUQRcDaoklmLdlBI6guAKkHZpldYE2g6MJIiTvuQZBDkLjs6EYftyFoV/OqD9v6kvc8LXuvo3FzoNIMUZ+dnlVIURbmvziRJvw0JRXecsxS6iioyZjKAJqltUOiCalPQUqGBn59LbI7GYVxCrlIKyRBxKNtAuwYiFZwVlEq8kqETLBZpifp6hTNl/bXxa8cV1oVTsI4EX4DGiZczFvHGSxNOQUJVPzRONNYVoJq+8l2QGZWguqYk8dXaTIbTDisNRILKoihKeV6l8AptqgjasUI7AlD+HSIBQXHM76+UEwzLyC5wTkNExgmFJBQq8bnbriAxDbRSFKJoSIbCklgHLsWoGXAZokYRyRGTkuoCl1ewqhuDN3BeKHkUcXWQAovFuiqogqxIvG68tljl3/Mj6wSMBF18hRHAWYwtSFLB2vb54XzZKBF1RfOoZcW8MgpQZqA759Dicys0lxPV9lN6nbMMLbnhkODrWjLInb9nP6rNdXvpoTaWrBCSMEuQa2ioICx7BREAExxYpRzaGVxIpMOBFR30IbxIlAvFeSTISPvEUVrH6b9WBBVGr6BZnrygvQ6HIuh/tH4AQKm4CH6OXVrJlVfCTOI3Vy2ELJRDz5UjF/FGX0CsI7mMQ9FWWFUtQ965QsxfK39m1nqj76ON7YFK2WdK+WMI/Y9/T+NshqgCJ+HedRki3nQ7q5BkEuMqQIpyRZAmtpRRTovvF7SzZBQ460f4ThTWCaXMt2odv0/ijRGAj8IvdA5AJ95bnZmZobevl6mp6dCZ2NZI+mfaakto6MLvl56x/7+sX2fRrZsen8QUZDJ9F9r+Ube33ZZeDlv2HmurA7lonxe85lr/t/0b2/HZ8Iq1KHXxd8rnId/DHxC4AiQjsb6CmXKQ2twnsDmHFr822IYftVM+yUiwYNvOEg5f1NZ6A544R1NJq3yvEYcKEqVN5Y87sQ7tFfP9yNk4ECGX9o842I/QDGUetK9YKBIUlMSF88B30s6HjB0CugjdV0j2Iml3xmJbbexsEq5X6DzEtqYB/Cc07X6l7GzC31JGWC5zz4kJ25JwPrrVwYpq+nMRX8LZKos2BdpWsFLBkSJNg5HUj3BC1UDjBBG/ghspO0gvr1oEpSUXwuWt+8yWxynh+L1Ou05oOZOte15sq6WvJPTsy7cGp5X2VL2Ib1ERX45JXdI85W/h4tdVx/18OUfe32OF8sZdQvImEqo7SDCn7qMMN3JUcHgsBSIVkEYw+gJ4OVqLBtVR5EkMuBRCGWacCtURHeLCUsOyfoQ0cbYKygRfU4fjaxeq6myLj2L86ThfpxxF+bfzUuUOn6ApyuuJXNwul/Z7nZ+48L1SNKjzOxeuzKJ1Uf31VeHcch9pkArtWIVf3+D7kCCbHgpYlU6of15GNXzPa8Jv0IWaFWXdBmkVFCof14xB+ye5CtUAuTQJcNZ3cnXZunUr3d3dvPbaa61lKsaYVrjqo/NPt4DFdzZ+TGPK8Tr4fGjEWXQYJZRFRC4kdMKt/X38oaryuFSoQZfYAsH6WTQvdO5HyM7/EJ1ojP/Dn2kYLfv3VKvjLyur+epvoI3fmVNltTk/XysuFG7BtkKXyvl1zIWoULE9jBo7msdhO37kHQaqLN/qCJ0CLePrC9GodkdchpLLxVWtDvoiZ0lsx6WT1nOnOguVXNpRlodTZmwLNkRdVFjCRTgu26oDo50XsVFi0EZjgza/shqn8eV2pQidYiiaRFlSh1bhJqtMR1Vbf26dZXdcqH53YYW6sl2gfcIfrSewrRKRoYV/rtv6cl+88HjEQWLFl7213tBZ8cYvrKBr35NXgApFhQirD3wBG3zbOUGkXSK7fE7523YpTspcibbrVFa7EwSxCqdtOAsTfn+XmRe5wta4HGWkozx/Ve7b+WJcpe/6yVBOJwlegjk4Ty1v3AYHnfZrdJYva/UGfmuiaZfQLt8Pg6GfJQv0GuAqLGgUOuWAr0Vv6eDBgyxbtozPfvazNJs5tVrNy/L+zLgrepRVvhQGFarJ+dWnCV6RvCyNenFVK7no8cmtUy2r/JUGqBR0FQeGJJyL10y3aIworJS1xaXV8TpUK+xrkfZcpCrL9DqMBC/eKXIlIaLgjaoVR1kK16KxHTLITqTjURrudgW0djnlEJIP7ekEnDK+Y5YCCSVmvTMg4W8TEuLch3SyYX8SnIHycUF54Q8jGPswN+4dAoVyPkJRruUGhSJDWxW+Y30Z4zLfw1mcaoDkoQMPTnpZjtZpxPlRqnIKq/z5+rb2hW7Elbr3zo/8VdM/b8nmKT+Kdb5yoX+kdFYZ/On3Ea3bufOuLkek5eNn59LfnzjICkiNlx5WOIw4coFcccE48ErwDoAK7U44f91qP18UymecKGf8VEy4vtiQOIoG0tZvBpv5z1l/3XW4B9p9Apd2B5d7XCGpFbQLo33lHfCyHbQTXyToytM6Zp8QpWpXCyx/Q+H369IOZ/Vytqj9ui2nAi9wuj+xM/tYuOpKgNAZAro2OHPmLM899zw9PT309fUyOTlBnjev6j5bhUqw5Rg43Ladv9gyFGY7hiGXu7EVn5QT4A1i6FDDsbkwbvBGXVp/g2oZ4taYsjT60lGqVFxp1y84W99mfu7fIhiR8H0fFfAZ5B1FYYOzEWbYW+bdj+xLI9z5o3et/dhyZOUcTnlDr0JVPm+YguPmTMuB81XoOq9Fp1PRuffw+iUlfXX70coB0C0ngDIC4ZJgtJNgQBKwScgraEdSynK7InlY3dAesfv56MRHaUpjE/IgrDLYMFXgr4k/pnaEJrRoGY1oOSTl/+UjQ9yVOdIX39Veurct4dvy22YRhc90T6wLS/9CIaKQvmGDHblyB0D562FVx3XzzyEJDoAKhj+cm9Xtz7gE5zSWcE0IDhVle4btEkrfhhLhF99hl3tcadNpZ8scyXYuRmj40gnQn1j33nmXlL+xjggAwEW9aBmxKH/i7d61DPZf6iH9MjsBs68E6Hy5WAdBBVC1ssivFRpNRW40OtGkmUExSaJqPiMX7Y2Y+PKoV3Zr/NOfUmXHhg6eaBgVt8wVbeN5SVtevP0P83avLuK8QXIAqoFtjf/BuTqKAp+M5V9TzqFMeQs6jIR5OnFo39P4imyEZVjKS8L6tvCdtQ0Rh6rxe8qVfz81vp/KtXcekg6f6eKQoEeHhw8j+h99mcFv22FBJ2DSEGUQ2l0qIeyVtLcrZXj24n1d0Grh/4uvq+sYzfi/nQi5LnDiUCEDy4mj0HlwYlyYBrE45WiKH81aNM3E4cQgDqYTwbnMuwYdGe7glw8SIivl5J22Ce2wvxe8KUs2+0PrWOkgHQ4NculteIVWO8wMtYcSsx6CvfRauBBpKp1NxAvZJLb9jY6z/iexomiH5hNQ02EjOT6/RGEoJ8+TkGcRIk5qqhXtE5rgQmRNNXAojAoRI0mBAlxSTkT9jGd/eYrgVGsXpgNaP4NfhKnd0jmWEAkgOEgdhCmu8Id/1nHgrtVqEqKuF04L/LKG/kuuyjDR/ZS/rglEc/LkKU6dOsWXvvRF+nq7QwSg3SV9tLO6sphc+a8L6X7+hu0cSX/Yti7mk2zz8pjsRdELHc6lPQ7xgwm5IOPbtUYXnbPMtJLAOpO+pKMzKhXNXBillKHich15+b3Lt/7FbdlpsMt3y6hMGUpXIarQrjHvOj7VvmKXWEAuf+0u99olMY9L2gfwo/MwQoeyA7Mhacy/Yjt6PhtG8eWUgXScY+d+Wrl9ramFzmO6KFpxyfsdUY0Lpjqu/N68+uOuS69Fef+0nABoq+V9xJ9VeX+0+o1WjoQLzmG4fyjvnc7PhuVyHeNS/54Jx+nCNS/3cemd/NN7mys8h86Rsrv8Vf7k+PDf7KXu2k8763bPe7l1Jb/MzL4DUGZwQ0gC5Joa/YMvBzkwMMDw0CA//vE/kBehNO/H0CVFIpFIJPJxcFUiAH4ZV+cr15YHkGhNvV7HAePj40yMT/l1txd4lR9dzjQSiUQikV8UrlISYJurWwvg6uQWKAXNvBHm3YRqpVZOCnbExD75AFgkEolEIj8rVyUJ0AYZLqW8gtxsJgEKgtJeT9qvzZeLRHB+frbcupmbb76ZvXt2kucFjUaTLOviwmzuzhSlSCQSiUSuLa66EqBjdnMArLOIpVXQRmt9YZGLWeD48aM8+vhpjh/ZR1Hk1GpdNBtesreN4ZNcbx+JRCKRyM/DVVcCnO0YfTniHxsbxTkvUVtWk5ot9h/YD+KwxTRaHE2To3S1o4BGDP1HIpFI5NrmKuQAyEVJgLNrLJ1zKKVaBl9Efg6J3sujtaLIvcZ0Jat2RPpDAuBHXM4UiUQikcgvGlcphu0+5P+fd5uhSAm+xvXnHnqIf/kv/1cWL140i/uBvNkkzbwQ0EyjAQhKSnnYEokZAJFIJBK5Zpl1B8CG2vNlYp6IalVf+plwKbhQk1J5+VJb1LCuyeOPPsXBAyf43MN3tkp8+ukH+3MlBWpxUFiw2pekVRk5BVblOFUgTqFtRkwCjEQikci1ylVZBnixBsBs1gIoy0YmiV8JcObMaWq1Okr5mtqdjkAkEolEIpHLc1WUAFuymldBBdAUFucsWmuazZyxsTGGhobo7++nUqm08gGMKWZ3x5FIJBKJ/BJxlSIA7SRA52ZXMEdpRZpmNBoNqtUq77//Pm/s2MGv/upX6OnppShykuSqr26MRCKRSOSaZtYdgIsLAc12KN4vL7SIUogIGzduZM3q1fz5n3+bM2dOo5TGFMXPl3cQiUQikcgvObPvAJQx/xD+V+qj1p/66YhAURRMT02ilaJSqTA6Ooq1pr2fOP8fiUQikchP5SrEykPSnwAtWeDZk80VFFlWQWVdKK0YGhoijSH/SCQSiUQ+ElchTu5VAMvQvzF2VhMBHY48z9Fas2L5Crq6unn0sUevuZLDkUgkEol8klyVobN3ALxvUUr1zmYugLEGZS37Dxzg8JFjTM4cAqrEdfmRSCQSiVwZs+4AtNTyHTj8mn1RPiqglfLFfHA4rjQ3IEwnIJQBi2o1JbeWyakJlCToNLnCbUUikUgkEoGrMgXgUCpk6yshd7Bo6TLWbdhAkiRoDNrmV26upQAKcAK2AigKO4qQoZQFaWKKdPZPIxKJRCKRX2I+nrVyInzhC5/n9ttvJ8/zsJQvTtpHIpFIJPJJ8bE4AIcOHuSNN95g7dq1ZJUKWZbFUjqRSCQSiXyCfCwOgJ//1/T39WEKgzEmLtWPRCKRSOQT5GOTy3vn3XfYf+AA3/zmb9Pf3z+L4sCRSCQSiUQ+Kh+LA2CspV6vs37dOh555BHOnDkTcwAikUgkEvkE+VgcgERrVqxYyclTJzk/OooKOv6RSCQSiUQ+GT6eCIDxJXyVUihRiEQHIBKJRCKRT5KPxQEYGhpi9eo17Nu3nyzLKIoi1AiIRCKRSCTySXBVagGUqnzKgTjLqhUrOLB/P088+QQTU9OotBLL9UYikUgk8glylcroSetfwfHaK9t5rdxhWqGI+X+RSCQSiXyixGF4JBKJRCKfQqIDEIlEIpHIp5DoAEQikUgk8ilk9ssBi8QlfpFIJBL5peWXxcbNugOwZcut/HP5n2d7s5FIJBKJ/EKwZfOWT/oQZgVxUZM3EolEIpFPHTEHIBKJRCKRTyHRAYhEIpFI5FNIdAAikUgkEvkUEh2ASCQSiUQ+hUQHIBKJRCKRTyHRAYhEIpFI5FNIdAAikUgkEvkUMqtCQHmz4MWnXuGF7c9SmBkQh3EWAAsICkFAHAJYEVxZOdAatNaIQFEYlAgOsNYBgk4SsAbrwIkgGP9dp0lcgQMMmoQCK37b2NK/aUsdiDhEwOFaL4sISimssThxOBJwCegCZQuUEwy+sqH/V6FwOAcOjVMFoMBVEZlCHOASnBQ48ccIhW9up4AcxPq2cEk4ngLEgVNop1AYcuUQUWijMMpgRYFNSF0TqxVGhNQYHC5UWExAGX++tgbSBLFgKyA5YPyxXCBiFRohyEG0r8iFuA95fsHGSnWscM0/7fzBH/wBIyMjn/RhRCKRyGWZVQfANC3PP76d//M//GumG+fQicUm0Gw6dKKxRmGMwWHQCgwKpxLEOZQCsRacwznrjauDJKvgnGCMJbU5RhRGKbA5KA0upWpnsAhNUjIaGMF/xlwc4LCARURIEkVhTEvSUZzgnMMmDqXqUFSwapLENEms0FQKhcVZh1EZqS2djgoumQGbgO1G1Hm0A1wFIzM40d4AqxlwmX8wCeJdCnFVXzZZNbFicDYhc5qUJtOJQ5ymajIaSYOChFR3kzVHaYol15pqYbA4muC3rXK8A9ALasrvx3SDzAAFuDQ4Gq5tu50LbeONv+JCH8F1POBiB6CjjUX57UQHAICvfvWr0QGIRCK/sMyqA5DVEnpH6qSSUaiUmWKKwgBOMHmBs4KIRusEwYL1hhdrMdaiBMR5A+2cQ2lNURTePomAhEGm9YbqwlGpAlSHoQrGqOMT4FBKoVQwWk5QSvx+mjnlRm1uwDkk036b1ganxEcA2g8L5GHTFmiE5w5o+ufSNq7+wDqiEUCiE7QWcpMjQJamaKcRWyDaoqzDmcJvXlvy5iQVAZ0ocmtIEoUTRTPP8Qa+3HqzNar3x2iDVS+PhwuPSdoREcuFDsAvh+p1JBKJRDqZ9VoAzjlymwO+KJAAOhGsU6AUODAmRyvQOsFaUDpBK8AZjHE+PC9+W4j474kghfFRApEQjg+h/BbiTa2UY9hLR6LW2nCcoJSmKAwUhXcfRPwUgAgKhU5SEpdDEcLiIiHKHZwR52MAfqpBKI2uax0JPuTfMrwG0O22Ch6NdaCUgCgcDusMWaIR43DW+TA+ChGFk5zCCdbgp1isbU2z+NF3OJQLHICm378LbVJ+vtMhufC/1v+lqxOJRCKRXy5m3QFIEo0oqNQyeru6QDsazZzJqQYzMzlaJySSYEwBzpEmmmXLlnLTTTfy/HM/4fiJ4+R5gRNIspS+oSEQhc0LZOwskzNNcmyYQnAd4WlvqlqBbFFcEiYIaJ2EKQaLUr4JlLPgjLeRAvWuLj7/6w8yfuIAzz32DE0DQhFsufiBPX7O3LkQmpDiAkPq7WtwXoKxbR9xiaDFdnbuAAAgAElEQVS1plrvZXpmkqLpqNfrpLqAiWmUhiLPQSp+kC4WoYYoS19vF6mB0bGJdki/3LxYb/CdgpDBUH7Ah/ndJfGRS8y9SHAiLj7mSCQSiVzrzLoDUBq0b3zjm9x86w2cOHeSffv28/jjT/HBB/sxpiBNNEmS0WgUWGM4duQo02tWMTQwyIkTx/2gX2tWrl7NF77yZQaGhpi/cBF/9Ud/yAsvbqfRLMi0IpcEqzJkxofekyTFGB2McUKSGIqi8CeqtR9BO4cxBVqnzJ+/mEpWYe++fd4ZEFAISmnSNEUQisJirfXTF0qRJBqooPICZw1K6+BMOHAJSepwhcE5h9YapVMcCZLPBOekdAJAQmRjaHiI3/u9b/Dqqy/w4gs7+O2v/xY6sfz5//sXjI2dRxJIVBVLTpIq8tyxcMEC/vn/9HucOnaO/+dP/4wzZ88iCKK8Adc6xdoCYwwiOpRpBqUSxBqs8VEPrTWiFNY5CmNxTny+hvUOkiiFEosxZvZvlUgkEol8Ysy6A5DnOeKE8fFxvvOd/8yTzz4FoiiMQ0lCmmbcdNMm6rUqzzzzHNZYpiYnOXnyJBvWr2fv3j3kRYG1lvffe5f3//UulE741j/7ZyQ6QSlFVsnYvPkGFixdg6r38sz3v8u58SYPfemrPPPk33Py3Fm6h4a579breeyxx9E64fbbb2PunPmcO3eeZ575CUVhmTd3Lp/5zE1UnnuevbvfwxpD72A/t95yF8NDS7FJg/PnRnEIOklZe90K1m/YgK6N8PaLj7J/3wE23bKFE2ePsvuDQ1Szfr7+9c/yyPe+z+Sk5cZbbmDF6rVMN4WXHvtrTp+exFqHRbDiHQFjHWmaURSW3t5u5s0ZRrTi3PgoI8Nz2Xj9Bl57Yzv5jLDllpsYHT/JB7tOsHzFSj7Y/QGTkwWDw8OMT47RVe9j7fqVmCJn7ZrNHD2+h2effZrurnlcd90ytIbFi1Zy/Mh+nnv2J2SVCjfccD0rV61mqtHgpZe3c+LEKW7evIUjR49y6MBBli1dwtzhfl5//XXywkc4TCwgGYlEItc8s64DoJWiXuuiVqsyPDzI0qXLmDdvPlmWYa2jUqmwZPES5s+fj9YhaU9gz969KK1ZuHihHx9LGJ1ah7U25Kj5JXirVq1CRHjpxZew1vH1r/0GlTRh4ZLF3H//vYgI99x/P/PnLyBNE1avXsXE+ATbt7/C6tWrue++eymKgrfffpudO3dyxx3b2LTxeipJxsz0FDt27OC5558jd5ZFixeRJCkjc+czMnceb+x4k6PHT/D1b/wa8+cO0t83wBe/9BBplnL9xpu5/vpVNJqWpUvW0NPbxbPPPYtSKb//u79FTz1FiSXRyucSOHDWT0OcOn2a6ZkpNm7cwImTJ8mqNbq7e1i3bi1Lli+hp6eb61avBgcq1SxbuozXXn2Ds+fGWLh4ASKW/v4hvva1r3DPvVt5e+dubt+2hcVLR5gzsoBv/c632LBhLe+88x63bL6FufPmMjw8TJKmPPfc8yileeD+B0jShPnz57Nm1Sq0EjZs3MDcOXPaSyaVoERaqycikUgkcm0y6w6AsZapmUmqlSp33HEH3/zmb/GlL36RwYEBlBLGx8b56+/+Nd/73vf8iFIE4xxjExOcOnuG1WuuI8sy0jTDWT9P7UpDqRNEaw4fOcZMw7Bg8QImJyfp7e1jZnqaZ59+mtUrV9DTVWfT9et49ifPMjk5zYH9h3BOmDdvHs1mk+7ubpwzFCbn1de2c+DgPr7527/N6lWraEzlnDh2kqOHjnDq1GlAyNIK58+PcfzkKUbmziep1ujt6aEx0+T9d99jwfw59HZ3s/a6dTzyg0do5jMcOXqcM+fPsWDJApxAf3cXxcwM4izWGZ83EC5BVqnSaDSYmJhgzsgQ58+fp0A4c/o0x44dZ9GypcybP0QxM8OxI8cZGOylp6eb08fPcfLMGZavXIZISpFbxsfH+aM//hPefGsnr766g3Pnxshzy3vvv8t3/vN3+OCDD3jt9TfRScbZ0TGmZhrMW7iQLEvJspS80WDv7l3MmzuHoeFBumpVPti9m2aeY60LKyGIDkAkEolc48z6FECapijRTExO8Dff/R5Pv/AsReFACVqlKAU9PT0kWmg2C6wSlPg56AMHD3DHttuZP28eR44eo16p0iwK0AmJKJqFxThh2x13ceP1K3hn9wGWLF1KkkCWat7a8QZ337qB9RvWMj05wd69+6lW6nz5y1+hXq9x4sQJBgcHGR0dBfwc/apVKxkeHuDpZ59mfGIcEcFYQ24KVMjSn2k0WH7dGj7/hQfYt3cftYH5VLIq1UrCocMH2btnP+vWraFWTdmxYzdKK7bcegs3bV3P27s+YHhkBC2TKAcKiwW0gjxMq1trmZiY4p233+fwvuN09c1heOkSCpNz+MhRbtp2K/2VHg4dOMDE6BRL1q5lZM4In33gIWy9wqpVCxkY6EUEpqZmmJ521DPFj3/0GNYVDPU68ryg0TDYYprHnngSpYXbb9/Kls2bee+99+jvH0CJwjnLiRPH2LTperbccjPNxgwnTpxsa/y0VjlEByASiUSuZWZfCjgkjKdpyuKlS7j++o1ct3YNXfU6Wmsq1Qr3338fX/rSF/3COGOQROMEjh47xvT0NCtWrCDRimXLlnHLzbew9bat1LIqhw4dJjeOweFhTp46w+Gjx1A6xZjCRwuKnJ1vvsHdd27j8Ucfpdk0IdlvASdPnub06TNkWRYS4yyrVi3ngQfuY8/eD/jxj3/EkcOHsaUeQUsd0Gf59/cPYJ3j6LHjTDaaKK0o8gJnc5564lk2b76VkycPMTY6hQgMj/RxfnSCY0dOYZzD5E2/MEHEKxRYhyhQStHb309XdzenTp1jz959jE9O0tXVS7WSsnfPXpSusnL1cg4fPkil0s3w3CHeePN1Hnv0Sf7hH/6Rk6fOsnr1GtI0LA+0kBcTOFtQyVKQnCzNKHJDYXNUoskqVbp7+xgdn+TI0WPkhRcQ0koxeu4sZ0+f4nMP3s/hg/sZHRvzoX8lYWWhtCIBkUgkErk2mVUHwFlHs9HE2IL9+/ezYP487r//PrZt20pvby9FUWAtHD16lCNHjuDT7r0Er7GWifEJduzYwaKFCxkZGWHvnj2MDA9zw4aNPPPkU+zZv5+mKfjhD/+erFJj27Y7efrJJ3nxpZfJiyZ50eTdd9/l0P797Hr3bZwVJiam+Lu/fYQF8xexcuVqvv/977Nr1/tIWCb49DNP8fLLr9BozOCcC/K8ikT7jH+lBCeWN3e+xcGDB9l8661MjI7xjz9+gsmpaQpr2LV7P/v2HeC9XW/inGV6KufZZ58k1RlbttzOuzvf5JXtb6K1aq9M7Hhy4sRx3t75FiIWpTSj50d5Z+fbzExPMj0xycTEJIcPH+L8uVESnXLi+DHeeO01jhw+ypHDh3nmqafp7urh3Pkz7HzrPbROyIspRDTVrM7pM8d5+5138RIKXl642cjZufMdpqdnuOuuezh86AjbX9nuV0kUBefOnOHsqeOcPXMGZ43XI8CvJEiShNlVB4jRhEgkEvm4ETeLQ7mZiRn+3f/+f/Hv/uSPGWuehiQnN4JW4LCIS8A6TIfWnIgXCRKlceRUKglLFi7l+LHjTE9NYHBeB8BmKGl47X1SqrpJ01msaKpFjiWjKZC5BhYo0CjncIKPEliFV/T3+gMqrIcPyvkoAa1SavVhRoYH6e2rctPmm3nnzR288vKrWMlAch/Ad3VqdhpLQa4zDAplC7Qr0EDTCSRVrLMIjkwgKZpYwIiiELzgkBNwGRqHkgLjDCJe8EcQ+vp6WLBkBVvvfZAXn/4R77/1Ns3cklUEmzuc1eQaEmdwzvrqCE6hdIKhSUqCGOdrCgDWAsqhWzUMNAqDxS+bVDSp1LpYMH8ht928icnxcR5/8mkmpyZbokylgFLpDFhrkERhrJdVFusQ51oaRCJtsaP2rdahhqgSf7xFHuoQlKoO4f7AYZ1f3midu6YiDzt37mTDhg2f9GFEIpHIZZnlHAAHtgjPVFgulgAOcQax7YIzVhTKOcQaIMEaAeWYacyw+4O9Xk8fAwI2CNq4sogPClsYL3ajHNZ5Q47qlLNTCLl/zxYglaBp06mCFxDBIogo5s5dxD33bKVeL3j/vQ946623vEyxclhx4CzONrE4CgSrNFiFiEE7CXUNhMIJJBoxTcQU5HhdQoMNSoWE7MYcwXqjCVhnUWKpVyosWryIGzdvZtf777Nv7yFy67fgguJwgQGrEefn5I04n8NgLKRAYUkQms56iR/xKy4kiCDhFDgDonGi0EozODTIDTdtxlq/LHC60ewQNQptH65jkiQo7bDOobQ30mIcypRywtJSRtaiMc50NHtQe8Q7B4jy0YlwrFopr6oYFIpLVclryQGIRCKRX2Rm1wFwhNC6oET76nXKG4ZEKWxTcIRqfDaMDlvZ8Bcq+7fHgNCpUKe0wnkfA5WID2vj1f2Ma/oRvxIwrv1VoKXHT6eMcHv7ImBdwZ49u9iz521Q0wgqSPH6OgPWWtJUwGpcXqATKIwJUsUqVAH0xqsIzyUIDFnXqafX1t0vj6VTlc/nHwjvvPMuO97ZjXOKRFms9RUPLjaB0rGdi9sxWNkL2sKJICrBVzD0wj8myBGfOXGS7333uySugQ7JmR9mc4213uiHXdjCovGRBgckib8XGnnx4UmDznmfLKgOininRABjS1loCfLPtOpERCKRSOTnY3ZzAPDFdmxL6c6LzhrjC/oYb/W9WVJeWa9t2h0tLftWdbqO+XLx688VwuDgICMjQ36UWIbMRRiZO5eh4QGv0y+lbxOcjJZevmrJ+Lbxo38l5VmUVQn9+Ygoevv6mD9vLkmicU5aKrlliHvRwkX09fb6Y3aOrt4eVixfxqpVK6l31S6QK+60qG1nJJjI8M/MTMPnJDiLiBcMKnPvLxTmvdiBsqEdS5NrL/lkaCB6+/oYGR7yqx2AIi9o5kVbRdn66oeXNd1lNCYcjC3alRUT7dvHhO8rUR+uJCyCCrkR0qqZUI76fZRBEGxUIoxEIpFZZZZXAQiFsaRJym23bmVwcAglivUb1rFi5XJfBVD87LtSuowC4w1SZ/jetrbXflGC+RNu2bKZu+/aRiXNWhEHRLjrvvvZtu0mIIwkO3FlULp90ra1by+Hq5RDMO29OtcKT6+5bi3333+XN+bOBWOnUFqjswq/+Y2vc/3GdSSJH6EODgyweevtfPVrv8HixQtbCvyt9XQIgkK3TH94PThIWspxvQObo3SKL1F0OQegNbQP0wGu4yz9c6GsRyBhH4p169dz++1bUUJIgAz1mqwLqxS0lxGm80ZpCRm3tt7T08tdd93N5x96iHVr1waHLERCjGlXX7zcHSOCs4aB/n5u37aNBx98gM8++ABrr1tDrV7HGh9l8PUbrq0cgEgkEvlFZlYdAKUE6ywDvYP8t7/7u1x33XX0DQzw67/+VW6+5UafBa80XV1d9PT2kia6VXs+zRK6uup0d/dQqWSIQJpWSLM0GOeEWjVDi6GSJlQrVRyKSqVKd1cdrKNaq5JWqjgSqrUatVqtlVRXr1Xo7u6hVquTiHdAskqNarVKV3cv1ayOsr5IjpIwBRG0+lWSkGZVdJKSJjV6enr9yFS80axXq7z11lscOXaiNZI9dOAAf/s3f8OxY8dI0xQQrChE/LF3dXdTr4djEU2a1ahUqnR1dVOr1dHKqySmWtPbXadWrdHd3UWtUvHVCpOE7q4uunt6ybIMwY+Ws0pGd1edrq4esjTtuMwdjodotNIoUWRZRl4YKrWMWq2K9v4BtXqdaq1GpVJBqbaL0h6fe++tVq9x//33s3HDRrq7evjiF7/A4iULWtGRaqVKvV5vuQ2XEBIL586dy+ZbNjM8PEJXVz20r3emrLHR8EcikcgsM6s5AD5HLCGtVDk/Okpvfx/Dc+Zy7vx5pmem0UnKmlWrWbvhOnoGhjl34iDPPv44E9MVttxxE0uWLcAaxXvvvM07b73NjZs2k9QLXnrlTar1+TywbQXPPPM8CkErx9DQIFvuvBfGJnjsyefROsUgzF2wkLvvfZix43t4/Ccv0T8wyB233UzX4HyczXnxx99nLIf7HnoYWzTRXUPMTJ3jlSd/wJGjkzjx8/ZI0AEQX1xnaGiEhx56gFQNMHZqHz9+/Al09wD33vdZ5o/0c2LvBxSFQxLt8waKAq01EJLskir9I/3cfdsmar3DJDrjjSf/gWNnp9h697301BNUdzeN6Slee+pRDp8eZ9ONm9i0cS3NtJ85vVV2vvQMz73+NitWruD6dWtJe0c4d+QAj/7oByxZvoJbb9lIrV5hRvVybv9ufvLkU0znCh2cGqsSrBV0iBPoRNPb38vWO++mYmf4ybPPU+0bYevNN9LT3cN0o+Dl557k0OHD4SpLmON3CIrunj6WL1/Bf/2vf8n42Cj/w+//LtdvXM/efYdwzvHwww8xMDTMt7/9HZp589J7xhhQmqIo2Ld/Hz95+inGR8+1nA1RPrHSWuPzAGIOQCQSicwKs5sDEMLI1WqNqalp0jTlpptv4u133qVSqVKvd5Hnhpdefpnnnn2eBQvmsnzZQkZGhrnxhuvZtes9fvyjR9m1axfWOgYHRxgaHkZpTa27h+XLl4Q5eahVK9x/390kWvP8C88zMzNDkRt6env4/OcfYnxsnO3bX8EYqNa7eeetN3n6yafIsgpbt9xIpVJlxao1NBs5z7/wMlm1wqrlS9CqjAD4MDhKY5zCWOjrG2D3B3t46qlnuHXLLSxaNJepqUmeeOxRpqen6R/o90ZVKbAOpxRFkSPK+KbWCUlWY8/uPTzx5FOMT0xw7523+ToGi5eRJJrnn38BRFi/7joGh4ZYv34tO3fs4MUXX6LRnGFy7BygaDQKnnzySZ555lnWb1zPYH839VqN9etX8+qrr/PiC9u5bu0aKlojkqCUDkvxwIlCQmGlvt4eHv7cg3R11dnxxg7youAzN9/M5OQkP/jh3zM5Pc2mGzaQaBUEknwiJkohyudGGONYv24DX/nyV+jr7WN4eLgVATh58hSnT5/+qUZbwrTEsqXL+MqXv8zDn3+YuXPnoUT5tgzRmDgFEIlEIrPHrEsBqyQhTVPGJycYHRsnywY4efIkC+atwljHwOAgd2y6nd7+uQx2WapZwtTYOfbv38eWzTdz/bpbeeYnj/HB7j0kSYbSFtEOnGBNgYjF2YJbbtnKwZPH+Q9/8mdMnjlLwyYkacrW22/n3ff28//9l0cwY2NY3UWiE77w4F1Mqh7mz5vD8fOHAOHs+XF27NjBsdMzmC3rqdcytLS1AZyzQBq0CmDv/v28vfM9psegmTep12uY/DTnmmPMTM+gBNJEyMtwtwPrHNan2KNEU6vWuPuuW6A+xNDQHIqDb+MQRscn2Pn66xw+cJgN69bRVc3QSujt6kKLkM80MYVhcmISYx1Lli1j7b13YLvnsmjRMCrkFuzds5s333yXvpHl1GsVrM1JdB1sgcInE+pEYYyhUquxYcN6Jmem+dNv/xeOHjlGUq2zeMkSRnq7WLl6HUMjcxk7/gH1WpU58xdw67ZtZPUujhw9wVNPPEFXVzer16zB5AVv7XidU8ePMnekP6wMcLz08otYBGN+yhQAcPLkSV55dTu93V0sX7qEgb5+vv/II4yNjXtHLCR6RgcgEolEZofZnQLAL92qVGtMTU7zyvbtpNluBvurGGMZGRlh2+138PJrL1C4/Tx4142IKMYnJnjyyWeY8/4wN6y/lW13bGVs9DzT0zmDgxlJWmXegkXUalVS7fXqd73/Picnxrnzvnt4/keP0Tg3TTPPefe99zl9Zpqtd9zBa0/9PTO6xsNf+BVO7N/JWwfOcv+D94KxODTGCaI0hYO8MIg4nC186Fn75XJAS5jHrxQQevr6cNaRN3NsWPOWJJqi8OvcC+vCCgdLrVoDSdAqQVcqbL7tNibGzvD6y2+zZes2RooC5wTrQk0EoJEX9CWC1gqthTtv38L+yQrvv7eLgwePMWfZOpavWslr21/AdM1l8eBW8tz40bmyqKAF4JzFOnwiHV6fAARjvBBRnhfs3buXk6fPcsOmG5g4cYRzE9NMTUzwwcljvLXzXawRps8dp8ibnD59ihdefBGVpkxMTJMbw6nTpxgdHeWlF19gxxuv8xu/9mXOj46FiIGwYOEiRCfs27f/smWEy6TQ8bExnn/+BZQ4btp0A7dvvY3urm5GR8eCAxYNfyQSicwmsx4BSJKE/oF+EM3Y2ASiDAO980krFUQ0eZ6zfuMGGoWm2WyALVi6eAmf2bqRel+V7uoCjhzbxcxMkwMHD7L5rgf4zW8MMzk9jKhR8txQqaQcO3qcF97cwbYHH+JLv/Ir/PDRZ1Bac+TIMZ597g2++JXfYtlAyiOPvUDezFmzaiVqYIlffWANSmmvEFgUiCQY61Bi0MonAvpFZ4JKUpSkWAurVq3hd37nd3BFN2/tfJNDh4+zYtVqtt5xFzdtXMfqBXMY7O/ikUef4frP3MjNt9zIunUrmdtbo2fwfZ59ZQfT0zNsuX41rmuEWlcXbsqgRCE6TBeICvPePvGt0WhQr2l6+/vR8+ZysLeLiUaDeq2Lmz5zI+dUL2VCntaaomgiyq+CKPIm9XrK6KigtGDK9faAVhpwnDhxgqd/8iz3fPZzPPzwA/zDYz/hnbd3sm3LLdx0U51G07Dr9QlOnbKMjY1xenQUnWYUTnAWThw7xhtv7GDL5lu59ebNNJvTPP3M0+hEgxMefPBBhobn8G/+7b/FNC/NAShXCyxbvpybb7yBvt5uqlnCrl27OD963ueVSJlgGp2ASCQSmS1mVQp4enyGP/w//og//cu/QDLDnsNvo9IeqollaKiH08cnmDdvHvMXz2FiMmfy7HEa588hepCRpcNU6gnFTMaBg+9y9uwoqe5n6ephugcGOHq4oO6Oc/z4UfoH5tGTFuw/cZKuwSGWDc1j77HT1Hq6seYcp06do29oGcsGq7x78CTd1Ro3LJvLeWqcOX6c7sZZDkxYhhcs5tSxA0zmFebP7aPaOMaJk+M0xZELOBJEKkDG4OA8Fi/qpqteoTGl2b/rNcanx+kZWcTKdRtgapwaDSZGx3j9vQ8YWbKKJUsXQmOSmliOnpnmgwPH6e3v4cYVw0ypKmfPjNI9eZp9p6fpm7uQyfOHGZ0uGBkeoc+Nkw0v5N67bufgrp0ca3Rz66brmDr0Fn/11E7mzJvL/P4aZxspTJ3l0N7d6O5eBvsTDh4+iVUDrFncy6nDRzg7UyeRaRwFhaohOsFZx8BgH3VdcOrMaXr6h1gw2Meho8eYscLKFcvp7hukaBpOH9zNyVPHyJ2iUH5aQ0jC8ktNf08vSxcuore7mwP793LmzHHyEHVYtGgJabXK7t17MKZUAmyvIkBlKNHMGRli0aIFZIlm9PxZjhw+wvT0TOs7fgWjj/5cK9MAUQo4Eon8IjPrtQD+8H/7N/zh//0fGS/OYdQ01qYIBqUMFBoRhRWDRaGDJr+h4kfckoM4lCtV9SxOWa8oaLtQMuXX07sKFZkix2KUomLASEYhlpQm1gmWCsrOeKleBEXqBYpcjm7VIhAMDhdEgMRZnK2CFDhpBpVCQSRFVBVkymve2yoVmhgxFEkVJwnSnKZKgRaYdgqjq4BFuSYVZymsXwZoS7Eh8evytQ12FC8TbAihf7Fct+lm7rrzTvbt2sVYw7Jh5RJOvP8mj7/0OnkzR0yBSetQFOBycuVX/FsnuAQqFrSBaXGtughWC+KSIItc6h64VgJnWxbZG3flILU5RhIKSUEMuJwMhxUwaQ2lMmwzJy2m0crRIFQ7DJpHnboBng4Vg6SGdo5q4miiyU1BQoFWQuE0VlISM4NzQiEVUjuDC5LC1ocG8CsTLIhtiR+WqtCdCosfN9EBiEQiv8jMei0ArX0lPXLf9Srl17k7Y7wccKn019KBt0E5UAUxIINzKnTgJhgqvDNQFtAhFJcJqjit7HAf1Q7FaEJNAuuXmRkRr3uPoQD0BX6P88YkCOW0TJVzIGFbJgflEAnHbjv08a3xIW9jKKxDqaBEnGooFC6Mhim18JUCLM5BgSJxNhwDtFbaO2HP7vepJClzh+eTVnJe3/E6B9/aSaM50z7KVgOJHx2jQhsVWKvCcj8b6igQFA69UqAvCkBrRN06H4JqoWubT+u800Kod1Cu67d5jtNJeZHatQjam2q18WXvGOOwOPK8idUVSt1BYxw2iBIlWmNMWwqqRGmFMRaVpN5563jvQ4SHI5FIJBKYdR2AoijIbUGiUpwuKAqHVlCraxpTXrhfQscuF3Tpnfp2F9UCKA0PoFONMQIWdKJ8LQAjpGkFa2dAIEkVpklbT9YJrVoA4g3YhbRV8+RiQ+VAlEKrhNw2yDIFJoFmkzTFGzud4EwBLmxJK3JfhQjBoJNWjaT2RsNuLq1L4EevWaKYnpnk1VdeBZPi0gaJtdQKCVEEiw4jZq9+UBrrdqXF1lbLjbe1gNBp6o/ZOpI0wxR5q8jPh9O+Rlr5JMkCQbTGFjm1SoKxJlRmujK01oi1JNrHZbRSZElKnue4oFjokyv90sVw8iBClqQ0XIE1ppUrEIlEIpErY5algB1ZVkUp5XXgHSiVYIyh0bA4F4oEWbzErNYdQrbBuITRfmnIWuYxiMBgYfHixaxcuZxE+SI9fnmYZcWq1SxfvsgvOZOLfZtglZy6UHUYKKcDNO0yweX7on29gZE5c1i7dg1JkmKMz7g3Ba2kuutv3MT8+XP9SghjGZozl623384dd9xBb29fcD8urgUgqNa4v0MK2C8lQIzzBQ/x2geifEFjGww4KvVREOmwfGUdBVcq/LcEj1shfkRwxjBv7jyWLV8WIij/9LXtxFofFciqVe/4aC6IcRwAACAASURBVEUjN+TFRwu6O2dRWnyNBfFuzMxM0y+dtBaUark2zhQoASW+oFMjb/hIxMWG/9pIEYhEIpFPlFl1AEQUzTynklT51rf+G5YvW06iNZ/93IPceedtJIkXoxGl0InG2VCmFvHzt62RcVm5r7VlQKGV18bfuH4Dt9x0I4lKENGoIBJz861b2PSZ9T5yrzqKAYE3JiGqoMM77VoAymfiU7ocHUNm8ap+S5ct45Ytn6FSrVAWJhKlUDohqdb4tV/7VdatXUMlC+6MKZA045bNt7Bw4Zyw5aAQ2JpqEHR45sqSPGXRI2dJtUYrAVcgSeqjIOKnJXJryF3hpxPKokqhsmLnv56wl3K/4kvtLl+xnE2bbgxFj6RVzOfyF7ezXTyVShXTaGKt4zM3fYb/8b//76jXKh++jcttVoQ0SWk0c3p6evjCl77EHXfeTpr6+Z1E4IH77+N/+Rf/gt/7/d9n/oL5OIEsSzsiPB9pl5FIJBJh1iMAvi8eHBzhrnvuZsHiBQyOjHDPPfcyMm8OojVZVqW7u5vevn6qQfMfoFLJ6O3rpa+/n1qtjoiQVWpUqtVgaFOqlQpZ4siylGqlikpSapUKXV3daNFBuz68Xq3S3d2FUj7xsLu7i/7+Abq7e0lE0FpTq3dT7+qit2+Irrp/XfAJc2UymTOWNK2QVWokaUqtVqe/v58kTfFpaI6uNOU//dmfs/2V12nmDlHC2TNnefWFFxgbG0fE1wJwohDlax709fXT09NLqgSlEirVOvV6nd7efmpd3WRJghhHlmpGhnrp6+qnt2+Aas0XBdJa0zvQQ19/P9UsA/DHV63Q39tDX28/1Yo3xtJZCyAYS51maKWpVDLAUa/X6erqQimFUop6vU5ff394rRTmbcfZnYPGTAMnmoe+8AXuvPs+7r3vLiqVpHVNRYRarUZXV9eH3i/GWhrNBnPnzOFr3/g6W7fexprVq8EJSVrh7vsfYNWqVfzwhz/AWMNdd22jt6cLY30+hdbS4evEOYBIJBK5UmZdB0CURpTm+LHj9PcPMGdOzu4P9lDkOWla4fpNm1i38Tp6B+fRGD3GD777XUYnUx74/D0sWDSHZgN27nidHa/v4I477iPrMjz25HPUe5bwG1/YxN/+7Q+9WI+FefPn8tCXf53Rg0d45O8fxzmhURQsX7mKX/nyb3Love388LFnmb9gEfdt20x1YB61asYT3/0OpyYNX/vm79CcmSRPeiiaozz7w79kz96zPv6gBCTBGsjzAkQxb/4Cvvq1r5C4AdzUCb79F3+JdA3w0MNfYvXyhTz+d9/j1e3bfZwhRCskFB5yokiyGnMWzuWhezaT1Prp6e7jlX/8PrsPneHzv/pV+nsSZlSCzRu8/KPvs/vQWe68axsbN66mkYywZH4fzz/2PZ548V3WX7+e9etXUO1byMzp4/zVt/8Ti9eu4+HP3glYxm03k0f38ch3v8d0Q5Mon2RodYqzPmu+MIUvozwywucffoiZmRkeffQxhkfmcdu2bWRZlUQMzz/2I976YH9IpBQwoRwyQprVOHHsBIf37+WuTStIQsVHrf3UzLe+9S3mz5/Pv/pX/4rmZXQAcA6lNLXq/8/eewfZdd13np9zzr0vdc7d6EZuRIIAEQiCYEAgSIIURZGSKImiLa1sy7Ll8cx6d8be9ezUaEe7qpmtkUbjLVlWsOyxJFuUSJkJzJQYASaAAJFz7pz7xXvvOWf/OPd1NyiQkqrgkrf8viwQQPftG957hd85v/D5pti5cyeT+QIZaWMDKMG8eXM5fGgvp0+fpX1eDzesXkRzUwMTkzmkwI0JWgPIqamN32zvf0UVVVTR/z90hZsAXcCrrqpCa4Pn+WzYcD37332LRQvbSKXSnDx5mkPHDuIna/jw7TcwZ3YbPQOwuHsBz7zwFPv3ncSTGh1ZPJVEqgAL+KkUmXQKawxKChoaavjovXfz+tt72P3KaxRDRRhpuro6WbhwJc888zwnD7xFaH3Gx8d58vEnKKk0t2+/jWtXr+Dp1/YhlM+7e9/l3RMX2bbtembP6uDMqRGklBg02hiQPkYIgjCiWCzy5I5nGO4r8r/9yf/EvHldHDzZx4M/+D6fvv8+PN/HWDf5gHbjhblcFiFCQGKsIJcv8vSTzzIRwA033sjG9Ws4dfE5EB5Hjxxj5zv72LzpRhYsnM9oMUHX7Fk8/sQjjBUauPtDN9I3cJZiIeDYkZPs3r2LTO0svvBbn6CpoQaMxVeW7/3tg9hEI7/10VsRxgVYJS1RFLmJBKFQnodSiuaWFu7/1P2cPHmcl156mTCMuPX21Rw5eoS333ybzTdv5KoVCzly5gxh3EbhKYW0mshAIpHi4IGDdHW04CdS5AvhFLLXWsuLL76I57k+kPeTsYa+/n4Yz7F42TJSSdcbUFtXRzKVYs6c2WzZtIUzvSNEUUAikUIbi/CkayaV0g14TMlNWVRUUUUVVfT+uvIZAKWwwODICD29fRSKkomJCbRpJdQRt99yK5u23UhL+1wmBk9yav87DPb38dJLL/LAA5+m+nc7+O5f/yW7396Nn0jhJy3Ks0SBjkcHDTqK2LJ5Mzv37eadvXuwxqANpFMZbrr5Gl54YRdHT57EBgHWSzB/4WL+9A8eYMxWoYRh944HMVaRK4acPnuOfC5EKo/qdBJfSfJRiBHxoJuwYAXKTzA6Ns7g4AiFPG5XbwxhEGBUgiAM8ZQlnRAUpQTtwlBVVRVR5IxzvESSOXPm8Gd/9GlEVQsWn6MvPOJwu6WAU6dOksvmCCJNXUIQBEWqqqvo7OqCwRSpVJr+/iyel+Hjn7iPjRuWoJNdpINxvv/tkGohuHjxAkODQ9Q01VCdTqE8g2+ThFEJBRgLyveIwoDq6hrWrV1Lf28vDz/8ENlslnQ6Q2dnJ3d95B60tngi4vDun5NOp7jq6mv55KceoDHtceLgfr73N3/H4Ng4RvoYIJfNU1ebYbxYItIapRTHjh2bWhhe9vMS9wDkC1l8lURJhbCuX8MYQ2NjE/Vt9Xz3299lcCLk4x+6gTAMiHEKcQZBuvfrkl6Actmioooqqqiiy+mfxAugpq4OHRnefH0XQlYzd3Yr1lrmzJ5L96JFfPWrX6MYCj77yTsASRCEvPXmPt7eu5d1q2/i+uvXMTDQy/hEls7mKrxEhiXLr6K6uoqk72bOd+zYwUQU8enPfIYdf/9jCv3j5PI5nnryWfJFwcc/fh/PPvQ/yMsMd955J9/5q2+x+3gf9z/wSTcGKBXaQDKRIDIhpSDAhNqhdAVIBda4mXrlKUwUudFEAc1NTZRKRcIoZg0EIalkklJgCLQl1BrpJcEalHJNilJ5SD/B2vUbePDvf8TLbx3ljg/fxaKkRkiJBpKJJMY6LwDhKZKZBKGOWL12FbMna3n1lVfpuTjIgqXXIbTmz/7tn+NVz+YLD3wk7oYX+L6YmkQIwhJhCGEU4ctyi6MgCiOEsOSyWV586SUG+nq5++4P89hjjzEwMEhfXx/f/c532LnrdYgiZFDAJBV73nqTd3bvJSk0lIpoKzHGRyV8wDXm5fN5hzI2gkwmQ3d3NwAHDx68bAnAWksUhXhSouIJCy/jI4RldHSUc+fO0RtMMDQ0wqx5S0gkk0xmc1PdCEopIh1zDaZaWqZBT5VMQEUVVVTR5XXFMwAJ36e6poYwDJ3ZjnGz/8lkmsmJHKMjo/yrP/5jxiYDJvqPYm3IyhVXc+e9W2loqyUq1vDs848wODAK0Uk2b/84f75uPe/uHyWX7aVYDEinUxTyeX7+6qvceNudfO6zn+MfHnoMz/cZn8zy1NOvctdHPsW/+qMv8q2/e4ijR47yuc/8NpvHoX+ghzCMkAiU5xEEIUIootCQ8sD3PCITTRHsVDIFRmC05Zo117Bxw1omRgzPP/4DTp++wJprN/KJ+x+gs6mOaP1q1q5azv/73e+zaetW7vrwHbTVp7n+mqv42asH+MGPH+X0qVN88YFPccP2Ev1DY4S9RwE3/x4EJWd8IwTaWopBHukpOmd10iga6WhOURw9S//ABWpravgPf/4lesY0yo5jjSs9hFGAF7+rQVCisTHB5ICbEtAWNzEgBJ7vozyPXDbHzp07qcpkuP/++3no4Z+yZ88ePv7JT3Hb9jsICxO89vzj/GznbgwKG5YQaHwMRoNSPvf/1mfYeN011FRX8Z++/GX++ocP8uabbwFw4403snjxYv7kT/7kfT8zxlqWX7WMuz/1APO6u/GiLLXVGX7440d4+skdfPa+u/nyl/8TgxMlHv/J9xgaHsHzBKGxGGuQ0sdcUmKo7P4rqqiiin6ZrqwXQLbIf/0/vs5Xv/WXlHSeoh1D+TXoUh4hQ2yUwPMUyrcEISSwJEyEoZq8LWCVRpkMyisSaYvVVViVBd+HqJGkHQJCIq2oSxkmQ02IpFr4lFSaUIdIkUNKhVEN+PlhwlQtIojI2AIFrwapNbU2x6RXRYSHsEUiakh7lmQ4TKAlRkGAwQgfjAQvhZIpLOOgAwRpvLAAylASPipVjclNUCU10lpyRqAT1SAMIsiTsBCQgGQ1AoNXGsMkMwgrqQ2yFLwMgfBRNkuAj5AeKZtl+Zp1rFp1NU8+/ijDE5p779pOS9ryw58+Sy5fwERFtKgmLUIwJSIvgZIhYWSJqKHWK2KCiAJVeLKEtZpIpZCeJApKDgUsDEpKdJzNECLG6wqFn0hiwwgZFtEJSWQVVviIqIRnIgwKkapHa0CEJIJJN58PDscr1VTtX0rpcL3v/QB6GZR1COeS8LDKQ4QFJBaSVW4Ms5AFK4hIkJIlIHY5lLF1symPVk4Ptah4569/gxmACgq4oooq+uesK5oBEFiUCUkYQyHKo6TBFLMo4QA7ECEiTag1IImsRWPRFNyMvNFoMYEJfZQFGHPAmZIBO0Ygo3iWPkW2lEPHWd4wChxpT1mUARtpjB0jwmKK4yAVkzIFugA2ZAiLF2Zj/j4gihQMFJBAGmEiEEWEdilrEUYgI4SI0NaA1vhCEBkQvoculRBAqC1eGcyjtVsASIlC4+sSplRCCwiUgqgAxjIsFF6UR2IJAUuE9CQBglwpIlHVwKatHyIXahoaazny9uuExSzSahSgPE0Yui74UAdIrTBWgD9JIVL4SLTIxhkNgbV5TOBBXM4AYkdEN9pnrcVql7UpFQpQJicEBohABI74KARSWojG8Kwb58P3iLTGtwakwGiNLxy4yMTMh/euNoUpYoUkFLE/gdYIlSTSGkoO5yilQgpQpuQsm121A2MEUsmYGhEDkIBK2r+iiiqq6Jfrn8QOWCoFISBcml1C3L2vmCa2i/hfcc0voGtnzJtPHYuMgYBiikN/yREzMLeXnGpKdsav935bzrjkzEBS5sw4Kp2VxnX4x1a4rsSswSqU7yEjgzEGpRyxD09BGFLe+Ma0/Evuo8zbvwSzE8Ptjh87TH4yR3N9C0URcmD3MCNnz1IyroRhiZ35hL30h6f++N7X8dKntsR8n7hr//J6DwCofNvWlkF9+IkkUbGINsbt9COD1e5AKRwg6v2CsrusxfM9hDFEkYMeKaXwEz46DInCCCuJPQ7cAsAQEwGFwPzim11RRRVVVNEv0RUfAwxKAYEu4Ze9AEKNUJZMlSSfdcFeSdzu2ZbZfMSRaMph59IlQEx7E9Lx/7VWCAMqIdHaNZz5fgpjiq6+rQQ6EHEvWNkLIK4RCxl3mc+Ug8kI+55gRxk2p/A8n1AHeL4A6UEpIOFDQVtQypkOxfcsY6c/oTVKOk+gUjBz6VEO2NN+BzPvSAlB0lfkdcjZM2c4p3uwfhHPGjKRQ+ZqAQqPSEf4mBleANMLrCnE8ow1l3s5BdJPuCyFCfF9nzAIL5uidz82vTCbOlW84pJSUApKCCmIjDN8UtJNG5R/WcxUhuHyFxBEYTh17ij2VdD5EAH4CT8O+hpP4jJI1k0JCOmaNHUU/Qo444oqqqiiisq64hmAZDqD5/lYzxDZEsrz8D2LjjTCaqRSBFojlEvrEpZTwzO3ydMRy5YDppDO6lbDksVLqE6UOHj0EEH8fW00K1evRoaj7D9wFEjg0hBllbeuYsoqdjpeOCyvJILpK8akOTcJ0Nk1m+bWDIePHCA/qUlKCCNnhIMQbNqymf5TRzl16gzaGFo7Z7Fy1VVUJyx7du7kYt8Q0zS+8vJGzLAmlgiM4+Ebiwlcp76yDneslUAY5coaEnylsJGPFZppz91ylLVMWSXGSykR5x60iGHHUcS8uXOpqkpz5PCh980AuDuzM9+JeFEkUL77+CglSKZSYAxaa6JcfirB48oKIOTlswxSKTdSaS3JuDERaykFJbQGJRW+73pHMBaCAtJYlBIExqKNxQpTCf4VVVRRRb+mrmwPgJCUSgGZZDW//fnf57FnHuLkifN89GN3MTnex3NPvUIYGYSSzkEuDKZY+Jfy/2duWaeDpZQCYy3d3QtprjIcPXEMoQ1SWrS1LF+5EpM7z7sHjjkvAFM+B7GxjId0XQTOVKd8baGcR045+3DJAsSRDWfN6qJ7SQsnThxFSgM6vh8hkMkE69atY09hjIvnzhJpyE1O0NPXz603X8fFE0e52DeCLVseW+0yEbi2NYtwdsTuRUQK6RrjPM/5/OkQqXyEDhGxZ0JYdsBTCqxEGD31sglmlhpgCoxjrVsASVfy6OzqpK2thUMHD7hnMVw+SDM9UOd+d1kVExn8VIply5eyZdstKM/jjddeYferOykG0/aH7mW9fIQ21vk+VtVUc+stt7Bk8WKGh4d45plnOHfuLEuWXsXWbbfS0NBAsVDgzZeeY9+7+5nI5kBKPN8jDN8fMlRRRRVVVNHldcUzAEhBfUMD3YsX0bqvldHxIsuuWs7ePaNYKamrq6O5o5FEupbR/osM9faijaS1tYGWtgak8BgZHGJoYJCGhiaspxkemUDJKjpaaxgZGcaTkkRCoRJJOlsaaPBTnD7XTyKRIAoSeIkU7W2zSYgip873IIRi/txOUtWNFLIT9J85jvYSNLW2IaWgqqaFQn6CgbPHCUILwjrXWSEw2pBM+fiJBEIp5sybi4gyDPecZnB0CD+RYP68eTy540kGzpykFFqEkmSzOU4cOsTGtSuweC4gSw8/oejsaKaqtoGoFDJw6jgBHnXNrSQ8S1V9PUGhwMSFcwRBRF1dDXPnzCaQSTwRMTlwkbP9Q6SrMsyZ0wWJDGMXLzLUc5Ha2lrqatLU1dZhUxkme3oY6u9HIJECLK4EYy0oz0cg8D0PKQWzOmbh+z7nL1wEBG0ds6irq6eQzdJ/4SxhqQTMXKIJ14SnNXUNjfzoxw9SCgM+/9nPcurgIXr7h1BS0Nk5Cz+V4cSJEzN+elrOQlrT0tLChZ4eXn75Rbbffjurr1lJf38f6XSKo0eP8NprO8mNZ0mKEGMdDTI0BhMETNs7VVRRRRVV9KvqioOAhJAI4dHX2091TS2z587jwP6DAKRSaZYuX8bcBbOpbWwl4wXsePgnjIz7fOiu20lmPCYnShw7fJDsxCTXb7iJRHXEU8++SFV9J/fds44f/cNPMSbCGsHiRQvZuPU2zh88wsW+UaLIEGnDNatXs/Gm2zj2zitcHBijc84cNlyzDK+mhfb2Fl5/8mHODEzymd/7POOjQ4yWFJmU5s1nHubgoV63F5cCgwIrCAKNsYKuzi6SSYUtVdHRsIFv/83fUVIZFi9bxtqVy3lxx2O8sWsXVjouvRVuFy6lcxxUiRStne3ctGEF2quirb2Tk6//nD2HznDPx+6jKmkZyOWpSiXY97NnOHRqgC2bbmLWrAYKoo1l3e288uzDjBQsy1csY/acFjL1s6lTmu9/56/o6u7mox/ZxuDQIBNRFelwkp/84IcUigolLJGVCOXFaXnjaH2ex6JFi7jphhsYHBxkfGKC+Qu6WbFyFYViica6Wt55/WX2vrMPLG7CwIqY9+/O9dLPXsQKS3N7K0pK/ESSVDKBNpqtW7cwe94CvvKVrzhPhfdKekipOHnyNKdPnsT3BFFYIpVM4Cnn8pjJVNHQ2IjvJYkmh9A6wuDogmUHxXLTYUUVVVRRRb+armwGwDoueyaTIdQR1lquWr6cvXvfYPmSLnwvQW9vP+O5UdJVjdxw7TLa25oohSF1NdUcPn6AE8d6GRnqoVgKsFahbYjBoqTvatjGecLPnTub9vlzePzpFzi6Zy+hSWAsLFu+lHkLJA899Cg9J/YTyTSTE1mOHz5CUZ7n+huuY/niBZzpf4dsIWDXzl0cOt3PnXdupr2lmSOiFyEkEdo1xUkfN2KnGR2b4MnHn2ZksMR//LMvMKuzlf3HLvLoT39KTcpDuJZ3N5FgDAiPQqEARJQr6aVSwJHDx8iTYJVMcPXypbxz+Cz5YsDh/ft4891DbNu2hc6uWVwciWhubea5559mOFuHvHsTPb1nKOYD+vuHGBq+QLp6gI/fuZXa6gxaR0yMj/D97z+Il2nj9+7/EBiLkh5CGoi9AKR0dfdEIsHcOXOYN2c2O197jdd37QKpuPrqqxkdHeXAgUOsu3Y1y1cs4cChw/h+kqbmFpSXIp8v0tvfP4X8TSZ97vnwh7l4/jzDQ0MYYzDG8txzz2Olh9bvM5pnjGMO+K48s3TxQhbMncsLLzxPqVAkn88xZ84c5i9cRGQsrz39KMeOHkZHrgQilMJUgn9FFVVU0a+tK18CiJvMhoZHOHb8OD2942Qns0SRRnqKbbduo2N2K6lMI1Venn27XmZwYJBnnnmG2+64hVs238PPX3yKV156Fal8pAqQSmCta0NTErSOmDt3DgdPnWBicgwlFSVtUMqjs6uLffuOMzaZdQsSz+Oatev4yOa1nB83NNbXcKr/JNoqCqWQoaFRgsDVkFMJHyUg0Bo71SnoSgJSeUxks0xms0RRHOitRYcRqIRbLFiNryzF8kthLVXV1WijkJ6H8pIsXbaMT965kZGiorqmntEDu9ARFIOQwcEBgiCkFEZU+ZYwKlFTW8ONN9/Ihf4k1gouXhynuqaZO7Zvp70tQeC101GXpFSKqLEwMjJILpejKqFJ+B5SGpTwiaIiSkBkXZZGRyGJZJK2tnZGhgYZHR1FG4OvPOrr61mxchUrV6/B6pDjh99Beoo58+aw7dbtJJNVnD17kccff4KJ7DipZJrtd9xO56wOvv2Nb1AsBXieQmDpHxhE28v3FgAgZVxOMMyfP5fbbt3GsWNHOXTgEEZHHD92jMNHjmOEx02bNnP99Rs4e/YshfEJrACjI4RQl6suVFRRRRVV9AG64iUAawWNjU1IITly6DBCnmP+vHak8mhv66C5uYUnnthBECk+sv16QJDwfSYmcjz8j49x1eIeFnbP4eCBOgaHhlkxbzads+cyb+EaamtSKCFRUvLqy69wcWyMOz98NzuffI7DJ88TBAGvvrqLvv4sH/v4x9j51MOcHymwbs1aXnjmWfadHuauu+9EAVJ5GFxDnEUSRgYbRRgdIaWbbzdaAm4E0GpNVVWG9o520nOaGB0dYXwiS7oqQ3V1PU1NTRSGGqitbyA3MkltfT319dVUV1XT3NxEff0Y2VAyb+EiXt+5k117T3HTlq3MwU1GWCRSOCOlyFqEUiTTPtl8jqqqKlo76tm//20mJ3PMmteNMIZ/+OFDyMws7r97K0LauKN+etohigKMEQ7OI8utfAKtDVJCsVDgrbff4vSJE9xwww2A5cTJU5w5c4ZjJ06yZ+8+dBSSnRhGRyUOHj7E/kNH8FSKMLQoqUgl0ty08UauWrqMf/zJQ6QSKZLJJGEUIqVi4w0bqW9o4okdTxAE4S98ZtxIok9LcyNbtmxhbHSUd955h5raGiJr8ZMpMrUNGBR1dXUUCnnKoAQRt49eQZhlRRVVVNG/GF3xDIBSinwxz9mz513jmxAUC0WGhkYYGBji0KHDXL9xI5O5kGPHTjAxPsms9k7W3byS6voMJqhh956XGRocJSicZPHKDjZv2czJk0UOHz5PNldgYnwUnSvxxrv7yUWSVStXMTheZGhoCF3s5a23DhDaDNddt57+53ay87XXuGnFchrmKS6cu4Dt7Scolujr6SOXzWK0ZKBvkNTEJFJJB/2xgBRIz8NYGB+fQCmPO+68g8Kk4IUXnqWnZ4CuxSvYcsvt1NakWL58KUkPHtrxHAsXdbPh+utIJj3WrF6J9ep5/pU32P/uu9xz80qq2hYyOp7j3NBFwtDt/icnx8FaRoZHQE5ihXYTE0LgJyTXXbcOWRzg6NmLDA8NsW3rbQzlJGdPnaZUisjmcvT09CEEhEHI6TNnSWU8RODm8Uw8NSCkQCrBxMQE58+d49397+L7iqVLlzEwOMSePXucl8FdHyYo5dnzzmtuRw5YY4lshMCVEQSWJYsWgTFs3LAB31M89/RTnDp9Dt9XNDU20DZr1geUANy8QnNTE+1tbRQmR/nQ9tsZHBrm+Rd+xqJlV7F85Wq08Bgbm+Dll18gm8vHk5RlmuEHgYwqqqiiiiq6nK64F8BX//3X+W/f+kvyepKACRBVWF1ACo3VPkpJUIZIS3xr8K1GiwwlG2JlhLQ+UkVYLbDGw8oSVnlgavHtGBaDMT7VfkjBOC+ADIpQpghtiLJFhJQYWY0qTRL5aYQ2JK2mpJIIHZGhREkmnbkNAVqkSUjwo0lCk8BKgxYR1iqsFQgviZQprJ3E2hBh0/hREasMgUgiEikoZMkIjcKSsxLtZUBoRFQiaS2hVVgvjRUGFeUxXhJhBemoRCQTREIhKRDiIYTEp8iqDRtZuXIVTzzyU8Zzmns/tJ1aUeBHjz5HvlAAHWJkFb6NwAaESqGkJooEWiWpEiGEhoJI4OF6KYzyENKBc7AWgUYKMQ0BEq5hESHx/AQ6ijAmQHlgtUUIhdECa2NTIekGAy0W35OEQUBCSYJII+PFS2gMnvIJZ8B+puBCXhqBhCBh5QAAIABJREFUIOkLIh1hjcFDT9H+NJ5jEEgfYwQJijH0SKLNDG6jNTMokBYlpeMp/AZrAxUvgIoqquifs664F4AkQmEwuuTm83UBJUEIixAatEEbDSi0tRgM2gZuOt+CEQVs5KOsRZB3JLnIgs0TSRPP0vsUo8B5AUiIogijA1AWacFGBmMLLnCEeaxUFGQSTAAETAKedpV6hwoICYwgsALwETYCQjCRS5pH1g3DS401FmsMQgi0AeELbBgiYwe/qXBjDEhia1yDshEmmkQLiKQEUwIDWRSeKSGxMYYoQHkSIxR9/YMsLmnuuONeclGEIuTtXXsJSvkpsxuhDFHoJvQjE2FM7AUgCgRa4SMwFONzC6wNIPIcHTHePV9CALQWGwfT8ugfgA7LT+Z4A0LE5RNLPJanKJUilBCYSLuxQ2uJjIMbRdrEbAIoF+wl5RYLg4wikAkiARLtuAR4WHx8UwQTEYqkoyBq8H0focEajbQ6pjnPWF5YgVKe+1xUVFFFFVX0C7rCUwAOg4sAKSRGCqRQrqYuDNZIrOP/golxsmWC3SXM+UtAwEx5AeBc5WzMDJJKYOLTSanQRPG1Rex9+56bmzqvfc++UL7nuBkBUcz4qZhAh5DYCKSKTXCEdKl6LdwxnoitdwVCX3rmKRzwFLTn8l4AUsDFC2d59sknqalqIJQBweQEhYFBQqvjar5w/H1hZ4B2ZjxZmTg4FRdnsA/jUge4so0x+lej6c04xhjjxj6lcu+DjKvyZX+DGPJj42M/6KRaG4cMtsJlcLRxjZjWTi2uQMTeB6Ajt4h0Kwh3LYtDE3ueIgwrDgEVVVRRRR+kK94EiJAYaxxaVym0lhgT4vuWwJoZs9vuWDFVG44Db5nGN2O/WPYCcIsLN4MuhcQKlwoWwiKl+5oos/WsAhP9ohcAIh7IuxQF7P4/jbyd+o6UgERJhUA5Ep+U07cVByBPeSirMeWsgZRIDJ6SKGGIzMzzTu9Uy6nwmV55AvClJDIRg/0DDNlxrF/As5aklhhB/Lw+2kZIzHRKfQoFXD73pU9Z7stwgZt4dBOElW7n/2vKWmfOI8vnxAVoEa8DbPmFeh8JBEoqEj5E8dslY68DAKsEYeDeZ8f7EbHNsEEKFZ/bURndvdip837woqOiiiqq6F+25C8/5NeVQHk+nV2zSSXTCCTNLc3U1jWghERO7RbV1GLALQjKAYwZu9lyWLNT6FyB4Nrr1rNp040kEz7TZkKCTbfcwk03rps6/lKVQbbOqGc6NIr43HKKeT+dqI6PF5IlS5ex7fYtVFWnp7ronR2tQng+933yPlasWIqQjuU/q6uLuz/2MT73O5+jq6trOuktpr3rBQI1db1pqA0WbKgR2h0lIV50OOc7KwEp0MI66JAsR8tyiJ+ZQbHxtaYy/uV0BletWMENN92IEPJXa6K7zCFCSNrb21myZCmzurqoraujTBuUwr2vv2xhIWLiopdI0Dqrg+qaGhfMjUUISUtrC4sXdTNn9mwSCR+Lcx2cNWsWCxcuZP78efh+AoTzJQiCaMqsqKKKKqqoosvrCnsBuEau2qo6vvCF3+PBR77PiRPnue++++jtOcGTj/8cHTlYkFAKGwQxZ36mF0D5z+WxtfLXBFIIrNW0trTQXG3c/LdwsVEbw6yuLmweLCq2oGXqZzEapEIiZngBlJcPKi4yuEq5mVnLRyCUR31DA23tLSAkUoLVwl03Jv0FQUAYOfc/LAwPDLD77be5e/tWamurAYkpr7esiZvtQFowUzkJE+/OBR4WI5XLW1iDFR6C0N25tURauwsJz6XNZzwt4Jr0KDsUxjcVewEIKRFCUldXS3tbK0ZrZ+NrzGUXAuI9Xyr/tQwUWtjdzeJFS8jl80gT8sJTTzAymXNgpDij8/52gC5743k+K9esZt31G+k7fYQnHnsMYyVds2ezdcMafD9JuqGdXa8+w7t732HB/EXcdOMmwiikvb2FHU8+zqHDh/E8iEL3PDqqZAAqqqiiit5PV3wMUEhFJlNDdU0NrR1t9A9NUldfT2+vC8Sz58zm+ps2UFXXxKG9b7L39Tcw2mPl6hWsWXc1vpfm0LvvsuftPSxatBSZ1Bw8cpJEqpW1V7Vw8MAhJBbfUyRTKVatX838xhZ2PPNzfD9BqDz8VJotN91Kra958rmfI6TizttvoaVrPj3nz/La048jMjVcvXoNvqfomLuE/p4zvP6zJ8lmLUq6gGVwneTSukWAxXL79ltpqO5i7xs/Z9/BQzQ0NfOhD99DgohctkAUuV15MQjou3AhJgFKrJBImSBdneLmG69l1pz5TI5leWXHPxLYBItXrKKmyqNrYTfDA/28/cIzjOQiFi6Yx80334BNN5IQIacPvcWLb7xL26x2tmy+GZVp4OCunbzz5uvMnTuXuZ2tdHfPR1S1cPiN19i7+x1AoQRYoTExNMcKV5eXUiKk4PoN19HY2MSLL72EsYLrrttA9+IlXDh/nldfep7sxOT0wsiWU/+GSMPO13bx2mu7aGlt49P33UtTYz2j2RzpVJLV666lqbWVxx55nCj6RRSwNe4cyxbOo6OzC2stdfW1lLMl1228nkJ+nEcfe4Klq9azbt1q+nousGXLFk6cOM0rr7zMXXdtZ8OG6zh37jTZXA4h3lvIqaiiiiqq6L26oiUA14gl8HyfsbFxEokEK65eyf4DB/E9n+rqWppb2zl77hxnz57nuvVr6e6eQ3trK9evX8/Q4CB7du/j/IULCCGZO2chCxcuwPd9qmsbWH/tanzfp5zmXr9uLddccw3Hjh8jijRhqBFCsG3bNubOX8CJ40exSObMX8jo8BAHDhxk/sJF3LzxWqoy1dy8+RbmzJ7DqXMXaZs9ixXLFuApptLHQjh2vjYujb6oezFRFHDixAnuvfdDtLc3UQpKvLN7NzW1tXR2zgLA9+LmtDi4umSEQPpJ6lvasFHAgf0HqK6p5fatN5NOpVi3fgPLly3j9LnzNLa0cPXVy6mrb+Laa9cyMtzD2TO9NDY2UirlSSZraGnu4OChA5w4foqbN99MQ101jQ0N3PWh2xibGOXUqbOsX7+WmnQC1ych4p5ACcKVLhCCdDrNxo0bWdS9iL6+XqQQrF9/LfVNjbz55pvU1deyZvVKlBSoGJAkhMDzHMNfKY9UJsPCRUtY0N1NoRgwNDwaExsN7e0dtLe3/9ISQ09fHztfe43+/j6H9hVQXV1FU1MzY+NjzJ+/gO6F3XR2zmLevHl0dnYyPj7OihUraG/voLOzk1S6ylkIK4HW+oNaDyqqqKKK/sXrnwQElEqlKJZKBEFIa8ss9u9/ixXL52JxgJrOubOpa2inpqaautoMg0N5isUcLc2N2ChFz8WzlIIAKX0QBqRL97sUtUFYy6pVV9M2PsoPHnyEvpNnKGkfKRXrN6zn7LlhfvjDxxnvPUkkM+TzebquWkjRq6GmqopZrc3sOXaBsck8b7z+Jid7x+ho30p9bQ0q7su32NgLwO1EI2O5cLGHV195nYmRiNtuXkVjYz0Xhi6y/8ABVl61BBHXoCOY6sAPgwBr9NRsvTWWxoYG6tpqaGptJekVAMHEZI7jB95g37FT1NVspaGhjnR6lLq6Wvbte4PB8T4WzWtmbHyYUjHE95J0zGrEr55FZ0cHyYSPNYYLF87y3LMvkart5MarF2CMxlcpVw6IRxiV8sBa0qkUS5ctY8G8uTz6yCPsP3AAz0+wePESEqk01kBnZyeN1R573t5DY2MjK66+mkQyxcDgMG+9vZtQO7OeBd3dNNQ3YIFEMgX5PMYYnnv2WYz4IFCPsz/OTmbjsT471cyXSKbIZDKsWbOG3p4+Tpw5TU1VRCqdIpVKsWHDBsbHx9j37rusWXP1JWe1FjylMPoyBkQVVVRRRRVd+SZAt1sWDA0N8/bu3fz8xRfJTmYJw4jqmhq2bN2Cp3wG+gcIwhCBYmR4lCd3PMPR4yfp6prD1q1baGxqwFpBaCKQHspLYExEwpNEOmRyYoJSqUhbR4frBrcQRhGjo+MuC5FMYi346TSbNt9Cc0MdQ0MjjI2NYSKNNoJiKSQIQ4IgIghDh8u1GmP0VGMeVoK2CAuTuRzFUolIa4w1+J6HmZHWDqMQa+PRQEBYSzqdwQoP30/gez5r1l1La1M9o0MjjI+OYcIQrS1BqAmCElEYkiuUUL5E24iGpkY+/4Xf4YHPPMD4eI6zZ4dobelg5cqrsTpkdHiMfD5HEERYYwmCPGEQEAYhCLdgstbhf724WdBaMFpjrGVifILxiQla21rxPOVAPJ5HLpdlfHyC3W/t5tVXXkdHEWEYMjk5wfDwCBMTE2hjMMYwMTHB8888x9PPPEeoNbO7ZrkRTWPJ5fMO8PO+CwCLNoYgipCeH+/c3X1OTk6glGJycpIdO57i8JHDRFFINptFSsnQ0CA/eegn9Pb04HmKKIriNgPXR2GMfp9rVlRRRRVVdMXHAJXyaO1oJ53JMNA/gBBZFszrIJFIUl/XiO8lGB4dAZkmnUwgMdTV1dLW0UQ+l6evr5/GxgSe53HhYi+bt1/DyHiejq71NDUajLYkfJ/jx05w6OwZrtt0C7X4vL77AEIIjp88zaFDZ7n/059m9wuPsff4Rbo6O+k//AaFbI66+gbGewW+n0AojzAMESqBFJ7bqWNRUmAkcU+exEsksUBbewerVq2kKtlCT08v5y/0Ut/URGfnHObOmUMyKjI2PMShU+dp7+yis7ON5pZmuhfMZ3hC0zOapbq2jrA4wvjEBH4qhQoFnucjlHKsfKWQvg8CEkmPnv5ezp3Pko2aGDh/GmEhmZBkkkmGByZR1TUkPA+pLIlEgigKsNailI8xBqUkJrAklIwDogvMUkIURpw5e4Z3dr/Nls2bCYKQPXve4dixYzQ0tzA0PIQOQ4b7+sBahgYH6e8fwEskCELtQEiez/z5C0inq/AzGWpr65jMZrEIEgmPO++6m6a2Vr79re8Shb/oBWDjRszGhno6Fy5k9uzZ1CZh0aKFnDjXx66du1i1aDbLly+jsWMeQ0OjHDl8jFdffZW2tg6uXrGCpUsXc+jgESYmsq5Bc6rnsFIDqKiiiip6P6kvfelLX7pSJ4uCiF0vvcWut9+kb7CX831nkCqFMCGlsMiZUxfJ5rK0tDUThoYjB9+l//xFlFfHnIWdNLc1okOfPXveoKenn4nJAOlrqutqOXWinwsn93Pu3HmMhvHRfg4eOcbA8AgN6RoGxybIl4r0XTzN4SPHGRnN01Sd5FzfEL0Xe5jVWItOVnP4wCGGz57k3PAkQWTpOXeafAmEDskPXmB4LIe2MZVPeAiZcNMCQuF5EfV11RiteP3Vl+kfHKKuuY3lV68kOzqCDQtgNKfP99DaNYcF3QuZHBlCGkMhhAsXB5iYGKOjoRqVrubMmbMMnjzG2f5RAgODfefIFgKshcnhXiKhWLx4EYVCnlxJs2zxfKp9y5GTZzFG09LUQKEEZ48f5vTJU5SspZifoK9/mMj4CJ1jaKCPfJBAEmIxGJlEqXgsUMDI8DCnT59ifGyMTCbD0NAQff391NbW0tzSRk1VmvzkGGOjI1hjMQiiSE8NTPrJFIsWL2FWZxdK+ezft5cLp0+4hkELmaoqxiYmuXD+AlpP78inxhKlj8DSWF/D3AXdznZ5oA9rLYPDY1zo6UPpkNaWVsazBXa/tYvx8TF6evpIp6toamxkaHiQN996g3y+gJJiKuvhLJh/c5MAX/ziF2ltbf2NXb+iiiqq6IN0Rb0AitkiX/v3X+O//dU3mYjG0DKPsQmEDZFCg/aQQqFlhDYSD4uyBi1SDqOrQkSMmRXxVKCVGiMkmGqkyAJgTZKUKhBg0EhSFjQpQiI8AhACTQqpC2jlxuQkHkaAMCE+rhveWtDCYPEcrtiEWJMCobEiwNoY+CMTCJHEigLWRmBSJG2AFppQJUElEKU8KSJ8CTkj0SoNRAgTkBYQaoGRKqYRaKxwjYK+cdtVh0HSaOH4AJKI9Zu2cPWKq/npjx8kVzR8/CN3kCyM89CTz1MoFBFGY7wMIoqwREQyhugYsAqSFpSGggBljavFKwEorLFgDaKMIJrxMbBCThH+MBaMRggHZ5qi7llACJSSjqBgHZXQlwJ0iGa6mdKNMk4RHaY/fIBIZFAGMr6iYEICE6HCCE9JSCYIIosMI/eqCUkCV2aRShJpi/J9wjACzNTOX2ARtnzt39w0QMULoKKKKvrnrCvcBGgR1iCEBRvPqVsbE/p0zLjRELP0rbVoLNpqbIx1tUKD8XGutuEU2A4bYoV1QVnGRjAxIdhoi0GDcnP12lgscbpZR1ip0EKAdYGyBKiY2OcwAyHaEJ+w3AbINNJWRy4YSmd6MxXM4sWK1RohBdYIwtjdDmud8x6uEU1gHXpXgJESiMBCgMKzGlkeXLMa5Suk8Dh65DCz2mfxmd/+XXI6YLT3Arte2kmxVHTeCvFrbmKykbEu8lsrQEQYI3F+fRojYr6ijcmIVkxR9IwxXJIsty7YW+1KBpRfpzKrwMYkQimxRrvTGYuvFFpHM1gEHxx8LWBNCEZQLEVYXyCsIeF7CGMpBQE2bhK0OHKhh0MMRvG9aRPF15rub7BYVGUMsKKKKqroA3VlewDif3ytsCihMFIiDChP4itF6Px3XNwpc+rdV5jJ5iMGAU8HpTjSA8pzbnQA0hPlmIrn+c5USIDnCS7xgLEwBRqaAaS5FJJbpuiZS75Tvl/XVGbxExKEhw1DPM+NuiHlNOLYuueNjAvKAoOSjkM0fU079fzlxcbMqwpjkUowNjrEU0/sIKEyaFXCBiVktuiyFtaiEGijUTNRwDPvvRyAp8GKU3+RnucWacbg+37cQHd5UM+l53S/GWPwfY/QGJQURMYgpXCgJ371OXwhpFuLWMAYpHBo4EiHGGtBxv4PLm+CEJJIG+JeU/e6SxEvViqqqKKKKvpVdUWnAASQSmWcY1uMay2naIPAYOKg6GKfQioVA3FhKtBMBetpk5wyw1ZJgTUuVLqdN47uJ2Tcue92tVEEQvnxTZWDezkCy8s8tKMOun3mpZ51ylfxPL9EeQqtKfvPxHa07oESiSSe59ZT1hiE8pCAcoPzly4rZix+ps2Aphc8xoKyIIyhkCswOZ4jl51wUwLW8f2U56NkJra7nRGkrTPRxcr4fGbqvZlCDZcDZhxFIx1N8fsvL3vJewJlAyFDMpnEWKivryeIXKp+5tLtl8kaje95pFIptABjLUHcLOgnfFAKbbTrHzBu5y+lIJV076+Osy+Vmf+KKqqool9PV3gKwFIsFfGkx8qrVnGq9ygT40UWdM8HXeTimYF4pt44k52ZZi3v4wUQ5+gpM/KV9Nh22500VUU8/vSTjBciF6g9n3s/+TEoXuCRR59jegKsnMK2lP0ElJ0Zzty53X+aS3e8AjfCr1h37XV0L27lqaefYGQwwvnQSJTysH6KP/7jL7L31RfYufN1QgPzF8znlu3bmNtWz8M/+D77D53A0e3KwdSFSS/OdkxlBoR0xjqRRioZm+porJCYSLsjhUVjiGwQ1/QlROWaSNnoSMx4jtggKV5gCeFq6Ndffz0tzY08ueMJxyv4NbLmWpdxzS7VXwwCNt6wkb6LvVw4cxZj7CVZgPfLCgjlkvXFoEQqk6JrThfh+CR9Pb1EYUhTczPdsxfgJZKUhGX84hn6evsIoihuZhTo6Fd0MqyooooqqmhKVzYDICTaWhrqmvjDL/4hS5ctpaGxgQc+/QDrr1uL9Mpe9bGXfFx7FpeUAGZu5cSMv7vACCEJT5FMJDBWTvvSa0MilcTzExjrxfz7Geew5aA7nQGwU9kBb+rrEjfzP7WhxpkbeX4C6SmicNqSWODAOkJrXn7pRU6dPovAjdidOXWKB//+7zl3/jyep3B7fYmzsHX3JUT5XgTGWd1NPa6nFJ6QSAGebxB4Ll0e1+AjrbHSOMthO/1KTb1iM0bgRNlXoZxOES6jIWAq/a/ixcZl39f3nhs3FSGERxgH33Xr1nLfJz7BzZs2IeWv8bEyDuxUU1XN9u138OkHHmDrli14noe1lgWLFrFmzVrq6xpIp9NIqaaeRRvXk1GJ/RVVVFFFv76ubBOgAKV8Eokk4xNZ2js6OH9hmInJLMVSCQOsWHkVv/v7v0N9SyfPPv4gjzz4Ywoljzvvvp2Pf/Ju0ok6nn1qBw8/9I/ceMNmVDrkhRd3kqmZx4dvWcpzz/4cqzWeVKQzae69/7dY172Yr/w/X0cpH6s8kqk0v/v7/5qOOsl//to3EELxv//p/8yCFWvZ/85uvvvVr5Csb2X7h+8mk/RZce1NHDzwNj/4xn9lZFTjKYuRAmM9tLauPo4kjEL+l3/3b+ieew0P/+CbPPXCi7TPXcif/4f/SNIEfOe/f5W+iz0YLMaTFHM5giBACA8rFMpLUNNQxxc+9wmuWr2B3p4+/uorXyIQGTZt205zY5rVN9zAyeNH+cHXv0r/RMj6dWv5/Oc/i1fXRUIUeePnj/C9H+1g4ZIl/NEf/i6J+k4e/f7f8vhDP2H1NdewYvkCbrppI8nGuTzxw7/hiUd2AIqEEkQWjPKwxi0goigC4ex777//frq7F/LNb34LbSyfeuABbrx5M+/u3cP3vvUNhoeGXHOlFRjrGjhjrACzumazZdttPP+zn9HR0ga4bFAqmeQzn/ks9Y2N/MVf/AX5Qv4XPjLWWKwSLF68lKGhYU6cOEG179L7QnlExnD+4gVe3fka2UKWlHXAo3KOI9Ia30t+QA9DRRVVVFFFl9OVLQEYi7GGRCpFsVhEa8MNN97EgYOHaGvOUF/fgPKS/Of/8l9IVzXykTtvYsVVi+gbgu758/n61/6CkycuoIMCaIvEw/fdeT0vQUtzC0EQoZRAKcFtt26lKpPm//rK/0224GrHvqe4/9P3MzI8wg++9bcUI5/Fy5fwP773N4zk/5p7PvoR7rh1Cz97Yz+ds+dyZP9efvKlL3PDxlWsXrmMl189SIRr+DOinKJWSClZs2Ydjz36MN87+WP+9F9/lkPHj3Lywjn+zR/8AZ+4715S6QzaQjKZcMHVT8TMfBeYhJekpqGRF557nm//zT+wafNWPnr3h/jR4z+jpb2DMD/El/7PL7N+7WrWrV/Hm/tOc9WKpXzzm/+d4Xwdt99yLa+/9DLWJjGR4H/9t/+OqroufudT9/JGUx1aa9atXcV3vv3X9E/AJ+7YRH11kmJOYqyZGt8TCLyEj+d71NXWc8899yCl4Nvf/g65fI5tt97OiRMn+O53/ppt27awfv01PP3UCzhzP4EVamr0TyrF+us28MYbbzA6OkJzQyPGGte5b+HChQtM5nKE0S9CgOJPDVpH7N33Dn5tmo6uNrRMuHvVmqgUMHfOHKLrNMO5Cc4cfJd8bhKFdNx/Kdy5K7G/oooqqujX0hX3AvA8n4SfIFfIky8UqKpWDPT309G+kCCISCVTfOJTn6K5pYskkyQ8yeT4GBcvnuOuu7aTm5A8seNhTp04je+nkKqIG5kXRFGAiPG2mzZt4ei5M3z9G9+llM1R0opEIvX/sffmQXYd933vp7vPOXebfQVmBsAMgMFgJxYCBEmQ4AKSIsVFErXajsv2y4sdJ0q92JV/stRzpd6SVCV2Esvl2C+xY0WyaG1cRZEUQYIkJG4gQRDEQuzLYDAzwKx3P+d09/ujz9wZgKRiVeCy3+P9ogCCg5lzz+176/avf7/vwj277uPdd4/xnT99DFsOMUpRLBT5tS89StVvpr2tmTMTZ0Aoxi5P8eYbb3FlsooQknTgo4RAJ1xEqw3OIMCdng99cJj3Dx6hlLfk83ly2SzWTFK1Gq1jpLAEviBasBvFUewIbEIhkAgL996zG7+5i8amNmaPvImwgompaQ69vY+xkVHCjTENKUeSTGfShLGmXKyiPA9tNGFF07O4l/s/cwsyt4Rl7blkuCE49P5BDh48QlNHP9lsiigK8VUTmAhhLWiL8h2fIJPNsmXrFgozM/zpn/4Jo6OjpNMZli1bxuLePrZs3UZnRwuj54+z75WfsWRJP3fffQ+pbCOnT5/jiaeepm9pL82trbzyysv0r1iGUIJ0Kk2hXETrmJdffonIGHT88Sx9IQSe8jCxJl7AQ5gjho6OjnLw4EFSmSwbN21iaXsje37yEsVKxXEYpfyFVAd11FFHHXU4XHcr4GrkSHljY5fZ8+IepN/I0p4OqtWQrq4u7t59N3/1/b/kzLlLfO0L9wAeM9Oz/PAHP0I9K7jj1vt4+OHP8vgPHifWUC4VsVLhpbJEYYVMyieOqux77VVyne3csXs3z333BwgE+XyeV/a+SvfiAXp6+7hwbJxMUwuPfvGLvPX6T9iz/0PuuON2BtKaKIYwcptgOFYgXyziG4vRkZObKRBSOt8BbbCxplyuYNFobdFGk8mksVpjjTvxFksVqpElErHb8K0hk0mjVEA6ncYon1133sWBd95mz2sH2bbjJm5b2U1sLFFsyGWzmFgzWyjSlJFYoeletIhv/PEfcO5SwPf/8s85cfwiA0M30d3VxX/7sz9nupThH/zK5wmjiCiOSKUkQloq5QpRWEXHrk2ucEFFkRXEkUZ6kkq5wttvvUU6CLhj1y7GRh25rlwu84Pvf593DryHjWNkHOJ5lqNHj3Ls2AlCbVEqhUGwdet2vviFR/n13/g1NFUCPFqCLP/pj76BlIpypYJNpH1Gf9SVzxpLFFaxCDLZtBuZZFNOAmjhysQVpkYvI5XP5fw0n7/7Nt568y1KlYqzM7bzZMQ66qijjjr++rjuHYBUkKJv6VLaWtsw2mB1iAQymSyZTI78bIGVq1axbtNNrF67hHNH32dRVzf9Qz2otKSltZXxsXGKpQqnTp/hC790FyrdQPeiG1ncladaiUmn0xQKJfa8/hYPfumrfO6hR3jhlddJpdMeCXMuAAAgAElEQVQUSzN885uP8dtf/2fsf/FJ9r59GCUVy3p7uDPbzW233cal/XtIp1Mozyefz+MFGVKpDAanZfcERAlvUCiFl86CEKwcXEG5uIuWXA9nzpzh8OHjdPb0MDi4msHBQdpSCmlC3jz0IUtWDrJiYBmLFy8mWr+WfKg4OTJBOYxYv3YNJtPBDVu24Y8cI+X7KM9jemYW4QekslmMrRCkPY4eP8arr71IVXQRFyZobmokrBZoa2lmy6YdBM1LWDEwgOcJspkMxeIs1kIqkwUs6YxitiDxlHMIdJYKiWG+tZRKJZ790TN84fOf49777mXvK69x5PAR1m/cSKahER1WGTlznCtXxogiTaw1mUwD1VBjjOV73/0u3/3ud7BSs3bjWm68YTN/9d/+O9lshiiK+fo//jqLe3v55//in3/8G0Y6JUV3azsr1g6yZs0amqTH1q1bOXLqBI1tbSzr7kV6ASvWreHNN99iZiaPU5QKpBBYW+8A1FFHHXX8oriuVsDlfJnf/9//iP/2ve8gU3D83Psov4GML+jsamJ0eJrevl6W9PeSL1SZvXyR6tQEqHZ6VnSTyvlE5RSnTr/PlStT+KqVlWu7aWpv58LZKlk7yvDFYdo7emgMYk6PXKKxo4vlXb2cuDBKrrkJHU8xOnqZtq4VrOjIcejMCA3pLFsHFzNts4yNXKKhfJkzeU3Xkn7Gh0+TD1Ms6WkjUxnh4ugsEZZQGIwIEMIH4dHevpj+gVYaG1KUC3Dqg3eYLRVoWbSEofU3QDlPhpDZqSnePvQhiwZWuZZ4tUAay8XLJY6eukBLWxPbhhZTEmkuX56ksXCZE+MFWnuWUZg4x1Q5pqN7EY3kSTW1cceddzJ87hRTJcXm9UNcOXuUH730Fn1LltDV0cJ0UUBpglMnjuI3tdDe6nP23CWMbGPtQCuXzp1jspzFE2UMmlilkFJhbExHWxtBoLg8PkZbaxvdXZ2cPXeeWBtWrV5NU0sbcbXCyNnjjI1eQhuBRREbgZABFkkqHVCpFDDS0tzcQGdbKxdOnXXkPD9wIUmZDIePHHZxzlfJE0F4AdJCV2sHy1YPEKRTyHKVcrHI0TOnaO/qZml3L0IprkxPM3LqQ8rlMlFyLQvYJGZ5HjVNBX+b9kB1K+A66qjj7zKuawFQzVf443/1Df71n/w+U3EBKKG0ISMERkBVgLYGITyk84zBop0OX4iromA/7rYkEmQW4wV4ehoMxGRAlfE1pAgoKIPUEQFQ9dJYHTmbXaNRQuB7kijSV9nn1B5JSLAKhPMDkNbHyhiLRRqJFU52Jq1rnWgCNCmQRVBOnhfEEkGaCIFHCSMssZCJ6cA8e/1aWV1CEwSEyz7Acvvtt3PDDet56qknqIZV7r//XqamZnjuxz+hWq1ijCXwM2hlMXGEFBIlJVE1dF4CtTW0GCxSOXWgjEEjMMIDknGF8AhMFawzUfbBZQcgafAtFZuiYtOgSog4JDACLSBWAsiC9vHMFIFnqcZzjxo4xwMZAgrIIa1BehViEyO0AiSGGITHfCs/RllTs/PVgBYS8FGeDwp0WAU00ppafgRYpHQujJ7n1QyF/rZQLwDqqKOOv8u4zlbAFq0NGo1UCoOH1S6eVkqJtQbheUjhIS1YEzPXlQZq+nFjPjorTh7BEb+scQY5wmng3T5nEVKAsUhPYCOD1ZE7b1qL57lTYvwJZLR5nfz8Y1sSadnCr89Z4ZK4AGKusi7QqORXhMGiawfeayx1Fz6umPNCcBI7TymElLzzzn5yuQxf+9ovEUZlPvzwBHv37iUMq7UNz1qDCWNkysNEGqENnvKQUoA2Nfa/lBKtDVIJpLR84hIvvDOhAEUchcQYlyxknU+ClBJtFhgnSYUwAq1t7TW11/g6WOeqVMtQEEJhrV3wvdf6QHwUc46AWItSEozFk7iuhjFoYxAk+QZJ3kQdddRRRx0fxXXnAAg5b+07t6ELkRjRJHAf4u5jXylVi4mdO/1/0ge3EE52NhcQlAo8ypF7DCklkY7Ak7XvFVImBYJBG4uXdBpivdBAd+FZ3LrTv3WGPVZoqMXKzrnNyeQ8DQKNS/aTzIXkaHxA4hMRioVb/idsRAI85blwGyFRStY2xUqlynPPPc9zzz1bs0MWYm7ztslzcWE8Rs9veC7cZ+4+Xani+x7CzEX5zr8aYq6+SbIMEqNlDKCNRCoPISKklQhrsElwkbQWX0r3CNaCifE99zStnnu281u7u1/wvBShKeH7AqkCwmqYcPg/Sub7+HJgfh2lkElAVNIpSKyNLS4V0RU99YyAOuqoo46Pw3WnT0vpomRNGDkGuXCBNdoY55VvDBJBEMx7uc/9XFdXFx0dHZ94baUUWENrRztNzU3Eem57ozYDDoKAJUv78H3lZHxYOjo6WLpkKYsWLWJuVHzVdnyNEb4QEoFKXIKl20wliZWwqJnsCWxiH+wih5UBkumzTIoEd115Tcs/uWchktwEaGppJZvLYkyMtdrNy42TPArhyG5KOX8C19Hw8DyfOW9fG7lTsU3+XZsYKcBP8gmq1QijNVLMJR8kP7rg79jEx194WOlhhE9jaysdbQ1gI6xxqYauce/GKlhLW2c7/cuW0LuoA2vmnRvnF9Tp9YVw8b0dnR2AIo7dWMc9vk3cGhdkQFz7OqERQuJ5fhIKFGGMxljX2fGUIJ0KEALiOK4VlHXUUUcddXwU17UDIIQgjmJ8z2PLthvp7uugUXnkx8c5dvxDzl8eR/geJtQu511IhHQntVwux8MPP8zExASPP/74x57cjDEo3+OhRx6heOV9nn9uH1HVbaKeUFht6e1bwt//9a/xn//g31GcrCIF9PcPcMeunaR8n29844+YzecBsIn577xV8Ny51UUam9p32YRMlpxJ7TU++8Y1DdyXXRiPmft3KxBWoXCD8YWhQO5qgqamZu6//wHGx8bYu/flRALnRhrSuqAjz1dobWrZRsaY2klfSoW2GuV5LF/Wz+pVqzAm5vixo5w6fSYpnNxJXUqRZDBcbcK84EUEvMQuOGBwaC1DHTFP/Og14iQqyVpwFDz3a2hoiHvu+AxZM86/+be/TzmMIPE8cLFQbl18YRkYWM7OO9bwxA+/x/iYwU8yHuZHKgtGBle9+nMGAZY4rDI4uJLBlQNIYTBRxIkTJ7kwPEIYRiipkEoQ/S1zAOqoo446/i7juo8AwG1O+UKRtZ2rWdrWwZ6jRylXyggJQSpFe1c7aZWikJ9hcmYSgFwux5EjR7h8+fInzm/nInc9pYiimO7uRUQ2x9jYaUw1IpvOkk6l2PPiyxQKldos+J139jMzPcGdd96BtrbGHA+CNK2t7fhBmko5z/TEOF6QoiGTJuX7yEyO4swsxfwMBo+W5kaacjmsVPg2ZnJ6lpmiobkhoLmtCyMEkxfH0ZEm09RCmoiGpjaszTF7+TTVqssotmKeaSCkwlhDrGOiOEIpSUdbG8YIpqan8DxJe3sLnu8xMzPD1NR0bY2FkG7zTFrf/f0D3H//Z/jg4EEaG3M88MD9fPOb36RQKNXWb4GbP0p6tDY30tDUQhhD6cpFqlGEkj5t7e2kcm0s7lmGb0fQxuIHPi2tjbRmUlQLZSamJgkxvL7vVUQouf+Odck2LUEo0qk0nW05dCAJi0WqsxGVMMIiaGpuI51upDx1mfxMhdhalO/R0tpGpVymWJi5ugKYqw2SPIOVKwfp6m7nxLEjhNUqxWIJmxRxWutaRHOdA1BHHXXU8fH4G3AC9NBac+r4cToXtyAWlzh0+LCbdacDdtxyK/fecx8pLTl6+AN++NQPUUrx8MMPs3btWvbu3cvx48dRSjk7Xdx4wBiTRL9arBAMDg5w0/Zbybau4Nlnv8++F/YwuGKQr/7m38dEeQ7vfwdbLSdkMc91D1RCOpMKPwgYHFrD/Q8+THt7JzNXRvjLv/hTWjv6ePC+20mnfDKdKzh15ABPff+7zOgsX/7q51m1vJeG1h7agln+nz97jP2Hx3jorhvZsH0TXnsvL//Fn7D3tbe573OP0t1YZUn/WkK1mJd/+Ef87GfvEBqLUoK4RvoDbQRxbPB8n+XLl/PoFx7lxKkz/OTFF1izZojdu++isamBw4c/4Pvf/yGFfBHmTuLuD6SS9PYtZXh4mD0v7WHlin523nITfX29fPjhCaxx6xDFMR4CpKKzq5sH7ruTNRs2EiN56Ynv8MZb79LXv5wHH3mE9kXLaWzMcvKnf4VSkqXL+7nvgV0MLu6hND3Ln3/zv3Nq/BImFvi+W2OMRXgeQmXZuOkGHrn3NuKmNJPDF3jszx9D+Gk6Orv45V/+PKnsWs68/zpP//AvmSiU6eju4jf+19/k/ffe45mnHsdqfQ0HwI03hBKUyyUujYS8d/AgUTVEOZ/iGjnSaNcRmXsP1VFHHXXUcTWuewEwN5MVSuL5LufdWoOQinQmw5Ilfbz44oscfGM/lVKRYqWIEIJvfvOb7Nq1y92U5zYTKWWNSGitRQrh2thC4KmAP/nP/5WqaObrX/8NPnh7P0eOHuFf/97v8eu/9tVEWpiMJeIQKZ3MUCXJfJ6fQhvLk088ibGCRz57F+vXruHCaIGmhhwvvvACR4af51e+fC+LFi1icbOLpP2DP/iP9A6s494dfRw9egzf72Hk3Dn27H2Fvs238Dtf/jxv/PRNQitoa2nkP/3+N2js3cSX797B/rcPoEOdEOwsUjq2v/I9gnTAys6VrFzez549L/Lue4dY3LOIG264gR/96FkmJiZ48KH7Wbt2iP1vv0cmk8X3UwghKZVDQh3T2tpKKu3x+c9/js6OVtKZFD09PXxw+BhSSbQxjoUvJZ6fQfkB7x54j2eee45tN93CmrXreHP/QTZv28o7+/fz2r4/4Zbbb2VVawWRaAiffeZ5SpOTfOVzjzC4apAToyOgPCphhOf5LmHRSqSfplIu8xd/8RdUsgFffvAzDPT1MRaDF6R55vEnGLm8h8/uupG2lkZmSyGlfJ69L7/E1NR0knx4bQEAjkwoibVm49A6WpobqZaKvP7Gm+RnZ9DG8UHkggKyjjrqqKOOj+K6FwBzDVfP850PfqyTVqyhWChy8L332LRpK0NfWs7pUyd47WevUalUarG+C9v/c4z2uTbunCIvjjUfHD7ClYlpKiYkjmN830MbQ5Cc+nzPScOsied/1lisAakUQkh6lyxhaGgNwgvoXtTM8eTeR0aGOXvqLKW4FR3HBB6E1tLZ2cWKFStpWdRLoVAkDmP85oBtW7awbssWqh0DpH2nUogxvPvuO1wenyLdqWnMpsE4Ep7jJjrCnvAdaz2by7Fu3VqOHzvCufPnqVarpFIpuru72blzJ2FYobW1nWw2RzqdZuPGjaxfvwEdW9557xDvHzxEEKTYvv1GfvzME7zy6mGymRSlUiEphGSiWBRoKzEGgkyGrdtv5OYgTXt3F+Hlc6RTknSguHRpGBLfg1AbEB5tHZ2s3bCcJs9n2eJeTpw9h5EWrCCKYpqamkFIpPKxoWFg+XKWL9pM2NpEe2MaE0cYKzl/YZgzZ4cxqgcpJZ5USCyFQp6fvrbP8RCSqOir3lkugxljDMeOHqVYmMGTgp0378DzPJ798XNoHQLCrW19BFBHHXXU8Ym47gWAkgopBFFYxfc8pJKuTY3TgR86eJCjHxxlqH8lDz/4IOcvnufkyZN4nodSqibdEkLUxgC1fHntzGGEtYmOHJb29VIqlYii0PHXrEEpSTUyGB3XGPRCSPzAecwLKeno7GD7jlt48vEnmJic5u999XOOYY9xjH4l0VGEjmNSnkD7Lg74rrvvYPhKmeeefozZfIXdd20lXyjx2JNPsnjTzdz5S7vRQoAO8QLnlx9GTi+vYzAWhLJIm0jt4hijNfl8nr17X6atpZmbtm/j2ef3EIYhY2NjPPfcjxm5dJE41sSxJvB93n77bfbvfxchJGEMnp/iwvnzjCxdzN69L9Pe1k57WyvDw8NY69QWQZClXA2d4E4o1mzcSKlS5b9/61vsumsXN/R34yuL1lUasmnSjVlWrVmFnDiB8tNs2LSZdw78lA/fO8CvfumrCVnR8RC8IE0YGyfTjC2ZlmZuuGET3/7T/8ikhN/8lS+BNRjpRh9KSiJt0Dp2xZA1ZDI5lq1cxfTUDCPD5696X82N/6VypMipqSkmJsbJpHw621pZPjCAUsrREgXOD6CuAqijjjrq+ERc9wIgjmM8z+eWm29jww3raU9nePCBz/Lue+8yE4Vs3nETbc1ttKQaOH7iOFNTUyxetJjNWzYzNDSEMYZCocCBAweYnZ29qiAIPB8jFIVCgXXr1tHe1ke6qY+f/OQFZqbz3LjlRlZs2Uh39yIeevA+3n7/OCdPnmDHjp2sGhyku7ubBx98kHcOvMf0bIGLFy9yy223Mz2bRwpFtVLB2ph8vkBYqSJEQKlYIgotuiHm8sQEpSujlEWabdvXkX/pTUaHz7Fl1zbuffBBTGM745MzxNZg4wpjVyYwUiIMTF2ZIJ1SxBWn23cZNsK11oWgXC4zMT7GB4cOcvttu9h5660c+uB9Tp48xe7du5mcukKxWOLNN9+kkC8m7W2Dp3yslVSrIceOHmPzpvV85jP3097ewptvvcn5CyPOL18IokQaJ5SP0Zor41fo3zTEQ597mI6ODmanRsnnK1w4f5abdtxI/+qQbCrFVKmENppLl8bYsGEjq5YsoamllcrpUyjPZ/utd7B21WaskHzm/t28sO89ihquXLnMfffew0UhMNoQRTHWMxTyBWIdgxQU8wWkdZLFtrY27rp7N4ePHOHSyEUniVz45koMkwI/YP26dQz0LyHwJR2tLezd+wphNUyKTUl976+jjjrq+Pm47lbAf/Qv/5D/87/8B5p62klnwDOGINYMj44QKUFLZyeZdAO+EYxeGmFqdopsNkt3dzdBEGCMoVgsMjY2RhiGtZEAOM24kTk6e3vpyMWkggxTs5oLI8fxIk1PVx+Nvd3EpTwZZbhweZYrly+zbNlSl7SXXGt0dJyZQpHm5lY6F/VQiWLCmQnCwhRlCx25DDOTUxRkikVtzZhqiS27H6S1IcOxgweooPgHX9nJ9773I949PEl/XyfWV0wUSrSKiNPnztPY3Y6NS0xOxgTpHgbaKgxfGiPUBi1AIxFSIZRCImhuaiIOQyrlEq1tbfhBirGxMTKZND09i/B8RaVcZfjiMNWKc1cUwrXyhQwwSDwPOtqaaG1qREoYvnCBSrmUhABJtHF+B1J4GOGRbmykt7sFP3ChSLIww5XJSVQ2R09PL0ZmKBXKeNVJRqfKpFq7WNzbhIpCKtMFZooFpipFepeuJus1kVXTaB1x8vwYZZuhpynNorYc00oQXh6nMl2mINtpbTNMXhkhNq0sbk5TnR1lthKhslnauhZTKOSZmZwAE9fGAI7fLxFeGl9Cb+8isrkcwhqmJyeYnJx0nRYpQcdonNMgJrqmiBDMv+MXZBJ85Cv/86hbAddRRx1/l3FdC4DKbJk/+hd/yP/xX36fWVPB2BIqjskgQAnKWLS1SOUjNWAMRsxv8AstgD8+C0BgRQ7rB/hmGqsXZgFY0jJDnghpYwILVRlgbZzo0d1M2ZMCfZUT4FWKfgQSIxIxm1WoQKF8yb13P8DAymVcGhsBLVndm+HxHz7P8eFZoriEVhaUwqs6xwAtDJ4bKKBtAES1R/toFoCb0dtkLOC+66/vYCf9DEZbgkAh0MRhiEx65nNruvB5euDu63+QBWClxFhJVhoqBIQiBV4ZEUWkrCSyFq0AkQOTwtOTeNIQJlwDg+/Ue7UsgAzSgvKqRCZCaD+5txib2A47fFIWQID0AnxbIfAkJavQcZWMcr4EIT5S+HhRASPSxCjSpoi2ztPBIECp+XURZs5HyVlTs9AI+n8e9QKgjjrq+LuM6z4CkFLWzF9REhvPW+EbLML3nBDeOuOXhRv93Kz/k+xbay58xiT289I59ybacGONO+EqgY0TFz0koJHK5QQYM2dM+1G4r5lEcy6c/S+SsBrz6msvMzV7A42NDejY8IM3X+X8+RGwKWcoZGOEjdF4SMCzGiMWbij2Ex517rHcsgh+ceKa1RqEIgpDlEoIcJ6ET7jOX7c7bpHOFdBWsVaAsqBdGJIAR2gUkKTxuHyGOWvhj7PxsRYhFNq42GVhFcboa77r59+d1c7vP7QxVqVd8SgsOragJCbWeEoRWhB2fg1EEpQUG4OU6uc+Rh111FHHpwF/A0ZAziEOm/yXxNsf58+uk1B6IUTCyJ+f8dfIfp8AIZ2//xwjzFOK2M5lAeAIZZ4jEspaZ8Hdh9EGT7rgHaPnt6i583iiyp83srESKzTWCKT0mcnPsO+1fVgrkdIQ6BiFxdoY66Xc1eIIi4dN7HJjgds4mXOo/7jn5KyTnURPOH97oz9p7/74ayiFNeAHAUaHWOyCsJ6P+X73DNF2gbcObh+fa7VrAcYqPD9A2RARgzAaq1wWgAIQghhH4ENHBM6pOSkC5pvqC7d1qXxiA0pKpHBqAfc98+6E86/NteWAe16e8lDCOE8FKcEuCCUSklgbV2wq4TInrMshEEl4kP7rJCHVUUcddfz/HNc1C8AxsKVrpcYxIvGsn9tWhZRIJZMP5HmnNs/zSKVSbN++nQ0bNvycQkAgpWLztm2s3zCEkM7e1qUCOk/51tYW7r1vN7lsBmsMSkq2bNnCL//yL3HfffeilKt55s/jV+cA2LnQneTvxlistrWsAYF0Wnqo5Qrgp0AIlJhbUjm/cV2TBVB7HNwmqa0llU6zafMWBleudE7Dv+Ak2i445SIkgR8QRdEnpiqK2p9iwX0tGEoIH4SPEQHdvb0MDS7FkzFYXfsuJ9HUSGDbjh386q/+CvfuvtM9fwGIJJQJV2VIYZHCSSlvunk72VyKKE6sjN2TSE7rP69nksQxz4VGeQptLGEYJ7JRsEphjCsUTJzYLSVrGkWRKyKvbTLUlYJ11FHHpxDXNwxIQBiGpIM0d993H//Lb/0W//Sf/g5f/MIXWLKkz+nwcR/GCxMApZSk02kGBwfp7e39xAJgjiuwYf0Gli3rRgiJVEn4jpQgBE3NLWzccAOptIfyPay1XLlyhUqlwspVq0ilUwv8+CXzG7ZYsAUapHCbnZKghEH5fq1oEUIhpEgsfQU2LIGJk70vAvRVE3yBI/rNPdocrHBeBV4QsGpoiN6+vprh0S8Ea8hkMxgd09XZySOPPMKXvvioC1/6H0Bc8z9ujRUIHyEDlixdzpqhVUjhzJ3miwaXrmitZeLyOMpTbNmyiVQw9wxlbS3BbcK+tDQ0NbN+wxoXUiSU6wQw1yGxH7mreb6e+3cpnazUDzzWrlvHb/7D36JvySKkdN2TxZ2d/Movf4Xf+I1f51d//ddoa28BIQiS94K4igRYRx111PHpxfW3AvY9ojjk8KH3ybWkyHR28frrrzM5PY0Q0NHRwdrV62gMcoyNjnD0+FEA1qxZQ7lcZnh4GK214xLYqzkCLhnPpQL6vsfNN98Efjv733mF8uQM3Z3dbNywgWPHPqRUilyanjFcuHAB35O0tbXWWu0CSWNzC6tXr6ehsZGJ8RE+PPI+2aZmFne209iQJde2iIvnzjBy7jxFrRgcXM7Svl6EnyLQsxw7dpKzIzOsWNLBitXLifF4f9/r5AtlegeGkKZIX/8qjGjh2Ls/YXo6n5DinAWwoy4k5L8kxS+TSbNmzWqKpRInT54km82yZs0acrkcZ86c4fTp09esifu5sBqyaNEidmy/kUwmw/LlS3nyyafwPIkxNonKnYcQgpSfZuXyQZb095MvhZw+9DYzswVSQZrVa9bSsaiflYMrMKMHsAYaGrKsWrOGJe3tTIyOc+jIUaom4syJE/S097G8e22iSlBY69He3srGNSuwWY/LwyOcPzlMbAXKD9iwYT1S9TB65hjnTh9BG0Mql2Vw1WomJq5w8fy5WizyQhitERI2bthA5/LVrF27lp+91MjIyBjKV3zhy19i/NRh3nvzfe667wFuufkmfvzCi8TJmEnMGQohqMU61lsAddRRx6cQ17UAsIm7Xaw105cvMzU1RVsqxfDFiyAl6cYcO269lbaWdqZHxlFK1Tz6fd+nr6+PMAz54IMPkFLWrFx93yeOY4yxCG0IgoBtN27l6JHTyOwSBpYv4jv/9c/wVYpUOsX6NWvY9+IeRLWSnGidrXAQBFjrWuWZXAODq1fTN9CPFIqtW9aDzmNUjr/3lYe5PD7CyGzA+qEV/OiJJyiJFnbfcy+zk5doX7yCpe0RZ89fpLuvjZ03DpCPYhat3syWnkX8lz//DttuvYstQ60cP3WR0O+jvyPkySd/TCnUNYtiKZUrBITEWkil02zdvIX169fx9rvv0NLSws0330xLSwuVSoX+/n5KpRJjY2MIIWpdFOUptNaE1So//dlPGViylIGBJUghMa5H4dZQ60QnL7DCo69vKUNDqwiNZcvWDSxtz/HMj5/nhq1bWbN2PSNjMyjPx0qBVIpVQ6vp6+tAxTH37L6b2BjePnIYlLMz1trMufXgZZpZs2YdXe1ZSgFsXr+Wp//qSawKGFixAk+UuDLVzEB3A6Xp81y8PEtzUxMPPPggR48eZfTiRWwcfvQ9ZixWWi5PTHJ2Yj8b1q1GSDfGaWhsZnBoiKe+/WdMF2O6urrpa7bseeU1KvniPC9C2GTzX8iAqKOOOur4dOG6xwEr5drk0nm24vu+I7dJgRKSpsZGpqenOXLkCJMTV2o2wAcOHKCxsRGg5gA45wZY2+ikQAsoVyt8+OEZnnnmJaqikd/93d+irb2N0dERXnpxD0t7OxzLXAinNDAWrWNKxRK+70HZkRGnpqapVo/jpzP0L+1kSV8P50byzM5Ms3fPK5yfCvj1r32G1pZmOloHsVbw4gsvsrh/hAfvHGJ6dpZ81XDuzGucbuUAACAASURBVHmu5AuMmxy/e/8Ovv3Nx6gayflzZ3jiBy/QNbiDX753OcIafAlaCCLtYoaFcm6JqXSKlSs2USzMsufFFzl+6hTLli2jv7+fd955h3w+zz333MPQ0BATExO0tLTQ2NiIEIKJqTxT0zOUymWqlSLLevtqBMjA94iiGG1NUvwIrFCkUjlmCgVOnjlNGGm8VJq+9lYk0D+wjIMH3+PdA0fYsfMWVrdHSCkZvzxOqTqNDEOWLeqhvaMTKwVYRaFYIp1OY4QEFDYyXL5yheJEBd3ayOr+pXQ0tzAaWUYuXea5H79MvtzMI3fvIJvOEPhl8tPTfOfb36ZSqThFB9cMA6ypzVCGz58naOl07oLa2UV3dLaj45jdu++mqa2HQx8cYv3SRucHMEf1MI6LYmszmnoXoI466vh04m8gDMjRwKXyXOtZa8cu14ZSqci+V19l/fobuOOOOykXCzz7wrPk83mEELUQoIV5AHMKASEERlussEgEo6NjlMtVyjr5YE884oVSCdkL5jzlrXXBO34QEGuD8jzSmQxbtm2nsbGFMIppaGwk1hptDfnZaaYnp6hUm4miiJRnKYVVBgb6+ewDD0C2k1NnjzJTKLNoYIidO9dy8coVovZ+pIBYO/LgxZFRisUy1UpELpNCJEQ1nYwy5qRxFouX8mlqbqRYmKVSrRLHMUopWlpaGBoaolwuMz09zezsbK1bMjg4SBzHvH/4GDPFEpVSCc9TV2n/oyjJQjA2WSdBZFyewsCSpdx60w1MTU3T3bOYoDJBLuvhe4LZ6QmQEKQDQl0F6bN2/UYW9bZAqUxnVzcfnj6DnmP5C0ljU7NTYOAhhcfNO24miGcp5tLOiCkKMUhmZmeZmZ4lEjmEAC8x7ylrzdmzZx3LwHy0/T+nLbDGEhpNSjrC39xBfmZmhp7FPRyIIp5+5hnw06zuvQlj4qvoBcKKa7QJVz9GHXXUUcenAdeXBIgjtSFARxFe4Nf0/+Cia4cvjvDCc8/z8ksv0dHZQU9PT23Dqjn+JSRApdRVgS5SSQLPGblkshkslp07dzI+Pk6+kMfzPIS1ZDIZjHbX8jwvIcMJpEwKDGtp6+hk9dp1vPnGm/zsZ2+QyWZdlyKQCXcApGeRQuIrn0xDlgMH3ufihYt88N77/GTPzyiWK6zfsJ7JmVmeeOY5xi5dABkgpcRXkjDWaCGRnu/064labY6b55J8DTrWlEslXn/9dUYuDXPnnbtobGykVCoxOjrKm2++yZNPPMk3/+KbHDhwAGsthw4d4oknnuD555/n1KnTib/B/PrNhSjVioFElimlxCAwVtC/fDmXJyb44RM/ZHJynFTgE0UROq7S1dVGU2sTm7dsJpPJIfwUg6vXcOjQEZ586imK5bJj1FuQykOogMsTU0khZgla2xhYvpw9e17iJy++7LoVOLMkHZuaO2EURght8CS0t7XxpS99kRu3b3dyzwQLFRQ2eR+A4wOk06kkNRImJiY5cvQIlWqFi8PDbNm6lZGRUcrlas3bQYg5c6RrdRm/IPGyjjrqqOP/41C/93u/93vX62I6jHn9hZ/x1uH3uOeh+9m0dSM9nR2sHljB5PQUXibNZx95hN2772Hb5i0cOvQ+h48cpr+/nwcffJChoSF6enpob29nfHycYrF4VTKg7wVoq+jpW8oN65dx8823km3s5OlnHqcwOc1du+7ms1/8Ak2NGdavXkFsFaOjl3j44YfZddvttHd2sG7dOsrlCueHh0lnctx+x510Ll7M+MULDJ85xWypRGsuy9lTZygYS19XB2MXhgmDLNu2bKa7rY3uJQNs27aCM2fOMjY+zc6bt7J+80aqsUaVyuz96Rt0L1nK5MRFLo1OkUq3s7RNc+zD44SRSTT2AiE9hJQEqTSd7R2Mj45y9OgRehYvZmD5Ck6dOkUcx9xzzz1s2rSJ1atXMzo6Sj6fR2td+22TCNzu7k4effTz7LzlFtLpgKFVqzh79gylUhmpFNpolPKQKoW2EhUEbN28nhu33Ug1rDJ+/ixHj50kloKdO29l1ZoNzExNMT16hlNnL2JUiptv3c7WG24gPzPL2QvDXJqc4IHPfYkbt+ygqyXF8hX9nB0eZzZfZXF7M/fcfhOdg6sYO3OS8yfOUDQNtLX7XDhznFDnWNLRyNTYWa7MlmhqbWPNho1MT09z4cJ5rNHXNOgFQngIG7Pr9p3sfuBBmpsaWda7mIbGBs6fH+XD4ye4bdsWbr39TqphzJ4fP0WhWEEpQawN1jruxZx5VHLVv5FBwG//9m/T1dV1Ha9YRx111HH9cN2zAP74X32Df/2n/x6T9VAqxDOGtLXMFgtEvsJLpfBUgNKCUqlANaqilCKXy9VIgVEUUSwWa6fYuc6AsAKrcmSaWsjJIkp5lKqKfHEcXxuaMi2I5hwmLJGVlomyplQs0NLcjJf4D0gpyRdKhHFM4KfI5BqJrcVUi5iwTCQEOV9RLVepioCGtE8gYffnvooOy7y171ViEfDPvv5lfvD4s7z13gUa02A8qMSaxtgwky8iso0oShTLFum10Z4uMFsoEhuLkU4+6OSE7r5SQYDVLu0vlQ4QUlIqlfB9n1wuh+d5hGFIoVC4JiLZYvEARZDyaGzMogQuBtlCPj8L1hJrN36QQmCsxEgPFaRpyCqkUsRRjFcpUq5WMJ5PY64BK1NEoSZti0xXQGSayDVKRFiFakQ5CimbmIbmxfgmTUpOIazm8mwFrTI0SMilPcq+wBYKmCpURBOZbJVyaQZtGmkKJCacoaIBzyPd0EhYrRKWiwhrajQ9g8AKiZQ+0kY05BqQ2RxYg0JTrVQphQYTa1ob0ggvoFqJ0KVJYuNsCeLkGnNGUPMFgONjzNkRXS/UrYDrqKOOv8u47iqAMIzQSaCPtiVUtUpWSoSSlKMQUy6jvBQqBqNjNBpjDDMzMzWy37U1SW0EgMBqTbFQJDTTWG2JbRqUMwQKq1VmRvMoYvLGUpUBWJienkZKizDOvtYkfgSVqEq5NHuV+lwimK66drq0IVUfKrHh7IdHefgLD3Hb7TdRLcecPvwq5z48jYgsk+USWhlQikrVbVq6OI0nXNs9DqcZC+cZ7cK4TUcQI7SbR0dagxVooFisMJcFoLWmUqn83HWXSoH0sMYwOTGBEBbfV1SrEYlTLliRuOYZlNWgY+JKzHTl2iwAiMKIfDjl2vVGooXG2IC4VKIaVRBRRBqP0MRYBfnpKbAZvHgSJQyxBUmFPD6zRWpZANZmUOSpFKtExiB1kdkYLMZlAcQQTudxWQC2lgygASsE4DmHR+WRL5XQpRJ+EKDnTI+E4w5MFzSeKqHjmKwSIC2RnpNdsmCstPB3HXXUUcenC9edBJhKp5BSYKMYodwHt7YW5iyAAw8TG0jUWDXyXsL4B2ryv2vhGOyOMIa1ifxtzllQEOoQpFMiELmBu5AS5hIFhanp76/+6F9oW1szs8diiEJ3Lwfee5tzw2dr/IRoaoJisYi1KYxVrrtgYgyBM8khyQKwQBJF8/FPisT+N3E0RDpr3V8ARmtXVPgSz3M+DFprlJrzFwCuKnPmN7yaIu4aWEAb16VQIknlE4A2SGOBGE8KjJwnMyZOy+6ervEznDNfFsIjMhpPuXa+Ttz6bO3VuNoE6Npb01qDEWQyGaqVCnE1RPkeQkiCwKdaLmOtJY6Nk6QCceL8JJUEKetWwHXUUUcd/E2oALSuEa4cbGJRK5AS4ihCCA+lPHSskcJps+eY/sBVxL+FkEK6k6ByMi4pBcKI2kZhjXVEryQLgLksgEQz7ycRefqqSyeWuM7f9iqHQCM0ComSPmFc5tLIJUC5LACjUdZlARDkwJZBayxeUgCEVEhOrlZ8ZCNzK0NtbWxyv0Ikz+kXOJQqz8OYpHBKMhDMAuOfpAbCGFPzPbRQWweRHI1FLY3QJSIaFEGQRtkIEVqEjsEzzh0R6Z6Bse4COiKlLDrJAriqqBJzbNNEHWIVoB0pc86X0dr5ipD5EuWaXhBSKawxVMpl9xVra4ZPlXLskv0St7+5q0kpQEjCpMMkpfzEwKk66qijjk8Lrm8WQLL5WqzzYZeSVCpds/u1FrwgcDHARqMSxYDv+zQ0NPDoo4+ye/fuT7QCNtbgBT6PPPooDzxwG4Hv2O4k0jMhBD29ffzjf/KPaGnNOR8C5fHwww/xh3/4n/id3/mnBKk0MO/F73rCEqyz6kUsIIUlunEduzGFFElhgNtg9dxGp5IOgPy4bd4NFj5iA8zcKVvT3NLCI498ntt27nTdE/uLbU5Ga/xUiiCVqtn/Oma8W/O5A6/BIqRwUcELsgAW3hNzWQAyhZUpBgZXccv2jQSeAZH47Rsn69TaZS186Wtf5Y//8x/z9a//NlJ6yaVVcrXkwa1BAStXDvG1X3qUjo5Gwkgnq5NYAf81sgAEzjDJ87yaDbTveUgpE4MlSaw1nu8jcN0ga1wOgadUTVpaRx111PFpx/XtAAiolMvkMg08+NVH2bB1LV2ZLCcOvc9zzz/P+yePE8c6sb8FbbVzcYPkA1z83A9nT3noKKapoYGJmZgoBhUEmLicSN+c7M9o1472AheK89xzz3H+3Blu3LoVLwgw5fL85p9MmsVVnXGNFK5AUNKihCX20pjIoIRAKB9FjDUQG4GtFEDGWGkRRG7uz1x7XSDwkqIikUPW1muuZa/xfPdSGO30/7H++DHIx0IKokqVpqYsX3j0y6wcXEFYLfDEE09x5MgR4nBeZunyGOZP2gv6NIi5dRAu70/IgM6uHha1hVhzCKkkxgo8ASo5aRe15ukf/oDLw5fZtbWfwMMN7ZPrSZzqQQmBB1SjkCCVplo1SBXg2RirqwgW3tfHzSRch0ADQht6+vr42le+QnNTIyMjF/n2t7/N1NQ0j375i9y4/SaUVFweG+PFp7/H0eOnieIYpML3PMKoliFdRx111PGpxfUtACykMxlK5SLf+6vHOH9pOysWLeLx73yH2BiEFPQvH2DXbXfQlm3m9KkTvLLvFYQQ3HnnnTQ3N3Py5MmaPfBCtjtArGNkIPE8n+amJr721Ufxsot5+pnHmLw4yvL+Fdz98EOMj1+kVIoxseMBxLFmdnbWsd3juJaa19HVzW2330FbeyfnTx/np6/8hJaORQwO9NLe2kpb7wqOHHyHw+8doBopbrnpJtavW41I5Qj0JD/96Vu8f2yErev7ufHW7VQJeOEvv8OVqTxrt9yK1FNs2LwDLdrZ+8yfc2n0ClIkjoY2YQaYJBlRKqTn0dTUxK5dtzOTz/PGG2/Q0tLCrl27aGlp4d1332X//v1XZSTYpNdtE7vfffv28cSTj7N503o2bdrEiePHMXOcitqIw6U2ZtI5dty4kXU3bGZipsAbLz7N+OVJcpkGdt62i6WDG1jU1cmVw88jgJbmZm697S5WL13CuZNn2LN3L1UdUimX0GGU2A0LhPKwxmPJkl7uuX0HtinF6SNHeff198BPkWnI8pn7d5NrGOT4e2/w3v6forWmsaWFm2+5lQvnL3Dkg4MfmwVgrSCKY3zf51vf+hbFwiy/+7u/w+DgSvbvfwcsPPP0Mxw4cICwXCFNFR0bpIDIaKwxbvRQ7wLUUUcdn3Jc1xHAXCiNMQZtLEoppJRUw5BYa5qamrn51ls5feYM3/r2t3jllVfI5/MUCgX27dvHxMQE3d3dC8x7qCUFKqVcyzzW5LI57rnnLk6d/pAPjhzht//RPyYIfC6PjfPM00/T29eD7wfufK8UWkf4vkc6nXI3KgRNra2sWr2Gc8MjvPraT9m4aQPbbtxEe1s7v/JLX6G7q5n9B45wy807WLKkj8FVG9l+y828s/91Lo2MkUsLhkfGWTa4ljXLl/LMD57i4tgU//J3/wkZaxlct5n/7ev/kFPHP+T4uWG+8uWHaco5YyRtLEYIlPIdqVEpEIJsJsudd95FY0MjR48epbW1lfvvv5/x8XH27t3Lli1bWLFiRc01cQ5CCFKZLBMTE5w5c4apqSmsNeRyOcqVMJFSukOvs0hWGOGzYuUQXpDisb96DKM1Dz38MMLzufPu3TS3tPCD73yHt/e/TakaI6TP+g0bGLk0xl8+9n2GVq1ix/btmNgiPB8ZuLwGd5KXpNu6GBwc4p2332LPnhfZsWM7K/uXIIXHDTdsRsmYt989wODgcnq7m5EWMqkUm7dsZc36dfiB/zHcfIH0A6TyOH36DGNjY4TVCg2ZDJ50axJrN3oqFstEUUwUaTzPGVQJMW8gVEcdddTxacd15wCkEmc2YS1RtYqn3Gw+8JzWHKBvyRJ6e3rJZDI1t7owDCmVSm7WLiVhGKKUwvM8qtWq6woIiZWSiekpvv+DJ3nrzUO88cYbVKoVuru7KZaLzM7OEocR0g2WnZmMEFSrVSYnJwlSAQhBMV/g1KnThOUy7V1dWKCpqREjFIc+OMhPnnuJ82cuopQgk0rRuaiPUqHM+bPDnDp1hkw2Qybrc/70WQ5/8CGLurvJV2IWtzeRCRSlquXxJx7njZ8dYGpihpamJsJqhO+B7zm3QbdZqdq67bztVlauGOCll/cwNjZGY2Mjzc3NhGFIU1MTzc3NrFixgiAIWLRoERs3bmTLli10dXYSlkt4vlvrjo4Odu++h3379gEC31eJkZKHsRatFNlcA6fOnubCxWEGBgaohGXiahmFpbEpx8FDB5mamWJqahKpDErBoUOHKJaK9PX1MpMvgFKIwCkzZianyTU0YJJuRnU6z8lTpwhSaRYvW4GOYzJeQBhZXn9zPz/+8asMXxh2s3oZkE4FTE9O8G//7/+Lx7///Zr6Yh6OfGCqEQKJ7/sEgc+jn/8cE+NjfHj0CFFYZXJikoceeoh/++9+n3/zB/+BpUt6AKcesIlypI466qijjr8BFUAcx85733On2lg7olcYx8SlAs8+9TQbN25i+7ZtpFMB3/3hd5mcnMRai+d5tYJAJYStKIpqf9fagNCkA59pa5FKIrUl8AOqYdWddKUkjBL9e3IeNcbg+wGNDU2EYYzyfJpb2v7f9t48xq7jzvf7VNU55+69N5dmkxR3UtxEStwkLqI2SpZtLbbs0djxGyfOYDCZ4AUJ8PCCJH8EySBI8AYPycMASR6CN2/GNmbGsmTZ1k5REiWSokRRokSKO9lsNrfuJnu92zmnqvJHnXvZ1GJ7DM6DbZ4PILHZzXvvOXUvun5V9f19v3z1sSfQ2jAxUSZfLFCv19EmxhqDwBDFEfVanYynmZwYY/mKHUxv/1Mqtsh7B17j8vAYt6/dzhNbF/HpmTPEnTMx2lAPnaWMThoRarWQfNZHCQhjiIVBSqe2t9ZZE0ulqNWqVOtV2trauHRlEIBSqcS8efMol8scO3aM06dPI6Wko6OD+fPnE0URk5WQK4NXMcYw97Y5/MVf/DmvvfoCp0+fBmi2AhpjnD7BQFQLWX/PPdx91wpOnznDrFkzKehxSsUAT1l0WAUJxdYiYTyClVnu3/EIpVaP6vAw3dNmcPpcv7tHY/GzWYqlNqRSKOuhgjxPPvkkE5fOMBp4FPI5orAGidZDSUFdu1a9QAp0GBIhEX7gujm+CAHC9107n4m574H76e7u5u9+9CMmJyYRwL69e9j9zl6sUHzr6ad54IH7+f/+44+abYYNDUqqAUhJSbnVuekFQEPM53kehVIJz1Nks1nCKEQj0Fg++vAjLp8d4IH776O7u5urV68SBAHZbJYoiigWi00bYK11MxjH8xTKD7AGuru6yOdyfPUrT3Hq9ClGRkZoKbSQzeXo6Oggl8sT1C3WaIKgQC6bR3keuVyWMK7Q2tFBz6xZPP/8L4gt3HfvOvxAEuS8xI3Q4GUkgZ/BUxkK7SV++csXOX/sEBXyTI72E0aahQvmcXn4Gq+9sZdtT8xCZfJ4niCX8RgZrBILRSaXR8caa1xJ4ntQixuuAxajY2q1Gu++ux8T13nk4Ye5OjLKxMQEAwMDnDp1iuPHjzd3SXK5HEeOHOHTTz8lk8lQLodk8iVaSzm+//0/4Wc/e54PD36A5/kIETZ9FjIZtztTqTs/hGnTptN/foDXd+3i+9//F+T9HOVyjTCssmDBXKrWZ+OmjVw5vBuhPHpmzebdd3fRf/woq29fBUohrSDb2kKQK3D+0kXyuYDJCngdXXR0dvHasz9msrWFh+5e53wClEcYxq4DIOsThyHCaAIPOqbN5I++9yccPvIpr774AjZ2W/XN4N6k5c/4PsuXLWPN6tU898w/UJ6cIF8oUK3WEL5HNlskDjWLFi7iozd+nmgmcG2WfN5oKiUlJeVW5KZnAex9ZQ8Hjh7iq089wYrlS+hua+POlasYHB7CL+R44qmnePQrX+We9Rt5Z8/bfPzJxyxbtoxvfOMbzJkzh5kzZzJjxgwuXrzI+Pg4cN0XwPc8wljQ3tXJqmVzeWjHDkbGQ575yY+x9ZiHHtzB43/8R8T1KpvuWk1dQ39/P9/61rfYtnUr+Xye9es3JKvp49TDmK99/XE6urp4f+87XDjXx+j4OAXP4+K580xEES2FPFcGLqKDHI8+vIO1q1axfO06Hn7kLk6dPMbhw6fYumUjm7fezfnzA4xdvsLeDz6ipb2L0ZFLDA2NAXk6M5OcPXeOemiIAU2SBaAUQSZLMZ9n8PJljh07Sj6fY/mKlRw7dozx8XG+9rWvsWnTJlasWMHAwADXrl0DaNomC6EIMhmmTetk9epVLFy0gE2b1nPXXWs5fvwYYT10Jjn1EKM1RngYJJV6yKYNa7jv/u2cOXOGM0eP0NfXz1ilzNatW7l9xWqOfnKYqxdPc27gMlfHy+x45D42bVjPscNHOXu+n+GJcZ745ndYu3odHUWPlatXcOrsBa4Nj5H34FuPf4XO+fPZ/8ZOLvVfYjLOUipJLl04Ta2eYVopw+jQeYbG6+SKRVraOxg4f4FLly5izfWz+oZ4UXouVfGB+++ld9YMli5exPZ7t5LNZDjb18d//oMfcP+Dj7B2/Qbe3bePd3fvItI2qSKcj4T4zA7AZ8OGbhZpFkBKSsrvMv8MWQB/zf/8//wbxk0FYyoorckLiRYW43vU4gjwkDqxw1XXnQChkdSWXFwy8Tf/RIAsQhCgwhFAEJssVlYIDPgEVH0BUY2cgio+JnHEs1ojkmMDbSxSeugkQc9KhTQxEo2REmUNwkIsfKSw5LMBX//Wd6lVJtj39ptoAv7VX3yL53/+Cu9+2E8cjqOVBanIRjEWSSgUgYyItMKKEhnG0MblItqkxRDhevWNdmY4jcY8Y90RQmNMoCFm1Em0sbxhXKx18btCGazReJ7EWJ1EK1tnjJOIMr3EgClGOftdW0+uQ5GJ64ClDigrMNIDqyjIkBoZIpUDVYV6jcAKYixaSVBFCD18ruFJS90oCAqIsI6wGh0IVGxQNkMkcig1ibYhVufxMQhbRQuFERKkwlqN0DpxXGj4KAqs8BBeDp+IIJBU6jES4947JQiNBBWgdJ1YZEBDIKtoC57yieLE7d+6WGmH+1wJkSQo3sQSIM0CSElJ+V3mnyELIMRYjZAKhMLGMRaLUpJaFEGi1pbJ1rfW+nMeADe0uE3507n9Gaw2KGGx2jZtc52GQGHiECUhji1Gup8ZbVBKNPrukBasjq6b4uqo4UeH1IYY5ygojcbPB1TjkA/27eHbf/xtHnxoO7VKnf2vPcOnHx9Hah+npXTPEFnlChsbOQtkNNZUqF2/A4RNih+rnU0xLnbY2oZtjrjhvuFGe+SpEb/g+vE9z0ObCGuNs8HFOFc86ZT/NtFjaK1xV6zRwkuuWzhzH2gugSXOPEej0caircUSg3CaDiUlsdHu8UaDymDjhvWwRtbHMQRYJCIO0ShiK1DUAZO09YfENOx9nGOic1cy7vWnfraEcxWw2mBsRKgNIlMgDquUsgH1SIOfxcYGZQ1KSepCgaxhI4vyAozVaB0hlTt+MQ27wGTMlfSITfSbftxTUlJSfq+56RqAbC7rVqhRjPAEiMReVhsn4vI8d6avcR7+0k38v3EWgHRZABbwfA8TO+dBISW1uA6eRCqJMDrpr8dNUMmkS2PVzK/IAnBfYtGE9QiE5MTJT/nLv/xL11MuIaNjp0q3BiMUWLcS1WSRgEcNLRo7zTc63N2IRUmFtk4xKIXCWP1P0qhZLGEUIkVDPJlM6vb6uTk4fYY1N17HF2UBNMYlNgIpfTyhURZ0IwvAukneb2YBWDAaJZNdDNsoh25083cFiU+sK3ieQMiAOAqT8unzN/z5LACBFM6yWElBFIUoKQmjGK0NBo2w4HmKahQhpCBOukrq9bobk0QUaqw7FvA86YSR8ZT3PiUlJeUW4Ka2AQLoOE4mT2iE9AjhfnFLKbFJ+ItSXvO3e8MquKWlhUKhcMPW91SEcHavpdY2CoWc29oW1y1tBeB5Ph0dHc72NbmGYrFIR2cnnR0diZ3vDc+aiMOmetBLQDUT6JQM3IQYxVjrtt81jcs3iCALUiVzvAIkimQSTFaujev7nPWulAilKBRL5HI5vuTWfwNEs4PCjZX7TynRdFtsJOY17HdpHI0n5xLCiuQgwkt0Ah7ZQolCMeuieXWEEAYlwJPS7WQYS6lYYlpXB9M625o5A9edFl0WQON6gkyWltZWpOfGWDQeYRuBSbY5Nl9kBYyAIPCTBMRGS1/j1QRWKeph7Ao9kmwFITHWNn0ApJIo5T5LjQ4JwRfnT6SkpKT8oXLTfQCc2YxiVk8PS5YuZdWqVSxYMJ9SSwlrQfk+1li0jpHJGbjneZRKJZ588knuv//+L80CcAmAHo9+/evcf98GPC+ZLaVEJf30s2b38l/9xZ/T3l5A4M69N2zYwH/33/43/OC//AGZbHbK5NKYCp1pwPUsgGStKCwC49ToyUQihHTmPUkRYBsGv8aF5NxwuW5UEEhk8vxTxWZWCIyFUqmFrzzyKBs3bkRIQI9TuAAAIABJREFU8VusRN2kHmQyLFy4kNtvv53Zs2eTz+fQ2jZ1A40xvG4C/Plqw6UmeiADUBkWLFnKPRvX4CvjuueSnQWTBPAIIdm8bSv/+r//1/zpD77vDIqSLAD3Co1DDYMShrnz5vONp75Oe1uBKAmDao5LM6L3+nV9NgxISOf1j7XkCwXmzJuH7wXup8IdTdw2dy4rV6ykd/YsAOJYk826sVm2dBmzZ89274p0/2nt9BZfHNmUkpKS8ofJTT8CiKKIwA+44861rN14Bz0tLRzcs5e397zD8OQEAMVSEd8qorBOPa4jhMD3fYaGhhgeHv7S55ZKYWJDNgiYDEOCTJ5SJk9lsgbWhb34yuPMqbOEUYz0POIoYufO1+k/d5YtWzYjPdWc/KXyyWSyKOVj4jphrYxSkkB5Tjjo5SE2zlJYZvCUR8bPgJIEukKtWicMJT4hQSmLFALGQ6y2iCBDRhi8IA+2gK7WnYiPqetcgfJ8Iq0xGOdXbw3FQp4ojqnX60gpm+17YRgShuHnxkVJiTGCUrHEpk2bmD59GlFc4eOPP+add96lXg+buwDNLQYLQiiygcILsmiroBo1BZKZbI5sUGT6tFm05sdc8aY8shlJUQqINLV6ndAaXv7Fzxm9MspDm5ehZGMCl3jKI5cN0D6ISGNDSa3uRIeIgJbWErZeJqxV0clxUJDNouOYONI3zv5JFoCwFiUlnZ1trNy0ja89uoO//qv/jeMnT+MpxV13reOhe9YyXrV0zOjlR3/zf9J/7gJbt2xl7Zq70CbC8+Aff/IP9J07h5QuukCI36bwSklJSfn95aYXAJlMQLVe5cVfvsDI5DALps/gmR/9yEXCZjyWrFjBnXfcSdZ69PWdZe/+PUgp2bBhAz09PQwPD2OMcaK2z6jetY4RvsDzfXpn9/D1aXPw8j28994bHP/oY3pnzWbzfdsxUZkosslxQ2OVpwmCgDh22gDl+czsncO69Rspldoojw2x+/WXKLR1su6O5WQzHn7rLC71neLAu3uZiDNs33Y3vTO7CYodlNQ4r7y6mxP9o6xfNY/5yxYhix0cevVljhw9xdrN22nL1emeMY9IdfPJOz/l2LHTxMbiKZcFYBHXswCEIggCemb2sOnuTVy8fIkPP/yQ3t5e1qxZQy6X49y5c+zZs4dardbsAnDn2QZQXBsZ4Yc//CHWGjbdvY55825zIkAhmvN+44xeCEVrazvr71zO7Hnz0Vbx8b5dnDhxhvbpM9iw4W5aumbR0zOT0RO7EAhmTJ/O2nW3M6erk+p4mdd27aIyPoKOXYum5yl0kgWAzDJ/3m1sWrscXfQZHxxi3659SD9LR2cXO3ZsQ3q3cfnUYd7ft4vRWkhrRzv3P/QIfWfPcmD/XtcN8JnPl9YaqyyLFi+mUq0mGQ9JEFTg8/UnnuBnf/v/8snRPr79L77P/fffy8sv7WLLli388Ic/5urwIP/Z977DnXeu5eLFAer1KDki+DKNRkpKSsofJjc3CwDn1tfwnvc8jyCTwVqn8y4UiqxZu5a+/vP84zM/Ye++PZTLZSYnJ9m/fz+Dg4O0t7fjeV5TO9CwAxbJWb8xBqkkc+bM4eCHB9mzdy9PPPkkpVKRK1cGeeWll+js7HAmODgFvDYalezPq8R3P5vP09rWxieHj/DW7t3Mmt3D6lW3Uyy2smnTXdSrk+zdd5AVK2+nZ8ZMFi1ZzYKFi9jzztscO3YCXxmGrl6ltX0aPoYXnvslh4+d4c/+5LvkBUzvXcD2rZv54L33OXriDA8/tJ1cIJOUwUR7ryRIgfA8hHQWvtvu3cbkxASHDx+mra2NTZs2cfLkSV5//XXmz5/PwoULm+PSKI6CIIMFlJLMmDGDjRs3smjRIvr7B6hWQ2f/m2xzS6WwQqKCLG3tHVy9NsJzzz7H0NAgGzdtQngeGzZtIoojnn/mp3zwwQHCWCOVoq29naNHT/CPP/kZLaUWVixf7m5EuZbKZuYAAi9XolAssuedt3l915ssXDCPubNmYq0LYbp86TJ7391P7+weujta8BuaAkFiJ60+vx5PVPvGGD744CBHDh+mnNhHCwHTZ8wkk8lgjGHjpo0sWriQ6dOnM3t2L62trXiex+Ytm5k5cwbTuqchVYCxIslJsNd3R1JSUlJuAW7qDoBAOAU+brs4CkMgEQJKQb1a4/KlS8ydO4dWP0vfmTMcPXkUrTX1ep0wdME1SinCMGyKA5v2womRS7VWY++eA5w43kfdDmLMwxSLRS6PXkFUqoRhmKjMndWuEC5EqFatIZIwHJdLIFm6dDHZYon2jnay2QyWkLNnz/DB+x9yLepEWEM2o6BQIpPJEkeaWi0iNgZtLeXJMq0tM9i8ZRPMWEBXSwFPSuoadu/ezdGjp7ltZS/trbOdJ4F0Z//WGNee6PsA5AsFVq1YTn/fGXbufI2RkRG6u7uZMWMGtVqNuXPnMnPmTHp6ejh9+jQLFixg3rx5ABw9epKTJ88Agra2NpYsWUIm69He3obve0RR3AwDwoKRCiV9JqsVFi+azdz5C5jW00NQH8X3oFjM8f57BxifHGNichwduMyCar3OwsULaFt+O+0dnUivD6sEWEmlUqFUasUgkZ6HrtTxPJ+1a9Zgp3VQKpXwpCCO4Oixkxx4/xPwe1ByKZ7y8aVkfHyUf/z7v3fb8fqzq//k4Ea4oi6OI2QYNpWC1jj1fy6bZfv27YxOxvzt3/4tD9+3BimdG+W2bVsZHx/j5Vdeobd3ZvKZanx23TGATk8BUlJSbhFueheATdqrGqvThspaa009rLHn7bd5f/97CCG5d/u9zJw5s+kDoJRqGt5M9QZoFALWGoQ1+EohEgFXZ0d787mFuL6aM8ZOEbyBVB7ZfJ64sZrt6OTe+x9AKsXV4WEQgkjHGBq9+QJtIqIoJlCWWIe0trbzlYcfZtmSZex++wBXRydZeecaFi+Zz7Vrw4S1MtpApAXCWgwSBIRRTKBUsnrF3Yd0snitNdoYolhztu8s5XKZBQvm4fu++5nWTExMcPHiRV5++WU+/vhjrLVMTExw5coVLl++TLlcTu5ScPLkSf7mb/6G3bt3s2rV6uaE2RC4G2vQVlCLNctXr2b+woVcuHiBOK6TySiyGYkgxvcEftZnZm8PVvoIlWXTPVvIl0pcGRx0xjwN5bwFL8gilJ8UgJKgUOLee7dTq1QYvHQFpSQ6jprJh1IKYmPd7gzuuEZJyazeWbS1tX1uNd7o0bC4MQxDp/Fo7BQh4PLlQTLZLKdOneRHP/4R2VyWKI65du0aUkiOHT3Os889Sz6XIwxD4jjGWNddYhuf3ZSUlJRbhJuuAbDG4Hs+K5cvY9Udd9BTamHLls0cPXaUcR1x+x130FpspVgsUilXkFLS1dXFypUrWbp0KcYYhoaGOHr0KOVyGSllswjwfR8rFEYbVq5cga9amDZnOe+99z7jY5OsWL6SuSuXMn/+fLZu3cxHx84wcL6flSvXsnTJEubMmcu2e+/lyJGjhBo8P6C1vQPrZQgyWdcA57uVstEa4WmkVEjhg7QMDFygPHyVKjm8TAblgSchW2qh0NZBSylLLBRGQsaXXKuFGKFQyieO6/ieIjQapCDWSf+9cCvPKIr49MinjI9d5Z5Nd2OF4uzZs/T19dHd3U0URVQqFarVKtZa+vv76e/vJwgCosgJ71pbW7hj9Ur8wKOjs5WLFy8SRXEy+ZqkDc45EFrr4oiDbIaW9hYKhRymWqNSrjFybYh77tlA78IJFi9ayPDxK1jpzvYLhSJxaxt+xokhpfJZuWYdq1beiR9k2LLlbt4+eIxQZfADn872dkKlyAQunlkkeg5jDUIqjNZ4wiIVTJ8+jW8+/cd8cuQIO196EWu+2JpXCli4aDFzl6+mp6eH9evXo/wMh0+d56fP/JSVixYRk2XukuW8v+clTp48xVu7d7Ni5XJKLQVmzZrBrjd2EoWhayWdEpeckpKScqtw07MA9u/cz95D79MzbzZxVOXalUEyUnFlcBCUYmZvL+1t7SgreO+9/fSf76e1tZWenh4mJye5du0a9XqdwcHBG8RujSOA2CpCYyAqUyy2cvrsBfa88wY2ipk1cxYdPTM5c+IYOU8wdG2MwaEh5s+fTy7IMHDxAr7yGBoa5uKlSwwNDdPR3sHExAQH9u3hwrk+ro6NUR0dY/DyIJNhTG1igquXB+mcM5fbZs2iPjlJLBUPPXAn58+f58iR0+QyHkE24MTx45z99Cgn+/qpR5rhwfOMjlWJQ0l9tJ+LlweJYtc+aHD9/1K6drlqucLlCxc4f66f8clJ/CDg3LlzDA8PJ+FGOQAuXbpEpVJpjrk7HnGq+9bWEgsXzKeQzzE0PMjePftcwqE2zTZApTznZSAU45MTZH1JsVTg6KefcurwEQaHrzE8OkohX8Ai+eTgR1zqO8GV4VGuXB2jraNIoCSHPviQM33nGKuUmTtvCcIoBi+dBgH9A5eZrERMXr3CtM5WxuKYA7vfZvDSEKNVSb0yzPDgRWo1D1ubYGToEmOVGCsV5VqN/r5zjI5ca7o8Nh0bkQjpI6ymt7eH9q5pnDp1grhWpVKpMHh1lDOnT1MIPFrau/jkk8N8dHA/Wmv6+wcoFkv4vsehjw9x7Pgx5w0gRZKS6MbnZnYCpFkAKSkpv8vc9CyAv/4f/h3/y7//K8ZNDWMrqDgmLyRWQigloYkRwmUBYA1IPuNr/5nO7+Rn7mIFyAI2yODFI2AEsc1gZZXAWAIylD2L0CFZAVXhY7VOznmdv7+UAqMtJCtRi8uzF9Yg0Vghkck1GOHaATOBx45Hn6SttcDxY0fQRvG17Sv52fOvcuj4IHE0iVYGlCITaiyCCIEvNdpIDHk8yonHf+K+4xzoXd9/En/rjHicK55t9M8n997YCZn6veb4SGe5K4VFCANaJy1zJE6LJpnoXMeBtGCEcg6GOKdDKRSBroO1hMJlAVipsFaRlzF1AiKZBa8KYd1lARjQnntPiAM8ew1PGupGIlQGYherbHyD1BZJDo2PUlW0DUFnUdZgCbFCYlDOu9jGCKORiVODswiSLgsg8Am0xleSiogxUUxOuHGLfQ8dGXxtiYXECsgSJlbDkshYVEMTcX0EEUnOxM1NAkizAFJSUn63ubldAE0VeKLMkjI5s3Xe77GOEZ6HVLLpyPfZ8J9Gy9/UYqDxtcCdn1sdQzKZXv837m6sdj7w2lisuV5YKOnEiVa702tnD2zAakg89I0FkYj7tLXOTlhCNYzYv2c34+NjLFq6lEUL5/Pyy29w6ngfQkdumrIgrCGyCm0l0sZO/4DB2pDINlb+DTGeU65Z7a6jscq90Zr4+r03Jv+p32sWS1Lieb57rHDn/J7y3Fa7Tp7bNMbJTcrCxu7ebRKOY6e8vqXpxS/dgxMth8thENZ5GwppQSQOfsqNgW0UdnHVdYUgQGsMgsgCNsbaRsyvRtNIR0xe31x/r28wTkqKJhtHxEYTRjGNyVsJhdXGaQysvq4f8CTKefxhjHZiUDPVJrnZWEDDFiolJSXlVuGmawAa7XrgznsbfzZXVta6X8LGTRiuh9s01f+/+slxPebJxBf4HiZyzy2VJNKxO5RvuPlJ4bzuk9Yx1wkoXasiXzLhNv8uMBiEdg6Aly5f4Nlnn8Vo28wCkCQTp/QBk0x0ARKLT0QkwDRm1C9ZWwohXBaAcat0KSTa/BOzAIxBZhTWul0Fz/OwUya0zz7VVA/AqVkAjdW2Tfz7jBVI6SGIUAi01S7oJyn0fCnRjSJMx/jKNhX5N3j4THldz8sQmQqeL5AyIA5DFwz1BeNzoyeg+4tUCqE1nvSIdQ3PU1New5VRSroC0A2i2/loPJN0cn+XBZCSkpJyC3PzuwCgudImCWJphMJIpZwy35J4sSeFQiLwmzdvHrNmzfpSK+CG4nvOvHnMmjXddRs0TOatM3LN5wssX7GcTMZv7gDMnTuXdevWs3z5ii/IApAgJA0j2MZZcyMLwK1GFQbXWSBQboJsisac6x9SIS24LADVzAd0aUTy8yta90gsAuUH9M6e81ufF0sliOohyvPQRlMsFNw4C5ptbjeMI4l5cDJmjSyA66pEDys9DAGtXV30zOxEoMFqXHKh2yGwye7CbfPnsWnjelbdvsSNr2jcd2IFnFyHFJZSqYUFC+YT+D4uHyo5fbc3eiTeWKA1cJv0nue7oxOlEo+DxKq5kXlgbbOosUkXhCsUbDMPISUlJeVW5+b6ACRq9kwmy33bNjFjdjclpShfHeb9Awc4OXAe4TkVvzbXz2E9z6NYLPLQgw8xNDzEhQsXbjgauP78blK5+57NTA5/zBu79iOkxFjwpMJYw4yeHp5++tv89b/5P5i8VgdrXFGw/HZKxQJnz54lnJhMJpfGlHw9TMgKt5UvsBjhJjthDMrzMDHuvFwKhI2aRYCJ3Xa6ULijBa5vpbvdCIULCb4+udF4LSnJZLOsW7+eoaEhBoeG3Pz0T1igmtjgZ7JJFLLC833++Ok/Yvebb3LhwgW3yp86jp/5+oafJQFICAkyYN7CJSzpjBi48jah9bC4XZXG6GGhpVRi7V130ZlZwvETpyA0XA9Acmt7Fy9s6OqexqbNi/nlLwaplC1+EqIkGjsJ4sZ1v73hC5ecaI3FGOieOY2716/jwO49DF8bwWrNmnXrWbtkBcb3Ga9OcnTfbs70X0Ab19FhhUw8IFJSUlJubW76EYAUEh3HXLp8idkLe5jW0cmu999jfHzcuQMGPm0dbWSlT7kyyfjkOACZTIZDHx/i6tWrzba/L9InCiHI5XJUpKCrs5uQAleHz2Gi2Pn6C8Grr7zOxETN9d1by7FjR4mjGvfeey+medYt8f2AltYOPN8nqpWZGLuK5wfkMwGB7yEyOerlClGtRs0qWltLFPM5jFT4usLY6ATjVUMxKyi1dwOC0csjxLEhKLQQEJMrtmFtkfK1s4RRRGOxnRzJu6JGgEp62j1PUiq1EkYRExMTeJ5HS0sLnuc1XRM/Ny5SYIzGWEMu4/P0Hz3N4sXzOX7sGBcuXvjsADa3xqX0aCnmyRdLhFpSH71MFGmU9GhtbcfPtzF9ei8ZcQUTgx94FFrztAc+UaXG6MQ4YPj4o4MUgxYe2bY80SG4HZRMENDe0oYJBFG1RlTWxMbiZ7K0tLQRBAXC8WuUJ6rE1qI8RamljXq9RrUykaT0NXDvmjEaaQULFixg7baNbN6wgb5PjzN87RoACxcvRiA4ceIElajG+PhEcgQAxibiyC/5bKWkpKTcStzcAiDZ2o90xLFPj9IxvRUzfZKDH36IFQI/l+HODRtYvHApplxn4Pw59h/Yj5SS1atXs3TpUo4cOcLx48dRShHHbqXmDIUM2miEcomAS5csprurF6/QS9/Zw+x+9TVmTJvB3Vu20N6S4dD+/WBDt/Uu3S983/eT1i9JkMkxb/5CVt6xhly2SEbF7HzpeYJCGw/fdw9xVKXmdVEfG+TNna8xaQo8smM7xayi2NFDV77MM8+9zLkrdbasXUDbjG4K0+dy6YN32blrD5vv/wpzpym0yBF5Mxg4/Cr79h6gnijyr+sMnMLdGEsQBCxatJgN69Zx4vQpDh8+zLJly1i0aBFKKcbHx9m5cyfj4+M3CgGTbXDf99iydRuFfIFDhw4l951sjSfCOiESwaJUTJs2g3Vrl9PW1UWhpYNTH+3l3fcOMmfBYu68ax1GFpg9ZxYTp0eQSjJ73m0sX7mArkKBlkyOl159jRMXz2ONwPOd7gDjnlv6BZYtW8KqxXMJ84qMMez8xU6El2FGz0wefGgL9WgmlaE+3tn1IkMTFdo6O/jGU9/mxIkTvPX6a6A/v1I3xiCkR6lU5ONPPmHZwoXu82EtKMnk5CRXr17k3XffRVtN3oRIkRzHGJr+Aza1/EtJSbnFubkaADFVBOi2z7PZbFOFn83mWLJsGf3n+3n22Wd59913KZfLlMtlDhw4QF9fH0EQoJRynv9JVHDj7F8K1yEQRSGVapWdO9/g5z//Oes3bKCro5NLly/x0osvui4DqZpCOGMMxhhqtSq+7wFO2FeuVHjrzd289vrreIHH0qUL8YMcnV1tHP30KK/v3MOsWT10d3WxeOlqSqVWXnv1Vfbs2UscVRkZG0NrwZkTp/nFM7/gzbff5Ztf3UFeCTLFDtpairzy4mt8+NERNq6/EyXBkwIlRdIS6K5DKoVUittuu41tW7Zw9OinHDx4kLa2NpYtW8a+fft44YUXaG1tZfHixc1uCXDHJypxL+rq7GTJksX83Q//LrFSli6eWQh8TzXzA5AemVyRSGs+OXKY55//OUcOf8L8+fMRCFasWsn5gfP8/GfPcuDA+8Q6xvMUE5MTvLNnHz955jnGxseZO28uCIGVHtVqLdliF9ikX390dJRXX32FnbveoFgs0jt9OlpDGBne3/8hb775Fm1tbbSUigSeT1Sr8v7779Hf3/8F5/9TZfuWY8eOM9B/jjAMnWkTJPbBgkcfeYQ/+7M/49vfeTr5PDUljy5RUqfBPykpKSk3/QigEQYUZLNEsSZKJiJtDPXJCQ6+/z53b9rMHYuXc+jDg7y9722iKKJarTZb3RoTVWPibq52E9W9EJK+s+cYGhqhbmuue0BCFMWESYxuEDg1vDEaE7sCRCpFrA1SeUilWLB4KevWb8TLZJneHnDuxMcgYHhokHNn+hjT3RgTkw0E9Vgzo6eHrq4uOrunMzZRZnyySqbYxeOPbcbmMtQ7FtBa0E4FLxSHDx/iyqUhMl012lsKKOFEc7GhaZns2h6hpa2VdXeu4aODH3D6zBkqlQpBEDB//nx6e3uJooiuri4uXrhIPp9n/fr13HnnncRxzK639vDhwUNs2LiR4eFhpJLk83m6ujrJ5XNUqzUwScEhJRqBDmPaZ7Tw8EPbaG1vp72ri9G+o+RyHoV8wOWLA1SrZaq1CpVMiEYy57b5rNu4iu58npkd3fz8xRfQuJChWBtaWtpASFQQYGPLqlWrWbPkUeKODjo8w/t6NxbF5cEhzp0bwPq9rkj0JNJoJicnOXjgg+YW/eelerZZ+FRrFQoll6Mw1Rfhww8PcunkWWwQcPf2LWy+ZxOv7XrLtTGKZIciPQJISUlJ+WfQACinqI/qdfyk599aJwQzWnDk8GEG+i+wsHced2/cwLkL5zh79qxbySrV9P9vtAU29ABCOPGZcmYArh0My/zb5lEuTxKGdWRyvu15HlGc9MAnq2UhJL6Xaaa+dXZ1s279Bva88w4T5QpPPvaga0YTri9eSoWJQ0xsyCiFCRTlcpV1a+/kalXy0is7GZ+ssn3rGiYqFV765Qv03nE3d9+30fnkW43wAowURIn3gIldi5xQFiHdCjfWMSaZ/HbvfhslLBs3rOfV13cRhiGDg4O89957XLx4kTiOGR0dxRjDwYMHOXHiBAAjE84ZsFqr0dnRxoMPPMCCBQtoLZU4duwEZ86cdZM/AmMNsQWUZOnyFVSqVX7xwi/Zdu82Zrf6KGkxOqRUzJEt5Vly+1Lk1RMoL8uKVWs4fOQTBo6f4KnHHm92MoDAC7LUwsi1fGpLpqWNlStX8dJzP2Ys4/Pdxx92vgfK9eALKYiNIY5dwSSsJZ/Ps3DZcq5eHeF835kbPlduT6lRCDq/ACFlM93R8z00msuXLjFUH4Agw+p1a5g2rcvpHoS7Un298T8lJSXlluamFwBRGJHNZnnksce5a9MddGWydBWKvPjySwxXyzzy+OP0zpxFR66Fjw5+wMjICEuWLGHHjh0sXLgQgI6ODl555RUGBwdvcMDL+hkiC0bHPPTQ/dxz932MVjP84hf/QHmiylceeZS77t/KzOmtTPuXOV55az/vvfceTz75bVavXEX3tGl0T5vGy6+8yonTZ7k2Osrj3/gmF64MEoZ1dKyRMhGMaQ0iSkx7JJXqBKVSiWmFBUwXOdqKVS7+9Hkune/jmw8+Tvvs2VwYr1PRhshqch4M1ZzDnTCWKKyRz3vUJ925tjUCoVwLo/J9jIWBCwNcutDPjh07eOqpp3j99dc5ffo0jz32GBMTE4yPj/Pcc89x5coVxsfHGR0dxfM8tBUI5bNr506CQCG04YnHv8bA+X76+vqc0Q/u/Ft5PlYExAbGxifYvvkueuf2Ug/rlK+co1yuMTBwjie/8RjXKm63ZWQEwDI0NMy2e7fDhg14GoxwWorHvvkd1qzYwIKZPv/1v/xz/sPf/5Kh0Yharc53v/M0p+oh1YrTLUgr3W6MsFjhTHqyvpuTp3V38+BDOzj08ccM9J/DmPhzc7W1FoNhxwMPsnbrBhYtWsT3vvc93tm7lxff2sV3v/s9ZndMJ1aK0co4L/3yuaYRFdIVjQiJ/YIuk5SUlJRbiZtvBfw//l/8r//+35LvbsELDJ4x+NoweHUIG3jkSi1kMjmUhmvDw0xWJwmCgI6ODjKZDHEcU6vVGBkZIYqiphYAcMfAMk/7tOm0ZiIyQZaxSc2VwXN4xtDV1k1hehdRdZK8Z7h8rczIyAg9PT1kgww62YkYGRmlXAsp5Fto7+giNJZo4hpRbZQq0JUJKI9PMikDuktFRBRy546v0xpkOPLBASat4E//i6/zs5+9wAeHzjGzM49QgvFKlXYhGLg8RLZ9OpgxRsc0QXYGc1vHuTR4jchYYgmxlU4s53lgLMVCAROF1Os1WlpaUJ7HyMgImUyGrq4ufN+nWq0yNDTUjEdu7JbgZbAaslmfeq2MsNDaWkKHEeVKBSmEc9pzS28QAVYGZPI5utsLeIGiWq4gKxOMTUxAJktnZzdW5ahXQmR9hGuTdTKtnXR2FRBRnXCywmS1ymRYo2vmPLIyR05NoOOY84NjhF4L3b6huzVg1PcxV4eIJ6qMqRm0lCImxgaJTTvTCx5ReZCJMEZmsrR0dVOuVJgYG0MkraJNgyLXRoL0V3pcAAADL0lEQVRvoKOtlVxHCWEsnjZUqhWujF5j2vSZFGSGWAjGJsepjwwRaWc0lHhAAnLKEUDDjeFX2TX9dqRWwCkpKb/L3NQCoDZR5d/9T/+W//3//ismwxp1QhCx23y2Fpn0wlubqLL5bc5jG8Y/JnksTLVxtckxwK9Nd0vU8M2vE1vZRhe6AIwQBJ6HpxT3PfgQixYuZGhwEG0Mvb0zee5nz9N/7jxRFLojCikwccMHQCCEbQb1OM+85Bo/dx2//v5/5Tg171k2A3R+zbN95rXdsYho2Cp/5t+JhpyyYVAw9ToEOA/mRk9D8m5IiTDO2Mcmz+0mctlwHgIrk8nXXp98m+/Ll9+r8zWwN5gYNDwcPvuwL3ND/E9BWgCkpKT8LnPTjwCak7El+UV//fd5Q5U/9ZfxP73+uD4BTX3sdcMYO/WPX/E09nNfT52gbfJ9bQyx1ux+600GzvfjeW7Idu9+iytXrlzPKRDujH3qFdnmRKb50mn5N7z/XzlOzXv+Tbe17edf235REI698f9fdA0WaE78U75p9A3vyfXV9VSfYDPl+zfey5df+pTrnHr5n/n7F/yTlJSUlJQp/DMUAH9YNISJ5XKZQ4cOAddX41PbFa21Td+ClJSUlJSU33VuehbAHxpxHBPHsTOgafgRJJqExoQfBEHzZykpKSkpKb8PpAXAr8G1EAoymUxzklfKmeo0CoF6ve7SBn9dmmFKSkpKSsrvCGkB8GuI4xilFGEYIqVstiV+1qSo4VmQkpKSkpLy+8BN1QB4GZ97HtnKv+r2CeOYWGgaMiyBbWgCgZvfcpWS8rvGbxvvnJKSkvKfgpvaBpiSkpKSkpLy+0F6BJCSkpKSknILkhYAKSkpKSkptyBpAZCSkpKSknILkhYAKSkpKSkptyBpAZCSkpKSknILkhYAKSkpKSkptyBpAZCSkpKSknILkhYAKSkpKSkptyBpAZCSkpKSknILkhYAKSkpKSkptyBpAZCSkpKSknILkhYAKSkpKSkptyBpAZCSkpKSknILkhYAKSkpKSkptyBpAZCSkpKSknILkhYAKSkpKSkptyBpAZCSkpKSknIL8v8DZ/W4ifmohm4AAAAASUVORK5CYII=\"></p><h3>Input Jumlah Elemen Array</h3><p>Kita juga dapat membuat program yang meminta input berapa banyak jumlah elemen array. Langkahnya secara umum adalah:</p><ol><li>Deklarasikan array tanpa mengalokasikan jumlah elemennya.</li><li>Buat input yang menerima jumlah elemen array kemudian simpan di sebuah variabel.</li><li>Set jumlah elemen array menggunakan variabel yang diinputkan tadi. Coba amati program berikut ini:</li></ol><p><img 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t6SkpKTkx8MlE1KlqESy0gC0QQvrU8EESyRF8e0AeOkV59aiwLehsCpzoz13sGDwRfkvKnhi1ChIjtEcqx5Ri6igmKJgNkVVF1ELFNuFAOKXE1IXhciLxAmqBiRgyZZeoLCXpecj7pm4knO+GAvnLalZel2roL0C4eS9dT+2yAq/yjWzJSUlJSUfTi6dRdqrqrK0ZrTYpChFCr8goSd6S5qlBCmWvxhRAoIXLeZVBSQocqElqT3lRSlmWZcsztCTtd5r4ihEULnQIpVlSQ1F+xoKIZQlAQ3FviK9UguyvOcFJ3sBvf0RwBc/ChD3XiuFtKSkpOTjyCqFVM/7dSmsZ6XMBFG80WUZEXoWqvZErTe3KRQiSm8eNRiQIBg1iHjMkkUZAgaLhKhYVmMchXCBLvmNe+8VpFcjzPSOqTgK0XPWqQEkJJwTwaWDOGeRhveyJrUnlmpYFlFZWSjbAu59jGdJSUlJyUeNVQipoj2BWRJHUZYtQwFEY5wo3gbUFJag0SIAyKqBUBSUDj3xFMD2NKuQQ1O4b8VhJQcVFItoBGp7tqYrrNjlIymW3BT/eQqBW0r9sPJdvmcvS08I387iXBJVy/JNw9uJqtpzQym+sIgl9Ixh03P3XvxIl5SUlJR8eLl0Fimc7w4VEKcUdaSF3AcwglWwHiI1GDyqkPXWlUYBkgCqulzrNEjP3Sq+EFu1xXQkATUOvyTQRGgQhAjUYwRCyFGh+F3BEBfLO3quYVmyHk2nOJsQEGNWnEPPZtVqcWugWkyv9lzKxemG3pxrQAOYXgBVWTewpKSk5KeDVQip9IJ6CgLgnCNJEgB8CMSmgjFgfEYiCkELTZQILxGxD4SeZatSuHFN7gkKIpZgLWIijMkJPhQiSYSieLNIrh2srZBnUK8O4DIwWKyJCN4Vcmdycs0QiRER1BtCEOLIogouyyFeEkazHCwlaO/GIIAocRSRZV0iG+F9jixHN3lUukQ2IUsFS9wTbHduZKR065aUlJR8XFlVtoLCOlxys1psUidD6AKZWNq1OjfdfTd9I6ME10vVZyNSG9GOE4KJycWSxzEdEXJjcRiwEbm1uMiS40m9wysEtYhEEHk27uzn8n1DaNzkqn1bqPR5gnRRUvK8RZwIqjlx3bP72vU0RsDZRTRK8dIBk+O0UwTVhmGQUXI3gOowXgfJ8gYu9OFDH+ARCRgbcL5L0Axw5HmLfdft4Zp9W7GVBUyUkmUOSEB7867ielG9JSUlJSUfR1YhpIJRi6hBsQSxmCTB1hqYeh/Uq7T6aywkMXPO4cQSTAyVGlmtSrOvRl6vkVViXH8d118n9Negr0HHWvJ6BV+voLEhqVdRY8FWC6GNA3f97H5uvXs7I2s9v/Kb9zI6ESPRAl6aJLVA7ubxocXExgb7b9vGjj0j5DKDk1mqA54QLZLUHVEthWobTRbpGxGiehdb61AZcNh6h6iRYgw4n2KMUKsl1OoxYj0333qAVnue/mHhplt2o3SJ4wRCfC4AqRTSkpKSko81F+3alWJhC14FF8XEfX1su2wnqp6s2+KNw6+TNMaZ04xuCFQTR2oaXLZvP12NYKSf7NXXmTp9it3XXEUza+PPztN8Y4qhNRvYcM1VnDozSXZqkrOTx4k0xhqDI0VMB+87PPXks1x3024ee+IhGgOe/Tdt5aXnjhObjN3btvLSCwcZGIl44fmD7Nm3iaefeY6BPuXGA9uYn+rQGGzw5ONPsXaTYfvW7Zw+uUi9McDTTx9k065B1FZZu26Mo0+dBevpG6zy+qun2H3ZJrJWlYe//xJRfYHK4BrWjo1hjMFoRPDFnGkRmLQUrFRSUlJS8nHk4i1SVUQzTGLoGmF8+w602uD5F17k2KGDxN0W1g/RydpogCROWXfZVQxt38krB9+k1e3QzaHeGGXz5h0455k6fYYsBAbH1jK+dRdnF1vMz88QmQriI3zaITYtjOlipcbsGcEEQ7O1QK1uGR6rsHnXMBNbGlSHI7q2S/9wjeOHTiHxPLv3NKg1lDUb4fibR8hVGRgeZHBNBbGe1148RhIlJHYIjT0zbUcyZtlx+QCLfpbxXV3ioZQr9o0xM9MmSmr0jVt2XrmOl196DSEmywI+5GC6gIOQgNYu3V+spKSkpORDxcULqYBYwQeHFcNAY4CpyVPEUUTIc4J31BoNnBckrtINljUT6zl8+A2SSp3NG7bS6TrmFjv88LGn2LhxB3d/+jPkWA4eOcYTTzzLTTfezMjQUC9aVohtTPCCaEzaFhamUx797iTzc03QmOefnGLfgS1su2w9B189iZjAgZu2c/c91zAy2ODAtXuIQ4PWdIOZk1Ue+840k68bJB+hNRNTsaM8+r1nqUUV7r7rE0ysaVCLDcEr3ekxYlnL5XvGOHL0IK3WHHHjKHfds51jb55i8lQLIcLapaUyK5NDXILEwiUlJSUlH0ou2rVb5BNS8jzHxsr01Am2btzAQBRoTxuas9O0m9MMVUcZvGwXZ461mJ48ycimCUZ3D5LOz9LttBlo9NGwCdpOOXr0BEaFDevWE8RwdnKKdrPVS8JQZBvSYCFUac5BdzEhdOu01liqa+pMnThJ1p1FQsTpyVkuv3IrD37zNV555hQuWuTeu2/BuAHmplp430KDIbGe7kydYBJacxBX6+Rdz8mjU7hmRneuTbvp6bQ7nDpxhltuu5a//KNv430/u3etI7IJ8zPC7l1X8swTk0TiiGLbS/2gxbrSMhlDSUlJyccW0Yus3Hzo0Gt89rP34MSSmwST1IiiiKpVXHsBzbtMV9cz2ueJWhl5eoZMhqmODtDuOOJYCPMp1WoDrQiIpzUzR83GJPV+mhIw4jDNGcgDERGRiQjkBDIqjZi5xXmSaAwxi8TVDtYKv/7b9/K1v/kHpqccka0Rsgq+3YettKjVHHmm2LhN3mljTB+Qgx1F1CChRpadRmxCY6SDs5bUzyPNCplt8qnP3cDCmQbPP/YMvpNQ6RNCxRMDmhk6iwnWNMjyFGNTikVBvYQMqwuQLikpKeH6627ky1/+PcbHx3/Sh1KygtVZpKbI/GNRNE9xaYeuAaMeQaj7GeRsF/FCZD02tHDTTYyxSEupeENottFWQMTTp4rJunjXxhrpZUKilyShN/cIIDGdlpJIP0YdwRus9rN/31b+/r7nOH08w1Cn26pRiQUTLyJB6bQ9JtTQLEKlH9I+gu0QQlqUWwtgTRUNCYuzDsSiMkSsEbuvGuH0yQVefHIG0homRHTn+8iiFMsiSzaocynGhF6ielhO7FAWoCkpKSn5WLKqhAyhl6jeaBHB6/IMiSyiiqoSaYeqK9IFphoRqUNCQMVT9UWBbxXBqvbqihY5eUU9lSC9VPQRS/ONulwmTTAhAgRCII67ZK06P/jey6ha4qgOfhgxoDQJ1mGC6a15NaAxwRisJhQGedpLreuW099LqANRkQ84CK8+28bZGSTUiDXCaISXDJG0V+FlqaK4o5fssJd7d2Xi+5KSkpKSjxurShG4JBGGgLhAxVqCc5hI8AreKGiEF0MmhkRzFIMXQG2Rg1cU4w0oBJFece5COKWXCF7FUywnWcomVIioqMUHwCqxreHdMJ5ptOgcEzXxPhBsPxqKpSgqHiQQrKI0UTGglSJvsGivtJorkk2IR4LBaAUrCUgXT45oFaSLmEWEGNFakVZQXM/6jJaPsUhgX5qjJSUlJR9XVjFxp+dqjypEkdBfr/Pvf/d3+YWf/wXiOCaIxUmFXCrkpoqTBE+Mk+Inl4hcIpxEK55bMlOkENSeVSe9jlRCz2bVXgUXJbYJ4vtJu46QVbEYJMQYk6HaROxSVRhdLuem4nqPGUEU1QpBKwQMQQQ1OWocSNYrsQZeJvF6phDOUAdJwXSQ0IBQO29cVt5iQM8KLikpKSn5WLKKhAxC7AEUNdB1ntvuOMCRN4/wjW98Hc1TaqGCNw4VIQmOJWdt1RXRrFFYKhejhF7uWrvkItWlth1LBc8knBMkNaGYN8UhGEykCHOoRKhC0By0hkhETFF4u+i/mHuNvBCoFEFGkrFsCBev9ozIIveuN21MqGGEIreuWSSQoGGkcGtLSpF4YcVwvqUmaklJSUnJx5HVlVELgRDAViOCKrV6nXanQwieYu6U3rymYldoie0J1jnxOocsi+iFL144z3hOhHV5S7ZsDBbVV+JzbZ7XwlJtlnN1Ss9rXc/vS8X3Srct9euKo1eDnCeUFx5jWcy7pKSk5OPORfscVZUkSYjjCJc7fvmXf5ldO3fyl3/xl8RRRBSVafFKSkpKSj7+XLSQihiccwRVjDXcd999HDl6mF/51S+RZhnel9ZYSUlJScnHn1UFGy0RgqIo09NnqdVqvTR5JSUlJSUlH38u3rVL4d4VBGMMqtBut4jjhMHBAaJoVStrSkpKSkpKPhJcvGu397+qEkIAVZ544kmef+45tm/fjoYyUXtJSUlJycef1ZmNvehYayzGWAzK/fffT2yAoGV62ZKSkpKSjz2rkDop/okQGSE2vWLWCJnzePPeGq0oQRRBiUKRStA4GMos9dygKphetiM1hjQSMGBUGE6Frb5GogZnwFuhX2O2ZFXGfVLU1HaBJAgjLmY4NVSxOALtRFgUT2Ygi1ckfKDIrhQEnBFyA84KLQsVm2B9cYYeSC20e9kLq06KVIe98fBWMEGwYkitEDllR6fKYKtY9CMBql5wRsnxVIOgvX9L604NSshzTAhYVdAU41OsgrURuBzNHGIrBNtHZaiP3LRJghAFJZiEPOonXzOChi6oYsUhwaMhImhCIMarEhQiW8EroAaTW2IM2C4haVMfNti4A5qhajAYbBohxpOanEqIqQ9McM/tVxPE4ENM0BpZiMgjSxoJTTxZXMHZDKyg2kV9WoyT8QRynFGC9cjQOIt9gwSboeKJpEKjCzXfwijYEEgcWIRgYiJJiNUwNjHBSF+D3DgiG7NmbCtr166nYlMURdRiNOCxEAlGU+qqGDqIV0KIcCYliMNUAjaLyKQGtk0lQJ9rIs5S1XaxgEoiUjUEFBfXueWuT9KoN4h9oOLyi/9qlZSUfKRYpc3YWzcZAkZ0eVWmmIjAewccWdXlNZ5BoGOUPC7WZ+aAjwxVIrwqvie2NlVydaytDXLdxHbqXSXpeEyA0b4Bbh7fzg0jW2ioRRGqEnP12Ga21oYIqcOIpaKWIalQc4LpBRcvhU4FVYJXrIfEQ10t1hjSNGVHZZjt3WI/RIiDYMSQGrAdh1FDPwmXmyEGukolVfpyqNbqbF+7iTWhQuQUFwlOAxUsSRQRaW9NrJw7Fo9BkirBxngTURdBKhW6VujmHlttIJGBIAyt3cY1d9wKFQjBECTCRYb6+m0cuPdTJJWY2MSot4QQIZLgQoAoYJJirW+7myM2Qo2iOKwRcudpDFW5+2fvoN5oYK2BKEclR0TIdRG1ig+GW2+9HRO6RM6QxgmNy3ey/rr9bN55OdVKDdPop7prByPr1yMOEpNQj+vYUMGoJbE18EKc1Lnhzk+zfc81qBEyY0hFcRrhE0uwER5LZoS2sxiJaDvPTXfexb/+l/8j115zNc54BoeG+Pmf/zz/2//6b7ni8k2ohN6tn5IFjxeL1QhSg837iHyCtX1UcFhxhJAjsUVNha76QrTVQFyhlRtC8MSakohiRQkI1foAd95xF9XIkpgyar2k5KeF1eXaVUUERFaowAfAKGgoEtergDFCNVgqXY8JjoE0pmYC7YYw1I5wskgt7adT6yK1GoMO+ls5I3GFUxGcPHuGs86zaWSMeldp1oX6Ysbs6SMcjzPMeJ0KEJpdxlLDgEbMJoGzFRAprFGrQqxKpevpJ0KyHFOFIY24sTJMnFf4XucUkwEauRCM4jQwkEekPrDZCbev28gjrSanY0e7atA859jccVrdDmGoigsp6zpQ78DZamC+CpEzqCgeQU1EBnhjcCEQVaq0Oi0CNarW0HYd0rhKRTJaGpicPs3UQ28goUZqq2Q1w1zrLI3BETrdFhpVCdcq7xoAACAASURBVJ0MtYLalKiRImGRjmbENiAmQkyFVJSkktDJFsH0Ua2MMDP/Jt/+zv9Ha1ZIKg26ehLjE/r6R4miDnm7Qjw6zLWXb+Ir/8/fYHJYu3kd41u38vwzzzAUlIrUmc8zNu7YTXqkwky1SzP3VGoN2nTQUMN3UypRTOaqfOfBR4jp4Doxrl4njRxN26BrAoPB4qM6US1lYXGIYWbwScKMOr7+Z3/Cg089jtYMZ86c4f/+oz9ndLjylk9mVKkQRzGRtrAyh3YEHwf6tYrTLnWp0F5YxNUWGUrruNgRu2nyqEbkTpNFfQxEKTXaZBk428B1Ovzwkcf40i/9AkNrBjg7nZYJrUpKfkpYtZAumVJyEQVOilJsRU53o0I1UwY7gU+s2cFEY4CWepp0efjMa1zb2Mwriy+wvr4B099kYVHZPDrMviv3skYr/MOxFzhdsXQzh889XhRJYiY2jnFb/yZ+MPk6j3WmWOMjDoxsZXRgiLmsw+ybhyiSEhbVaGxQKh6uXr+NHY1RaKY8svgm/RlsHVtHFi+yfXCIudnjNOZSrhzbzLq+QVwn5YmTh7hu3Q7GogY7d1/OTOcUJ+YmuWPrVVyRNXj09Zc4SsZlrs5tI+vIBquc9Is8uHiMihZWKGLIMUxs2cJnf+mL/Ic//EN27NnL9gHD9599k1sOXM3IxCgtb3nsa3/MjquuZdv193Dkqe/x4qM/IK4Ncfkt17D3ygnC0LU89fBX6KRK1YNJYhwdagM5n/nsPtZtrDMzM0fW7uNvv/oQu6/ayZV7LmfXlgp/9kcPMz9j+e1f/SJJssjf/sdnODMzw+d+4zbW9W2l2TRMTv+AH353kc17rqI9c5z5RU+3WiFSz/jYBNt27uaNl39Eu9vl7l/8Ahv3XEt340527N3Ndx99its/fQ/zrVm2TGzmyMFXeP6xR7jzU1+Eap1v/+n/RbW6hhvv+RQdnWLr7tuZa8/yyB/9MSNX72P/tj4GNt5DmH6Yf/jqA2QGSCyVOKFr/NKnC2st9oII8kgD82fPMNEv3Lp3I9t3baF/rI/Dj/6IB0+c5rduvJ1Wp0l1V50nv/EETmvcuH8vvlqnguNP/u55rt45xrYNY8Ra5aEfTXLo+CydZpsjx46xbsNaTpyeBElW8/UqKSn5iLAqIZVl9VQupjy4QTCqBLSXLF7wopjYcvSNN5jsNNl34Go2T1UZcjFeCuup0fVErs6JzjzfP/4i945exobqEKeZZbZhmBwQ5jHkWcbBzik2tgy2m2OqEZvdAFuzKv/w8vMcHzZojXNO6MJjS6RClAfCXIt8ep75uM3p4PnR4in8fJOH2tMsxIH9VDHNDmnTc8XIeh50OU9Ovo6Z2M43z7zCZAOyquVHJ4+y1WyirgarwtZ4EElzvn/kEEQG36/FnK4pDkDFcGZmjqR/AFNrUBsa4dnHH2TT1XfwzMHXmLr/KLtvupO+8RFefellpmWUepZjJGHTrsuJBwf4o6/8MVfe+Ou0Z2dQp1QqNVIfEyQlSgxnz07z0sEpJsaHidTSbudkPufIm4fp66uybdc43/v2Wf7kT/+Kf/rbnyT4IpNVrk0e/sH3ef3IFJ/45AYIgcGxcUI+j6qlEynZ7Bw/eOAhrrhmL5vv+TTfvP9bfOP++7mpo7z84Pfw2UmkPs7owABPPPZdHv/299m5cQ0szvLwQw+y5aYDpCHHmAb1wVHeOPwiL37rfq7dfw0jtWE2HLiRB/769xnes571lROENEcVMnFIKFJMRrbwENgoIs/Pn69MuvMM99XYu2uYjZWcv/naw9x57UZmjpxhdNBTCRl/9Z2nqB1P2DDYYN/6TXzjmw+xbVudDSPrcO0ZRhojLEyfYerYJFOnFKs1nHOoMWQhR60pM0SWlPyUsKo50iWXrupFJmZfUl8BL4qz0I1hMYFTdDHVGDoZCy7FGhjKI8aTGiEyLEaOmhM2dWMa3pAGj/FKX8sx3oKRtlLJlLWLgbGWMuAto10hc45mw9LAsrZj6HOyfOTSm6oMqpyaPsOxqZPEA3XGJybwiSGEwKBGjKbCRAv29k0wbKr4Vpd6nGBEyCqWdgIxhuFWYHvTsnFe6cuURgb9mRAsVOOEkdTgvcfFUhSIkaXycUprcYEzJ45z7ZVX4NpNppvzDNfrpPNNJtZOsG3jeppnZ2l3WqwZGSTKPBvG1tHf10e302LN8BB7d+4gX2iSiOLwBGljo5Q8T/Euxwh471F11Bsxu3dvYW72NJVYMeKANjbyuNBGojZIB3URaSegziBUUBEOv/oqQyMTIJ56AHzO2fmzHDr4KoNRRCN1DEcxCYEka5N0Urb2N8hPHGf21VeRs2c48czT1NtNRmqGZtqksWaQ/pE6WbfJ4ZcPsrbWz8zhNxiu9SEmojaxlptvvZGzJ6dwxiME4mCKaQLAeY8Yg3fuLWuajXjIO4zUldxP0z9i2DjhmXUdrlw3ykvHTnE0rfLKcc/B2ZRm1iWPEvZfu5mz8ynOpzz97Ku8eXKKG267mVqjShBIKjH9/QOkWY6G0q9bUvLTwqqEdElAL3aONLeQ9zLXV7ySdAO1bmDYVLh57z6u2LGT10++yZux43Ql5xP776CvHvNm7Jmu5tQrVX7u8uuYaTc5nM6wedMmfmbP9Vw7tJ6b1u1ksFrn2p1XsnvLDvbt2s1VazYx7docNW3uvPYG7t66h4o/v0A5Cj4SBresY/OBa9D1I7x04g2sUyYXZ6ltGOMTu65ms9Y4dPYksmGExq6NPOHOMi+OaddmMsq4Y/8N7B3ZwHhI+NTeAwxv38S1+/ezvtLPCzMnmakod1x3I1ft3UPccXgpysRBIAqe/tjy2rNPsaG/zqEnH6eSOVonjvBf/9Pf4tM/ew/f/uqfk03OMJAHKmmbe+66k25zgTcPv8a1u7fz8/f8LCd/9Cyh2aGCIw85SIZVRbOEmVOW5kxCc6ZOd77C/BkhUcs/+blPMX0spzMfuP66K/jX/9O/YPu2K/mVX/tFQsjozsQYVyEsRjRnLWpg6rXXaLmEzRvXUM8cv/bP/kv+2f/yP3Dn5+/hh9/+Fmu6GfPHDlMfr/Hf/Kt/zvbLdxMlcOTgK1ivRHRBPN4ovnOG2666gk9/5udoxDlh4QxJChMizB99lckzUzRUuefzX2Dx+GvMvjFFN3SJ1SOpFq79UJTaM6a4UfHu/DXNrlInimJePfQmfVv28Mu/8AUOnxXOhJioMs6h2UVqw4PYTsTc2S7Gev7b3/gCdWB6tsm68WF+8Vd/mZ/53Od5+IUjTM7N0zGW0bVjbNm8gcmTZ4mkzO5VUvLTgqhejFMWDh06yGc+ew/GGIwxxHFMt5t+oDa8DXiK6NiKNyiGvi7cPnEZx06+ydFaxlyUgzGYjgMLMRFzVU9/KlRdEbDkDMz3R/huxrpFJVjD2QFDFAR1nqHcECMsxIqxlsw7rBQRu64ek+fZigEREgwm90QBTIDFPksklrzTpRJFRHlR+cZHhTvaKGAMbfEYhT615HmOGEuIBOc8dY1IxDBbA2cC/aniRekaT5IreWRZrvGqRWF0ayO89yCCMYGOWgyWRhSTZW3i2GO0StcnhcvWeULUoBkvUksMSauPELcYbC2wGNVJrOCcYqIKThxqM9AcCRZDDcciEgJ16aPbMVCNSc0ihpS6reNTxVmHCZaq9tNJTpFLg2ShynW338YNl1X54698m3YUk5oYdTn1kBEHR9To50yagw3E0sCQQeaISDDS7p27IprTZBhfM/R3pvBRAxcqNHyVZjTL6LqdTBy4iXoC2ewiLz58P9Jp88nb7+CTN93O333z73no5cdZWx/ntjs+w+c+cxd/8H/8zzz10kmiUEFIaZuEKGT0GUOUWaxmtE0/3mdopYnFkkuVSjdjYrTClburTHihi/LdF6eY7RbemEgzulrMwTbtAF/60q9z+OWXeOaHj1CPhe4ql2mXlFzI9dfdyJe//HuMj4//pA+lZAWX6Jt+EZFGAEEwPXemMwFnDd5G/KB1nGa1TauiOBcwxpAkFoxBNWBUCImQqyIKzUTpWiWOhLwekRIIPXdxWjWoVRoevIG25kjFIEFQr2TBLR+9UMyR5howkeBE0BCoZUondrQTSGNFYyXyEAdwFjBCZA2kDmMtbR+wiSUVpZMokljidiBNhKYEBpyg3RxfsyReqDuYi3ul3nql2irG4NIOibUYBOeVPoFchK7rUJdA4or5OCtKJIpqjg0p9RAwKUR5BycBFYMxICYrxtoJiCX4YmmPAGmnTVKziFpcbolig5qMSAwaIrK8SyQVjK8XLmEXMLYPRKlXIp5+7jkWTqR0e3Viq+rJXQZRIBcluA5VFXAQC4j32FCU1BPpBXuJweIw4mjnQoLgvUNChNUuCY6ps6foPv80o5Uax468DM4zYCKef+wJ5mbnWTh9FhuK5UqHDr3C7//+Cxw5fBzB9tbpCkZiNIK2z0lECbEjV49NKjQ1pRH10ck8NuljqunpnlxkgxPemFVOuQa5SaiiVGjjjOkVnIfvffd+Zk+dQsxHyRot1n4rtvj8a0A0oMYQxEIRR766Lpbr/Pa4mMjED9znhccsF32Z+nBRThl8GFmVRfrZz92LSBGxG0UxWZa9944r8AIRARt8kQRBEnKNEQn0i8Ma6DhAhCzLqNfrbwkcKSkpWQWSEYgIJERBiNUhIScXQ2oTTMiJ1fc8JYUWqSzd8C2X/z2vIq9esEH0gsv/273+Qdp/r75WbrvgfZe8/QvO7/32tRymuXL/d2lracOB62/md//9fygt0g8Zq7RIl/7CZkUE7+qJbATBcc2+fRw6eoypqdNUq1W63W5ZWaak5JJShEmcS4wixNZiCVQ0Q6SYTtCeMkjvndKLKyhEocjMJStaWrocKIoRc541GDQsXy/Oa0tWtCVLbenbt8+59s+79vTaEiNv2f+ckOn5/S+3tOL83rb9wn1y/v5vbUt771sWzXcdq2J/XTozeef+laV4RMV7X14LP0Ssch0pvYQMl8Zbo4CxxbKVT9x+E+vXr+XZF14himK8dxhTJu8tKbm0FHP8KsVcfFABY4m8I/JdnLV4s+QWPyc0BSu3rbSjVlJkfTrfytK3fd9b2+It287vf2m/t2/rreauvO0+y+L3nu2/rU35lrZCT7zf+/ze2taF/esFbXnJixE1F+77AVAPZTDcJeUSJWSAi/qDvg0hKCayrF+/ganJ47RaTYyxvULieVmeraTkEqIIxcqr4vIfsDiEijrG+yKG+wxiVlnJSc8X0uKXH/MiWz0nj8u9/7j7/Edgu5lh8gffoDU8jJEi2beed+19O0f1+dsqjSoTuw9gGyP/eAf+MWdVqlRYiMU6UtXVf0il1+b6tWup1WqcPTuD6QVuqGopoiUllxq1iDqEgJcILwaDUomUa7at49aJCoOh+x6X5ncPgZHl/3pdrnizUjiX362tD9pXkdvknITKij4vpv0Lt11oj77T8b/fsbrw9dB7XPn7ub7OMv93/zvzb3Pu77f/1xu7uPs3Ezbuu5OyRNel4ZIo08WuI72Q0Cu9liRLxcGLJSGXytotKSk5n6LUhGDweAzBCIgh0cCgTdk5GDERyfsWh/fjcHwnZ+m7tfXOztC3d+wuuUPfT1/vt/33cux+kPYvvv/oPGfv+21r5bazrRbp3FTPxVsK6aXgkiSth4vLtXsh1hqyEDh06BBnp/dTq9ffZs6ipKTk0lEsfzIUyUACFMvKfE7VtxEbkcfne5tWRqK+Hee93ruK9yoVLk9ZLk2TLgfQvIPavF1f79R+L6bn/EjZ9+jr/bb/nn19gPbP4wO1L0iIgeS9lVfPf7ryvdW8SUVy0FDaKJeIS5a0/mL+Issflt4zVdDgscbgvCdJEvT8j8LFH2vv0ax4HnrNWl36EkgvKQCoCLK8xk6KMlxqeo+9D/WK19/t83ypPqsrv49ywfZ36nc51uId9j2/3aU9364nveD5O7HsXLtgn2KsilErIjSNnusxXPD87c/u4jm/lXc7l/d/niKsmNK48C/yfrb95FlZCVfoVXMCQDHqektikvM/Y/oeFqde+F4l9HyrosJSROvSd1/edp937uvtXj/PdatLjfcigZeVSd61r3dr/8K+3qv/ix+rd2hreawUle75Uc29BhR63sFzjb7l2iBCrAbRVc57l5zHquz61c6RGgWlqJ8ZsIgGahE0KpYXXn6Fm269i927r1gu1XZx4d4KBIIJeBMw6kmCR8XTiT3dKGACWA3EroKgJF6QkJB4T+SLxeq57WCCpWs9lgzFYqSLkOPFImoIYnoiq3gTQALeht4xnJNwISB4EA+EXmrA9zoNIYjgTFE4XBGMCtLbrgJBArkt2vMmYDWQ+OL3orB10U7six8biselwuYmWFDBW0ewGSKByBtMEFQcQfLlEV0pt6KC4DHqMcEikmF9DHisOkxIsBRFySNvipzKUfEFr7iinW5UrCuOg2LVY9X3rCQlSSyhd/ccNKBSFDlYsqCWLgpGFVElN0WbNhQ/UCTj8L27e0NYHvvihIrPcXEB8oAvbp4osm39/+y9eZQd13Xe+9vnnKq693ajuzGPJAYSBAgQHESIpEiKpEQNlkzaimzrSXESy07i5TjJy3tJFNvLsZ+8khXH8VvPWU7s2JFlKaIt0ZIty1JMyppMUZYpzuAIEvM8NYae7lRV5+z3x6l7uxsESUCARIrGXqtX162qe+rUqbpnn733t7/NzPvsjbkXiqLEWqX/Wmq1ISViFGsyjHGVoipj29KrTPP6kES7lMbRMQMIQubboFCYOqUk1Vm9usH6ku0z/b303KpARbX4OFNbL9f+ma71ct+fvR3njOlr8qrXerXrv9L3T7/+dz9Wr9YWPUpuUJ2x3duvsy5xpuNqAt4kXHTrXji5QHmk57fK7qPOVPFFzvipFrvS3fz6b/xnpqaaNBp1jLGUZYGc48OPCg7SMpAGoZUExlOlVgjD3UAp0E6rH7sp8VYojOClpKgUjAtxOu1NrdLvcfzvNJD4OApGQ38FaQOoGmwQ/Eu6Lec0n6YeNEBpIkrPKrhKRycm0iQWDlSiwkCilVfa+F+NRjYnlNIIQaIVYlSigoG+5dqD56tKta/6aRtFyjP7qnpFsyEqM6NE13+/BEpvf2TOiWMVi7v3CsL3eftn5M2hMDnZolav4b0nzTKKIu/38aUm7Mx4Xm8rWsfan1Bh9rvb88vN2KVS3dX0Iid6K+JJWVpDxZEXkxEIZ+uoCj1fXOkLtDSUZc6ixfMYnzg145ozL/bayjRaV/qfoVrgYs7lFb0o3zc5z/k2rjIuTFcuCnBB80gvzIOp1+s4Z2lONQEYGBhARPoJyOdKxFSKkIRofXWcUorBlXF5lnjDgIfjBhAh2A42WIJ4rAaCWIwGjCo2CEYDLkjkphWtEtWj27e0gcIKNhi8qcrCERWcSlQsUU7Lw3vFAMqM+zDxB1CYqNwKKkVU0ewBpKWQVdumWph6A6mvlKUKIkrXgp/24WFDVKi9Va/VqDiDGIJxqIRYN7Z3B5UymZFGjmqcdHNXARhMQIiLGFGPGgOqDBQBp9oPzwSJi5EkxD4HidSMffd05Ylw1qFB8UUZFwAoQQxGAyq2rxCmHe2vIj0rVGdqz+nP8a5e6inQ6nnlRQFSAII15iWMdNZYJElIM8fY2DjWyTm/uxflolyUHwy5ANVfYOY6/3xERHDOojpdBiuEym1nhLIsz72PYplKHSfqjqZzmOAYLCz13JBbYTyDgcLQyA2NItAooF4GGmWgVlhqZZycTXCoKDb0OEghaEJQh6j2lWWQqFRQCxqJ86MLtuoPM5w3VRDEnIVb3IVolTZKqJdx22h8gImP+rgwvecQ7cPSCLkVPLFfVqOy9ZW1GogK2ij9ewCQIIgavDhyY8mNxYuN9rj0rNRoDvfcrF4sXhxCwIWYwJ94C5rgAohajFbWssaFTUDITbTxTYj9LoxQGkNpDF5MZNrJUq6//noWLlxICNHtKtVCxxLwGAzxPZl2hb3SS2GIVWgFJEz/AXFEDYKv7LTp9qa3hDRNuemmm6jVai8pHE51zurVq3nbHXdQb9QjIv2iXJSL8oaU1zRGeiaJSGDBmFj/U8T0QU1nEyPtnR9dwEJtyULe/bMf5ud/7Vd493vuZqQ2h9AqCEFoDaSMZgZfWpzN6HYU4xzeg7gGhVeC1ChUsUkDn1pULF2TUVpL19TomBQJQlIKqXckmpKGFNMKuBwapSEpPM6CL0p8AK8GkybVzBxwAmUZmZsid/FLrZdWTegkMT5aitASz6QLjCfKRKpMpNCsWzqpQZ1lPO/SNIE8tbRTgxpLWsKcQrBFyYAaarnHBaGhNhYyr8j+rUbFF0zKqg1X8fP/9iP861/4JeYuXEwehG4ZSGo1SlUChmBTCpPRVhcVfdvS8MJwnlIvUxq50ihSarmSo+RiUJMwXpaUjRpdY8EmtBXKNMGLJY/lb1AjrFi+gjdddx3jYydx1nLb7Xdwzz33cs8ff4Y3Xb0JbIL4EmsTrHX9MQRTjWm0INetvYKf+ZmfwZiELMsIIaCqeF8SgqdWq1GWob+4MQREFDSeh0h8PwSGR4b5e3/v/SxatBDvPSIa308B5xx5t8v+/fu5+urrWLRw0XSfKpd3TO36uyACLpvlSpSkDudL7P9Giu8ZF8foDCJpg3NiIXojjcsPkLzuGA5mItbg3F3GqgFjLCEEkiTlsps3880nn+TPP/VZBjoljcIzsGgh89ddQp7Cjhd2MUHK4iVzuXLhzYxxjNbuQ9glq6k3T7Bw8WoOv/g4WibYunLFiisYL3IOHdjDxGTB8uVLWb5sLsdOnWD/3kPMXbQEE2D9iuUc3Leb5vGjFF3PoK/ADy7BZTVu2LyZoYGMF5/bwqH9uxkams9VV21ieGiYrS88z8GDB2cpU1MEGt4wWACFp5UKzYaja2LMcYCEfKpgnmZcYgYohucSnDA2Ps54t8mqoYXUhhLcZI7XFvXCUXSUU96zMKlxotvFZ9KvrqNqmDMyn7fc+Q5+6/d+D9OdwJUFtj6HpYsXsGDuCM2pSfYeOEQeDFdcdS1pfZATx56hdTwnrynL5q/lGF2O7NhKfeEihhuWFXPnMzY6xv7de0gXLGHh6pWkQTi2/yDtdpO5SxczXKvRyFIO7N9Lt9nkX3/k3/Gx3/tdvPcM1Bvc+Y638+8+8i/ZNdpmgUyyas3VmFP72XV0gstXr+R4a5LQLbh+49UkScr+Y4c5PnGKzZvfzJUbNvDuH3oPT2x5iiNHD3HppSu48sqN7N61k+07trP5+htxBibGj7Js6VIefuwxOt0cRPEaKMtAvT7AsuXLuf/+L3P48GFQWLlqNQP1IZYsXcjO3VvZsWMXRVHwxS99gV/91Y/yr/7VP6PZapIkGevXXcnOnbsoyx9s5KSZu4LkspsgeMLkKOX+p9HOxKxzJG1Qu+XDdB/7HGHyGACNu/493Uf+hPLg09/VdSVtkFx5J8W2b6HtsfO+jzOKq2OGFxNO7PnetD9DkrVvxS3fRPsbv/2SYwM/9uu0v/G7+KMvvmo7ZmQZ6ab30vnbT4E/twIiF+X85AIV9r5wMdLzF+lbpCEEJkfH2HztDaxZvRb1hnygxjV3v4uJokv72BiuTFh6zZtYeu0mDo0ZhjddgQ7P5Yaf+ClWv2kTZsmlLN+4gcaipbzzAz9GU4Ul6zcysHQZc1et4/LNN3JEA5s/8GO0Fy1k4w+/hyvf9Q6OiWf1TddxipyybgnBkyQpiPCmzZtZuGgRu/fsZnJiHFFl06ZNLF++jCNHD9NqxfqcM8V4ZcXwfG66dB1vv+xqblq2lmFvIS+xiSPrBuZ1LcvLlNsGL2FNWWejH+K69gAbZR6311cwOFWyacEKllPnqtoCljZhhTRYN7KEJQPD+MLH+GOI5dRanYLRySnecdddNOYMQZKw5LK1XHLFlYx3c060u/i0zt0f+geU9Tl0a0M0Nl2Ov3Q5t/z0BzngDEPXX4uuXsolb7uNlW+/mbEs5eYfuhsZmM+1b3snYXgebv4Slq/diJ27iHe8/8eZu2gxwaasXbeBkXnzSFPHzh07IATybofnn32eX/nlj3L1dddTTxNWXLqKf/ozH6bRaHD77XdgrWHz9dezZMkSTpwY5fjoKM1Wi1OnTtFqtjl08DCdTs7atVdw++13cPToYW648UZWrVzNBz7wf/CjP/o+/vGHP8xVV21k/borsNbiQ0W0LkIZlGazxdvf9jbmzp0HAnfccTt//yf/Pory3ve+lyxLAdi9ezfBlyxYsAARIU0T3vKWtzAwMPj9/2lcYElWXE266Ycww8up3/ZPqN3605VlJdHKArAOu/SKaFlV4lZeA425AIjLZltRImAqtLCx0+1A3DauCp73yFqYffy0tqRn6c3ctgm8Cm+3W7yWwff/x9n9Ot1qFPPSdoybDeQ5zRrvy4w+mJEluGXrppudcZ1kzWakPnRa505r06axLwpiU84JxXhRLoi8pnmk3wsRgbIMOOcovWfXt57k8I7jfOAf/0M+L3/KvJE5nDhxkoNbd5EWJYkd5rqrbuArD/wZ9ZMr6JaBhhlgsp3y4De+yTU3f5B2URDSBk/t3MHT23ZwyxUbmFLlH/38v2D//p0sXbyQbY9uY6idsqAc4NFvP8ix7S+gi4ZY0un5SqHUkqJU9u7dx53vuJP1a9dw3xfuZef4CW644QY+//nPs2/fPur1+kvAKw01lKNjHJ8cY6gQugOWelIwZyBlqtXF25Ry0DHlDe1ulx1HD3LZkhVkNmFo6VzmZYOscktZlg5ywNSZ3xEWzFnCqfkNbKtAWl3SAUspPqYMqKHdzfmje/+E667fxM1vfSt//ZWvcsnl63jhuac5cnAPqrBuwyZOtro89uxW3vneH2X3i08xIgt4/uEtHNu6nxVXXkXWVq6/HyqeFgAAIABJREFU7Bq++PlPMKWWw2Mtlq2+gsuvvp45p45RTnZ54ZEnKNIBjk22eHzLFhJjGMxSBtMEl6aU3qOqFEXOZ+79DE89/CA3/8g/QtYM87/u+w7/5K6b2fzmN6OqnDp1ih07d3HbT97K+g0b+cu/uo+HnnyMF17cyhWrVvPsM8/SLZVbbrmZO26/k8vWrGXJkiVs37aTLM349iMPU3NtXJqSZSkhRKBbIHIA5UXOrt27EDPtkk/TlK9+9ats3focb7n5eoIPiDGoerp5B5ckqCqtVpuPf/wPX/cx07PqnRj84RdpP/j75M//FQPv/090H/9TBt77i7gVmyiPbaf5578Wz01qDH7wtygPPocYi6QDNN7zi2RXv4vQmqT5F79GcuWd1Da/j3DyIJ3nvkb9xp9AxND8y98kTBxm8P3/AckGaX7xP5Nd+TbKXQ+h7XEwlsGf+E2S1dcTWmNM/q+fJ7v6vWRv+RBiHZ1H/5zsTXcj1tH+5h9Se8uHkKxB+1ufIrn0Gjrf/iP8qX0Mvv8/MPknHwGB+tt+FrdiA3N++g/IX/gW9bd8EElqdB/5M1oP/A4jH/k6hBKT1pn83C+Tbnw77tI3YRrDFDsfZupPf4nGXf+e7MrbQQOT9/yflEeeByC74UPUb/tpJK3TvO//7Q+nmXsJA3f9Em75BvzR7TS/GBW5GVnBnA//LMUL38QsXku27q3gcyY//W9IrnoHtc3vp9z7NJ1H/4zaWz5E52/+4KIq/T7LeVmk/fI+qq8dIlEiI0sPYRlUEecoxDCyeAmXrL+MeQuGOLRvO5NTJ1AH0qhx6fr1LFy0iNRCs2izYOlyNrz1SlxwNOY02PPktyAISxfUaZ8YxWUZ7YOHqKWOkcEGfvIke/fv5YnHHuLRr3+V5x98kOX1FHPiKMdffJYhAs3Dh0gUNPd4iajWxBrydpMvf+mLvLB1Kze+5a0UOI4ePcq1117HNddcw5w5c15ym4UvcfOGGNy4iuSqlZhLF6L1FPUlA2mGC0pe5DSTwDHT5eQgjGeBVqoc9JPsHD/GidFjPL7zBU6Mn4JGSlLLyCa7NJKU9lSTNAgGR8dYfD1j6aVLWbfmUhLfpTk1QV6UWJuxdOklLF2yklptEK9Cs9Nhw3VXc8XGdZSjk8xLHfn+YwykgcHOFLadM1dLmgeOsWx4AQf37CYvOmx7+mmeeuBbPPvYoxw6uJ9LFi/myI4d6OQEptNm4thRJk+eottus3z5cox1WJdw3dXXMDJ3IaP7d9MqQMouv/MHn+S973kPW55+Ckoo85z77r+Pxx5/nFtuuZXhgTmU3YKBwUE237CZBQtHOHz4AH/9wNf48y98jt/+b7/F81ufZao5gXWGpD5IUItiAcMPvfuH2LB+PUKgniRsumoDgwODXHXV1YwMz8V7j0sMQQNpUsOrxQdl2dJ5DM9JOD46ipgBXDLM7bffxrIlI6+SYQi+yn2Of54gnlDl88ac3l5OakBitBqLx1DGAumUTGdQSj+lZeZfYRJUShJapEExoY4nifnPcvZFvbUzheZNsuvej118Ge3v/Alu6XqSK+8EYOC9vwAC+ZYvocFDKCl2P0bzvt8iTB7DLVuPWIc/tJXml/5TVNDf+J8Uux8nvfYu7II1+FOHaH75v+JP7gHrpmOHqhS7HqH1V7+NtsZJLr8FjKXc+wSTn/qXEArKPU8w+al/QXnwOdrf+H3ybX9Lsuo6ymM7qN3yk9gFq9C8jXYn0dYY3ce/gOYdmn/2K5T7nqT94CfpPPp57KrrovVXdml/7XfoPvsN0o1vBzGEk/uY+tNfxi5YiZl7aezTV/4boejgLr+xP1b+6A5aX/sfFNsfJr3iFkQi8C1dfwehOcb47/8jwuQJ3OW3AELt5r+PH91N59HPUuz8TmyzLHDrb8ct20D3iS/R/s5n0KIFznGRP/f7L+dlkc7m2H0tFKmihBnVkeJk4SWSFJxsNlEzyoBLeepLO5Gpk2w/fISxS1bRabdh7AS1Qnj0r/8KUuGbWx5j7vy5FGMT6NbnmWMtW776eYoT+2kOC0PdoyRlnSe++jUYHeXLf/LHDNYU1x7D0mb0xB4e+vYxrGvSVsVYpTAaqzSEuOAouy0oOuzbtYOx46O0Wk3U1rnvvr9k3rwFlQX0UuBWUbNs75xge+fE9E4LMWXDkwaYg6HVbbNTTtJKlAOTJ8iaXQ6rMpJ6Csk5mUUQ0snmAeYVFilK1Nc4npU4wBTgs4zSCv7kKC5LmBg37Bk9QqqG73zjG4wMNpg8dZyaEw7t3M7Y2ElawBc+d4j28ZPsaD1Ns9XCGsszjz5AuzPB5z/zh7QmTnLgqSfRagIsx4/iQ8CXHlc0ObnjecaLNgOhhHaJBToT43zqDz/BO9/xTj72sY/hnOXk8eOAcGricfbv3wdFyeGTTXbs2MYLL76AUaXT6XL0xHFGT53k4cceoTk2CaXns5/7HKCMjR9ny1PHOTZ6hDzPSdOUVqvJp+75BCdOHMdah7WGdruDD8LW51+g2+3iFDpTk4yPneB3fvd3UA3kecn9999Pq9Wi2+1yzz2fpiiEWj3hXe+4jd/5b/+FZrNJXgwQcNx44420Jw5y4Ogrx/dMmEEFV2V6TifqxxQmL716omFGJtXsPOeZv5fT025zSbEyiQ1trK9TkuElIUhApDhrRSppHbEpZmQJWhYQSrqPfYFwYi+sfhN20Wr8tr8htE7F87MBktVvQn2FxLfRJVoe2kp5YAuN9/wCZv5KUI/YhGLnQ9jFl1O/7afpPPTp2dfO5pBtvBM/MYrYBFx0q5d7Hqc8+DTJ2psp9j5GefAZarf9U9yy9eBLECi2fZvaDT9OVnQo9j4BoQRVQnsCfEGYOEy29mbSa3+YcHxvP489TB6n2PsEKo708jejZU5364OUB58jtMYwjRGyjXei3SZadJAZLmq35gbcwlUREGJs3x0tgwsoDz5LOLUff2QbpjYEIth5K8ifvh/Uk218B9qeRMsOFF3a3/oEtZs+RG3+B8mfuv+sntVFufByQbh2LxRp/bmLALZPo2U0vpBalhhrCZ02bipHy0DLtxmqWeqJZXz7LgQlDR3EWLL9B+iQM+IU2XuAYbGEvESTFN/uklnL1PGjdH0TawKt9l5SDbQO7qdTs1iNgX2vJePddkwnqfIiATQoIShpmmKM5eTJkyRJwvHjx/tW/fj4BJOTU33L3ppzS4ZvObBGCKVnFxMYMZzULjIIoQy8kJ+iEKXbEDoWEt/lUFFQzxxt36G5ZA71XEnygJQFRVEQyi7dSaVT5Awmhnani+MYExMFtTSlOzWFc45uPk6h0D1qGGjnlN0uNQwhdJlotrDGcWj8BQYkwXSalKEkeKXTiopEFVINhO4UhMBMjKJzjscee4wVKy5hzZo17NmzhyNHDpPnOc4lpEnCm998Axs3buCJJ56gLEuKwvfHsyxLRIRavU6z2WbXrt04F8Foxgi7d+8mTZPqPMO2bdtwzuF92c9bFhH27dvX/44I7Nu3F1C8DxhjmJycxFpLWZbs3LkD5xyrV6+k0+ny3DNbKXKHc463vvUWRkdH2b1rz6v+Yoya6XxXZqbfVHaoKEEqRSS2TyIBVBSMnjTk/V8KM77b25OEDC8ppSkw1lIqgI+cTiEydr1iH+euIL36LrJrfxh/5EWK/c/ill2JP/wiYWAeYWIUFKb+9Fdp3P0LpFe+LcYra4PY+StpPfiH1G/5yRmdi4vIZO3NFDseQtIBZGgxdv5qih0PY1dswsy7ZHYf5izELl1H99mvY+cue0lbcTvetVu+gfLQVuzCVQhQHngKf+oQ7tJr6TzyJ9NoR18gaY1k7R24VW9Gp0bxo7uwC1bOHERmxmDqt/80JhvADi/Gn9iNXXwZne/ci1t9/az+JsvWU+x5HLt844znooQT+6LCPrYTt+42ug/fCyHQ+c691Db/GMXOh7ELV9N56DO41ZsxtSHM4CI6D3yc+rv+FVL7wY+7/6CK/ehHP/rR7+aLJ0+e5NOfvqcP64+TyPmjEJMkwVfxsFdj34iTSaxeIRoLFDuJLDaCYgXSIuY7dtMCSYWiKDAYEpRcOmjdYqdyXBII2o1K0ec4awjiKbQk+IALJRaDLUuSUJBgsGVBTUE1uqqiI1DQvMSJqWjRFCOC9PNgtRqz6RizSCTsDyFUk3jA2HNzz5QWfAhYa2llgi0CuYMJGxi0KeOJJ1hoq4fUEiouCHVCbiG3iis9iYIYIYQCK1C2WwwmCaYoqDtDUbapiVJOjdFwhgSPFDlJKKHbZsAkOCLpgkNxCpQFqRFMCOBzrHpqzqBlFxs8xuc4DRhf4qzMig97X5JlNbZt28bExATe+yq3OAJ3FDh27Aj79u1l585dfWVn7XQN25jWUlTKsZebHJVgL6VKVTHGMJ1+VS3QxPTfxxB85CpNEkLwGGNi0fkyWjeqVepLnpOkGRMTE7zw7DP4okBtShDL6Ogozzz1OK3JcXyfgu9ln2okfZDo1lXxkerSelQCli6p5lgtK0pFP+3arSgWlSr/l9N5uWJ6kAs1glGCURRHKQnBKnNoc9XIAOvn16klL7OkMw43bzmmMUK59wk6j34Wf+ApxCYkq67DNIbw+58GLSl2P4w/uhNJ62jzFMXOh9Cp46SX3UgYO0y590m0dYowdhh/fDdh7Ahu8Rq0aOMPPos2T5JuvJNw6gD5k19EtcAffA7KLtqdBO9xi9cQJo9S7n4MbZ0kTB4ljB1Cknp/W9uTJCuuQtvj+EPPUR58Fju8HFxC95HPQtGJ70NnEnEJZnA+xY6HsMOLMbUByoPPUe57EqkPUR54Js5C3SZmZCl4j1ih+9R9+ANPA4Jbug5/dBvlvi2Ek/ti290WyaVXo82TlAefwx/fhbYmyF/8RkQkr34z5a6Hybd+A8kGybf8b8LYQWTOAsKRbVWbL1IefA4ztIBk3a0UOx+i3LsFRCi2f3v2IuI0OdSGBRtvZnjlxnNLrbkoLyui32Vwc8eO7dx117sRI/0JpdvtnneH6vU63W6X4P3ZK1KNlHlGtapDqJQhxMnBZHgJdFwXn0DWEgZyi6aOtmujvqRW1igddEOXWmpxHtQLhQjBJhgv1AyEEEhDAF+ikuCswQdDYZWARxCcNRR5gZWoRnuxW98jk+5RsUlsz1p7Bleu9Cf0s5XSgA2KVUPLKY0c8kQonTDQDnQTqJdCECjwGBGyYJGgqIHcxD6IKt70GIsil6cJke0IIxQSImWBD9jKJdXjABJjKnRrdYPaO9pbOICKEIIixlQ8RJGCSUTwwffrz/afsWo1Rj56woz0GbV6gJ3eOPWuEXOQe6lQ0/nIve/E0/W0fN343xiD99Phgh76u3ed3nOLijYwc703nb8MvrrXGgX4ktIkeJMRVEkoSLUkl3T2U5+FOQhkWvZdq9OO3Yq0sG85BsRIhQCVeN8Vujhg6JL1F7uCor6cBQ9s5I5uUlC6nMQbVBNKqyyWU7x/9ULet2GIkVpx1u9hX4wD9ZXFNtOhXDFq9fYbB6HgTDYzxkaF0HuPXrbNM13zVfoWyv4LM/xznyHf+gDtb/7P2W2KREUTyqovWrWt0y9bdd7A+36NYu/T5Fu+EM/vf99AtfCb1fZpfZh13Cbgi+k2+serfzPbFCLK2Rcv7dfLyOMnhfUf+LdccuuPw6su5i7K2cj55ZFWLt3XCmw0HQfqTTeKD4oYwaYJGgKFsdTnzWWwrpw6eoSGzUiTlLLdYSA1BJcSsgaekqSWUnRamAAmRGCQipCLoytQz5Rue4rGQI0yLykwlBoIRUkkKo82qTNmxm9mWpnOnCx61k5UBi9VmOeaTuQCmBCVReZNJAgIQKkEI5WbOfLdOrGg4PF9kgAboLCRUpAec1HlMhcr+Io20BsT6QCt6Vu1SIxVg+LtjH7L7HtGQHFgzUur0giIcTHmPYOaT0QqRSaz5gjVl45R79i04ovKVKr7Od3JMfudleq7sxcwpy9oes9tpjdhZl/726a6ZjAYcVXqTLRcY7zcvuSxB+/7ZCRiHGXpqmdQTZjVu+5sJO7AGEoCpfeUvkSUyh3tKz+wUDeeEOgzNSVSxVk1Ek8MlyW59ZTBV4UMLMHCgqQgFf/dQx/CTBYynb09I5Yblejp5/QH5CzbPNPxs+hb9fwn/+j/JrROvLRNVdDyzH2Z+e6o0rr//0N9Z3YfVKNiP1N/T+vDrON+xsLl9OPK7DaV2TmjZzEPqyoawsx1/UU5T7lA9UjNa5ZHKj3EroBiwJrIuKOgNiHHsHz+EpbPncNT+04RgtAWwWUNKKZwOCakwYZrr+TosYOMHdyPC57ERy7dMkTg0vprN/OOG9bz8U98kmvffANpyHnwsa14LbAhx6UuKtcy5ouGilA+jsrMkmLfo3HQ6dJUtrqWVTC+wvAF6No4FSMaKQJnKFFXKUrRnn0ZV94iQlBBKkq9WGklWjvTWU8xKCxIVZXlFaRS6Nq30Km0W9wXU28u8OC8JlIp8H6cU6f3IaD2DPcpoIKGyBvcTDJUemSGGse+cuEKYIuA9UoiSk1AJGB8FysxnOBEGfBNksSRpY4scaRWSKyQJhZnDfOw+LrBZJY5PiHD4RuGuu1y+UBGLXl5F+EbRcLUkfNuQzvfI2KI74FktQyXJK/q8bsoZy8XoPqL9F1e33/RuNIWiGXGwHtF0lpcfxvL3FWrqc1bwHNbnqIwCencubj581iyagXFiVH2PLeNRRvfxJqbNuN2v8iiZZdw4Jln8M1mrJ4SlCQIwdd407or+crylYzMXUS9e5KOt1yxZhXzBwPPb3s+AgFDtKAiL+1MWMf3Vrz0anwKhYHMV0lBEsvC5VXI1VaeKTWRb1cqY8cGsFW1j57rMxo1Amp60V8sJdovcGahV5JMokvNhFdxFckrx9HPinD+B0YCYCtl6qNFCsSfnZlleUPP8uz5VmC4O4aVgBUlkUBmhSyBWmLJnCUToSZK4gyZETJnqNmoLLPEkhilTkqWOGq1lFpiqSWWxAqJNTgDmeQUicUYw2BuqAVDtw7BGoZFqUv4Hi8BL8r3W7qdbsRr9IudXpTzlfOu/lJt8do9kV7MIrorXZrS8YEghqH5c5kzbz6yYD52/jzsaGB43eW8/ac+xD2f/ATXXbmWyQP7GT14kKHjK3liyxbM1ASNauWfikESw5BPKHP45le/xo/c/SO8uGsfVpU0bbBuw9Vcf9UKnnz6yar2JPRYRnpD8v14X4OZBumUlSJVAW8Ek0OwPfdvRcveGzZiDdDESySkByo/K0hAtZehSKVIPZ6q8o0U/Qge+GgRhfQMvavaBCDnTFVVehKV86sBIE5/32Z/nhGNOw85Q8xuxpHTlcusNBGN1iE9iI8RjFGsxEinM0qikFaVzHuuWyOGWq3G4GCDeq3OplrBUBKiAnQGF/JYbNt4rMRFpLGemnNkiTDgDAOZJbNK4gRrLMbViIFTj2hBagwiHgkBCR6hJE9iIfZBA0kQukmgaz1pCKhm+JeZJqQ2hLgaYerYOY1s/fafI3/uq/jjO2ftT698J+pLim1//aptpFe+k9A8Sbnv8XO69kWBxLmIRbioRC+YnJcinSat54KR1p+bCKKzLSAtSzIAheLoQU5MTjH3vR+kmSu5KsOXrOe5z/4F6fY9dJatY6gLQzVIT51kYHKcxvgkTgo6aYwhNHJDR1I0KTlSKqcO7OaS5Us4ueM4vj3O/ff/Bd+8bxITPCEYTJJRloKIjSkwlaIPZ1O8+zzEzWDKyXxUpnE/tNM4WXuxeBsHR4h1VE0FnsiTUDkfe3mJVSlmDUCJIZanziswkGhVQgxBggBJhSExaA9nxAzFXP1qrYbKfUw/3xepqAWEqs6qzlDo8YDOxGJoN4J6JIKVVCtXscQQQylVWbMKHNLLvTRVyTavsWB39KRUpbv7/VIUg8dFaz0EJASMxCLlolopSos1QmIgkUDNKZmBemJJnYARsEJmA3VXUrOezAg1o9RsQeo8C00gTVIaaRItRSM4gcS0sNLBui7GKMbE1KbUGowRnAErghOL7S06+gCemXFCT/AzPgv0wDuxvqyjXsTn3DWGiTRgKUjUk5RJrG4UB+HM79zK6zFDi+g+/mcvH580NsYXpfJeqJJedxfFoa1wfOcsgJBbvRnKDsX2b3JG1KmY/n63+k344wcqRVqN90zQ3jQCbLoPp/dpVtt2RuzxjS1FVaTholw4uSCk9f24z+tQ6mnKorolXLqME05ZWDNs3bWTRpZSjI1ifE5qSubNqbF21aW0du2hOdmLd/Qm8IKEEjGOR77zHd75kV/iWzt3Ijbhpptv4saNK/nDj/0+nTJQFB5rs9PQoK8H51jA9RCNMm0/9VWdglJW1lZ8ljHuHfoAXMUSdLbF6ZH+pCVAqu3pknEy006LVuPs2GoV49Y4D07HlPvQH0R74Bit2hU6bnBGeDWgoeevrtoIsVi4kSr9iKgkY5wxUJrec/XgQ/8cKxqVo5TMkSaJE5wxWFHSxFBzlnoto5YlDOKpSSBNLJll+s8ZnIVMLIPGxXikUTKr0TVrwUkc8DyNKTfWCFYgMVVdVS0hKFZH6AGaREOVvNKzdqNdX8wMtJ72EzQaS+69klhVxCsmRCCTYKvatJH5qLT68v6DEBDryG74AJq3yJ++n8H3fZTO39xDcuXtmMEFmJEllIe34RZfRpg8TvubH4tdTWrUbvpJkvW3oZPHaT/4cQCSK25lzqLLKA+/SPsb/73v9kqvvpvsmncTWhO0vzJN7m7mRp5fM7KU/JkvEyaOk17zHkw2SJgcjSlWC1bSefhzFNsfJLvmR0g3vYvQGqPz4CfIrr0L0jp27nI6j/wZxbYHeH38Xi/KD5Kcp2s30CtX9nqNW09NTvDUN/+KJASOHz1M++v3M3XsKGmSsPvRh0jzgvbxgzz5nSYjWUZiZzruIvjD2cCuF57m2J6S8ckpfu9//C5jhw9hrGGi3WLVmstxSYLTEhFH6XuzvJ4Viu77IQJVEezT3aCVV4FYBD2ChSo7uk8AXilKFTLvK7TtdCyvAogC4I3Oan36WhXyVmMCR09Bxu0exaNSmIzcDFQYJo+tjhtCP35oNRB8iQkaXab0LOuqfmgarR/RgKjHBI8xMbfXGWXYwogTGvU6g42MRmKpZb3YoiPDMyefJHMRpNNTpokzEbCTJDgb0bNGwJqoJJ3RChgUU7dEQmVtxX5ZCRgMRjwalAKDMTaSPBjwvhufiBXESUSDB6DnbTC9CPI0gvOVYsqKkttXfv8KW7mINcSau1iC2Ej2YEKVUnXm75rGCDJnIaY+hLanQBxu1fXIk3+JXbIOBIr9z1G/+YO07v+vZNe/D7fyuurLDu20aH/9Y9Te+lMka26I+8VQ7NlC/Y6fId9yH/7ETmRgHo07/xntb99Ddt2PUrvlH/b7kL35gyCW7tNfpX7rT5Fv+1vS9XfQ+dYnSa9+T6xKs+dJsut+FH/kRWp3/FM6376H2pt/nNqtH8YMLUQ7LYr9z1C7/n0UO7519ujfi3JRKjlPi/R1qj1nii+YPLAP6xxWPc2De3DWIXlJRkTkJBiaJ48x1c0ZKXsIyxjnVPWEwmOdMtUqcMbw4vNbseIILmP58uV8+StfI+/meBW8VACTvrw+FCkIXmJxcrRXWLxn40Tr0WqB04JedC+6VKt8GInwGDsD0Rsqd2+fUEcg13QG02eY9YYYhCAJAYk5v+qRHomAVMpGIdWYE2c1VLyxUVFZE1OSRsw4gkawjDMkJsYds8SSWEtSFqTO0shq1LOEgSxhsJ6SWkuaGFJTkqjHVt+zKIl4nAFnAtY6TLIQa6O1KFDFJKt7UsWq7RNuCFAWOcYrSaVcA4rXssqzjrFzr4EyKGAxVkiCi25pH+LiSywqStnLTLA50qs/juDRSqnGcbdBcK/APKQS3fmv8ErQNQ6ngVQ1QvckpRDAlKi2sfHuX/3t6qHWZkj7K78NWR23cBX5c1/GLlk7XdlEA9QGSK95N6YxHGn9RChe/Bbdhz9N/dafROqRc9otuAxJaril69HJ0UiW0BgGiAxFLsUtWYs/sh1BKfc9Tefhe3HLN9J64OOIE+yiNdiFa2M7yzYQxo+gnUkYWkjrvl/HDC/BLV77dwPJqtPemx+EKfwHQS4I124MRb1eFMZssQbKvAPBIkaoIZGhBsWGSKPgrFKKodBI5GCcBWNQX5Amjtx7fN5Csxpl3qVmHSEYUhP4m7/5a/zEGMZXyqfvtpyZRgKv9Rsb4UDRiWmsnZWf2RPREqM5zrjKUorEAKX3+NITEDq2DoASYyxihF4OqUog0xh31BBdlDEk62MMPSjWeoyYvpVpNeAkKsrEWoZSZWGjoF6rMVBLSJ0lNUpqY7ZwllgGizGcsaQWnJEKxSpkqSV1jgFncZWlaEUqMvdI4m5EKUyKSh1jwEjF9xMKDD2LslIeGiKzAtNWdnSzCtBLgI/7nSOic6GK2VaED0AZIkI6qENNdIULhsyHyv1tsFWc2GsPLw0hdKISleh0FTFgKhILhFLAh+lYYERcz/AHqEF9nZkW7ExRlK4XQiihKNHgaAdDOyhOSgZtF1vPXpUDXbtN3OLLyDa+C8kaMw5UHpkqrqkzYphmcAHZpnfR/ts/xs5bMatX0yQMUfzEUdTnFLsfR5un0LxJuumd8ezJE6gI3S1/GakC51+CXbiGvqbQABpLrvmJI1DmFLseQVsT4FLsojVV/14/3qPvtaRpinXu78ai4fskFyiPdEbQ63UmZfDYrIFSEHxB0ASkl/DssFJSAHlR4lxK8DEH1QdPYqDsdPFphqFkqvAM12vQbONxuLJFc6LEFoGsNwZ9d2g/YFdNCq8xFZcYjE0qEE4A77FUcTEtEYFCanTMIILGOFkZqfSsRPKUGGMskcplbSUS6hgCplpDDHVHSauyYrXUkaVCPc3RyGizAAAgAElEQVTIshQnhhGZpO4KaklKLanFNA5ncc7G9A3jGaSLtSZS3oknTW3f0ksSg5N5WGMwpock7rl24+dgo5KL65kQF3nqYx/FkmqFWK30oIjOcMMLiOJNpxq3+C/0AFAarU0hISrb6vEaA317XSuLXiudEIk9os1t+sfKIi4wvPbquAg+BEoN+ABFUYGmKld7UAgaKu5myK1QGkOoEuxDpbiCBkIIeBUmtagWNRGUJUQCld53uibBlV1c2aUMCS1Tp1Ah6x7j8pHA1SsXMpCeaZqYftfzJ75I9g9+i9ot/wAtOpH5K2+hoUSCR7vNOLZFG3yOdiYJk8fwo7sZvPsX0bxD/sIDaN6CootqIHQm0crFGk7to7vlPhrv+b8QhNZf/ddYqaXs0Hn0swy+7/9h6MP/nXLf0xS7H0M78XrabUVyeqNop0k4uYfus1+l8d5/gyC0H/xEJJUPvt/n148H6Xsn04utN/69fr/kvCgCf/iud1fQfkOSJHQ631+KwLOR0sLIwtXMn5exa9tzqB/C6QRCIOgAVqcoXZ1OPcHnypCPNSR9Q3jnrbcyvnsvj+/ah9Mp5q3ZxGWL5jN19AjPbtuP8yfp1hsYb0m8x2MJfbL53rTpq08XBNd1XlKRyGE05oNKKHG92J2BnFhCKzHRmnMScAZSgcQJqXgGTIfEWlJrSCvX6mCjxpxGnXotZYQSi+Aql6shVAQAkWhhMIyTGk+WpmQuxVkbeYmN4IwQVPucwWJMVAyVIvCR94+yYgqKwNyoWHo0eACmjOXDolo0IKYfatSgBELllo7ze1R+USGFvsLx/TZUI49xz/PiUZo+oaMSlRtCETyll+i98AGKgC3jd0JPGYqhDAHvA14DnYSKw7ePKyaoUgZFg2JtPfI8+bjPqxJUqn5CWwPtoBVVYWy39L6vOAtVxvrKNY5jWRR9JaoK2AZZ6GK0S0ccbTuIsY4lnOJda+dy9/qFzE9e+js0i66gcec/jxy7D91Dnw5PQ4XS7SFsKzCahunfc4/iTgwkdchb1YKlZ12HMyNrkyqVx+eVEq8WP8YiSQPNp6oTe9c7Qx8gXjP46XbOdM4bWB47qaz/iY9w6a0/MV1E/aKcl7zhCnufLqpKVy2Fj9NnaVKMClYFT4qTGKXbsOlaDh84SvvQUVRh3tz53HbrW/n0U89QKtSTlMlmm8WLl7BqwTye3b6PxCq57yI06KmpWTLTynmNxaBkeGqppZGlNNIGI4M1sgookzhhMHRoaB6VpA0kImQmUHOGLLFkNmNObZDE2ZjKYYVUwPWqW2obtVlcXGkAX8TYp/oqHqpMmgZddZTBk3cVDWW0prwSfBV1lWk6wFApEJCKTF/AtKtjUXloNQn2rC7vbMV3FVmZymDoek/hA2WphGDwQSiCUvpAGaBTeryHUpVugKYKPkQFGkKIyra6ZrTqo9UbLUiDiiX0SvgFoZDIJBVCiApco8net1hV0NAjzI9o2cgnLL0wKCXj1XUjCMz3rFtizm9MT+qR0FtiQDWhB+qCl65FtWdWVzFNKTO62sFIm7bLaNlBCIZBL4QwgoaU6MY+TfIm+VP/m3L/lhmu2BmKr6+QZrhM+//99Dl5s3/aLAvpTOkZFaH87PbjudqdnHmXL98HiJbxK/XzDS6ir/189EaTC5RHGs5YQ/O1EGMcIZRVJQ9hzpJLSOYtZ3TXA2RFk2JkBLdoFQNzBijbOZP7Hqa2YjNzN17PhHmIgcZSxg48RIdBxscPcfjgETJjmQqe8vB+Dh66hkuWdUh0jNKMoFoQxNMyBSTzGBpusOmKdYRuh+07t3JiMnD1usuZ48HOnceTzz6EqS1lcXKcxctvpDO2g+d27Cdkw6y/YiWnTh3i0L59WNPAawSfBFNiNcGo4CQgIafWS6kwkfKtYXLq5GSJoZYaahaGB2oMJIZGLaHuhAG0coFGbk6lBVTLIGMYNJaatVhrsdb1Sd2VnlUotIOl3Q7kZUERYvwvxuqiG1OIE5pWgIYQtU9UhqqU+BgHrFyROstiUjqmxoQZREPoKzHvfb9uqdfACTNS7S+jdec9Pnh8WRJCYMK46C71Hu+LM/DynuldfTnX+8vtr38Xb+e5Sja9OWM9Nr1sjS7pM06LMv21M+3vHQk2EDRUFngO2sUiJNqmIRmelLY7wxWmDsG2Q3H7TMdnXTIi4XvPQV/aqwsuclpgV/vomh9w0ejximmzvayJc5MkGFye/52wvr9fcoH8ja+f9JdeonEIUK/XqA8Ps3DTVRwee5GTrTbLr9rIW27azDcf+Drr33wdTx7eQrfTJu92mTxxCpms4YtAJpEZ5mw4hHtAEGctl122hm7eZc0llzI00uA7j7/IP//5f8aX/vhe5q5cSTKgSLaIWzcs4OsPvMhdd9/N/o//EeM5bNiwga3Ptxk9fJgi99G9VcnK/ACbrriEgYEGiTRIxEegjtU4j5k5eHFIKBH1SCgxWiKhgHaHSeCIDEUyAg19t6j3IVqCWlJKgkeilaglZaWYepZeAIqYekmpgZK47VUIRHdjiyxaYT5O0EBfoaoqXdvGz7Aee9K3JqWJlyP0Aar0wD6mj151xUQ15tV3g/YJG0Sga6aLBAgxteTviLFxzuJNLPQQOY6jp8ZJQrAp4yR0utA433SQGWDEM6F7vydyuoX7epmgzlO0SoUyEhe8Za/qyznIuB3Cp7U3zJi8HuSCFfZ+rUjrT5cQlCRxhKDkec7koVEWXG3Iu4ZEBli8aDFbH3mCI9t3sWz5UkwO+dQYk8ePcWp0FCYS6j4gJtKmnd3LpjjryLKM9evW0xofZ3BggFZ7DOccR44d4zuPPkK+ZQvJAFx/47v4xtcf4JEn9nPswNO08y55brn33s+QJB5f5Bipz/p5jPuE/ZMB12qj3lN0OxgBDSXBl7RkgKadExVf8BUYKBZ7llC5TEOrUli+8sZVwJVKAXWMks8oq9SzRrVi/BE1pBUlfsDEXEMik1GYxT4UX6veu0FlkfQRM5V1ApFcfVojQhCPN3HiFiNVO9K3cBEluJ55Fvqe85jWE9uwM6sSwbnOM3+nxJuAB5wXLIYkGMQKLbVsP9WiZnMGzPlaLhX7VM+j/F1YUed+ydl2bwzBvj7mqPORRmOA1avWoBoNhSIvznlhMnjpJQyvupKLJdQunLzhYqS9tI4870bGsBHIbU6ycIThBYOkg8KWR55mwfIRmvkpJvIp5s9Nmduo0bCOAo8WJd7nlD6iPGNC/RmvBoA1hqIsmDsyl2XLlvPHX/4yP3b3j2BECKUn0g4onW6bdunxZcHQwAil38XeA8fpmgSbDPMb/+U32bH9ae755CdRbylmzF/j9YVsOepBwLmEEOoUpce5GtYlsa5o6NDzDohIrMkaFNGIGA2mVpHQV6taY6qMjd4M5wmh7KM6rTHIDKtYVCsWtqi0tFJgisS0WxEG/WQ1aQoafJ+wo0fIoCZMX48eWKhqEyHVjMQ3pr8jgpHKitZ4vfE07+tlEKwx/dNVYspL7xIXLdFXliCe6J+wWB+J7EsCUx6eOjLGliNK8Qq5qmcjs8rLyXQd2e+lmNMs354i/0GXzdev5Td+7tdZtGTJ9Mt9rgsE3wGz5A2xsHi9yAWKkUbk4OtB4g/Vk2UZqtCZGuf4Iw8xLxX279xJd6LAHD9Ee0w5deIgjRCYOHyI7U8La1Zcwgk9TvNYgrOgQfouSecceRHRoabidA1alW/zihHDwQMH+MsvfYmrNl7F448+yr6Du2k3A/feey+doktRzf5PPfU42eQprAUrGSJgjWV8bIKh4aGIEPUeZqzcRT3WKIiJcT8jWOdifmgZsFpiq9qJWqFUkQjQQWd4DESnDUDRGfEqJQnRXRzPI4JC/EzQR0wNiSqsjNCSHs5EogO2i6OX+6iSTFuDPaM0dmf6S6ZnacbTQjCo6dXBPH3mi+jWVHuvbaXkfbyXSNokVczv4iRxNmKqFYcXG4vRV5zD3iU0aRCoo9T65/cf3Qx5tX397d7i5pU5Is6q/XM53j/pu2zrrNo/j7bOpf2OXYKahcD87952Md1Zc8tFOX+5gDkZr5eJS2eQDYD6Fid2PcdxUyJ49OBOxJUUXplqT6EG0iLn2N7djIUS5w0phqLbYs7AXN71Q+/hvq9/jS45d9x+O9dedQ1bn/0SiFDkJaZmKt0SATkvbN3Kzueex2n4/9l77zhNjvrO//2tqu5+wszszO7O5rzSKq8y0grlhIQEEiYIHLDBBttgc/YRzva9MDjIRj7ufGDf74fvbEyOJ4sgISFACAkkolDOq815d3bSEzpU1f1R/cw8M9pdSWjFCtivXqPtp7u6urq6u77588WTUdDL448/ToTD61CDctfOHfSmBd4orAMXeeYvmM/6Dev5zne+hi0K9DSzS4GeYFYdrFzf0erKqM3uslwh0b+0FIQ6c0Q+K1H2Opyri4PhCRmZ+6veUrJPKUHgpQzg6DDWEjHJSeeV6nJads4WIbK6hJzr2u87DFqwqqBlDpxGVSkiJuyEHe2Ysry7F+yL5VX8BSDtQLzCSigADwWhUDsUKkFbMD6b9qYc+Gs/YFu/7+PPpf9nutah6H9/5/ws/R+oL+OL57/SSvLMbQ7Tc6KD5iN9sVJiC4zzWK/B6/AbV7IcRYEhcjmR8xjrMTgMiu07tnHtB/6OSuoojCan4I477+T7330M5Z5ACoiiiIKA+ypqgpcE6uIhAqU/0aNRBJg5DVKafcWxefNmrr9+A2NjO+mr1UlbBWImH4+UgPITGOXd/AewYsjU1A+k+yPsoAhJJ5/P+8mTS99jgcHK/l8JL6EYeOizY6L1pYkpMNeqzQ74PJyEurH7k80FT6glvf8lxYmdenjSxdq148X7Tr6YKLYSYAlF4VWAbVQUKDTOaZxywP4ZqScYFZzs//h07bSMPni6xsrkN3Sg85+p/4N+vOu7frb38kLNlZOcn0fU82F6bnTQfKQvVmZqXFgoxBkEIdceYwPUWktrtDMYn6F9KIqNz3FWk9Qj8kZOZIUCj45VyDmkIBIwOmiFznuMUvhQB2WCt0xnEw5KRKCOgTJ8Hp0KKVmW4YqcSpKQ5zkmqmJ99/kKhZSg82UlE+jathMB/xPVUjrHSu3NY/AdRrkPRiRSoGUfOYMleRTGKTpMtPS8QtdYPBH7kq19qTNOhU3cFylkvzVNCQxfHTiKVLsX57v4YqTI+oCOZASrLKbM+VU+BJcFJ3q8r9dlyrbyBz7evU8foB10CYv7Of+Z+n9Bju/n/p7xXvax/XzmSrzhsNvixUe/dD7S6eREBeh0CX4zLwqvJ6VDwZLpUAcTCQyrMEKcOpRSFFFpwnRCLIJ3IyA1ig7X9B1odoMiBx9wVkN9TYN0MFnRmE5WP5AZS6dSZmQNosvx+ZiO59KX5bJCvc8OYtIkiw4W0smvUpXPYOrHGQSd0N/EWfshP5HIvy+aZJzd1C0vh/nef++dEe3/Gn5CWNg/qWcMfjm80DxbynV4v01Z5UUwdKAPwzwqnuFx/HKQJ6RR6QinZKI8oEwIyI5KoQ75m6Us2LR5iEdxmKbTQfKRvni/tMAfO8zH08mSgFCLEXwwV07YU0KgTkermTBDlpqkSI73eoKVdbOFbiYTzutob+Fot1nWqm4GKF3tVOdydLOe/c/x0z/tbhOnn9LkmZ7TM5tEp/Yg+9j/zO/CfiAE9nuV6XQYmeXgkSuFq0m3QQm8P9HC86sy3WI0WjmKIiVSHcuSK606Qm4OJAL+fMiqAhX/PMBAfhmo43aaMLm9YFc6SD5S9aI17R6mw3SYDtMzkVehQIDKxlnSoxmILMalpeCtcaLIjDvkjHSB38PQw3fjts8skY2evu5OqQCEfzHrOS8sFS3EZSEo01QZWHw01VkLeCEiln/p8kgP02E6TIfpuVPI9a5Jzhkr5nDiYEw1H0c8FBKTq4TevH3Izdxxsoeh69/HiFYopYISM40vSFfMSgdU5VePhNQnWGUoHDRNL8vOupzjL/9NiHsP+tUOQj3SQC/WeqSH6TAdpsP0TOTwOPFELmO2anDsjJiFSQU8ZKpKqir05mqimtPUWNv90b5cMs923/Tj4VrOZ+jI432BcyF/fTpmrmPq6H4V1RxfBpY6FBZhUzOlse0pXihJ6CAV9g6+xsN0mA7TYfpFpVD20BE5S81n1IoUwWNKsJM07q5X2mFN3Wzr6T0+Parg6aD9+9o3SZ0I/3Lbx+AjEBAt+GkJMuIng/Um+51kq93HJxNsZNq1XHl2d//l+V1jfXpfB+p/ejJP97VUebZDUPvpf19zdaBkIY/xjrpr4nDUCkNm87Ju8MGn5xlsVN6w/CrKPIfpMB2mXyaaDCXSOAxWchQ2IIBJMS3afDpD3Rftgzl6v4+YlwOF301nxp4pAYxTfnsQ1RX02NmWfRyfDMDcd98dZjqtf7r6n+hrMiVu+vUn++9cq7svN2Vfpyrv0/vv9NVhutMZseyzf4/CiaCdRZdVc1AHSK17HnQQgo3CQzoca3SYDtNh+kUloVNiUFFITKqrtJWgycmVkCtNpYim5IAeGrIgz7Maz68AeYRM1chJQCxONJYY5EXISF8MWqink9tVSjMSGHzhPHESY7MMrRx5IcRxlcK2kTLB3LsUpRIKsWjfMVuEYtCiQIlFvCX3CoXCuQytYpzPEQn4SB6FEoVzFqN1cO47V6LXlXCF1qGMwflQltmJQtkcpyKMgtw6vGi0eMTlKKVwvsx/JYRBxLmnMAqrHMZpvCtLoRkTcHhx5L4g8jFWQRZB0rbEeJrGo7xGCwEBThz4CIk8mZOw31m8inC0EefBKZSpUvgMwaJsgtYxhS+CT8bEqGIMLwZvBJ/leB2hfI74BNFFWfJJhQRWlaEkJvcWLYrCOTRFMN1IDF7jVBbQlzBlIewYTxaeq1eIeHxhcFKEaHGtAhSkTJWqlarg8xSHYEyGcprCJxgdyrvZMsVIS4y3gnMFoiwoh6hQss1lRUiFiEBZg7gErzTiM1yUoQpwro7oNuItVgweMK6zGAPSDrnK3oDyOG9wXoiNxReeHIWIwygpq/ZoRDTKaKwrUNZhjITiCdrjXQgi8c4hHrTWOC84Z1ETczE5D76U2rU3ZMqTWCEzETobxZoqWgqC9uUQV+C1QpwgOgruGlfgUYAFZcAbcCnKO7QRcp+hqGJ8WLis96UVrwT18IJ4jVKC9zniDA6LlwooBy4nVpDbPGgKAta6Mj998j4ov4IXklQ59FyHayknFErIVTAxTkbvHmJOKrDverqHqZs66YNWDIqEkMb1wj2752Uw7vaRHppgIwllvMrbEDzOFuGutJCFfHIUKUWeIWJKO7zBFYQFzIITjfcuSBVO4YkRXSXPM7RPw8cPKFXgrEfrUGjaG6EQofCgjcE6S6eAsHMWFarvTqAgWe/xtsAJVBRYAW8LvIAtsXVjcWiXAQ4nuoTk86GMtHhSFa6hETCKtvbk4hFxKFVggFRH7KwINnJE3pJJgdICJuALKeWxEpFqT6YjUhzOg/UapeGYo5YQKYu3Hi85opsYHNrFeBfA8x0J2rXQgNchJ9eJRsShVQVrC1B5WHzF4GjinMcpj7MB0Un5Nko3EfEIhoI2opshoMN7vNNY71A6zKm3BZoEbRTWh3nwJZ924kNtTQWN3KOVBIhFNUJMinMR+BxliwCabhzWeoSIxMQosXhaWGnjJCWSAuPapNIGAeMqWJcgXtOwoyhpoVUP1raIfIYToVABilHwWGVwxqJMgcbjSSnweKVBmmjfxusINFifImJRSuO8Jis8VgQjBm8L8Jo0byEqCmlxDhQGrEd5QVy5byIfujRzicOTg3MU2qG9x5oE7VuEwnotrBWsSBA2JQdRZE7hvAmVj3SEEygkop1HiGiM0iGEIwpCibYOsQohAgkoX4GZuhItzBKbFrHkRJLjiZi/cAlKKSKXByxfb/Heo7XuMjhOonO90KS8IF7RNoLxBT1FikiK1RnGFyTWhfkUf2j/EDz68N8z/IEO75WAw2DcvsBkDuL783xOnqhTech8pL40cxR07O1RFIVam07hrIAX4qjGzIEBsqxBnlmU9sSJwjvQOlSax8H4+BjgUFpotZpUKlWcdcRxTJJUg6boHNYWJHEF78oP3zraY2NoFIqAwauUIityMm8pvCfPU8CjdYDQazXzkoEEDUOpEM6epm2yLMO7qQ+9rQWMQKVGK8px2jGiMtqJpZmmtAuPchHEGj1zkLe9/1rqS+fRVBpR/eTtgqbXjFZrNE1Mo15jpGZoa4WtV8i9xVnPS9dcxBlnnI61BTpK+Zu/excvPfcEzr/4aLzsotY7jmMPooapVi1aLEZAY8Aq0AYrFmUq5L5FWngsBV4irIBCYXDMnTWPN73xN4hMhELI0zYrli/n0kvOI5KIdqMAnxJLhSLLgDaJrpPEDnEZkfLgcowXtNdoF6NtBWUr1GvVcmHOef3rX82FF55LkhjStInWjiwfoxI5tG6j9SjeD6N1kySCVStXcd3fXccb3/g6ojhBfAWtEvJiDFHjmMgzb84SzjvndJQdpmIc9aSCImICzEAcohQRM3BphM00RmL6euv89V/+GX/2nrcza2ZMbCpEOqESxeAcgiWJFD3ViCJvUuCRKEaimKTeQyPLscqgkgQVxXgc3qdo46lUDN5bAlcNjEeJohIpkJyKS3FRSo8U+DhF+xZaZ1QjQzWOSZtNjFIYhFgblHd4m2PTUcQ5cAVx5HB5gctTbGaxWQVnCwrXwrq0LAhf+qx8KcViuOzysznq2Pm89W2vodojiGryyle+kiVLVmKdYFQFVxZ9aLWav5phpofpF5oOWgjTofORluI4FnAURQFeUBKhVMLb3/52XvvqN/CKV7yCufNmUUn6SLMGRdHGe8H6NkobEKHeUwNxWJdz4okn8u53vRtjYtI0o9VqYZ0niRO0jmi3W4gonIdqFDGjVscQDM1ZXkaHmQgVJxBFJEmFoijKotqe3r5qqNnpA/M/8sgjueCCC6jXe0iSBJkeXZYpJBNswyGFQTtDpBKUU8xI+lC6TkGMbWfovYb7vvYT9FCDJEtAZkJcRdIYq+pIkTBjcAFvetsfU/ERvl3Q7xKOWLCc0097KTfccD1aCyb2xIlneGQ3Jmmj4wb/6U+uYc2Zy1myuJe3/N419PUqWo0hIl0Q6YLcNknzcQqXYmJLUjFBMxVbakcF4lv4ImXO7CrkLbTPSaIc5TNm9ht80WKgt0ai23jbphJ5YtXGZQ1sOoTRTbQ0iHUONkVc0HyU12gX0U7HgYwogocffpD169fSag1Tr2mcT6nFVVpjKWILtMvRZFA4bFuz4fG9fPxfP8fQ8Dpc0SbWdYosxyRj6Moe8mKIPPP0VIVa0kAzTqsxEkzmpafEiw31U7OCWDQVI2Db5K1R/u7av+Tee76HURm23cS2x7FZg9hYtG9RpEPk+W6qcYpSKYUdx9ox8nyUKC7wvknaHqYoxvHSIooLsnyUVjqKdSndCFneCkULtFTQhcHlkI20iKIKkY+R3JC1xyjSMXqqOsylT1Gk2HyM2GTUqi00bRJlETtCJYLYWIwotKsRGSFJQFQRzLUTwSc6mLS9QiJLO2tQ7bXkRUruRvn27d/m0ksupV7vJcsc3gtaG+r1WlnKraze1GVx+qWmqArqAPXl9kES11ADS55+QEXo2SueHfCACGpgERJVnrntYdov6fe///3v/1lOHBoa4tOf/iRKCSIKrXVgYs+ToijC2mDmeTbc2asSwqvU7qz1KJ1gXUArec3VV/LNW77Jd+++g2ZznFe84jWYyNNujfPyy6+m2RolqfXzW7/+ei666FJGRvcye3Aeb/yt3+TYo49i0aIlbNu1C1vA5ZddxFVXvZb5CwbZunU37/iT/8TJp5zOqSes5qqXX8FP7/kxjWYDHcekRQFGo6KIK15+OVdcdiVr1pzNIw/dy2lnnEfW3IZKZnP5pefQTD2//ebf4/ijV3H8sUeTtlO2bt+JJRTpVjgK3Uv/6tUce+bpHHni6QwsXcbjW7dx9FlnMWPuIKsvuIThOjSbo5x55lUsWnkUGx76Lo3CMGPNOSw9bTknn7wG5i2gNTLK6pe/jNnHLWJ23E+qc8a2buela85laGwnjz1yL4oI5zVr1z/Btq2bGdoxTp4Jq46ew+6dOzj9zPMY3b2ejRu3snD5fF552fmcfOaJrH/yISqmysUXncpF551HX73G9i0bueD8ExHriIxw1ZXns379Rk44bjaPPPoYZ565hsHBPsaaO1myqJexoTZXXHEp4829WDvOa1/7ck4+6Rhc0WZsdBcXX34mZ605jZNOOoGhod2MjoygIPhRAV1RnHjMSi665GJWrZpDc3iMdZt3ceUV57Nty0aWrJzPmjNXMWuW4cKLTmLNWUdxxKr54At27xxicE4fMwfHefLRLaS6zuJ5s7jmdedx/KmLGRseZqzlOeeUpRx79NGcsHoVm5/aznge45RgfB4YqXYcsWwWV152LqeetJpGew87d+0ijjTLFg8wtH0346lioD/ikovXcN7ZpxNHnvGxPfzuW3+D409cwZJ5g5y95iQ2rH+M1auXctmlF7JiyWx2bl3L4gUzufDCNZx6+qmsPvEEHn74YZRWwbeMAhRKO45eNcBVr7iYI46dz9DOtSS9hmte/VKWrljOS16yig3rNnD86lWsWDyX8y8+n8GZ/WzZvpllSwa58uXnctbZR7HuyXWccsppzJxl2LllPeef8xK8NwyPWU5+yRGsXDKXTVu2IjrGldkWAV5PIz5ieHQHe/cOs27tOoaGCpxWjIzmrDriCLZvWUej1UbXqvzOG99IX2+djRvWTX7fpXr6QsvpHRhOrVqcOruHo/srmKTAKRcKNXgN4pHqAD2v/XuK9ffgs58N81bNWgFKIG9N7Ot53T/gG8O4vZufdQuG6PkAACAASURBVD96zhFUzvwN8se/M/Ve6rOoXfYu8sfuALf/IhQAmJjqeX+A27sZ3xh6Tvfxi0BODMp5mpklnbWChae/7AW5zvMS9SZB691E/c9DTUI3UITwb//277z6Na/hA9f9AzNnD7J+/QYuv+xy6vUa9VrCrp3bOPXU08mzjA//z3/g4Ycf4v4H7uXfPvYxHnzoYf6/f/oQa59ax5w5cwHhf/3zPxOZCueffxGXXvQyxsbHGejrpa9eYfGiBSRxhFKCLcuVnX/hhQzOncOHP/RhNm7cwoUXncecwYV4yagmvaw6aiWbN2/lM5/5DDd97SY+/I//g3vu+THWWZTWIbgEjzYV9IIVDLcy/uMr36FR6WegfwHzlxxP3lPlO3f8kHMvuJBmUfDNu+5kcNliimpCqoWB+fPQlQpf+tJXOf6Ek2g0W9x5x3fZuX0nt9x8M2uffILeeo1KLWZoeAfOKvAGm1d48rFdjA57dm9TGGazd0/G3MHl7No5SmO8hYkcOmrz+es/wVhzAycds4wjFi9gZm/OFz/xOX74vZtQWYvjjhpkZl1I4oIjj1yAjlLmzu3hj97xJrZve4p7fnIXJrIcf/xRXHTJ6dz89c/y1JOPESdNbvjyF/jJT7/PS887iijyLFo0m2996xYeeeQnHH/ccozOEUlR0kYkJc/bPPzQA3zqU59g4/onWbRgLricpUsX4n3BgnkDzJnXx/wFA4w3dnD8CcuoVhyLFs1Cq4I8H0PrFKXbeNdC65TPfeHjPPHkQ6w+cRntdBwv8JWvfhXrCo4/4dgJU2Rnya/WFGedu4Lv3nUjt3z9sxxxxFzqtQjvLOI1thBEtTjmmKVs3vIEX/rK5zn+hJUsXNzPUccuwsRt6knKknkJZ568nIvOOYGvfvETjO56iiOX9rB4bky94vjCFz7LjBk9zF8wN/ilJ78CBBga3sQXP/dRtg6tZfXRS1A9ljWnHM/37v4OzfFhFi2ayeIlg8wd7OOrX/0itZrC6Jzx8R18+aufZfuOx7ji5WezZ/dmTj/9GPpmKmYNJuwZ2onzGdu2reOpdY/jsdiiIIoSOoy8k9u3c3ub8ZEKmzY08K4XV8RkmaWdNUkqoSxeO825//772bxxAxqP8iHUzotgX0RFqFVcJV51NhLXwcRgYqTSN6FNikmQpI4kPWGfjsK/IqG9aKpn/QbRstNCAFdJ6f3foNizKbSBoE3qqKvPHiSpg0mQ6gzQEWISVM+s0CaqIJUZYTxKo/rmBCtUpXeapiuhj0pf6ANB9c6cGKckdSSuTVxfTIKqDYR+k95w36K6+uktxymT9945f2LSyn4rM8I9K1OOt69ruxd0HLarM0DHk/MH4Tw9tUbzi4kOEmj9ISyj5lXpEgq+oTiJaadtTFKnmaesW7eev/2bv+F3fu9NvOGa3+Kf/vkjnHveS1ix4gg2blxLUXhuvvlWXn3FRbznPe/mRz+9l5tuvQ0ALYJz4J1n7py5XHLJFZx4wlk0mnt55Dt3sXt4N3uHhhmIIwbmHQMqlFVbMH8hw+Nj7B0dR4tm+9adIIr1G9Zz5LLZWOUZ6B9g3FZLDcLTTlMqlcpEpVRjDE5p5s6dx+ienbRHc9qZIx/eQ03XiFVEv69Qt4aNDz2E29Dmax/6V+KmZzRu4WZHpEmMp01Pq4EeGsXkGdVGkxoenTtmF2CyDG1z2o0W1hZUaxFZZqklGm9jEBfKv7letPThfC9PPfU4T2x6gkvOWkb/rLmcddFLqF5omXfkEm5dv4m1T6yjf/Ycfv31v8V4ewNfv+knDA3txBhN74w6UaVCq91i78gYG7bsZP6iRWzavAsRw66dwxSFY+HCxewZXs+xq09g1ZHLmT0wE1s0yIqcvcNjjDUyGo2M/gFdCi0e3wkKEwOuY9DwWJtTq1UxGioVg6iIxPRRZA3Gxlt418fIsEXrOihDpVrH5k0iE1NJFBddeDbGHMW8lYM8ef9WjFbs3DVOu4gYb+U4FYKyJhcPg1KGpcsXMe81V1CMRzy89hFaaUZk6kBEUqmTD++lp7ePs88+lZGRXYyNjTPebDE21qDVbDOydw9ZNpdatcqs/n5ef83VuMLyve9uJ23lbNm0lTQtaLdyjI5DcFBXsFFSrXLJJedSkxqzj53HfbfeifUVNm8eZvfunK9+5U5MJKxafTz3P/hThvaO8eUv34yLNVdf/Wr6eoWVR8zgR3c9xuOPPcmxJy7luNVLWb9pI2musGIZbTSp5Bl4UFrTarUxEcFX6214CD7C+wQvEd5HmKSGVwpjVKhwpCyg2LRpE9rluKJAaT1ZrE9U6OtFRFKfRe8r/2uY8yghf/x7tG7//+l/19exezahqjNo/+R6zPyjyR67i2LzvdSveh/Nb/wT0ZFnoecdhXee/JFvAFC74HdJf3QD8QkXM/qxt2KWnERy8tU0vvQ++t/5dezQJlT/AuzudUjSg89btL79L2EwcY36q/8eiSuo3kEaN/wVAL2//iHQmuyBb9L+3r8BYJaeSu3yd0HawKUNGje8N9yPjqhd/ueYeUdAXCP74RdRc1YQLT8NnzWRSi9ufA+6fz6NW/4Rn45Re9l/hqyJa4/RvPHv6fuDz+L2bET1DND4xofJH/4mANGR51A57dUQ17DbHsWnTSpn/TrFhntJ77uFnl97L8W2J0h/8iXi4y5CdIwvMtp3f4bktKtpfPmvqZz7FsgatG7/yNOQnF4MdJCCjQ6lj1RN+bPWEicRWdZk7tyZvO997+e66/6OpctWctNNtyKq4M477+INb3gjm7asI8sc5593AWeccQZzFyyn3W7hvWPTpo3Uenq47rp/4IQTVvP440+wbt164iimt7eKtQ5BY63FOsvYyG4cYOKI//yn7+TSi1+G8oq77ryL0097CR/84HVcfvkl3HHHXezes4U/ettf8Na3/DZGV9FGaLdbnHLKKVz3geu4+JJLMMYwY0Yff/onf8qKFStom5xoRsQ5LzuX17zp1WzavpadI5tp53upakclyWmNDTFz5hyu+e1Xk5oGl1x1NQuWLSBO2iH6tc8wNraL3OSMDe+iaI7xW3/4Zo47dTUjUcFjm9Zz1JEnUK3G5LkF6eSseZCMKI7wEnHfA08w3rRYW0HrPmbOXEylMsAjD2+AqIfe2XNZfdpLGZi/gFwqtBzc8+Barn7db3LRJZcxNmqp1npQup9vfOsutO7j3HOvpNky7N6dc9ttP+bKK36TE088nSSaxezZS2m1PbgZKF3B2R6M6UXrPpTqwVPB+QhXRuxZGwKncJC2M5I4+H+2bt3K7//+W1ixYjkSKcToIOlKhBdIbYOTTjuS177uai4671W8/nVvJIkrzBwYZOn84xjZo2iMeCJTxUmVRhrTzkPSt5UCT9AIxRnaTbj5prvB9TF//hEUuWFwzgL+4A//iAsvvoi3/v4fcNSq1Tzy2Hqcr9BTn0e9Nod2O6KSDOJdD87NwDHA2vXD3PfQVmbMXMnA4BF4mUla1BDdh7OaPHOlFaGjBRKeGQWVHuGI45cwtHsrqgIRHlNNMCrGeY11FcbGHd73gO8BesDV0aaPnp5B1q/bSRz1IjKDRx7ezJqXns7W7XtptRMkjjn1JWs4++yzERWifLU2E4KtlyK8P2JBtYO/U+WkLcfcuXOZPWcOIyPjFNahdMTVV13NH/7B71OJTddddL7tFxmVi17rjn+ldedH0XNXgoAb20PzGx+m+e3/TbTyzKBpiQIRRGnstofI1/6Q9g8+R/74HZP9KRM0sI72ikxorHZ0J81b/yfFuh/j9m6heeMHiBYeh+qdE84tMvJHbqfY+AB6YAFqYDEAzW98mPbdn8YsOGriMslJVyCVHuzwVqIlq4OZGVD9i0hOfQVudCfiLckZ14Ao0vtupPGVv8EXKa1vf4TsibsxC48lOfmVSFLD7t1KtOQk1KzluOGtNG/5INmj38UsOn7imnb3evIn7sbueBI9uBKp9GK3P0HjxmtxYzvx7QaNm/6e7LFvkz1yO8X2xzELj8EOrUdq/ejZy0iOPo9i8wMvSiYKBwm0/tBF7UoIaAA6kbvOWaAgihTDw7v5q/f/Ndo1yYsYr2J0bJk3dwH333sfmzavJzK93H777Xzvtq9SiTyjjQY+qpKn47zrXe+ioqAlGnGaD37wA8S6H8cY3ld4wxt+ncwKVclw+RhaGzyGd/zJH6N0TF5YdDvir977frTKiJII24Ktt3+dn9z2A4bcbmq+Tq5zRjdbrr32WkzewOEpJKaZD/Ff/uw9SJGR2ArxyC7u/tr9PPX4Boy31PKM717/WSrje6moGO0Fu32Umz/yr+z5pGNO01Ipcu7Y/BRFW4iM4bbPfx6XjmJcjc9+8J9Qpk5MRlUUjz36BKeceDIXX3wh37r1blLbBmmHudVj7NkL199wLyKadrvg5lu+TeGr/PjRB6hhaeiykHoxiw9/5BMUhcF7j7MxY+tG+S/vvxbEkVhF5jzXfeBf8JHn1lu/S9aKqMz0fO6zNxH5fv7q/R9GkhyU5uabv0kcOShqeJ9zww3fJktzdu1cyz33rscTzImdRTfWwpyZvYznGXMH57Hu0bV45/jSDV/GiKJFFa0quFxQDr5z23WYyJFZh45q/OD7H6TXtHG5ollJ+Mf/8b+oaktbe0weM64Sbrzp2xR+Fl//1p24VoZEfdARLDHYTPPTezbwyE/X0xrJiHqE3Mf8tw/+d/p62pB6mn4u0OS//cM/U4kjrAth+3/8x3+BSRRRUeHW23+MdQk/fWwDWn2PIs9whaNqEuxDG1A64hOf+DTaxISwgslvsdVI+ei/fokidyS1Cs1GhvJ9/O11Hycdm0kU95EVDb5x693E1lH4KolKUFrxiY//X2LTxNpRbGow5gh66vPZsXs3O3c28H6QPB/j1q/fQdweJqrMoMjtxOIfVgYHFPiSkWJrIJZKfSZnrjmDBx54kMZ4AaJD4B6eNM2YzKT7+RXEmAqkt09Mon1SsfVh9Oxl4EK0ss+auLFdgAYJflXiSrktITe3yCBvgsv22adENUSZiRH59jhueBt2dAfYHLtnY9kwzLWefQTVC99K9uA3wzmlZcRuexjRmq4JRZI6fu9Wio33U2x6ADeyJeyPq4gHu/Mp8qd+hG+NY5adhN29ATe6Az8+hBvZjhvdhVRqqKQHt3crxcb7KDbdjxvZimuNYEe2Y4e3oQdKJq80yQkvJzpyDcVTP5wQQNzIdtzwVlTvvBAdvuMJomMvpXbx20gf/EaIAE8buB1PUr3kHYAnX/+TMp/ZTrmnFwMdlMLezrlDUthbcCSuSaEMuSTgISJFbA4YvK4wTkodISkyorkDnHbBJQzWe/niRz9JYSN8JaPaHiMXx6gHbWpoJyigQAhytMNjUcpQ+CZBQs7xqRCLIlU5EoXkfgCnFYUUGAPSHqXmFN7HuIZDtJDYhNxn9MgMjFXEPmGolqJbmkL1h5xQXdBSDXpTE8AKXEa2czfF6B76mw3aUS+6GGZBqhnVvYzGIxjdQzsVvB5jyVgOVCmiNoN5k73JPCKb47JRYuVAxqlIhC3SIBCpBFc0+NrX/oNzzz2HtrOgBOUSICEXEJ3hixmAECtHzoyAtZDHpHhMEZ4K3kHWR8htF7wWstYg3isUjtSF9JCcHpzzIVitrsjaFiV9OHJUTeG9wSGIHiCzhAVC1QNAgYkROnmTIcgobAva7mbOvKO57NRTWbd+HXffv47cg6eXtgfnK+SuEj5GVcKLddyLGYhEjNoYUeAzQMc0CRpupiACCqnhpUWWRaAilHUhKEwBtAJ4mdW08FCvkZdCp4k1rTxGRAER+F7QfbS7LJdK6vgcCu8RKigBZxO8FTQRJhJy5xGJKV3xuGLyViYZQkzuB0F70kxQIfOKZg6+kpJJeMfFQyYKUUJKEcziRGRFL5GagTee0196CjNnDfDZT95EWtQhGiIWcNRxlT7alOlZACG7GETIpWRRvkpeKpbGN9m1fQc//OGPaRcRRlc45fgTGR5u87F//xyZq9FJoVEelDwX1rZvcij8AXytThReoC/3OGVpRzkDNqdioRBNW0dEPpscRWchn1jQw796cDm1i96O6p9P8dSP8DajetqrsctPQw8uCy1bo8QnvRI3Pkqx6cfhdAGfjuNGdlC74s9QvYOB4Xb13XXxKf9KUsM3RyCqlA+/nC/P0xhO/uT3qZz1m6haP1R7IR0DD3bPBoptj6FmLgqMbvp63s2M8eRP3EVyxjVlP334R7459RF1C0NK40Z3IL1zul7O6dCBoEyEb4+Fs0wMRUq+4SfUT7yc9l2fQURR/7Vrad/1aYqt909/hIeUxP+MSApPPvkEV77iMkSCRhpFEWmaPu8BVatV0jTFWfuM9mLBY1xBoTS5VABP4i02b6KihELFNGybXjxxKrRiQxoLM1CYVkEaWYoI4tRQiMdJeM66RDJxEgpw7x8WLIzPSki90Qj4YOpzgPbhT4DUBDQaLw7lBOUFLxKAmRGsTulNDZnSaO8pVMaosczIgzY8YA17anWcHSPJLaOmRiKjRLmnUe3B6jGilsG7fmzSpNZoYUwvhW4S+zaj0RwMBZEW8nYLpVSZqxokRGNiiiLHe0+tVqPRGA9mup+ZymCRcp5cea+K4oCJ0SW2FFCm4/tu014noqcoO+6E9nT+H7QX68E6TxTFZIUFHaR7L6F3waE66RUyCbQ9WTDcd0Fn03UfXeSjyfFMwfyESf3G7+O4lP5DQI8eaALLey976u6ujIqdMqZ9DFIB5hnkWyeWfcGAd/41orqww8JFuxfZMFNT35Pp2t20oZMXBZVKhTzPA+qR85g4Cmu/c8HnPY1U6SOdDsTuy5SzCaBzQjm0zhsxefzAsA5BGNfMyXbx+pPmcNkRfSyImmgHuUrIVIz2OcokmCPXUKy/Bz24gmLzA0hSR81cjN3yIDPefj3tH1+PG91GsTEs9tHSk8E7vM3IH/8uqn8hZtHxFFsewu3djFT6mPGOG2h85Vrc7qfQC47Dt8fwrRGKzfdjlpwcNN/+hQDYoY1Eq87Gbn0U1TtIse1RopVnhvfcO+zWR1AzF1Ns/ClSnYHqn4/d8lCYkaiKWbwaqc/Ct0fI134fPf8Y3J4NSLUfPX8Vogx2xxOgNL6xF9ccxiw8Drv9MaRvLqINbu82zOITQj+tEfL1P8LMP4Zi2yOo3rlInGB3PBme3Yz5mMWr8VkL3x7Fp03QEXbrQ0hlBmbx8eRP3o0kPZhlpyDK4F1B/vidmKWn0nPV+xj96O+i+uZSe8VfMPapd+DHdhzgaU6+iYWqYArLrrGUkVUX85K3/fdncd5zp4NU2FsOLdau15OfiXiiKCG1UIiit1pD2g1UpEmMIrOWsXbGrCQBCvLcB4g8mVyunUyK9QdGlSolKQIqCoRPV3vojMiJwomj0DnaCZENC7YQhLKi5LRx4VE+B1WgCo8RTa2vih1pYxzkrSaFCuu3V0KiLUbHWAHrLZIVzIx7aeVCw8SouuBTATTiqiSFRkcWo0JwRJKEv7179+Kco9kcI0kqKKXZu3cv9XoN534WGasrj7FrnyrlNSsaJwd+7UK8TBkFKZ10Dl/6AD0mqI34kjm5ae9eXSvyNAdbkCiNaE1e2AlupEkxvr3/AUxwrgM08HZijJOjfjr7CHsUAVFrcvEXJAAoTLnm1O1CdRj/NAFepjUvhT7h6Yxw+tw8/YKqozyW90UILvPhmy4KS2wMuS2wRUElqUwL/AmRuVN67hpcZ1u6pqZaS2g2GgE8xXusONpZAHMwxiBaPU2TUi7aJ1M+0D6mbB+YlXpAu1L48wZLhCVGyhgB5UuBo2iTP/JtAIqNPw3ntkawW0YAcM1h8sfuwA1PprFkZdBNh9zwFrLhYFLFVKi/6q9AFHbbY7iRLdjd66e0LzbcA4DdtXZiX2cMbmRb+N3tbwXcaGA0vjGE7Upr8XmL/KkfTGlrtzwYjrXHcHs37XN+ik33hTZ7NkyOYVo/nTbT+3Aj28jKcU4n3x4hf+J75fYo+aO3TzmuZy2h2PIwbnQ7es5KWt/6yLNkoj9f+oUv7O27OLjgKWxOpMrQcZNwxmkncP89PyQi4oSVy/nRQ4/gqnWyvBn8+yrGW4I5N6wfFBJAeiBgcFIyyW7UmG5SE9pBad4pNdpCFLnSWFFERYF4oZoFE5L48GE3xaGdw5KQakfLOJQzWAyuPosocrT3DOEGNPHchcxZupRel9HavYdNazegfJVqliKqSuothbfU581ndMdmkkJhtSCuzkD/AK+/5kpu+frXWLd+A/WBWfzeW36PT37yk2zetIFKEqOUorCWarXyM7sgpFy6PJT32Xk7ghboUM/QdxmlyaSGOCnMTOicga8KE1fzXQ2bzuKNKzXqgty2A0Rih7zgfcLU5bfrMFPfq6eTRygQOqa3aSqiTDJ9Okxz2vIuKLzrm7gr7ye1KMrvypbWin1cfuqouy1/XZzFS4kd233paaS8m3psgvOVvyMh8+C1R7QwFk6abE7naU8j2f92O3VE1X5y61AiFN4hJsyX3U9XzzcFRk0At+yb7SrvqLomsctQ2FDHUgwaC11Wkmei8c/8CT5rPPuBFW0a178XXNZlyj1MHcruvZH03hsByJ/83iEezf7poPhIA9buoYmm8hOaT3jZtYTfFqHaO8Bb3/xm/nfeZvfeMV77qiu578HHaGpDoSzKe4QaxhVEhacqmra3+FjIS9PkxNJtA3auKI8roQHzvB2g/bxCGRVA45XCt3MiXcEqQx4ZMueIqeO8kChDSxxJZJC0TdtYoiwn1wM4ndKI2kihQdVYunoN7d272Tx8Dy3fIhGDDC5hcFaNx267lVT1kPo6VTcOGpo2JU40S44/kXE3Tr61SabB2iqnHHUE6598nG0bN+EKy67de/jKTTdzzrnn8oXPfRq8DTjFPL9UJvF+ggn5jlbmHYocsQ6logkTaxkd09G5Jrwlgfl2cFYDrKB4TwdoNpeoZE2T/3ULOFYC+HteakKiZEILBChC7CpTFtSORgbgfZmWNKmpTUDfAeAQyQl4sl3G5a5pC+Oe5GAinbq9ky1ET03pmMjFLjsT8jDGCS20nFeZFC4mtNBuza/LQpRM50x+Kl8Vayf67kq/nhxTx4SuJueme5xChxk/e8lLRE3i2lM+7/DqYbQJcz1FQA4FJKb0sQ/JoONm2tf7q8RNsZF0LGmTqoAntikzIkdNCrSAl1A8IrQ5UN3RSfLp2DO2edo52fhzPudXhXxxAMvRM1GoYBLet/28FweLDlIe6aEhT2eBBMQjLizkDsGJplk4dm/bzoqVK9h9/4NoXxADI17Q2qOdh0KoWqGeCyYviGsRe72dcGspL6A0s2bN5q1vfStXX30199zzI97y1jdhjOLd73k3V73i1/jaLTdx7Qc/QJal9MQx5B6rFb3zF3L2yy5l2bLljGYp//I3/0g8fzZXvupVHL1gLv/nix+jvX0Hv3HNO/n8TZ+if1Bz1XFr2LO9zarXXIEdG6I4/zw+86F/ZO/mvWzt301ie9m4ZQOtaCFrrn4Dxyyqs2zRHP7yv76b8y+4hKOuvIqLLl1DdUuDj/3HR9m4Nmf5kct44PZvBJ+tD2hU9913P+ed81IGBwfZvXMbCxcs5D1/9l7+/gPXsmXLlgkQ8edCJWT5BGtTHVGkKKjGGu2z8qCf0KBkkgOU1XM8SlQInnEOl7VRogIQvQiproSHYx2+LFsQ3oSgdVScKs30ZZ1DCQtpR3PKO6hZIohSKPyEdgSB8cbKhCYASqGV6uJADi0RuhzjJJxjt8Yp6JJLCApRDkrkpQ7TUdHkoivSwWie/OCN5FO0vekLgRaFnqapKVWyGBEUQtXEk3qXQBzFpfDSYWJltmbXvXczKRE1MS/lVKDLPsNxX2p7z56Umnofynu0Y2LB885Ncyt4PJMoQp376yYpubpSin0xWZyb0PrD62engMg4MVg1SGRbLKwZKmXcg0fhxeMkFAg4JCSKn1/ah5QM6EDXezZtXgTkPdZZYtEkleQ5r2XPhQ6ij/QQmXahq7RRWL7DsqrwYhjes4ehoSFmL5hHJAXaebyY8hyHIWZ+rcbcvjpR7hjRlkZz90QhdXGeotQkdu/ezbve9U42bnqKKIq44MLzWLduHeeecza5gly5MsIy4Ol6rdE9PTSd40Mf+jBX/+6bmXfESuaccgw/3byeJx59iFPPO5tv/J+P8ekbbuSYM1aT97b41Gc+jW8k3FOMk+/dxq4f3Mlg2qaHGcHHKjkRTZpYBpYu4savf5JZs2ZzzpVXc/OXbmKt9PHoD29k9rYmo8kIolegVEiQL7KUOKqSe8F7IbeeWq1KHEfsHd7LZz/3KcbHxxAhpPM8Zxtvt46ocN4i3tHbW+eEVStZrEep2PaEFqWka+HvfJxlqTUtHiWhskyAAAwLYT6hCVkUjkirgHNctkd6UAgqVEtDy6SGCx5UgVe2S5cMbQODCcWElStzQkttbUJ3LU2fxoeo4Y6GN90iIwgGmVjgReRpC7yo7nP8JPMoma+exkinUwjemtZnRyNF8ALZlKCvENnrZdJg7EszbkdomK7dh/nv0ngBR2NSAZ1Q5qd5Jn3nQGd78oRwLdXVdlJ778RbTJ8rNU1g8FO2pGsspTl92nLkS816sr94CkO3oklVjLYxtUioiAuCNpMG+n1RdOR5+HSEYuO9+zz+vElpqhf8Ee27P4lvHjwIPz13FVLtp1j/w6n75xxBdPSFtO/4lwOceyTRURdMtjEV4qPOxe58ErvrKdTs5YiJsNsfP2jj/VnIex+sUR7arTaFff4QtvujX3gfaSdESPnJjwgELyGv0BUF69Y9xemXXgKuCIsCqowlCRG5da+ZZapEzuEkxbgyrcJ3NCrF6OgYt9xyC0uWLOKaa17Ppz79cVauXMGWLZtBFA5XFj8xPa/cdAAAIABJREFULF26nOaeFo8PjxAbzdDQMGrPKG5omB5lEA9je/bgdu1h96519I6nNOcImfLoRGGkwFtB2ZyqslSLBtakOB9jdYZXENtxEsmRRoPmxg30J3XU4h7EC9ppBuIeakWLIhEaGPLWOEaESGma1iFRTKVaQSlFo9nCe0uRw8aNm3DOlekZz4M6a5tSaCfk7TZrn3yMnT6U81ISqt10NCBRgZEa5Ym1D5VItBBpRaKDNhpphRHB6AKtFJEIkWiKwhGJJ9YSTOt+JPQrEvoRQUmHkTqMCpqc0mEMWhTaBDjG8NsTYULQjYQ3QJcRaWGhD8EnSiyqTBuZGngU3p0yXCow3w5T6TreaQFMEVg6Qun0oKzpQo3y06AK/KSFRkQ9/ZPs1AvtogI7ec3SFNbtxNalZj3Vqzip0QZEqY4/uIuRTmx3QOy79k0xk4cROwn7JvqdGEKwaxg1FR7OT2nUbTbvFhsmz59wJ+ynlcKiGAtCiJey9qvBSbcI1tWDjsFmqPoArjv4ShlwZcaBqJCXNOXY5G8xCd5mU+Z7ehsQzJITkR9/capIVV7/GUmVLgw3OUaJqkhcCxB9MAkh6CxSm4FZdFwwPdA1/s564B1S6w9tOpeoz6bnNX9L9vDtNG68lvjIc1H1GTQPMSOlVPAmhM3nqhM8B3qePtIwwEPqI+2sUVgQjxODVobItphdyWjkGVu37GRevZ+81se48lT8GGLjsIRIi0fTcZ5s7kEhFOLIdGmOlJD+UhRN5s1exJvf/DssXLiIn977Y0aGR/nC56/nne98F698+Wv43t138cnPfIL+/hm85y/eyw+//wM2/fvHmZU2mN0apUZB7/goJh9m+N4fcfHLLiEB1m56igf3DPGqy07k/97weZYfvZyLX345X//aNxl58n5+7aorSY9cxsc+/RlOOvVMTj//fOo9wiITc/tt32eguZF6kTHDpuhdO4iUZfyJn/A7r7uG8a07uPm2mxnbtYvto+NU581jbP1GdKTwPmPB3LkUWZvde4ZIWzmDgwP8+Z//Oddffz233XZbaXF4bgKSLRd/8aCxYQ5F0/RCa9yxXRLK8uYTfkgIJkIp7eniPYib0EDLJz2x4KhS41ASUhu0UihFqYUKRltUqeEG5hjaGKMxOqZmHFXtiLQmjgxGNJHRRFqTRDE1ZZkhw2hsWRpPQrUTQp8KAdMEKdAiHYj4CQwejWC0JokDkzZaY7RHK4hUYMpKhEgCgk8on1uACxp28BE7WjrBi5poowhm0OAvdlgV6rtCcGsocWgU4stgLDxtrUB1Ard8ycR8R1fGuEo54vDMvHflwhMKQRT/j703j77kqO48PzciMvO931I7VaXShhaEBAIEyDL7ImywYbzQMza2xzRuuz0ee8543N1jHw/HPd1jz9geZmjb3bb7HLu7j8cLhmYzZkcgwGBWITbtC1pLUu3Lb3svMyPu/HEj871X9asqLSUQqO5R6Zcvl8jMiIy4+/cmR5MZoeR+t/NsLJIKrbgseBnz0Ck/uSAU2hAys1EFyZipSZOl8uokYE8x4avTJFIed/OVmRADwYo057Ql1AQowIqeM2HKxgJbkk60yo6lStbWAVoRxr4iOCuo7gXQFqdWmzVhVYz8pnNY+Ln/iJvfzMoHfh9/7rORI7spn/kqwlOfj1vcRnP3Vyl2XoLGhuV3v5nyih+nvORFyGCB9r4bWHnPv2b46l+jeuariPvvYfldb6Z6wc9SXnwVMtxIc+fnWX7H/zor0Oy6nI2/8nZWPvD7hPOfx+B5P0Kz+2ZW3vu/kw7eSzj3Ocy9+l9y9L/8HOGpV1Fd9QbaB29h7qVvgtiy/PbfQDZsY/51vwnOUd/0SdLRfbB2hPmf/D3cYJG1z/wlzd1fJGy/iM2//nG0HrH8rjejTc3CT70FN7+Z1Y//KXHv7TNzXpwDcYTzn0PY9YzebfKdpm60Y4qPe73s05hHGhiPH3vU2SPJI12PUkqWm6YwGq2xYcNGmqahyIW3H01Kh3Pmu4kx5oLdBkPnve13XZRujCQsJy6pGlJL01CEghQd1XCOUVtbyoqD5HKuKspcsvLPbdtSliV1XfcakialkRLxgvNCjA1BFGlrBjh8bIniia4AgZSUInhisgWjbRt27tjBL/z0T/H37/s77rzzTjZt2sib3vRzvO997+POO+9kOByyY8dO3vCGn+TDH/4wN954I06+HSWVvz3UKVsAQcd42hxsJjnKWnPOr4AkYlEbU84MdFBUeBEK7/HOU4SWwkHwnkIchfcEPIXzBOdw0uLTGsFB8C6DsFtEeXDZl5k6DVsIHirvKTwUXvBOCKHImrn5aA33iKxhC84lvFgQnBfBqRowhBM89t0mP2EoAngv2UduemRyk/6ZPg+iBY45KzGomXm7nglNIhQmEc5TgnW3jIkF/qmz/anTeMX1Jl5jaFNaagepx8Tq5XrrV8fAM5KQmL/fLALJgkt6AWyS8mK53T6bkLtzOgeEFVJvnAGGeI241DF3h1Kg6lHfUF72g8z/2JtZ+eBbaXd/k+HLfoF0eDdu89m4jWdRf/1DDF/+z1n9xB8Tzn8e6dCD+O0XIsNFRl96J4s/9RZW3ve79nRtzfBFP8Poi39L8bSX4YYLjL/xERb+29/hyB//JPHAt8AFNv3a+9EUGV/3buLeO5l7zb9g9Lm3UV35esZfeS/j695p2L9v+H8Yfe5v8TsugFAZwEI5T3n5D5DGK7S3/QODl/48K+/7HcI5lyOLO6i/9veEc6/AP+UCqitey/J//U3mfuhfsXLNv6e44EqkHBJ2XUo6shcdLVFe9gpWPvAWymf/EMtv+1UA/Obz2PA//jWjL7+HcNbTae75Gq4asHrNH52u6fso6bssj7RToZ8IFEJgPB5TFgVVVTEej/HeU9c1ddNQVdUjbrNtW4qi6BmniFCWJePx2HLtYksRSsoi0Obixpo0O7gdsW4pE8hoRKURdQYaIEHAOVsUGsOEVfGkumGQNZy2idn8CalJpCYZ0HdqzESaxgTAoyQnxGRBM2lcE8T6YyCOow/t4b3veTeHDh2kKApSSnzwgx/knnvuIYTAysoKKSXe//fv5447b7fnjukJM66PjZSUOl8+1LlEnIhpsQakkXozUPKOVQkGmt6aZhySlWPqNLcooU81dTnIzWtr5l4EdTZOThSfI0ZNW42mPQuk5PCZkXoBSWO8WF6zc8Kc2tgGb+d5geCE0nuC85QllKUQnDcNOHgGZUHhJDN2R9UYYw3OmwVJkzFp77Lf8SBOMrN3YsFHmrKWLwx9pPAWVOWdWNBXMMbtnRjjSSkrIRbQpSn2vm8B8AOiK82CkKzWqGRNU7IPVbWzAiloa4xaO4btWJZqxonUGYElWi3i1ufC6mJxCsZEc7BZHq/UZ3ebP116SEdFiFRpTJ8oI34Sfa4JkQgIzT3XMb7ufQyu+gnGX5ldPsff+BjxgRuIB+6lvuEjSLXYV2eJ999Ie8dn0fEKbtNO/FMusDJsfZUXpbnvGzS3ftpesJzUB5W5TQhKc/dX8Ru3gypuYSvt3dcTD1jOpq4epLnnq1Qv+Vl09Sijz/815TNeZfcvKiS2KFDf8QXa+76K33oOsrgDt/0iysteTlo72kWSEQ8/SHv7P+CGCxRPeyl+87mkI3tJywcZf/UDx5ieuymWqG+6luLCq6iueC3Nzdc+yrn63UmnB2v3OGfMd45iNKanKIPBgNFolFNXHAsLCzTNKerzrUMiwng8wjmfC3EHY8z1mOFwSCgC4/HIIkCdSdPVoGI0GtO2DYOipESomxFVYZrx0AdiYx+3ZHiyNB5ReEfbtoh4nIegQqwtYMcHTxMbfDDczhQb0zzbBkkJmsSwKkxr9h4lktoG74Soyu777zdz32hM27YcPnyYsqyIMTIYDLj//vsIwVCA2rbFe/+4m0S+PTRJ7dCkaLBSTkmVGBOtKqHwSMyBZdpSxtVsPhZLqYpjRCcplE0IRNct/oKkaJpe7q+GklU/bxqQWGBUZ7IlR4uqhpz6Yb5bMw9rNq8qoraY9gwlGVN3EhFJtK6llRaH+ZBJidQ2th6KCWIDL9m8HLLZG/MRO6shvElaghO896Z9Z225CMachyRKUTOLB08QtZr1TnA+4EiE1OC9I3goxJhsECi8w3soYqTUBu/BOXuHQhIha/zOe/OlCzinFPlv6JkcyCBk/23M/ZPMT52Rx6KOpgKVmEQjZ5eT05bOozyjsXbMXOy8hFgwYue/logjF26gwD/lYuo7v4iOjuJ3Po1Zp7P2JvU8wP2R4rJXWvT5/BY0toQdF7P03v+D+df9+jHf6vHzrX3gFvToHjb8zB+w8pF/BynS3P55qOYmwA+q1Ddey/Bl/4zmnq+TDtxN9ewfYvT5t+F3XgLS+UFnA9zKS15CWjlAOrq/3xt2PZ3qBW8knPNM0uGHiHvuQFePUN9wDWHXZaS1w8c9I0A68gDjr7yH+R/5TR75KvvdTY+JkU60lSfOYtuZYIsiEKMl5YsYHnDT1DyaoCjJml0HCt40Lc45hsM5UoqoQlFVGXPYIkfXVtdMoh8MiE1LI4qrHG2KZp5NjbmUUofOI+BgrR5TliWQiKrElPDeoW1rNUrFFtU2trggrNYjqkFJcJ52rabJhXx94Q2H1SlNLkvVxpaUEsPhgLaNBqFX17koe4OIMfHBoKJpmu8RJrpOII+aRi9kfFrRDJeYySni1HzuiiEQdbE4krUhra2oSefZTQb7J7nQfWDMILZ58bfI4R4zNu9LBmqbka6Mmfa+OxFW3IAkrteizFdqaT7GsOdwEoiaaDIqD6HzJVvs9OHsfJRkflTqlP3RCjS4WPX3lykfqqPFOcG1LS7FHAzm8FhfmZ/XfNM+m54LLxSSGFQFhVPzBzth4IQqmEnbixozJ1EIeGfBQDhHcI7CKU4SgWTnOrMSlDQE76iCt2A0D4WDMgeiudLG1uVxkjwPXRaGQsd46c7TzFaziVuE1leQlCIU9m45EMssD7nPNTK48r9D2zHjL78Lv/MSdPkQafkA6dC96GiJ9i7Dz40H70FXD+E2n404R3HuM1m95j9Qf/W9iPfMvfznSQfuJR3aTXv/N0hH96KpZXzDRw07Nz9fc+fnzWT8kqNos8bounczeOnPovUao3/8y/6zjXtuYvTldxEfuo20tI/VD7+V4pIXoeNl4p47SId398w9HtqNxkRz4B6qF/40bnEb9Y0fJy3tpb75kxRnX4auHWX8lXdTf/XvGbz4v2f48p8n7r+Ldvc3aO/+Sn/fNF6lvvlaaMeMv/5+/I4LaR+46bFO28dME49D5zJ4HO/1veYj/U7QdHrZdF56h8yjosQu3UI7iXnyF8hg5yejid6f4ytsqZQJPNwEYWnamzRxurt0yps8KUj6SpezkaaT8bIiA8ox49mfadCOafpgNlE6bLxdgqATBng8ddGurHOOaVljP4ku77SdaXStIpaEWNHV4u20YWSS8tK6zmqU8rtMmDXAaijt+JSZszd3KqiFWNHl5LreJGvtWAm5wr5nNf+iiKFYiSoikbH3NNkMLJoogsuQe1nzFpfzeXMAmUa8JPMvZwZbNdkM7hxBEqLRoqu9IA6KzmSeo78HZUEIofcvzwdh4LPJ2wdCMP+2F+lRr4IHNx5x1uKAHYsVQxcRqc2y4xQfc/5sh/6f2ixd5Y+j7//OIW/tzr/+t0kH72PtM/9lKgpWrJ2YQTe6dkwaYyZHs2tv+hxfZIHwmDqtveklP0tXLaX7jPqNqa/ZdRVidHIfyZBYXfvi7LzYHPOOTI4/4fJKlZqCCsfhtcjBi17J83/pLY/LnU5bHunjyu6/C2iWaR2/TRf20M0FyWbCfFI6hdAwYZZTy69INkXZRz2BHp+1EUxPmzNkzHGCcnNsT2ELQmf+y/mRXd92Kf0+JZykY6/s28dKBJz0OTS3vS4okIDTsflu+3MnGiMY4Hzt28zQumfpFlZr2yc/9b1MhDv7EJUijae+DcVbnGxmmNBKyMx0ipGK9tjJ4IgZ/QdJRAHJfkbTfIWWCoNCsUjgpk19FLLxhgStTnKKs5/W/MqmYq65BbP+JNPyqzJk4AYDVqhop0zx5uJBa7pIY9c2uNTinMe7zvcKIXiKEAge5nzNprTGKy7ZyaZqGwtVixBpnQUq+U46SVOGy64fZj6j2W9r9SNvNYY07VtUnU1fmWZKJ6q8Mn1OPIHx9Fi9aD1/5rEPfCwzzu6N2X0GgHLC+zzhmGhWNHJGSdM0x1e0OY30GJGNJkv0d4ny+LhQXuLygpe1zQ5iDvtdxKmlW2b/giW9n4xSVgpErYamYJGZUQzGzangT2Jc0GPu9+QmT+rq2MrsGgjGlJIfQcc+RfL2RM8vo+srq6hM9vdjqy1JYv5tgqZ2N8zktAN96ID3p88DSR270Qy9mM2g0jF10Owv7fZ0GmzH+FvneutHJwZMB+GoFP1HKznSvLufSC660ONT9WUCrAXJUIqSJs/TC4x9Fi1OlWE7KUE20YUy6pPQp9wo5MAjuz7liZUwqDjn7T51xyC8B+8ZaUkHIYkqzhWTHldFy07gzMex1C5RRetEcoJqYEesuVIt7ShohKREcTmn99EtxHoCn+IZepxJLXLd43rEtMeLHiMjnZJlH79n/K6gqYIx/Q6zwsjx4VhKLtt1zM6Zy2e1fJ8XwS7YRaeWZbv38Sg3x7Yej2MZT05KSMezTkCCnzKDd+D4+ZBZvPDoDNTd9IgoIglPM4Woc3wq0TS0npnlp9ldZnITg/7kPl0+rZI1w+mPb8JEFSvAwNTd7UkmbbaEGR/SLDJQD+/AFIs0bT0fF5luPW/3/WXXehqQtn+vvj8EcngPQppgQfQRQ5P+LdUEGwOdmPTHpE0/1ff0pspOPon5Ll2WgSKTPGlxtC5QUxJ1lTYpXiNFMo00Jotajt1zPUJ6NPnYp2zPdYUO1vuQzVyumrKA/+SUoANKRQNtRJ0FqKENyMktRY/uXo+BOpOuqc9P3kV6vXqlE+3z4fWLSpx87pqT2zOJQsj1sJJTYk7C17xgCEpSR8sZH+jDIjm5ZmE9PelLmeVTUxvHCD8zJwjpFKbdPjL0JGec+PmMwccZaD44dlH167YxOafQ0xFfeYyPd935cPy72tTomH6OqJ2VTXo6VV9OX7Ce8CKsZ/WZMPYgjkCkIhFyek5S05hVHUktCv6RkHQvJJMKqY91mRQB5wNN06IowTvadtqfSs4xJqevuRlM4ScTNaoMGeNEaVw1Mcv7JxgjnUCOue+RfMPvHPWG4KkApUnwC0yCTugBILSXN0+qXp2hM3SGTkUpGugBBXvjgFtWBuz1AInGeRovbKpHfUH4h0umZGS27h77HNVO3VehrErqZnzczBexKjpN+/hhyz7RSQVGfkDUQOFgX1Owc+NZ8DgpG48t2IjOAiNPah/p6aEJE52YvibaRhIrDN35X6dLjwnHmB/P0Bk6Q4+IBNPk1mLg6w+usm+pZii1mXadEsUCsR6JStm5zg3QoUu2eWy0c8dZXP2qHyQUBa4sCbGrtZRJjWGHokTahhjT5EGeVCQMU2npTNKwMNjE2c99JfjBqS99FHR6ABn6QIkz9KipZ6Kur7QB5CLXgMTsCpvon6JdAW2Xw0CebJPlDJ2h00OaDBCjdhW3H6y563ANGhEaRFpUIit+k/lW8/zsBNiZmu5T+/olMWlOWJ49l+lzT9FWZ62+asdF/NMf/p/ZsWPHSV6mu3iqoScjWeQaWboAeYwhQSeh01LYO6XvHGj99wpJrh7SgXBHFPEFMVdi6SIM7dwMGaiZ0fpA29YEpzjnMiBFSdM0ub6lI6VI0zRU1cBSAzpPYIaCi/HM+J2hJy+5nKMZXaBxFWviskUoIrT2L81lnOLJdceGgqFTft5phqbHHM+/++0ujmn6+nXbHyJScNKl+7iLnqT0bfR4nR4WfUYjPa3UpQ8U5QCP4ryjXqtnjyO0qvjhgLEaTKY2a6SUGAyGlGXJcDhkZWWZpmkMAi4EVK1o8nA4YGFhgRgjhw8f7oH+z9AZejLSJHXHUpFSz4wcSgD1VKwxxff669bb5gTHO2iLR3LN7PU5evkMPaHoMZp2s7bEGR/paSWxxIgjS0f50R/7UUJR8uH3v5PpaZWA6D3jGDn74ouIK0usPLSb8bjm5S9/JRdf/DS++c1v8IUvfI7XvOY1NE3Ltddey9VXX83XvvY1vHe86lWv4ZJLLuLP//zPePDBh0gpngkaO0NPUpL8XyRoiySz3U6SaITWHeOPfHR3eUwttC6dYaNPQHqMjLTb+k5GjU5/ml3wzcTkvDA/YOv27RBbHth9P4SKxbkBC/PzjNvIwf37KIdzzA+HzA2HLC8vcejQIWBS0BdRfFTKXPA7OcvPS/m1W2fnDVpYcAWF81Ywux4z0pbCBxZDhVM4NFqmKkuaGBkRmScQvVDHRPSKSkLUykLteOqFfPa66zlyYB8lHjecI3hhcbiBOipxaZliwwbOuexSlnbfT3P0ECqehcVF3v/+93LXXXdTlgNe/oqr2bPnQb76teu56qrnc9PNN7Bv70He8fa388u/8kuMx2M0KWU1YPPmzRw6sJ+mqTNT1YymlHK2X5jq7+NtUKec5qcKitLZrNv1zpWTpHQoTCIrZXb/7NkT+9fk65mW/VPfRHfuVOA09DmWrOOP6gLBprMrjyedhnxb521Up2qc9XaIyXZOgjrujWbamPmts/frn3X6ykkA2/STrT8OnOTo6aUTAS129FhzJe0LtyLmnsZwdpPZWVMHn5+GNhdyByUD9SWkyFAMaF8f575YaBO6fIimclPKy+lZe49F/fveJ5vnnaBklYdszBXBFxWuWqAvan4SOi0+0u9cYW/BdfldEnOel0PxaCpxfsjllz2NJZT/5mXfx3Wf/wy37B/zG7/4Rj77mU8xt+tirnn3X3HBs17A1S95IZ+85kM85/JX8PZ3vIMjK2tEKWnxtDrikmoTVyzsZKMULJfw1X338tB4CYLniI+o85zfVLxqw4WMDi9BUvbGVW5vjnDJtrPYuH+VHRu3cEt5hLlQcs9D9/HABuEFw+3sTmvcksasVKt4xmwceeZ2Xszq+U/l7J0LhM9+ikN7ltj8rFfyjGfv4OvX38pZZ1/E6DOfYv4p57F4+bO5b98DuC0bWXtgmSOrNaEUBoOK2FbU0XHf3t1s3LqZKCuUA6WpFe+GCEpZOlwKbNpyFr/4i/+Mt/1/f87u++6xAKbUsrGCXRsCtMpqrIhtawD4MRFTa5CfKaGaWHY5sjGH/ftp7E+FFKbB+STvzkFrrkPyKXJNSxtjyGASagFuXlpbOC1kPLeRU7BECKmdwJKKmcDbnrkKLlkNWfLiiTjUBTLeDSox38MWaA9oa/g+rvNPi84IDSll5N6u9JYo6pos1NGnhLqcuoAI0XsspzW3mSLT0AaWOO5MU5rBwjWBzqJJM+BH7m9Sh5ObS1p3sHsZpL2rW9qxpphmJRtxrg8eFBFaTZPi2v2ouV5MkAzlh+TgQzUQexvymbCa4+Zut1+Zirg5AcVTBIqcChkMHOiJF0TNjFHF8rF7oSn3hQKrBcw1kYXG+nVUKL5oOc83vGjrBuYHDVHa2WChqb+cYPtE+1hne4O7i9vf+Ra+FUIeP4vmP1n7J7+X/epqLneFNzrB5GTPvx49nHd5pP1zqvZP1daJ7x9BGiIFKpKFpxbnA2MtmN96Fs95/a8y2LjtJG9sdBogArtH/s5opB2Ae/fD1lYhRnAusG/vHs5+xjPYuHGRSy+9lNs+dxP79j7Ahz70Qa589etZXFhk0+bN3HzLrXzxC1+gclB4b6D5hS1SZShYWjrKXQ+t4FcbVuc9K/MOPyio25ZtyeMixBhZlcR1y7vZVsyz3Q05q5jnpX47d/oH2NussClUjBxcEIc865wLGRxeYzxqUGpbfDEg6v3793HXeJlt570sl1UTNm3dzt333cftt97GhZc+h9J79j60h71793LbrbewMFolNZZ47FHacU0o5lldWePQoQM869lXgMLy8jKqDk3dZ9UgArt37+Z3fvf/QsbLVqYqeGJMbNiwicsuPY+NOmJzfQQocd5M+hOG141B/qQUY54p2eSMBtrRNEKKhoWasr82pUSKkTZGVl3iSGj7/ZoibWoy/KolyS+lzRnObrJ4p6SgLSRY0QEJR0yJiFr1FnsjlIg4Q6xJqhYoh0O1q78CqkJC87VKVMX5YAXZwawQ4jNsu5FzIbcRreoODq/DXpNSZ+wy9p3lkMYhkjFmRcxV0nWeCo0/jHYLs3RMOlchEYCSoF19Xc1l/KQHkIgCjZvozq5HJOoKdSuFOLOAdGyyGzc7Cx+FoJnVZyHBnlVzpSNPyP511YxO1GivLYlMWXamrp2m1kHdKd/T8zmvfKJQ6PjEiwCzKFHrkaibwhleh1RZ9/AU+HzUSKWJMjnECT4lfLPMeZsqXvjUIefML85YXE62kJ+KuRy73b+nj6zd/zmqsiSlhHP+4bvVTsAFbRwFnJBi/gYfbxfPepzvdLX5SC5IBVEKw1LWFicNKgWrqWDPjV9n71Wv57wNW06plT5m025WAr5DPlLlWOMVGENzvqRtx7zx536ZD3zyk7RRs6VGGY0bEMc1H/0om0PLOZetUg5LEOEz//g5AEIoqdWwUqWNzG/ayOaztjB0BUd8y6Eje6nXVm3hilk6LwMueEaFY7WENYEjhWN/s8bBZo1xVXDn6n7OW9zCC886n28cPMwFfjPX1w9CRY7GNeg51ZZBGVgMnv3eE1Kkqle4967b2TQo2TlfcOPhA+w8+0I2O2VeHGlcUzIkIDiF4IAYWZybZ++DD7HrOU9lx45dDAcLCEez/NOCRKBlcXEjz3jG07jntps5dOiAmXFDYPeBFVavu5GiWaXqxtx5iuCpqkEOZPI4H9h3AsMfAAAgAElEQVTlVg3f0vlJIWjnKLzHOU/hIsEnKu/wEgherFSWM7BxT8JnhtJpO06s/JbLQ7wU5vuxd9kop6oG0J0Sq+Q0BU0ZqDohdADnLUkKM9dpzNclk8y7bRVSqoiqNBgzHqeWFitX1qrSREdMYliwqjRtk0HVlagRkiPm5zJen3rGr2oCwUi8MXNNfZnIpIJmuLxGJFtXMoMXAfX2XkDUliRN/u5TNkkZ40zJJvcgBdMe1QQE0/ohZQHIWXy4WZR02mhsf9RbgetZZJ7MaEVoEEaqWXHOC4Gpqv1CmdT1QIBdibhZmmVyxxbVMZZ+8qWqlZMjNJnYd5LFUEyMOjY9BZF+n08Antp5ah+ILlJKiUtKFRK7Nni8xl5wsefWWeaoXX74NC+Z6Iaz2qXm6zvxKgtbc6X9Vodq7HNUZ1k06+w7gU7aARpLBo/oxvJR6cyPVmd8JO2f7F6PQOdVh6jSipLE1h0PRG1YxbO89yAROSUThdOUR/qd1EiPY6R5Qia1Ekdf/NIXmR8M+NrXv8n+PQ+wcvQoX/rK9SABL47RuGH3/fexzynicukgccRcTcULkJQDR4+wcugoAO3As+bULEUxMS6EsYe5tZo9h/fjm4ZxgocWhLvGR/hS4RhuqVh2iaMCe9pV7oiO+5sjLAbHIdcAHq+CqEGCq45g5RCH77uXbZs3M9q7xMpD91Dv3cO2hW3cef0Xcc2IlYMPcvjuO7n0nHO5bd8+XIq4zrwngsbEl7/4BQ7s3ccHP/Ah5gY/zNGjyzMLoi3CEUj8xE/8JNd++P184hPX0CqIr1iJQlwd4VJFDHPZjO+gVljJGo80QMSzavUesQC04ALeuQxb5qhCg/cxF3WGwqmVy/JC6T1zCgtRKIKjCELpHGXhGATHoAiUhWcja1YH0xnCqtWuBF8qQQSXjub72fgFpwSX7JiDOnjGocAREI04zZVcYuxR0iVXNLFiXxBxZs5VY4maza6mNSdEzExuWplmhlca00xmHtVsJk2ZwbfRkzRl5mtmupQwBpxglDxJhZhMCIyd9p7yNxKlDy81C62Zm6MqEeO+SX3W5HO6VK6ymZKQVFkN9Mx8oikaGL1qYuwcNeT7pixrmAASYyIiNKkgacznmLCqCilGkiai89aPMdpxN6V2iuKSR5LPPiqZQfWyxd1R94n06y+ULeGkykjCnXRBNAFE1l/GpGsjUovQ+ILalUSfcLGlccLIlYxcTaFj9JjnM+bJ1Hb3jTEFutIx10mloW57lhF7xBXG/Fxuf2LHeNhsbmZftlqoWhpQp9s/qrZOso8TbJ+O9h/dvRLCiCiRJB5o0dQiPhDbEVQPHz7zNPlI03cQz3Fq+mQfiDhAE4mGj3zsYyTxhDTGa2LsB3zuwXtyySUQF7jlxhs6bxmS/WRgRYJJLQ5HDLDms7lMWpJYtRWXfU5BYdXVfGn0IGkOhJrU1pQKt6/tt7qNznxkd/ua+9NRVOBb7Qq5G3EJEE/0gkjLXBpzw+c/z0LTMkiOu276Go4xK8sPcsee+6nUMVo6xFeu/ThlVEqEMgS8ExYW59mwcYEjh5W/e+97UL+Gyjx/+qd/QlFUhGIjWzZvwntHjC1NPWbrrk2kFLnxphsoy4KULOwCX9EkwUtri61kgWVKdeiS1I+U80AukZWHRxRzBUbQesH8EWp1J51GPFa/0mVGkEQmtS2JeE1WaDprl6GNlIWnKgLD0rNhrmJYlQyrkkFVsKNUCmeLQiGKl4hXzYWkhWE6ylBNS/VOCaJsnB9SBUdVOFzhaedMS63EUThBW0OLdQJBvS2A0vR4sV5M29IUSW2LSknyc33fiJXumSyoongNphkmW1BTAicuu1A90dUWCpGB1e2YQ3Pedhg7ijqX+u4ka4VWY282rxsbo4QjqpmWm5iZYEqs+i5ArGOSnRbd/fMwg5OrM+WokngarSaD3WnHZsvG2E9hjFS7AuomDNh7tIzUsUw0QSImxuMxdVNPhJAEB1vN5n4z1betnR+juQEilQkKKfWmMpOB7Z6Nd1bJJpkQ40Tw3uf2rcJLQ9ULQscCzZv/ULNW2+C1JbaRQbPCnAytdJtTE8A6v/eMUKCoTO8DmBzvtdQTaKwTRhpQLfsiQCqTrj8OCOKYfcrkmun2Jy95DPM5QfsnuufJ2l9XN5xqq9PJZq6fvheT9k92r/Xan1x87PGIuIYmY8YnsHHUROsdY01ZsD41ncbC3gXj8cn9GA+HHmlhb68TCar7ALvOS+TKiOoQLPo0imSQeSWJs6obM7akaXnMGnJJSE77NrvRcEwmSRlhFGCltIFqPczXsHUVxgFqLwwbC1jwCfYbv6GMUCSYq20iaq71qCitM8OlU4dPnuTG+OTsPXyNpIrWQfQtJQWpqQlsBGkoq1VicmhcoGnGaFjF+0XG9QGG1RypWUSjw5eHGddH2Tx/LvtXxngfWSxgbWUFKecYuxJFLCVAE9GdXPYaRPsGOtAI2570aMsAq2+p2XSbC0ATbYkSx9iHbIQz/UlUc4k404SPVnO2naxQtBNjipLMgIhqX+sydPtT29cHCbQUzgpMl8EY5cKwYFAGY8iFY14SlXgGhWfoPW7cMnQwV5RU3uMkmsbrHMFBVQSKMClE7X2k8CMzSzsLwAneNGKfrUWxCKQUicn61osF+nTAGxqHCGYi9/mzkyy0ako0rib6BicOsp8ymoPWrCk4hk2nDeXFQqELYEIcw8gkUKk7rRs5VRA/q8kpmZHad28j5GftQsfM25TRupKq8di+0osJBGOF1dy4Qv9+fTEMVTSOeqZ4rGaBKk2am7TZa2kTgWAsjlYw7TwfdyL2LklpxDOS0oSJbOae9gWnlGhbzGcviRZPHROsLXNWWOOKczZy7uZN2d88013HKbkn0qhOdrwfHmlR4gR+cEqePRUjPW7f1DWZrx+//XAZNZMHXfeZpu+1HqN8JG09XEHhJO3btiBaEAkYrlXEa4s6z2oquXffEbb96l9zweXP5VR02gp7P7HSD7uVO6Hq8qJspjnJkiHdVOs0CbsgH6NnkN055F8OxXVpMCIkUVqHBY0A843dfZwj31ZK+oVsHCRXboFBk0tnSWbdeWCVDlc3UqYWpSCKEMXhiTh1OWayJcoAlYRPZtQL3hMbRVyiblvMvxZN6hVI2uAcJFpSjOYzS0IRBhw9ukyo5hAHy8tHmK8KaiKiKS+keclMlks3MVdN+lxUiIS8FktfFaeb9La/ARozJUknxEwk8FaUxncpBpqv645noaVdpdM4RDotx/pbBBoXLOldLdrXiYIr8nKvqCwYM08JqRWnCV1prX9lFXEmODmBwgmlwMA5ClFK7ylECAGCdxTOmY9XlNJJ1pQ9Q6nZpMvmRw6OKnjKwlN6R1Vk5hjXrI0gBOdw2hKcUmS/sY81glBkM3hwSpBEKZKDlBxjKjIAD2ARxtal1mdxZl3v+jrlhcq+gX5sgL5MmVi/1y71pdiYGoWpnxwbDXtcCohYcI7LgWHduNpjKkGFha5dyXcQTxcpLCilFh3X7K0i3XcGQpsCk9U05ffIAolCq1YGrWfMkDXiThsRGiEHjFk7HaOPCazA+hxKTaQmqpIocLqZQZpjyzBHDh8XsfTYWOm0j7SbJ5p9ud27CTOHmen+k+075vr12nrY7T+Se00xtXXbfzTvolO99rDfz2o7q8tru4JXR8qLsjtZcNox9D3gI43Mmp5gZsHA/F0pTziniSQuS/fZjDj9Mc90nh6zpTgVQjTTZevM1KuijL0y10AZldYJZYTWK42HQWuTeqnsag8oZy3bwC2XpqViT2rMyEWCRgqNqDqiK2nFW01SdYhERCPR0WuwAtTjmrm5zayMVnHSEFtjEtWgYmV8iLnBAHEwHq8xX22lrR0pKs57Ezh8yWhtlY3DAUEgRsXnmoZ2j04Dz4LItDEj928TJghMffkx7YpkkU1fswvvJGPTtPxhjNjyOZWrCf12QSLF7IdT822rkIN6BO+tJJ1adA8iFvyUV27Gan5IshzqnKOq5qjblqZpoAXvF/I9I+IgJfMBW+hRwqvgMEtHQCl8TqZJ5mcxY3RF4RJBFK8NPrWZGTuCOOaGnqosmK8Cc1XB5vmKqnDGeL0yH7LVI7VIaihoKSRSipnBSycMvFAVJVVRURSeMhT4HOBl2m3Eic+au30PIuY7dmLWEksdyj51xQJaOnNX9ofOzK5pk6emSU3UPI46pbF2YypRe802xWOqkoidY5+KrLuUtG5ovtWu1WOeKYWUBTYBEVKbE3TyY3h1+Kl1qisobq05hGSpWuroUpKMq6cc3Z7QNLR3kI5FlyQZEoG2HbPsWoKkDPNp87nLCz/W79lvTx/vhekptSwLBbmzzbSL1antfazaKQVTGmU3Ap3puL9+4q89lYr38Nqf2ndM+9P+4IkANVEL++N9+zp5f5ncf1IFa713Wa/9dd5Pp67p21fEN7RiZn+vStBIS2IV4eB4mS3Hf4rr0mmoR9pJbnqKsx8fSn0W8dTsy53p1OWPsMu16jreJoqKGX9PLATMsNh+aUiuw7m1fSFNihm3Tmingui6xAIFSyNQxav5S2NuM6hmD632z60azGQmHksJr0EdyZlhSqnMBKz5PQHnPKPRUcrCoTrEeYfGxGhtlUE5TztuUQ0Myjmadg2RgEggJaiGJaNmhUFV0KaaNrWoeJxYfqg9nZtZRI/rNzm+NqtMLWb9SQqTRE9mih6IZl8xHeOU/pKOIp6pQ5OJnZmH0hrz7hzhClHzgilCyBYEyd+GotT12I6VhUmibczPkBdFMd+5ZA1a1GV8ViVmc6uoRwiIU1opGLtBNltnn6io/U72ZmnZ8kYdNaJr2R9vTE4EKpcI3lEWniL7bwvvTGP1gSGROW0JLlG4MYUTKm9adPCmSS9IpAieQXCUQRhWgcIppTctuHUBJ5KjpzGmL9kf7KAz7Toh7xO8Mx2us/RExPxNuU+98yZ4ZQbbSiARst6nmcnnvlCrrNLKxBc8nVLVa2MxZutXjsvIdplu4nVzzr5PD0Gy1mpzuEgRl+LUBzedp9wJZRmDWnXi7unUGAHPKkkcrQx6s6+kMYXzhCpHU3froHR3yGtOTm3QqViSmePdvqltCQUaJ4KpnWt9budy3PxQEfyms0lHHyKlduoawW3Yia4eQtvRZPLMzOHJPr/tQtLhB9F27Zj2J2cfv0/W2e6EgNn213/+2Wu67Ufe/vH3Qk50TRevl8hhhIh4fLBYidmV58R0Wgp7fydpEmk39QEiMyPeS0iT4Zo6f1J0145N05Qk1LelM6YuIQs9agz02AqAMjXJiz6JUFkuZ8+ZmUAqQNHfR3JKCHhSL0GWWRPICwdW8Jcc8Uk2sQoR5wVi9jvKkNQCRFRsYREJNGmcI5RzhKObPOCJemc98unUn9Qxw0UXsNNRO6OwnvpDnjxVzIqKvflMs9OLp04n8E99wwrEHHzjjq/laGM9Ob8XHsV82cd2T5mOjxnoBC4j08PMtB/AVTPnrtgrsX49aTN/e7E4gKAJE70seCu4XNTZzxFcNNOwJIJESof5hr1jQxBK7xiUgUFwDIOjClB6i5wOJIITCi+UwXJGzQRtjLdwjgEF3pmp2wvMD8tswYgIQvQmgLnuWV1OW5KUUbOgoIsGbvNwua6XAemBPDrQld51kAW7MqWZT2WKn+U1QuhynDu9dlr4d+rxybzopiWlPF5TsBsyRimJVChCoMFLC9pAtPSa9RCWpFpkePUv4xa30dx9PeMvvf24c/yOS9GVg6TlvXbNYJHhS3+B8XXvIR66d2bcj19lpiiUzL/8n7P68T9El/dP3aBg7gU/xfir7yXuvePE12fa8GO/xcoHf5/44E2nPPe7lczC1s1JG71CxEz5SZH24VfUOm0+0jN0hs7Qt5caHHVe/D2JIDnyPEUkRaIUrLpt0GarQooGSyE9phOBGiGhcQwoLlnCj2ntwkZpmPcY4/RCEMlBVUIRLBBrMQSqMlCVJWWAYdmaJh08wStBlympKUOgDC6jK00Si+acY6HwFCFQBMstdllAdllSbZNpxabcaZY+kuVxA9JkK4N0olEXxGba74ghtRRm8cgaNWoBb2CaXDMTSKeYiTeDpOR95q+ts/EoM3k8SXwWdo/PXhi88I2EnZcw+uJ/JZzz7MmBYgjtCFSZe/WvUd/8CcbXvdPu1Iyo7/wyafXQiT8Al+E6UwRfQmoQBLdpJ+IsHUhCZVqtCG7jdqQYQDGAZnRcc1IM0WbNmt56HhIGU/eBLIHbuaFC2zE4DzhIzbrt9Ncbosrxzy8CcSrNJAysrRQn25qQYg5tVjnWpP9EodOAbJRNcmd46Rk6Q99WEmemeUPEEupkOani6RlK0Ryxc+n16F7IdsCK9zgJSBjiRGbSP1BlKSZ8Y8FJXZS1UwvgsnzRhjYtWzpJNvsS40RDdY6NhbDBG4CH98KwqkzDLTxFKCiTUsUW71pLLxIlOOm14iJ4tgUheE8ZfL/fI3iX/e/FwLRcZ6bpQgzdq2OoBMlZWwmNqce5MoHC8mHr0DLxYXYWrIkVCS0IKRK0wWAzPK0LKL73461HunrEmEu9ytq1f4xb3MHw1f8Ct7gV8QXNvV8jnPMM3MbtpKN7aW77NFIMGb7kjax8+K3MveK3GH3ur0hH9rDw+t9m9Lm/YfGNf0R7/w3IwlbSwftwC9toH7yV1ff/DgB+24XM/5P/EwklOl5l6W//F2R+K/M//m8Bob7pE6x9+s8gtYRzr2DuVf8TOE9aPsjqh99iD17NM/fa3yScdRl4z+izfwnimHvtvyId2YNb2Eo8eD9+0y5G172X9r6vMnf1L4M40tF9jL/5URbf8Pu099+EbNjGynt/m/aeLwFQXPhiBi97E25uC+1932B80zUs/Ni/QVcO0T50O8XFV6HLh6jv+gp+6zm4wSJp+SBx37coLnkJS3/xPzD3uv+NtHKAtY/9wWmbU4+WHqNpN/sX9QkrKJyhM/Q9S5IMREMgR59jfriObapS6XiKFXRR6Z3pW5iLo04UxsJz3IwfrnEFDSWdp991DCb7P0UEcYtox7ASeMm5nAaBzd7G5SiFrMWppTo5aRBngUBBfM7ptes9SsiAGl5gXtfwTjKQhwV3Wd6vpwqBxeHQfMFlYJAjpc0P7PEIpY6yKRbLMU4Jpy1lkBxZ7RmU3vy7GWrRVjfLJxcRVhiSpGZIAic0yRGlyK6C2t5tHY1i/PX3IwubmXv1r9I+eCvNzddSnHs54xuuoXz6S2G0QtxzJ/Utn6L51he60TUUqlyQWiRvO2daYIqsfuwPGbz4jeholdHn38bwFb/U3zMt76e+8eO4TbuornitMfLxCmvXvYu0cpjhi34GqRbQ0VGKi18E5RztPV+lfMbVuM27APDbLqC45CU0t34Gv/0iisuuprntM8QHb2H1Y3/E4pv+I83Nn6QJFdVzXosM5qAY0N77DcrLXkFz3zfRZo3Vj/47qhf+NOXTX9wz0njgLuqbP004+3KKS15Mfds/kFYOsvKef43ffjF+59NYec9voaoU5z0Xt/EsiktezOi6d1Fd+eOUz3wN4exnsvyuN5+m2ZTnSMqZHu7UaEbTdFrqkeqM5HaGztAZ+naQpUNlaECdBGelPpDLMXYl04wzTTNSEebblIEupGe0SSd+d+8SItlv2f9/qjKOulw4ovNp9t5pOod0dEJ007HZ+bycDpMwhiSao4qT+XrNh6WoJMZ+wY6jWJHtmAOzaoSasl7CIRYolaOTC0dGw3LMBaHySlkWVEVBFRyDwvW+4iGJDakmhIKqCAQRiC0h5Eho79FByxwt867B+UDyQyhKBnGFrUWD9+ujK+n4KGvX/gnNXdex4ef+lLjnTnS8Sjq8h9GX3kV779cIF1yJ1mvQHu9XF9f5eKd7T4kP3ExaOYwefIB0+AF0yvQaLvx+5n/gVxh948NmJnUe2hHpwD2kpf3225mvWco50uGHiAfuZ+1T/5l08H67b1FZMN2+e4j77yHtv9s04KUDxP13oWtLxAP3QjkPobR2Dj1I3H+vtbN6GI0tcc+t6NJ+8JMYgPJ5/4Ty6S8hPnRbfjeHLh0g7rsTt3EnurSfuO9Oymf9MIOXvonm5k9BO0aX9tB86ysMX/yzxKP7iA/dfOIJ8ohpKq5GU1984eHQ6fGRnsDJfobO0Bl6/Em60P7saukDTkmos8C7CZPrAquM2TZS0qWldI4anTrP6TiDCh53V8BynmsvU1cfT0WqKTsfmkr2Pbqc6pJBHVJjPtFO02UC4O8UJA6YPKVmhVuJyWLf6yr17ynk3GFVg31sLRJT8KjG7KuLPY6zhQklCuoMsOGyadkTnKfwjuA9mwtl0TUshgZXDNECymLE2WGJK3c5zlpcfzmde82v27vNbSbu/RbtAzdRXvZypBwYQxMlHn6I8pk/QLv7m8QHp5mDoqMlBlf+BLJhO9Om+elzJiOSR6cYoKMldLSChHL6NGYaSIn2wZupdl0GJGQwn78HJR42Bu23nENa3p99ncdc37cTaR+4meq5P2rtVHOwdvSYR5wK7qqG6NI+pBxOnTDdbn4nX6Arh9C2htKQwsbXv5fymf+B+ovvOP45Hgvl4E3nDARnMJh72JeeHh/pcdLSGTpDZ+jxpiTOMEJVc1oOOcAGJguT9NuCQVlOZ+dGKfuQme56enQtZsy8U2E8fbsChA5RqteImbqDGYRjt9RI54PMqVRijDJkNKEuD5RZtsl8HM2w6gy/0VvDxl0gixqmk9UK7lLbXA4sAuhSlEwja1M0DGMSKeR0pQjSai7+YOhZQgRXUSWlSJFWxrTeMZQx3/+UhqduWeQpi5pzVWdp/LX34XddCikRP/OfiAfvY/Vjf4jffjHajtCVg4w++58pzn8eWhvGkwwWLRipGTP67F8Qzn22MbPYEvd+i+W/+7dorKmv/zt0vEI6uoe1T/8ZmlrWPvOfSPvuIh2+D3zJyofego6XGX3pb4mHdkOzxtpn/wIdLwNKc+un0bXDuE1nEw/eg9YrrH7gd2nvvp7VvbcTzrrULBVHdqP7v0U6ch9oYvWaPyLuuRVcYPWaP6K953p05QBu0y7iwXuIe+9g9YO/h8aG8Tc/nCPHjEaf/xvCBc+HtqG+4SPEB25ibbRs3+Se21j73F8BUN/+j2isEV+ydu2fkJb2I82YeOA+2nuuO/kEeaSUp4qmRJsia2urD//SxwIR+NrXvRrvnVX1KAKj0bcfIvBU5DOod5ulXcvKVJKnn1zJi5X78oKLgkse9Q2kABLxeCKRrhKHc2Z28lIQU0tygk9W9UGlIDpP0oYC6WoDT1I8shnOe0ds49S3NcHTnBkQwUKxBVAPknPdsnTtCDlqugFJxBSAAmRkQOypyA9gC01KJp0bTYV3K6T8MEW0xbB1mtFayN6zXKxKtIdeTDica5GkJCkQIlFdvmdr2kEuVN7l8DpxFmIuIGLwayKdFjRl2+ig8pzhstqS6IjOIdpkxcT3KQqCR6xyKSfSjr6XqAuXgd4wm4NrzPyqArWrOt0xa3tAhmMEcGraZl+GTLtt+x2lyvUayShATPlZoUiJQdv27HoS0jTp/3GQrLXK1H7ph8inREhtb5qezvVLGfSiYImOKSrkeWWISeIcOm5ABJ99iJqSmagFEMGlJkckCziXCwRYeTznrXB3m7S3rbmkSDIQC+vPyMFqG54Grw1RKhoNSH2Yq3e1vPHZizxra3EcNMyjIhHmf+y3Cec/lyP//kfOBKAcQ+Xlr6N8xtWsvO/fouOlR91OB1PaSoEBajb41KBSMnIDbr9/D+f+2ju44PLnn7Kt01jY+4kx2NpJ5JkJD8fKljBHuXmROrUsHT7ESoBDLjJUGNTKWlFQtonlQUuZSqpmnrVwgK3bLuT7nnsun/vEF1nSMU1Y5Jxzn8545Vsc3beb4OatVqYUVPEIThNr7hyWBxWRA2xeTSADRCKKVaNJYig8c4MhF1/wVG6/5Ubaeo3E0MxVOU/UrHWKJAhYZYKUSlKxjFIgcR4niRAXrO6FO0SblojyFNq0nVDdi0uHcHEHuJLox+BaJAWSmKnn3HOfgqNm9733oa3QDgNFhGErHC09a4Vj2CSG0UxhXmHVB1pfM9eOUd1I7UoWy8Po2hqr7GJO9rHGZlrnUdlHSY1rFyENiK4BV+cSXgVtSjzniqez56H72bfnQUqZQ6OYT8g5WqyMnfOeSEuItkCffdHlbN9U880vfs2QoIqaKAU+ljiOWADIk4CRTjO8aZpUFIEy1ccdnzk3L/2xYwFyfNqqECcYqHbR1L1grWCdg7PrQXGKmhY92g6zI9cxpshg9oLsBu4zTrw9hGXFdJayrnElSQA/tdxlLP6Uj3fm4k4Ms+MTgQECg3SU6FoUZdg2lOqIwzHqWkK7SKGOJKeheIcqKx/8PdB4homuQ/XN19Dc+klLh3nMlJigRynOCzFFmjimjQ9fMXxkoUnH0fQgP4EWrsxEU0q4QcllW87mgnZIIY7lQlmrrD5mSNB6x2AEm8eO7SuBQSOIb4k64AUvvQJdWaMRQ9tpxbH1gvPYues8IiV7Y6Ip56i1ZM0NaGWAGyzw4pe8gg2DRbw6iibhclFrQfqalZs3b+K5z30+PtfptMANeoxfRwZAx+WgDIGu5qJajclYD9i540KedfnzueKyH+TcHc8FHeP8KnXdgFSoKEka6rZGRGhj7C1+559/Pk+75BJUlbIoGI6VQSMsl1AHe56UEltqzy4d9ljFYI+T1HHO+RfyL3/jzWzesYttu87nB3/g+3FxDWlbYp1wFBgWa0KlBZmAgJch8H3PvZKzt+9gIIEiQYFQJcHVDY1Txh7qtmFzDCBwtFKWlg/zylf8EBdffJH1iQbT1qmZqjtzhs7Qdy81q+sGHp0hINaniYmePnpMjFT7EPgnjot0OBzgvevz4XO34gYAACAASURBVHamknOOKofvvI+De/Yx1MCG1cR5e1u2LxlzXBwVbF1SnqobmV9VIiOKTbt43vMu4qavXM9qXTOfAmUY8LHP/CO33nwHwc+zVszT6IDRYJE9mzeyd37AfU7ZdNnTWS4Dh0thXHkOxhGgffRdWZbs27ePd7/7ncQ2MhpZ8vKU0cvKNrWJtqkzwLwHlxmFBrx3VOVWnnnpVdx80x0cemjI8y59HaVPqB4iqVJVm0iiaNGQPDRtQxEK2tgyHo+59tpP8KlPfQrvPT4EtI2MglJ7A9Xf3Dg2L0Wet/Vcdm3fzpE4Ml9RBvkXH9iyfScrTeJVP/Q6Nj3lbC65YBtzZaQUZcuGrcTaTMIAKjUxNYTCoiAF4W/f9jfc9I1v4hNITGyi5Mq5nZyzJCzUwuIYNrqK79etbI0FPiUOHNjLRz/8D7zxn/48oUhoKo2ZuvFUD56hM3SGztC3h05L+ssTicbjmrZt8d4xPz/HucVTeLpuZ3xxYImDbD5Ss2PLVsYbGra4gm/sexBZ3ML3n7OZO5oVnrJzF18+ehc7n/Ms1g7vY211lXp+A+C5+MoreM3Lr+Zjf/JWlo8c4sVveD3nzs2x7/AqG88f8om/+hueddUPMti4iec897mMHtjD/TfcyXB+DsZjNCnOOc455xxecNWVPO3Ci/iDt/7fzA3nWBLwSSmTULXCZik5d3EL5ShSJcc/6kHWGJt2p54YlQ1zW5if28Q5Z1/AroXLOG/n+QyrwObNW/jtf/P7/L9v+R3uvute/n/23jvakuq+8/389t5Vdc7NnSOZbhoaEEnkDBIgRFCwwrI1ntHY43njt/zmjcOzlz1e9nrjecvSc1jPHttjy7IlW7KQLAkRBAKEQGQhIRqRupvOdL5904lVtcP7Y9e59zZBgLqReqT7ZZ3Vh3Mr7KratX/799u/3/ebuwJlUqgor2q1OqedfhqXXXYe2zZv4PZbb6WbdygGUoLz9BeRjP8oX+OcviVMdguebeykX6dVIDF6paXzdAvLVLPNrn0HqA+OoNiN+II1q97Bh3/+A/zFn/2/TI3nMXyiIkl8nuf098/jwgsu4H03X8vnPv0pnnt6HfWkzlHpCGckCxiQBom3hESzINQ4J1lIUXrafoKxUPDSS1vJskBWU+StXiJLCWSv2S/mMIc5HAypjyBJDT+15+090WswIwFI2ofUhvFTu193V0n7kPowfvL1tzkScEge6TSB9BG2Rqp1pE3rdrtsnNjLej/JA5PbeLY7ylHDC2mMT/BgvpO9nSbn6kWYEMhbbV58eQt7du7CW4/UE3ThsSEyu4S8YPuGTYRWF7oldZ1w0lHHsP6pZ1j/3WdgskM+3uDAph1s/N46nv72Y2x75jnqpcPkZSUMHJlnNm/ezJe//BWKMkcrhXUWL5GA30lctymDo13kdMuCdt6dpbQDvVSOssxZsGA+WS1l67ZNFLZLQBjdf4Bf/83/zNZtW/DO45yP96QK7ZZlyfe++13uu+9efHBVAbpC+5hc1CPj77qS2oIRup0u2vbqhWcgQkzuCJ6x0VFGhkcIonHO89KmTXzik59gqhFT4GP4Wqa97Xa7zf3338+2rVux1kaBZXpJVXF7jUSNTiVoY0iMjsT/SlGUeVR1MQmhknY75JWKOczhZwjpSZdRu+gX3+azCOnqS8jOuPFVf9FLVlO75OM/dG+9dA21i2e2kdow/Tf8HskJFwKQrLqUdM3lh7fJPwIOwxrpTNr7kQhrFFYL/Z1A5oSdxRQnjCzh5N2epWk/GztjFNoxqR2tfmF/2aIoYdNz65g/byX1gQGcESakYHjZQiYmx6gvHKB/8QAjwxmbX95AfTjlped/QGoCA32G0nYoJSfJFKVYRENZWpyPChalLfHOo5SiLEvSNK20Oat8XA+ZhUFvGCFhvjdofLUO6EEcPnjGJnbSaI4yPrGfRSsUL255jHZuGRxexm/+9m9x0knHQxAyU8fmRSxYrxg7nHOIRANqbYl1jv4CMid0TfRId9c9n9/7DANLFnDCwAJEV7yaVfG9ArQEik6LybF9nHPmWqyv40hZeeyx/Jff+nWG5w/NLOYHQ1k4RAQlCpMYGq0WST0jdyUljh3tSTboFi/6CbaHNjvLBpukzTom+EFnP03xeCssW7YQWzo6rRKlQ3WOhFfXo81hDkcGxFTREtGgkoP/lr6iZlHUjCf3etvo9I3X1JSJ55vdBhX/X/pGUMNLX729PrhtkX7qFb+9FnT6Gm3uxx3Yjt314quOL2kdPbz01eecdb7pbXrN6xshO+f91C78BaRvPnrpavSyk964bW8zDpGQgen10SNljfSV6BY53+3uY2tfSaFgXXsfWmnWnnwKL3UP8J36OItdoKRNUXM0jKBCnbB7O89t3c8Jq1cx/sxLdIOj/fIu+o9vsfao5Wx/aT3P33EX2fgB9MIlHNi2HU3O7u2bOG/tu7jmxmt59hvfomk7OJfTV+ujLC0iwlVXXskVl16Ot5YPffgj3PK5z1IPkZrNCTQzIVeB3XY/Kni0EQpxEDKQDmARMvqH4LY7P8eF551Dc2oP9z/+TVyW0m4azjnnbJ5f9yCbnt9JUXoSI4RQoJUmyWrcdOOHOOXkVeT5BMV7rueur91FoQNpCYNeaKRQhJKh/oxHd29k0dAgWdfTzioBZQBvGd+/h+2bGuzcspEX130PN76dkhoTrQ6XX3E5X/zCp5k80MZZj6iEWqYJXjE8Mp+b3v8+Fi1ZzMVXXE2z3eL5p18gV/Dt8a3kdUuRKJwKJHmDe0OLkCkKAv0Dw3zg597D7bffgS01XrogCfgaSItX69POYQ4/OSQnXkL/B/4QP74bNbgQd2A7emQZ+dN3Uaz/Fn3v+jUkyfCtSdp3/THDv/ol/NR+RBvyZ++leOZO+q77TSTJ0IuOp/vwZ0jPeC/YAjV/Jc2v/iHpqVfTfeQzhMYB+m/6fezOF8jOuYnQGCWEQOOz/4n0tPdECsChhXQf+zwAohPqV/4qeuFxdJ/4EvUrfxnVN4Ld+QL501+j7/rfQYo2mIzW3Z/EbnkSs/J0+t7z2zQ+8yskJ15IsuYK3P4tpCechxpcQPtbf4ukNfqu/S+43esjK1JjFNs3Qu2yj6P65mG3r6N4/j70stUM/ft/QExK+5t/hZ/aS/91vwFJndCZJH/m7lfcTSHYAjW4iOT48378D/N18FMg7P3D0RTHs+UBOn1gSkcjg8fzPXxncgd5Br4/YbzVYExDRzpMZXVGcs1g3ubeR57kg5eew7oXtuFqwuiB/dx161fRai81LFOjj+J8mz0bXmTYtRj2Ba2pfXzz87dgzATDrZLBpIYNButjCNU6xyOPPMq3H/gWRgk6RIq2JFS1m1X9Zo5FUqFigCOzAelJlEmssc2LCUyiePDb96H0AXStgZflXHvtTTzwwP08/PCD4AXxOgpOC/jgKTodvnDLLShdIKFA+UCSprQ0lAgLOlV4WXuUCjS1p9mdxGg1XesnIXqjO7ZtYWzXGMoV3Pv120jlAEPzj+am97+fz3zhH9ixcwvOa0TqBBcZbETBgQNj/O3f/S0mcdiyQ5YYbFz+jeLZtZjJrEVhM6ERAokP1Lxw/AmreO75p/nuk09BMIhqx1l36N2f12fZmcMcfuxQBj+6ldadn2Dw3/4NdtMTFEWH+oU/T7BtpG+E8qXHyE67Br3wWBBF/uSXCM5Sv+I/YHc8DaJp3fVnDNz4u1AbRvUN077nL6hd9DHspkdJT7sWQRGkov5TCj+5n9bt/43+6/8v9JKTcDufpRBFuupCzMpTcfu3YlacDElK++ufJHQbFM/dj1lxCunJl1I8ezd0mzTv+COyd1yPWbYWu+VJ3OgWsB2y069HLToWu2Mddu9GKLuka68kWX0xdtv3KLc9TfuOPyI9+Sqkbz7uwFaK576FWbmW5KSLKNY/iJ/cS/PWPyBdezXpSZcSbAlZP3bb02RnXI8b3f6q2xm6DfIf3EPtoo9Rbn4S7NuQwRve2ghymOpIo7DxkYhOalASGOg2SVSgRNNVGb6/hgklurR0sirUQR/DFoKepKDGvs0/4H9ufRbnPTRhCAuhG0kOSLAUGAzGdemiQfWh0g5DDnCa0mjKwCxqreqGuxLTC7GKxsnBArImxE+shwMIBNEE3QHfV9XJttEGumEUklAdeR6EDl+/46+48/ZYYlJFYolEByngMVLVFnqAGFYugbQqIByrB8DSB5Qhh4phrNAglCQOSqmDLskosa4GugZ+khxDPrmbf/q7/w8fHMFn1fnbVceMws1KinhYC6nUCTaW+fUkzmeTMmg7cx+cwEvPPM5LFUVEZIyooz2gOjhmCb3OYQ4/ToQew9PBkBAIrXH83o2ETrMyRA5MgkoHCFN78ZN76Tz4afz+zUDA7d0IopEkEmqYFWsY/qVPkT99J2FsB9I/j/4bf4fuE18C261E0avzVef1U/vwezcQ8hYq7SM9+31IWsd3p2akL9M+1OAiJHiSM24kW3s1dveLUGU0+PYkfu8G/NTZSBL5julMUWx8jOzCnyeM76Z46qv03/C7hE4Tik5UJSLgdq8nVExKEMjOvJn0pEui0RVBRBHak4T9mwjNM2D+0ai0n9Acw41uo/2Nv4jEN/NWVCLxxDBo8JTP3kt28uXUL/wo3Qf/fubvbwGRvARm1z73VHx65YhvFocpO0OOWE3SEEKsqSRE7cK31M4QjegRjVc/befcT3hiE3DOEvzbs1bZK22awxyOLLzO2PKafTX+Znc/j2SDiCsi76yog5f5A0jWh28cIH/mbnzjAGrJCYTmGPm6u2N4t28+oWiSnfNz9L/vD14xIszKY9EGN74TNbBg+q9205OU6x+idsV/rKTKRuNa5+z9XyPtwD53L2poEaFs4Sd2I2l/3PeV67izDiNZ3EaS2vSPeuUp9N3w+6Rrr8Ht+AHFxkcRk8Y8ioF5BO9fff8ChO4UnQc/RbD2VUmQbxbTe72OBF54Cz7pYRP2PkLtKCEETj55DdddfgFf+dIt7BufeuOd5jCHOczhLeO1l7jcnhfpPt6G4Onc82e4nc9BCHS+/knspsfpll3U/KPxEzsJ3Sbt2/8IN7oZENp3/HdU/0Lc6FbKH9xN/apfhawfN76LcuOj1C//Zeyel8gf+kf00e8gPP9NgisI7UlsbRC8p/voP+P3bqbb2I1efgpux9P4xn5Ct4Hb8QPcga2YY87E7XgWc/w7wVnshgdxezeQP/Y5AOymJ6okpXh9bmwbrS//Pn5yN6HboHXrH2KWnIjd9Hj0hJv7keR5QCi3PBmFuTuT8fi2pHj+PtzuF2jf+ceotB+75TuUmx6L5PT5FGpwMW7/S7h9W/ATO6fPG5qjtO/+E0LepNzwEK2v/Ff8gW2ved/fGIpQCShUYrVEEfeeWOCbP+Zh4drVWmNMQrf7atX1t4rDzbXbN7yAf/uLH+Pe2/6VTRteQGV1ipDiRWFCiQo+En/PYQ5zmMMPhcIpCyGQOYMLCpd1uHCB5eNrFnL64uwQKAJn2IpfieSkyxi46feR2gBu32aK9Q9Tv/jfgIAd3U7j0/+e0J1zEN4qely7pUoik3goSSVQBkXLazbu2Mfxv/GVHx/XrvdHTh0pRPvrK/KDJE0oS8vo6ChZmpL7t7iKPIc5zGEOr4HeMpGoSokmHGrS5WuUP4RA+eK3mdh8I5LU8Z0J8I7Ot/8eSfogn6rqqA/hvK9xzp8VeOnJPcRkEl+xtvmZ5JI3hcPIbHRk3HznHEmSAJZaLeP0005jdHQ/1tojpIVzmMMcfiogM2Q0gUAIVMLph3TQ1/656MRPbxtbxM8P2+dHPefrO8c/dZAAvqc4FKiSxXQ1SfqJrJEeGW6eUopOp0N/fz+7du3mpZc2cfZZZ5KYhGY3R70FsdY5zGEOc3g99KJwIoLWseQkvKYI+ls66GFo2f8C5zzSECAmzWp8CDgXsO7Nh+l/6upIlRKSJKEsS0ZGRuh02rRaLUQJaZZQhrnQ7hzmMIfDgBCmHYiyKCmKSCByCAd8tSf443BQXsuQHiGO0duJnn6vFYuvVKdxntJ5LFIxub05/NTpkUaR6NgJtNYEW2CUICatBFyjULAOcV0hyBvHwWfXhh0sXhyhgxAkYJUHCSinMF7HWipV8ehiUEShawJISGPathAJFsIPb8er21D92uOmrWqifKXrGEIdVAdChkiHEGJKuwklhUpJQ4eu6ifzOZYUUJjg8WKj3BkBFQzGaQLgtKvEnc105EcqPUwVwrSepA+gJIo9hhC7qkisNUZiKMXQwUqGooOTDIKg8ISQoihjeEwq/tygIKTVPXcgLgqFi0VCwIsgwUwLQAexOOVR3mC8jnJzyuKUQxFF21XQRCF0BT6t7lMaz6XahFCrND1dpB5EKnpGqt8q6bZKJn52b6j0kBAU4hOCKuI+oVZdTw2RJoJgFVSBpapmrZct2KNhdNV5e3GnsqJC1BASREqEEkKGJ9IjBlUQqu2UVyQ2o53EI9QrFb5WGhm06nZ2b5rJUXyt/hXr6np0HFUfq65UgkIqpT+rwFUVHMpDEgJBfEzCCb11p14PCrFDVEIM8SbEFSpkpiUCKC9YMXiJ75HyFkXAi8aKrt7ntxcqBPAKT8AqkOCo+cBYy/CdRj97ihzjD036TIQodQho9eqBPEk1w8NDKK3RShH8j1L8MctIhugQJWmCEkVRFvysxHV7de2+6pOCj7XAovDK0HfUEoYXL39Tx/qpWyPt0Raqiv28MTnB/r27+ZM//Qt++3d+i927d73CKL3RzGumiOoVlO0zBdDVRNJHQdE4DIbKauCZ/kqoCAeq4ahX8fumbt0r2yAzP0s8chzwolGXyojEgatnDBSKAi+CChYvKnYeIRozLwRV7V8ZdxVMpC4kKsdIMNWle1SYIbjvtUtVzXLOoVQCQfDBIypE+lAf08wlCEE0EjQ9vVIJKo6pvQFVekkUvRT1KOEmXsfz9lLXg4D0wmoBL7EdEqJxdUg1wfDo6nyhumYhThQIKn4XF9vBrASOysjFe12Fe6p0eYKamRDFBxHXzqb3dtGwhazqK5qgfFX4LdMkTLE98X+kmiuHisEKb2Y8BJnpj9Go22ikgwLxVV+sDFNQIAGrBB3A9CJV1TNLXSTZeO1OOOstERA/85RD9daE3uVWpr933f4Vx4kXZ6p7WE0YK21asCBxUjLTBpm550AICq0sZVAYk1GWFiMgoeozoni1HPnhh1SawiJU2rwO8cLLYx3uae9CSagSjg7hHFJpFhOFG17pLa49/Qx+49f/gPnzhkF01ckOreqgN2ZSCWuIyM9Q0O7gKw1UUYYAJjGk85e9qaP81K2R9trhQwAXZxe33PJF/vVf/xXvozLMW/Oe38x1VTPnMFN7FCoj4CWKcOvgKlL63qzcTQ90Bw8ib60d08PbtDGp2jPt0UWOwem9g0J5IGi0t6gQMMFVzCBxYI/OQKTcK1WvbYKEgA6eMH2WaAyczPhkqkq60CYOAtGMOdJMUxQ5iFCKiuxI9GG8inNBcagQQyrThr83QEhPfimq2TsVB2XbMzoqQHAz97InhI6bnrQIuvpNVa1MmPa4iM8h9gt98JMIswcpgZ5QeUiqczF97QcPepUXNv2JA300juDosaio3s6znnG8Z0GKapTriQWY+DxxIEV16ur5iJ2eaKigkZAh3uBUZ9qL9NXcLaluZ+Kg1L2nKQe1oPdLCL2+E5+uP4juJU5QnBJU5VyKVGRT9KZwlRENswXXw7Thn36u04awau30s4rTCu8CQQKtdpt6qmaxfv34UMVXqisQEI2T2HcmupamrlOoN0Hu/kMQqJwAgWBffY3zZASZfwx9SxdPd5sjZOj9mcZhXCM9ciCVdyAS6ejSNMH7GKr7UULQftb1zQwqATU9iFaeX9D04u7RMxIcUbFFURCCqQatBK9yxKdVOCGpwqlvvQ0x5FalcQddhQNBsJXDa6MoOCGGYNEoIGBQwRNltz2KgFUqetJBVefTFDq234ToKZrp4wuFEiRoCgPaC16EJESmEe8dWZpijKEs2rSaB0jT6CUHSau2p/F8PcMvtvJGK28qhGqw7YVYo0fjxaOC4ESTBI9VnsRF+sAYZtTRW6kGahUE8Ukc7KtnE6hCiT0yYzxIZaykR/XW83ZneYHBRCOqcpAuPlT+mEjlscSPx+DRqOr5x+MZgvh4buUxjsrznPH+YqjYVsfw1WCpq3NW4W3s9DUEksqDKEDy6rkbJBhUUFiimpAApZrpOypIFZ70BIlGa/oqhelrUdU77iVGKqqeP90bvQS8qmIGIZ6rd76A4FVAKOP190K4055+7GMzUaHpo8a4cLV0EAh4azCJoW9ggHZr4oe+K28vpmMvBKDwDq0yfEhRUlAjn54G9jA7YhOnBeFVv7/qFLPGltn+YRJytAS8LVAmqZ7dHH7SOEQ90pkZ5hGyRDqdtqyUol6vo5RgrcPaEmN+xHmDMrHDzkp3VxIouh10FTIUrbE2gFdopXA+xweH6BoOg7gcHQSFIZCgk+j6eW9j+DR4QvAxYhg8SvVes8pgVm1w3uODrzREoSy6aAkEL3idRB9Macq8iUIwpvKCQxVSVikqQDckiFKUGBwarwRrNA7wovFofNBk8+Zx9sUXopIEtKYkELSm1SlxJq5Z5SbDSkIXjUdwVQ3vBRecz7nnno11OfNG+jn3ne/g/AvPZNnSFK86JDKJqA5IG6RJKR2UyhEUtgR8SnCGNEnxzhOcEFyGk7iOE5RGPAzN6+PqK89DqQIlnjTRnHDC0Sxc2I9Sebyfogk+oMWjjMX5Eh9KROdIL5RNASRxe11NKLyK3lAoCBSICoSgIFiMcoADFZ8JKto6owRcABK81ySqhhZNcAqjNd4ncSKDwygV2xak0vf1nLT6OJYsGsA7CD5OHhKTEqwQvMI7hZIEISOElBAEZQJHH7OAy684g/POW8WixQJ6MvrQlbPe1YGWODAapwJFGr0pBZWgAbggUSEoSbjk4ktYsXzZdJA3EL3aGJVW4BXGKWpFQLvKPCiFIkTuY6IpPOmUlRx1bJ3Lrjwdk3ZwoUMINkZFVC2GrkPP6w4EckS3ufjyUzjr3JV84COXkCYpg4ND/Ppv/AYrV66YfjUDMfpkrauiTb7K3Tj8CMz2quMkJ0iCVymlyhA0yiuMV+hZH3XQd3nN3+NHMEGhg0x/N14ftI2pli2USeP880gZeH/GcRgMqVRG9Mh4oHEwioTtSimc81V6uvmR+GcDIEozMDjEr/0f/5m//uu/4w//4P9m2dIlzJ83Qpl30Uooipz++iCJSrFl1MjUWULXCe+5/iZuuPZqXKfEloFux2EyoShLlFJISKcNaBQAcJTTi/7xkxclyiToJCFNM7zz2LJgqH+gSrpRFM4jSvP+m97HaaetivRg7akoYSaQGEXhqjXEviE6pafM+rFpjQPdgqYWXJJQKMGKRkyNPMuoz5uPVklMAuofoRUMtZEFdCShQLH6zDO54tprUf39uODRScLKo47imuuuZd26dWiBxBjWrD6J4048kZVLhjn19BP5w9/7FQYGSy654h1cc825pAMa56cQuhgBjSLVwtTEKLVUU0syjBh0kmPLNk45jFiWLBvg6svPQWijKeh0Gpy46ijmzc+wdoo09ThbUMsSyrJF8A2yzJFmFh8aWNsE6WISh0ajJNDpNBAl1Os1an0GnRSIaVHaKWo1Q00SKALiNL7QaPrwhcEXGikMNVPH2i5ZYmiMjSGuS6bA2w5Ga2yZo4LF5p0o7m49zluUcqxZczRLF/eTmZTUJEgo6HbGMbpLcB36aimhjEluBlDBU+ZdFi2cx3nnn8mqNSuZt0DhZYpA1DQwHtAKk6bo0lOzCkqLOIeE+F4EZdBJylSrTZJojlqxhKGBgeolqLzRIPgyJtRpJwy7hKNsjeFSkQTBBVcli8X3xwucuGYl/YPCO889GaW7pIknMQolQt4pSZM601EIIhOdUiVnnr2Go46dx5XvOiuGTyfG+JfPf54PfOADpGlKkiQoEYwx9A/0Y61FKU23260moocXYVb4O8YhYrQkhJj5UNBPIYPkMkhRfV75vfyhfx8iZ5CcIYre91fuT33Ggz+S9St/xnBY1kiPpPBuNEZRSehwrd06YMnS5YyNjfMr/+mXEWcZ7O/jg++7mXvv/QbjjUk+9tGPcuvt3+SYE07kundfRKczxlfuuIdzT7+c6667mvrkZk469TL++Z9vYXQy5yMfvpD+bAX3feMOdm/t8v5fuAlnLbt27WJkeD633vaVgwx/UquTZjWuu+bdrDr+eB5/7GG+8/ijXHrpxTzy8EMsW34cC1YcC2WXK668irPfcTzbto5y9z1fY/vLE8TJhSWYGkkaGDluNUcvHSGdt4R1Tz6BDI5QWz6PVSMjrFi5nAe++TCJr3PK1VcyvncXSWKY6sLKE9ewdPESjl+0jDu/8zCLsn5WnX02q4YWYYcGee6e25kcn+CjH/0F/uXztzA11QAvjI9O8eTjT1EooTV5gCVL6rz88npOPGGEk05awtYdL9PpNLnw3DNYe9Kp7Nre4sEHHyOtBT78kQ+SJoZv3fddDhzoctRpx7H92V3oxQs4Lk2YCAfIW7uoZwVXXXItT2/YTAgNkrTDoiV1zj73Yr7xre8yUE+57n03o9OSL9xyK/PnD3Pc8SexZtWZbNuxnUceeoLg+xDlMQl4V9AuHUMjmo/8ws10ug3uvfsJOo2co46qcfrpqxlcsITb7rwf0V1WHXc8Jx57NDu3buKhR37AwgVLueaqixisGR64/16MGmFo4SDfe2YDxx+3mGPmL2LdsxvIvUMbhQ9doECki3Mtjl25nNNPP4e7776T5Uct4uKLz2b3nl089sg6Qq6xrkkIJUZnZEkfO7eNcv+9jzPVmGBsrEkwGbmHpIwrqNEDsAAAIABJREFUqdpDYh1Ly4Rj5y9m+97d7MtyShxIghgdHWnRXPPu65k3soCJiTF6GVExACwkxpCFBBUCK80gxyvNd8d30B1WlJnC9sZ3idnczz+7gdE9B3jogcdRwSBKs2L5SubPW8RT3/8+znWqOGdcvy4LRVar8eD9T9Lq7GdqsoNzHqUS1q9fz7nvPIMVK1eybcsmtKlx2dVXs3/Xdp5Ztw4RIcuyainn8MJLLynOUy1SxDB35Uj08gtClcLc+y7V8kXvLqppUyjTf48h9d73XuhXIhdsiM4BAjr4I2SkncNsHGIMpHrgRxhp/ex10MPRrrwomJycIs1qfPpT/8gll15KUeQsXLiAs886i6OOXskxxx1H8MJ7r7+B2772VT77T//Art27+daDj3LXPQ/x8EMP8D/+5M/Zu2cv77nuBp78/uPc+fWvc9NNNzB//mKuvPJyzjv/XNacvIaT165m0aKFzPZIS2u56aabyfOCT3zyk5x33nksX76UK6+8gixLWbFiJe+98UbWrXuaJx57gs/+06e45fP/wq5dLyMYrLM47yiDR2c1Tj/vQhpFwbPbdnH8aWcylnvOvOJyOng2bNvGmeefz3izyZ3fuJvlxxxN3i1Ian2ccNZ5NEj4yje+yeqzz2H91u08tf4Fnn7+eb5291002y2GRobRiWLL5i14B0olpEmdzS9tZdOLuxgdF+qmxnMvbOK0tcdTtCcAYbh/gKlGl69+9V9417vP4PjjRrjowlPYtXMdX7rlM+zZtZ5gm6w95RgS5Vi4cJDVJ6xE65IlCxI++uHr2b1jI9u3bSCrOU459Wg+8HPv5ntPPUpqAvMXDHDPvbfTmNrNL338g6xcPsy7rn4nt3/1FhbNH2DF0gWIC0iokna0kGWGU9aeyBdu+ScOTLzMpVecCdLiQx++kl07n2PrlnVcdvla5i8Qbr75Up5+6kGuufqdrFimWXlUncceu5tv3P1VLrxgNd7t59rrzqF/sOSKq8+kLJq0WhPkRQeTCNoorMtRuuSyy8/inWefzMPf/jorVmR88IMXcMed/4C1u1m8MCMzBWedcQIXXXgyJxy3guAUB/YVfP+729iwfpR9+wKF7Sc3sRxFe0hcYLGqcWbfEk53Q5yXLmHewED07JTGe8F5SGt17rrrDhpT4yyYP4/Z0SYVBMqAa5fMrw1y3NBCTlYjnLH4GOZl/QSRuGYqEnOoBTa/NIrr9PH4wy9SdFLwKfV6jXkL+slqDuebQBHXyYOhls7HFkOse2oXm15scd/Xn4+lHtULfeDAKPNGRrDWYrRm5bJl9Pf1oZTCe48xbzWh8M0hHOQBejQOjUXjYp6BFCjJURRoyae/K8lRUqAl/q6lOGhbJXncfta2M38vq2MV8e+UHCnRvznM4BDLX2Zl4R1BkFmRj0N9nwRIdcLY2Bif+rtPcc9dd/HvfvFjBOv4p899gZtvvAGdCF/54ufJOw1uv/02brjxfSBdvnz7Pby4vQne0ewW5M4iSY2VK5ey9qyfozmpSdOYRDIxNkanU/LUU0/xrmveHRMWlKaeZRR5jvWxFnPDhg1orfnud7/HvHkLYuq/aBKtKdstrLV0ihyla3TyA1UCDaRpjZqGrg04pZhoNnnkqe8ztOw4jlm5DC+a3Tt3svG5HyCdkr39u7DO0/UBSTNMWqNT5rTzDtu3baVdlrSKHKMN+8fGWTVvKTZAURbU0hpKNEqBx8dB1UGmamhJKMqY3j/ZKdk/2mLb9hc5+vi1jNQyzj/vVLKLVhGkhTYlTz75Pd5/8yWceOIqvv+d51i/YRSNp5YFElUNMKFE6wSRwPjEPrRYbJkzb9lCGlNNyqJF0YUTjn0Hx166lhUrh9i1aw8SSp75/jMURQebdxHv0arEe4dIEjlUdcHixYN89PSbWbh4hJc27sWk8MLzW9m0YZx23qA+1GDBogU8/8xutrw0zl/82ZfJfY3jTh/m4vNPpSaK8bFdjI/vYcvm9Vx56Vlo1+W5FzZi0gytE/KiQOmASQzOBZYsW8Gml35As7WPE1afzPBQjRtvuo5aVmPPzqdACvbt20NSM3Ra0ZNzXtA6I3jLdP2ulDhACxgXSBQ08xZueIBOu0U3s1jvY9a0UoTgMQrK0uIClYmQ6j+AWB4gWui6nJbLaQVhbHIc21dCGpO+lAR0iOuzRvrptBxp2odzJc4HNmzcwKYt6ynLDsqomGVfvazOhph1TEIIGVqg4yxeAb5ES1wXDaLInedzX/wSddtAhxIfFM1mi1q9L5ZyEBO4ZtJ7DgEhTHvZqpcN3kuWw+NE3vbkHyuGIyX6N4cZHKY10iOHkGG25mgM7xx6u6QsOWbZcj70/g9w7jnn0mh0ODDeYtfeCVqF4tgVK9m7dT1ZZhlaOMj2PQdoNAMLhxfQF9pMje1i1VkXc8373sPgvH6effYRdm9rsn3Ldh789lO0bQtxnuBLRGm8KBzC0Mg8/sMv/28ce9RRKJdzYPdOrrnqSm6+8QZOOGEVW7fvZueeA7z/Qx/j3LPOpFZ2UAF27t3P9Tf/O66+7t2MjCxGtLBm7Rl87Oc/hHEdLCl99ZQzL72ENSetZHTfDmpFl1qZE3xB/2QbNTrB8NKFnHfJpdQXLeLYM06HvCTJp+gv2tRNSWZzaqWlMz7OwLxhLjn/AvqGhui0cvbv2s8FF1yAyiCXAisGyyAYwagE6athpY+77t/M3gMJIwPLGR7IWDTYz7btjp17J/AhYXBkNeO7Au2izqJFC7ASsG3hqqsu5axTj8Nriw4D7DkATz61kcuuuZpjVyxH+zqPPPQiYwcC177rWvozOOO0VRwYHWfXzkmcNQh94Idw1uBdhlZ1MG1QhjRbRGFL6nXLsccsYHT3AfbsaNBph5ioQ6AMGXkxwPi4Q5uU3LUogzA+VaO0Czj6mFVMNAM79gTGWtD1msceeppTVx/D9x96mnYYwEofzgtGKYxofEiwDHP7Pd9ncP4Q77ruSsbG2jz77D72vmzYvMEyOZ7Salt272uzaVubXaNNChxeW0rfJWARKVGhoL8IBBUodcAr4YAUPCljfKs2xqP9DRoBvEQhZu0LklAiruCKK67itDPP4/Krr+HY408khIBRmuAtTlvyrGA/kzzr9/FANs6GpENLHLpnbgW0D/SXIKUjGKEIBU45vA6sOvkkzrvoYlRax/mEadINKQnSjsQY0q0yuR1d00fQmiwJrFi6gH2j+2Jynanx3ps/wIfeexWZbWJCSX//IDZoPNHoqOBRh2McEEuvNCv6owlODE5UVaccDevb+jnkq5jD24FDklF77w3XRAFWpTAmIc8PjdUDDl1GTaqiYqWEgYEBGo3mIbUnkjsktFot5s+fDwJFUWKtpb+/n+uuu46ysYcHHrifsVzIBuZRtNuk4sk7HUzfEGVZUK8FxGd0uxajQenoldWyIZpNy8igo/SORrtD1t+HtSWdRot5w8O4PMeJiTyQ3lOvZ3S7Od4HBgb6aDab1LSh0+lCvR+lFZmBVCzNqSY6HcSiWDys2Dk6RTKynIvecz133PN1BEs+MUlaKsyiBNudYiAHkRrtwRHGioKsbugrWoygCGWKbXXoNlrUF8/Dj7eZqAWWjiyg6yxpaFC2LMMDI/zJn/w//M5//U0mJycoux7l+uhKTmkDQ4MlwVqKZsLAQIY20C4nGBrSGDVEGRp0Jj1ptozQ3I2MpNCdotmtMzKS4fMSW9eoRk5LAvNMSq4FFQL1vgHGxyfIsow875KlKSKKbrdDrV6nKHLSJKXT7WBMDZtbBofm0Wx0KMuSoBL6RubTnNxPklgWL+ij1W5hA6ATkqyfYmo/lBrrhjFJQuHH6RtQNMa66HIeab0PGR7Dlpa6GULrKVqTbRbOW8Rll5/JrV95gELNn+5nIQghlFiX09ensb4grbJPJQiiEoxK6LQLQlAYYyishx9CYxazSpkukVJBwLpY5+kDWhR5qqqSowitNd47arU6ZVnS19dHCJ5Wq0273WZgoB9rZ8gPEg9J2xJSTWmgq+NLowIYL+jgo9GZZqvycT3YO9IsesDddolSNV4PAch1HXEF5555Gu+6/Cr+7M8/SREER8qHf/7fcNnJi/m93/2vlKS0nKBMBgIq2KqGWyoGm/+1cc7Z5/Gnf/rnLF68+CfdlDnMwmFINqqWzY+QqVKcF1TL+tXa7aE4yyFAabv09We02lPVOkxgcHCACy44D2sLHn7sCaY6Fq/qNBot6looux0SrQgu1tAV3Tymx4vG43C2RGlotScgJDSaJaLjpKTodoDAwMAAnU43eire40NUtmk0WtU6kKfZbAKxLEZrRWEtpQ1o0RTdZlX+YymCMDqeR/o+79i3dQs0JzFS0q+EVIMabaKrGsYgCrN/nOG0n7zRQNGu6i5raCUs7s/w3Q55zbFEhLB/D9Q0DotgaDQb/M3//FvWrDqJ7zzxKKH0pKnCKYNJFL70GK8Z7hum1WkiNUOp+5lsW3zRJs08SEqn68nMIO1OC+0MJh2i0bSIV3gMKTVEoNl1kBi8czTbOUoNUFiDC4a8iHUpLhi6ucb5BKUyAhnWCmKERjuAqpPU6rjgabfGyWoZrtSM7ndo0xczUgk0m01SSVGk6KRO4S1BUvK8JK31odIaLniKVkCrhEZeQLCsOn4ta1afzPqXNoBODgqWCAptslj6Y2OJTekM3oeqFteiRUDqBIHS8YYv3XR1Zq8mUUJk4hMVJ5zCq16OyEilaLfbKKWYmprCOYcxhlotw1o768hgBXyfAYn0kGlQlRpKVWMqPUaoGcIF56JBLXJfHTvljRLqtcDg4CBnvuMMPvX3fxOv3XpWHL2MVAv/4y//Go/GhooRaFaR5lsVaZ7DHN4qDskjvf69767qGRVJktDt/uQ9UujVYSoGBwdj1ugho1prUaoaSGY83zRN0Xi6pcOZPpzz1BVo10UQul4hSqHICdQIpIj2uNDCqIAEBc6gjMY6i0jkJlVKEbygUISgUBqcC/Hv1RNTSlGWJVppjIAtLTZJ8QGMWDLlcKUjqDqlaMQ2SLMBus7glaB0gdgumRfIoZ5oSl3QkgJIMWWKsQZd03RUC6c9NmRYDUNFvC+NLJCVjhRFI4OhpsPrGk4leF9S1x6xJUalFFZjTeTITQIoGwv0gwZroFQO7zzKB5TugO9DwjBCTjBTBO/BD+KDR4tCJRp8wPpIVximn1aJiGC0wQePd55pHkcRBINWCc5bQogTkBA8znuURFJBpSLPbfAaRay59cHifYlJJJYnBYNW9YqooE2gQCuD+BpBNCU5WinKPCdLY1u1UoRQ4m0AXZ/VaVVVugXOu1hbKlQ1y4J1liRJIn1c1b/DW8zgnKYyrNxUH8J0KHY2jDFYayuO5DA9YQ4hVB7rjNXzAk4L4nzlgcbX1hP5fJ2KRA2zudxFQnWNoHQs/VHy+nP6ADiVIt5GD1PFtvgg6LRO6QJ95VSksghCUh+gXRSxjwQf10iFnwpjOueRHpk4JI80vvhVp/4JUHa9FnoeYwhMC44fWglMmE5aUCL09fXR7XZxzpGmKc45rHOIjsQBJNAZG2W4z1SMNwkmM5C3QQklARcgq9fBdrGdgsxoCi8UhWNosE6n08AhKGPwoSIydxXLy6zb7L2L8k2EqMNqImmC9YG8m6MNJDrBojBJQggGpTS6jHxLOpSId2TaEBIFoshtoEggzRQaTYLGWUfIhOAcw6LoFJahkMZ617xkJOmnaHdIAyRK00LoIhSlwxeWocSQFyWlCAYPvkvwNazzeAqUGMq8JGhFkgyQ5w1SpWLReanIfQJ5SVCGukkIvoto6LZahERRUwlW+YrfmOn1MOejXqMoITIXVf0gWJzvEV0EfLBV36l+IyC+V64QCfFjpotBCQTrEJ1F3twqACLKxHKFAK6iZ1QkBB8waUrwkeHIBo+EOuhXcMNK79mqyqgooJpY4dEGfMjjMqL0kmfeWHxYQm/NMlo4DzBNqiAEz6vMS2+yOFsmrPfvK2uxIw9ziCQUQWJNajVheT2EIJWwQYhZ3W8gHCGACmWczEqcQPTa48ochcKqHkOSoixzdI9HmvgkfhRq9znM4c3iELN2Z+iyjhSu3TiDPpx1pILWkZfVe0+nkyMSPfBWq0V/f3/0Vjx02220VvT311ASyC14lbB85dGcteadrN+0h+c3bCcIDAwOcvY7LuQ7Dz1C0S4Ymr+A0045iQULhrjnrttxNmZN9tRAeoPC67dyZnaPVgwMDCBlh9LamKTvIROhaHdQkla13HFwzSvqQK8Mhakj2lB6wQZHaRIQg5USj6FdlGhtaJWOUgnK12noOn3zR/A2J7QnSQeHGFy8jFqaoqYmaOzZRV50kIE6ZT6FUZpSD5CNDKKTLq2pBsYHtFOYUOPd770EVJu773qEJfOH+cjHf4mvfenP2bpzL6EsEeUprGOgltLCId4RdEBcRQ6ifGUpYFqWpOeREiqvdDZj8Mz36XsZDF4UXlx15x0qzAQJo4HyCC4aIg+RArDy+nAoX1EHYgmk1UaBSPfnwGsi9WHM+pymIgw9/lzXOzAzpVC9a5oh134j9NZAJVTMvLOWOw757QhgXM/jDDhR01FVIaBew1DPnLn3eeOLUGGGeC/Mmjz0FIicmJnnPP37TDeYwxzeThzS6vv0y3gEEWzMrJEexmP6SOOmxMSyCImE5bWsD1cl8imBWqLRlfdaFiWiU4LJWH7UMRjj2bdvFwGHqFgOMjXVxFsQr5hqNNn40ibee/0NGHOwEkaPUeWHwSQJeTdHBJy1dPMuIpCmkYu1lmXgA4nWpEaDc5FuUCmsTijTGoUzpK5Of24YKlPqZEgw6JDQZ1MGyhSd1EglxauUlkkxoY+h407k5PMvp2VTnCgKpRlctoyLrrmWdGgeVhJ0fYCmc7ikjyaGKTPA4ImnsGDtKUxoQ1sUSMaJx61hxdJF3H/f3SgVmDiwj7vuuourLruYWpbFUJ0jhrxLj6BQTmL4O0jFq2um5dKUNwf/G/Q0wboKodp+1rbeoHwSjV2QmDWqOgTVjvy6FYdx7O4OJSWaEh2oyOJ1VXDvY21hcAhltU9UDJnWJutx+TKb2N4SSfojiX9sY0wUOuiafMLBhPqv03dnJRL1Mj+VlxiG9Yf+0moPNQemOo1TAatCVEcJEkP4r9l5hWk1mDeQEJzhFHqtA1XcxqIJMovqYM6CzuHHiMNCWt8rgzkS0PNIoWfg5ZBLc5SKPKCXXXYJF198Mc899xy33XYbxx57AqtXr+as007iiSce5fHvruOCSy6mlhrWnnwyX73zPn6waTdozdTUGJNTY2gzyOpTTuGDN9/ED57+Hs/6p6twFYxPTDA1NUliErq+M2ua88Zp78HHqb8xmgvPv4hrrrqKrRuf49avfBmH4sRVq3jfDdeyd/sOvvivt2JtgVIGK47ceQbnDbH8pJNZvnwp/eK4847bKJThtHeez7FHH8Vz33mcbZs3cvbVl7HxqWcpguLo006hNppz/PveTRZSLj/uaF7+0md4qdVhassWzjr/QjZs3U5Wei669BLyWsqSeQt56LEHCX3HcNrl7yYbarLsuFU8/+1v09i0h1NOeQdbNz+FL3OgBi5n/foXOG9tnZGRYSZaBxjsn8d7338zzz/2Pb6z6Xl06A2e1fPqeZ6v99ilJy2nZlyW2eokISrSICWRS7dSY/G6mkRFebYoW2ZRQUWZUFRUogEUriKsD0QauZ5R66nnvJLavOeV9pJzKsM3bXBiP6hiskSfy1cqQ28eCqYpAQHsIc6AVYi1ok5BqSsuXqLnK8FHYy1xvfQghLc6ZkTy9l4mMjBrQuOna11nUe9XUn1zId05vP04LMLe3vvpdYufNHrp+7010tlC3z8KApCLMDw8yHhrin/87Kf533/1P7J96/Nkieam6y7hv/3Vp/n9X/s4z2zczhXXvZeXn76Hz3/1S5yy5nS2bNiI9wNkyiNlGx80G57ZwJ+++Jf8n7/2yzzAraDatF2NIJCmOq7ZKTedGCICtUbJWQtWcmZ9CQNFYJSCh8a2sF11KVNN6QWTDTA0OMipq9fw2X/8LM3WOFN5zooVy/iFj1zHX/7pH7O74cmpo41i2LfACV7NZ1d3AVefcw6P3vZF1n7wRhadeQHp8uWYej9PPvUMa6+4kh07Guzaohm58jqWZDX8/d/jma0vsGfEsnrBUnZ+/j4axrPETzK1eBkHpE6fjzV3wxdcwpbnvs23Nu3l1Csv54nP/x2PfS8wPHAMG+/+IgvtBH3ZsbBkkO6L20gKg69pysxgyyZNu4iBdAGjjNNVnvnz5+P6A6nPsUZIvcIpwYlCv6mJ06zRGHg9PUsJCcbOSGP52fuEyG3jppcqqzXZIEBWGQ+BMAiqjBuFGqgierxSVEd9ba/MzxKFiM09NKMQJKqsHs7wkVPQmdV0M2sY8CKz9E5fAXkr44UQZmluzraNPRF0Ew5WT5ozoHP4ceIwCXsfGd4ovHKNlMOyduu9ZWhwkBNPOB5szsT4OEoprHU8/OgT7Ni+nT/+xCdwPqHZaHDfffeze9IxMfkdlDa4MqfUHpRioD5As+NBRYUUUZq8W1LJY3LQ2tGs8FRR04wpy27pMlxP2ecdo9rS0B4xGhMM3U4XUfDYY48xb/4I551/Dg899ABnn30WL+/cydiBcSQdiZqRWqFJKPIy9gKfs2PzJsZG9zO2Yyd1rThq0UI2r99I3Si2vfACIRTs3reNdwyewAlLl3Hf6G2EVBBnMUrTSQVnBKzCiccYwQaP847gS7Zu3kSz8/+z9+bBdh33nd+nu89yl3fv2x92ECBBAFwBkiAJitRmLVwkj0hLcpixHY9tesqemVTGKUt2xY4jz2Qq8ThxZjyTTMZOlSvxKHZsLV4imRlJI9GkaJLiKi4gQYLEDrx9u9tZun/5o89974GEFhKQ9ESdb9UtXNx37zl9+vTp3/79DVM3W9DWEeY5gfUJT0oLSdbD2RxTqZEKGNHkzjJQH0Bshljf0LnX7fK//m+/j8szn2Ursp6WYIkSJX7EcIEx0iLL8SIJrIuBc924F84BrPCZqPValQ0TE+zdewUTE5sQUZggwFqLc5YTJ07RabWhSD/JspRut02WpV6o6wilDK12i927L+OOOz7A5q1buOngLYRRtVCz3ZqzntsIWSnF9NIC3zz5Kg++8jxPnnyFbuC7qqgkR9KEIDTEccjY+Dhbt26l0agThiEPPfQQY2MbuPenf56bb7qJShjirOU3f+u3+bn7fhGXZyjbY0ArVJ5S7fQYjkJeeuwRrty6idGhOrSWMTrn3e+6gZnDh/iPf/Hn3PDuA7hYmDt2krHhIa687UYqgzVqI8Ps23cVwwMhV1y1l1qtinSWqSpNI1CMxTGhQGtqksu3buSdt95EozmASMKx40cYHN9MrTFc2IiC0TA81KSzvAAuI4pifud//F1+7ud+zisj62TtlShR4kcTF2aRntPYe51sZit0hf3xfHdZgd8OSgkvvfg8rcV5FML9f/MFup0W1Sji2Wefx2UplcoArW7Kv/39fwPtRbQu+gUqTaihUh+iWmuQtS1nz5xicWGBxx99EJu0EB0QaMPgYI3zz6ejEypym7GsFcTQDYQkEnInVGJNIAEGTbvd4tALz1Gr11hcnGdhYYFKJeR3f/f32LphgtlWh6TXJtSK//l/+ddYmxNHIVWd8ch/+jLaWZ762tfIrCZ1wvLR16hVYrKki7YJTz34JZbaS4Dl6yeOoV2OOzPFf/r8X1MNYrrtJcQojjz9NM8+9U2GFzq4bpev/sVnac+cQVjkr//kVVRmmT12jAe++HkGsmVP+hAM89wzT3HLxz/EUy8epXVmkjiO+bH3vJuF2Wk6rUX6jbhb7WVM0V+2tEhLlCjxg8SF1ZHq1TrS9RIjRSl0YSGnaYoxhizLiprL4C3VlWpxOBHOnDmNEk+KsJKZqxShCej2fAystbxI6ECHRY2bjpg6e4qJy4fZtHk7rVeP0+21WVpaJNC+fALrqAyG7L58D4888ii9Xsqqs8BbqrXcYIrkE6d8JmeUCVWniCw4cmwAKGF6Zgo76TtjKIU/nghHj59ATECEBueYXVhAgEwCjFPYpIfB4tIW2gRU0OSLCYsLjlApsJas12MQ6OUJmc3RThiRkHRmjgUdELouTkKSM2exWGwWEzlL+/QJ6qJJVZdu0mLARNTE0Z48jZOEQBQiPZYXpvnqQ3/H9p2XcuL0JPW4Qp6mPPTQA6RpRqADGsNDPPHEEzzy9QdXaoVLlChR4geFC+TavaNw62rCMCBJ0u/8w++Ai8FsBJ683piALMs804oT6vU63W73om+8okA7hSMEZdHSK0oBDTbV6KBGrZqRW0eaZkUM1xMprBS2BDFic+IwJE9Sz/6C73jotKCtT3ix2r/AG2HG+To+AHf+OoMVqH7m50rNoq+EdEp5kvGiThJRRY6kr7B0/b+JEDjj+VO1JdP+eKENcMqQK42mi7FVrE4RnRPmVUCwQZsgj0lMhOgMI5ZM+84ioct9VmxRy2qd8zWPSmGMQTkK5ibfbSYNIlye4PKMyHjXru0Xl3zXyUYlSvzwoWQ2Wp+4KFy76ylG2i93sdbhXFZQqfk4brvdXvnOdw9ZE6k850xr0vCLBr+FEHJKI9YLwyCsIS6n3ckA50nw9erR+kd3NkcDvV5CqA3i7DkR7FCKcv4ilOpJwYtSj/OVF7xurFAIfJGicELhlCmisq7IejSI6JVi+v7ozErxvsYpRW78/0zBqZppfxTjBGssaIU/ckKmK755sUrJdYQvBVHkyqCdYIrCBQh87aXNQQfY3KJDjVjns6+VQumInhUcOUZpL2RV37W7PtZfiRIlfvRwEZKN1htWac2UUlx22aXcddddNJtNzLfplPGdj3meovDiv2q1cs5/rIxPggFc0cJJad/qahk9AAAgAElEQVS9RRWsOqpguRG1SrggIr7BsnVv4AV1yIo1KrBCKuCUkOlvJ0jVatF7wZij8K5hhy9RUAiB5EV9o/ZsePhjS/+7yjMsZVrTCTSJ8QLXKaEXOjLj0Fis8YxHTjlEZaRGSAJHbiypAauL/qTKU+ppKfiGMWhRhAqMVhjjxavvLmRAGc+aE8QryhHnoawrUaJEie83LkiQ6qLN03rqR7o6DB+3PXL0NPXmKLsu2YKxSxjVwymHVQbEb97fHn1Bt0IOR19grhKcFcX7KgXlSdl9f8UQpRxOZ6iCN9UfTxf1b2qlqLzvVhUcTgtO9+1BjXamEKCCceItQSXkRlY+/9YJVQXVnLKgcm9RFkLJiBA6z1GbE6PEUxEa5ykg1EpM1gtuUQ5FTpwLoVVYZRAMYa4xDnID2sZoEqwy5NIgEEtoHTpvFAw9jkAsgcsAb2n6In5PL5fjrVCtvBLixOGwCDmKHJEE5fKVO+BUUIzD343SrVuiRInvNy5CHek6ytg9B35MmXVkeY5nuhH6/Nhrw4XfefjfWdie+7839/03fL7ipnz9cd/c0b778597D1fP/sYjn++ba9OiFHrlHUVvEVW8P/8I1Dmfynk/P/83QK3PpVeiRIkfKVyUOlKPdbqjiXD48GH27dvHNVdfg5zDL1qWTZQoUaJEiQvDBbaMPzceuR4h4tiyeTNHjhzh2eeeQ+T1ZAdljK1EiRIlSrx1XKAgLZJr1lGM9PVQGqq1mJmZGeKohtGrSUFFus0PcHQlSpQoUeKHHRckSM/t+rI+BanWisFmA2MMreUWSgVrCMLdmyTPLlGiRIkSJc7FRXDtSpEbsz5duzccuJ4zk2c48sqrxJUK1hZ9IEuUKFGiRImLgItCyADrtx7+sUcfw2ioKd8EetWKLgox16chXaJEiRIlfkhwgeUvq9JznYZI0TicFbo289xD2vdn0dKv6VynGkCJEiVKlPihwIWR1hfW3XpONtL9glETrWlSZlcqIKV085YoUaJEiQvARaojXb/lLyVKlChRosT3EhepjnT9xkhLlChRokSJ7yUu0CLtv1uvNIElSpQoUaLE9xYXgbR+nTX2LlGiRIkSJb6PuIiZNqVFWqJEiRIlfvRwUZKNyhhpiRIlSpT4UcVFauy9fmOkjqLptVIrbcHWUDIUTbJ9X1Cr+o2ui7Keoj8ogFO+ITVKF585VNHL1AJWOTQOxPcbVSuMT4Jbw/ogK6/VzjlvaGpWcEXoNa/V7/hzyzkNx8R/X/neo7KmPtb3GJVilFKMod9fdXU0RhfdUIvOZH5OFMaporG3fwGIKhqTiz+WwqGwQP9cBiEoxiBrZn21o+u5LVTPnRUElBM/huL/2slKM3MpssQFd55K4PVZhlWiRIm3L972MVLRmtwYUidIagktBNb/zfoO1kS5IXBCO3b0Ao1yIVZCJNJYEpzNcKEl14ZcKmiTEaoeuuswYuiagMR0iaSNcTG5rZDnPSTrYpTGBv2OM14YWWWpVCMER6gVYaGQ9AWXEUXgFKFVhM6/1+IFGrqL6BSlHVmWE0gEaYLJNdpmiGlhdYBog3EQ2hjjLEp3feNxUThCHAEohQ4ERYa2FmUUufZNu43TiGgqmSLuCYl2pLGvu821w9AhQJMRE4Qpxi7jJCJWKVlisDTJtAZtUU6jXIRTDiM5kRiMC1GEKAMYi9IZCvEVvkYTp/4+OYFMQyVThKJR2iASY4IQkRQkKwRsf35XFYYSJUqU+H7gbR8jbaSK0WXHYKJoSEg9UyiEduhtu8AqlmJIAwgt5EqwWoNS2Ehz4JprGY4a6CRH54pAQnQOKnMEKsI4Q2RDGrlGZw7tAjKtcbUKYVwhce51DWZ83W23l6CUIk/TVdp/JVjlBUdqoBdCN4BO2M+Q1sU0K6xVVOImeRoQmybG1QmkjssVNheCUCE693ae0rgVG1ytvATB2gwFWGvpKEecQzWFxChmI2GxakBrmglEqbc6+3DOIGjSLCMINMrEaEmoVQKUgizreetdeSvSaXAarCpseimUMWcR61DWYQPNsrK40NA2jm6omK5Du6KZCx0tZRkdnWB0ZBSlIAyCc8hAZH0uwxIlSryN8baPkbpuwvWDW/jPL7uJd2zfQ9qMmal5d2klB6u9C3EggS1LMNx21DJoqJCbr72eGy7ZTTvP0WGVNIy49cMf4rp3v4duFLNci1kODaiQSh4hOiJBs3HPHpJKSJI7UIZAGVatJA2i2Hftfj7xq59gcHiQLE+g+EbfhZpryFThbgbfD076rxAlFcRWGahtYGz0UiaGd5EuR8R6gNAYOp1FUJkXzgQ4wjc4Qe+668P85MfvxTlHEAREShNZL8AzA5FTdCuapUgYTTVbllUhqQwQYExEvd7kxhtvIQiqaBOzYbRJd2kW5XrEoQLlCmGucBhypejlKQSGar3KJ371k9x6yzuITUCsAwYyGMsM9cTRzDVxLoz1NNUcBjNFhGbLls3cddeHaAw06fW6JRlIiRIlfqB428dIL1MNLtdNHj/0LE8efQlp99i4rLhkAQZ7kAReqDZSqGYwkGssMB84DrzjIH/7yMNoqwhTMBLy2FPPcej5V1AqoicKpwIybVjUmnYU0W0McO17342t1siVJnAaY2Gtu1EpxauvvsZnP/s5uu02Wvt4pBKFEQgdVHMYSKGZwEgPtJemgPGClApiK1x71S0MD25jx5ZreP+77kblEVo0WjtEZTid45RGVMjr79Gjjz3Cgw8+gDEBWZahcyHX/jvVDAKBWuK4Ohxlx+hGlpRFi1cEEI21jst27eVnfvY+Dtx8K7t2X8lHf+JOBmoBmhTIQHJEuVUFAUFFIZk4Or0ef/Znf8ah51+A3KJyoZlpdpshairAAXEOExJzmW4Q5f4Y33z2mywuLfLhD3+IKIq+H8uoRIkSJb4lLlKM1K2bGKnWGhGHUoparcY1Oy/nmsoYB3bsYdsl29mWx9w9vJt7Nl/N7RO7uXzRsJ8hPrTpSt6x62reuWEXI7lh1949TBAxNz3DQkWjR4c5ePeP846f+hinJWc21FzynoPc/vP38tFfvo/3/vxPk40O8q6PfYRNV+zh7o9+nJtveQc1QrR1KCUYY1DKsH/fAX7rN36bu+/+CXSgfQYNXqCHzlvKYxKxtzbGvuo4+8MxKjrwLlKhsEoNzcYoQ4MbOHl8hmrc5Mo91xJHdTZt3sT9f/MFrr32GpwTLyhzi1L+dhtjuPPOu/jN3/hNrr/+BkQccRyjRBAFgQMjMJYF3JYNs39gA2eW58mic5eLUiHWKY68+hqDgyOYsILLexgDN990gD/8g3/P6OgIGo04i1EGjCYXS60xwM/+g3/Ab/3Wf8v27dv9FDhhNDPcEI8TtBK0CPV2zo624TqGGE0UxoG1jvvv/xuuvfZaKpVKGRItUaLEDxQX2P2lj/VjjTrXF+jC8vIyX198mcbQLr585gVONODDY9uZ6bb4y+Q0t9U38R4Z5xUHLsv429OH2TGyFalFNLZvYKndZlan2CzALVseefAhPrhzN6HT4BT7913D5MuHefalR3j3R25lMUv5+lNPMCspj/z1pxlZ7jGuaiQIThw2S3E65IknnuTlw4f5R790nxdyOER5FzPgk4SAOBPCTkZVDKq6Ns11tQfs+PgG9u3bx6mTp7ji6i3oQDM5Nc0nf+2/4czx4xhlcM5i1Orvcmu5//77OXnqZS7buQ2lNEmSEhlDpoVO6BObtpsBDjS38vjxl1ioJF7rMta7axWIOHRgWGq1OD0zxeDoFeRyljzLeebpZ/jd3znO4vwCSmoEaKzNcTi0Dum02/zxH/8xgwMBgTEorWg0G1zV2MH2tMaBnVfwfD7H6FiNq1yDbapO0oxZ7pxkRgmddgdjDMYE+IzkEiVKlPjB4CLGSNeHMPU9UjXOCUEQYI3yVlYckyiLyhxjxAwnioaOSPKUwAoLLmWm4nh5aZJ2r8fkkWOMDA4TBxEm0tgkYXBoiOVOm1BphgYGGB8f46Vnv8lgvcHpw69ieikT1QbdmQWUzRCxtGyPTFl8pFOhlCEKY8R5y9DaFKV82UeuIdOKXgBtLXRjTVoPSaumsFodYFfqYzqdJXLX4/DhF0hth1dPvUgnW0aHIZs2baMS1dEYXJYSaRC32v8GwJgArRVaKwJjECfkGpzy5TTHXZuHpl9j28RmRioDLEWWotgHsAgWhyOqxszMzbFr9+UEQYQOKzQHR7hk+6VUograQYRBO1eU9SjEOrI0w4mAUuTW0k26PHnqFV5wCzz22iFOthf45vQJvto+wZPpNA+depl2lqKUYmh4COccWZauJz2uRIkSP4J428VI+xZpEHhjO4s1Z3XCdNYmiw2Ptk4xXxU+fuN76Brhfj3FsracCBJmazBZ93HTk4dewYll08QEMTCgAlyrw5W7dnPPB+9iJKiydHaaZGaWYTEsvfAaYy4kefUMd918K//lL/8y27duoRcLmS5qNQsL6mMf/zif/fM/54MfuJ3f/tSniCsRTimshiQQ2hHMBhmHlid51S7xYjpHKhkoB0VNqEiOkPHQg1/j7p/4ca678Sq+/MAXSWyXIAz4J//4n/Jj73kfWjSRUeBSRHxSkTGaX/vEJ/idf/G7/MLP/0PuvfenSNKUoFGjlvla2rkqzOqMl9QyT7ROMxBEjNmIlYboyuHEYiVnub3Eq68dYWR8lF7qSDNHu5vyK7/6CXZu34FBYVBoEYwTlLVs2biBP/h3/457PnIPn/zkJ3nfB97P/NIic5HwtZkjJFVDq9dhLnI83D3LlxaPsjxgyPMMpRT33nsvjz/+OO12e/02wy1RosSPBJS8xUair7zyMh/+8dtRSqOUIgxDkiS54AFVq1WSJMFZ+5ZSgbXWWOtdfSKCUYoBG9AiJ6uFhElOzSmCnsUaaNcMlS64QGjVDaSOwCrQiuuuuYq9V1zO5z7/10inRxLX6DgYwKLF0g0CgixDB1Vs1iHUCkeVRDl0kBJkOQ6F1p5QQClD7gRdZPEqHLjc10/qsCgTKUgilE88UtZh0Fjdp0/IEQxIQGCq5CkEShABJz1UxbFj525+/dc+yR/94f/OE994miTrEsaGPLdoFWHFexBEMnSRcW0wJDYnxpAaSIwmthBYIUARocjyjCRSOCUYcYiE5DpE6xScxekGcT5DVBlh3/4D/Gd//2P8y//hXzB1ZgYwOJUjOIwJKW4RqrDWxTlCFZJbT7wQonCBpqcduTgqotHOJxvtvHw3737XbXz60/8XeZbibEHLoMSTRfR70JYo8TbDgRtu5vd+718xMTHxgx5KiTW4wBjp2s1qfVgFzrkVN7Mq6nJa2gEa3UvBGNpKoF4Y407oxv5t2LOFa9gz6hx66UVsQTaRBRptewz0zwPEeeFWtB0C7Xl5FB0qAmT4c/a/XBBX+FjlmpieDrzghHOnUArBqdU5zEgQFKWkFutaqMAfTWuFyy3GGUaHGvze//QvOXz4MKpfsUKwwgZUJOauJB+J+Gxaow05PumpmheMThpShBSgSDbSBXsTSggkLS7HoG2HnCqVwDA41OC//2f/nLm5OUQJkPcveEXR6Z/b18dqMgTMquMYbOEW9nPgilvWWp7nM5/5c/LcIRgcdkXnUmUhaYkSJb7PuDBBKp67zguu9bmBWWux1lKr1bDW4qxF6W/t0VZKoZS3bFutNkeOHCHPfxiSWRRZlmGM4eGHH6ZWqxVubqFSqZAkaZFl/b2FiDA/P8f993+R4HVkCRcLc3NzWOtI05QoCi/68UuUKFHizeCCdla3Jka6TnKN3gBjNCMjI2zcuIlarfpthWgfzjm0NgRBwMLCwppM4PULESGOI6y1xHFEt9vFJ4Jp0jRD6+/PDQqCgCiKMcZn6X4vBGmSJCRJQq1WLZSH772CUKJEiRLfChe0A/UtUc+1e5FGdIHwYxJEBGst1WqN22+/nf379xWlEt/dMdLUW3BRFK2bjORvh/490NrfjzAMzqkb7b//XsM5d856+F7MXV/JSdOMMIxwbp0svhIlSvxI4iIIUnhdK48fKKzNMSbAOYvWikqlwvj4OA888AC9Xu+7PErRXWS9aAffJVZd7Oe62vvC7fs5Dn++750C0l97PwzeghIlSry9cZHqSNdPjNQ5IU1TqtUalUqVRmOAJOkRRRGdTqd0A5YoUaJEiYuKC0o2Wmt1rBfvZxiGOGfp9XoYY9i8eQsiQrvdIorCImN0nQy2RIkSJUr80OMCXbsr79ZNjLTvwjTGU+O9/PLLVKs1oiha4QZ+08dUq42nX+/GXi23eOMEqKJWdG0L7XOhi5d502M6zyi/5Rj9OPG9Tp0fkyjr6zqVRYlDixA4T7KvpRi34EnqUTjlyLXv9Rk6ME5wBcNSaD0/r6NoA2d8o+/AuqJ9myl6vhbuWCUrL1FyzkgFQVSO6BRRKVL0F5WiZbhnXdKe5H9lfvsvVTQyp2gCoF/3UkWNaX9+HCtsUfTJLgDO99tzj+MZpuzqsZSfU0+agS8Pesv3zxUFP0WZ0bdYs0rASL99uu8UZIta5JVrVXnx6l/j2uvU51k1/pz9lxJdNJZfXcueH3LNmhWNKMEphyj/HV3cn36j+XOvURe/N/49q/16V+7LyriL19rrBpQIungVRV0r51ltEujHZLUrnuE3cw/O9/3zf9afm/49989Nf91qnMLXfq+T8FeJi48LFKRrG3uvn0WilF6hCrTWQpF4FIZvpVRizYavVh+wfrcWL0vO7Ycpxe/AocSisP5hWqnpXP19n4D+QtHfPNTrNoLV8fgG4UYAnO8KY3KcykEJxmkCG2CsWdmEFKCdFxxO5+QmQxREuRA6RWb8tlzJhdAKTvuzp4HDiKWSW6zSWAIqucE4dc5cuqIv6do5QQlOW5zOEJ2CyovNSBVzaNFSqCBi0eRoLLpQBnwD9EIMyOtea8SbKCmES+6JMQrWqNWxnOf3/Y1bQJHha2P7M2+LsVoE4+tb1erWuXK/1+Dc/8rK/fNKjFsj0M5/DC2gnP+F1WCLfq/9r+hzlITVa1z7WqvU9Dv0rL7316ad8nMttrh2UzRSV4VQ0zglWJMjKsc4r1hp8Y3W/X3WhaJhUeKVIUQX4+g/GMX/+0K/rwAoe84c+Pu/KkS1SLE+/DFXlQiH0xarc6/0fVt8e0V07XfOeY6L51xL/747jIAplCGrQnKlEHlj96USbx9cICHD2vKX9blIkiRhudXi7rvv5nOf+zxpmvLmFrQ6/zO15s9r/dqrz2uh2Rd/81r9KmSFO5c1/7519IXlG4ZXjMcp6JkA1ScwcN56UmJwaDLtGY2stt5KBYw1xbVpAmu8QMWQK7Dai1sH5FphteBQDOQOhUE7TyahlMUqIQmEXug3clNYpoXcXBm/KAGJULYKKkeJKy5Je2VFCQhYvVYwFPOnNIgt7kdfYKzZ8VYmQ4rNFvqegBUjdWW+HE6fbzMtbD8FSFC84uJ3GlTmjynGPw/Svy5WLKK1R9TnHF6zapsbPzeFPb+qFJ07nrww5gQprNO+tcZKH1psvRh6n6e5z5XsQNnXadJrcx36YZsAp/2/gkMKUg+UKhoteEoMLxiDYqiGvk3oCFAFIYcU989p7wVZFZoKtdYyFVMI2f5LoVQPJaq4LorP1s6nrKwhWXMvlfPMYt/ZIP1u9oRVi3P1rH7OrCoscDROaVRhIXtlzyt8a63WEm8vXGCMlJWm3utUjtJut/nTP/1TKpWYTqddZJS+2aO8/uLWCsHX/13O+VwwhdbMilD1eKOb7cJwvhuw1lJW5Np/yziNcd6acChEaaxSWGMRnaHIUc73WkV7C8CI9p+hvdWD8iT0FIJUgUITWEeg/WaSaUFhMVhy43udBs6sdLkR6c+D+H2z+FA7jahozRx5V7ESQRWuspU5U32BqQth2p/L/m669j6tsaLou18LYatg1aUqbxBar59PVfSFRQL/uc5WjkrhpRB97i/feMS+sFo96lp496Bas2761+WPZH0TIm8BuT7jVCFElb9HgYTF94tmB0XzhNW1t9Yb8nprTLwVWbhhRfXP7wqXfKEk4r+jnAHpM3H13fEGJUV4Q/pWuhegXtVUK8f051GFQC7eo4v7cq6XxasZqzPmlL+bUrQC9Jaz8le39jH7tjjfc36+v8sbPutfJwqvwBSKkCksed+XV767YZT4ocNFaqO2PuG7q1jSNMVa+zqS/TcDDeKKrcH3X1Xa99hUxcPuBAKjccV5lPGWnsNggNBmWATRXlOVvgYrFq3AyqpV36cpXIu15Tj+vUOkf405gsIEgS8Hkb6eLP69Uv48WsAJRhSRA2cFEwTkYos+pA5lHYEIWhtyNElh7YTa+E0BW7hFFZHzY7BaF7+3pIEiU5rEBCA5RjIi5QVuaI2XOdogNvdOS10Qe4igjMa5Lka3EQkRFfiYm3ZgBe0ClIQ4Iys9Z/0GLUghnH0/2kJFUHhXazFvmqC4gxlaHE4EpwwoA3jrTEmOUmAlLBRFb/k416eO7Du+LYq80CBd4eotWs1pCy7AFRaUwKrwd57/WYsUNtSqzdkfpdIK6xyx89fgCiun73XQhQnd1yF8TA60eBGWF25wlEWZhXPX1MopdWFcR/5vWgp6zT4hSSHAlPMWqESIaO++VhlKK8QFfjw6K9zyUXFfvOAWpRAVoMQWQj4iF9DG4SQFUSgVILbvrulb/DlK50jRqEGcRRMVx/NuXH8Zmn5swGgvLX0ZufLhHRw4v5bFPziArNxLPyer+8FqHTb0pa+n1RTEOUQFXlg7W6wLRS4COkQwRPQQB7kWtInBJQSuWGtFiEKt6FryFpX6EusRF5GQYX2sCM/g4x+QarVK/2Hwm8SbTzYSQEShtUEXvT2d87p2nqXeCFKa3Dp/bnEgDqUMThlyDMoEaEnReC1cGQ3au039DBZWmQjOed7Y18/nihCFlQewzyusUKC8A6kfJfUbhPiHXhzYjIiMUBKUS0A7Lz/EopQDm2IsVPOASmaouACtA1QcM75jO0QxTnzsJzcOpxym2DSzwOEiAEsnsJiBATbs3cvwrssQFKETnCgCKogKyLWPZ1mBRn2AgzffRK1WQWnYsXOczZvgyis3oE0bZToILbROCZSCrB+XA6MN4rwrcMVTCN6icSFahV54WhDn7RMlIcoKmhyKhBBr+3OdM9SsMDHaxGZCYCLvBiZARCOiUTogtw6UIDoDlYJKCIOUXZdtYGyswthIhFarDRzWqm/aCrFTRFYVK3GNxawNmYAOK2zetoPNG8cK12Cx6aq+EuaVpMA5YgsRuhCuq9arXyc545ssA4Mdtu8YIK7koNMiRhmgXIxWXkAaFaP6LlUBXVj3Q0MVNm5oeC+FOLRyQIJWOSNDQ1xz1ZVs2jiAVmmx7kFUhpgEq1LCKGR0uEGsQHKFdiGBiRDrlatAVcBGa6xQAZWiTJttlw6wcZtmzzXD6MKaFnHFNRaxUgehUwRSrMeCFhNNoVAVsVjx+5TWptiv3Mr+5QqFWGFw1qs0fXrNLVs3c/DgTYyNj2ILV/3ExARbN29aUdQ3bt7K9TcdZNe2TUTkaKO47b3vY3hkAkXu04yUYPsuinVULlji4uCiOOzXUx1pYdwAnKNtvlUoQJww0BjkF+67j8985i/5/X/9bxkfHycIA2yeYW1OGEd02m2MwlP15ZYgiGgnGQduPshtB6+nEnktOc0ylDY4UeS5YHS0Mt5qtYa17jy8uIK1OUpr8jyjUok9l61z3hIVyHOfJfu+97+P8fEJjDbEUUQYGJRzBNYhVsiVoqMNSwp6YYiEEVG1jkRVMhNjJaTVyWhbx+i2bbz3rjsxlZi4UqXjoG0M3SBARTU6Vqht3cKVBw8iYYWoGpJmjtOLLW678y7qzSFyJ/SMoZ0ZesrQUw4baFrdDnffcw8bNm6k1V4mDA133fFjHLzpan75l34OE4CohDs/9C7uuef9hCajUYvRukslcth0mShwhDpnqBkThzl5ukCWdFAuQ/IERUpkLFHgwGUol1OLDbFxBNoLDNVXviTnqisv45aD+xmoBvQ6S2hy0u4y1dgQaofkPbRYjGYl7qiwxLHh3p+8h+v2XcHVV+0iCAv3Z7H8NBA4RcUpwsQRdPOV9QXgxHslqrUB0txyz0d+gjve9x4kTzBGk2XZmjiiV5eiTKj2HKaXg3hSf1skG/kOOsLBg9ewcWOTe+6+g9GROqYf1RONkoBet4W4DOdSTOAIAofNe1jXJa4orrxyG+97740EOqNZqxAHEIeC0Y7OcpuNE+PsvWIL0KVSMYSRAtWjm8yjg4yh0TqXbB2HbIFY5USBotdZBBIio3BJBvbcHAGtQUj50Iffx8F3XM1/9Su/QBSFCF74iXNogcBpKgQEqSWyjrCfwets4QXwnqHcWuJqBaVUUUtuyLKMMPRc0Gma4QpFJM+l8PQEOCdcfvku0jSh222jC+X3x977Xu6843YUQrMxxPziMiqq8rGP3IHO2uRph8nJOX7mv/hZ4tA7/RzgVEie5/R6vTVWf4m3Ay64jrQvrNZLjLRPEtFPnPDW3YUd05iArVu20W51uPfej+FshjGK7du3MD09RS8zbNy8hbmzp6lEhomNG2n3LKfnlrjk0l3svfIKqosxZ6bOcvTMPMoZtl9yKeJy5qbO0msvs2PHJWRZTpIkjI+Nc+r0qTeMIQhCNm7cSL0+wNTUJEkyx/jEBubn56kP1BgYHCbt9dh9+V4iE/DiC88zdfYkWZISBoX1ZiokUYSqNag0h4h0QGtmFtvtIoMNqpWIYaNJpqfQccyitXz+//0CabuDzSx6dAtRs0otiumcmqK+eSMTV1/DwMQGwtemMWdeQmyVmeWUaHiErnXkWjNw6Q6yzgBRlDE/fZpeL2Hn5bvYtXc3v/Hrv+6bp7ucmak55iZ7nD62CLZCtWrYt38vh55+jvGxKmdOTIJe160AACAASURBVDEwZhkerIFUmF9Ypt1qU69pmo2AMBxibkbR63bZsGmEIBSWlxZZXGwxMbGR2Zkl8rTH2PgQkzMtrM0wUR1nE0wgWNdBqTpiF9m7extnzp6hXtGMjdfIsozZmTlQ0M006Bj/CGUkvS5nTk8zMz2HlhCXv27RWSEUReQUGxuDJK02HXqs6LJFO8JOt0ut0eSLX/oS2YlvEgeKJE2JoiqptWu8KkLTRGxqjnBsfoq2QKqkCBlAaBXGwfx0ysJsytnTiyS9VRe4TzbKGGgqnMvYsGEIrYWFpXly16M+UGV4OGbbtgGsnUe7LpVoiOH6EMvdjPmFNoYGi7MzbNyaYsKMbneJKAzZtn0UZZqcODuLlZTR0YDLLx1hoR1zanqBSi2jXjPEStOxgg0MCam3SAvvgpWAyTPLTE61OfbaNE76pUaFN0IpdO6o6ojR4VFadpaFdhsVaJwIubMoE+B0gNEhg4PDNBp1Wq0Wp0+fYvPmzYjA0NAQi4sLLC4sU6kMsG3bNpaXF5iaPkOaegt4bm6GJOkiUmF8YoKHH36YbnuZPM/o2jaZtkzOzBG6IWra0VLwwksv8Y4D+9m7Zw9PP/EsrhYxNDJBrHrMz81jnSXL8lKYvk1gPvWpT33qrfxwbm6OT3/6j9HaxyOMMeR5/p1/+B0QhuFqPPMtSmfvwlFEUVxk6V4YnGgajTrXXHMte/fsZW5ulm67zX3/8BfptrvkueUf/6N/wmPfeIyPfOQjTExMUImrnJ2eYcPWHRy47mrGq5bMwqmzs+y9ej/X3bCP8bEJrtx7BWdOT/Gpf/bfcfDgLQwPD/HO297J008/VYzdbx5GG66/4QA3XH89g4Mj3HTTAY4eO8Z99/0iTz3xDa68Zj+333EnZ06d5ODBg0WzNd+JpdtueW2aiJ4KcbUmN3zgTsa2bWV403YazWGOHT3NLXd/mOp4k8t27iCu15labnHJlVdx4/X7OfPSS7jMccMddzOyfRuV5hAbNmxluZcysncvQyPjZB1LZeYU3WWhV69zxY3Xcfgb3yB3Obd9/GMMjW9jw6ZxBhpVZqYmue7aa0g6HV489AJK++41J4+e4OyJKb7x+GG6qWPnZZsQadFpLaKdZXFukXe+bx9XXrGLoZERLtk8Qau7wH/9T+8jSZe5+qq9nDw+SaMZcdllm9iyZYRrr93NyRPH+Og9H+G1V19m965tvOtdt/Hs8y9hCXBolMoR22HXzg1s3zrOho1jDA7WWVqc5ZaDNzA+0eSyS7dQq0VMT52lOjDC4OAGorBC1ktQynHk5ZeYPDPF/OwSaQZOh6sWqRUaJmZQDDuHNhD0chYi593zgBTlG9qEjI5N8Pd/6qdp2hZHjrwMQUTigCAG8bWjFaPZpKvsGd3CwuICaaDoaYczXpAGThGIYnJ6nk4r58grJ+i2Mx/nXCk7caBbbN06zo5LNrJr1xYuvXQjx4+9wm233cjY+BBbNjdQDl4+dJz9+65nYmKQ6667gqOvHSXtGrZunqA53OGlw6dQQY2rr9rD5i3D3Hjj1fSyhOVOzjtv2EFVCQduvJlTk6dY7i5w1VW7uGrvXo68eBRfvtNPHdIUbeA5fuwEZ05N8cTjz9Lr5qB8/FspTahCTCqMmjqXjm6iFgi9bhunFZlSSBEXNSpgaHiY/fuuYdPGzdxxx+288MIhfvzHP8L+fdewbfsObrv1Vl449BI/9VM/w9hwkyuv2Y9WjlOnTrFl+zaSdpvpuRmUqrFtyxbe+553MTE+xuHDh0kyQUd1Bkc3cuCSOk8/8QQdU6VHTMUYhgcMk6enSY3h9g/9BLt3buWF559fiXefmwvx+uSzN2Lz5q3cfvsd1Ov1C97XSlw8XJBF2ic46Mcc1gN8skk/BX41seCtQkTA5Zw6cZJP/4f/wM033cwv3vdL/Mmf/Amf+8wXefd73s1Y9Sm+8lf/D8s5vDbd4s533sSpI8/zwtOP8sLTj7Nt2zjN9qt8+UvPkOmQm26+lU07IevVuXTr5Tz+2Ela7SV6vZRjx15l0+YJojggX0g80b4IeU9zyc4r+bsHv8rh46f5wAfey6bNm6kPNtHSA63ZODjM8cOHeP6lwzz5tb/kxNQCPRsxIEIqMbHqYANLUw1BNMQj9/8hevA6btm3E+JBjM048egDHGsnXLJtN+lsl4cfeZw9u/eQGkNvwJCHluNPP8OpyRPse+eP0Tn+GsdeGKK+ZY5nvv4wDekxGFRRqkuqHDarkLsm1Cocf+hrdBLDO9/9Lp554hnigTqdpE1uU5QLiIM6S21Q2iJ2iigK2XP5EM8//SQjzTH2H7iUI6+8jAqEb3z9SV6c0uzfNEAaV2jEwlcffJrRxk4yF1GpZ+y4YpRms46hSp4rzkyeZtcV4+zauZWvfOWL5HmK0gMgMSIWow2onOsP7OHzn/8CDz/0HEPNcW45eIDTk4dpNgcYGRrmqUdfY8OWBhu2DrK00OK5xQWUBCx0DMgA5AatfCZtkciKUYZqIuyNRrmqXSXrNpluambbM7hQ0EbRE0uO5tipaV4+Ns1oFFPVmiXlyLRCtBCJIkphXNe5Sg2za0GTmGEOZYukYmkVictOCVYg7SkgJk0En+WsztmrbR4QBoYr9m5mbDCg05lnYkhz2c5t/NH/+XmwV7BhdAR0zvhElR2XbmJgUGh81dJZaIEkCKZIKO5Sr1uuvWI7mzePcPLYMDOTJzjxyhm+8ZXD3HXvZjZsrXH87CDffPYsz3MWq6oobUAKhXelZlTTaYtPYOo4nNZEuSZ0ip7WZEpRsSG7wyGuW6iRuZiGa/C0XWQpEowYImdotTowNs7Oy3YyNraNHVtHiSp1GsOjfOOh+3ny2aO868Y95CYmcz3+v8/+IdnwdWyIpzFiSGtN4rQLtgLEvPjSEYIK7N65BWcTdKogAlEh2kSkmSUrEq2yPEPFfh/SwN/89V8xFCcol6MxOKd80uI5hC/rxLVX4k3hbZe123c3rzR6vkCfsyp8w0FgqFVrPPPM01y+axcbN27igQce4KabD7J16zb+4q/+im7H8ORTz3D0hSc5cMUOrti7h5NPvIxylubgCI2hUVpJztTkWb769S+zNA9L8z1UPkEQGMCxtLxctCILqdcH2LNnL6+99irLcz3yLOeyXbvoYWg2mhx97WV63S47d+5ky6ZN5NbHa9vtFgduvJnOI08w28qpppbm0Dhbx2s8+tpr5GlCpBVDtQrBcIPO0ixV7WjPzUGS4ZKEV18+TLM2RjwxQrNaoxZXWJqbI3QZJk0waY+q0QSSY9stBuONbNs8TrKUkU53GBveSKwcG0ZHmJlJUb0uJF2CvEojqqGtY2Zykl3XXkW9VidJcqyzaBWiTEirNU/UiNlxyeXs2rmbZnWYiQ11/vJzj9LrCc6GpLnlhReOEG4fIw6bZJnm9OlZlIE7b3sHzz37PAsLM7zj5neBDvj6w3/Hx37y/Rx95SgnTk6BHvTNDQLB5jnKGKwNefLJl9h//UEWFyOOvXaWFw4d4fGn/pal5R7dZahUxnj1yHFeOXoE0MRRhTzru03VSkmOdqCdwhkBo2llOc/PniLaGDLfmWRqJiGIApykWOsIogBR0KhHNGoVTL1O3BwkW+qCdohYQKOMZq69xKG8h2wIeHb+FAuNABtqn8xWlN/0KxuLlXze9V1vNrjuwE08/PBDRBquvWYPy+2UXuLYuGUb9fowJqiz//qbaA6P86d//hnef/tBuj1Lc3CU5uAw1UqXRn2IqDbKXXf9Pf7o3/8O116zG00FoyKyPCAlJBMNOqRSHaBaM4wONTn2yllc5r71TiR9K9X5CLFSYBSZUSQDIS8uTlMLItrpHC+0p1gajHCVEJUpXJITGs373vteFhcX+dKXHuSjf+92n6iX58zOzNBLEh75xmPY6mZa3Q7OWs5OnqVtj5HZAVqttk9ycz6zeXBokEZziNGJDQwND5GlhtmuI88ywkqFLNdUBiokuWVkZBjXmcSKo5dkXLptjJ0bGvzdI4/6HIooxvdcWB+JmiXeOi7Mtft//3HRBFsVrt0Lb4B9sVy7Sl08124U+sSeHTt2MjExzvHjx3nuuedwzrFnz24qITz6xONIUGXjps2MDdWxWZdDL71M4jRz83OMVCPCqMnc/CJT05Ns2DxIoz5CHFdYnG+z3JrmxUOHOHniFJOTU5w+dRqlNVddeTUzM9MkvYzp2VmGBpvElQqLi3MceeUVZudmaTbqtLsprxw+zKlTJ5hfWGK0OYAOY2ZnF0m6ywyOjLH9ks0cOXmGSEVcdu0+ktmj5C5k+uhLuFYXHeQsTZ7C9RICZagPDDE4MU57bpYg6bA4N4txmsWzZ8k6bURBMj3NXK9DXTu0E5YXJhkdaFLbOMbs4jzB3DJpa5FEJSwcPU7asdhej7OvvUprdoY7P/gBFubnODs5hRNQ2iDOUanG1CoDLMzP8pUv/S0PPvAYZ05N0+saFjvLzJ5tsZQYKg56SpBOwouvnsVmASKKNOsRxwajDVNnF5ibaZGmKXuv2MWh519jYc5ixfiyEu3I8x7YHC2as2dm+MpXH2Ri46VMTS0yPTfDwGCDWn2ALKswNdMjCEM/XgKshVUCgSKjtMgqFeVLX0RDqiGLA6boMWUy8jAiw3lZEfgSKmsdu3ZcRqCh152nm+UsLHcAg3K+LtJJhgSOdginpct0mNOJPdOUUNSVFlSJ7js8Qt20hbOW0MQYHXP69CwnTy/QSR1RtU6vl3LqxCwvv3KGNIeB5gBT0zPMzbWJ4mGGhkaZm5vE6TqnzyzQXlqmGkf0ujknT85xdrpDt9Oj3XF0Xcrp6Vm6Xc3Q0CAjQ0PMTM55MfJtQoX9SzBFbWiuITGQGCELYDbrclovMl83LMcKFwS4bkpVhyilmW8tIS6nXm1w/OgRpmZmWV5aYursCRaXeyiXkBPjXMaJw4fIg0EiaWPiGpsuvZR8boq5pR5hUGVi4zjNwTqd1hK9VpduN6WXCiMbJrh62xCPPfY4PRMzPLaJu27/AF/9j1+g0+lBFHPzzbfw65/4FT7zmc96AdpvbbhSs1y6dn9YoeQt1q288srL3PWhD2KMRmtDGIZvok3Zt0a1WiVJEpy1b0mQ9ktxjNE0Gg2Wl1sXWJojOKcIAp/pV6vV6fW6NJtNbrv1nezYcQlf/Is/ZXJqmlZR+xhKgsm6YCJaEhEEAVXbRusGuQMrCWEtpddNCUwFcTU0Xe+Sc4619aT9ZARFiLW+VCaIY/I08SUYymGQosbNgFicMagsgcCXbWjn60y1TumqGoPVBtd98EP87Rf+iA4NKjbBZCFpKMTaEjpLnkFu6vTCGLEJNUkxkmMlJNCQJz2yWoU4yWnVKoRJFxWEGOkRZprFSkAWx4wtWVSe0R6ASpoDdayDSDsCl3Hpzm185J6P8gf/xx8wv7QEKvAprBTJJdIlDkKcVZ7kwAXYoEPNNJnPQwbFsWwSBmxGT0UYqRfCq4sxbVAWmwnjo5u49dYbUbrDV7/8GN2WIRNHrnwpizG+DtM4sC4jqse0WhlhWEEkxalOQT1XA2niJEEbijKKtQlt3kXX5/2VggYRrcnEoQOzUjdbzSKU9tzCVjKcOLQJQQfeJ6x6/jmwEJuqb4eHQ4znSc6Ur1WmsD61gKGgrfwuV7cNeoh1VHQMTrC5pVaPaWcdCMGlDm0jlIp9+EZ30SYjz3JCM4zLHHHQJVUVMjFgMyo6QZNjVUxKFaMFmwo6EiwOkQicL1cJVAQo7Ldh9xIEq4XI+kzdTCva2mEDg7FQcQGiO6RasBq01QxYQ2gVmQi9AAIjGBehVI5zCicUz1yFIEhJpYYlZyKw/P/svXmwHMd95/nJzKrqfvcN4OEBIO4bBAHwAAEe4CWSom6JEqXxWvZ4J9Ye2bGxsY6YmfBO2OHZ2J3ZXR+76/Cx4/AljWzZlmiZti4eoiQSJEGQAon7vm/g4eHhHd1dlfnbPzKrXwMELzzYguj6KJ7Y6K6uyjo6f/n7Zf6+v8FaC2W5yLiDD3/+Z1jQFvP0c6+wZ+8RMmMRY9GkRBa0RNy0YDlrH3qYm0qX+L3f+V3GknY+/8X/gTdef5UdP34Zlzl6BmbyM//dz3Fs31b+7ptP4Zwmc4LWPle6Pmf9LokUt665g9/+7d9lypQp7/EOF/xzMClD+pGPPlJPTI7jiGp18t7fZA2px4/s8qRrEVfP+crzyK5lf41orWlvb6dWq1Edu+gXTBDjlMJIFlQ3qb8Xu8wnnzsNOkXIQGeIxDgMEXnqzhVzuhJ6RYmYkMLLF6iIz1utK87keXOunvytxGGVwuB1ZVPVSoTDlttRldNYrYktKGdwJsKREjsfQqypEqKSYKwr/n3xsoexhUoEShSVyFLKFJlRGElRTjMea6zWdFYgdsJYbImdhPlIjcLW82qTckwlDYIVolFivOCBCtJzQYJO4VV6nK5hXETVGEoZ1KKUcqaoaY2SfIFPhqiq15sVSKKY5taYsfFBsloCriXowFovoCD+XIxEvkvTDichRxcJAgHg1YwSco1Vf7/kCq/CiwZYpTEu6CdJUNHVQhbmMUtZHETeHV63dwIlhmrkU1Uiq4mtD9Q67UiNJdMOh0aLCakgBM1nXdfK9SIZ7/xkW1MD0WgXo1wU8lVTnE5xuoqWEsr6XFN/nl7/GBRIjHaKSGXU0FhlMAixS1FicTqipuOgKZ16gQ0USmVBM1dhRLyW1DsUnheEWiTEVlGy/jp6mUr/uXHaazMrr7VsnL9mAFUN1UQRiSXKdEhZMmGvGYoYIcWqBKeE1qxGTTcRSY2azjDN3fTFGeOjjrGqI9NgtZf7i63Xoo6b29GtLURjZ6iMjlCjTKmtg8roKEoywKGTFprKMZWL58O5RkEAUheG9APAB26O1DPh0TUaplqtRqlUvub9NeKcY2hoKPwrClu5IAqvsOE73lgorPa6m0qJF7iWUpBSM6At4rxU21vmdHPvVHkRcoshCpVB/P4hw2CoIWiclw8gVQlGUjSOmi5jnB/kGGdApajxUYwYtKr4zhKFto7UqKD66lAqI7a+87faooLWqlVCjMG4jFTHJC4jdgnW2CDv51eWmpB0j/gKMT41wwUZ9iAkp4Txaq0egvRGxeCDmBbxQwxEWy9Bp2qIGKwyaKpYVUaJYFUSOvg0JOwLkIRxiKOWOdKLY6HjjOrC+Qp8/FOFu1UXGfHzcrmgq1fxCc+CysKwJU//euvATMjDuqoudK8RTKiU44115s8NCWL0E3VSvAZtiNXiReUVQW8nVF9JnB/QeKGpCQWl/NjvBeUMSsL1ztWTQpUb7XKRBO1FOxRM6OCGZ1MFhSPt54ZFQAhCGHnFBDGgR1EuQRGBGkdLEnSe03d1n71375+MVEPkfAWi2OWfW1wwzI3eeBYWKHsBCv9cO1QYcAhOa7QTrNb+MwWZStCSIRKBqlEbH+Pc6DiRi1Ak4X7l2sD+VaUySlobJZYMo2IUmurosN9WGf9rSi0j6RhRSBcsZkU/WEwqiWmisPfkF/X8U9HX10d/v88Za2pqugYnNx8pvv2frzzhuzkVJLV9JQiNxnnptqCEo1SGUjYYL40fHb/7imengsehvGFQofP182A6VJ/wnxvxBhel0OKwytS/4zV2HbGzaIkw4oXWnco1cFWQAHQ4Zb1ijPPlsRyQKSE1YJU/N6sVRmzYr18t6ZTGiCLOQ5HK68BalXtLrl5dxL/XWBIt14TVwZj4R1TyKiI6DR2+oFQVp8UL4xPhZelqOF1BVBa+GwdjrBGJcJT8ldA1JnRngwA9Gh9Sbpzrz9tj/HYKvDh92rBt4/MAoOuekQKvYxz0iP39yT1I77l5AffgndT/fKm6XA7QD2Z8nqiWCONMvZqPxt8Pfwz/ezTO/70bWkIlFxG8V5zhixkotDPh+HkpsyxYqYiJMbj4Zz1MM+T3TsTLB4r210dTDZrABk3qhfXFBBH8dyex/teSKT/X7LSXL1TKhfJt+RRI8Fi1w4bPS9ah3ESRAJXLRypvXK3SoUqTwhFjQiUXX7LPP6d+IJQPJr0JzZWCjTi0ZFhiMuXf0+K9Voe/LwjoG0T9reD6cx0MKeQLLG5E2tpa+dSnPsWcOXOw1v2TSBlKkCHLSzuB//FJ8FYUoZPBh3kQBy6vbZmLc787uRx43QOacF/qL/O1mqJyzdlGP2dCg9fIRBhJiIIx89t5FRbfKWpx9c7Dlzjziz2c8hVKsuBlqiDDlgvS5/VPJdd9JS+F5ut2ivIVVhpLUkE+Vs//gnSiCiW1cD60SBBTJ8WFa5pX0/Gyfak/Rv3q59J5GlzkfUCVhnuivEcWStnlBmGixqkNouuEOVJ/H1VDiS/qod2JZ0vjPaZ8wVFqhFoUFhyFuTylQgm3K5DQyUdO1UOz9UVLoR2R9d6iVULN+H2mQdkICV7be1j7p0MRAW9cUpSqocjCMxJquwZd4XrhgHqt18Zz9hMZDjtx98Iz72sG1XylmOCZq/xu138nb48CSpkfVDgNaSRUo4kFR9VIqBihZhQ1A7XwOjP+tpQsRGFAUn/GJBfVD9NA5DWD/VRC7v9rafz9TNyrxjqx/vxcGBT6fKe80uvEdorG56Pgg8Uk80jzMNiNo7V7JQcOH+f4yTO0NiWobBSTlMgwiERh7urtKn3kvLuRy42nL5uWv+fq74HXBPXekfZVVUwt/EBtKJ79bsdwwfP0/yX89J1SaDKcMj7gJI5MGSKpBk9NE7s0eGV4Q0Ne9syhpCkEvHwn7Pfqw6na+ZG9U34eSsSfh58h9B5f4ixIQmYcWny90YnyYN4s+sowodhzQ695Zck5xURFET+XFZFXCUGMN1qhmol/r+w7LDHBS1QoicL98N6lqhs41zCwUd4DlXwgMVFH5PKaoYqJWrFCXklG1UOuVw4gG+e282NxWQm9vDt1SoIX/NZBqMr3rSZk7aVhH+Si8EwM2PIIc73LviJf9O3w4e2802+4N3n4UQjTCyEhFsVERR1/Nk75ourGNTyX2n+uXahvK63hfGqIlELbsolzfac2Ep5N8V62P9+JQaIKXvnECuUQJg/3Mq+Ek3/ugvdqxF8nE54X4wRUFjSrLcaVwtENmZ7wnI2T+uDS6twg+8iMjxD5kK5viQ3ZUNb/9pmoLysNg8WJdhf8NDLJOdLGG39jGlJREeiIjtZWmssR41mKaBPmrnJD+m57eecN8p9YY63BK9/zxiUfp2rQ+cIsGxbUvFsLJBiby2saSjCejvyH60PNBr9/pzSRpEheLisYHKvyzjOpd4xW5Z24Xw1juHxBR34e2lLvGHz4NsLqqxnS0MbgSWl5pw5DXeY5+4nJsMAKJl7nZcsAv+gH/JxqCOUGL8rTGG7ND+Pq20281+hZNd6LRiOXbxOM8LswUVA93Pur/jzeuaB741fUZe9e/sxebZXuu6W9TLTTNRxn4nyFxkiBuqL9jZ6Zf2j8NEODVx++oMNAxElzaGgGkoTd5i7zuzc2y5/Dyxv2tt/UDdvk35WGcwPfHG8A/Z5MCG+7UA1I5c+aaB+Wp6ENYS8T72t0Pq2jGn732LCp/7289TG4+l0u+Onius2R3qgPgbOWHTt2sGDhAhYvXuyrWjR2jjdmswsKCgoKfkq4TnOk3DCi9VeiNCxbtpTXX9/Mtq07JtRnJoJsP9kGFhQUFBT8VHMd6pF6rs8UqWC9TIxPWr8O+FqkGUZHZJkN4afGxQOFIS0oKCgouHaugyFVdSGByaJC/p9S+rqVF5o+vZ+OznaGLw0Tx4mfu7hsAcmNObdbUFBQUPDTwXWsRzr52K4IWGtDxZbr4+WOjo7wrW/9I5dOn6AyXsWUYjB5WPdtV4EUFBQUFBS8Jya5ajfkYKnrVdhb6rmeWqu3yuVdA4MXzqPE0SSOUqmM03lod2IRekFBQUFBwbUyycVG9VeTPPxE6oFWiubmFgYGZtHa1jyZ5tWPoBReLLyecxdy527g1cYFBQUFBT8dTMqQThT2vsY5Upfnk6WAIK6EiNDS3MFtazZw112riSITEtLlmuZNjQhGFFWryHSMRVCkGLEgBkf8/ttdUFBQUFAQuC4req5XHqlWvmL8mTNn2LZ1F61trWRZhhMJ1Vuyd99JQUFBQUHBPyOTDO1OyFtdjzlS5xzOV7xlfHycUrmJ/v7+y0qgFRQUFBQU3EhMziPNldpErssK23xhURxHjI6MYjPL1KlT64uORIqcz4KCgoKCG4vJGdIQ0vWe5HsoNfEe9mdMxMjIKO3t7aRpjW3bt11RZaagoKCgoODGYdKFvX3qy/USUFA4Z2lubiIpJajGLJWCgoKCgoIbkElav1BN4XoZOxGctfT09LBmzWqOHTuOvR6ebkFBQUFBwT8Rk/ZIRQTnXNDInTzaaC5evMizzz7HuYtbENdEEdItKCgoKLhRmaTWri/o7bSmkgmZE6I4wmCJXe3dd6Ar/r+SAAp0BRFIszHODu5BbDOFES0oKCgouJG5PsrwQE9PD5/+9KdZuGAhWheTmwUFBQUF/zK4boZ0ZGSEN994k8985tO0trQWZrSgoKCg4F8E182Q1mpVduzaQbVWI80y4njS068FBQUFBQU3PNfNkCo0TeUm9u3dy7333EsUFYa0oKCgoOCDz3UzpE4cThzd3T0cPXaEtJZer10XFBQUFBTcsFw3QwoQRzF9fb0cOXLk2qrBFBQUFBQU/JRx/UK7CpqbmomTGFC4wpAWFBQUFPwLYJITmd4OGxFmzJjBr/zKr/Dss89waayCnbzWQ0FBQUFBwQ3PdbN2R48e4d//+3+HtZYoilBaXz/pwIKCgoKCghuU6xbazUXro8hcN7nAgoKCgoKCG53rGH8VsiwL1WAUSpmifmhBQUFBwQee62ZIRSCK4mA8FdbaeqHugoKCgoKCDyrXbEi7u3v4lV/+H69nWwoKCgoK3oH+6QO01qZnSAAAIABJREFUtLT8pJtRcAVKioTPgoKCgoKCa+a6CjIUFBQUFBT8S6MwpAUFBQUFBZOgMKQFBQUFBQWToDCkBQUFBQUFk6AwpAUFBQUFBZOgMKQFBQUFBQWToDCkBQUFBQUFk6AwpAUFBQUFBZOgMKQFBQUFBQWToDCkBQUFBQUFk+CatXYvnB/km3/5Dc5fukQ1q+CUBbxIvVYOnEahsVhEabSAwuEwCAqUBeVQolGiAIco8Z8RobD+tUQYUkQ7HAojIGJwSjA4BMGJRuMQRdh3DGIBi0KhEJSAU+D1EEOFGq0wcUQURSxbtozRi5fYs3NXfXQh/ptIfd9gwh6cUmjJX3vRfgWIAqNinAtHkgwFKOPLy+Uy/k6pcL0E0Cgd0dLSzMqF8zk1eIaDh4+irQCCUxonxl8TJf57AvnZAGitEPGtzT/SWiGAu1IFUiCKIpxzxFHM3Llz6OrsYtOrm3A2v4/1PYV7AijfnvphlQLRDVvIxAHCtbiccM5Ko8WBOJzSaAQtQqZ0uFcSrk/jOC/sW/I7WG/VZVu8d71LBcqQ32VtNM5ZcsVM1bAjpRRGG1Kbvee9/1Nzzz33cO+99/6km1FQUMAktHb3797LFx7+LPtOHedSdRirajiJMNqhlUWsARSiLY4S2jkUKZYEwYCugcpQLsKIBmo4BQ4NlFGqFrrKMomMYZXFak1iBScJmYGEGs4JGTFaUhyA1qDKIBlIDYAoGLkMkGDAdBQxb/ECfvbnvkh3Tzdbt2zha3/+FUYuXCRWikjFpGJJBQQHWrBKkThBEDINUagSl2kQF8yiBu0inBgASqoGCFZprHN102C1hmDko6SFOctu5gtPfJbqwT185e/+hnMjY7jhMcCRKY2VElALPbwOBmXCcClFMKSglUJrBU6wvvWXI9449PT08LnHP8uKFSv4oz/8Q3bu2IG1GSLevLjwTcGEL7n69/3ToyCcp6qbsYl2XWZI81EGGpTBOIvCkmlDJA4jQlVrtASjGgwuoqhbTBHAkRvuxr+JT94jSqNNE1o5bOavq4jDGD8g0YBSYfAj/lztDSRL/eu//uv8xm/8xk+6GQUFBUyqjJqiXGoi0jFaKZyBxMQocYgTIhPhHKRiCe6R7+kmesX6nuQy7yL3ckBphTjxBsLU3Ulfnk18N68U4K7s4OQd/hW8razGvh07+I//4T8AztdPrWXEeA+uKjXvLUXeu81sGjrbhlO4kmBDnEAU+VJy2hiszVAijZtMOFgK0mqFPVu38r+++QatbpxKrMhQmHc4i7ccWoQoihBn0VrXvdO3QylvMP7gD/8Aow0oiLTGZVf7zhW+3lvO//LPpfFF4+0W5W+YyiZGHcqGL/ioxMQBctPoPd76RVMTHrFccYj3hYDLMhyOKI4QLM4KztWdXkQsWmnAUdR2KCgoeDuu2ZCKCNZarFiMjnC6hnMOkYxyrKhVLAqN1gorof8k7yKD7yCE8OGEkfG9oveolFZokxCTkpICGuUEZSKSyIdZrfUmR7mGzplgvJVBib2i5QqtFBEapyCzzvfVzmGMASvBIwPRBl2K0FbhXIarG/zLBwN5Z553/7mRiiONjjRxuURWq2FracPZuuBxabQSxGgipVFVUFbQcYL3ofMvuLphfKcuXSlNFMUYo1HOMlqtTViGBowxDA4OEhsfrBYnpFl6lUFHbtDeet7eM7RXuRpvh/iQuwhKDBrlDWO4Dug0xMlNOPdw7Mb2y2X/ufLt906ITKh67VzBBwn84E2jsFZw4oiUxhZF6gsKCt6Ga15sJCI4EbQ2dHZ1oU2MiNDa2kKpVMaEDt05QSmNVnrCc1Aw0fVd2UmHZolCKc2d69fx2GOP0NbaXN9Uac2Djz7Khx6+izg2SD2GGMyZBE9GwISw7oQ5VWgd0WQ02vn5OD/1J4jz5yRK47SmuaONT33ucTZs2EApLmG0QSmNqhuYyzvw+mkpcC5j2eKF/E//86/ya7/2vzC9v3/CCKtw2UOIVYvQUirx2Mc+xuzZM1FRQmalPkc5cZ3e2cO01tLb28sXvvB5/tNv/iYb7rvPDw6uQpqmKKX8XK74cHAUxwiaiZlWTf0RyUOzosNlVn6gRO75+r/GwRBXFHbXYe/1k7/syumJiAMT85TmijBu497yP8GEa/o+fFOZaHNraxt9U6bQ0dFFU7kM+OuitUIpcIURLSgoeAeu2SM1JiJzQmtTO7/xv/9H/ujPf4/tW/fwS7/0bzh35hBf/crfk2WWuFRCR83YsbEw/ldoLWhjvIPixHtg2iDaYcV30EmiSbOMyBjKSQlrFSZJSCxU0oykVMJkJazVxOUyupbhnO/IjdaoKAbRRLVxMpQ/HoLSZbTSuLRCpBVoTc06lNJ+YKA0TnsjYJIYIoUTh7gwN6eCkdEao5Sf9zSKSCnvXCmImprJxsbYtnUruw4d5V898Vmam5JgX/wiF6MUSkdoHZG4GlEcMXVqH2dbysGs+AVRTq4yxxlQSgVD6Tt95xxnzpzhy1/+Cg9/6CG0VhitScP2Wmu09gbLWku5XCarpfVogTiHiRIy6+eWjY7RCkRSMmcBjTYRSoNSMTiNtuN+UEWjadR1I6qU934R0M4iziIC2vgBRGRijBLEZX7eEoXRICZCOUGs9eYytN0Bmc334R9f5/z901rqC4bya2OtvWpYVmmN0gajYz70oQ9x74a7OHv2FKdOHudv/uYbXLww7BekKbwHrdRVPfuCgoKCaw/t4l291tZ2xqsVOrra6Z4yFW0ihi+NoJRm1sxZLF25mJb2Xk4e2sMbm19mrBazaPl8Fi6Zgybh4L697Ny+g5tmzaPcZtixez9R3MPKJb3s27uHONKUSwmtra0sWbCI3qSJl17ZQlIqo3WJlvZ2br7lTkoywg82vopIxIa7b6NzykyqtSqbnn6KkZrjzg33UxsfpXPKTNJqyrbnn+L00DBOJBg1TWYdSht6enq4/c61NHe141zGmdOnwTnmzJ7NjClT2bL1TZJyzN23reWNLVuYPm82Az1TSHTEWK1C5/QZPP3UNxk5f4ZqrYZOEpxTPoJsIsrN7ay/dRmdvdNIJeLVZ55iXEGW1li44CYGFq/gQlV448Xvc/78YO4AhlCoxiqDUTB79myWL1tGuZywc+dOdu7cGeZIFUqDURFOhDjxRvzmm29m/vz5ZGnGK6+8wunTp1m1ehUD0wdobWnh/PnztHVN5dvf/nucS1l9y53MGJjK0PAZNm58hdHRjJtXrqalM6K3dxqVkRpbX/0Bp0+fBbxhz1dlC6CNoX9aP6tW3UJLSzPnjh/hjdc2USVi5fLFSFajf+Eaxi6e5ZUXnmNctbFy6XxiV2FgzkKGBs/zw+efR4BFixexZMlSrAhb3tzK/v0HWX7zSirVKnt376Gnp5sF8+fyxpYfMzo6yowZM1i3bh0bN27k2LFjbzGmfmDkSG3Kk09+gyf/7m/p6+3is5/9DH19vQwPXQqDE/FLwgobWlBQ8DZcex6peO8vKSUMDl6gVCqzbPkK3ty6lSiOaGlpoX9ggOMnjnPk6DHuXHcbixbcxJTePtbdeQdDQxd4482tHDt2HIVi1sy5LFy0kKSU0NzewW23raZcKodgneOWW1Zw57p1HDt5glqWkmUOAe574H5W3LKKQwcOkqXCohXLGR+5xJYtbzBj9lwevv9ukqTEhgcfZsXyFRw8eoKWrh5W37Ico3V9QY8TwZgIrTWjY2Ns276NLa+/RtTczMLFi4ijiJtmzmLpoqUkpYSWtjbuvvseurt7WH/33fR097BsyVJmDMxgyc03M3PWAEkEmAhROhhCMHFCz/SZlGLN9m3baeno5DOffIyShr7uLubOvYlTp8/S2dXDnWtvJYpM8GL9HKkOaTsDMwbYsGEDQxcvcuzYMe677z5mzpwJYc4vraVoo4mTBAGWLV/O3ffcw5YtW7h06RKf+9znaG9rZ/269bS1tbFk6VLmzZvPwiVLWbJiCbffuYrFi5fw+o+30N7WxEc+8hDlcjOr19zO8puXs/fAIVraOrh9zc2UIuM9NoJXagzaxDQ1tzJ9YAZHjx5j75693Ll2DQP9/Uzrm8aD99/FY4/dx4GDp1m2fCnzFw7Q1tLLE098gQ333sb2bdtYectKbrppFu3t7XR3dbJlyxZGR8d45OFHaGpuoqe3mxXLl6O1ZuHChcydO5darUYURXR3d7N48WLa29uv/uAHD9cYQ6lUYtasWcycOZM0zTh79rz3sp1fZBTH8RVh9oKCgoIJJrVqN44SopZW0jQjzRwD06fz0sbvc+vqxYDm2PHjzLipn3JTE+OVMVpbyiAjIJbenk5Ghx2jw0PUrEXryHsySjBRTJrWfLqFOJYuWcyCCH7///sLTu4/RCoxSmnuuON2Ll2q8du/9SfUhk+CKrN/737W3zyf/indjI6M0d/XhVaKoYujPP/8D9h54CRTp09nSmsL4DBakQHOOh+aNYaxsXEOHTqELhtmLJlLt03QyudeWpsBPqQ7OjaKiSMq1RqbXnkFs+Y2duzZTdecefT29rErVVDSZOLQKqSoOGH40iijl8r0Dwxg4oRpHZ0gwvlzZ3lp03O8tmuQOzumMaWjFRH8CmjJcM6hRVBOmDplKr29PRw+fJg4MvT29jJt2jROHD+OtRlxkmAzb1BBmDlzFqCYOmUqIsKqVav46le/SpqmvPTSS2RpyvDFYZZ09DOtfxpTprQwMjgatrdMH5hJR1sH584NcXTHNnbu3EtbqYt5fWVwllgraqK8p2ctSVMLaWo5feYcA9P7aW9tJokNrc0xZ44NkdbGefIb32TrPkNXi+PsufNYN8DRY8f5qz/7MoPDjlc2bUZHCcOjY1wYHqW7r5em5iZKpQSXZRzYs5e5D81mSl8PHR3t7N69C4A4jtm+fTs7d+5829Cunxt2aC10d3fzwAMPMHVKL4cPHyRJ4suec6AI7RYUFLwtkwrtZtYSK8X5wUF+/OMfs2vXEQwptTSjqbmVT3z8E5y7eBahxNQpU9iO5sLgBZ76+2+zdOUi1qy6jXlzZ/D0975H5iCKI6I4oqmplSSJibTC2Yxarcqps+eZPX8OI2fOc+FSDRFhZGSUs+eGmb1gHofePEvNaj72yU8zv1Ox5eB5enp7sMdO4MTglMY6QdCM1zLixPjc0kwQQ5i7NfVEfyc+7cbZDKNKKAdZrUZTUxOlOKHU1kZra6vPOVSKaqVCpA1iLdXMEWlDZAATkYmglZBECheXuPueDayaUWb34TN09/YhlYOIdWiFTx/CzwMmcQRKkWYOpf1coTgHkcE5R7ncRF9fL2Ojo2zevJmTJ08CgnMSxBaiINSgKJdKtLW10tvXS5ZmPPnkk1TGKwBkNqOpuZmhoYsoY6jZDCeO/v7pVCvjVCqDvPzSq2SZI45LiAiSOeI4oZRYtIKaFUSJTyNSmmqlSldvDw9+6GEqY6NoLG2trSTaEQG18QrVikXQPP+DjeAu0TN1JtZaKhWLtY7nf/BDtNYsWbqUhx5+mN27dtHV1U1zczMijgsXzjM2Osztt63BaM3JEyf8SnJrKZVKtLe3c/HiRSqVyluNqQrpVeI4d/YcX/6LLxPHhiee+Czz5s3h3Jnz9dXXtbSG1vqGyiMtKCi4cZhEaBdQip7ePpJSiZMnTnBw/4HgDcV0dnRQLpc5dfoUp86eQcShcLS1tjF1yhQuXBjk6LFjlJtKJKUSp06fYVp/P6vWrOHWO26nu7sXcRDHhr179vLyS5tZectq7rxzHR2dnYCwa/deXtz4Ch/72MdZt24tSZKwaNFizpw8wakTJ4iiBINgoghtYmxmQUegI78oBYUyoMNiTx/Ok4ZFUZrIGC9woBTDF4fp7u5m1arV3HHnnbR1tPuFLVqRRDFZmhGF8LCVjIFpU1i2fDnTB2awYP48Zs2aiWhFZ18vI5eGOX78BGlmQbwCk0ZIsypKaUTAhjbWFwkFFIrTp09z7PgxxsbGOHr0CAcPHuTs2bM0NzezbNky+vv7mTN3DkuXLUNrxYGD+7l06RLHjh/n+PHjbNu2jVqtSpZlNJWbqFarXsQhrFjdf+Agw5dGOHr0GMeOHuXQwUOMj1cRh8871QYnGqxDEULXWvmVvfhwdBIllJuaOXf2PMePn/BhaRGi2C9Ack6BVFE4msoxIlWSJMZayLIMrQ1xUqalvZ3xSo0TJ05xcXi4PnipjI9xcN8+PvTA/YyNDHPu3FmiKEIpxdy5c/nSl77E/Pnz3/YBFhGM1tw0ezbLVyxnxYpltLS0MDQ0TBSpuvHV2g/CCgoKCq6G+Y1rlEcZGrrIP3z9W1y4NMrpc6c4cvwgypQxyuf+7d1zmGqtyspVNxPHzWx++QXOnjhJuamP29etZtHSBZRLnfzoR89z+MgxxkYyWtoT5i2Yz+4dxzi4+8ccO3oUpRPGhgfZunMnx8+cYfa0AQaHLjGW1jh7+hjbt+7gwOGT3LxwDgeOnmLrtm3cvXo53TPn8ewzz1E9e4x9JwZJWto5vG8nI6MWZTQycpxTZwdJRXxqjDIYFZPLxWkFOlIsXLIIU8nYv3sv5y8O0d7Wxk1z57L70H4O7tnH4UOHsQqO7D+AZJZz589T05qjB3Yyb0Yfi+/YQFap0N9VRuuIbbsPc/rUIHeuXEDPtAFe37KTsRMH2HPwNKWmEoMnDjN4Sci0IR0/y+lT50ktOKxXaNIaHZcYuXSJkZERli5dwsIFC+nq6uTo0SO0tjRzzz1309HegbOOlvY29uzdy9EjR4mThJVhwVFzczO7d+0ijmLOnTtHlqWcOnmaC5dqnDlzhB3btzGtdy63r1lFf38baZZx+MhZoriJ80PHuDA4Qkk3IZXTnD5zjtQJ1oFTGmUiFJpqlhFpw8qbl1MqxezY8jqH9h1mvJYhIhw/cZJLNUFLRktzwmjF0VyOObh3L04cKopJ04xKWqOru5vly5YzOHieXbt2cuzYUVyWUS4lLF+6iFdf3czRYydCTqiiqamJOI45dOgQQ0NDb32Aw+rpcrnE+vXrWLnyZtrbWtm8eTP79+/HZrYeyW0qla+SY/uTZcOGDWzYsOEn3YyCggK4donA8bFxfvs3f4vf+t3fZzQdJmUMdBlchlYZ2AitDGIs1kUYHJGkWJrIcIhOUUGMwCfhK5xOEa3BtWEYBRxOEpp0lZpYMqUpi8KqEqkSIvGhSatbMOkoNooRBwmKTBkvDiEpmYoQ0TiV4YjR2hDZUawonxpZz0H06SItLc1M6euhrb2FW29fzY4tO9m06TUyEYxYRCkyo4mdQwGp1hhrMYBFk2lDbDQ6S6maGJwjdqlPZTEJCkNkxxEdIRhKUqUWlINjJdRc7MUgdA1nQwalykJ6jcLleax53qVSuKBoBD78q7T2akpxBCjEWRSCs+JDyFD3vh1gdIRSmtSB0l7FicwPLNApoFCqhKgI0RXEaYxKSGwNFxSHbC6vISB5Ckzw5CKjwGYoceRqvgI4U0JL5iMEOkbhUM5n/bqQi6rCYi1xzts/pUjimGlTp7JixQr6pvTyd09+k8ELF+qCGPXFTyFEf5VHH4K3L+IQHNrnuqC09nPmYX7UGEOWZTeUIS0kAgsKbhwmsdgIjFZeLN5lPrdQrO/oRFDBM3XW5weKCJkIlswn0AuIquFchBEFVL36mwWkhtO5jpAhcyFiqHzOoDgLxgspiAjiql6+Pqv5vNAGrd1xwLjUzy8KoCzOamp1XYDGVH+vpjB1Sh/33LWOUmw4tO8Ab7y5lVpQpdcS8kidXwjlRYeC/q6AVQ4cpC4X4k1BpJ7LqUKOpgVwGYosfGYRoCIKyEAc1k7kYiLaCwNcRRwgtxPOTXwm+WvnMCaq59fqoGac50aK+FCtC0JLihpi84tTC1dE+YVWLkVIweH1lKVCpkooJViXAg5jvGFyLvM5wuEYznrrba+0RrY6IZbhGpWfwv0QCYZu4lyNMbS1t7Nw8WI6urp4/gc/YnhkhCA4/A7G87Krhp9PnrhmbuJChi2CBlV244jVFxQU3HhMypDmI//YRDiVopTGKMFog62F+bKgl+tXPcLV5PXeorVb9wQ0zgYR8UhhQ5/nE/FTb9iMgvRKlZxcHuBqCkS5WHzeUaqJbZXCimXf/v3s378XEz5NXa7S44KijworinNvMX+dH+nKf1/eAuHy1r3dRLVSCmUMLsuCEL0Jq4bfB05wKheTMHWpO3EEPV5FkiTU0gzr3FUXpuaGyRtTV/d4cSDW1U9VnCDK7yOvfhNFGqUMaZpOiFhNEq01IyMjPP300xO6wkq9B+NZUFBQcP2ZVD1SY7zYueBXQIIis1ldPpAGVRgVJALzvFDfCze8ptHO+sU9Cujo7KC3pycIq2s0GqUU3T29dHd3hnJoUV2Vzsdq8+ChrpfDmuhic92gvC1Sd+nydlJXFPKKPX4RTq4P7MvDecNqAB0MiWq4nBICprlBv9KIhvJm9TXCVyGoMMRRRF9vL62trfU2vj+8kpHW3pjlnqpWEBkv95emaWjV2zQlDJhyQ2WiiDiUYXON59cwVoqioLNsxYdJ1TtJ6L8//MreCsaYepusvVJTuaCgoOCfh0kZ0sxaIh2xbt16erp7UMDSZUuZN38uxnhdWr/qNCLMmuE9uMYuNX/d0I3XdXkVN998M3ffvY6mcjl4gj5EuHb9eu64cxXa6Aad1fAnE/uMmPBR81NWSteVWhu797xGab4QxaH8FJ+4eu1RdZkpbDyFifeUNCrBcoWBCkZYNW7xVvKzaW9r49777mPBwgX1Nr4flPYrgMXBnDlzeeyxD/PAA/fT3d2NdeJl9JzPUX07SyoiWOfquZRGGxYtXsKaW2+lXCpDaOdd69fz0IMPsXz5UqIorq/kzWxWn2+8HohIWPXr7+qEVGJBQUHBPz+TMqS1WkZ7Wzc//wu/wPyF8+jo6uIzjz/OmltvCd6qF0KPk1Kwnb47VVphjMaYCKNCYWhlfLgwGBkTGTQZ5SShpbkZpQza+CLcOKGpuZlyUzOoyO/HeAMJGqMhMjGRifJKmkHX1mCiEsaU6v6jvwDeexTJy2V5TVltYkxcwiiNUXmuqa8IZ3Tiq4X4cuNo7SvWRMYQaV3fv9GaOIqIgveOUl6vVnkPWyn9tkZAGY3SmtaWlqC65A1GvqgoNyCN7111P0ozd+58PvWpz9DT08vyZcv4yEceo6lcqvvEJjLB876KLm1I/7HW4ZxjYMYAH/v4x3ngwYcol8u0trZxzz33cMstq+ib0ssDD9zPggXzQ15u2Ie+foY0pzGkW3ikBQUFPykmNUeKgnK5zPnz5+nu6aZnSoXBC0OMj4+jjWHBwkUsX7WUto6pDJ46yA+f/g7D4wm3rVvF/EWzwUXs2rGdN3/8BkuXrqS1M+blzT8mLk3j3rXz2LzpVR+C1IrOrk7uffhOyqnlue9vxEQxWEVv3xTu2vAo6dBxvvXMDyk1tfLwfeto65tBFMf84MmvcOriOJ/43BeojAyRtE/FOuHlb/8VR4+d9qehfNoGIX8zSRIWLV7MiuXL6ers5NShPbzwwx+QtHRy3923YjEknbOwo6d5+unvEbf2c+/aFbh0nJaOKaSVEb7+9W+gteaee+5l2vR+Wlrb+fb3vsvRI8f5xKc+xSubXuXQgYMsWDCfu29dwV9+7W8Zr9bCgqgQ+m1YOFNKEhYsWMAdd9zB7t272b59O4sWLWLp0qWUSiX279/PSy+9xPj4ODAxrynWEcUllq1YwZEjR/jHp77JkkUL+OUvfYkf/vAHHDh4hKamJn7+5/81mza/yqZNm96qSxtC9UpBX18fd911F0NDFxgfq+DE0dHZztSpU3nmmWc4c/Y0n/vcZ1i5cgWHDx9mZGTUh2Dd5SHuySAiIRw98e9ifrSgoOAnxaTnSJuamxkbGyOKElavXsPWbdsolco0N7WQZpZNm17lRz/8EVOn9jJv7gx6u7u55eab2b9vL9/+9vfYtWsX1jq6Onrp7evz2qfNbdw0awZRZNBKaCqX2HDvXTQ3NbPp1VcZGR0jTS1tHe08+uFHqIxX2LRpE2nq6OjqZuf27Tz9ne8yXk3ZcNdaImOYPW8hWhteeGEjo5Uay5cswmhFFKqC5eHgKIoolZvIMseLG1/mhY0vs3LlEmYODNDd2cWqlYuJtPCj519m0aL5TJvWR3t7H3fdtZ6x0Yt8/9nnWLVmNf3902luaeHEyZN8+9vf4cDBgzzx2SdAwfj4OGvvuJ3mpjLLli5hdOSST69omKvFyxz4vFGtmT1nDmvXrmX//v3s2bOH/v5+Vq5cyZYtW3jxxRdZvHgxc+bMqYs35N6qUoYojmltaWXwwgUeeeQRbr31VozWTJk6Fa0UIpZjx48yOjpy1fuslKrr0i5avBiUYvPmzYyNjWOtpbOjEwX0T5vGo488Qk9PD729vSRx4r9PvqL4+nuluR5uQUFBwU+KSXmk2kREcYlLI2NcGh2lqbmXs6dPM3Ogi8wK3d093Hn3HfT0zSBRF9n5WsT46DCHDx/g7rvXcdvqhG9960l27dyNjmKiOALjfDqJc4hYnHPcccftHD5znN/9vT9m5MwgNRsRJwl333MHO7bv46tf+0vsxfM4VWZkrMK/+fnHqUQdtHR0MLzjLIimklpee20LR46dZ97S5fS3NpNoR9WqsN7IH0/piFotpX/GTG5dcyudXV0MtGaUYxgdrlCrjvPqq1vYfyjlq3/1d5w8eYZpM2dwYWiQV1/dwtnBMf7rH/8pp8+dw5iYj33yk1SrVbq7e4iiiLRa4fVXN/GlX/4SG194galT+viHr/8laZr5edzciBrjhSG0oqe3h+XLlvLsM8/w+uuvMz4+zty5c1myZAlz5szBOcecOXM4dOgQx48f595772XFihWICN96+nl2bttJR2cX99y1nu8/8zQ/+tGL9PR0kQRBe2sdTz31FC5+6X1PAAAgAElEQVSkE10NcY7eqVOZPWcOG198EWU08+YuwBhDuVxm0eIldHS289rrr3Lu3Bn6p/cHL1bVF55ppQqFoIKCgg8c12xIx8fGOXzwCEmSMDIywqaXXyFOdtPV0USWWXp6e7nrrrt4efNGKrXNPHTvKsAwOjLK97//Att27WDF0jtYv34dwxeHqFZTlCkTxSV6p/ZTbiqTRBHiLNu3bWOoOsqGBx/kxe88w5lzl6jVaryx5Q3GK8La9ev58fPfplbT/OwXf47D+7fw4rYj3PPQQ3Rah2Copb6KhxPFWKWKisBagtxcmL0Neaqz585n1Zrb2PjSS2ij+cSGlWjxwuzjY2M+N9al7Ny1G0SYMpBx8aL3KrMs5c3t24lNwic+8QiDF4b47ne/y+pVq7jjjjsQ5zh79jSHDx3kvnvu4tSJ45w+PThRExTxqj6iyDIvoDA8fImNGzfS1NTEihUreP2110nTlDNnzvDSSy8xODhIlmWcPn2aarXK5s2b2bt3L845Tp4ZAqU5e+YsR48d47vf+x7N5YS+vj7Onj2LMX7+cvas2ZwfHGTowtBbUmCU8nmk7W1t9Pb28vDDD9Pa3sb0/gHSkZQ9e/dw/vx5Xn/tNV7Z9AoPPng/lUqVarUaNH9jMmsvy9ksKCgo+KBwzYZ08PwgP960hYF5C9DGcOnSCEoJnW1lX3RbG2q1GkuWLqWSGZyzIBkzBgZYtXYFzZ0lWpumc/bsYSqVKseOneD2ux/k8c89zshYN3E8SppmlEoJZ86cYdPWN7j1nvt59JFHeeb7GzHGcOLkaTa9uo2HP/w4c3vK/PXfP8vY+DhzZ99EtTyFOE4gKP7EpRK1Wi2IqkcocRitsdbVczqVNjilqKUpJopYunw5lWqVSEcogSjCV6kRQNVQIpRKESJVOto7sU6DOOKkjNaGsWqVjs4ebr31Njo7OqhWqxijyWo1XnrxRb7w+c/xp3/yp15oQYEh5MqqYOC1QhuFzTL27t1DltZYu3YtLS0t7N27l2PHjrFq1SouXLjA8PAw586dw1rLyZMnOXnypFfkkRjEsHnTJhYtmMdHP/pRujra2LjxJfbtO4BSmiRJ+Pmf+1mee/77fP+5H77FK3XOkWUZhw4d4s/+5E8wccysWbO49dbbefmVV7h48QLbt29n1eo1zF8wF+ssP/zhjxgfH0eF4ucEVaYiDFtQUPBB45olAvfv2c/nP/yznB0exSUVjpzei4k7iJWjs6vMhbNj9PZNYer0XkbHHGMXT+OGL+BUF53T20maDK7axMkzBxi6MITRXUyb2UZrVzvnzhhK2UkuDJ6hqaWLzjIcP3+euK2DgY4eTl4YxZRL4IYZGrpIc8csZrYZ9p++iNERt8zs4lLUwYkTp+iXi+wbTumbMY8Lpw9yqVqis7uHPneCU+eGsCJkQKY0DgM6xiRlpk3rp7Ori5HRUUoj57g0eI6qCL093ZwaHOZSaogZBxS6qYsZU9o4fuggtcziogRQlJuamL9gPmIzBs+dJYkjjh49glHQP62fJz73OF/+yn/jwrmzZD5hlZoVdBQDyq+kVZqujg7Gx8eoViv09fUCcObMGdrb25k+fTpRFDEyMsLRo0ep1Wr11azOOZyUQEdoLQz099He2oISx/79+4gjTbVWRRvNwIybuHDxAoPnL7zVI9UqCP8bnLVY5yg3lWlrbefCuUsohLbWJgYG+jGRYXDwHKdOnSLLbGhHEMWQoqrn9aKQCCwouHG4dkO6ex8/8+gT7DlxnEu1i2SqAsQoLFpZsAatDFZlOEkwOLSkWFX2c3E6BeXQotGiQSxOOZzW4JrRquKVh6RMosbJsFilSRw4EjItxFJDECwltKvidMhbJUEQRGr4KqdBLAKH5HmkQdavUTChrkHUmKoRhIsUClEa4zKvgKQNsVjECZmJ0C5DiWCVRpQC8WINStcQp1FExEmF1qZO5s6ex51rV3LgwEGe//4LZFmKE3BKeQk95RcLETw4FYQr/K26PO81p/E2NurMNkeamtNIUwc4h6uNU5IqOrS1hgFlUK5GIo4qbxVO8Pm1E+k7ztmQaiRoJ95Ldxa0AxcFPWB/3l66yaKVxjm8910waQpDWlBw4zA5rd1QYgzxYuLaGK9/6ywmCAEgAsqLADoJKR31xcIOkdDZ5oqrzn9HlCBBgs/lsVcA5HKDIiDidWrFOdAapwiatI4MMNKg2hMk7Gxd8iH//wZ1JScTxxMvJSH5NiqfybSI5CIGGdTNclBKEh3a6gCNiMJaRXNLibaOTvbuP8hrr72OFal7gP68gl5so7DE1dM7335hUMP71nr9JFutQeQLVuugieGc+CIBkg81woDhLfub+MwYQ2qt1+XVGiTF2sxr7OIavutfae0zVZ0Tb3wLl7SgoOADxrUX9hahWqnhnKUclxiTFJtZkkRoao4ZGwFRfp7PObmiAw16tHjDc7nWrkcBJjG4TKOcYBKNtQrlIIlLVFwVNMSRJqvSIF6rqXuZSvNWkfdca8i9czJGo/EWvFuK856mUqAsNAwIJrSIXMOXGo6thCQxnDw9yJnTL6NMhTQNHvnbNEFpjY4iXK0WBBm8nN/7CSIkiaaSApEBZ1EC5XJErZK+L6PmrC8/h8Xr/9oMjcb4IQXWWuIkIik3MT5e9brvAjrSRLFQGXd+rrSgoKDgA8ak8khbWpvRkaFmM5RWxElEmjrGxjIQMEpjbVAKiqIGubxg6CR/7Q1RXWs313bNhJ7eHqYPTMfUJeQV1mVMmz6dadOmYK2gdHyFUQzerSh0MBaXd+EqVEFxdU3cuo/boDQ4sfWEUVQN//Nau8aHcq/4ksKi6nVNvJdaqVgUGiuQWfFzjm93C8KuYmOYMWMG7R3tZNn7V+9JU194PI4iRPsq5qPjGe/HpimtSEoJWuuJvE3tQ+QOr08cRQZrLWNj44ALC7MUWeaoVELE4n3rBBcUFBTc+FyzIVVKUanUiHXMFz7/r5g1cxYI3H//Btatvw0TGR8S1BoTRWBzDzCPU9ZnJLnc/fPN0kqhFNyy8hbuvXs9TU0lL3wfOvC1d93FnetW10UHJk5HBS/Uyw3mn0zYDb/9WzVw87Y1KuTmwgh4gyz5nuTyP7lcf1fLhI6vFurGHECZEOoU8UZUvY08IP7829vbue/++1mwYOFldTbfO0K5VCat+XJujzz2GOvX3RHkAN/jHsSHiI2JmDptGl/84hf5xV/8RW6/4w5KSQljND09PXz605/g3/7bX+KhBx+kVCoDXjKxLuVXxHULCgo+gEzCI/W+XE93H488+ij9M6bRO3Uajzz6KNMH+n1Y0sTee1E6VB0JnXe9JItq8EobPTpvhoy2xJGmlJRQOiY3WirI+Jk4QUclJtyrYAjFlzFTYoIhVcFg5V5kdJmo/MQxTcO74bWo+r986/IQb4SvIWqZiJC7uilWDTOrecsEIU29gpEJYu/yNgIFIlJXNSqVkqCzq993+ogIjI9X6Oju4j/9l//M8hUrWL5syfv0DgVnLVrB8uXL2X/wIC9ufIlVq1cxY8YATeVmPvqRx4gizbPPPMuyZUtZvXoZxqh67qgxkwp+FBQUFNywXPtiI+UNgzaGQ4cOMW1aPxeGUnbv2UutlmJMxMrVq3nw4fvo7JvBkX1v8Ldf+XOGLiU88vEHuG3tKnAlXtn4I5575jnWrr2H7qll/uE7z1JqvolPf/gWvved72GzFGczenu6eeLn/jVtovnKV/8WJwpnHVOnTePxL/wC2dBR/uuff42k3Mp//7OP03fTQpTW/Lf/+3/j2PlRfuVX/x0jQ2dpmzqHWprx5B//H+zZewQBIq1xodqL4PWDb7/tdu67bwN9vb3sffNlvvH1b9Dc0cdnP/UwmUS09y9jbPAgX/nyX1DunM0nP7welVXo7Z/D8NBJ/p/f/X2UivjsEx9lwYKbaWufyh/+8f/Fvv0n+eVf/lX+8TtfZ/vW7ay+7TY++fBd/Jf/83cYGR8ndYSQqV8MlGYZlWqVOIpZufIWPv7xj7F582ZeeOEF1qxZw913301LSwubN2/mqaeeYnR0FJiQzvMrbmHWTTfx//7277B65VIWTGunlMB4xUcWmto7+M+/+Ws8/w9P8s3vPf+WudN8kVEtzXj22WcBoaOzk2r1VqZOmUK16hd7Pf/8D6iMKYaGhli0aDHbth7g4sURoogggXjNT1tBQUHBDcu1G1IRtIloaW7DOsE5Yd269Wzb+joL50+jpbmVU6fP8gd/9EdEcRufeOwe5s+bxaFjNW6aOZO/+euvsfWN/SA1XxfbKtLMVxcxJiKOI9I0w2hNZ0cbH/noI+w7cpgffPu7jFcgzSwzpk3h8c8u4ZWNL7H5R9+lYmM6eqfx13/5V5wftTzysY/xwL3r+LO//Q4Zml07d/Pcn3yNdfdu+P/Ze/Mgua7rTvO7976XS+0bCoV9R2EjALKwkSBAcN9ESRRJySJlW27LvUbPTMR4ujvaEw477GlHTztsjzRe26IXyaZaErWRFCnuJBaCBIiV2FEAqoBC7YWqrMrlLffe+eO+rCqQIGULHWOZzF8EgERW5tuyIs8795zz/VjVvozOzm6EgMhaB4yQHr6fwU9luHy5j6999Ws01NfzL3/xM8ybM5diJGltruON3e/y4l8+x6//b5+nubmewGZYvGgRT33jv7P/4N/w27/zn2mbPYeRkTFee2MPf/vN77Fx0za+9MQT/MZv/A7v7H2LmzdtpKvzHEuXLGLX7t0UisUEnzeJOHJuMp6H76VYvWYNUlieeuopzp49S3t7O8uWLePJJ58kDEMee+wx2tvbOXTo0KRPp5QSpSNCDadOniQMQqJ4OcYKiiEoCbEQhIUC3/3O0wxcOHPNxdcyFF55ynVFxzGLFi0inU7TdbGbhjrnF3vzzTezZOEaslVpxsYvJ642BmsF1roaaWX8paKKKvq46ToyUoGSbmZw+MoI/UODxHGa3FgOY2cRxJptN97InffdzsxZC8kNdnL60F6uDI2w563dPPH4L1D7lbl8/ck/5e29b6P8lFvC9CCOdNJsazAmZtu2rRw6dYxdO79NHERoLclmMmzfvoXdu/ez7+AhTBRjhIeXyvLffvvXGbU1WCHofO37WCOJNZw4eYpSMUQLQXWVT8qzFELXamQTA+w4ijFp2Lp9Bzu23UpjQx0mdxGPmLCgyU+Mc+zYWSbymv/79/+UKApZtmoeV0ZHOHmyi1JQ4jf+z98mCCJmz57Df/mv/xejIwVqqlvoGzhNFIUcPXyI+x/YTtvMGTQ31vPij96eJCyRLLlKz5uEz89sm8mN69by9NPf5fz580RRRCaTYd26dezYsYM4jkmn05w9e5aGhgYeeeQRtm7dShzHfOPrf847+w+Qzxewvo81Bk9B1lfkghgrLTqO2b1zFykb82Gr/cZadBTheR7L29v51EMP8daePfT3DdDc2MqNN93IuwdK/NVfP8nKFStYtKR1ytC7PMUjxAey3Yoqqqiif+66vvGXKKSxuYUgCNi7+y2kqmX+3FaMMcyeNYvVq1fz1a9+leErRZ547G5AEUYhhw4c49B7R7hp7a1s2nQTA/09TEwUaRRpstk6Zi9YQlU2Q8b3sNbwwvMvEEjDY1/8Ii9+94f09I4wkS/w3HMv4Kdquffe+9j74vcYyBu+8pWv8Hd//Te8+M5JHnzkERYLA1JRKEVks1UYM0q+UMT4hjh05yKlxFqFTeAEy5avZM7c+fze7/0eJg751S/cgzQxvicpFopABDqgVMhjscRRicHBYbQOiaOIQIek/CruuvNevvf9H/D9p59l88bb+OznbgOrGR0d4cihgzxw392cPHaK0bECQrqmpNjapJ6sMdr96evt5VsnjtPW1sq2bdvYtWsXQRBw5MgRnn32WQYHBwnDkDiO8TyPr3/96zz55JMuK9VxUq+WpLJVKOU5WzTcc76fws9Ws2zBLMYvX6BrYPSDS7tJ16/0PObMncP9DzzA4cOH2fvWW1gsQ0NDnD512jn5GMPMtpkUSyWKQQmtLam0II5shbVbUUUVfSx1XUAG309RVVObNNC4zk6TZFZBENDb28vdd99NoH0E40Rhkflz57N5+41UN2bwRDOdnccYGh4lCrrp2NrOY194hKErVQTBMIViiATGx8fZc+AAG3fcwT1338OLr+7GWsOV0Rx79rzOpz77BJ97+LP8/fd/wntHj7F540ZmLOuAVIZif4+DDFiYmJgA4WG0ILJFPE8SadeF64BCCotgeGiYiYkJ7n/gQUqFcTzpE8cW0ISRdY+Fm8PMplPouEh1VY2bc8Xip9OA4lxXN7duX8/jT3wJX1YzNDzsQBVa885bb/NrX/kyz3z/GUTCXpBSuDlNIR0QKDE6D8KQSz2XOHPmNLffvgMpJYcPH6anp4dHH32UXC7H2NgYr732GqOjo8RxPGWjlsAQ2ubPZev27dywYhkNqsQv/eIv8Lff+jajoQGt+cJjj7L3lRfoenXXBz5nayzaGLLpNDfffDPt7e2UghJPfOkJzp44zv59B9n/7n5uueUWNm64jZGRIV5++XVKpdDxjJP6aIW1W1FFFX0cdZ2s3S/R1T9IiQnGiwNIvw50SDoNQQGqslVkatIEIYiogAwLWOogC8K3oLMEwShhEIKtJl1j8TJpgmI1aT1MEE0gZBV1acNYsYjxUtSnsuRjiRYgmSCKYmR6BrW2wJhWEFvaqgQFr5ZCvkCLnWDIeHiZOuJgjJLJkM1UUacHGC+GaCAWYISHtZ7D5SlFNpUinfbROiQVFImjgMhCJu1TjDQl0qQI0MZiU7VU+5rSeA5tQSsJpFDKo74phQklYckivCJBPsATPouXzOXuu3bw1FPfZXzsCpEGocqsXc+N+gg3t5nyfayJ0TomlXIen0EQkEqlqKqqQilFqVSiUCgATDYZaa1RFqyUqGw96ZpaPBPgRyWUtYxMjBPKNFhBXZWPDIqMBTHXyhuFdNZu1TU1KOl8UjGGsFikVIpIpRTprI+vaigUC5TCHFa7nmlHM3Y3M5VA+j9HFURgRRX9/Oi6mo2UDdHRBMVgFCHBBHmEsERFjTSKIK/JF0YwpBJMX4RmHBsqkCGIYYTxUFYCVyiOgxmXwASBCFzdMoY4KGGkQduQsVKAsQlrFzcbGQZDXCEJAFJyaTwLtg9syCUEni2hwwliAJGnODFC0Xq4oRaLsBaIEETu1AwUIijkSRp/krEZISkVHEbJSI22ztVEB2NMFF1mq4VMEIGa2FiGB8bdqIz1SWWKNDa2sGL5arZsXs3b7+xnbCyHSTgLcWL9YmKdjAhpEFAq6WQ21hLHhcmPoFgsUiwWP/Jj0sp3gItggnwph7WgpEDr2I3U6BLaWPITAoy9ZhB1F0VgtSWfGwNcV7AnBL61pKVHFEUEcYCxkevodnY6DjAlkmnc6SjIiiqqqKKPia7P2FuoKUiAAKU8BAaRzEBaK5Iv0TLcFa7m7k09ms4EwoqkeVW4L2Qme3CSx2JqFvXqTSWaPlf6fgxAeU60TCq6+qeTY61Tb0+OxwW2yeMQZtr4q3E/LwMbbJmTa6afGMZIpCeItGbXW2/z3nvHP7r3pnztytEI+48fIUn4vcpT2NhiMZNQB6OnwqYQAjt5Du87DCHcMvM1HisBxojJayGwU2zkpFMXIbHaXtV4VFFFFVX0cdF1NRu5eqjFVx5GRlhjEcKSTguCwtSXtnteTIspU4hA+34mLUBC9XFenO4bWXgCjEPzSc8jNi57VJ5AR/J9rF1NOfiI5JvbTtu2+9t8gAV/1Xf8B3gF5WOW01i7CZVokrsrpvY9yd+der+SgsGhUYYHD4IsOaC8lVybbZSwdqXCRFHSwSvROv7HLY8mRKEoqZtiHBe37C6DdRB/a8o3Fh/eWFvebxzHkJxhqA0qqS07prJDEjqjApvgAwWRMR/EHldUUUUVfQx0XRlpmb+aymacFZhQCRLOBRMlFaFxHF4hZGJHVg6e0xGB0x4J95dEYA0sWrSQuqzhzLkzRMZt11rLilWrUCbHmTPnQSoXyyYDV4IItFPB++pAKhHEV/3MTv/x+1TOWh1cvxyIywwjsJgPvFVipkED3R6CQOMpLzG4cbVQE5WD7/t36hpzspkMi1eu5MrIED09PR983U+Rm+UUYDTpTBqlqsAa8vm8oxVJtx9jQX0E7Mhai1KK6upqhBDEceyWiMOQKAIpFTWZFEJm0EZTiiKMAGM0QaiRH4JCrKiiiir6566fOZAKISgFEZlUFY996RGee+WHXOzu44EH7iY31s+u1/ajDVOowCicYu2KMq8Wptb6ppZbXUbqstJly5YzpyXFxZ5uCnEJIV0YXr1+HV48SOe5boSRk+9zS8PaNQ0JiWd0kiOWcy33/HT+7dTDa8xQWlC47EpP1vimAvbUUvBUOFblucly1j19VVuC0e7GwlgxWUf8wPXFXbvq6io6Ojo4eeI4vb2XMeYf1/mqtUYqRW1NDbffcQcNDfXEUcgrr7xCf38/Rk8F8Y/aqhCC2tpaNmzYwLx58xBCkMlkOHXiFHv3vsvceW10bFxLOlXP6NgV3tz5MsPDE0gpieMIKQW6vBxeUUUVVfQx0nUBGSxQV9fAmrU3cOTMfsbzEWvXreP4e++AlDTU1bNg6TwyVY30dnfSc74TYyUzZ89g4aLZeDJNf+9lLnZ109TUgpeRXO4fQqpa5rW1MDw0gMB5m0rPZ8HCNmZW13HqzAWkVAipkF6KJQuWUZexHD1xmjAyrFuzkvrmWUxMjNN5+B0i4bFg6TJMFNLYOo9SEHLuyF5KQZjUYAWmTMZN6pKNjU0sXbqYVCpF74VOei/3INJZ5s+aAdKjoW0eYwOX6brQRSZbQ0t9NdXpFE0zZzHY28P5cxcw1rJ4yUJmzV5AFEveObATgUd7+2ou9XUykZugtrqOpfOXcvzESWysk/piYuidwO3Lqq6uYcmSxYyOjnLx4kVqa2tZvHgxmUyG8+fP09vbe1WQtTZZOI9jGhsb6evr5dChQ9y2/VbWr1/PK6+8QmQ0vu+xetVq+vv6uNzXf82P21pLLpfjwIEDHDhwgObmZm6//Q6E8shkq7j55q30DVzg1IkD3HnXbaxfv5Jdbx4gDDVJSbVSH62oooo+lrqupV0rLL6for9/gLr6euYvWMSpU6exFtLpNMtXtLN42ULqGtvY3LGCZ7/zLQZHFXffeQf1zdWM5yJ0HDHQO8C6tRtpnJniuRdeJV09k/vv28Bzzz7nTLatYfGiBWy5/W4GOy9wvqsPbcBqy5obbmDb7Q9y/uhbnDhzgdnz53Hj2jXImmbmL1rMW37AoVNd/NKXv8LwwCWGC1BbX0+NGebdg8fRlsmlZ5cdCmpqalizdi0L5s+npaWZzMYbePq7T5OqauSLn7+P8XzEULGa+TN9nvr7v0NVz+NXHn+A3u5OJkqSJZ+6iz/8/a8hpcfmLTfi+/UsXLiSmXOqeeWVt7jn3nt59+BO3tm7j5s6Otja0c7Zs51EiUOOEK6CaxPTb20MtXW1bNq0kVWrVrFv3z5KpRK33HILzc3NeJ5He3s7zz77LENDQ+6zSbB+Ugik8ui+eJGu7i6UUuTzeWbNmoW1Fs/zSKXSPPLo59j1xpv09g98IOOd3JaU5HI5jDG0traSz+c5cvQYjU0tKOVx4vgJlKyivraW9mVLeHffMYJgAqlAx9Mz+Yoqqqiij4+uY/wFlPLxs9VEUUwUx6xcsZL33nuXVe1z8f00V0ZzHD9xkqrqfrZ0LGf2rBnkSwVqqrNcON/Juc4B+i53UwwCsNItW2Jcpjk5ogHz58+lZU4ru/ft5/CevRRD1yXavmI5ixav4MUXX+bsoT2ENkUcx3SfP89o0IWfzrJ+9QoOnrxAKTYcPniEtw6d5NY77mD+3NkcPnwckmVXYwxCSJSfwiIZHRsnf/wEjQ31PHTnJmY0NTJRElRnPHbuepud+3r50uO3J9g7n6pshl27dnLs5CV+7V/9EtnqGvL5En0DVxjo76QYCG7btp0Xfvwq7+zdw81bOzh1/CQL5s9l55s7KZZKrllHyEncrpLO57Mqm2XDhg0MDw3yzDPPcOnSJVatWsXixYvZv38/URRx9913s2zZMnK5HK2trdTW1iKE4HJvP6NjOcDVS2fPms3ixYt5/vnnkwYjSxiGPPXUtxgeGLrmymu5M7tMJkqn06xYsYL+gQGujOaYOXM+NfX13LL1FlJeDXEcIoXFkyBF0sVMGcjwM//GVVRRRRX9XOr6MtKEVjM8MsKZM2fp65tgPJcj1hbl+WzauIlMbcpBFep9pBCMXhnljdffZP2GNTxw3yZOnjzErp1vIqTnDLKlQKDQOsaTrqmlubGBKDfC6NgVtDFu3AJBY1MT/f2jXO7rRxuDVYqly1dy54ZlnO4vUFtbj5i4iDGSYqDp6+snKEaUwoiMr5BYzOT3vPMJ1dpSXVvPpi1bSXsSJS0pT6FshA4t47kxurt7KBYjnnrqBwRBicXtC+kfGODixV6CIOC/f/1vCUsRN6xZx1333MmJY500N81GKUkch5w+dZIHHtjG8qWLSXmKI0ePY0x5TMdloSKxTCtn9w0NjQz091MsFtFak0qlaGpqYvXq1QRBwODgIBMTE/i+z6JFi1i8eDFaa8J9+7kyOgbW0jZzFo88+ghnzpyhs7OTWGtSniKOYk6dOOVmVa8R6MoZqpQSpRQLFixg4cKFPPvsjwnDmEhbWme2MTBwnpdeepGVK5awcGEzOo6TLt7r+S2rqKKKKvr51nWNv2hjmdHUhPIUp06eQsoeFsxrQylJ64xW5s6dxw9+/D2CSPHFh29PZkphcGCYF196lZXLx1i3finHjzUycmWMecsX09o2i4VL1tM6owEpJEoJDh8+Qn9ulDvuuZtUZDl+6gJaaw4dPMLoaInHn3icl57+W/vlAl4AACAASURBVE5fGuaBBx9k33N/z84jF3jsF3+JNKA8H5tg95ASbSVGG4xO+n8kSROPxFqY1Tab1pkz+eHTT1NTnWbF7NuRWHxPYGx5/jKkUJhwvqPSoGNDHGu0jpmYiEmlqll3UwfHT5zguede5p67HmLegjoEMJ4b5d19+7jnrtt55aXXmcgXkUnPUWwA7OQ4itGa8fFxXn/9dZoaG9ixYwcvvfQSExMTdHd3s2fPHi5fvkwYhuTzeZRS7Nq1i927dyOlJIwNfipFfW0tj33+8xSLBfbv309VVRXFYhGL677+9Kcf4vTJkxw+euyazUzl+dFskh0PDg5yubcPhGJgYIAL5y8wPOQQiHPnzKa35xLFQglrBSqZGDIf4r1aUUUVVfTPWdfVbOR5HoViiQsXupNRD0GpWGJgcISh4WGOvneUjRs2UAglp093MnYlR1trG2s3r6K6IYPQ9Rw6eJiBwWEKE10sXdPG1q230NcHx0+cZmIiT25slMtxjgPHjzEWWpYvXcbgSIHh4WGu6GEOHT5BYKrpuOlGekb28PxzP2bz4sVkZi2n6/wFGsZ6iKOYnouXyOVyWAOjwyOMiCE8TxDHLuuzCFASgaDn8mXOdXayectmJsZHOXniLLlckWIMXRd6KZUCHAnJkvI9xnJDDA6NEEVujlal0hhg/7sHuWXbWu69735K+ZD3jh1HIBDacvzocTZ3dHCxuxvpxjuRQgLJHCYglYc2hsu9l7nU3cXJE3k2bdrEDTfcwNGjRzl+/DibNm2iVCoxNjbG7t273TkmNU0AYd0YUltbG42NDeTzeXbs2IHWmqef/i46jvE8RdvMmfR0X/zIGVJjDPX19VhrefvttykWC1ibIZcb58DBg6xZNZe21jlcGR7gwLuHiWONFJI4Ngmco7K0W1FFFX38dF2s3ccf+EUu9veSJ08uGsE3WRQxIg2mYEhnsvjVaaIIdFhCRCUQVXhZgfQE6DSlYIwgCLFUka0BL+0TFH1SeoIwLICXIeP55IMi+IJav5piGIESWBsSRhqVqaFaGMYDi7DQUiUIZZZCoUQtRUZjQSpbRxSME2qfTCZDlR4lH4Q4nxWBFQohUg7iIKGqKovyJDqKUFFIHAbEQDqVohQZIquQNnBppJemOq0oTYyjHX0eg4dUKWrrU1jjEZYMKVmkUCggVYotm25kzZo1/N1T3yYojBPFCivTxCZGetqVSpOxnpTvE+sYbTSZdAZQlMKQjK+oTftoTxKGMUE+T2xNMlbjYW2YLL8rMpk0mXQaIKk/a/L5PNq4ZeJ0Ok0UhZQKEdaaJAN14zOTvyxC4Pvu+hUT/1RtJVKm8JSlutpDWElQKhGFRXQy8+OGhGQS3CuR9H+GKqzdiir6+dF11Ug9JRFxiTAaB88i4yJIx4bNWkFYiMiVgMk5T4tgAhEm3an4QIRjIBXIjxvIJ/za5Ds30kVKgbM3wxQZLVqkiLEYtJUgFaY4xqhRrh4nBP25GMwYQsBQQr2LxsMEsxdTKuQJbDlAlGdPQcgIJRXGaAoTJYfMkxZr3LqrNZagGAASIXGBwmoI84yHk1tCGoMREbGG0aESeCksBhuXaJs5g7s+9QBt9XX88McvkStFeNZi8DA2CyrCMIG0GqtBWkUQxxgMVkiKhQBQGN8FvonCBEUFWEXKOFShwQOrEvqFxdqYYiGmWMhPnrLvp4h1jJWSMIooBQFCSoTwSXke2kSAy1bdsqzBWksUhURhmHQ5AybGmJAwhjC41m9JOXBWsEYVVVTRx1PX1bUbRxprNZ7wEFojhcbzPYJIJzOMZXr5tbMQOxl6XMbiOLXwQR6vZpJhS8wka07Yac8LpJJY7fBJUsmrWLL/ELkansEKg1Bi0t7MERXc0fq+j9Y2oTeVz6FMPXIqe564XDflMjEZIxCMjY3z5s43kEXNxYEhR3kSIJWr05a5xWXi4dWahP+WDxhVPtd4OlO4fF0+/FzLDUtRknFK4RxdhJHoxFrOWIOUDstYthIVQuL5iiiKJ7txK6qoooo+ybqOfkqBjS2xCXHf/B5IiHQEVk5D45Wp81O+n+8HBFohuDpsTEfYSxBx8kI5+U4BCUd3Gv+WKeqPQDh/z2se+QeDVDl+22Sf1lh0pLHGokhGObBYo5HCJpleeWtuBtVO8faTwzEI4QKpSgHCQ2s4d66L7kuXiY11b7XlYxJYrRHCXgXpB1G+V0hGUWzC+xVJp7OaBGS8D7j4oVKeQluLVC6Tz9ZUo3WMsRprJ1mOyQ2R4wSXcYJuPlXyM1YFKqqoooo+VrquwQQhwFM+wkK2qpqaxhq0FZOreJMZaTJeMj16TWfbTguNkwHx6nAXJ9mn9yEz/R5Yi+cpHnn0UW67bcdPbWyZ2vpUaJ/8Wwh8P0VDQwNNjY2kfWcD5wlAxxgdT3v/9GN1S9CTtw/W4isFwtI8o5l/9Wv/BqUEUlmEUm4uM+lk9b0Ut95yC//xP/0n/sWv/gr1dfWT230fHgGBZd6C+Xz60w8xp20GVpeDuk1McZJs+KdkpFbrKXCiVDQ1tyCVQkqXU9fW1tHQ0EhVVXXi5uM6nJ2Ru4M9VFRRRRV90nUd4y8GKzQxgqraGu7+9H20zWzgr578K0aGRyeDUrnVZGpZcipPvXrhNflSdjMqiKtqmOVXegjKzF7JpJUZAukp4jimtXUGUVRMIOuSOL62/+W1gPUiWd6sravhlptvZtGiBfi+x3BvN6+8+Aq58Qm0cSMqk05pJLxcYSY3XAYOuv+EYAX1dTNYuXIJSlls6HjAUngYqfCAOI448t4RQltg9fq5pNLe1Udr3U2GFAJPCbIpn5amhgRr6IE0TBqbMnVSH7awbq3F832iKCKVTnPn3Xexdu06/vKPn2RoaJAFCxZz++3bk8AveOutvRw5cjQBM2iEdK4+FVVUUUWfdP3MgVQpiZIKKauobchSUy0Zy0UsX76KA/v2kEnVsmb1GvwqyZr1G+np6WHnm68Th5YlS+bT1NTEmpUbOdd1kjfeeI2xXMS6mzaw+eaNpFLVvPqjb3Ox+zL33X0f57pOc/pMFxm/jjvv2MbuN3cxPhphCDECrBVuOdK6bEkpie97fP6xx5jI53nhJz/B89Lcc/99zJ4zj87Tp3jlx88QJ+9xOD4XXIS1LFmylBUrV/Hcsz/CxJovPHwfK5Yt5MCh94hjgxQSjfNcdQu+is1bb6Vj4wakUvzgya9xZbxIGME9d29l2ZoN1DTNIIxzKAWZdC2337qZVes66Bse5bmn/hytBeO5MQYH+tHxLKxJ6pZCMWtmG9vv3E5jaxvnT51g16svJRl3zPZtW7izbQknTxxn3xuvUQhClJTcc+995MeGeWvvO5N10PfL0ZwEa9eto+OmDsbzDujg+T7r16/n4sWL7Nv3DuvWr2Xbtq1cuHCBXG580s/0/U6vFVVUUUWfRP3MS7um3CFqfebNnk+xMMahw6fo2HALqZSirraFrVu38+ADd3Po8GHqG5ro2NBBY2Mjn//C57n55s3sfHMn8+bOpX1FO7Nnz6WpuYVdu/dw8VIvDz30IDNnNNJUX8eaNatIpVJ0dKxn/rzZKGER6Gm1SACL8NySZHV1Nffeey+tM1t5990DZDNVPPzww0ipePXVV1m8ZDFbNnck2Z3rwC2nqOlsljlz5jGeG2dsdIyVK1Zww5obmDdvLlL6k+ld2WNVSsmiZUtpaGrhpZ+8xMDAIL/+v/8vpNPV3HPPg6y/aSU//P4P2fnGPrJVUAoEy5evQ3mSZ599nmxVLU988QGU1Cgh8XzP1SEFYAW11XXMm7eQixd72LNnLytWLGfzhrV4wrJ6VTv19VmOHz/JsuXtLFgwy9UxjWXhgnksX7KEdDp17Q/QOl/SGa2t3H///bz62msMDg4RBAHZbJbZs2YzMNBPdXU169evY/ny5TQ3tzgP1eT9lRppRRVVVNF1jb9YhDUgPdauXcf+wy/RfcmwY3ua1uYGcnlNMYh5+eWXeWfvAcbHixhdINaa7u4uDrx7kPdOnMbLWCbG84yN5SjkS7TNmkM6W002m8ZieHP3Gzz40AO0tjazcsUSDh98m/HxAG0dlkgkjUZSuqaZquoqli9fzOjIMH/+539GLjfOjBkz2bxlC2/u2sW8uXOprq5m1coVHDp8jObWFhYsWQbKo7d/kK5z57HA0qXLeOzRL9Df28M7+/ZRTGZOlSeIjEVIBRY832Owv585s2exYNECpBLU11WhhODG9Tfxve/9GV0XcqBaCKMFeJ7g8uVBZs+ay/xF85HSY8aMFqSVKCEoFvJIa5FIkIJSGDA2Nsr8lvk0tDVQW1dDXU0VPVdynD17hjdfepOeQprVq1eSTmfwPB9rDN/85t+SQlAqla756fl+CmsNN3V0cOTIEQ4fPMCixYtBQDaTIZ1Js2HDRlIpj3PnzuF5CiVdJ7OQAl3OzCtu3RVVVNEnXNflR5pOp6jOVrHl5i0sW1HHYL6JRfMaOLhwNgffu0IpCBgfLZDyUhx77z2sKTFz5mxy4+OM5saI45j9+98FCWvWbGHdTR2c7TzFyMgV9MwswsLlSz0UCgFrVq/G8y2d57qJ48SU2wqMlaDAGjeyYrRmbGwMpTxaWloYGxsDYclmsxQKBcbHJ9i9cze5gUsYExPGMcVSEW0FQVAC5Sy5pZS88cYb9PX08C9++TFiY9DGEmnHwTXJoKvWmo61a9h66y3s3buXsSsjeGoR1dUZlJRMTExghUdTSzN+Ko2xKW7ZupW5swVHj59nolCAtAFrMdYtS1dVVeF5HspT1NU3cPPWrYzmRxkeG6VYKKDjCGMMWkcYExEEKgFJeESxITaaYj5P/BH8Az/lk06nue2227DWctNNNzF77hzmtMzluWeeASAoBXznO/+DtlkzWbt2DflCYYq7q8pjMhVVVFFFn2z9zIFUx5pCvsDy9nZOnDzO3/z1VxmPq9m0ZS0L583m5PkCSEsYhARBQGw1Qjrbrpq6Wow2xDpGKkPKSzNn7lx0rDlx/AR33HkfjU2NCOHmNY8cPs6XfvEX+M53vsHgwCAS198TmzJMQWOEhUgTRTFnOzvp6e7mP/yH/8jv/s7vMJ4v8PbbbxNrzXvHj2GiEJvPoTzo7b1Mz8AAfipNKXCznqdPnuS2rduY0dSMj8JowanT5wnCCGMtnnAtPBbQOmbxwgX09/Zy/L2jfOHxL5JOpSnki/T1X+L2HXfw8pvvcd/9dxGHA0glaF+xhJPv7ebk6fPcuOV24mIfShlqUtU0NTaRz4+TTiuk9Giob2DGjJkcOXGEvIbZc2dz5qBrpAqjIoVSiPTqKJVKaBOSUimU0vybf/1lckOj/I/vfZ+J4IOkhGKhQLFY5L/87u+Szmapymb57COP8JMfvshAfz/Hjx9n/fq1KM9j6dIlnD3bSW9vLzBlVlChFFVUUUUVgfqtn5EzlrsyxnPfeRaRzXC++yxnTh9nIo6JgzyNmWrOXriEUpLR4QEGrlxBKEk65RGFGs9X9PUNMDFeQik3mzg8PE5LazM3bezg0sU+uk4d41J3F4EOscJn4aL5HNj/LrnhcbAglSU2CqnSWBujPA+lPBrr67nQdY4Tx48zMDDAypUr6ezs5MyZs3Rs3Mi69eu5YcUKiqPD9A8NYxLz7FhrhHAjHrlcjoG+flavWs3ChfN5483XOdvZiUk4uDo2IKSD4QO9A32sXLmSG29cz8kTx+g718l7J89wurOT27ZuZd78Jby9bz/F0SGOnzjO8c4L3L59K4uXtnPmdCe5vgtc6hlj85bbWb9hHTU1PosWzqdYCDl3rpswjLh5283UNTRz6sghLp8/z9BYiZQyDPVeZjzwqapKc2XoEiMjE3gpn6bGWgZ6++juuUxs3pc5ChBS4nkeQRBQKBQIwhBrLT3dl7kyOsrw8CD19bXceuutFIoFXnrpJYrFElK6+VGjXY24Ekr/abRjxw527NjxT30YFVVUEdfD2j3VyeP3P05X3yVGozGMX0IE0gHYZYyM3VhILIzLHAUJ1l4hhXWjEzZBBAqw+AjPgrBYI0hJi8TDYLll2xZmtc3mmR+9QCE/6rpr8TDEDp5gLSgPaw0O2RBPzlAK4QIlSKSnEMJD6BjfRITCQ+OB1AgTkZICIwXWr3KAiSjAMyHaGGJcc42YPvbiduCanqR0jU/W4llLbC0aiVJpN2JjIpQ0pKTCGov1JLFxxKAqGVAK0yDr0aKIVAXnKBOCxEugFQarPJSxCCuIVIo0EamoRF56CASeiYgRaCSe9IGAWF+7t1Yq5WZBPYU2BmGTLmRt8T0PrQ1SWrACKT2iuDg5FyyEScZgwFRqpP8kqrB2K6ro50fX4f4CqXQaz1rQmkhY0lZjsETWksVijCWWJEOXU1OkBpO0CyfTptZiibGxmZzHjKxkwYIF/OqvfoWGxixf/X/+mCCIMJThA65rGBvjgOiuzohUgHA1U8FVPp861oBFYZwdmpVYqcAaF3i18zqN4xIqU4MAUsI6KHyUkJkmo5Kd6l4FrC7zgyEqn5lwy89CAWji2CBc6CY2Aqs8pPIIIosWYKwGoTAWROyOyVqdsIhNMrcpsVZhFck5WCDCWunOQRgsksiQQCyuDU1QykvOwoI2CN93MPu4RBg61xbpa4z2iCKN9MBogbXOSk4Ii5RqslZcUUUVVfRJ1XWxdoNigDERKc8ntAYpYvx0migsJdZkdhrW7+ov9atoRtNZu8nzSnn09vbwm7/5nxFCIaUDAUxBAMqs1zKwQSGVh4ljhLQopa5yLvkHSThyjxAeJjYIrdECovcvjV51Dh+EO3g4OrD7ofMWFTjnFKVjHMfW+ZoKq0kp8IwgMmX6k/kAInD6XoVIyL5aoyRIT2Eid72nkBf2I+NbFDqIfyqTRlmLjiLwFZ4n0TFIqYhCi/LcdY3jELAoKfF9RRhpNwJVCaIVVVTRJ1zXx9o1EJGwdo0CZQnj0jTWrnud+2c6hm8aa1dMZ+2KyfdobYmjkjO8ti7z0SYGkQKhkiNXWBzjFukCdiqdwvd8t2z5IazdZM+4ADwt4FgQQpJKpaZYto7UwEe5l9j3/Zk2lurO2xjSmSqa6uvQ1hIlKFupFEL5LrkG0n6abDpFNpuZ9CSd3EdyeaSUSOG6iv1M1nVdIaehFsv66CXXdDqNkIIoCByYQTmHm0nzbeHq0Na4GwHPA6VI6snvD/QVVVRRRZ9cXUcgtSglSMs0WhvqGxpomtlCbCSYcsAUTALlJ5m7H8xhprJTEsKCxBrjanBGIxF4nsDzyq+7xre4MaRSaf7tv/13fPZzD6M876ebSF+d6Dn2O4YwjEBK6hsaqa2r+0cQfMqkIybpP77nznvGzFn8+3//r6nKpkAKF5QijY00WEj5Ke6//17++E/+hN/4zd+gubl58lwn8bnJkjUYlq1ayVd+9cssXTjXXe8PsHbNhyzqOoVhQCaTIZXN0trWRmvrTJqam1FK4SdQiNraOtraWmlpaUEID6sFSip0YoZeiaUVVVRRRdfF2rUYqwksNDQ18LknHqWttZk//uOv0d87AAg8z0MIifIzGKMJwwCsW7aVUuKparQpEoYhxko838dPKQQ+cVBACoPnOduyKI6xVpBJScIoTljvSaZoQfoeQVCiWCxQKBQwRlNTU00UxZSCABCkMxmk8iCOsKUCkxlpojgGL50im65i6Yo13HHrFtJRjj/5i78gDOL3XYHp9yACP+Xj+z4gsMVxBBBbQdaTpFLVNM2YSduMGYRhDMrH9yV+VQZrFCoOCMKAHz7zAw4fe5dbtq92Di/JtpWUpNIppJdG6hijI2xQopgfJ4histX1hGGALebButptKpUCGxOF8TVzU6EUpWKROfPm8ZnPfhblefgpj2e/9z26LnSzZvUK7rx7K0YrqrIN7HnrRfbseReMRAuXudufsnxcUUUVVfRJ0HWxdj2p8GQN9Q01hMEYJ06Os3rVjVwZepHqTCObN2+mqtZjwdJVDAwO8sbrr1KYCOi46QYa6huYP7edvoEuXnz5RUZGSmzYfCM3blhPTU0jb7zwDKdOHOOhBz9FV/d5Dhw+Sm1NPXffeyc/fv4FRq/k0ca5aVuTANSFII6dz2ZDfT2PP/5Fenv7eOEnL1Jf38hd995Lc8sM+nsu8pMffJuwqJl0prEgcO+fu3A2s2bNpqenh3lNaQTgex7G2sTgOsk4pQumfirNtu3bWbPmBqqrq/nxt57kbHcPSmV5+DP30zpvGVWNrUSlCTwlydQ2csetm1m2ah25YsTz3/p/6RswxAakcJ6nxoAUrvt2zvz5bLtjG/XNrfRdPM9rLzyDUJJM2ueeu7ZDyyLOdZ5l54vPk5vII6Xk4c99lvyVYV585TWC6P03AeXKtGBiYoJvPfX3FIpFHvrMZ1i3bi0Xuy+xdt06Dh48xP53DrN50zZuueVmTpw4w/DQRLKsa356xl9RRRVV9AnQdbB2NQhDLBRLFi5hYmyYg4dPsf7GjaRTimy2gfXrO+jYsI7vfOe7FIsh69ato7a2hnvvu5cFC+fxV3/116Qzadrbl9PWNgtjLd/4xjd4/fWd3HfvXbQ1N1HMF1m6dAEZP8XmjVvxfZFkp4op1zUPcN6aSika6ut5+OGHyeXGeeaZZ8lk0nzx8S9yqaeHv/yLv6C2toptt25ASgNKIYREComv3L9d57r4yfM/oafnMnGsUUpNdgWn02k8z5tcjpbKZ/6ixYRhxJ/96Z+zc/db/B+//r+SSmX5zMMP0zajmT/8b7/Pt576FmnPB+Exd8EiBgcG+aM//CMGhwf55V/6LEpplJQomRiSJz1Y1dXVNDW1sGvXLr75zb+jdWYLW7d04AlLe/syJvI5nn3medraZiWs3WQcyBqqq7L43rXvlYQQpFMpxsfHGR+fQApJQ0MDg4MD1NZU01Bfz8DAAKvX3MCt27Yyd94cmpqa0CZO6ta2EkgrqqiiirgeRCBuflLJFOvWreetd1+gFArSaY85bS0MDMeMjuXZuedNLl/q4XD6MMYUieKYEyeO887b+8hNjPPW3rcplYqMjRVZnF7E9u23U9vYCtYS65i39+7hC1/8NPPmzGTRwgXs3PsS+YkS2jjYvMV1mErlAkg2m2X+giVcGR7mj/7gD4jjCN9PsaJ9BT19fdx+xx3U1NRAWwvZbIY5s+fTvqydDCF93V0cOXkW30tjtaMHISTGGHzfR2tNFIauBipdLVQpxcDAEAsWLOau+x+koaGBOCjhSVi4aBHfe/JrKOXGUeKwgKckg0MjLL+xnfvuv5/mGTOQshdhJAooFPMoIVAokJJSFBFGIStXrcavqae5qZEeDDrWvPfeYd7c+Q5DYTVeKoWUHkr5GKP5zre/RVpIgg9pXNaxRmuNn06TSafZuu1WfM/jvaPHUMojk8ly7733MDEe8vbbb7P6hvlorZPar0i8SSXa/CM7oyuqqKKKPmb6mTNSC3hK0djQwPIV7Wy7ZTP3338vLa0zWLxwDkJBGIdEJUM6labz7FnOdZ7DWkMUxwRRiDaaY8dOcOFCN6tWr2HVDWu5MjrG+GjOWYhhGRkZYWhwhI6ODoqFHBe7Ljs/TKFJEi/AoLXBWksUR/T29jIxPsHGTZtc9mgMQRgwMZHn4qVLvPLK67z62jvE2jAxnqPnci8XL11mZGQUayxhqZRQjgQYg7WGOI4nz7ucwWItUazp2LCRdR0dDPT3ky8USXk+6UyKKIqpqcogPI/5i5eQ9hUGn+133s3Mma309vVSCiOs1mAN1mpSvqu1SiVQStLY2Mwtt96KFdB3uZc4jtBxlMAhLEqB1hZtTLK07a7FzNZWmhoaPtR82/d9pJCkfJ8tW7eyes0N/Pi557gyOkoQBERxSD6f55vf/Dsu91zG93xyudxkFlomUlVUUUUVfdL1swdSY4iiiPaVyzh69Ah/+Ad/wp/96R/x9Pe/w8L588lkfIQEHRtKQRGDRvkeQkqy1VW4ERe3bOqnfDLZLEoq0qk0c+bMIZPOOBKSsBw9epKOG9dz6Mg7jIyMOgdQpXF5sZqaZ0xGVS6cv8DLr7zMo48+wpYtW9Ba8+orrzJz5kwymSyZTJZSKcACQ0NDHD9yhFMnT9LT04MxluraOtbcsJaV7e3MmTOHLZu30NzU5C5YkokKKR0dyEBVVRVhGJPJZJm/cCHYmEI+4MSJE3zuc5/l1ltvoWPjJnQUoRSkknOtqq6huWUGOo7IpD3al7azccMGGhpquGHtSmbMaMXzfNLpDDXVNdQ1NtLY2AiTpuUhURQilU8cRQhh8JRHNp3hV375CR761IMfaqMWhiHpTJqly5fzK1/+Mp2dncyaPZsNG24iCmPeefsd2tra2LHjNjo6Ojh48DADAyOIsncrlT6jiiqqqCK4Dtbu6JVRfvStH5ELi5w+d4KBwcvEUhIV8uhSSNelXgqFCUaG+hkdzyOkwPMkQSmkUMgz0DdAMR8hpWvgGRrKYYWmpaWJkyfPcProIfp6+4jjiGxVDTPbWjlw8DBjYwW0BaEs1nhuDtPGSM9HSImJY86d66Sr6wLnOs9RX99AV3cX5y900TJjBo1NTdRk01wZ7GVodByTIAZNHCKxaCuoqmlg8dJlpHwYGeilqrqagaEhxvMTgJu1FNI5rligt6+P+tpa6hsbOHjgABeOHubsxct0dnUzv3UG1suy+619DHef4VzXJU6d62bJ3Fa8VJZDh47Sf+EsfQMTzJu/nJrGGnLjw/i+x+hIjkuXerkyeoWZbTMpBCGH39nLpQvdDI4WCQvjXBkcJFeSBGGRkYEexnJFhJREYUDX+Qv0Dg6hzQdDnhAu462vryc3Noa1lvr6WlJScf78eQYGBgnCAm1t87h0qZc9e3cRxxpQgMYadxtTMff+p1GFtVtRRT8/ui7W7hMPPMGFy91cCUcxqRAZSgQGLTSedplbrCza1CRiLAAAEMxJREFUlBNfi0C6SUtrgRSOtWux+FiZIAKtwBNQna1h1qzZrO9YTTFf4pVXdlMojiWIOom1Sc3OWFA+toz6E3GC15s6NYtMeLgKazTC2mS/JHOuBgUgJEIqNwNrDEoYtDWYBIJgdDJAacWkuTckNePksWdiYiHQKJTwHXTCajwbkfI8jAErLDESiyRtS0Q6gxG1aIoIVUBKi41A4btuYaGxUqGsq07HKk2akFRcopAYjvsmJhagUUjhAcE0ROL7PvjkWKVSCYhBI5XCi2OH/hMSI2Ni7SFkCksRkKAViDDhCkvXdFbR/++qsHYrqujnR9cBZAAhFR4WX0i0tkg0vp/MGWIQWByKddpa4LQAJ6aecM8Z7f4kfNmq2hpW3XADqXSWdw8eIoyCyY7UMpgA4/i5k6zdMvQhAczDNHBReXyFZIJ08ti0OwbH2UdJdy6gEUphhaM46dhM1iaFMNP26+qb1sRYExNTPkeLFhIjBNbGGCmdl6qJ0Fo74LuwxNbxKgwgVAorxCTD1lp3HFiT1GstxojkfMonF7ljTc7WJpm1/ogxTyFc4HdQKPdYAqmUjyclEpFk3sKdo0z2lxh7W+NuZipYhooqquiTrp+dtYsj82gTuuzG+ggRJj9w/0yxdqc9OU32Ktbu1ZLSY2RkkB/+8LsglHuVcVAGJ/0Bjq/0PEwUISR43kezdssGYFPUIBcoymbVUrnaa5R0qsrkMM01TmUaYdB1Ml/1EocIlFLhKRDWBXKbwO4FwnH2jUAbwGoXqK/ayPsQTMLZuKEdBlH5Ch1ZB/T/wFFdW1JKtNYJStF9RtoYjJDE2rrtu4vukI9J1BZC4HmK2FZYuxVVVFFFcJ2sXQe2McljCQpCHVNm7bpAKa+i+v1DWbtxrImjxEfFJI4uWDczOsnalVOsXeFgBouXLGb27NlXYfo+eOQWiUn+TIVzKR1dyQpBrLXboEyyNusCpJzE7iZLuZOH7tJZK+VVYU9Il3FX19axZtUKhBDE7uCS90usASUl8+bMZcOGDaxes4pUKj25Dcs01q4QCAE1dTUsXLyIqqqsA1JMvrKsj15yNQmIXyV2auX/x9oFaSvUZMYuJvfrOnVdrbSSi1ZUUUUVwXUhAg1WGKT0kAI23XQTLU1pXn3ldaI4SoKlnbbcKhzA3U5lbtMzuatYu1YhMCghMcSJz6hxS6/W1RenYoZ7XJ5vvPuee7h8uZvnn33O1TQ/pIY3VbWdItNaY8ETKOWzdNlS1qy9gfGJCY7u28/Q5V60tZRzYJLl2DIDl/LNQHIaUgg04ClBZKCltY0nHv8Cv/Wbv0UcgRJubAVj8JS7mWhsaqBjwwYyVSUGB3oZzIdTV2oy+Lrbh7a2Nm7fchO7X3yGod7hZJlVJzXiqduYj8oXU6kU69evZ8WKFYBzhBkZGmL37nfQxrB5040smL+U0dEJdr/1KqOjeZRyy/hufxVVVFFFFf3sQIZkuTNC0dBYS0fHGhobGjlx4hRd57uQUlFTXY2RkuraeoKgxOjoFayRZLMpfN+nuqqJUpDjyugV4khSU1tHXX01QqQYG+onjgIaG5oJw5h8voBE0dRSx+jYGLFOanflMCzcOE0ZFCGlYMaMGURRxPDIFYRQNDU3k0pnCAp5xocHsHZq9VS44h86MjS3NrFg0SLypRJtc2ZT523h9Rd+Qi5fwNrEOxSbLDM7KH9dQz21tXUgBGM9F4mNITKClvoavGwd8xYspjaTcZ6kyqehtppMXRNRZJkY7CSMYo4ePfL/tXev31VUaR7Hv7su55p7OIGQhCREQLlfBARBlEtjt4rQb7TX2L36xcyb7nk//8r0HzA9a9bMsITYaKNCUCSxRTCAEE0CBkhyTgJJzv1WVXte1MkFwWmHrGmZ4fm8YCW1ck5VnbB4qL3389uk81Ps2bdx/hEURTAQpKa+GisUppzLkU0n8ZdDeUQiVTS3Rsmm0+SmJv1NulE0NDTgOUWSqVRlz9KHeZ5HJpPhzp07BAIB1q5dy4r2Tj7r/ZJtW7exY8d6bnw9SOfK1ViB3Zz+4Cyl0uznXRlJkJFdIcRTbhGF1M+CNVWUhoYGyqU0176eZtOmHcRHb1MVaeTA/v3ULglR1kEc1+PixT6mJmc4dPBlQqEQ5byFYZc523OGyXt5tjy/gWUtS1kSW87tgX6+6O3l1UM/Ix4f5ULfX1je3Mbel3fx7on3mJnO4aqiP6pcmcNThsJxygSCQTo6OnjjjTfo7+/n4sUv6ex6ho1btuC5/o4sPadOMB6f9EeOK0+VCgNlmmQyWXo/6yVXzLNj1w52r99IVbSKbC6HpxSu5z+RzfaU1jY0sP2FXdTX17O0eTl3Lp/nzPm/EIs1c/TnB5nKOtQ3rwCvjGmYNC5vZefm9UTrY1TVN/JVz79x+UoCw/UD6g3DxNMahSIYDNO5sou1m9diR6qwcfjsow9QhqKxsY59L21nStWTzaQ5/+F7JCanUQqOHHmdXHKKk386Rb5Yeuj3p7XGdV2Gh4cZGBigpqaGpqYmBgdvYVlBVq1eQ1/v51y9coNopIbnt23i4hdfMj42XVmx680tehJCiKfZ4wcyaA1K4yqT555dy0RinGvXh1m1eg3hkIUyw7S2dYJ26O7uZmYqSWtrC5Zt0dLSTDI5zYnubspOmRUr2rAsi5HvbvP+qff59PwFnnt2NbVVEe6O3GZlZwu1VVVs3byNZGqaQqGIW9kE29821Kq0n/hznE2xGEeOHKGvr4/e3l6CwSDHjh7jypUrdJ88SbFYYPuOrRimQhkKZfrFCwy0hlKxTDqVJmCadKxoZ2JikmQm7d+3N7s4xx+2DgTDmFaQoW8Hee/knzjXc57Xfn4I07A4dPhVEmO3OXH8OGfOnMUEAraF42iuXu3n+L//B0PDwxzYvxtLaSylcB0Hz3Xm21MMg2wux7lz5/jz6Q8JBGzWPdeFoT1sy2BgYJAzH/fQ2NhILLYEy7IxTYP+/st+ktQjekhn3xegXPZTkpqamrADAQa+HSIYihIKRTBMg1//5h1WrerCNi1qq6vAczENNR/cL4QQT7lFrNr1hxYDVpC1a9dz4YtbRKtqCIVDdKxoYeSuRyqT5dq160xPTdPb9zmumyMSrube1BQ3Br4hm8ty+vRHlJ0yllXD3n2vUFUbIRytoz7oz41eu9rPli2raW1ZRltrG6c+epd8vojWFrMji0qpuazdUDDIqtUrGbl5k6tXr1IsFqmrb6BtRRsHDx6i8GKBhoZaRobyBCNhVq58hu07dqGUzeDQLT759BPKTplwJMSuXbuIhIKc/fhjcvm8P5c6u7CostjILTtYhsWBA4exAiGqa2qIhGxCQYvlzcv51xN/pFQqUyi7eE4Jx1MsaVzCmwd2UfRs6pa3YE1/5W/urcB1ygQr8X2mZaJMi86uLtZtXocKRFixtJrJm1+jPY9EYozBoWFmStUo08CyTdAKz/Po/+oyQQwc79EbfOtKy5FlWViWxQsvvEAiHiedymA1Rqipb2D/gQNcOH+B5FSKV/ZvxSkV/bSpynv4i48e/2+QEEL8f/D4hVSDUiZNS5tYuixGR9sKamK1oKC9bRl3E+N42sUp+bF1k5MJtC4Rboniei7FUomyUyYxMYFlWby4ZzfhaJRzPT10rlxD44ZOQJPJZLk9cpe9e/YwNv4do3fioD2Ucub7KJWuBKpDsVjk2tVrlAp5jh07yvHjx3HKDvcm79Hf38833w7iOiXymWmKTomhWzeZnEpiKJtUOof2IBwKs33bVjra2vns3HnGx+Nzq5Bdrf1QedOk7HhoT7Nzx05CwTDvn/qAzVu38nzLcximSTqbpa21mUQuwaZt2wlYJoYZYM++V4jHb9F36TovHnqVjpAf7+dvTh7A8zwM5S/SamhoZMOGjVzu/5LpTIFfvvYynnYrC548DAM8DxynshF6pT1o86YNuLkiN4aG/RXI3zMbxK+1pr29nTVr1vDPf/gDrqfJ54skEhOEQgX6+j5n47oNaK2ZnkpWUhgVhuGfUwghnnaLWmwUsC1aVz3D1WvX+OO//Cd5u5rntzzLnnVdfHElAXgYyqBYLIJShMIhHNfBsm0s00J7GjtgoUyDmZkk9fUNvHn0lyRTBYqFHAYKy9QMDAyzc+duej79hGw6BwpMy8V1TL9VQ7sobEzTxLJsRm7f5srly7z99lu8886veffESU52d3P4tV+wafMWXLfEh6ff5ZsbgxRKaVLpHKYRRHsGth2gq3Mlv/3Nb3GcAsualoBboPtkN0NDt7ANRdlx8bTGsmwc1yWeSPDSS/t5+623SGYyZFJJ8rkCPT09/NM//D07R6a554Rx3RKm4TI4NMyvDu+mtWstOSzIj1IdjbJr7+ts37uN+phJy/IYf37/U24Oj5LP53n9yJvcnZwC5eA5nh9GrzQat5LypAmG/I6daCjCwQOvcH9sgqGR2xR/oJ9Wa00kEuHYsWNcunSJ0dExtBEmnytw+dJljh7bxz/+/ndoR3PmbDfJmSymYeJWQi0MZfihEkII8RR77IjAm98M8XeH3+ZeqUS6PE0mGSevTKLBALFomNH7aerqanEKWaYyebAUhqExlU19Qx2pmRSFnIcyHFAGdqCG2LJGwuEgqXSeQClDeuY+jlOivbOLgwf3ceJkN2PxaRztYdgubtlCmRaeV8SywnieQ2xJjGIxSzadoba2lqqqKsbjcZQyaOvowLaDlEsFJiZHyWTSaNefW/Vcf47UUCY11VGam5eC8vyoPtchPj5OJpfz50hNE60VZddDYxEIBmltbce2bWZmZmggy83EfcqmzabOFnLaZiJVptnO8N34fZxIPRtWNpHOeySzJaLOFBP3szTGOgnW2BhGAU+7TCamyaZLVNfW0djUQMEDnZmhlJoi5Vo0VtvkZqZJOTXUN1ZRyk2SyTgoQ9HS3IhbKDN+/z7OD/yKDcPANE3a29uJx+Pk8wU8gihlEwjaLI0FqY5Wk0lmmZgcxXVcPG3gqdmFRkYleUn8rUlEoBBPjkUV0ncOv8Vg/BapYgZHuXimvwTW8BbGKxg4GJUM3Up4g2I+b26uq3S2B9Nv0LRMRV1dHRs3bmT9+vVcv/41Fy5cIF+oxARW8m5n32s2LOC/v1tV2b2k8hS1sA/0wR+bm/tTc9fqWxj0oOfuYe6VlTv20JXspPk/1fxxpTCUxqsEO/jH/Vf6oRN67mSzT5vz11+JVKy0+Sg0Hg8mPDF3xkflST3qY1n42VVWcGlQc9fxY/OSxN+KFFIhnhyLigj0C4rfy+n/gz2frzNbXmZLxPcDFB48qB8+riw0cOfuXSbv3WNsbAynsufo/EvnX/Oj/j+g9QMheg9fx9yPPfLr+WMLDz789fc/i9n7mzuuNd6Cc88Xu7lsxQXn8hZ+80AE4HxC1MJyufCMP85D91P5XhYSCSHEX7eoQvq/SSlFMpkkmUzOhS0IIYQQT5onNudttr9xNgfWNM2f+pKEEEKIhzyxhdQwDCzLmpu/836gH1IIIYT4KT2xQ7ue5/ltMzDX7yjDu0IIIZ40T2whXahcLv/UlyCEEEI80mO3v5RKJcZG7lJ0yni6sqX0gn27HtyK+q9t6CWE+J+IxWLEYrGf+jKEECyikAohhBDiCV5sJIQQQvxfIIVUCCGEWAQppEIIIcQiSCEVQgghFkEKqRBCCLEIUkiFEEKIRZBCKoQQQiyCFFIhhBBiEaSQCiGEEIsghVQIIYRYhP8C3QAMGRLgY64AAAAASUVORK5CYII=\"></p>', 'https://www.youtube.com/embed/S7s7yIPUn_s', 1, '2023-06-01 07:42:05', '2023-06-01 07:42:05', NULL);
INSERT INTO `contents` (`id`, `title`, `lesson_id`, `description`, `url_video`, `published`, `created_at`, `updated_at`, `deleted_at`) VALUES
(11, 'Array Multidimensi', 7, '<p><strong class=\"ql-size-large\">Array Multidimensi</strong></p><p><br></p><p><strong>Array Dua Dimensi</strong></p><p>Array yang telah kita pelajari sebelumnya adalah satu dimensi, yang hanya terdiri dari satu baris elemen. Biasanya untuk menyajikan sebuah data dalam bentuk tabel, dalam tabel tersebut disajikan dalam bentuk&nbsp;<strong>baris</strong>&nbsp;dan&nbsp;<strong>kolom</strong>. Hal ini yang menjadi ciri khas dari sebuah array 2 dimensi.</p><p>Sebagai contoh</p><ol><li>Buku tamu yang terdapat di perpustakaan untuk melakukan pencatatan kunjungan pengunjung, dimana dalam buku tamu tersebut terdapat informasi nim, nama, tanggal kunjungan, dan tanda tangan.</li><li>Rating film yang dilakukan oleh penonton atau viewer. Masing-masing baris atau record diisi atau dirating oleh penonton, sedangkan pada bagian kolomnya adalah daftar judul film yang akan dilakukan rating. Visualisasi dapat dilihat pada tabel di bawah ini</li></ol><p><img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAloAAADRCAYAAAAUsxzYAAAQyklEQVR4nO3dz2scZ5oH8G+W+Q8EYmcEgyRyDMKHOsTp7BBEwOAJETksxIsmLErAhAmWIb54wT7IYcSCA7JQCAavDl6RDOwhtHAChiBMJh0Hpg+m8TFIZhbtQEP/DdqD5F+JJlFivV0l+/MBH7rdqnoonq7+1ltvVT23s7OzEwAADt0/1V0AAMDTStACAChE0AIAKETQAgAoRNACAChE0AIAKETQAgAoRNACAChE0AIAKETQAgAoRNACACjkV0+6gM3NzcOoAwDgSJmcnPzJzzxx0Droip5Vm5ubtg+NpT9pMv1Jkx10oMmpQwCAQgQtAIBCBC0AgEIELQCAQgQtAIBCBC0AgEIELQCAQgQtAIBCBC3K6bczX1WZXx/8/L+9s5SqqrJ057DX08tSVaWqqlTVfNr9n18aT4lG9ueuwfq8/nzmDdI+U6U6087P79C9/dxy76c/+ov3nwdcPodzZ3jY1+hMrnRn6q7iMb3luay9dCE3l2eyvVxl7uRSJrpnM1V3YQxfA/szSXrLVeauJ0mr7lKo1UhmlrtpUof2lueyltmsds9mqt/O/Mm5LP2um7PH6q6s2YxoUc73jpR6y1Wqaim7x0A/PFrbPYrfPVJa+urxRf3U3x5MLxvXkzw/kZEkU7+bTbKWjYOMSvD0aVx/Phqy4Ht99L1R1B+Meu718+5I08ZjSzqs/pw60033/oHp6EQmkqx9ZVTrpwhaNEO/nYWFTvLWarrdbqazVmAdW9lK0hof2339m4m0kmz97RecOuLZMoz+TJK0cuGLblbfKrR4nlKDtD+4lE5ms9rtpvu7FOvQB2tc/6+s5ZH9Kf+QoEUjDL7dSCetXHhz9yTe7mgTNMOw+nPqzJXMjBZZNE+z/tfZ+CZpXfzD7mjTsekU3YPeWcqJhU6SVqZfHCm5pqeCoAUAHEy/nfl3dsfLWhcvOjA4AEGLBulk6/8KLn5vTkHn3vbu6//bSifJxG8dkXEQhfsTntCDfVsxvSydvJROkry1miuv23cehKDF0IyNt5JsZaufB0Pd9428OJ1WHk6s7H21duC/PbipTL+V5LutDJIM/raVZDbTrpghTehP+BGPzSkd5OsvOw//b/TlTL+U5PrG7oT3OxuPzdE6rP7cveowyUsXcvOMa7UPStBiaEZefzuz6eTSySrVB1uZeOmR/xydyZVrs8n1uVRVlY3vzTD40b/9GabO3MyFXMqJqsqJheTCF27twK4m9Cf8Q6MzefutpLNwIlW1kK3nH739x0hmllczm7XMVVWqr/JYhx5Of+5dtZ0k3+zuQ91L62Ce29nZ2XmSBWxubmZycvKw6nnqPNPbp9/O/MlLycWbhpgbSn/qzyZ7pvszg7TPnMil7N73T4c2z0H70w1LKWKwPr93VcpsVof4I/Zj9yGavebGeuzSnzTa3kFAJ8nsteGFLP1ZhhGtwmwfmkx/0mT6kyY7aH+aowUAUIigBQBQiKAFAFCIoAUAUIigBQBQiKAFAFCIoAUAUIigBQBQyKHcsBQA4FkztEfwuHPvP+bOxjSZ/qTJ9CdNdtCBJqcOAQAKEbQAAAoRtAAAChG0AAAKEbQAAAoRtAAAChG0AAAKEbQAAAoZetAarM+nqqpUVZWlO8Ne+xHSb2e+mk+7X3chsA/9SQM9+vtSLffqLgeSDDto3VnKiYWJrHa76X5xIVvv2FHvb5D2B5fSqbsM2Jf+pIH67Sx8OZ2b3W663Zu58N1c5tcHdVcFww1ag79tJW9NZypJRl/O9EudbHzri/B9g/WFbDw/m1bdhcA+9CeNNDqTK8szGUmSjOTlV1vp3NuuuSgYctDavtdJa3xs79VIJp6PL8L39dtZWJjI229O1F0J/JD+5EgY5OsvH/29gfocykOlD2aQre+SjA9vjUdR78+XMnGtm6m06y4FfkB/0nh3llK9s5ZkNqvLI3VXA8Mc0dodweJH3FnKXFZz9ljdhcA+9CdHwbGz6Xa76V5L5qqlmBJP3YY4opWMjd8/Zz6S+yNcrVcN7d7X+2otub6W6vrD9zon55MvrmRmtL66INGfHDG/mUgrG9nqJ1P6kxoNdY7WyG8nkusbu0cY/a+z8U0r0y8a2r1v6kx390hs76rMVlq54EeMhtCfNNqdpVRn2rl/edXg2410XprOy/qTmg11RCvHzubmxfmcqKokyey1rp00AE/u2NncfHU+J6pLe2/MZrV7/ypEqM9zOzs7O0+ygM3NzUxOTh5WPU8d24cm0580mf6kyQ7anx7BAwBQiKAFAFCIoAUAUIigBQBQiKAFAFCIoAUAUIigBQBQiKAFAFCIoAUAUIigBQBQyKE8ggcA4FlzkEfwHMpDpcfGxg5jMU+l7e1t24fG0p80mf6kyba3tw/0OacOAQAKEbQAAAoRtAAAChG0AAAKEbQAAAoRtAAAChG0AAAKEbQAAAoRtAAACqkpaN3NSutcbvTrWXtzDXLj/VZarb1/79/IoO6SYD/9GznnO0zDDD4/93D/+dHdusuBJLUErbtZaZ3Op8NfceMNPl/Mren1dDqddDrrOZ/FLH4uatE0g9z4z8XcrrsMeFT/RhY3Xsn6/f3n5umcs/+kAYYbtPo3cq51Ovn4ak4NdcVHw8jvL+fy70fuv8rx6eO5vXHbqBaNMvh8MbcmT+V43YXAo0Zfy+UPX8vuHnRv/3nv7zUXBcMOWqOv5XKnk/emhrrWI+vv924nk+MZ+emPwnD0b2TxT+P5938dr7sS+BGD3N64nePjv667EMiv6i6Af6C3ktOfnMrVzgt1VwIP3P2fxYx/3MkLuVF3KbC/3kpa736a5FSufugwlfq56rCJeitpvXsv5z97L2IWjdFbyelcNSJNs029tzvP9ePkdGslpsRTNyNaDTP4/Fxe/9N4rnYuC1k0yt2/fJp88mlanzx87/Yb55LPLue10frqgn3983iO51bu9ZMX9Cc1MqLVJL2VvZBlJIvmeeGPnb0rYjvpfHY+x3M854UsmqK38tgtcQZ/vZXbL76S4/qTmhnRapC7f9m96cXp1iM3v3jxfNYfXEkDwL6m3sv69Lm83lrce+NUrnbsO6nfczs7OztPsoDNzc2MjY0dVj1Pne3tbduHxtKfNJn+pMm2t7czOTn5k59z6hAAoBBBCwCgEEELAKAQQQsAoBBBCwCgEEELAKAQQQsAoBBBCwCgEEELAKAQQQsAoJBDeQQPAMCz5iCP4DmUh0ofZEXPqs3NTduHxtKfNJn+pMkOOtDk1CEAQCGCFgBAIYIWAEAhghYAQCGCFgBAIYIWAEAhghYAQCGCFgBAIcMNWv125qsq1d6/+fXBUFd/pPTbma/m0+7XXQjsQ3/SQIP1+Qe/L9Vyr+5yIMlQg9Yg7Q82Mv1FN91uN90vLiQLC3bU+xqk/cGldOouA/alP2mgfjsLX07nZrebbvdmLnw352CeRhhi0BrJzPKVzIzuvRx9OdMvdbLxrS/C9w3WF7Lx/GxadRcC+9CfNNLoTK4sz2QkSTKSl19tpXNvu+aioNY5WtvZ+iaZ+O1IfSU0Ub+dhYWJvP3mRN2VwA/pT46EQb7+spPW+FjdhcDhPFT6l+gtz2XtrdV0j9VVQTP1/nwpE9e6mUq77lLgB/QnjXdnKdU7a0lms7rsQJ761TKi1VuuMvfdhdw8M1XH6pvrzlLmspqzwidNpD85Co6d3Z0HfC2Zq5ZiSjx1G/KI1iDtMydy6fnVdJeFrO/rfbWWXF9Ldf3he52T88kXj8xtg5roT46U30yklY1s9ZMp/UmNhhq0est7IctI1r6mznTTPbP3ot/O/MmNTPsRoyH0J412ZynV6kRu7k2IH3y7kc5L07moP6nZEINWLxvXk2TusSPi1sWbufK68+gAPIFjZ3Pz1fmcqC7tvTGb1e79qxChPs/t7OzsPMkCNjc3Mzk5eVj1PHVsH5pMf9Jk+pMmO2h/egQPAEAhghYAQCGCFgBAIYIWAEAhghYAQCGCFgBAIYIWAEAhghYAQCGCFgBAIYIWAEAhh/IIHgCAZ81BHsFzKA+VHhsbO4zFPJW2t7dtHxpLf9Jk+pMm297ePtDnnDoEAChE0AIAKETQAgAoRNACAChE0AIAKETQAgAoRNACAChE0AIAKETQAgAoZMhB625WWq20Wq20Wudyoz/ctR8ldz9q5dzng7rLgEcMcuP9+9/fVlrv34gOpUnufvRIf7ZWcrfugiBDDlp3PzqdfNxJp9NJ5+PxLL7hi7Cfux+1cvqTuquAxw0+X8yt6fXd729nPeezmEUHAzRFbyWnc3WvPzu5+m+f5vRHfmGo31CD1gt/7OS9qb0XU6/kVO7lnlGtR+yOGJzO1Vz9t7prgceN/P5yLv9+5P6rHJ8+ntsbt41q0QxT76XzxxcevHzhX04ln9xyME/t6puj1buVTzOe8dHaKmigkbz2YeexnQU01d/v3U4mxzPy0x+FoRv8773kxfH8uu5CeOb9avirHOTG+69n8dvk+H+sR6SAI6i3ktOfnMrVjm8wDdS/kcU/Jec/e82BALWrYURrb9Sms55XNl434RuOmt5KWu/ey/nP3nOgRPP0b+TcG4sZ//hyXnPGhAao8fYOIxmfTG7f+3t9JQA/y+Dzc2m9m1zt+BGjgXorab1xK6989sh8YKjZEIPW7kTvld7913dz65Pk1L84JoYjobeS1/80nqsdI1k0UP9Gzr17L+c/cxBAswxxjtZIXvvw6u59tPbeOf4f67nsqAOOhLt/+TRJcrr16cM3Xzyf9Q/Ng6F+g7/eyu3czu03Wll88O4pBwbU7rmdnZ2dJ1nA5uZmxsbGDquep8729rbtQ2PpT5pMf9Jk29vbmZyc/MnPeQQPAEAhghYAQCGCFgBAIYIWAEAhghYAQCGCFgBAIYIWAEAhghYAQCGCFgBAIYIWAEAhh/IIHgCAZ81BHsFzKA+VPsiKnlWbm5u2D42lP2ky/UmTHXSgyalDAIBCBC0AgEIELQCAQgQtAIBCBC0AgEIELQCAQgQtAIBCBC0AgEJqC1qD9flUZ9oZ1FVA0/Xbma/m0+7XXQjsQ3/SaL0sVVWW7tRdB9QVtPrtLCx0aln10TBI+4NLsYVoJv1Js/WW57JWdxGwp4agNUj7g41MvNUa/qqPiMH6Qjaen40tRBPpTxrtzlLmMpvZuuuAPUMPWoP1hVx6/u38YXzYaz4i+u0sLEzk7Tcn6q4Efkh/0mi9LL2zlQtvTtddCDww5KDVy38vTGT1zNRwV3uE9P58KRPXzsYWoon0J002WP+vbF28mJnRuiuBh341zJX1lueSa91MJSbB7+fOUuaymu6xJCYZ0zT6kybrt7Pw5XQuLo8k2a67GnhgiEGrl43rydr16pFJip2cOJPcXJ7JyPAKaazeV2vJ9bVU1x++1zk5n3xxxREatdOfNNng2410vunkRHXp4ZvvVMm1bs4eq68ueG5nZ2fnSRawubmZycnJn/13g/X5nPhy+qkPWb90+6TfzvzJjUz7EaMg/UmT/eL+TC9L1ZyQRVEH7U83LAUAKKS2Ea1nhe1Dk+lPmkx/0mRGtAAAaiZoAQAUImgBABQiaAEAFCJoAQAUImgBABQiaAEAFCJoAQAUImgBABQiaAEAFHIoj+ABAHjWHOQRPE8ctAAA2J9ThwAAhQhaAACFCFoAAIUIWgAAhQhaAACFCFoAAIUIWgAAhQhaAACFCFoAAIUIWgAAhQhaAACFCFoAAIUIWgAAhfw/9N3nVOOlYPoAAAAASUVORK5CYII=\"></p><p>Tabel di atas menggambarkan bahwa setiap view akan melakukan rating terhadap 3 judul film, misalkan pada baris pertama melakukan rating pada&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">judul_0=4, judul_1=4, dan judul_2=3</code>.</p><blockquote>Jadi Array 2 dimensi adalah sebuah array yang penomoran indeksnya menggunakan 2 angka yaitu satu untuk baris dan satu lagi untuk kolom, atau sebenarnya array 2 dimensi adalah kumpulan dari array 1 dimensi.</blockquote><p><br></p><h4>Cara Mendeklarasikan Array 2 dimensi</h4><p>Untuk dapat mendeklarasikan array 2 dimensi mirip dengan 1 dimensi, perbedaanya adalah jumlah kurung siku&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">[]</code>&nbsp;atau subskrip. Pada array 2 dimensi berarti menggunakan 2 kurung siku&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">[]</code>, pada java deklarasinya seperti di bawah ini</p><pre class=\"ql-syntax\" spellcheck=\"false\">data_type[][] array_name = <span class=\"hljs-keyword\">new</span> data_type[x][y];\r\nx = jumlah baris\r\nY = jumlah kolom\r\n<span class=\"hljs-title class_\">Contoh</span>\r\nint[][] arr = <span class=\"hljs-keyword\">new</span> int[<span class=\"hljs-number\">10</span>][<span class=\"hljs-number\">20</span>];\r\n</pre><p>Selain contoh di atas, deklarasi yang lain juga dapat dilakukan seperti di bawah ini</p><ol><li><code style=\"background-color: rgb(247, 247, 247); color: inherit;\">tipe_data[][] nama_variabel</code></li><li><code style=\"background-color: rgb(247, 247, 247); color: inherit;\">tipe_data [][]nama_variabel</code></li><li><code style=\"background-color: rgb(247, 247, 247); color: inherit;\">tipe_data nama_variabel[][]</code></li><li><code style=\"background-color: rgb(247, 247, 247); color: inherit;\">tipe_data []nama_variabel[]</code></li></ol><p>Akan tetapi, yang sering kita jumpai atau sering digunakan adalah pada no.1 dan no.3, ketika menggunakan Java adalah seperti di bawah ini</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-built_in\">int</span>[][] ratings;\r\n<span class=\"hljs-built_in\">int</span> [][]ratings;\r\n<span class=\"hljs-built_in\">int</span> ratings[][];\r\n<span class=\"hljs-built_in\">int</span> []ratings[];\r\n</pre><h4>Inisialisasi Array 2 Dimensi</h4><p>Untuk memberikan nilai awal pada array 2 dimensi menggunakan operator assigment&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">=</code>, ketika melakukan inisialisasi array 2 dimensi kolom pada setiap baris boleh berbeda seperti dicontohkan di bawah ini</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-built_in\">int</span> a[][]={\r\n    {<span class=\"hljs-number\">1</span>,<span class=\"hljs-number\">2</span>,<span class=\"hljs-number\">3</span>,<span class=\"hljs-number\">4</span>},\r\n    {<span class=\"hljs-number\">5</span>,<span class=\"hljs-number\">6</span>,<span class=\"hljs-number\">7</span>,<span class=\"hljs-number\">8</span>},\r\n    {<span class=\"hljs-number\">7</span>,<span class=\"hljs-number\">8</span>,<span class=\"hljs-number\">9</span>,<span class=\"hljs-number\">6</span>}\r\n}\r\n<span class=\"hljs-built_in\">int</span> b[][]={\r\n    {<span class=\"hljs-number\">1</span>},\r\n    {<span class=\"hljs-number\">5</span>,<span class=\"hljs-number\">6</span>,<span class=\"hljs-number\">7</span>,<span class=\"hljs-number\">8</span>},\r\n    {<span class=\"hljs-number\">7</span>,<span class=\"hljs-number\">8</span>,<span class=\"hljs-number\">9</span>}\r\n}\r\n</pre><p>Array yang pertama pada&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">variabel a</code>&nbsp;kolomnya semua sama antar baris, sedangkan jika kita lihat pada&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">array b</code>&nbsp;kolomnya berbeda. Dalam array 2 multidimensi hal tersebut diperbolehkan. Ketika divisualisasikan ke dalam sebuah tabel seperti di bawah ini</p><p>Visualisasi untuk&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">array a</code></p><p><img src=\"data:image/png;base64,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\"></p><p><span style=\"color: rgb(51, 51, 51);\">Visualisasi untuk&nbsp;</span><code style=\"color: rgb(51, 51, 51); background-color: rgb(247, 247, 247);\">array b</code></p><p><img src=\"data:image/png;base64,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\"></p><h4>Ukuran Baris dan Kolom Array 2 Dimensi</h4><p>Seriap array baik array 1 dimensi ataupun array 2 dimensi memiliki ukuran, jika pada array 2 dimensi berarti ukuran pada baris atau kolom. Untuk mengetahui ukuran atau length, bisa menggunakan attribut&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">length</code>&nbsp;pada array. Cara penggunaannya adalah sebagai berikut</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-built_in\">int</span>[][] a = new <span class=\"hljs-built_in\">int</span>[<span class=\"hljs-number\">3</span>][<span class=\"hljs-number\">4</span>];\r\n</pre><p>Ketika dipanggil&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">a.length</code>&nbsp;maka hasilnya adalah 3(jumlah baris), sedangkan ketika dipanggil&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">a[0].length</code>&nbsp;hasilnya 4(jumlah kolom)</p><blockquote>Ketika menggunakan attribut length tentunya akan sangat menguntungkan, baik ketika akan menginputkan element atau menampilkan element menggunakan looping atau perulangan pada saat perubahan jumlah baris atau kolom. Kita tidak perlu mengubah kode yang ada di dalam looping untuk ukuran baris dan kolomnya.</blockquote><p><br></p><h3>Array Tiga Dimensi</h3><p>Array 3 dimensi merupakan bentuk kompleks dari array multidimensi, seperti pada konsep sebelumnya array 2 dimensi adalah kumpulan dari array 1 dimensi. Begitu juga dengan array 3 dimensi, yang merupakan kumpulan array 2 dimensi. Contoh penerapan array 3 dimensi adalah pada gambar berwarna&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">RGB(Red Green Blue)</code>. Visualisasinya adalah di bawah ini</p><p><img 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\"></p><p><img 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\"></p><p>Dari visualisasi di atas terlihat setiap gambar memiliki 3 channel atau layer yaitu RGB(Red, Green, dan Blue), 3 channel tersebut yang merepresentasikan array 3 dimensi. Setiap channel, RGB direpresentasikan array 2 dimensi. Jadi sudah sesuai dengan konsep array 3 dimensi bahwa merupakan kumpulan dari array 2 dimensi.</p><h4>Deklarasi Array 3 Dimensi</h4><p>Untuk dapat mendeklarasikan array 3 dimensi yaitu dengan menambahkan kurung siku&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">[]</code>&nbsp;atau subskrip menjadi 3,&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">[][][]</code>. Secara umum deklarasinya adalah di bawah ini</p><pre class=\"ql-syntax\" spellcheck=\"false\">data_type[][][] array_name = <span class=\"hljs-keyword\">new</span> data_type[x][y][z];\r\nx = index array\r\ny = baris\r\nz = kolom\r\n<span class=\"hljs-title class_\">Contoh</span>: int[][][] arr = <span class=\"hljs-keyword\">new</span> int[<span class=\"hljs-number\">10</span>][<span class=\"hljs-number\">20</span>][<span class=\"hljs-number\">30</span>];\r\n</pre><h4>Inisialisasi Array 3 Dimensi</h4><p>Untuk memudahkan inisialisasi array 3D, bisa menggunakan representasi array 2D. Atau secara umum dapat digunakan dapat disajikan seperti di bawah ini</p><pre class=\"ql-syntax\" spellcheck=\"false\">array_name[array_index][baris][kolom] = value;\r\ncontoh: arr[0][0][0] = 1;\r\ndata_type[][][] array_name = {\r\n    {\r\n         {valueA1B1C1, valueA1B1C2, ....},\r\n        {valueA1B2C1, valueA1B2C2, ....}\r\n    },\r\n    {\r\n        {valueA2B1C1, valueA2B1C2, ....},\r\n        {valueA2B2C1, valueA2B2C2, ....}\r\n    }\r\n};\r\n</pre><p>Keterangan</p><ul><li>A adalah indek array</li><li>B adalah baris</li><li>C adalah kolom</li></ul><p>Ketika diimplementasikan menggunakan Java kurang lebih seperti di bawah ini</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-built_in\">int</span>[][][] a = {\r\n    {\r\n         {<span class=\"hljs-number\">1</span>,<span class=\"hljs-number\">2</span>},\r\n        {<span class=\"hljs-number\">3</span>,<span class=\"hljs-number\">4</span>}\r\n    },\r\n    {\r\n        {<span class=\"hljs-number\">5</span>,<span class=\"hljs-number\">6</span>},\r\n        {<span class=\"hljs-number\">7</span>,<span class=\"hljs-number\">8</span>}\r\n    }\r\n};\r\n</pre><p>Atau misalkan dilakukan visualisasi adalah seperti di bawah ini</p><p><img src=\"data:image/png;base64,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INSERT INTO `contents` (`id`, `title`, `lesson_id`, `description`, `url_video`, `published`, `created_at`, `updated_at`, `deleted_at`) VALUES
(12, 'Fungsi Static', 8, '<p><strong class=\"ql-size-large\">Fungsi Static</strong></p><p><br></p><h3>Pengertian Fungsi</h3><p>Dalam pemrograman terdapat istilah fungsi, prosedur, dan method, yang ketiganya pada dasarnya adalah sama, di mana kita dapat menyebut ketiganya sebagai fungsi. Prosedur adalah sebutan untuk fungsi yang tidak mengembalikan nilai. Fungsi ini biasanya ditandai dengan kata kunci void. Fungsi adalah sebutan untuk fungsi yang mengembalikan nilai. Method adalah fungsi yang berada di dalam sebuah Class. Sebutan ini, biasanya digunakan pada OOP.</p><p>Ada 2 jenis fungsi di Java, yaitu fungsi static dan non-static. Fungsi static adalah fungsi yang dapat dieksekusi langsung tanpa harus melakukan instansiasi objek. Sedangkan funsi non-static adalah fungsi yang harus dieksekusi dari objek yang sudah diinstansiasi, di mana ini berkaitan dengan OOP. Sehingga pada modul praktikum kali ini kita hanya membahas tentang fungsi static di Java. Cara mendeklarasikan fungsi static di Java adalah dengan menambahkan keyword static.</p><h3>Sintaks Fungsi di Java</h3><p>Fungsi harus dibuat atau ditulis di dalam class. Sintaks dasar penulisan fungsi adalah sebagai berikut:</p><pre class=\"ql-syntax\" spellcheck=\"false\">static TypeDataKembalian namaFungsi(){\r\n  // statement\r\n}\r\n</pre><p>Kata kunci&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">static</code>, artinya kita akan membuat fungsi static.&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">TypeDataKembalian</code>&nbsp;adalah tipe data dari nilai yang dikembalikan (output) setelah fungsi dieksekusi. Jika fungsi tersebut tidak mengembalikan output, maka&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">TypeDataKembalian</code>&nbsp;adalah&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">void</code>. Sedangkan,&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">namaFungsi()</code>&nbsp;adalah nama fungsi yang kita buat, ditulis dengan cara camel case. Contoh:</p><pre class=\"ql-syntax\" spellcheck=\"false\">static void beriSalam(){\r\n  System.out.println(\"Halo! Selamat Pagi\");\r\n}\r\n</pre><h3>Cara Menjalankan/Eksekusi Fungsi</h3><p>Setelah kita membuat fungsi, selanjutnya kita bisa mengeksekusi fungsinya. Fungsi dapat dipanggil dari fungsi main atau dari fungsi yang lainnya. Contoh pemanggilan fungsi dalam fungsi main:</p><pre class=\"ql-syntax\" spellcheck=\"false\">public static void main(String[] args){\r\n  beriSalam();\r\n}\r\n</pre><blockquote>Kode selengkapnya, silahkan dicoba pada bagian Praktikum.</blockquote><h3>Fungsi dengan Parameter</h3><p>Parameter adalah variabel yang menampung nilai untuk diproses di dalam fungsi. Parameter berperan sebagai input untuk fungsi. Struktur dasarnya seperti berikut ini:</p><pre class=\"ql-syntax\" spellcheck=\"false\">static TypeDataKembalian namaFungsi(TipeData namaParameter, TipeData namaParameterLain){\r\n  // statement\r\n}\r\n</pre><p>Parameter ditulis di antara parenthesis&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">(...)</code>&nbsp;setelah nama fungsi. Bila terdapat lebih dari satu parameter, maka dipisah dengan tanda koma&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">,</code>&nbsp;dan masing-masing parameter harus dideskripsikan tipe datanya.</p><p>Misalkan, dibuat parameter bernama ucapan dengan tipe String. Sehingga kita bisa menggunakan variabel ucapan di dalam fungsi berikut ini:</p><pre class=\"ql-syntax\" spellcheck=\"false\">static void beriUcapan(String ucapan){\r\n  System.out.println(ucapan);\r\n}\r\n</pre><p>Cara eksekusi fungsinya adalah dengan memberikan nilai yang akan diinputkan sebagai parameter, bisa berupa variabel atau langsung nilainya. Contohnya:</p><pre class=\"ql-syntax\" spellcheck=\"false\">String halo = \"Hallo!\";\r\nberiUcapan(halo);\r\nberiUcapan(\"Selamat datang di pemrograman Java\");\r\n</pre><h3>Fungsi yang Mengembalikan Nilai</h3><p>Pada kasus tertentu dibutuhkan sebuah fungsi yang dapat mengembalikan nilai output sehingga bisa diolah pada proses berikutnya. Pengembalian nilai pada fungsi menggunakan keyword return.</p><pre class=\"ql-syntax\" spellcheck=\"false\">static TypeDataKembalian namaFungsi(TipeData namaParameter){\r\n  // statement\r\n  return variabelOutput;\r\n}\r\n</pre><p>Contoh:</p><pre class=\"ql-syntax\" spellcheck=\"false\">static int luasPersegi(int sisi){\r\n  int luas = sisi * sisi;\r\n  return luas;\r\n}\r\n</pre><p>Pada contoh tersebut, dibuat sebuah parameter bernama sisi. Kemudian fungsi akan mengembalikan output dengan tipe int (integer) dari variabel luas. Cara pemanggilan fungsi tersebut adalah seperti berikut:</p><pre class=\"ql-syntax\" spellcheck=\"false\">System.out.println(\"Luas Persegi dengan sisi 5 = \" + luasPersegi(5));\r\nint luasan = luasPersegi(6);\r\n</pre><p><br></p>', 'https://www.youtube.com/embed/gHEXYYS-KAo', 1, '2023-06-01 07:57:10', '2023-06-01 07:57:10', NULL),
(13, 'Fungsi Rekursif', 9, '<h2><span class=\"ql-size-large\">Fungsi Rekursif</span></h2><p><br></p><h2>Teori</h2><p>Fungsi rekursif adalah fungsi yang memanggil dirinya sendiri. Hal ini bisa terjadi karena di dalam suatu fungsi rekursi, terdapat statement/baris program yang memanggil fungsi itu sendiri. Ketika suatu fungsi rekursif dipanggil/dijalankan dan kemudian proses eksekusi sudah sampai pada statement pemanggilan fungsi itu sendiri, maka fungsi tersebut akan dipanggil/dijalankan kembali. Dan LAGI, ketika proses eksekusi sudah sampai pada statement pemanggilan fungsi itu sendiri, maka fungsi tersebut akan dipanggil/dijalankan kembali, BEGITU SETERUSNYA hingga didapatkan suatu KONDISI AKHIR dimana proses pemanggilan fungsi tersebut tidak dilakukan lagi. Jika kondisi akhir tersebut tidak ditemukan/tidak ada, maka fungsi tersebut akan dipanggil terus menerus (infinite loop) dan ini tidak diperbolehkan.</p><p>Pada fungsi rekursif, terdapat dua komponen blok kode, yaitu:</p><ul><li><strong>Base Case</strong>: kode program yang menunjukkan sebuah batas berhenti dari proses rekursif, sehingga apabila nilai batas ini terpenuhi maka proses rekursif diakhiri.</li><li><strong>Recursion Call</strong>&nbsp;atau&nbsp;<strong>Reduction Step</strong>: kode program untuk melakukan pemanggilan terhadap dirinya sendiri.</li></ul><p>Pada umumnya, format fungsi rekursif mempunyai bentuk sebagai berikut:</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">if</span> (nilai batas) {\r\n    <span class=\"hljs-comment\">// menyelesaikan masalah</span>\r\n} <span class=\"hljs-keyword\">else</span> {\r\n    <span class=\"hljs-comment\">// mendefinisikan kembali masalah menggunakan rekursi</span>\r\n}\r\n</pre><p>Cabang IF merupakan base case, sedangkan ELSE merupakan recursion call. Agar rekursi dapat berhenti, recursion call harus mendekati base case di setiap pemanggilan fungsi rekursif.</p><p>Berdasarkan penjelasan tersebut, sekilas terlihat seperti fungsi tersebut dijalankan secara berulang-ulang, dan fungsi rekursif memang biasanya digunakan pada kasus-kasus perulangan. Perhatikan fungsi&nbsp;<strong>tampilDeret()</strong>&nbsp;di bawah ini.</p><pre class=\"ql-syntax\" spellcheck=\"false\">public <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">Deret</span> {\r\n\r\n    <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">tampilDeret</span>(<span class=\"hljs-params\">int x</span>) {\r\n        <span class=\"hljs-keyword\">if</span> (x &gt; <span class=\"hljs-number\">0</span>) {\r\n            <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(x + <span class=\"hljs-string\">\" \"</span>);\r\n            <span class=\"hljs-comment\">// memanggil fungsi tampilDeret() itu sendiri dengan nilai parameter n - 1</span>\r\n            <span class=\"hljs-title function_\">tampilDeret</span>(x - <span class=\"hljs-number\">1</span>);\r\n        } <span class=\"hljs-keyword\">else</span> {\r\n            <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">println</span>();\r\n        }\r\n    }\r\n\r\n    public <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span>  <span class=\"hljs-title function_\">main</span>(<span class=\"hljs-params\"><span class=\"hljs-built_in\">String</span>[] args</span>) {\r\n        <span class=\"hljs-comment\">// memanggil fungsi tampilDeret() dengan nilai parameter 5</span>\r\n        <span class=\"hljs-title function_\">tampilDeret</span>(<span class=\"hljs-number\">5</span>);\r\n    }\r\n}\r\n</pre><p>Pada contoh fungsi rekursif tersebut, fungsi tampilDeret pertema kali dijalankan (di dalam fungsi main) dengan mengirimkan nilai parameter 5 menggunakan perintah tampilDeret(5). Dari proses pemanggilan fungsi tersebut akan ditampilkan nilai parameternya yaitu 5 dan diikuti dengan pemanggilan fungsi tampilDeret(4). Selanjutnya, dari proses pemanggilan fungsi tersebut akan ditampilkan nilai parameternya yaitu 4 dan diikuti dengan pemanggilan fungsi tampilDeret(3). Selanjutnya, dari proses pemanggilan fungsi tersebut akan ditampilkan nilai parameternya yaitu 3 dan diikuti dengan pemanggilan fungsi tampilDeret(2). Selanjutnya, dari proses pemanggilan fungsi tersebut akan ditampilkan nilai parameternya yaitu 2 dan diikuti dengan pemanggilan fungsi tampilDeret(1). Dari proses pemanggilan fungsi tersebut akan ditampilkan nilai parameternya yaitu 1 dan diikuti dengan pemanggilan fungsi tampilDeret(0). Dari proses pemanggilan fungsi tersebut maka akan ditampilkan ganti baris dan tidak ada pemanggilan fungsi tampilDeret selanjutnya (pemanggilan fungsi rekursif sudah selesai).</p><pre class=\"ql-syntax\" spellcheck=\"false\">tampilDeret(5)\r\n    5 -&gt; tampilDeret(4)\r\n        4 -&gt; tampilDeret(3)\r\n            3 -&gt; tampilDeret(2)\r\n                2 -&gt; tampilDeret(1)\r\n                    1 -&gt; tampilDeret(0)\r\n</pre><p>Tampilan yang muncul dari hasil pemanggilan fungsi&nbsp;<code style=\"background-color: rgb(247, 247, 247); color: inherit;\">tampiDeret()</code>&nbsp;adalah:</p><pre class=\"ql-syntax\" spellcheck=\"false\">5 4 3 2 1\r\n</pre><p><br></p>', 'https://www.youtube.com/embed/wdrSmK18nj4', 1, '2023-06-01 07:59:09', '2023-06-01 07:59:09', NULL);

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  `id` int UNSIGNED NOT NULL,
  `course_name` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
  `description` text COLLATE utf8mb4_unicode_ci NOT NULL,
  `image` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
  `published` int NOT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
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(1, 'Java', 'Java is a high-level, class-based, object-oriented programming language that is designed to have as few implementation dependencies as possible', 'Try', 1, '2022-05-31 01:12:34', '2022-05-31 01:12:34');

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-- Table structure for table `essay_question`
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CREATE TABLE `essay_question` (
  `id` bigint UNSIGNED NOT NULL,
  `question_id` int UNSIGNED NOT NULL,
  `user_id` bigint UNSIGNED NOT NULL,
  `question` text COLLATE utf8mb4_unicode_ci NOT NULL,
  `answer` text COLLATE utf8mb4_unicode_ci NOT NULL,
  `answer2` text COLLATE utf8mb4_unicode_ci,
  `answer3` text COLLATE utf8mb4_unicode_ci,
  `answer4` text COLLATE utf8mb4_unicode_ci,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL,
  `deleted_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

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-- Dumping data for table `essay_question`
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INSERT INTO `essay_question` (`id`, `question_id`, `user_id`, `question`, `answer`, `answer2`, `answer3`, `answer4`, `created_at`, `updated_at`, `deleted_at`) VALUES
(1, 1, 1, 'Mengapa variabel panjang, lebar, tinggi, vBalok dan lBalok bertipe data int?', 'Karena nilai dari variabel tersebut berbentuk bilangan bulat', 'Variabel panjang, lebar, tinggi, vBalok dan lBalok bertipe data int karena nilai yang disimpan pada variabel tersebut adalah bilangan bulat.', 'Variabel tersebut menggunakan tipe data int karena nilai yang disimpannya adalah bilangan bulat tanpa koma.', 'Variabel tersebut menggunakan tipe data int karena nilai yang disimpannya adalah angka bulat. Oleh karena itu, tipe data int cocok untuk penyimpanan.', '2023-06-01 08:11:49', '2024-03-23 11:53:07', NULL),
(2, 1, 1, 'Jelaskan langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas!', 'Langkah-langkah perhitungan volume balok adalah mengalikan panjang, lebar, dan tinggi balok. Sedangkan langkah-langkah perhitungan luas permukaan balok adalah menghitung jumlah sisi-sisi balok (2 sisi panjang * lebar, 2 sisi panjang * tinggi, dan 2 sisi lebar * tinggi) kemudian menjumlahkannya', 'Volume balok dihitung dengan mengalikan panjang, lebar, dan tinggi menggunakan operator perkalian. Luas balok dihitung dengan menjumlahkan sisi-sisi balok yaitu 2 sisi panjang dikali lebar ditambah 2 sisi panjang dikali tinggi ditambah 2 sisi lebar dikali tinggi.', 'Menggunakan rumus volume balok, yaitu panjang * lebar * tinggi, untuk menghitung volumenya. Menggunakan rumus luas permukaan balok, yaitu 2*(panjang * lebar + panjang * tinggi + lebar * tinggi), untuk menghitung luas permukaannya.', 'Menghitung volume balok menggunakan rumus panjang * lebar * tinggi yang disimpan pada variable vBalok. Kemudian untuk menghitung luas permukaan balok menggunakan rumus 2*(panjang * lebar + panjang * tinggi + lebar * tinggi) yang disimpan pada variable lBalok.', '2023-06-01 08:11:49', '2024-03-23 11:53:07', NULL),
(3, 1, 1, 'Bagaimana cara mengubah nilai panjang, lebar, dan tinggi balok pada kode program ini?', 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, Anda dapat mengganti nilai pada bagian panjang = 10, lebar = 6, dan tinggi = 7 dengan nilai yang diinginkan.', 'Cara mengubah nilai panjang, lebar, dan tinggi dengan mengganti atau menginput nilai baru sesuai kebutuhan. Misalnya, panjang = 12, lebar = 8, dan tinggi = 5.', 'Langkah pertama adalah mencari bagian kode yang mendefinisikan nilai awal variabel panjang, lebar, dan tinggi. Kemudian ubah nilainya sesuai keinginan. Misalnya, jika ingin mengubah panjang menjadi 15, lebar menjadi 8, dan tinggi menjadi 9, ubah nilai variabel panjang, lebar, dan tinggi menjadi 15, 8, dan 9.', 'Dapat mengubah nilai panjang, lebar, dan tinggi langsung di dalam kode program. Cukup ubah nilai variabel panjang, lebar, dan tinggi sesuai dengan nilai yang diinginkan.', '2023-06-01 08:11:49', '2024-03-23 11:53:07', NULL),
(4, 2, 1, 'Apakah fungsi “if” dalam kode program diatas?', 'If digunakan dalam kode tersebut untuk membuat kondisi atau pernyataan logis. Dalam konteks kode tersebut, if digunakan untuk melakukan pengecekan apakah nilai lebih besar dari 70. Jika kondisi tersebut terpenuhi, yaitu nilai lebih besar dari 70, maka pesan \"Selamat anda lulus!\" akan dicetak. If digunakan untuk memberikan pengambilan keputusan berdasarkan kondisi tertentu, yang memungkinkan eksekusi kode yang berbeda tergantung pada hasil kondisi yang dievaluasi.', 'Dalam kode program tersebut, if digunakan untuk memeriksa apakah nilai variabel \"nilai\" lebih besar dari 70, sehingga bertindak sebagai filter untuk menentukan pesan \"Selamat anda lulus!\" akan ditampilkan atau tidak.', 'Dalam hal ini, if digunakan untuk mengeksekusi pernyataan \"Selamat anda lulus!\" Hanya jika nilai variabel lebih besar dari 70.', 'If digunakan untuk membuat keputusan berdasarkan kondisi tertentu.\r\nJika kondisi yang ditentukan terpenuhi (nilai > 70), pernyataan di blok if akan dieksekusi.', '2023-06-01 08:14:09', '2024-03-23 11:55:29', NULL),
(5, 2, 1, 'Jelaskan alur program dari kode program diatas!', 'Alur program dari kode di atas adalah sebagai berikut:\r\n\r\n•	Pertama, program akan menjalankan fungsi main yang merupakan titik masuk utama dalam program Java.\r\n•	Kemudian, sebuah variabel nilai dengan tipe data integer dideklarasikan dan diinisialisasi dengan nilai 80.\r\n•	Program akan melanjutkan ke blok if, yang akan mengevaluasi apakah nilai lebih besar dari 70.\r\n•	Jika kondisi dalam blok if (nilai > 70) bernilai true, program akan mengeksekusi pernyataan yang ada di dalam blok if, yaitu mencetak string \"Selamat anda lulus!\" menggunakan System.out.print().\r\n•	Jika kondisi dalam blok if bernilai false, program akan melanjutkan ke pernyataan setelah blok if dan program akan selesai.', 'Menginisialisasi variabel nilai dengan nilai 80. Selanjutnya, program akan mengecek kondisi menggunakan pernyataan if. Jika nilai variabel nilai lebih besar dari 70, maka kondisi pernyataan di dalam if akan dieksekusi. Karena nilai variabel nilai adalah 80 (lebih besar dari 70), pernyataan \"Selamat anda lulus!\" akan dicetak menggunakan System.out.print(\"Selamat anda lulus!\");.', 'Program dimulai dengan mendeklarasikan variabel nilai dan menginisialisasinya dengan nilai 80. Program kemudian mengevaluasi kondisi \"nilai> 70\" dalam blok if untuk menentukan apakah pernyataan yang ada di dalamnya dieksekusi. Blok pernyataan di dalam if dijalankan karena nilai variabel nilai adalah 80 (lebih besar dari 70). Saat menjalankannya, pesan \"Selamat anda lulus!\" akan ditampilkan.', 'Langkah awal kode program tersebut mendeklarasikan variabel nilai dan menginisialisasinya dengan nilai 80. Program kemudian mengevaluasi apakah nilai variabel nilai lebih besar dari 70. Jika nilai variabel nilai memenuhi kondisi (lebih besar dari 70), pernyataan di dalam blok if akan dieksekusi. Karena nilai variabel nilai adalah 80 (lebih besar dari 70), pesan \"Selamat anda lulus!\" akan ditampilkan sebagai output dari program. Setelah menjalankan blok if, program akan selesai dieksekusi karena tidak ada pernyataan lanjutan setelahnya.', '2023-06-01 08:14:09', '2024-03-23 11:55:29', NULL),
(6, 2, 1, 'Apakah output yang dihasilkan dari program jika nilai dari variabel “nilai” kurang dari 70?', 'Jika nilai variabel “nilai” kurang dari 70, maka tidak akan ada output yang ditampilkan, karena tidak ada pernyataan lain setelah kondisi if.', 'Jika nilai dari variabel \"nilai\" kurang dari 70, maka blok kode dalam kondisi if tidak akan dieksekusi. Dalam hal ini, tidak akan ada output yang dihasilkan dari program.', 'Jika nilai dari variabel \"nilai\" kurang dari 70, maka program akan langsung selesai setelah blok if tidak terpenuhi. Output dari program tidak akan terdefinisi karena tidak ada perintah output yang dijalankan.', 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada perintah output yang dijalankan. Program akan selesai tanpa memberikan pesan atau tindakan tambahan apa pun.', '2023-06-01 08:14:09', '2024-03-23 11:55:29', NULL),
(7, 3, 1, 'Apa fungsi dari penggunaan if-else pada baris kode diatas?', 'If-else digunakan untuk membagi kondisi menjadi dua kemungkinan. Dalam studi kasus diatas, IF digunakan untuk melakukan pengecekan apakah nilai itemCost lebih besar dari 24. Jika kondisi tersebut terpenuhi, maka variabel order bernilai \"High Value Item!\" akan dicetak. Sedangkan jika nilai itemCost tidak lebih dari 24, maka variabel order bernilai “Low Order Value!”', 'Fungsi dari penggunaan if-else adalah untuk menentukan kategori barang berdasarkan harga. Jika harga barang lebih dari 24.00, maka kategori barang akan ditetapkan sebagai \"High Value Item!\", jika tidak, maka kategori barang akan ditetapkan sebagai \"Low Value Item!\".', 'If-else digunakan untuk memilih pesan yang akan ditampilkan berdasarkan harga barang. Jika itemCost > 24.00, maka pesan yang ditampilkan akan berupa \"High Value Item!\", jika tidak, maka pesan yang ditampilkan akan berupa \"Low Value Item!\".', 'If-else digunakan untuk mengatur tindakan yang akan diambil berdasarkan harga barang. Jika itemCost > 24.00, maka tindakan yang diambil adalah menetapkan pesanan sebagai \"High Value Item!\", jika tidak, maka tindakan yang diambil adalah menetapkan pesanan sebagai \"Low Value Item!\".', '2023-06-01 08:16:58', '2024-03-23 11:57:25', NULL),
(8, 3, 1, 'Jelaskan alur program dari baris kode diatas!', '•	Mendeklarasikan kelas Order.\r\n•	Mendeklarasikan method main sebagai method utama yang akan dieksekusi saat program dijalankan.\r\n•	Mendeklarasikan variabel itemCost dengan tipe data double dan memberikannya nilai 30.99.\r\n•	Mendeklarasikan variabel order dengan tipe data String dan memberikannya nilai awal berupa string kosong (\"\").\r\n•	Melakukan pengecekan kondisi menggunakan pernyataan if. Kondisi yang dievaluasi adalah itemCost > 24.00.\r\n•	Jika kondisi tersebut benar (nilai itemCost lebih besar dari 24.00), maka blok kode di dalam if akan dieksekusi.\r\n•	Dalam blok if, nilai variabel order diubah menjadi \"High Value Item!\".\r\n•	Jika kondisi dalam if tidak terpenuhi (nilai itemCost tidak lebih besar dari 24.00), maka blok kode di dalam else akan dieksekusi.\r\n•	Dalam blok else, nilai variabel order diubah menjadi \"Low Value Item!\".\r\n•	Setelah blok if-else selesai dieksekusi, pesan yang ada dalam variabel order akan dicetak menggunakan System.out.print.\r\n•	Output yang ditampilkan akan bergantung pada nilai itemCost. Jika itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan dicetak. Jika tidak, maka pesan \"Low Value Item!\" akan dicetak.', 'Program di atas merupakan program sederhana untuk menentukan status suatu pesanan berdasarkan harga barang. Berikut adalah alur programnya: Mendeklarasikan kelas Order yang merupakan kelas utama program. Di dalam method main, mendeklarasikan variabel itemCost dengan tipe data double dan memberikannya nilai 30.99, serta variabel order dengan tipe data String dan tanpa nilai awal. Menggunakan struktur kontrol if-else untuk mengevaluasi harga barang. Pada kondisi if, jika itemCost lebih besar dari 24.00, variabel order akan diisi dengan string \"High Value Item!\", sedangkan jika tidak memenuhi kondisi if (itemCost <= 24.00), variabel order akan diisi dengan string \"Low Value Item!\". Mencetak nilai variabel order menggunakan System.out.print.', 'Alur program dari baris kode di atas adalah sebagai berikut: Mendeklarasikan kelas Order yang berisi method main sebagai method utama yang akan dieksekusi pertama kali saat program dijalankan. Di dalam method main, terdapat deklarasi variabel itemCost yang bertipe data double dan diberi nilai 30.99, merepresentasikan biaya barang. Deklarasi variabel order dengan tipe data String yang belum diinisialisasi (nilai awalnya kosong). Program menggunakan struktur kontrol if-else untuk mengevaluasi nilai itemCost. Jika nilai itemCost lebih besar dari 24.00, maka kondisi if terpenuhi, dan variabel order akan diisi dengan string \"High Value Item!\". Jika tidak, maka kondisi else akan dieksekusi, dan variabel order akan diisi dengan string \"Low Value Item!\". Setelah nilai variabel order ditentukan berdasarkan harga barang, program mencetak nilai variabel order ke konsol menggunakan System.out.print. Dengan demikian, program tersebut bertujuan untuk memberikan status pesanan (\"High Value Item!\" atau \"Low Value Item!\") berdasarkan nilai itemCost. Jika itemCost lebih dari 24.00, pesanan dianggap bernilai tinggi, dan sebaliknya.', 'Variabel biaya barang (itemCost) diinisialisasi dengan nilai 30.99. Jika itemCost > 24.00, maka pesan yang ditampilkan akan berupa \"High Value Item!\", jika tidak, maka pesan yang ditampilkan akan berupa \"Low Value Item!\". Pesan dicetak menggunakan System.out.print.', '2023-06-01 08:16:58', '2024-03-23 11:57:25', NULL),
(9, 3, 1, 'Apa yang akan ditampilkan sebagai output program ini, jika nilai variabel “itemCost” adalah 20?', 'Program akan menampilkan output “Low Value Item”', 'Jika nilai variabel \"itemCost\" adalah 20, maka kondisi dalam if-statement akan bernilai false. Karena nilai \"itemCost\" tidak lebih besar dari 24.00, program akan menjalankan blok else. Sehingga output dari program adalah \"Low Value Item!\".', 'Ketika nilai variabel \"itemCost\" adalah 20, maka kondisi if-statement akan dinilai false. Program akan menjalankan blok else, yang menetapkan nilai \"order\" menjadi \"Low Value Item!\". Output dari program adalah \"Low Value Item!\".', 'Jika nilai variabel \"itemCost\" adalah 20, maka kondisi akan bernilai false. Karena nilai \"itemCost\" tidak memenuhi syarat untuk kondisi if, program akan menjalankan blok else dan menetapkan nilai \"order\" sebagai \"Low Value Item!\".', '2023-06-01 08:16:58', '2024-03-23 11:57:25', NULL),
(10, 4, 1, 'Apakah fungsi dari baris program default?', 'Dengan menggunakan default, program akan menangani situasi di mana nilai shipping tidak cocok dengan case-case yang didefinisikan sebelumnya. Default berfungsi sebagai pilihan terakhir yang akan dieksekusi jika tidak ada case yang cocok dengan nilai yang dievaluasi.', 'Baris program default digunakan untuk menangani situasi ketika nilai dari variabel \"shipping\" tidak cocok dengan salah satu kasus yang telah ditentukan dalam switch statement. Dalam hal ini, jika nilai \"shipping\" tidak sama dengan \"Regular\" atau \"Express\", maka program akan menjalankan blok kode dalam default untuk menetapkan nilai \"shippingCost\".', 'Baris program default berfungsi sebagai opsi alternatif atau fallback jika tidak ada case yang cocok dengan nilai dari variabel \"shipping\". Ini memastikan bahwa jika tidak ada opsi yang cocok, program tidak akan mengalami kesalahan dan akan tetap melanjutkan eksekusi dengan menggunakan nilai default.', 'Default digunakan untuk mengatasi kesalahan input atau kondisi yang tidak terduga dalam program. Jika nilai \"shipping\" tidak sesuai dengan kasus yang telah ditentukan sebelumnya, default akan menetapkan nilai \"shippingCost\" ke nilai yang telah ditentukan (0.50 dalam kasus ini) untuk menangani situasi tersebut.', '2023-06-01 08:18:42', '2024-03-23 11:59:15', NULL),
(11, 4, 1, 'Jelaskan alur program dari baris kode switch – case diatas!', 'Alur program dari baris kode switch-case di atas adalah sebagai berikut:\r\n\r\nProgram dimulai dengan mendeklarasikan variabel shipping dengan nilai \"Express\" dan variabel shippingCost tanpa nilai awal. Kemudian, program melanjutkan ke switch statement dengan mengevaluasi nilai dari variabel shipping. \r\n\r\nProgram akan membandingkan nilai shipping dengan setiap case yang ada. Jika nilai shipping cocok dengan salah satu case, program akan melompat ke blok kode yang sesuai dengan case tersebut.\r\nJika nilai shipping adalah \"Regular\", maka variabel shippingCost akan diatur menjadi 0.\r\nJika nilai shipping adalah \"Express\", maka variabel shippingCost akan diatur menjadi 1.75.\r\nJika nilai shipping tidak cocok dengan case-case di atas, program akan melompat ke blok kode dalam default.\r\nPada blok kode default, variabel shippingCost akan diatur menjadi 0.50.\r\n\r\nSetelah switch statement selesai dieksekusi, program akan mencetak nilai shippingCost dengan menggunakan pernyataan System.out.print(\"Shipping cost: \" + shippingCost);.\r\nDengan demikian, alur program akan menentukan nilai shippingCost berdasarkan nilai shipping yang dievaluasi menggunakan switch-case.', 'Alur program dari baris kode switch-case di atas adalah sebagai berikut:\r\n     Variabel \"shipping\" dideklarasikan dan diinisialisasi dengan nilai \"Express\". Dilakukan pernyataan switch pada variabel \"shipping\". Program mengevaluasi nilai variabel \"shipping\" dan mencocokkannya dengan setiap case dalam switch-case. Jika nilai \"shipping\" cocok dengan salah satu case, maka blok kode di dalam case tersebut akan dieksekusi. Jika nilai \"shipping\" adalah \"Regular\", maka nilai variabel \"shippingCost\" akan diatur menjadi 0. Jika nilai \"shipping\" adalah \"Express\", maka nilai variabel \"shippingCost\" akan diatur menjadi 1.75.\r\nJika tidak ada case yang cocok dengan nilai \"shipping\", maka blok kode di dalam default case akan dieksekusi. Di sini, nilai variabel \"shippingCost\" akan diatur menjadi 0.50. Setelah nilai variabel \"shippingCost\" ditetapkan berdasarkan case yang cocok, program akan mencetak nilai \"shippingCost\" sebagai biaya pengiriman.', 'Pertama, variabel \"shipping\" dideklarasikan dan diinisialisasi dengan nilai \"Express\". Kemudian, dilakukan pengecekan kondisi variabel \"shipping\" dalam struktur switch-case. Program akan mengevaluasi nilai \"shipping\" dan mencocokkannya dengan setiap case yang ada dalam switch-case. Jika nilai \"shipping\" cocok dengan salah satu case, maka blok kode di dalam case tersebut akan dieksekusi. Jika nilai \"shipping\" sama dengan \"Regular\", maka nilai variabel \"shippingCost\" akan diatur menjadi 0. Jika nilai \"shipping\" sama dengan \"Express\", maka nilai variabel \"shippingCost\" akan diatur menjadi 1.75. Jika tidak ada case yang cocok dengan nilai \"shipping\", maka blok kode di dalam default case akan dieksekusi. Di sini, nilai variabel \"shippingCost\" akan diatur menjadi 0.50. Setelah nilai variabel \"shippingCost\" ditetapkan berdasarkan case yang cocok atau default, program akan mencetak nilai \"shippingCost\" sebagai biaya pengiriman.', 'Variabel \"shipping\" diinisialisasi dengan nilai \"Express\". Nilai \"shipping\" dibandingkan dengan setiap case dalam switch-case. Jika \"shipping\" cocok dengan case \"Regular\", \"shippingCost\" diatur menjadi 0. Jika \"shipping\" cocok dengan case \"Express\", \"shippingCost\" diatur menjadi 1.75. Jika tidak ada case yang cocok, maka nilai default \"shippingCost\" adalah 0.50. Program mencetak nilai \"shippingCost\" sebagai biaya pengiriman.', '2023-06-01 08:18:42', '2024-03-23 11:59:15', NULL),
(12, 4, 1, 'Kapan shippingCost bernilai 0.05?', 'Pada saat nilai shipping tidak bernilai regular maupun express, sehingga mengeluarkan nilai default, yaitu 0.05', 'Jika pernyataan default digunakan pada switch statement karena nilai variabel \"shipping\" tidak cocok dengan kasus yang ada, maka shippingCost akan diatur ke 0.05.', 'Jika nilai variabel \"shipping\" tidak cocok dengan kasus \"Regular\" dan \"Express\", maka default case akan dieksekusi dan shippingCost akan diatur ke 0.05.', 'shippingCost akan bernilai 0.05 jika tidak ada case yang cocok dengan nilai variabel \"shipping\" dan default case dieksekusi.', '2023-06-01 08:18:42', '2024-03-23 11:59:15', NULL),
(13, 5, 1, 'Mengapa variabel isMember bertipe data Boolean?', 'Karena variabel isMember di rancang untuk menampung nilai salah atau benar', 'Variabel ini digunakan untuk mewakili status keanggotaan pelanggan, yang hanya memiliki dua nilai, yaitu true (anggota) atau false (non-anggota). Tipe data Boolean tepat untuk menyimpan nilai-nilai yang hanya memiliki dua kemungkinan.', 'variabel isMember digunakan dalam struktur kondisional (if-else) untuk menentukan jenis diskon yang akan diberikan berdasarkan status keanggotaan. Tipe data Boolean cocok digunakan dalam kondisi seperti ini karena hanya memiliki dua nilai yang relevan: true atau false.', 'Dalam konteks program ini, isMember digunakan untuk menentukan jenis diskon yang berlaku. Dengan menggunakan tipe data Boolean, kode program menjadi lebih mudah dipahami dan sesuai dengan kebutuhan, karena hanya perlu memeriksa apakah seseorang adalah anggota atau bukan.', '2023-06-01 08:21:08', '2024-03-23 12:01:06', NULL),
(14, 5, 1, 'Jelaskan alur program diatas, jika diketahui nilai isMember adalah false!', '•	Jika nilai isMember adalah false, maka program akan masuk kedalam pemilihan else.\r\n•	Program akan melakukan pengecekan total. Diketahui total adalah 200000, sehingga masuk kedalam blok pemilihan ketiga dengan diskon 15 %\r\n•	Sehingga, output dari program tersebut adalah “diskon yang didapatkan adalah 15%”', 'Ketika isMember memiliki nilai false dalam program ini, artinya pelanggan bukanlah anggota dari toko buku. Dalam kondisi ini, program akan menetapkan diskon berdasarkan total belanja. Program akan menguji nilai total untuk menentukan besarnya diskon yang akan diberikan. Jika total belanja kurang dari 100000, diskon akan diatur menjadi 5%. Jika total belanja berada di antara 100000 dan 150000, diskon akan menjadi 10%. Namun, jika total belanja melebihi 150000, maka diskon akan menjadi 15%. Dalam kasus nilai total belanja sebesar 200000, karena melebihi 150000, maka diskon yang diberikan adalah sebesar 15%. Setelah itu, program akan mencetak pesan yang menyatakan jumlah diskon yang didapatkan oleh pelanggan.', 'Ketika isMember bernilai false, program akan menentukan diskon berdasarkan total belanja. Jika total belanja melebihi 150000, diskon adalah 15%. Dalam kasus nilai total belanja 200000, diskon akan menjadi 15%, yang kemudian dicetak oleh program.', 'Program dimulai dengan mendeklarasikan beberapa variabel, yaitu isMember yang diset sebagai false, total yang memiliki nilai 200000, dan diskon yang diinisialisasi dengan nilai 0. Kemudian, program masuk ke dalam blok if-else statement. Karena nilai isMember adalah false, program akan mengeksekusi blok else. Di dalam blok else, terdapat serangkaian kondisi if-else if-else untuk menentukan besarnya diskon berdasarkan nilai total pembelanjaan. Pertama, program mengecek apakah nilai total kurang dari 100000. Karena nilai total adalah 200000, maka kondisi ini tidak terpenuhi. Kemudian, program mengecek apakah nilai total berada di antara 100000 dan 150000. Karena total adalah 200000, maka kondisi ini juga tidak terpenuhi. Terakhir, karena kedua kondisi sebelumnya tidak terpenuhi, program mengeksekusi blok else terakhir. Di sini, diskon diatur menjadi 15 karena nilai total melebihi 150000. Setelah itu, program mencetak hasil diskon yang didapatkan, yang dalam kasus ini adalah \"diskon yang didapatkan adalah 15%\".', '2023-06-01 08:21:08', '2024-03-23 12:01:06', NULL),
(15, 5, 1, 'Apakah output program jika nilai variabel “total” bernilai Rp.30.000?', 'program akan mengeluarkan output “diskon yang didapatkan adalah 10%”', 'Karena nilai variabel \"total\" adalah Rp.30.000 dan nilai \"isMember\" adalah true, maka program akan mengeksekusi blok if pertama. Dalam blok if pertama, nilai \"total\" kurang dari Rp.100.000 sehingga diskon akan diatur menjadi 10%. Namun, karena nilai \"total\" tidak memenuhi syarat, maka program akan beralih ke blok else. Dalam blok else, karena nilai \"total\" kurang dari Rp.100.000, diskon akan diatur menjadi 5%. Sehingga output program akan menampilkan \"diskon yang didapatkan adalah 5%\".', 'Output: \"diskon yang didapatkan adalah 5%\". Karena nilai variabel \"total\" adalah Rp.30.000 dan \"isMember\" bernilai true, program akan memeriksa kondisi if pertama. Kondisi if pertama akan bernilai false karena nilai \"total\" tidak kurang dari Rp.100.000. Program akan beralih ke blok else dan mengecek kondisi di dalamnya. Kondisi dalam blok else akan bernilai true karena nilai \"total\" kurang dari Rp.100.000. Maka, diskon akan diatur menjadi 5%. Output program akan menampilkan \"diskon yang didapatkan adalah 5%\".', 'Jika isMember == true maka outputnya \"diskon yang didapatkan adalah 10%\". Jika false maka outputnya \"diskon yang didapatkan adalah 5%\".', '2023-06-01 08:21:08', '2024-03-23 12:01:06', NULL),
(16, 6, 1, 'Apakah kegunaan i++ pada perulangan for diatas?', 'fungsi i++ memiliki fungsi sebagai operator penambahan', 'Kegunaan i++ dalam perulangan for adalah untuk meningkatkan nilai variabel i setiap kali iterasi loop dilakukan.\r\nDalam konteks ini, setiap kali iterasi dilakukan, nilai i akan bertambah satu.', 'i++ digunakan untuk menggerakkan iterasi perulangan for ke nilai selanjutnya. Saat iterasi dilakukan, nilai i akan ditingkatkan, sehingga perulangan akan melanjutkan eksekusi ke langkah berikutnya.', 'i++ sangat penting untuk menghindari perulangan tanpa batas. Dengan menambah nilai i setiap iterasi, kita memastikan bahwa perulangan akan berhenti ketika kondisi berhenti terpenuhi.', '2023-06-01 08:22:55', '2024-03-23 12:02:56', NULL),
(17, 6, 1, 'Jelaskan alur program perulangan diatas!', 'Program dimulai dengan mendeklarasikan variabel number dengan nilai 6. Kemudian, program melanjutkan ke for loop yang dimulai dengan inisialisasi variabel i dengan nilai 1. Setelah inisialisasi, program akan memeriksa kondisi “i < number”. Jika kondisi ini benar, program akan melanjutkan ke blok kode dalam for loop. \r\n\r\nDalam setiap iterasi, program akan mencetak nilai i menggunakan pernyataan System.out.print(i).\r\nSetelah mencetak nilai i, program akan melanjutkan ke pernyataan i++.\r\nPernyataan i++ akan menambahkan nilai i sebesar 1 setelah setiap iterasi, sehingga nilai i akan bertambah secara bertahap.\r\n\r\nProgram akan kembali memeriksa kondisi “i < number” dan akan terus berulang sampai kondisi “i < number”  tidak lagi terpenuhi. Ketika kondisi tidak terpenuhi, program keluar dari for loop dan selesai.', 'Program dimulai dengan mendeklarasikan kelas \"LuckyFive\" dengan method main. Dalam method main, variabel \"number\" diinisialisasi dengan nilai 6. Perulangan for digunakan untuk mengiterasi nilai variabel \"i\" dari 1 hingga kurang dari nilai variabel \"number\" (6). Pada setiap iterasi, nilai \"i\" akan dicetak ke layar tanpa diikuti spasi atau karakter lainnya. Perulangan akan berhenti saat nilai \"i\" sama dengan nilai variabel \"number\" (6). Setelah perulangan selesai, program akan selesai dijalankan.', 'Program ini memulai dengan menginisialisasi kelas \"LuckyFive\" dan method main. Variabel \"number\" diatur ke nilai 6. Perulangan for digunakan untuk mengulangi blok kode di dalamnya. Variabel \"i\" dimulai dari nilai 1 dan terus bertambah satu setiap iterasi hingga kurang dari 6. Setiap iterasi, nilai \"i\" dicetak tanpa spasi ke layar. Perulangan berakhir ketika nilai \"i\" mencapai nilai yang kurang dari 6. Setelah perulangan selesai, program berakhir.', 'Kode ini memulai dengan menginisialisasi kelas \"LuckyFive\" dan method main. Variabel \"number\" diinisialisasi dengan nilai 6. Perulangan for digunakan untuk melakukan serangkaian iterasi. Selama iterasi, variabel \"i\" mulai dari 1 dan terus bertambah satu setiap iterasi hingga mencapai nilai kurang dari 6. Pada setiap iterasi, nilai \"i\" dicetak ke layar tanpa ada spasi atau karakter tambahan. Proses perulangan akan berakhir saat nilai \"i\" mencapai angka kurang dari 6. Setelah iterasi terakhir, program akan selesai dieksekusi.', '2023-06-01 08:22:55', '2024-03-23 12:02:56', NULL),
(18, 6, 1, 'Apa output dari program jika nilai dari variabel number adalah 8?', 'Output program jika nilai variabel number 8 adalah 1234567', 'Ketika nilai variabel \"number\" adalah 8, maka iterasi akan berlangsung dari 1 hingga 7 (kurang dari 8). Setiap iterasi, nilai dari variabel i akan dicetak menggunakan System.out.print(). Sehingga output program adalah deret angka dari 1 hingga 7: \"1234567\".', 'Jika nilai variabel \"number\" adalah 8, maka loop akan berjalan dari 1 hingga 7 (kurang dari 8). Setiap nilai \"i\" akan dicetak menggunakan System.out.print() dalam setiap iterasi. Output program akan mencetak deret angka dari 1 hingga 7: \"1234567\".', 'Outputnya \"1234567\"', '2023-06-01 08:22:55', '2024-03-23 12:02:56', NULL),
(19, 7, 1, 'Apa kegunaan dari i++ pada kode program diatas?', 'Pada kode program tersebut, i++ digunakan sebagai operator penambahan (increment) pada variabel i.\r\n\r\nKegunaan dari i++ adalah untuk menambahkan nilai 1 pada variabel i setiap kali perulangan dilakukan. Dalam konteks kode program yang diberikan, setiap iterasi perulangan akan mencetak nilai i dan kemudian nilai i akan ditambah 1 menggunakan i++.\r\n\r\nSehingga, i++ berguna untuk mengatur aliran perulangan dan menghindari terjadinya perulangan tak terbatas (infinite loop) dengan memastikan bahwa kondisi perulangan pada while-loop (i < number) akan berhenti pada suatu titik saat nilai i mencapai nilai number yang ditentukan.', 'i++ digunakan untuk meningkatkan nilai variabel i setiap kali iterasi loop dilakukan. Ini memastikan bahwa nilai i akan terus bertambah seiring berjalannya perulangan, sehingga loop akan berhenti saat kondisi i < number tidak lagi terpenuhi.', 'Dengan menambahkan i++ setelah instruksi System.out.print(i), program memastikan bahwa setiap iterasi loop akan mencetak nilai i yang sesuai dan memperbarui nilai i untuk iterasi berikutnya. Ini membantu mengendalikan jalannya perulangan.', 'Menghindari Perulangan Tanpa Akhir: Tanpa i++, nilai i akan tetap sama dan kondisi i < number akan selalu terpenuhi. Dengan demikian, program akan terjebak dalam perulangan tanpa akhir. Dengan i++, nilai i bertambah setiap iterasi sehingga akhirnya kondisi perulangan tidak akan terpenuhi dan perulangan berhenti.', '2023-06-01 18:14:49', '2024-03-23 12:04:44', NULL),
(20, 7, 1, 'Jelaskan alur program dalam blok kode while!', 'Variabel number diinisialisasi dengan nilai 6, dan variabel i diinisialisasi dengan nilai 1. Kondisi i < number dievaluasi. Jika kondisi tersebut terpenuhi (nilai i kurang dari number), maka blok kode di dalam while loop akan dieksekusi. Jika kondisi tidak terpenuhi, maka program akan keluar dari loop. Di dalam loop, perintah System.out.print(i) akan mencetak nilai i ke layar. \r\n\r\nPada iterasi pertama, nilai i adalah 1, sehingga angka 1 akan dicetak. Selanjutnya, perintah i++ akan menambahkan nilai i sebesar 1. Proses di atas akan diulang terus menerus selama kondisi i < number masih terpenuhi. Pada setiap iterasi, nilai i akan bertambah 1 dan angka tersebut akan dicetak ke layar. \r\n\r\nLoop akan berhenti saat nilai i sama dengan atau melebihi nilai number, yaitu saat i bernilai 6. Setelah loop selesai, program akan keluar dari blok while dan program akan berakhir.', 'Inisialisasi Variabel: Variabel \"number\" diinisialisasi dengan nilai 6 dan variabel \"i\" diinisialisasi dengan nilai 1. Pengecekan Kondisi: Program memeriksa apakah nilai \"i\" kurang dari nilai \"number\". Jika kondisi ini terpenuhi, langkah berikutnya akan dieksekusi. Cetak Nilai Variabel i: Jika kondisi terpenuhi, program akan mencetak nilai variabel \"i\" menggunakan System.out.print(). Peningkatan Nilai i: Setelah nilai variabel \"i\" dicetak, nilai \"i\" akan ditingkatkan dengan menggunakan operator increment (i++). Kembali ke Pengecekan Kondisi: Setelah nilai \"i\" ditingkatkan, program kembali ke tahap pengecekan kondisi. Jika nilai \"i\" masih kurang dari nilai \"number\", program akan kembali mencetak nilai \"i\" dan meningkatkan nilai \"i\" lagi. Proses ini terus berulang sampai nilai \"i\" tidak lagi kurang dari \"number\". Selesai: Ketika nilai \"i\" tidak lagi kurang dari \"number\", loop while akan berhenti dan program selesai dieksekusi.', 'Persiapan Variabel: Awalnya, program menyiapkan dua variabel, yaitu \"number\" yang diisi dengan nilai 6 dan \"i\" yang diinisialisasi dengan nilai 1. Pengecekan Batasan: Program memeriksa apakah nilai \"i\" masih lebih kecil dari nilai \"number\". Jika ya, proses akan dilanjutkan; jika tidak, program akan keluar dari loop. Cetak Nilai: Jika kondisi masih terpenuhi, nilai dari variabel \"i\" akan dicetak menggunakan perintah cetak (print). Peningkatan Variabel: Setelah nilai \"i\" dicetak, nilai \"i\" akan ditingkatkan sebesar 1. Pengecekan Kembali: Program kembali ke tahap pengecekan batasan untuk memastikan apakah nilai \"i\" masih memenuhi syarat untuk berlanjut dalam loop. Penyelesaian: Proses ini akan terus berulang sampai nilai \"i\" tidak lagi lebih kecil dari \"number\". Setelah itu, program akan keluar dari loop dan selesai dieksekusi.', 'Program menggunakan loop while untuk mencetak nilai variabel \"i\" selama nilai \"i\" kurang dari nilai \"number\". Setiap iterasi, nilai \"i\" akan dicetak dan kemudian ditingkatkan sebesar 1. Proses ini akan terus berlanjut hingga nilai \"i\" tidak lagi kurang dari \"number\", pada saat itu program akan keluar dari loop.', '2023-06-01 18:14:49', '2024-03-23 12:04:44', NULL),
(21, 7, 1, 'Jika kondisi dalam while diganti menjadi “while(i > number)”, apakah output yang dikeluarkan oleh program ?', 'Output dari kode program di atas adalah tidak ada. Hal ini dikarenakan kondisi pada while loop, yaitu i > number, tidak terpenuhi pada awalnya. Karena nilai awal i adalah 1 dan number adalah 6, maka kondisi 1 > 6 akan bernilai false. Oleh karena itu, blok kode dalam while loop tidak akan dieksekusi, sehingga tidak ada output yang dicetak ke layar', 'Karena nilai awal variabel \"i\" adalah 1 dan nilai variabel \"number\" adalah 6, maka kondisi \"while(i > number)\" tidak akan terpenuhi.\r\nKarena itu, blok while tidak akan dieksekusi, sehingga tidak akan ada output yang dihasilkan.', 'Karena nilai awal variabel \"i\" adalah 1 dan nilai variabel \"number\" adalah 6, kondisi \"while(i > number)\" tidak terpenuhi.\r\nProgram tidak akan masuk ke dalam blok while karena kondisinya salah. Sehingga, tidak ada output yang dihasilkan.', 'Tidak Ada Output Karena kondisi while tidak terpenuhi, program tidak akan masuk ke dalam loop.', '2023-06-01 18:14:49', '2024-03-23 12:04:44', NULL),
(22, 8, 1, 'Apakah fungsi dari baris kode “int next = first + second” ?', 'Pada program Fibonacci, fungsi dari kode “int next = first + second;” adalah untuk menghitung nilai angka selanjutnya dalam deret Fibonacci.\r\n\r\nPada setiap iterasi perulangan, nilai next dihitung dengan menjumlahkan nilai first dan second. Kemudian, nilai next akan menjadi angka baru dalam deret Fibonacci.\r\n\r\nMisalnya, pada awalnya first memiliki nilai 0 dan second memiliki nilai 1. Pada iterasi pertama, next akan dihitung sebagai 0 + 1 = 1. Setelah itu, nilai first akan diperbarui menjadi 1 dan nilai second akan diperbarui menjadi 1.\r\n\r\nPada iterasi berikutnya, next akan dihitung sebagai 1 + 1 = 2. Proses ini akan terus berlanjut sampai mencapai jumlah angka Fibonacci yang diinginkan.\r\n\r\nDengan mengupdate nilai first dan second setiap kali perulangan dilakukan, kita dapat menghasilkan deret Fibonacci dengan benar.', 'Baris kode tersebut menghitung bilangan Fibonacci berikutnya dengan menjumlahkan dua bilangan Fibonacci sebelumnya yang disimpan dalam variabel \"first\" dan \"second\". Hasilnya disimpan dalam variabel \"next\" untuk digunakan dalam iterasi berikutnya.', 'Baris kode tersebut bertujuan untuk menghasilkan bilangan Fibonacci berikutnya dalam deret Fibonacci. Dengan menambahkan dua bilangan Fibonacci sebelumnya, kita dapat menentukan bilangan Fibonacci berikutnya dalam deret tersebut.', 'Baris kode tersebut digunakan untuk menghitung dan menyimpan nilai bilangan Fibonacci berikutnya dalam variabel \"next\". Nilai \"next\" kemudian akan digunakan dalam iterasi selanjutnya dalam mencetak deret Fibonacci.', '2023-06-01 18:16:41', '2024-03-23 12:06:51', NULL),
(23, 8, 1, 'Jelaskan alur program dalam blok kode do-while diatas!', 'Variabel next diinisialisasi dengan hasil penjumlahan first dan second.\r\nNilai next dicetak menggunakan perintah System.out.print(next + \" \"), sehingga akan mencetak nilai next diikuti dengan spasi. Nilai first diperbarui dengan nilai second. Nilai second diperbarui dengan nilai next. \r\n\r\nVariabel i (yang merupakan counter) ditambahkan dengan 1 menggunakan perintah i++. Kondisi i <= n dievaluasi. Jika kondisi tersebut terpenuhi, maka program akan kembali ke langkah 1 dan melanjutkan iterasi berikutnya. Jika kondisi tidak terpenuhi, maka program akan keluar dari loop.\r\n\r\nLangkah-langkah 1-6 akan terus diulang sampai kondisi i <= n tidak terpenuhi.', 'Variabel \"n\" menyimpan nilai yang menunjukkan panjang dari deret Fibonacci yang ingin dihasilkan. Variabel \"first\" dan \"second\" digunakan untuk menyimpan dua angka pertama dari deret Fibonacci, yaitu 0 dan 1. Variabel \"i\" digunakan sebagai counter untuk menghitung iterasi. Pesan \"Deret Fibonacci: \" dicetak sebagai judul.\r\nDua angka pertama dari deret Fibonacci, yaitu \"first\" dan \"second\", dicetak. Di dalam blok do, dilakukan iterasi untuk menghasilkan angka-angka selanjutnya dalam deret Fibonacci. Selama nilai \"i\" masih kurang dari atau sama dengan nilai \"n\", langkah-langkah berikut dijalankan: Variabel \"next\" menampung hasil penjumlahan dari \"first\" dan \"second\", yang merupakan angka selanjutnya dalam deret Fibonacci. Angka \"next\" dicetak. Nilai variabel \"first\" diperbarui menjadi nilai variabel \"second\". Nilai variabel \"second\" diperbarui menjadi nilai variabel \"next\". Counter \"i\" ditingkatkan. Iterasi dilakukan hingga nilai \"i\" mencapai nilai \"n\". Proses ini akan menghasilkan deret Fibonacci sepanjang n sesuai dengan nilai yang dimasukkan ke dalam variabel \"n\".', 'Inisialisasi Variabel: Variabel \"n\" menentukan jumlah angka dalam deret Fibonacci yang akan dihasilkan. Variabel \"first\" dan \"second\" memuat dua angka pertama dalam deret Fibonacci, yaitu 0 dan 1. Variabel \"i\" digunakan sebagai penghitung iterasi untuk mengontrol berapa kali deret Fibonacci dihasilkan. Cetak Judul: \"Deret Fibonacci: \" dicetak sebagai judul untuk hasil output. Cetak Angka Awal: Dua angka pertama dari deret Fibonacci, yaitu \"first\" dan \"second\", dicetak.\r\nIterasi untuk Menghasilkan Deret Fibonacci: Program menggunakan do-while loop untuk melakukan iterasi untuk menghasilkan angka-angka berikutnya dalam deret Fibonacci. Setiap iterasi, variabel \"next\" dihitung sebagai penjumlahan dari dua angka terakhir dalam deret Fibonacci. Angka \"next\" dicetak sebagai bagian dari deret Fibonacci.\r\nVariabel \"first\" dan \"second\" diperbarui untuk menyesuaikan angka-angka terakhir dalam deret Fibonacci. Counter \"i\" ditingkatkan untuk melanjutkan iterasi. Pengecekan Batas: Iterasi dilakukan hingga jumlah iterasi mencapai atau melebihi nilai \"n\", sesuai dengan jumlah angka yang diinginkan dalam deret Fibonacci. Proses ini akan terus berlanjut hingga mencapai jumlah iterasi yang diinginkan, menghasilkan deret Fibonacci sesuai dengan panjang yang ditentukan oleh nilai variabel \"n\".', 'Program menghasilkan deret Fibonacci dengan jumlah elemen yang ditentukan oleh variabel \"n\". Tahapan program: Inisialisasi variabel: \"n\" untuk menentukan jumlah elemen, \"first\" dan \"second\" untuk dua elemen pertama, \"i\" sebagai penghitung iterasi. Cetak judul \"Deret Fibonacci: \". Cetak dua elemen pertama. Lakukan iterasi menggunakan do-while loop: Hitung dan cetak elemen berikutnya. Perbarui variabel \"first\" dan \"second\". Perbarui penghitung iterasi. Iterasi dilakukan hingga mencapai atau melebihi jumlah elemen yang diinginkan.', '2023-06-01 18:16:41', '2024-03-23 12:06:51', NULL),
(24, 8, 1, 'Jika nilai variabel n di ganti menjadi 7, output apakah yang akan dikeluarkan program?', '0 1 1 2 3 5 8 13 21', 'Program akan mencetak deret Fibonacci hingga ke-7 (n=7). Deret Fibonacci dimulai dari 0 dan 1, kemudian setiap angka berikutnya adalah penjumlahan dari dua angka sebelumnya. Sehingga output program akan mencetak deret Fibonacci: \"0 1 1 2 3 5 8 13 21\".', 'Program akan menghasilkan deret Fibonacci hingga bilangan ke-7, dimulai dari 0 dan 1. Setiap bilangan dalam deret Fibonacci dihasilkan dengan menambahkan dua bilangan sebelumnya. Sehingga, setelah 0 dan 1, angka berikutnya adalah penjumlahan dari 0 + 1 = 1, 1 + 1 = 2, 1 + 2 = 3, 2 + 3 = 5, 3 + 5 = 8, 5 + 8 = 13, dan seterusnya. Oleh karena itu, output program akan mencetak deret Fibonacci: \"0 1 1 2 3 5 8 13 21\".', 'Program akan menghasilkan deret Fibonacci hingga bilangan ke-7, dimulai dari 0 dan 1. Setiap angka dalam deret Fibonacci dihasilkan dengan menambahkan dua angka sebelumnya. Dengan kata lain, setiap angka dalam deret Fibonacci adalah hasil dari penjumlahan dua angka sebelumnya. Sehingga, output program akan mencetak deret Fibonacci: \"0 1 1 2 3 5 8 13 21\".', '2023-06-01 18:16:41', '2024-03-23 12:06:51', NULL),
(25, 9, 1, 'Apakah fungsi kondisi (i <=5) pada perulangan pertama (outer loop)?', 'Kode program tersebut berfungsi untuk menentukan jumlah baris piramida bintang. Jika 5 diganti menjadi 7, maka baris piramida menjadi 7 baris', 'Kondisi tersebut mengontrol jumlah baris yang akan dicetak. Dengan i bervariasi dari 1 hingga 5, perulangan luar akan mencetak 5 baris.', 'Dengan i bervariasi dari 1 hingga 5, setiap baris akan memiliki jumlah bintang yang sesuai dengan nilai i.', 'Kondisi tersebut digunakan untuk membentuk pola bertingkat dalam pola bintang. Saat i meningkat, jumlah bintang yang dicetak dalam satu baris juga bertambah sesuai dengan nilai i.', '2023-06-01 18:19:46', '2024-03-23 12:08:41', NULL),
(26, 9, 1, 'Jelaskan alur program dari perulangan kedua (inner loop) yang menggunakan variabel j!', 'Perulangan akan dimulai dari nilai 1 dan berakhir pada saat nilai “j” sama dengan atau kurang dari nilai “i”. Saat kondisi terpenuhi, satu bintang akan ditambahkan ke variabel “output”, jumlah bintang akan terus bertambah seiring dengan nilai “i” yang meningkat.', 'Program memulai perulangan pertama (outer loop) dengan nilai i mulai dari 1 hingga 5, sesuai dengan jumlah baris yang ingin dibuat dalam piramida. Pada setiap iterasi perulangan pertama, program memulai perulangan kedua (inner loop) dengan nilai j mulai dari 1 hingga i. Pada setiap iterasi perulangan kedua, program mencetak sebuah bintang (*) ke dalam variabel output. Jumlah bintang (*) yang dicetak pada setiap iterasi perulangan kedua (inner loop) akan bertambah sesuai dengan nilai i pada iterasi perulangan pertama (outer loop). Setelah mencetak bintang (*) sejumlah i kali pada setiap baris, program akan menambahkan karakter baris baru (\\n) ke dalam variabel output. Proses ini akan terus berlanjut hingga perulangan pertama (outer loop) selesai, dan output akan dicetak ke layar. Dengan demikian, pada setiap baris, jumlah bintang () yang dicetak akan meningkat sesuai dengan nomor barisnya, membentuk piramida dari bintang ().', 'Pada setiap iterasi perulangan pertama (outer loop), nilai variabel i menentukan nomor baris yang sedang diproses dalam piramida. Saat perulangan kedua (inner loop) dimulai, nilai variabel j dimulai dari 1 hingga mencapai nilai yang sama dengan variabel i, menandakan jumlah bintang (*) yang akan dicetak pada baris saat ini. Di setiap iterasi perulangan kedua, sebuah bintang (*) ditambahkan ke dalam variabel output. Jumlah bintang (*) yang dicetak pada setiap baris bertambah sesuai dengan nomor barisnya, membentuk pola bertingkat yang khas dalam piramida. Setelah mencetak bintang (*) sejumlah yang sesuai untuk baris saat ini, karakter baris baru (\\n) ditambahkan ke dalam variabel output untuk memindahkan output ke baris berikutnya. Proses ini diulangi hingga seluruh baris dalam piramida selesai dibangun.', 'Perulangan kedua menggunakan variabel j untuk menambahkan satu bintang () pada setiap baris piramida, di mana jumlah bintang () yang dicetak bertambah sesuai dengan nomor barisnya.', '2023-06-01 18:19:46', '2024-03-23 12:08:41', NULL),
(27, 9, 1, 'Apakah output yang diberikan program, jika kondisi ( i<= 5) pada perulangan pertama (outer loop) di ganti menjadi ( i<=6 )?', 'Jumlah baris piramida akan bertambah 1 baris, sehingga menjadi 6 baris, dengan baris terakhir memiliki 6 bintang.', 'Program akan mencetak piramida dengan tinggi 6 baris. Setiap baris akan memiliki jumlah bintang yang sama dengan nomor barisnya.', 'Program akan menghasilkan pola piramida dengan tinggi 6 baris, di mana jumlah bintang pada setiap baris akan sama dengan nomor barisnya. Dengan kata lain, pada baris pertama hanya akan ada satu bintang, pada baris kedua akan ada dua bintang, pada baris ketiga akan ada tiga bintang, dan seterusnya hingga baris keenam akan memiliki enam bintang.', 'Program akan mencetak pola piramida dengan tinggi 6 baris, di mana jumlah bintang pada setiap baris sesuai dengan nomor barisnya.', '2023-06-01 18:19:46', '2024-03-23 12:08:41', NULL),
(28, 10, 1, 'Kode program manakah yang berfungsi untuk merubah array menjadi data string?', 'Yang merubah array menjadi data string adalah baris kode Arrays.toString(topics)', 'Dengan menggunakan metode Arrays.toString(), array topics dikonversi menjadi string.', 'Dengan menggunakan metode Arrays.toString(), array topics diubah menjadi string dengan cara menggabungkan semua elemen array ke dalam satu string dengan tanda kurung siku dan koma sebagai pemisah antara elemen-elemen array tersebut.', 'Metode Arrays.toString() mengubah array topics menjadi string dengan cara menggabungkan semua elemen array ke dalam satu string, di mana setiap elemen dipisahkan oleh koma dan dikelilingi oleh tanda kurung siku.', '2023-06-01 18:21:53', '2024-03-23 12:10:41', NULL),
(29, 10, 1, 'Jelaskan alur program dari kode program diatas!', 'Array topics berisi empat elemen yang mewakili topik-topik berita, yaitu \"Opinion\", \"Tech\", \"Science\", dan \"Health\". Variabel topicArray diinisialisasi dengan hasil pemanggilan Arrays.toString(topics). Fungsi Arrays.toString() digunakan untuk mengonversi array topics menjadi string dengan format yang sesuai.\r\n\r\nSelanjutnya, perintah System.out.print(topicArray) digunakan untuk mencetak isi dari variabel topicArray, yaitu string yang berisi daftar topik-topik berita yang diubah dari array topics.\r\nKetika program dijalankan, string yang berisi daftar topik-topik berita akan ditampilkan sebagai output.', 'Mendefinisikan sebuah array topics yang berisi beberapa topik berita. Menggunakan method Arrays.toString() untuk mengonversi array topics menjadi sebuah string. String yang dihasilkan disimpan dalam variabel topicArray. Menggunakan System.out.print() untuk mencetak isi dari variabel topicArray, yang merupakan string yang berisi seluruh topik berita yang ada dalam array topics.', 'Array topics dideklarasikan dengan berisi beberapa topik berita. Kemudian, isi dari array topics diubah menjadi string menggunakan metode Arrays.toString(). Hasil konversi tersebut disimpan dalam variabel topicArray. Selanjutnya, isi dari variabel topicArray dicetak menggunakan System.out.print(). Ini akan mencetak daftar topik berita dalam bentuk string.', 'Pertama, terdapat sebuah array yang menyimpan beberapa topik berita yang telah ditentukan sebelumnya. Selanjutnya, array tersebut diubah menjadi sebuah string menggunakan sebuah metode. Hasil dari proses tersebut disimpan dalam variabel topicArray. Akhirnya, string yang berisi daftar topik berita tersebut dicetak ke layar.', '2023-06-01 18:21:53', '2024-03-23 12:10:41', NULL),
(30, 10, 1, 'Jika elemen array topics diubah menjadi “String[] topics = {1,2,3,4};”, apakah output yang dihasilkan program? Jelaskan mengapa!', 'Error. Karena elemen array berisi bilangan bulat, sedangkan tipe data array adalah String', 'Error, Program akan menghasilkan kesalahan kompilasi karena tipe data yang dideklarasikan untuk array \"topics\" adalah string, sedangkan elemennya diberikan dalam tipe data integer.\r\nJava tidak dapat mengonversi integer menjadi string secara otomatis dalam konteks ini.', 'Program akan menghasilkan kesalahan saat dijalankan karena mencoba mencetak nilai array integer sebagai string tanpa konversi tipe data yang sesuai.', 'Program menghasilkan error karena terjadi inkonsistensi antara tipe data yang dideklarasikan untuk array \"topics\" (string) dan tipe data elemennya (integer). Dengan kata lain, program mencoba memasukkan nilai integer ke dalam array yang dideklarasikan sebagai array string, yang tidak dapat dilakukan secara langsung dalam Java. Ini menyebabkan kesalahan kompilasi karena Java tidak dapat secara otomatis mengonversi tipe data integer menjadi tipe data string dalam konteks ini.', '2023-06-01 18:21:53', '2024-03-23 12:10:41', NULL),
(31, 11, 1, 'Apakah fungsi dari kode “i < nilai.length;” pada perulangan pertama ?', 'Fungsi dari kode tersebut adalah untuk membatasi jumlah perulangan sebanyak jumlah panjang data dari array nilai', 'Kode \"i < nilai.length;\" pada perulangan pertama digunakan untuk memastikan bahwa iterasi berlangsung selama nilai dari variabel \'i\' kurang dari panjang (jumlah baris) dari array dua dimensi \'nilai\'. Dengan demikian, itu memastikan bahwa iterasi akan terjadi untuk setiap baris dalam array \'nilai\'.', 'Kode tersebut bertanggung jawab untuk membatasi iterasi agar tidak melebihi jumlah baris yang ada dalam array dua dimensi \'nilai\'. Ini membantu mencegah kesalahan indeks dan memastikan bahwa hanya baris yang ada dalam array yang diperlakukan.', 'Dengan \"i < nilai.length;\", perulangan memastikan bahwa iterasi berlangsung untuk setiap baris dalam array \'nilai\' tanpa melampaui batas yang ditetapkan oleh panjang array, sehingga memastikan bahwa semua data dalam array \'nilai\' diproses dengan benar.', '2023-06-01 18:27:43', '2024-03-23 12:12:23', NULL);
INSERT INTO `essay_question` (`id`, `question_id`, `user_id`, `question`, `answer`, `answer2`, `answer3`, `answer4`, `created_at`, `updated_at`, `deleted_at`) VALUES
(32, 11, 1, 'Jelaskan alur program dari blok kode perulangan kedua (inner loop) diatas!', 'Perulangan akan dimulai dari nilai 0 dan berakhir pada saat nilai “j” kurang dari jumlah panjang array nilai. Saat kondisi terpenuhi, satu nilai akan ditambahkan ke variabel “total”. selain itu, variabel “jumlahData” juga akan ditambahkan dengan 1. nilai akan terus bertambah seiring dengan nilai “j” yang meningkat.', 'Variabel j diinisialisasi dengan nilai 0. Perulangan dilakukan selama nilai j kurang dari panjang array yang terdapat pada indeks ke i dari array nilai. Pada setiap iterasi, nilai dari array yang terletak pada indeks [i][j] ditambahkan ke dalam variabel total. Variabel jumlahData ditambah satu setiap kali perulangan dalam loop j dilakukan, untuk menghitung jumlah total data yang telah diproses. Setelah loop j selesai, program akan kembali ke awal loop i (outer loop) untuk melanjutkan iterasinya atau program berakhir jika syarat iterasi pada loop i tidak terpenuhi.', 'Pertama, variabel j diinisialisasi dengan nilai 0. Kemudian, loop akan berjalan selama nilai j kurang dari panjang array yang terdapat pada indeks ke i dari array nilai. Di setiap iterasi loop j, program akan mengakses nilai yang terletak pada indeks [i][j] dari array nilai. Nilai tersebut akan ditambahkan ke dalam variabel total, yang bertujuan untuk mengakumulasikan total nilai dari semua elemen dalam array nilai. Selain itu, variabel jumlahData akan bertambah satu pada setiap iterasi loop j. Hal ini bertujuan untuk menghitung jumlah total elemen yang telah diproses. Setelah loop j selesai, program akan melanjutkan ke iterasi berikutnya dalam loop i (outer loop) jika masih memenuhi syarat, atau program akan berakhir jika iterasi terakhir dari loop i telah selesai.', 'Perulangan dimulai dengan inisialisasi nilai j sebagai 0, dan akan terus berjalan selama nilai j kurang dari panjang array yang terdapat pada indeks ke i dari array nilai. Selama iterasi ini, setiap elemen array yang berada pada indeks [i][j] akan diakses. Nilai dari elemen tersebut akan ditambahkan ke dalam variabel total, yang bertanggung jawab untuk mengumpulkan total nilai dari semua elemen dalam array nilai. Selain itu, setiap kali iterasi dilakukan, variabel jumlahData akan bertambah satu. Ini dilakukan untuk menghitung jumlah total elemen yang telah diproses dalam perulangan. Dengan demikian, proses ini akan terus berlanjut hingga seluruh elemen dalam array nilai pada baris yang sedang diproses telah selesai diproses.', '2023-06-01 18:27:43', '2024-03-23 12:12:23', NULL),
(33, 11, 1, 'Jika elemen array nilai diganti menjadi “double[][] nilai = {{75, 80, 81}, {90, 95, 90}, {70, 75, 82}};”. Berapakah rata-rata nilai yang didapatkan?', 'Rata-rata yang didapatkan adalah 82', 'Jika elemen array nilai diganti menjadi “double[][] nilai = {{75, 80, 81}, {90, 95, 90}, {70, 75, 82}};” maka rata-rata nilai yang didapatkan adalah 82.', 'Jika nilai-nilai dalam array diubah menjadi \"double[][] nilai = {{75, 80, 81}, {90, 95, 90}, {70, 75, 82}};\", maka rata-rata yang dihasilkan adalah 82. Dengan kata lain, rata-rata dari kumpulan nilai tersebut adalah 82, yang merupakan nilai tengah dari rentang nilai yang ada. Hal ini menunjukkan bahwa sebagian besar nilai berada di sekitar angka 82, yang dapat dianggap sebagai representasi keseluruhan dari kumpulan data tersebut.', 'Jika kita mengubah nilai-nilai dalam array menjadi \"double[][] nilai = {{75, 80, 81}, {90, 95, 90}, {70, 75, 82}};\", maka rata-rata yang dihasilkan adalah 82. Dengan kata lain, nilai rata-rata dari semua nilai dalam array tersebut adalah 82. Ini menunjukkan bahwa secara keseluruhan, nilai-nilai tersebut cenderung mendekati angka 82.', '2023-06-01 18:27:43', '2024-03-23 12:12:23', NULL),
(34, 12, 1, 'Apakah kegunaan dari kode “tampil()” pada main method?', 'Fungsi dari kode “tampil()” adalah untuk memanggil fungsi tampil.', 'Fungsi dari kode \"tampil()\" adalah untuk menampilkan hasil perhitungan luas dan keliling lingkaran dengan menggunakan metode \"tampil\". Dengan kata lain, kode \"tampil()\" bertanggung jawab untuk menampilkan informasi tentang luas dan keliling lingkaran ke layar atau output yang sesuai.', 'Kode \"tampil()\" berfungsi untuk mengorganisir dan menampilkan hasil perhitungan luas dan keliling lingkaran. Dengan kata lain, tugas kode \"tampil()\" adalah untuk menampilkan informasi terkait lingkaran, seperti luas dan kelilingnya, kepada pengguna secara jelas dan terstruktur.', 'Kode \"tampil()\" berfungsi untuk menampilkan hasil perhitungan luas dan keliling lingkaran ke layar atau output. Dengan kata lain, tugasnya adalah untuk menyajikan informasi tentang lingkaran kepada pengguna secara visual atau dalam bentuk teks agar dapat dengan mudah dipahami.', '2023-06-01 18:31:05', '2024-03-23 12:14:42', NULL),
(35, 12, 1, 'Jelaskan alur program yang ada pada fungsi “tampil()”!', 'Inisialisasi phi dengan 3.14, inisialisasi r dengan 14. Kemudian, inisialisasi variabel luas dengan memanggil method luasLingkaran yang berparameter phi dan r, begitupun dengan variabel keliling yang memanggil kelilingLingkaran', 'Variabel lokal phi diinisialisasi dengan nilai 3.14 dan variabel r diinisialisasi dengan nilai 14. Fungsi luasLingkaran(phi, r) dipanggil dengan mengirimkan nilai phi dan r sebagai argumen. Fungsi ini menghitung luas lingkaran menggunakan rumus πr^2, dimana phi adalah nilai pi (π) dan r adalah jari-jari lingkaran. Hasil perhitungan luas lingkaran disimpan dalam variabel lokal luas. Fungsi kelilingLingkaran(phi, r) dipanggil dengan mengirimkan nilai phi dan r sebagai argumen. Fungsi ini menghitung keliling lingkaran menggunakan rumus 2πr, dimana phi adalah nilai pi (π) dan r adalah jari-jari lingkaran. Hasil perhitungan keliling lingkaran disimpan dalam variabel lokal keliling. Menggunakan System.out.print, hasil perhitungan luas dan keliling lingkaran ditampilkan dalam satu baris dengan format yang sesuai. Pada kasus ini, hasil luas dan keliling lingkaran akan ditampilkan dalam satu baris dengan pesan \"Luas Lingkaran = ...\" diikuti oleh nilai luas dan pesan \"Keliling Lingkaran = ...\" diikuti oleh nilai keliling.', 'Pertama, program menetapkan nilai phi (π) dengan 3.14 dan nilai jari-jari lingkaran (r) dengan 14. Selanjutnya, fungsi luasLingkaran(phi, r) dipanggil untuk menghitung luas lingkaran. Fungsi ini menggunakan rumus matematika πr^2, yang mengalikan phi dengan kuadrat jari-jari lingkaran, sehingga menghasilkan luas lingkaran. Hasil perhitungan luas lingkaran disimpan dalam variabel luas. Kemudian, fungsi kelilingLingkaran(phi, r) dipanggil untuk menghitung keliling lingkaran. Fungsi ini menggunakan rumus 2πr, yang mengalikan phi dengan dua kali jari-jari lingkaran, sehingga menghasilkan keliling lingkaran. Hasil perhitungan keliling lingkaran disimpan dalam variabel keliling. Akhirnya, program menampilkan hasil luas dan keliling lingkaran dengan menggunakan System.out.print. Informasi ditampilkan dalam satu baris dengan format yang sesuai, diawali dengan pesan \"Luas Lingkaran = ...\" yang diikuti oleh nilai luas, dan diikuti lagi dengan pesan \"Keliling Lingkaran = ...\" yang diikuti oleh nilai keliling.', 'Fungsi tampil() bertugas menampilkan luas dan keliling lingkaran dengan jari-jari 14 dan nilai pi sebesar 3.14. Prosesnya melibatkan perhitungan luas dan keliling menggunakan rumus matematika yang sesuai, kemudian hasilnya ditampilkan dalam satu baris dengan format yang jelas dan mudah dimengerti.', '2023-06-01 18:31:05', '2024-03-23 12:14:42', NULL),
(36, 12, 1, 'Apa yang terjadi jika kode “tampil()” pada main method di hapus?', 'Jika kode tersebut dihapus, maka program tidak menampilkan output apapun', 'Jika tampil() adalah satu-satunya kode di dalam main() dan kita menghapusnya, maka kompilator akan menghasilkan kesalahan karena tidak ada tindakan yang dilakukan dalam main(). Kode harus melakukan sesuatu yang relevan di dalam metode main() untuk menjalankan program.', 'Tanpa pemanggilan tampil(), tidak ada tindakan yang dilakukan dalam main(), yang berarti tidak akan ada output yang dihasilkan ketika program dijalankan.', 'Jika tidak ada kode lain yang dieksekusi di dalam main() selain pemanggilan tampil(), meskipun tampil() dihapus, program masih akan berjalan. Namun, tidak akan ada output yang ditampilkan.', '2023-06-01 18:31:05', '2024-03-23 12:14:42', NULL),
(37, 13, 1, 'Apakah program ini menggunakan rekursi? Jelaskan!', 'Ya, program ini menggunakan rekursi. Fungsi hitungBunga memanggil dirinya sendiri dengan parameter yang telah diubah untuk tahun sebelumnya. Proses ini terjadi hingga mencapai kondisi base, yaitu saat tahun menjadi 0, di mana rekursi berhenti dan mengembalikan saldo akhir.', 'Metode hitungBunga() memanggil dirinya sendiri secara rekursif dengan parameter yang dimodifikasi pada setiap iterasi, yaitu tahun - 1, hingga mencapai kondisi basis tahun == 0.', 'Iya, Kasus dasar dalam rekursi ini adalah ketika tahun == 0, di mana tidak ada lagi tahun yang tersisa untuk dihitung, sehingga metode mengembalikan saldo.', 'Terdapat pola rekursif yang jelas dalam program ini di mana setiap pemanggilan fungsi hitungBunga() memecah masalah menjadi masalah yang lebih kecil (tahun yang berkurang) hingga mencapai kasus dasar.', '2023-06-01 18:37:39', '2024-03-23 12:16:22', NULL),
(38, 13, 1, 'Jelaskan alur kode program yang ada dalam method atau fungsi hitungBunga!', 'Fungsi hitungBunga didefinisikan dengan tiga parameter, yaitu saldo (saldo awal), bunga (persentase bunga per tahun), dan tahun (jumlah tahun). \r\n\r\nPertama, program melakukan pengecekan kondisi if (tahun == 0). Jika tahun sama dengan 0, artinya perhitungan bunga telah selesai, dan fungsi akan mengembalikan nilai saldo tanpa melakukan perhitungan tambahan.\r\nJika kondisi pada langkah sebelumnya tidak terpenuhi, program akan melanjutkan ke blok else.\r\nPada blok else, variabel bungaTahunan dihitung dengan rumus saldo * (bunga / 100), yang merupakan bunga yang diperoleh dalam satu tahun.\r\nSelanjutnya, variabel total dihitung dengan menambahkan saldo dengan bungaTahunan, yang merupakan total saldo setelah satu tahun dengan bunga.\r\n\r\nTerakhir, fungsi hitungBunga dipanggil secara rekursif dengan nilai total sebagai saldo baru, bunga yang sama, dan tahun - 1 sebagai tahun yang berkurang satu.\r\n\r\nAlur program akan berulang kembali ke pengecekan tahun dengan nilai saldo dan tahun yang baru. Proses ini akan terus berlanjut hingga kondisi tahun == 0 terpenuhi, dan fungsi akan mengembalikan saldo akhir setelah seluruh perhitungan bunga selesai.', 'Parameter dan Kondisional: Fungsi ini menerima tiga parameter: saldo (saldo awal), bunga (tingkat bunga tahunan), dan tahun (jumlah tahun). Pertama, fungsi memeriksa apakah tahun sama dengan 0. Jika ya, itu berarti sudah mencapai akhir perhitungan dan fungsi mengembalikan saldo saat ini.\r\n\r\nPerhitungan Bunga Tahunan: Jika tahun bukan 0, itu berarti perlu dilakukan perhitungan bunga untuk tahun tersebut. Bunga tahunan dihitung sebagai saldo awal dikalikan dengan tingkat bunga (dalam persen).\r\n\r\nTotal Saldo: Setelah mendapatkan nilai bunga tahunan, total saldo untuk tahun tersebut dihitung dengan menambahkan saldo awal dengan bunga tahunan.\r\n\r\nRekursi: Kemudian, fungsi hitungBunga() dipanggil kembali dengan nilai total saldo yang baru, tingkat bunga yang sama, dan jumlah tahun dikurangi satu. Langkah ini diulangi secara rekursif sampai mencapai tahun yang ditentukan.\r\n\r\nPengembalian Nilai: Setelah semua perhitungan selesai, nilai total saldo akhir setelah sejumlah tahun dikembalikan sebagai output dari fungsi hitungBunga().\r\n\r\nDengan cara ini, fungsi hitungBunga() secara rekursif menghitung total saldo akhir setelah sejumlah tahun dengan mengakumulasikan bunga tahunan pada saldo awal pada setiap iterasi tahun.', 'Pengecekan Awal: Fungsi memeriksa apakah sudah mencapai akhir perhitungan. Jika tahun yang diberikan adalah 0, artinya sudah selesai, dan saldo saat ini dikembalikan.\r\n\r\nPerhitungan Bunga: Jika masih ada tahun yang harus dihitung, maka bunga tahunan dihitung terlebih dahulu. Ini adalah seberapa banyak uang yang akan ditambahkan ke saldo awal pada tahun tersebut, berdasarkan persentase bunga.\r\n\r\nPertambahan Saldo: Bunga tahunan kemudian ditambahkan ke saldo awal untuk mendapatkan total saldo setelah bunga diperhitungkan.\r\n\r\nRekursi: Fungsi kembali dipanggil untuk tahun selanjutnya dengan total saldo baru tersebut sebagai saldo awal.\r\n\r\nPengulangan Langkah: Langkah-langkah di atas diulangi untuk setiap tahun, terus-menerus menambahkan bunga ke saldo sebelumnya.\r\n\r\nPengembalian Hasil: Setelah semua tahun dihitung, total saldo akhir dikembalikan sebagai hasil perhitungan.\r\n\r\nDengan cara ini, fungsi bekerja secara berulang untuk mengakumulasikan bunga pada saldo awal dari tahun ke tahun, hingga mencapai jumlah tahun yang ditentukan.', 'Fungsi hitungBunga() menghitung total saldo setelah beberapa tahun dengan menambahkan bunga tahunan ke saldo awal pada setiap iterasi tahun, hingga mencapai jumlah tahun yang ditentukan. Proses ini berlangsung secara berulang, di mana saldo yang dihitung kembali digunakan sebagai saldo awal untuk tahun berikutnya, sampai semua tahun dihitung. Akhirnya, fungsi mengembalikan total saldo akhir setelah perhitungan selesai.', '2023-06-01 18:37:39', '2024-03-23 12:16:22', NULL),
(39, 13, 1, 'Jika bunga pertahun diganti menjadi 7%, berapakah jumlah uang yang dihasilkan setelah 5 tahun?', 'Uang yang dihasilkan setelah menabung 5 tahun adalah 1.402.551,7307', 'Dengan bunga 7% pertahun, jumlah uang setelah 5 tahun adalah 1.402.551,7307', 'Jika bunga pertahun diganti menjadi 7%, jumlah uang yang dihasilkan setelah 5 tahun adalah 1.402.551,7307.', '1.402.551,7307', '2023-06-01 18:37:39', '2024-03-23 12:16:22', NULL),
(56, 26, 1, 'aaa', 'aaa', 'aa', 'aa', 'aa', '2024-03-23 12:23:52', '2024-03-23 12:24:33', '2024-03-23 12:24:33'),
(57, 26, 1, 'bbb', 'bbb', 'bb', 'bb', 'bb', '2024-03-23 12:23:52', '2024-03-23 12:24:33', '2024-03-23 12:24:33');

-- --------------------------------------------------------

--
-- Table structure for table `explaining_score`
--

CREATE TABLE `explaining_score` (
  `id` bigint UNSIGNED NOT NULL,
  `user_id` bigint UNSIGNED NOT NULL,
  `content_id` int UNSIGNED NOT NULL,
  `question_id` int UNSIGNED NOT NULL,
  `konteks_penjelasan` int DEFAULT NULL,
  `keruntutan` int DEFAULT NULL,
  `kebenaran` int DEFAULT NULL,
  `is_accepted` tinyint(1) DEFAULT NULL,
  `essay_question_id` bigint UNSIGNED NOT NULL,
  `user_answer_id` bigint UNSIGNED NOT NULL,
  `total_score_id` bigint UNSIGNED NOT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `explaining_score`
--

INSERT INTO `explaining_score` (`id`, `user_id`, `content_id`, `question_id`, `konteks_penjelasan`, `keruntutan`, `kebenaran`, `is_accepted`, `essay_question_id`, `user_answer_id`, `total_score_id`, `created_at`, `updated_at`) VALUES
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INSERT INTO `explaining_score` (`id`, `user_id`, `content_id`, `question_id`, `konteks_penjelasan`, `keruntutan`, `kebenaran`, `is_accepted`, `essay_question_id`, `user_answer_id`, `total_score_id`, `created_at`, `updated_at`) VALUES
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-- --------------------------------------------------------

--
-- Table structure for table `explains`
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CREATE TABLE `explains` (
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-- --------------------------------------------------------

--
-- Table structure for table `failed_jobs`
--

CREATE TABLE `failed_jobs` (
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-- --------------------------------------------------------

--
-- Table structure for table `lessons`
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CREATE TABLE `lessons` (
  `id` int UNSIGNED NOT NULL,
  `title` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
  `description` text COLLATE utf8mb4_unicode_ci NOT NULL,
  `course_id` int UNSIGNED NOT NULL,
  `posisition` int NOT NULL,
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  `level_id` int UNSIGNED NOT NULL
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INSERT INTO `lessons` (`id`, `title`, `description`, `course_id`, `posisition`, `published`, `created_at`, `updated_at`, `level_id`) VALUES
(1, 'Tipe Data, Variabel dan Operator', 'User dapat memahami dan mampu menjelaskan tentang Tipe Data, Variabel, Input-Output, Sequence dan operator ke pemrograman Java', 1, 1, 1, '2023-06-01 04:30:20', '2023-06-01 04:30:20', 1),
(2, 'Sintaks Pemilihan 1', 'User mampu menyelesaikan permasalahan/studi kasus menggunakan sintaks pemilihan 1 dan mengimplementasikannya dalam bahasa pemrograman Java.', 1, 2, 1, '2023-06-01 04:33:08', '2023-06-01 04:33:08', 1),
(3, 'Sintaks Pemilihan 2', 'User memahami tentang operator logika dan mampu menyelesaikan permasalahan dengan menggunakan sintaks pemilihan bersarang', 1, 3, 1, '2023-06-01 04:34:51', '2023-06-01 04:34:51', 1),
(4, 'Sintaks Perulangan 1', 'User memahami serta mampu membuat kode program dalam bahasa Java menggunakan instruksi perulangan.', 1, 4, 1, '2023-06-01 04:35:54', '2023-06-01 04:35:54', 2),
(5, 'Sintaks Perulangan 2', 'User memahami konsep perulangan bersarang dan mampu membuat kode program perulangan bersarang dalam bahasa Java', 1, 5, 1, '2023-06-01 04:38:11', '2023-06-01 04:38:11', 2),
(6, 'Array 1', 'User mampu memahami konsep array satu dimensi, memberikan contoh penggunaan array satu dimensi, membuat kode program menggunakan konsep array satu dimensi', 1, 6, 1, '2023-06-01 04:41:46', '2023-06-01 04:43:34', 2),
(7, 'Array Multidimensi', 'User memahami konsep array 2 dimensi dan membuat kode program dengan menggunakan konsep array multidimensi.', 1, 7, 1, '2023-06-01 04:43:01', '2023-06-01 04:43:01', 3),
(8, 'Fungsi 1', 'User mampu memahami penggunaan fungsi static pada Java dengan parameter dan mengembalikan nilai dan membuat kode program dengan menggunakan fungsi static dan mengeksekusi fungsi tersebut.', 1, 8, 1, '2023-06-01 04:45:03', '2023-06-01 04:45:03', 3),
(9, 'Fungsi 2', 'User memahami konsep fungsi rekursif dan mampu mengimplementasikan fungsi rekursif dalam kode program', 1, 9, 1, '2023-06-01 04:46:33', '2023-06-01 04:46:33', 3);

-- --------------------------------------------------------

--
-- Table structure for table `levels`
--

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  `updated_at` timestamp NULL DEFAULT NULL,
  `description` text COLLATE utf8mb4_unicode_ci NOT NULL,
  `deleted_at` timestamp NULL DEFAULT NULL
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--
-- Dumping data for table `levels`
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INSERT INTO `levels` (`id`, `name`, `course_id`, `created_at`, `updated_at`, `description`, `deleted_at`) VALUES
(1, 'Easy', 1, '2023-02-28 03:27:44', '2023-03-06 02:30:00', 'Start your journey with easiest step', NULL),
(2, 'Medium', 1, '2023-02-28 03:28:42', '2023-02-28 03:28:42', 'Step forward to medium level', NULL),
(3, 'Hard', 1, '2023-02-28 03:28:59', '2023-02-28 03:28:59', 'You did it! push your limit.', NULL),
(5, 'mudah', 1, '2023-03-06 02:00:35', '2023-03-06 02:03:41', 'as', '2023-03-06 02:03:41'),
(6, 'mudah', 1, '2023-03-06 02:01:02', '2023-03-06 02:03:57', 'kjk', '2023-03-06 02:03:57'),
(7, 'advance', 1, '2023-07-02 20:35:39', '2023-07-02 20:36:05', 'advance your programming skill', '2023-07-02 20:36:05'),
(8, 'abca', 1, '2024-03-28 09:55:02', '2024-03-28 09:55:10', 'abc', '2024-03-28 09:55:10'),
(9, 'abc', 1, '2024-03-28 12:29:10', '2024-03-28 12:29:14', 'aa', '2024-03-28 12:29:14');

-- --------------------------------------------------------

--
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(4, '2019_12_14_000001_create_personal_access_tokens_table', 1),
(5, '2022_05_30_114700_create_roles_table', 1),
(6, '2022_05_30_115524_create_courses_table', 1),
(7, '2022_05_30_120348_create_lessons_table', 1),
(8, '2022_05_30_141552_create_contents_table', 1),
(9, '2022_05_30_143915_add_role_to_user_column', 1),
(10, '2022_05_30_150023_create_questions_table', 1),
(11, '2022_05_30_180245_create_student_course_table', 1),
(12, '2022_05_31_015033_create_answers_table', 1),
(13, '2022_05_31_023057_add_nullable_to_answers', 1),
(14, '2022_05_31_030846_add_null_to_question', 1),
(15, '2022_05_31_070600_create_user_scores_table', 1),
(16, '2022_05_31_151123_create_badge_settings_table', 2),
(17, '2022_06_02_055725_change_column_in_contents', 3),
(18, '2022_06_13_155450_add_column_is_essay_to_question_table', 4),
(19, '2022_06_16_105917_change_column_question_on_question_table', 4),
(20, '2022_06_20_121634_create_user_code_test_score_table', 5),
(21, '2022_06_20_152419_add_question_id_on_user_scores_table', 5),
(22, '2022_07_19_073038_add_column_timer_to_question_table', 6),
(23, '2022_07_25_112343_add_column_start_time_to_user_scores_table', 7),
(24, '2022_07_25_125721_create_table_code_error_logs', 7),
(25, '2022_07_25_214126_add_column_on_timer_on_code_error_logs', 8),
(26, '2022_07_25_220037_add_column_on_timer_on_user_scores_table', 8),
(27, '2023_02_28_031855_create_levels_table', 9),
(28, '2023_02_28_062544_add_description_to_levels_table', 10),
(29, '2023_03_10_073837_create_table_code_history_logs', 11),
(30, '2023_03_10_074326_create_code_history_logs_table', 12),
(31, '2023_03_17_071601_create_explains_table', 13),
(32, '2023_05_18_144701_create_essay_question_table', 14),
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(34, '2023_05_23_060818_create_wondering_score_table', 16),
(35, '2023_05_23_061330_create_explaining_score_table', 17),
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(37, '2023_06_23_042517_add_class_to_users_table', 19),
(38, '2024_03_22_175814_add_additional_answers_to_essay_question_table', 20),
(39, '2024_03_22_180425_add_additional_answers_to_essay_question_table', 21);

-- --------------------------------------------------------

--
-- Table structure for table `password_resets`
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CREATE TABLE `password_resets` (
  `email` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
  `token` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
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--
-- Dumping data for table `password_resets`
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INSERT INTO `password_resets` (`email`, `token`, `created_at`) VALUES
('fransiskaly@gmail.com', '$2y$10$mio8nnHOnS0FKHjcDkEF0O1d8h7QhKHqRLgUcT/AUcM2e9/BQo2Ce', '2023-02-14 05:51:57');

-- --------------------------------------------------------

--
-- Table structure for table `personal_access_tokens`
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CREATE TABLE `personal_access_tokens` (
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  `tokenable_id` bigint UNSIGNED NOT NULL,
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  `token` varchar(64) COLLATE utf8mb4_unicode_ci NOT NULL,
  `abilities` text COLLATE utf8mb4_unicode_ci,
  `last_used_at` timestamp NULL DEFAULT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

-- --------------------------------------------------------

--
-- Table structure for table `questions`
--

CREATE TABLE `questions` (
  `id` int UNSIGNED NOT NULL,
  `content_id` int UNSIGNED NOT NULL,
  `question_name` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
  `question` longtext COLLATE utf8mb4_unicode_ci NOT NULL,
  `image` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL,
  `score` int NOT NULL,
  `hint` text COLLATE utf8mb4_unicode_ci,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL,
  `deleted_at` timestamp NULL DEFAULT NULL,
  `is_essay` int NOT NULL DEFAULT '0',
  `timer` int DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `questions`
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INSERT INTO `questions` (`id`, `content_id`, `question_name`, `question`, `image`, `score`, `hint`, `created_at`, `updated_at`, `deleted_at`, `is_essay`, `timer`) VALUES
(1, 1, 'Tipe Data, Variabel dan Operator', '<p><strong style=\"color: black;\">Studi Kasus:</strong></p><p>Lengkapilah kode program berdasarkan perintah berikut :</p><ul><li>Tambahkan tipe data untuk variabel panjang, lebar, tinggi, Vbalok dan Lbalok berdasarkan nilai yang ada.</li><li>Tambahkan rumus volume balok “panjang * lebar * tinggi” pada variabel Vbalok</li><li>Tambahkan rumus volume balok “2*(panjang * lebar + panjang * tinggi + lebar * tinggi)” pada variabel Lbalok</li></ul><p> </p><pre class=\"ql-syntax\" spellcheck=\"false\">public <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">TipeData</span> {\n      public <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span>(<span class=\"hljs-params\"><span class=\"hljs-built_in\">String</span> args[]</span>) {\n             … panjang, lebar, tinggi, vBalok, lBalok;\n             \n             panjang = <span class=\"hljs-number\">10</span>;\n             lebar = <span class=\"hljs-number\">6</span>;\n             tinggi = <span class=\"hljs-number\">7</span>;\n             \n             <span class=\"hljs-comment\">// volume balok</span>\n             vBalok = ……;\n             \n             <span class=\"hljs-comment\">// Luas permukaan balok</span>\n             lBalok = …..;\n             \n             <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Volume balok = \"</span>+ vBalok + <span class=\"hljs-string\">\", \"</span>);\n             <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Luas permukaan balok = \"</span>+ lBalok);\n             \n      }\n}\n</pre>', NULL, 30, NULL, '2023-06-01 08:11:49', '2024-02-26 23:45:59', NULL, 1, NULL),
(2, 2, 'IF-ELSE Angka', '<p><strong style=\"color: black;\">Studi Kasus:</strong></p><p><span style=\"color: black;\">Buatlah kondisi dimana apabila variabel nilai lebih dari 70 maka akan menampilkan \"Selamat anda lulus!\"</span></p><p><span style=\"color: black;\"><span class=\"ql-cursor\">﻿</span></span></p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">Angka</span> {\r\n      <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span><span class=\"hljs-params\">(String args[])</span> {\r\n            <span class=\"hljs-type\">int</span> <span class=\"hljs-variable\">nilai</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">80</span>;\r\n            \r\n            <span class=\"hljs-keyword\">if</span>(nilai > <span class=\"hljs-number\">70</span>) {\r\n                   System.out.print(<span class=\"hljs-string\">\"…\"</span>);\r\n            }\r\n      }\r\n \r\n}\r\n</pre>', NULL, 30, NULL, '2023-06-01 08:14:09', '2024-03-23 11:55:29', NULL, 1, NULL),
(3, 3, 'Sintaks IF-ELSE IF-ELSE', '<p><strong style=\"color: black;\">Studi Kasus:</strong></p><p><span style=\"color: black;\">Buatlah kondisi dimana apabila variabel itemCost lebih dari 24 maka akan menampilkan \"High Value Item!\"</span></p><p><span style=\"color: black;\">sedangkan apabila dibawah dari nilai variabel tersebut akan menampilkan \"Low Value Item!\"</span></p><p> </p><pre class=\"ql-syntax\" spellcheck=\"false\">public <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">Order</span> {\r\n        \r\n        public static void main(String[] args) {\r\n                double itemCost = <span class=\"hljs-number\">30.99</span>;\r\n                String order = <span class=\"hljs-string\">\"\"</span>;\r\n                <span class=\"hljs-keyword\">if</span>(itemCost > <span class=\"hljs-number\">24.00</span>) {\r\n                         order = <span class=\"hljs-string\">\". . .\"</span>;\r\n                } <span class=\"hljs-keyword\">else</span> {\r\n                         order = <span class=\"hljs-string\">\"...”;\r\n                }\r\n                System.out.print(order);\r\n        }\r\n}\r\n</span></pre>', NULL, 30, NULL, '2023-06-01 08:16:58', '2024-03-23 11:57:25', NULL, 1, NULL),
(4, 4, 'Pemilihan Switch-Case', '<p><strong style=\"color: black;\">Studi Kasus :</strong></p><p><span style=\"color: black;\">Buatlah program dengan menggunakan pemilihan switch-case, dimana berlaku aturan sebagai berikut : </span></p><ul><li><span style=\"background-color: rgb(234, 233, 237); color: black;\">Ketika shipping bernilai</span><span style=\"color: black;\"> </span><span style=\"color: black; background-color: rgb(234, 233, 237);\">\"Regular\"</span><span style=\"color: black;\">, </span><span style=\"color: black; background-color: rgb(234, 233, 237);\">shippingCost</span><span style=\"color: black;\"> harus </span><span style=\"color: black; background-color: rgb(234, 233, 237);\">0</span><span style=\"color: black;\">.</span></li><li><span style=\"color: black;\">Ketika </span><span style=\"color: black; background-color: rgb(234, 233, 237);\">shipping</span><span style=\"color: black;\"> bernilai </span><span style=\"color: black; background-color: rgb(234, 233, 237);\">\"Express\"</span><span style=\"color: black;\">, </span><span style=\"color: black; background-color: rgb(234, 233, 237);\">shippingCost</span><span style=\"color: black;\"> harus </span><span style=\"color: black; background-color: rgb(234, 233, 237);\">1.75</span><span style=\"color: black;\">.</span></li><li><span style=\"color: black;\">Nilai </span><strong style=\"color: black;\">default</strong><span style=\"color: black;\"> harus </span><span style=\"color: black; background-color: rgb(234, 233, 237);\">0.50</span><span style=\"color: black;\"> untuk shippingCost.</span></li></ul><pre class=\"ql-syntax\" spellcheck=\"false\"> \r\n<span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">OrderCase</span> {\r\n           \r\n           <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span><span class=\"hljs-params\">(String[] args)</span> {\r\n             \r\n                 <span class=\"hljs-type\">String</span> <span class=\"hljs-variable\">shipping</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-string\">\"Express\"</span>;\r\n                 <span class=\"hljs-type\">double</span> shippingCost;\r\n             \r\n               <span class=\"hljs-keyword\">switch</span> (shipping) {\r\n               <span class=\"hljs-keyword\">case</span> <span class=\"hljs-string\">\"Regular\"</span>: \r\n                 <span class=\"hljs-comment\">// isi disini</span>\r\n                 <span class=\"hljs-keyword\">break</span>;\r\n               <span class=\"hljs-keyword\">case</span> <span class=\"hljs-string\">\"Express\"</span>: \r\n                 <span class=\"hljs-comment\">// isi disini</span>\r\n                 <span class=\"hljs-keyword\">break</span>;\r\n               <span class=\"hljs-keyword\">default</span>:\r\n                  <span class=\"hljs-comment\">//isi disini</span>\r\n             }\r\n             System.out.print(<span class=\"hljs-string\">\"Shipping cost: \"</span> + shippingCost);\r\n             \r\n           }\r\n}\r\n</pre><p><br></p>', NULL, 30, NULL, '2023-06-01 08:18:42', '2024-03-23 11:59:15', NULL, 1, NULL),
(5, 5, 'Pemilihan Bersarang', '<p><strong>Studi Kasus :</strong></p><p><strong> </strong></p><p>Sebuah toko buku sedang mengadakan diskon akhir tahun dengan ketentuan sebagai berikut :</p><ul><li>Jika pembeli memiliki kartu member, maka pembeli dengan total belanja kurang dari Rp.100.000 mendapatkan diskon 10%, pembeli dengan total belanja Rp.100.000 – Rp.150.000 mendapatkan diskon 15%, sedangkan pembeli dengan total belanja lebih dari Rp.150.000 mendapatkan diskon 20%.</li><li>Jika pembeli tidak memiliki kartu member, maka pembeli dengan total belanja kurang dari Rp.100.000 mendapatkan diskon 5%, pembeli dengan total belanja Rp.100.000 – Rp.150.000 mendapatkan diskon 10%, sedangkan pembeli dengan total belanja lebih dari Rp.150.000 mendapatkan diskon 15%</li></ul><p>Buatlah kode program dari studi kasus tersebut menggunakan pengkondisian bersarang</p><p> </p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">BookStore</span> {\r\n \r\n      <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span><span class=\"hljs-params\">(String args[])</span> {\r\n            <span class=\"hljs-type\">boolean</span> <span class=\"hljs-variable\">isMember</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-literal\">true</span>;\r\n            <span class=\"hljs-type\">int</span> <span class=\"hljs-variable\">total</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">200000</span>;\r\n            <span class=\"hljs-type\">int</span> <span class=\"hljs-variable\">diskon</span> <span class=\"hljs-operator\">=</span><span class=\"hljs-number\">0</span>;\r\n            \r\n            <span class=\"hljs-keyword\">if</span>(isMember == <span class=\"hljs-literal\">true</span>) {\r\n                   <span class=\"hljs-comment\">// tulis disini</span>\r\n            } <span class=\"hljs-keyword\">else</span> {\r\n                   <span class=\"hljs-comment\">//tulis disini</span>\r\n \r\n            }\r\n            System.out.print(<span class=\"hljs-string\">\"diskon yang didapatkan adalah \"</span> + diskon + <span class=\"hljs-string\">\"%\"</span>);\r\n      }\r\n}\r\n</pre>', NULL, 30, NULL, '2023-06-01 08:21:08', '2024-03-23 12:01:06', NULL, 1, NULL),
(6, 6, 'Perulangan For', '<p><strong style=\"color: black;\">Studi Kasus:</strong></p><p><span style=\"color: black;\">Buatlah perulangan Loop For sampai memunculkan angka 1-5!</span></p><p><br></p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">LuckyFive</span> {\r\n         \r\n         <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span><span class=\"hljs-params\">(String[] args)</span> {\r\n                 <span class=\"hljs-type\">int</span> <span class=\"hljs-variable\">number</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">6</span>;\r\n                 <span class=\"hljs-keyword\">for</span>(<span class=\"hljs-type\">int</span> <span class=\"hljs-variable\">i</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">1</span>; i < number; i++) {\r\n                          <span class=\"hljs-comment\">//print angka</span>\r\n                 }\r\n         }\r\n</pre><p><span class=\"hljs-keyword\" style=\"color: rgb(33, 37, 41);\">}</span></p>', NULL, 30, NULL, '2023-06-01 08:22:55', '2024-03-23 12:02:56', NULL, 1, NULL),
(7, 7, 'Perulangan While', '<p><strong>Studi Kasus:</strong></p><p>Buatlah perulangan Loop sampai dengan memunculkan angka 1-5!</p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">LuckyFiveSecond</span> {\r\n         \r\n          <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span><span class=\"hljs-params\">(String[] args)</span> {\r\n               <span class=\"hljs-type\">int</span> <span class=\"hljs-variable\">number</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">6</span>;\r\n               <span class=\"hljs-type\">int</span> <span class=\"hljs-variable\">i</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">1</span>;\r\n               <span class=\"hljs-comment\">// isikan perulangan while</span>\r\n \r\n          }\r\n}\r\n</pre>', NULL, 30, NULL, '2023-06-01 18:14:49', '2024-03-23 12:04:43', NULL, 1, NULL),
(8, 8, 'Perulangan Do-While', '<p><strong>Studi Kasus:</strong></p><p>Buatlah program menggunakan perulangan do-while untuk menampilkan deret fibonnaci sebanyak 6 dengan angka pertama 0 dan angka kedua 1</p><p> </p><pre class=\"ql-syntax\" spellcheck=\"false\">public <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">Fibonacci</span> {\r\n      public static void main(String[] args) {\r\n            <span class=\"hljs-built_in\">int</span> n = <span class=\"hljs-number\">6</span>;\r\n            <span class=\"hljs-built_in\">int</span> first = ...;\r\n            <span class=\"hljs-built_in\">int</span> second = ...;\r\n            <span class=\"hljs-built_in\">int</span> i = <span class=\"hljs-number\">1</span>;\r\n            \r\n            System.out.<span class=\"hljs-built_in\">print</span>(<span class=\"hljs-string\">\"Deret Fibonacci: \\n\"</span>);\r\n            System.out.<span class=\"hljs-built_in\">print</span>(first + <span class=\"hljs-string\">\" \"</span> + second + <span class=\"hljs-string\">\" \"</span>);\r\n            \r\n            do {\r\n                   <span class=\"hljs-built_in\">int</span> <span class=\"hljs-built_in\">next</span> = first + second;\r\n                   System.out.<span class=\"hljs-built_in\">print</span>(<span class=\"hljs-built_in\">next</span> + <span class=\"hljs-string\">\" \"</span>);\r\n                   first = second ;\r\n                   second = <span class=\"hljs-built_in\">next</span>;\r\n                   i++;\r\n            } <span class=\"hljs-keyword\">while</span> (i <= n);\r\n      }\r\n}\r\n</pre>', NULL, 30, NULL, '2023-06-01 18:16:41', '2024-03-23 12:06:51', NULL, 1, NULL),
(9, 9, 'Perulangan bersarang piramid', '<p><strong>Studi Kasus:</strong></p><p>Buatlah program menggunakan perulangan do-while yang dapat menghasilkan keluaran seperti pada gambar berikut!</p><p><img src=\"data:image/png;base64,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\"></p><p><strong> </strong></p><pre class=\"ql-syntax\" spellcheck=\"false\">public <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">SecondPiramid</span> {\r\n      public <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span>(<span class=\"hljs-params\"><span class=\"hljs-built_in\">String</span> args[]</span>) {\r\n             <span class=\"hljs-title class_\">String</span> output = <span class=\"hljs-string\">\"\"</span>;\r\n             <span class=\"hljs-keyword\">for</span>([isi iterasi]) {\r\n                    <span class=\"hljs-keyword\">for</span>([isi iterasi]) {\r\n                          output += <span class=\"hljs-string\">\"*\"</span>;\r\n                    }\r\n                    output += <span class=\"hljs-string\">\"\\n\"</span>;\r\n             }\r\n             <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(output);\r\n      }\r\n}\r\n</pre>', NULL, 30, NULL, '2023-06-01 18:19:46', '2024-03-23 12:08:41', NULL, 1, NULL),
(10, 10, 'Array satu dimensi', '<p><strong style=\"color: black;\">Studi Kasus:</strong></p><p><span style=\"color: black;\">Buatlah data array dari data berikut!</span></p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-string\">\"Opinion\"</span>, <span class=\"hljs-string\">\"Tech\"</span>, <span class=\"hljs-string\">\"Science\"</span>, <span class=\"hljs-string\">\"Health\"</span>\r\n</pre><p><span style=\"color: black;\">Kemudian tampilkan data tersebut menjadi data String!</span></p><p><span style=\"color: black;\">Serta tambahkan import java.util.Arrays!</span></p><p> </p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">import</span> java.util.Arrays;\r\n \r\n<span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">NewsFeed</span> {\r\n         \r\n         <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span><span class=\"hljs-params\">(String[] args)</span> {\r\n                 String[] topics = {<span class=\"hljs-comment\">//isi dengan data array sesuai perintah};</span>\r\n                 <span class=\"hljs-type\">String</span> <span class=\"hljs-variable\">topicArray</span> <span class=\"hljs-operator\">=</span> Arrays.toString(topics);\r\n                 System.out.print(topicArray);\r\n         }\r\n}\r\n</pre>', NULL, 30, NULL, '2023-06-01 18:21:53', '2024-03-23 12:10:41', NULL, 1, NULL),
(11, 11, 'Array Multidimensi', '<p><strong>Studi Kasus :</strong></p><p>Seorang guru membutuhkan program untuk mengelola nilai-nilai siswanya. Program tersebut mampu untuk menghitung nilai rata-rata dengan memanfaatkan array dua dimensi. Buatlah kode program untuk kebutuhan guru tersebut!</p><p> </p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">Average</span> {\r\n      <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span><span class=\"hljs-params\">(String args[])</span> {\r\n             <span class=\"hljs-type\">double</span>[][] nilai = {{<span class=\"hljs-number\">75</span>, <span class=\"hljs-number\">80</span>, <span class=\"hljs-number\">85</span>}, {<span class=\"hljs-number\">90</span>, <span class=\"hljs-number\">95</span>, <span class=\"hljs-number\">100</span>}, {<span class=\"hljs-number\">70</span>, <span class=\"hljs-number\">75</span>, <span class=\"hljs-number\">80</span>}};\r\n             <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">total</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">0</span>;\r\n             <span class=\"hljs-type\">int</span> <span class=\"hljs-variable\">jumlahData</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">0</span>;\r\n             \r\n             <span class=\"hljs-keyword\">for</span>(<span class=\"hljs-type\">int</span> <span class=\"hljs-variable\">i</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">0</span>; i < nilai.length; i++) {\r\n                   <span class=\"hljs-keyword\">for</span>([isi iterasi]) {\r\n                          total += nilai[i][j];\r\n                          jumlahData++;\r\n                   }\r\n             }\r\n             <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">rataRata</span> <span class=\"hljs-operator\">=</span> total/jumlahData; \r\n             System.out.print(rataRata);\r\n      }\r\n}\r\n</pre>', NULL, 30, NULL, '2023-06-01 18:27:43', '2024-03-23 12:12:23', NULL, 1, NULL),
(12, 12, 'Fungsi Static', '<p><strong>Studi Kasus:</strong></p><p>Buatlah sebuah class Lingkaran yang didalamnya terdapat fungsi untuk menghitung luas dan keliling lingkaran!</p><p> </p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">Lingkaran</span> {\r\n      <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-type\">double</span> <span class=\"hljs-title function_\">luasLingkaran</span><span class=\"hljs-params\">(<span class=\"hljs-type\">double</span> phi, <span class=\"hljs-type\">int</span> r)</span> {\r\n             <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">luas</span> <span class=\"hljs-operator\">=</span> phi * r *r;\r\n             <span class=\"hljs-comment\">//tulis pengembalian nilai</span>\r\n      }\r\n      \r\n      <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-type\">double</span> <span class=\"hljs-title function_\">kelilingLingkaran</span><span class=\"hljs-params\">(<span class=\"hljs-type\">double</span> phi, <span class=\"hljs-type\">int</span> r)</span> {\r\n            <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">keliling</span> <span class=\"hljs-operator\">=</span> ….;\r\n             <span class=\"hljs-keyword\">return</span> keliling;\r\n      }\r\n      \r\n      <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">tampil</span><span class=\"hljs-params\">()</span> {\r\n             <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">phi</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">3.14</span>;\r\n             <span class=\"hljs-type\">int</span> <span class=\"hljs-variable\">r</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">14</span>;\r\n             <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">luas</span> <span class=\"hljs-operator\">=</span> luasLingkaran([isikan parameter]);\r\n             <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">keliling</span> <span class=\"hljs-operator\">=</span> kelilingLingkaran([isikan parameter]);\r\n             System.out.print(<span class=\"hljs-string\">\"Luas Lingkaran = \"</span> + luas + <span class=\"hljs-string\">\"\\n\"</span> + <span class=\"hljs-string\">\"Keliling Lingkaran = \"</span> + keliling);\r\n      }\r\n      \r\n      <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span><span class=\"hljs-params\">(String args[])</span> {\r\n             <span class=\"hljs-comment\">//panggil fungsi tampil</span>\r\n      }\r\n}\r\n</pre>', NULL, 30, NULL, '2023-06-01 18:31:05', '2024-03-23 12:14:42', NULL, 1, NULL),
(13, 13, 'Fungsi Rekursif', '<p><strong>Studi Kasus :</strong></p><p>Tentukanlah berapa banyak tabungan setelah 5 tahun dengan bunga 6% per tahun jika saldo awal sebesar Rp.1.000.000. Buatlah program dengan memanfaatkan fungsi rekursif</p><p> </p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">Bank</span> {\r\n      <span class=\"hljs-keyword\">static</span> <span class=\"hljs-type\">double</span> <span class=\"hljs-title function_\">hitungBunga</span><span class=\"hljs-params\">(...)</span> {\r\n             <span class=\"hljs-keyword\">if</span>(tahun == <span class=\"hljs-number\">0</span>) {\r\n                   <span class=\"hljs-keyword\">return</span> saldo;\r\n             } <span class=\"hljs-keyword\">else</span> {\r\n                   <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">bungaTahunan</span> <span class=\"hljs-operator\">=</span> ...;\r\n                   <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">total</span> <span class=\"hljs-operator\">=</span> saldo + ...;\r\n                   <span class=\"hljs-keyword\">return</span> hitungBunga(total, bunga, tahun - <span class=\"hljs-number\">1</span>);\r\n             }\r\n      }\r\n      \r\n      <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span><span class=\"hljs-params\">(String args[])</span> {\r\n             <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">saldoAwal</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">1000000</span>;\r\n             <span class=\"hljs-type\">int</span> <span class=\"hljs-variable\">tahun</span> <span class=\"hljs-operator\">=</span> ...;\r\n             <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">bunga</span> <span class=\"hljs-operator\">=</span> ...;\r\n             \r\n             System.out.print(<span class=\"hljs-string\">\"Jumlah uang setelah \"</span> + tahun + <span class=\"hljs-string\">\" tahun: \"</span> + hitungBunga(saldoAwal,bunga, tahun));\r\n             \r\n      }\r\n}\r\n</pre>', NULL, 30, NULL, '2023-06-01 18:37:39', '2024-03-23 12:16:22', NULL, 1, NULL),
(14, 13, 'Rekursif Bank edit', '<p><strong>Studi Kasus :</strong></p><p>Tentukanlah berapa banyak tabungan setelah 5 tahun dengan bunga 6% per tahun jika saldo awal sebesar Rp.1.000.000. Buatlah program dengan memanfaatkan fungsi rekursif</p><p> </p><pre class=\"ql-syntax\" spellcheck=\"false\"><span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">Bank</span> {\r\n  <span class=\"hljs-keyword\">static</span> <span class=\"hljs-type\">double</span> <span class=\"hljs-title function_\">hitungBunga</span><span class=\"hljs-params\">(...)</span> {\r\n  \r\n               <span class=\"hljs-keyword\">if</span>(tahun == <span class=\"hljs-number\">0</span>) {\r\n  \r\n                     <span class=\"hljs-keyword\">return</span> saldo;\r\n  \r\n               } <span class=\"hljs-keyword\">else</span> {\r\n  \r\n                     <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">bungaTahunan</span> <span class=\"hljs-operator\">=</span> ...;\r\n  \r\n                     <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">total</span> <span class=\"hljs-operator\">=</span> saldo + ...;\r\n\r\n                   <span class=\"hljs-keyword\">return</span> hitungBunga(total, bunga, tahun - <span class=\"hljs-number\">1</span>);\r\n\r\n             }\r\n\r\n      }\r\n\r\n      \r\n\r\n      <span class=\"hljs-keyword\">public</span> <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span><span class=\"hljs-params\">(String args[])</span> {\r\n\r\n             <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">saldoAwal</span> <span class=\"hljs-operator\">=</span> <span class=\"hljs-number\">1000000</span>;\r\n\r\n             <span class=\"hljs-type\">int</span> <span class=\"hljs-variable\">tahun</span> <span class=\"hljs-operator\">=</span> ...;\r\n\r\n             <span class=\"hljs-type\">double</span> <span class=\"hljs-variable\">bunga</span> <span class=\"hljs-operator\">=</span> ...;\r\n\r\n             \r\n\r\n             System.out.print(<span class=\"hljs-string\">\"Jumlah uang setelah \"</span> + tahun + <span class=\"hljs-string\">\" tahun: \"</span> + hitungBunga(saldoAwal,bunga, tahun));\r\n\r\n             \r\n\r\n      }\r\n\r\n}\r\n</pre><p>      </p>', NULL, 30, NULL, '2023-07-02 20:41:22', '2023-07-02 20:42:13', '2023-07-02 20:42:13', 1, NULL),
(15, 1, 'Tipe Data, Variabel dan Operator', '<p><br></p>', NULL, 30, NULL, '2024-02-26 07:11:38', '2024-02-26 07:12:27', '2024-02-26 07:12:27', 0, NULL),
(16, 1, 'Tipe Data, Variabel dan Operator', '<p><br></p>', NULL, 30, NULL, '2024-02-26 07:11:45', '2024-02-26 23:48:22', '2024-02-26 23:48:22', 1, NULL),
(17, 2, 'If else', '<p><br></p>', NULL, 30, NULL, '2024-03-22 11:21:16', '2024-03-22 11:29:52', '2024-03-22 11:29:52', 1, NULL),
(18, 2, 'If else', '<p><br></p>', NULL, 30, NULL, '2024-03-22 11:25:00', '2024-03-22 11:29:30', '2024-03-22 11:29:30', 1, NULL),
(19, 2, 'If else', '<p><br></p>', NULL, 30, NULL, '2024-03-22 11:27:08', '2024-03-22 11:29:45', '2024-03-22 11:29:45', 1, NULL),
(20, 1, 'If else', '<p><br></p>', NULL, 30, NULL, '2024-03-22 11:27:39', '2024-03-22 11:29:37', '2024-03-22 11:29:37', 1, NULL),
(21, 1, 'Tipe Data, Variabel dan Operator', '<p><strong style=\"color: black;\">Studi Kasus:</strong></p><p>Lengkapilah kode program berdasarkan perintah berikut :</p><ul><li>Tambahkan tipe data untuk variabel panjang, lebar, tinggi, Vbalok dan Lbalok berdasarkan nilai yang ada.</li><li>Tambahkan rumus volume balok “panjang * lebar * tinggi” pada variabel Vbalok</li><li>Tambahkan rumus volume balok “2*(panjang * lebar + panjang * tinggi + lebar * tinggi)” pada variabel Lbalok</li></ul><p> </p><pre class=\"ql-syntax\" spellcheck=\"false\">public <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">TipeData</span> {\r\n      public <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span>(<span class=\"hljs-params\"><span class=\"hljs-built_in\">String</span> args[]</span>) {\r\n             … panjang, lebar, tinggi, vBalok, lBalok;\r\n             \r\n             panjang = <span class=\"hljs-number\">10</span>;\r\n             lebar = <span class=\"hljs-number\">6</span>;\r\n             tinggi = <span class=\"hljs-number\">7</span>;\r\n             \r\n             <span class=\"hljs-comment\">// volume balok</span>\r\n             vBalok = ……;\r\n             \r\n             <span class=\"hljs-comment\">// Luas permukaan balok</span>\r\n             lBalok = …..;\r\n             \r\n             <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Volume balok = \"</span>+ vBalok + <span class=\"hljs-string\">\", \"</span>);\r\n             <span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Luas permukaan balok = \"</span>+ lBalok);\r\n             \r\n      }\r\n}\r\n</pre><p><br></p>', NULL, 30, NULL, '2024-03-22 11:31:41', '2024-03-22 11:58:04', '2024-03-22 11:58:04', 1, NULL),
(22, 1, 'Tipe Data, Variabel dan Operator', '<p><strong style=\"color: black;\">Studi Kasus:</strong></p><p>Lengkapilah kode program berdasarkan perintah berikut :</p><ul><li>Tambahkan tipe data untuk variabel panjang, lebar, tinggi, Vbalok dan Lbalok berdasarkan nilai yang ada.</li><li>Tambahkan rumus volume balok “panjang * lebar * tinggi” pada variabel Vbalok</li><li>Tambahkan rumus volume balok “2*(panjang * lebar + panjang * tinggi + lebar * tinggi)” pada variabel Lbalok</li></ul><p>&nbsp;</p><pre class=\"ql-syntax\" spellcheck=\"false\">public <span class=\"hljs-keyword\">class</span> <span class=\"hljs-title class_\">TipeData</span> {\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;public <span class=\"hljs-keyword\">static</span> <span class=\"hljs-keyword\">void</span> <span class=\"hljs-title function_\">main</span>(<span class=\"hljs-params\"><span class=\"hljs-built_in\">String</span> args[]</span>) {\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;… panjang, lebar, tinggi, vBalok, lBalok;\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;panjang = <span class=\"hljs-number\">10</span>;\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;lebar = <span class=\"hljs-number\">6</span>;\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;tinggi = <span class=\"hljs-number\">7</span>;\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-comment\">// volume balok</span>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;vBalok = ……;\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-comment\">// Luas permukaan balok</span>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;lBalok = …..;\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Volume balok = \"</span>+ vBalok + <span class=\"hljs-string\">\", \"</span>);\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-title class_\">System</span>.<span class=\"hljs-property\">out</span>.<span class=\"hljs-title function_\">print</span>(<span class=\"hljs-string\">\"Luas permukaan balok = \"</span>+ lBalok);\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;}\r\n}\r\n</pre><p><br></p>', NULL, 30, NULL, '2024-03-22 11:34:10', '2024-03-22 11:44:23', '2024-03-22 11:44:23', 1, NULL),
(25, 1, 'aaaa', '<p>aa</p>', NULL, 30, NULL, '2024-03-22 12:01:04', '2024-03-23 12:17:20', '2024-03-23 12:17:20', 1, NULL),
(26, 1, 'aaaa', '<p><br></p>', NULL, 30, NULL, '2024-03-23 12:23:52', '2024-03-23 12:24:33', '2024-03-23 12:24:33', 1, NULL);

-- --------------------------------------------------------

--
-- Table structure for table `roles`
--

CREATE TABLE `roles` (
  `id` int UNSIGNED NOT NULL,
  `role` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `roles`
--

INSERT INTO `roles` (`id`, `role`, `created_at`, `updated_at`) VALUES
(1, 'Admin', NULL, NULL),
(2, 'Students', '2022-05-31 04:18:17', '2022-05-31 04:18:17'),
(3, 'Teacher', '2022-05-31 04:19:36', '2022-05-31 04:19:36');

-- --------------------------------------------------------

--
-- Table structure for table `role_user`
--

CREATE TABLE `role_user` (
  `id` bigint UNSIGNED NOT NULL,
  `user_id` bigint UNSIGNED DEFAULT NULL,
  `role_id` bigint UNSIGNED DEFAULT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

-- --------------------------------------------------------

--
-- Table structure for table `student_courses`
--

CREATE TABLE `student_courses` (
  `id` bigint UNSIGNED NOT NULL,
  `user_id` bigint UNSIGNED NOT NULL,
  `course_id` int UNSIGNED NOT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `student_courses`
--

INSERT INTO `student_courses` (`id`, `user_id`, `course_id`, `created_at`, `updated_at`) VALUES
(1, 2, 1, '2023-06-01 05:58:57', '2023-06-01 05:58:57'),
(2, 3, 1, '2023-06-07 07:23:38', '2023-06-07 07:23:38'),
(3, 4, 1, '2023-07-06 20:14:36', '2023-07-06 20:14:36'),
(4, 6, 1, '2023-12-18 21:51:17', '2023-12-18 21:51:17'),
(5, 7, 1, '2024-03-08 07:44:11', '2024-03-08 07:44:11'),
(6, 1, 1, '2024-03-09 01:49:29', '2024-03-09 01:49:29'),
(7, 9, 1, '2024-03-11 04:59:04', '2024-03-11 04:59:04'),
(8, 10, 1, '2024-03-11 08:27:59', '2024-03-11 08:27:59'),
(9, 11, 1, '2024-03-11 08:54:12', '2024-03-11 08:54:12'),
(10, 12, 1, '2024-03-11 09:09:11', '2024-03-11 09:09:11'),
(11, 13, 1, '2024-03-11 09:20:15', '2024-03-11 09:20:15'),
(12, 14, 1, '2024-03-11 09:39:10', '2024-03-11 09:39:10'),
(13, 15, 1, '2024-03-11 09:51:06', '2024-03-11 09:51:06'),
(14, 16, 1, '2024-03-11 10:13:33', '2024-03-11 10:13:33'),
(15, 17, 1, '2024-03-11 10:22:46', '2024-03-11 10:22:46'),
(16, 19, 1, '2024-03-24 00:50:16', '2024-03-24 00:50:16'),
(17, 20, 1, '2024-03-24 01:46:07', '2024-03-24 01:46:07'),
(18, 21, 1, '2024-03-24 02:20:20', '2024-03-24 02:20:20'),
(19, 22, 1, '2024-03-28 08:58:46', '2024-03-28 08:58:46'),
(20, 23, 1, '2024-04-01 04:00:08', '2024-04-01 04:00:08'),
(21, 24, 1, '2024-04-01 04:37:18', '2024-04-01 04:37:18'),
(22, 25, 1, '2024-04-16 17:14:25', '2024-04-16 17:14:25'),
(23, 26, 1, '2024-04-26 13:24:54', '2024-04-26 13:24:54'),
(24, 27, 1, '2024-04-27 05:48:48', '2024-04-27 05:48:48'),
(25, 28, 1, '2024-04-27 13:39:07', '2024-04-27 13:39:07'),
(26, 29, 1, '2024-04-27 19:23:06', '2024-04-27 19:23:06'),
(27, 30, 1, '2024-04-28 05:53:09', '2024-04-28 05:53:09'),
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-- --------------------------------------------------------

--
-- Table structure for table `total_score`
--

CREATE TABLE `total_score` (
  `id` bigint UNSIGNED NOT NULL,
  `user_id` bigint UNSIGNED NOT NULL,
  `content_id` int UNSIGNED NOT NULL,
  `question_id` int UNSIGNED NOT NULL,
  `score` int NOT NULL,
  `wondering_score_id` bigint UNSIGNED NOT NULL,
  `user_score_id` bigint UNSIGNED NOT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `total_score`
--

INSERT INTO `total_score` (`id`, `user_id`, `content_id`, `question_id`, `score`, `wondering_score_id`, `user_score_id`, `created_at`, `updated_at`) VALUES
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(3, 2, 3, 3, 50, 4, 3, '2023-06-01 20:01:42', '2023-06-01 20:02:30'),
(4, 2, 4, 4, 68, 5, 4, '2023-06-01 20:48:40', '2023-06-01 20:48:40'),
(5, 2, 5, 5, 49, 6, 5, '2023-06-03 06:00:26', '2023-06-03 06:00:26'),
(6, 2, 6, 6, 49, 7, 6, '2023-06-03 06:40:02', '2023-06-03 06:40:02'),
(7, 2, 11, 11, 73, 13, 11, '2023-06-04 07:32:01', '2023-06-04 07:32:01'),
(8, 2, 7, 7, 58, 8, 7, '2023-06-24 06:25:08', '2023-06-24 06:25:08'),
(9, 3, 1, 1, 70, 16, 16, '2023-07-02 20:44:42', '2023-07-02 20:44:42'),
(10, 4, 1, 1, 90, 18, 18, '2023-07-06 20:23:59', '2023-07-06 20:23:59'),
(11, 6, 2, 2, 100, 19, 20, '2024-01-22 22:57:08', '2024-01-22 22:57:08'),
(12, 6, 1, 1, 80, 20, 19, '2024-01-22 23:48:21', '2024-06-19 08:34:38'),
(13, 6, 3, 3, 100, 21, 21, '2024-01-30 22:01:34', '2024-01-30 22:01:34'),
(14, 6, 4, 4, 100, 28, 22, '2024-02-26 20:33:37', '2024-02-26 20:33:37'),
(15, 6, 5, 5, 100, 29, 23, '2024-02-26 20:34:05', '2024-02-26 20:34:05'),
(16, 7, 1, 1, 85, 41, 25, '2024-03-08 07:52:30', '2024-03-08 07:52:30'),
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(19, 7, 3, 3, 100, 44, 31, '2024-03-08 08:40:00', '2024-03-08 08:40:00'),
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(23, 9, 3, 3, 100, 48, 35, '2024-03-11 05:07:59', '2024-03-11 05:07:59'),
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-- --------------------------------------------------------

--
-- Table structure for table `users`
--

CREATE TABLE `users` (
  `id` bigint UNSIGNED NOT NULL,
  `name` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
  `email` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
  `email_verified_at` timestamp NULL DEFAULT NULL,
  `password` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL,
  `remember_token` varchar(100) COLLATE utf8mb4_unicode_ci DEFAULT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL,
  `role_id` int UNSIGNED NOT NULL,
  `class` bigint DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `users`
--

INSERT INTO `users` (`id`, `name`, `email`, `email_verified_at`, `password`, `remember_token`, `created_at`, `updated_at`, `role_id`, `class`) VALUES
(1, 'admin', 'admin@gmail.com', NULL, '$2y$10$9Yu3jveXxD6UxNLoCCF6dOQz3PGZ7t5r6XFgJ5mKjfjNMii1988qm', 'uo1f0f2emkionuMAilZRGVFmir84BT5N4StXyh2q0QUmVmCIR3Zf4XUveVUY', '2023-06-01 11:21:59', '2023-06-01 11:21:59', 1, NULL),
(2, 'test0106', 'test0106@gmail.com', NULL, '$2a$12$yRljj7l8Kmx89U8HUlLbd.Bm3Eg4pgWJN5d/xMspE0X3ibadThNHC', NULL, '2023-06-01 05:58:54', '2023-06-24 22:29:00', 2, 1),
(3, 'test0706', 'test0706@gmail.com', NULL, '$2a$12$0Fp39tbhuKC6xu3AWTIOIeNB8KIKDpBW6fMgao7xJMLRSKh.l9xgC', NULL, '2023-06-07 07:23:31', '2023-06-24 22:29:08', 2, 2),
(4, 'fransiska_test', 'test0707@gmail.com', NULL, '$2y$10$R.vDVcCv5ufOaJFr9rb4Je0DrrIoX.11ooalBbMfKojZnAmicDyL2', NULL, '2023-07-06 18:37:55', '2023-07-06 18:37:55', 2, 2),
(5, 'test0109', 'test0109@gmail.com', NULL, '$2y$10$izw5.r5EwLcTdIDkYbb6HeajEHTkHK6.a8xNAtylIxAz8fCARpSNy', NULL, '2023-09-01 08:14:22', '2023-09-01 08:14:22', 2, 2),
(6, 'rossa akmalia', 'rossaakmalia66@gmail.com', NULL, '$2y$10$oYgZ49oPvibYzdu39A18ReINP4GyXmh7byUB0XyK.uhhJMN6/5kWa', NULL, '2023-12-18 21:04:51', '2023-12-18 21:04:51', 2, 1),
(7, 'Percobaan 1', 'percobaan1@gmail.com', NULL, '$2y$10$pZkSSzb/ZYVPJEaumgsz2.nM106KmW1vrNW2a2B0tzb8Knvpzf2iq', NULL, '2024-03-08 07:41:59', '2024-03-08 07:41:59', 2, 2),
(8, 'Admin2', 'admin2@gmail.com', NULL, '$2y$10$9z58abgbHvj1gqSWNnfmyeuvzEYBM0PJ53OMJcr2UaGSaHJE.owq.', NULL, '2024-03-09 02:39:36', '2024-03-09 02:39:36', 1, 2),
(9, 'Percobaan2', 'percobaan2@gmail.com', NULL, '$2y$10$dub9iNoPWHn9LYqrkPbiY.MFF2v3c.oCUKHjkOvBUTp5xCb33jbJ.', NULL, '2024-03-11 04:54:39', '2024-03-11 04:54:39', 2, 2),
(10, 'Case Folding Lower', 'lower@gmail.com', NULL, '$2y$10$7pEoOwfz1ZhZOGXfN35rhuEGMOmKyvhIMzrMDHy535ZfSQZ2y7BFu', NULL, '2024-03-11 08:27:55', '2024-03-11 08:27:55', 2, 2),
(11, 'Case Folding Lower dan Tanda Baca', 'lowertandabaca@gmail.com', NULL, '$2y$10$CXvEpobtXCeLiAPgyXroLusxgbpcyUQpZ39YgRcBnAwm.dNwpn472', NULL, '2024-03-11 08:54:10', '2024-03-11 08:54:10', 2, 2),
(12, 'Case Folding Lower dan Stopwords', 'lowerstopword@gmail.com', NULL, '$2y$10$z.YuIll2yOdv.IZRrU.yI.oehT9IwXxlzW8CVJ0McgUUtuHd2YtwO', NULL, '2024-03-11 09:07:04', '2024-03-11 09:07:04', 2, 2),
(13, 'Case Folding Lower dan Steeming', 'lowersteeming@gmail.com', NULL, '$2y$10$auZMY7SZZ5PFZgmUxKIdOOkRihOcPb8/b6q0fAB/a59lvenVF48Qu', NULL, '2024-03-11 09:20:13', '2024-03-11 09:20:13', 2, 2),
(14, 'Case Folding Lower Tanda Baca dan Stopword', 'lowertandabacastopword@gmail.com', NULL, '$2y$10$OB8eA7t.0eO0jL6jY5cTme4tDa/hq5yT9dSm16/y7VdI3G2HcUjCG', NULL, '2024-03-11 09:39:08', '2024-03-11 09:39:08', 2, 2),
(15, 'Case Folding Lower Tanda Baca dan Steeming', 'lowertandasteeming@gmail.com', NULL, '$2y$10$nn.yuel00two2Hvo/Cw0/eDDctUVeRdMRfnKcRhrmHYItQU.eaUA2', NULL, '2024-03-11 09:50:59', '2024-03-11 09:50:59', 2, 2),
(16, 'Case Folding Lower Stopword dan Steeming', 'lowerstopwordsteeming@gmail.com', NULL, '$2y$10$v2yAYfo/UnXC03tN6cj4fOGqi/m.qXxvvnHq03X2UVFb954vpwxsG', NULL, '2024-03-11 10:13:31', '2024-03-11 10:13:31', 2, 2),
(17, 'Case Folding Lower Tanda Baca Stopword dan Steeming', 'lowertandastopwordsteeming@gmail.com', NULL, '$2y$10$s4V7CNM12G5W3cvt5YC2EOKKGIWIJb6/FdfIgqfHo9KBAG.jTHon.', NULL, '2024-03-11 10:22:44', '2024-03-11 10:22:44', 2, 2),
(19, 'Case Folding Lower Tanda Baca non Sistematis', 'lowertandabacanonsistematis@gmail.com', NULL, '$2y$10$aOpVIl3u8/4.rymY6qKUvOLKMMGT7Cn0pL.TSropSiDX/l6ElnOji', NULL, '2024-03-24 00:50:14', '2024-03-24 00:51:46', 2, 2),
(20, 'Case Folding Lower Tanda Baca non Sistematis Stopword', 'lowertandasistematisstopword@gmail.com', NULL, '$2y$10$QGcfa26RyvHO9i/qOBWT3Ox5BdM46/mrTm/P.Jz4jz3vc5PUwcofK', NULL, '2024-03-24 01:45:58', '2024-03-24 01:45:58', 2, 2),
(21, '4 Kunci Jawaban', 'kuncijawaban4@gmail.com', NULL, '$2y$10$4Yd1AMuS1EQezGWfxyqM5uaNSlSxLq5R1GK6nzPEgFTl5avvCj2zi', NULL, '2024-03-24 02:20:19', '2024-03-24 02:20:19', 2, 1),
(22, 'Kunci 4 Lower Tanda Baca Non Sistematis Steeming', 'kunci4lowertandanonsistematissteeming@gmail.com', NULL, '$2y$10$uScWr2R3Qk3537fkXOL0SOjmwb7RhLDUDEkzCRGr99s5/NlcOSBQ2', NULL, '2024-03-28 08:58:44', '2024-03-28 08:58:44', 2, 1),
(23, 'Case Folding Lower Tanda Baca non Sistematis Steeming', 'lowertandanonsistematissteeming@gmail.com', NULL, '$2y$10$Jp4Mh/Oof0wFW9x8BiW7Auf1c2ylmnDkxio1ev1n5YZn0NmpbFRDW', NULL, '2024-04-01 04:00:03', '2024-04-01 04:00:03', 2, 1),
(24, 'Case Folding Sinonim', 'sinonim@gmail.com', NULL, '$2y$10$ERwH6SKrzJBhBySgdZC3uObFrLEINNfm5SyBQT/Kf86XaVOcCV0IS', NULL, '2024-04-01 04:37:15', '2024-04-01 04:37:15', 2, 1),
(25, 'User Baru', 'userbaru@gmail.com', NULL, '$2y$10$n65rIKYSWkY9R.Ad0G/IYea0v9jInnQdB2kLlQXBGFAzZPhLHwsO6', NULL, '2024-04-16 17:14:21', '2024-04-16 17:14:21', 2, 1),
(26, 'Jawaban Benar Ori', 'jawabanbenarori@gmail.com', NULL, '$2y$10$hTvv2Aqq5I1eHRrUckIWE.tKnmwXrerwCVYRaf6kym9IqcWawJBm6', NULL, '2024-04-26 13:24:15', '2024-04-26 13:24:15', 2, 1),
(27, 'Jawaban Tanda Baca', 'jawabantandabaca@gmail.com', NULL, '$2y$10$FWZMqgfWPfkOjC1adYonVeaxOwnjfJi/8dbQhQK7u6JhsxTGMy2r.', NULL, '2024-04-27 05:48:46', '2024-04-27 05:48:46', 2, 2),
(28, 'Jawaban Lower', 'jawabanlower@gmail.com', NULL, '$2y$10$Y4eKB0bawA.41ti.AiPI3OiicPkUpGTSQHNj5Mm.zt43h2Kk4jkt6', NULL, '2024-04-27 13:39:01', '2024-04-27 13:39:01', 2, 2),
(29, 'Jawaban Stopword', 'jawavabstopword@gmail.com', NULL, '$2y$10$Qjxavi3Gtx2KK92aK/Nwt.eaFowxQpi5dGMnYlvSmR6kMljR6JT0i', NULL, '2024-04-27 19:22:56', '2024-04-27 19:22:56', 2, 2),
(30, 'Jawaban Steeming', 'jawabansteeming@gmail.com', NULL, '$2y$10$49SDWTyotwnCF8axIYem2.vL9fKZD8kj0bOIUpOqxePtrEwTbdYhm', NULL, '2024-04-28 05:53:05', '2024-04-28 05:53:05', 2, 2),
(31, 'Jawaban Sinonim', 'jawabansinonim@gmail.com', NULL, '$2y$10$aM6tygESjJ2wzeqjoJH96OE92NuT.pOnVYh71wyREpqKAUTxJbcvi', NULL, '2024-04-28 13:55:02', '2024-04-28 13:55:02', 2, 2),
(32, 'Jawaban Tanda Baca Lower', 'jawabantandabacalower@gmail.com', NULL, '$2y$10$704t.mYRLNG4AR8SMZiileeFV6OuyZ0NV/NphYRReRxN4J9lQn7oG', NULL, '2024-05-01 19:20:09', '2024-05-01 19:20:09', 2, 2),
(33, 'abc', 'abc@gmail.com', NULL, '$2y$10$rJfslKPiEYaCSA3RMpHnX.ZDa7YFALUW3yF/Agz75X9R8c1vPafIO', NULL, '2024-05-01 20:40:33', '2024-05-01 20:40:33', 2, 1),
(34, 'baru', 'baru@gmail.com', NULL, '$2y$10$RDVAb1t9jO0FHG9mQhE3OOsOZFfKXdCNohzLepiV2WCcNHx59Flfi', NULL, '2024-05-01 21:30:04', '2024-05-01 21:30:04', 2, 1),
(35, 'Jawaban Tanda Baca Lower Steeming', 'jawabantandalowersteeming@gmail.com', NULL, '$2y$10$vvEa9rUzWjYmYgdFcuW9iOnNOmdvHMzazcJrxw/7.Pjjb8LRMgftK', NULL, '2024-05-02 16:39:40', '2024-05-02 16:39:40', 2, 1),
(36, 'Jawaban Tanda Lower Stop Steem', 'jawabantandalowerstopsteem@gmail.com', NULL, '$2y$10$WO3LfngPWcwBjjkkQHKO0.q33H7Rt5vN9kzJ3j93BAX/KpUl6ejSi', NULL, '2024-05-03 03:10:40', '2024-05-03 03:10:40', 2, 1),
(37, 'SteemingBaru', 'steemingbaru@gmail.com', NULL, '$2y$10$y0jzWd35jGpRTZ3U0egVwefyGNGpFCBUySYqznCrkIvA0VTRNuWHK', NULL, '2024-06-03 05:06:10', '2024-06-03 05:06:10', 2, 1),
(38, 'aaa', 'aaaa@gmail.com', NULL, '$2y$10$2WGpk17g.bNpEDL6N2Zdz.cJkr9jBvnyr2iAmAyDMTvsSoaCecB9G', NULL, '2024-06-09 20:12:38', '2024-06-09 20:12:38', 2, 3),
(39, 'Ifa Indrian', 'ifa@gmail.com', NULL, '$2y$10$0y6eOsEicvzhbFOvfTdbluepHmaMI4bunJZ6G06bgpSNkWHvtcfN6', NULL, '2024-06-10 01:50:09', '2024-06-10 01:50:09', 2, 1),
(40, 'Della Jannata', 'della@gmail.com', NULL, '$2y$10$99RvTjjUO.VkaxPyPzKSKepafxpo74RqaPcBtkdXbulOf5Jwna2zK', NULL, '2024-06-10 03:09:07', '2024-06-10 03:09:07', 2, 1),
(41, 'Lia Puspita', 'lia@gmail.com', NULL, '$2y$10$ObLkI4KvNbSM5N3RW4c5zu1mhF9euiSLoXLo5W6siAUsoCAUn/gGu', NULL, '2024-06-10 03:53:51', '2024-06-10 03:53:51', 2, 1),
(42, 'Rossa', 'rossa@gmail.com', NULL, '$2y$10$1dYp/OskcCPxeC8pqT76Ne3Vds2ULE0XxCj6iqAQMbcbryaOwB682', NULL, '2024-06-22 05:41:34', '2024-06-22 05:41:34', 2, 1),
(43, 'pelajar', 'pelajar@gmail.com', NULL, '$2y$10$JJ4o6TF4pm9yE2L9wBLJSuED5fwczIKf6PVye.y9C0x8Yy2tDf0Dy', NULL, '2024-06-23 07:44:13', '2024-06-23 07:44:13', 2, 1),
(44, 'Normalisasi', 'normalisasi@gmail.com', NULL, '$2y$10$h8SNuFcOOKUhBPwaElGm8uKNR7lANLXgGAhZ5JncIosyQ2c4FC2MW', NULL, '2024-06-24 11:39:34', '2024-06-24 11:39:34', 2, 1),
(45, 'revisi', 'revisi@gmail.com', NULL, '$2y$10$EwdW/pqRIjfx8.CGkrWkp..111VmhrfMeKMXDZFz5drvHNkLmGEMG', NULL, '2024-06-30 10:50:56', '2024-06-30 10:50:56', 2, 1);

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-- Table structure for table `user_answer`
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  `user_id` bigint UNSIGNED NOT NULL,
  `essay_question_id` bigint UNSIGNED NOT NULL,
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INSERT INTO `user_answer` (`id`, `user_id`, `essay_question_id`, `answer`, `created_at`, `updated_at`, `deleted_at`) VALUES
(1, 2, 1, 'Karena nilai dari variabel tersebut berbentuk bilangan bulat', '2023-06-01 18:47:46', '2023-06-01 18:47:46', NULL),
(2, 2, 2, 'Langkah-langkah perhitungan volume balok adalah mengalikan panjang, lebar, dan tinggi balok. Sedangkan langkah-langkah perhitungan luas permukaan balok adalah menghitung jumlah sisi-sisi balok (2 sisi panjang * lebar, 2 sisi panjang * tinggi, dan 2 sisi lebar * tinggi) kemudian menjumlahkannya.', '2023-06-01 18:47:46', '2023-06-01 18:47:46', NULL),
(3, 2, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, Anda dapat mengganti nilai pada bagian panjang = 10, lebar = 6, dan tinggi = 7 dengan nilai yang diinginkan', '2023-06-01 18:47:46', '2023-06-01 18:47:46', NULL),
(4, 2, 4, 'If digunakan dalam kode tersebut untuk membuat kondisi atau pernyataan logis. Dalam konteks kode tersebut, if digunakan untuk melakukan pengecekan apakah nilai lebih besar dari 70. Jika kondisi tersebut terpenuhi, yaitu nilai lebih besar dari 70, maka pesan \"Selamat anda lulus!\" akan dicetak. If digunakan untuk memberikan pengambilan keputusan berdasarkan kondisi tertentu, yang memungkinkan eksekusi kode yang berbeda tergantung pada hasil kondisi yang dievaluasi.', '2023-06-01 19:32:48', '2023-06-01 19:32:48', NULL),
(5, 2, 5, 'Alur program dari kode di atas adalah sebagai berikut:\n\n•	Pertama, program akan menjalankan fungsi main yang merupakan titik masuk utama dalam program Java.\n•	Kemudian, sebuah variabel nilai dengan tipe data integer dideklarasikan dan diinisialisasi dengan nilai 80.\n•	Program akan melanjutkan ke blok if, yang akan mengevaluasi apakah nilai lebih besar dari 70.\n•	Jika kondisi dalam blok if (nilai > 70) bernilai true, program akan mengeksekusi pernyataan yang ada di dalam blok if, yaitu mencetak string \"Selamat anda lulus!\" menggunakan System.out.print().\n•	Jika kondisi dalam blok if bernilai false, program akan melanjutkan ke pernyataan setelah blok if dan program akan selesai.', '2023-06-01 19:32:49', '2023-06-01 19:32:49', NULL),
(6, 2, 6, 'Jika nilai variabel “nilai” kurang dari 70, maka tidak akan ada output yang ditampilkan, karena tidak ada pernyataan lain setelah kondisi if.', '2023-06-01 19:32:49', '2023-06-01 19:32:49', NULL),
(7, 2, 7, 'If-else digunakan untuk membagi kondisi menjadi dua kemungkinan. Dalam studi kasus diatas, IF digunakan untuk melakukan pengecekan apakah nilai itemCost lebih besar dari 24. Jika kondisi tersebut terpenuhi, maka variabel order bernilai \"High Value Item!\" akan dicetak. Sedangkan jika nilai itemCost tidak lebih dari 24, maka variabel order bernilai “Low Order Value!”', '2023-06-01 19:45:23', '2023-06-01 19:45:23', NULL),
(8, 2, 8, '•	Mendeklarasikan kelas Order.\n•	Mendeklarasikan method main sebagai method utama yang akan dieksekusi saat program dijalankan.\n•	Mendeklarasikan variabel itemCost dengan tipe data double dan memberikannya nilai 30.99.\n•	Mendeklarasikan variabel order dengan tipe data String dan memberikannya nilai awal berupa string kosong (\"\").\n•	Melakukan pengecekan kondisi menggunakan pernyataan if. Kondisi yang dievaluasi adalah itemCost > 24.00.\n•	Jika kondisi tersebut benar (nilai itemCost lebih besar dari 24.00), maka blok kode di dalam if akan dieksekusi.\n•	Dalam blok if, nilai variabel order diubah menjadi \"High Value Item!\".\n•	Jika kondisi dalam if tidak terpenuhi (nilai itemCost tidak lebih besar dari 24.00), maka blok kode di dalam else akan dieksekusi.\n•	Dalam blok else, nilai variabel order diubah menjadi \"Low Value Item!\".\n•	Setelah blok if-else selesai dieksekusi, pesan yang ada dalam variabel order akan dicetak menggunakan System.out.print.\n•	Output yang ditampilkan akan bergantung pada nilai itemCost. Jika itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan dicetak. Jika tidak, maka pesan \"Low Value Item!\" akan dicetak.', '2023-06-01 19:45:23', '2023-06-01 19:45:23', NULL),
(9, 2, 9, 'Program akan menampilkan output “Low Value Item”', '2023-06-01 19:45:23', '2023-06-01 19:45:23', NULL),
(10, 2, 10, 'Dengan menggunakan default, program akan menangani situasi di mana nilai shipping tidak cocok dengan case-case yang didefinisikan sebelumnya. Default berfungsi sebagai pilihan terakhir yang akan dieksekusi jika tidak ada case yang cocok dengan nilai yang dievaluasi.', '2023-06-01 20:47:17', '2023-06-01 20:47:17', NULL),
(11, 2, 11, 'Alur program dari baris kode switch-case di atas adalah sebagai berikut:\n\nProgram dimulai dengan mendeklarasikan variabel shipping dengan nilai \"Express\" dan variabel shippingCost tanpa nilai awal. Kemudian, program melanjutkan ke switch statement dengan mengevaluasi nilai dari variabel shipping. \n\nProgram akan membandingkan nilai shipping dengan setiap case yang ada. Jika nilai shipping cocok dengan salah satu case, program akan melompat ke blok kode yang sesuai dengan case tersebut.\nJika nilai shipping adalah \"Regular\", maka variabel shippingCost akan diatur menjadi 0.\nJika nilai shipping adalah \"Express\", maka variabel shippingCost akan diatur menjadi 1.75.\nJika nilai shipping tidak cocok dengan case-case di atas, program akan melompat ke blok kode dalam default.\nPada blok kode default, variabel shippingCost akan diatur menjadi 0.50.\n\nSetelah switch statement selesai dieksekusi, program akan mencetak nilai shippingCost dengan menggunakan pernyataan System.out.print(\"Shipping cost: \" + shippingCost);.\nDengan demikian, alur program akan menentukan nilai shippingCost berdasarkan nilai shipping yang dievaluasi menggunakan switch-case.', '2023-06-01 20:47:17', '2023-06-01 20:47:17', NULL),
(12, 2, 12, 'Pada saat nilai shipping tidak bernilai regular maupun express, sehingga mengeluarkan nilai default, yaitu 0.05', '2023-06-01 20:47:17', '2023-06-01 20:47:17', NULL),
(13, 2, 13, 'Karena variabel isMember di rancang untuk menampung nilai salah saja', '2023-06-03 05:19:09', '2023-06-03 05:55:47', NULL),
(14, 2, 14, '•	Jika nilai isMember adalah false, maka program akan masuk kedalam pemilihan else.\n•	Program akan melakukan pengecekan total. Diketahui total adalah 200000, sehingga masuk kedalam blok pemilihan ketiga dengan diskon 15 %\n•	Sehingga, output dari program tersebut adalah “diskon yang didapatkan adalah 10%”', '2023-06-03 05:19:09', '2023-06-03 05:55:47', NULL),
(15, 2, 15, 'program akan mengeluarkan output “diskon yang didapatkan adalah 90%”', '2023-06-03 05:19:09', '2023-06-03 05:34:08', NULL),
(16, 2, 16, 'd', '2023-06-03 06:38:15', '2023-06-03 06:39:41', NULL),
(17, 2, 17, 'b', '2023-06-03 06:38:15', '2023-06-03 06:38:15', NULL),
(18, 2, 18, 'c', '2023-06-03 06:38:15', '2023-06-03 06:38:15', NULL),
(19, 2, 19, 'Pada kode program tersebut, i++ digunakan sebagai operator penambahan (increment) pada variabel i.\n\nKegunaan dari i++ adalah untuk menambahkan nilai 1 pada variabel i setiap kali perulangan dilakukan. Dalam konteks kode program yang diberikan, setiap iterasi perulangan akan mencetak nilai i dan kemudian nilai i akan ditambah 1 menggunakan i++.\n\nSehingga, i++ berguna untuk mengatur aliran perulangan dan menghindari terjadinya perulangan tak terbatas (infinite loop) dengan memastikan bahwa kondisi perulangan pada while-loop (i < number) akan berhenti pada suatu titik saat nilai i mencapai nilai number yang ditentukan.', '2023-06-04 06:27:46', '2023-06-04 06:27:46', NULL),
(20, 2, 20, 'Variabel number diinisialisasi dengan nilai 6, dan variabel i diinisialisasi dengan nilai 1. Kondisi i < number dievaluasi. Jika kondisi tersebut terpenuhi (nilai i kurang dari number), maka blok kode di dalam while loop akan dieksekusi. Jika kondisi tidak terpenuhi, maka program akan keluar dari loop. Di dalam loop, perintah System.out.print(i) akan mencetak nilai i ke layar. \n\nPada iterasi pertama, nilai i adalah 1, sehingga angka 1 akan dicetak. Selanjutnya, perintah i++ akan menambahkan nilai i sebesar 1. Proses di atas akan diulang terus menerus selama kondisi i < number masih terpenuhi. Pada setiap iterasi, nilai i akan bertambah 1 dan angka tersebut akan dicetak ke layar. \n\nLoop akan berhenti saat nilai i sama dengan atau melebihi nilai number, yaitu saat i bernilai 6. Setelah loop selesai, program akan keluar dari blok while dan program akan berakhir.', '2023-06-04 06:27:46', '2023-06-04 06:27:46', NULL),
(21, 2, 21, 'Output dari kode program di atas adalah tidak ada. Hal ini dikarenakan kondisi pada while loop, yaitu i > number, tidak terpenuhi pada awalnya. Karena nilai awal i adalah 1 dan number adalah 6, maka kondisi 1 > 6 akan bernilai false. Oleh karena itu, blok kode dalam while loop tidak akan dieksekusi, sehingga tidak ada output yang dicetak ke layar.', '2023-06-04 06:27:46', '2023-06-04 06:27:46', NULL),
(22, 2, 22, 'Pada program Fibonacci, fungsi dari kode “int next = first + second;” adalah untuk menghitung nilai angka selanjutnya dalam deret Fibonacci.\n\nPada setiap iterasi perulangan, nilai next dihitung dengan menjumlahkan nilai first dan second. Kemudian, nilai next akan menjadi angka baru dalam deret Fibonacci.\n\nMisalnya, pada awalnya first memiliki nilai 0 dan second memiliki nilai 1. Pada iterasi pertama, next akan dihitung sebagai 0 + 1 = 1. Setelah itu, nilai first akan diperbarui menjadi 1 dan nilai second akan diperbarui menjadi 1.\n\nPada iterasi berikutnya, next akan dihitung sebagai 1 + 1 = 2. Proses ini akan terus berlanjut sampai mencapai jumlah angka Fibonacci yang diinginkan.\n\nDengan mengupdate nilai first dan second setiap kali perulangan dilakukan, kita dapat menghasilkan deret Fibonacci dengan benar.', '2023-06-04 06:48:55', '2023-06-04 06:48:55', NULL),
(23, 2, 23, 'Variabel next diinisialisasi dengan hasil penjumlahan first dan second.\nNilai next dicetak menggunakan perintah System.out.print(next + \" \"), sehingga akan mencetak nilai next diikuti dengan spasi. Nilai first diperbarui dengan nilai second. Nilai second diperbarui dengan nilai next. \n\nVariabel i (yang merupakan counter) ditambahkan dengan 1 menggunakan perintah i++. Kondisi i <= n dievaluasi. Jika kondisi tersebut terpenuhi, maka program akan kembali ke langkah 1 dan melanjutkan iterasi berikutnya. Jika kondisi tidak terpenuhi, maka program akan keluar dari loop.\n\nLangkah-langkah 1-6 akan terus diulang sampai kondisi i <= n tidak terpenuhi.', '2023-06-04 06:48:55', '2023-06-04 06:48:55', NULL),
(24, 2, 24, 'Deret Fibonnaci: \n0 1 1 2 3 5 8 13 21', '2023-06-04 06:48:55', '2023-06-04 06:48:55', NULL),
(25, 2, 25, 'Kode program tersebut berfungsi untuk menentukan jumlah baris piramida bintang. Jika 5 diganti menjadi 7, maka baris piramida menjadi 7 baris', '2023-06-04 06:58:24', '2023-06-04 06:58:24', NULL),
(26, 2, 26, 'Perulangan akan dimulai dari nilai 1 dan berakhir pada saat nilai “j” sama dengan atau kurang dari nilai “i”. Saat kondisi terpenuhi, satu bintang akan ditambahkan ke variabel “output”, jumlah bintang akan terus bertambah seiring dengan nilai “i” yang meningkat.', '2023-06-04 06:58:24', '2023-06-04 06:58:24', NULL),
(27, 2, 27, 'Jumlah baris piramida akan bertambah 1 baris, sehingga menjadi 6 baris, dengan baris terakhir memiliki 6 bintang.', '2023-06-04 06:58:24', '2023-06-04 06:58:24', NULL),
(28, 2, 28, 'Yang merubah array menjadi data string adalah baris kode Arrays.toString(topics)', '2023-06-04 07:00:54', '2023-06-04 07:00:54', NULL),
(29, 2, 29, 'Array topics berisi empat elemen yang mewakili topik-topik berita, yaitu \"Opinion\", \"Tech\", \"Science\", dan \"Health\". Variabel topicArray diinisialisasi dengan hasil pemanggilan Arrays.toString(topics). Fungsi Arrays.toString() digunakan untuk mengonversi array topics menjadi string dengan format yang sesuai.\n\nSelanjutnya, perintah System.out.print(topicArray) digunakan untuk mencetak isi dari variabel topicArray, yaitu string yang berisi daftar topik-topik berita yang diubah dari array topics.\nKetika program dijalankan, string yang berisi daftar topik-topik berita akan ditampilkan sebagai output.', '2023-06-04 07:00:54', '2023-06-04 07:00:54', NULL),
(30, 2, 30, 'Error. Karena elemen array berisi bilangan bulat, sedangkan tipe data array adalah String', '2023-06-04 07:00:54', '2023-06-04 07:00:54', NULL),
(31, 2, 31, 'Fungsi dari kode tersebut adalah untuk membatasi jumlah perulangan sebanyak jumlah panjang data dari array nilai.', '2023-06-04 07:05:09', '2023-06-04 07:05:09', NULL),
(34, 2, 32, 'Perulangan akan dimulai dari nilai 0 dan berakhir pada saat nilai “j” kurang dari jumlah panjang array nilai. Saat kondisi terpenuhi, satu nilai akan ditambahkan ke variabel “total', '2023-06-04 07:05:09', '2023-06-04 07:05:09', NULL),
(37, 2, 33, 'Rata-rata yang didapatkan adalah 82', '2023-06-04 07:05:09', '2023-06-04 07:05:09', NULL),
(40, 2, 34, 'untuk memanggil fungsi tampil()', '2023-06-04 07:15:40', '2023-06-04 07:15:40', NULL),
(41, 2, 35, 'mengeluarkan output', '2023-06-04 07:15:40', '2023-06-04 07:15:40', NULL),
(42, 2, 36, 'program tidak akan mengeluarkan output apapun', '2023-06-04 07:15:40', '2023-06-04 07:15:40', NULL),
(43, 2, 37, 'ya, terletak pada fungsi hitungBunga, dengan memanggil dirinya sendiri', '2023-06-04 07:19:22', '2023-06-04 07:19:22', NULL),
(44, 2, 38, 'jhkk', '2023-06-04 07:19:22', '2023-06-04 07:28:54', NULL),
(45, 2, 39, '1402551.73', '2023-06-04 07:19:22', '2023-06-04 07:27:28', NULL),
(46, 3, 1, 'variabel panjang, lebar, tinggi, vBalok dan lBalok b', '2023-06-07 07:34:36', '2023-06-07 07:34:36', NULL),
(47, 3, 2, 'langkah-langkah perhitungan volume dan luas permukaan balok', '2023-06-07 07:34:36', '2023-06-07 07:34:36', NULL),
(48, 3, 3, 'engubah nilai panjang, lebar, dan tinggi', '2023-06-07 07:34:36', '2023-06-07 07:34:36', NULL),
(49, 3, 4, 'If digunakan dalam kode tersebut untuk membuat kondisi atau pernyataan logis. Dalam konteks kode tersebut, if digunakan untuk melakukan pengecekan apakah nilai lebih besar dari 70. Jika kondisi tersebut terpenuhi,', '2023-07-06 19:31:59', '2023-07-06 19:31:59', NULL),
(50, 3, 5, 'Alur program dari kode di atas adalah sebagai berikut:\n\n•	Pertama, program akan menjalankan fungsi main yang merupakan titik masuk utama dalam program Java.\n•	Kemudian, sebuah variabel nilai dengan tipe data integer dideklarasikan dan diinisialisasi dengan nilai 80.\n•	Program akan melanjutkan ke blok if, yang akan mengevaluasi apakah nilai lebih besar dari 70.', '2023-07-06 19:31:59', '2023-07-06 19:31:59', NULL),
(51, 3, 6, 'Jika nilai variabel “nilai” kurang dari 70, maka tidak akan ada output yang ditampilkan, karena tidak ada pernyataan lain setelah kondisi if.', '2023-07-06 19:31:59', '2023-07-06 19:31:59', NULL),
(52, 4, 1, 'Karena nilai dari variabel tersebut berbentuk bilangan bulat', '2023-07-06 20:23:08', '2023-07-06 20:23:08', NULL),
(53, 4, 2, 'A', '2023-07-06 20:23:08', '2023-07-06 20:23:08', NULL),
(54, 4, 3, 'S', '2023-07-06 20:23:08', '2023-07-06 20:23:08', NULL),
(55, 6, 1, 'Karena nilai dari variabel tersebut berbentuk bilangan bulat', '2024-01-22 22:07:25', '2024-01-22 22:07:25', NULL),
(56, 6, 2, 'Langkah-langkah perhitungan volume balok adalah mengalikan panjang, lebar, dan tinggi balok. Sedangkan langkah-langkah perhitungan luas permukaan balok adalah menghitung jumlah sisi-sisi balok (2 sisi panjang * lebar, 2 sisi panjang * tinggi, dan 2 sisi lebar * tinggi) kemudian menjumlahkannya.', '2024-01-22 22:07:25', '2024-01-22 22:07:25', NULL),
(57, 6, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, Anda dapat mengganti nilai pada bagian panjang = 10, lebar = 6, dan tinggi = 7 dengan nilai yang diinginkan.', '2024-01-22 22:07:25', '2024-01-22 22:07:25', NULL),
(58, 6, 4, 'If digunakan dalam kode tersebut untuk membuat kondisi atau pernyataan logis. Dalam konteks kode tersebut, if digunakan untuk melakukan pengecekan apakah nilai lebih besar dari 70. Jika kondisi tersebut terpenuhi, yaitu nilai lebih besar dari 70, maka pesan \"Selamat anda lulus!\" akan dicetak. If digunakan untuk memberikan pengambilan keputusan berdasarkan kondisi tertentu, yang memungkinkan eksekusi kode yang berbeda tergantung pada hasil kondisi yang dievaluasi.', '2024-01-22 22:49:43', '2024-01-22 22:49:43', NULL),
(59, 6, 5, 'Alur program dari kode di atas adalah sebagai berikut:\n\n•	Pertama, program akan menjalankan fungsi main yang merupakan titik masuk utama dalam program Java.\n•	Kemudian, sebuah variabel nilai dengan tipe data integer dideklarasikan dan diinisialisasi dengan nilai 80.\n•	Program akan melanjutkan ke blok if, yang akan mengevaluasi apakah nilai lebih besar dari 70.\n•	Jika kondisi dalam blok if (nilai > 70) bernilai true, program akan mengeksekusi pernyataan yang ada di dalam blok if, yaitu mencetak string \"Selamat anda lulus!\" menggunakan System.out.print().\n•	Jika kondisi dalam blok if bernilai false, program akan melanjutkan ke pernyataan setelah blok if dan program akan selesai.', '2024-01-22 22:49:43', '2024-01-22 22:49:43', NULL),
(60, 6, 6, 'Jika nilai variabel “nilai” kurang dari 70, maka tidak akan ada output yang ditampilkan, karena tidak ada pernyataan lain setelah kondisi if.', '2024-01-22 22:49:44', '2024-01-22 22:49:44', NULL),
(61, 6, 7, 'If-else digunakan untuk membagi kondisi menjadi dua kemungkinan. Dalam studi kasus diatas, IF digunakan untuk melakukan pengecekan apakah nilai itemCost lebih besar dari 24. Jika kondisi tersebut terpenuhi, maka variabel order bernilai \"High Value Item!\" akan dicetak. Sedangkan jika nilai itemCost tidak lebih dari 24, maka variabel order bernilai “Low Order Value!”', '2024-01-30 21:58:48', '2024-01-30 21:58:48', NULL),
(62, 6, 8, '•	Mendeklarasikan kelas Order.\n•	Mendeklarasikan method main sebagai method utama yang akan dieksekusi saat program dijalankan.\n•	Mendeklarasikan variabel itemCost dengan tipe data double dan memberikannya nilai 30.99.\n•	Mendeklarasikan variabel order dengan tipe data String dan memberikannya nilai awal berupa string kosong (\"\").\n•	Melakukan pengecekan kondisi menggunakan pernyataan if. Kondisi yang dievaluasi adalah itemCost > 24.00.\n•	Jika kondisi tersebut benar (nilai itemCost lebih besar dari 24.00), maka blok kode di dalam if akan dieksekusi.\n•	Dalam blok if, nilai variabel order diubah menjadi \"High Value Item!\".\n•	Jika kondisi dalam if tidak terpenuhi (nilai itemCost tidak lebih besar dari 24.00), maka blok kode di dalam else akan dieksekusi.\n•	Dalam blok else, nilai variabel order diubah menjadi \"Low Value Item!\".\n•	Setelah blok if-else selesai dieksekusi, pesan yang ada dalam variabel order akan dicetak menggunakan System.out.print.\n•	Output yang ditampilkan akan bergantung pada nilai itemCost. Jika itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan dicetak. Jika tidak, maka pesan \"Low Value Item!\" akan dicetak.', '2024-01-30 21:58:48', '2024-01-30 21:58:48', NULL),
(63, 6, 9, 'Program akan menampilkan output “Low Value Item”', '2024-01-30 21:58:48', '2024-01-30 21:58:48', NULL),
(64, 6, 10, 'Dengan menggunakan default, program akan menangani situasi di mana nilai shipping tidak cocok dengan case-case yang didefinisikan sebelumnya. Default berfungsi sebagai pilihan terakhir yang akan dieksekusi jika tidak ada case yang cocok dengan nilai yang dievaluasi.', '2024-02-26 20:23:20', '2024-02-26 20:23:20', NULL),
(65, 6, 11, 'Program dimulai dengan mendeklarasikan variabel shipping dengan nilai \"Express\" dan variabel shippingCost tanpa nilai awal. Kemudian, program melanjutkan ke switch statement dengan mengevaluasi nilai dari variabel shipping. \n\nProgram akan membandingkan nilai shipping dengan setiap case yang ada. Jika nilai shipping cocok dengan salah satu case, program akan melompat ke blok kode yang sesuai dengan case tersebut.\nJika nilai shipping adalah \"Regular\", maka variabel shippingCost akan diatur menjadi 0.\nJika nilai shipping adalah \"Express\", maka variabel shippingCost akan diatur menjadi 1.75.\nJika nilai shipping tidak cocok dengan case-case di atas, program akan melompat ke blok kode dalam default.\nPada blok kode default, variabel shippingCost akan diatur menjadi 0.50.', '2024-02-26 20:23:20', '2024-02-26 20:23:20', NULL),
(66, 6, 12, 'Pada saat nilai shipping tidak bernilai regular maupun express, sehingga mengeluarkan nilai default, yaitu 0.05', '2024-02-26 20:23:20', '2024-02-26 20:23:20', NULL),
(67, 6, 13, 'Karena variabel isMember di rancang untuk menampung nilai salah atau benar', '2024-02-26 20:26:17', '2024-02-26 20:26:17', NULL),
(68, 6, 14, '•	Jika nilai isMember adalah false, maka program akan masuk kedalam pemilihan else.\n•	Program akan melakukan pengecekan total. Diketahui total adalah 200000, sehingga masuk kedalam blok pemilihan ketiga dengan diskon 15 %\n•	Sehingga, output dari program tersebut adalah “diskon yang didapatkan adalah 15%”', '2024-02-26 20:26:17', '2024-02-26 20:26:17', NULL),
(69, 6, 15, 'program akan mengeluarkan output “diskon yang didapatkan adalah 10%”', '2024-02-26 20:26:17', '2024-02-26 20:26:17', NULL),
(71, 6, 16, 'aa', '2024-03-03 10:12:59', '2024-03-03 10:12:59', NULL),
(72, 6, 17, 'aaa', '2024-03-03 10:31:04', '2024-03-03 10:31:04', NULL),
(73, 6, 18, 'aa', '2024-03-03 10:31:08', '2024-03-03 10:31:08', NULL),
(74, 7, 1, 'Digunakan untuk menyimpan ukuran-ukuran geometris dan perhitungan matematika terkait dengan balok. Tipe data int cocok digunakan karena ukuran-ukuran tersebut umumnya diukur dalam bilangan bulat seperti sentimeter atau meter.', '2024-03-08 07:52:02', '2024-03-08 07:52:02', NULL),
(75, 7, 2, 'Program tersebut menghitung volume dan luas permukaan balok dengan mengalikan panjang, lebar, dan tinggi, kemudian menggunakan rumus yang sesuai. Volume dihitung dengan panjang * lebar * tinggi, sedangkan luas permukaan dihitung dengan rumus 2 * (panjang * lebar + panjang * tinggi + lebar * tinggi). Hasilnya dicetak sebagai output program.', '2024-03-08 07:52:13', '2024-03-08 07:52:13', NULL),
(76, 7, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok dalam kode program, cukup ubah nilai-nilai tersebut langsung pada bagian inisialisasi variabel panjang, lebar, dan tinggi. Setelah perubahan dilakukan, jalankan kembali program untuk mendapatkan hasil perhitungan dengan nilai yang baru.', '2024-03-08 07:52:20', '2024-03-08 07:52:20', NULL),
(93, 7, 4, 'If digunakan dalam kode tersebut untuk membuat kondisi atau pernyataan logis. Dalam konteks kode tersebut, if digunakan untuk melakukan pengecekan apakah nilai lebih besar dari 70. Jika kondisi tersebut terpenuhi, yaitu nilai lebih besar dari 70, maka pesan \"Selamat anda lulus!\" akan dicetak. If digunakan untuk memberikan pengambilan keputusan berdasarkan kondisi tertentu, yang memungkinkan eksekusi kode yang berbeda tergantung pada hasil kondisi yang dievaluasi.', '2024-03-08 08:37:07', '2024-03-08 08:37:07', NULL),
(94, 7, 5, 'Pertama, program akan menjalankan fungsi main yang merupakan titik masuk utama dalam program Java.\nKemudian, sebuah variabel nilai dengan tipe data integer dideklarasikan dan diinisialisasi dengan nilai 80.\nProgram akan melanjutkan ke blok if, yang akan mengevaluasi apakah nilai lebih besar dari 70.\nJika kondisi dalam blok if (nilai > 70) bernilai true, program akan mengeksekusi pernyataan yang ada di dalam blok if, yaitu mencetak string \"Selamat anda lulus!\" menggunakan System.out.print().\n•	Jika kondisi dalam blok if bernilai false, program akan melanjutkan ke pernyataan setelah blok if dan program akan selesai.', '2024-03-08 08:37:12', '2024-03-08 08:37:12', NULL),
(95, 7, 6, 'Jika nilai variabel “nilai” kurang dari 70, maka tidak akan ada output yang ditampilkan, karena tidak ada pernyataan lain setelah kondisi if.', '2024-03-08 08:37:17', '2024-03-08 08:37:17', NULL),
(96, 7, 7, 'If-else digunakan untuk membagi kondisi menjadi dua kemungkinan. Dalam studi kasus diatas, IF digunakan untuk melakukan pengecekan apakah nilai itemCost lebih besar dari 24. Jika kondisi tersebut terpenuhi, maka variabel order bernilai \"High Value Item!\" akan dicetak. Sedangkan jika nilai itemCost tidak lebih dari 24, maka variabel order bernilai “Low Order Value!”', '2024-03-08 08:39:34', '2024-03-08 08:39:34', NULL),
(97, 7, 8, '•	Mendeklarasikan kelas Order.\n•	Mendeklarasikan method main sebagai method utama yang akan dieksekusi saat program dijalankan.\n•	Mendeklarasikan variabel itemCost dengan tipe data double dan memberikannya nilai 30.99.\n•	Mendeklarasikan variabel order dengan tipe data String dan memberikannya nilai awal berupa string kosong (\"\").\n•	Melakukan pengecekan kondisi menggunakan pernyataan if. Kondisi yang dievaluasi adalah itemCost > 24.00.\n•	Jika kondisi tersebut benar (nilai itemCost lebih besar dari 24.00), maka blok kode di dalam if akan dieksekusi.\n•	Dalam blok if, nilai variabel order diubah menjadi \"High Value Item!\".\n•	Jika kondisi dalam if tidak terpenuhi (nilai itemCost tidak lebih besar dari 24.00), maka blok kode di dalam else akan dieksekusi.\n•	Dalam blok else, nilai variabel order diubah menjadi \"Low Value Item!\".\n•	Setelah blok if-else selesai dieksekusi, pesan yang ada dalam variabel order akan dicetak menggunakan System.out.print.\n•	Output yang ditampilkan akan bergantung pada nilai itemCost. Jika itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan dicetak. Jika tidak, maka pesan \"Low Value Item!\" akan dicetak.', '2024-03-08 08:39:50', '2024-03-08 08:39:50', NULL),
(98, 7, 9, 'Program akan menampilkan output “Low Value Item”', '2024-03-08 08:39:56', '2024-03-08 08:39:56', NULL),
(99, 7, 10, 'Baris program default dalam switch statement menentukan tindakan yang akan diambil jika tidak ada case yang cocok dengan nilai yang dievaluasi oleh switch statement tersebut. Dalam kasus tersebut, jika nilai shipping tidak cocok dengan \"Regular\" atau \"Express\", maka nilai shippingCost akan diatur menjadi 0.50.', '2024-03-08 09:20:18', '2024-03-08 09:20:18', NULL),
(100, 7, 11, 'Alur program dari baris kode switch-case di atas adalah sebagai berikut:\n\n1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\".\nSwitch statement digunakan untuk mengevaluasi nilai dari variabel shipping.\nNilai dari variabel shipping dibandingkan dengan setiap case dalam switch statement.\n2. Jika nilai shipping cocok dengan nilai pada case \"Regular\", maka blok kode di bawah case \"Regular\" akan dieksekusi, yaitu shippingCost akan diatur menjadi 0.\n3. Jika nilai shipping cocok dengan nilai pada case \"Express\", maka blok kode di bawah case \"Express\" akan dieksekusi, yaitu shippingCost akan diatur menjadi 1.75.\n4. Jika nilai shipping tidak cocok dengan nilai pada case \"Regular\" atau \"Express\", maka blok kode di bawah default akan dieksekusi, yaitu shippingCost akan diatur menjadi 0.50.\n5. Setelah switch statement dieksekusi, nilai shippingCost akan dicetak sebagai hasil akhir.', '2024-03-08 09:20:26', '2024-03-08 09:20:26', NULL),
(101, 7, 12, 'Dalam kode yang diberikan, tidak ada case atau kondisi yang mengatur shippingCost menjadi 0.05. Oleh karena itu, shippingCost tidak akan bernilai 0.05 dalam program tersebut.\n\nDalam switch-case yang diberikan, ada tiga kemungkinan nilai yang akan membuat shippingCost memiliki nilai tertentu:\n\nJika nilai shipping adalah \"Regular\", maka shippingCost akan menjadi 0.\nJika nilai shipping adalah \"Express\", maka shippingCost akan menjadi 1.75.\nJika nilai shipping tidak cocok dengan \"Regular\" atau \"Express\", maka shippingCost akan menjadi 0.50 melalui blok default.\nSehingga, tidak ada kondisi dalam program tersebut yang akan membuat shippingCost menjadi 0.05.', '2024-03-08 09:20:29', '2024-03-08 09:20:29', NULL),
(102, 9, 1, 'Digunakan untuk menyimpan ukuran-ukuran geometris dan perhitungan matematika terkait dengan balok. Tipe data int cocok digunakan karena ukuran-ukuran tersebut umumnya diukur dalam bilangan bulat seperti sentimeter atau meter.', '2024-03-11 05:00:58', '2024-03-11 05:00:58', NULL),
(103, 9, 2, 'Program tersebut menghitung volume dan luas permukaan balok dengan mengalikan panjang, lebar, dan tinggi, kemudian menggunakan rumus yang sesuai. Volume dihitung dengan panjang * lebar * tinggi, sedangkan luas permukaan dihitung dengan rumus 2 * (panjang * lebar + panjang * tinggi + lebar * tinggi). Hasilnya dicetak sebagai output program.', '2024-03-11 05:01:16', '2024-03-11 05:01:16', NULL),
(104, 9, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok dalam kode program, cukup ubah nilai-nilai tersebut langsung pada bagian inisialisasi variabel panjang, lebar, dan tinggi. Setelah perubahan dilakukan, jalankan kembali program untuk mendapatkan hasil perhitungan dengan nilai yang baru.', '2024-03-11 05:01:21', '2024-03-11 05:01:21', NULL),
(105, 9, 4, 'If digunakan dalam kode tersebut untuk membuat kondisi atau pernyataan logis. Dalam konteks kode tersebut, if digunakan untuk melakukan pengecekan apakah nilai lebih besar dari 70. Jika kondisi tersebut terpenuhi, yaitu nilai lebih besar dari 70, maka pesan \"Selamat anda lulus!\" akan dicetak. If digunakan untuk memberikan pengambilan keputusan berdasarkan kondisi tertentu, yang memungkinkan eksekusi kode yang berbeda tergantung pada hasil kondisi yang dievaluasi.', '2024-03-11 05:05:06', '2024-03-11 05:05:06', NULL),
(106, 9, 5, 'Pertama, program akan menjalankan fungsi main yang merupakan titik masuk utama dalam program Java. Kemudian, sebuah variabel nilai dengan tipe data integer dideklarasikan dan diinisialisasi dengan nilai 80. Program akan melanjutkan ke blok if, yang akan mengevaluasi apakah nilai lebih besar dari 70. Jika kondisi dalam blok if (nilai > 70) bernilai true, program akan mengeksekusi pernyataan yang ada di dalam blok if, yaitu mencetak string \"Selamat anda lulus!\" menggunakan System.out.print(). • Jika kondisi dalam blok if bernilai false, program akan melanjutkan ke pernyataan setelah blok if dan program akan selesai.', '2024-03-11 05:05:11', '2024-03-11 05:05:11', NULL),
(107, 9, 6, 'Jika nilai variabel “nilai” kurang dari 70, maka tidak akan ada output yang ditampilkan, karena tidak ada pernyataan lain setelah kondisi if.', '2024-03-11 05:05:17', '2024-03-11 05:05:17', NULL),
(108, 9, 7, 'If-else digunakan untuk membagi kondisi menjadi dua kemungkinan. Dalam studi kasus diatas, IF digunakan untuk melakukan pengecekan apakah nilai itemCost lebih besar dari 24. Jika kondisi tersebut terpenuhi, maka variabel order bernilai \"High Value Item!\" akan dicetak. Sedangkan jika nilai itemCost tidak lebih dari 24, maka variabel order bernilai “Low Order Value!”', '2024-03-11 05:07:42', '2024-03-11 05:07:42', NULL),
(109, 9, 8, '• Mendeklarasikan kelas Order. • Mendeklarasikan method main sebagai method utama yang akan dieksekusi saat program dijalankan. • Mendeklarasikan variabel itemCost dengan tipe data double dan memberikannya nilai 30.99. • Mendeklarasikan variabel order dengan tipe data String dan memberikannya nilai awal berupa string kosong (\"\"). • Melakukan pengecekan kondisi menggunakan pernyataan if. Kondisi yang dievaluasi adalah itemCost > 24.00. • Jika kondisi tersebut benar (nilai itemCost lebih besar dari 24.00), maka blok kode di dalam if akan dieksekusi. • Dalam blok if, nilai variabel order diubah menjadi \"High Value Item!\". • Jika kondisi dalam if tidak terpenuhi (nilai itemCost tidak lebih besar dari 24.00), maka blok kode di dalam else akan dieksekusi. • Dalam blok else, nilai variabel order diubah menjadi \"Low Value Item!\". • Setelah blok if-else selesai dieksekusi, pesan yang ada dalam variabel order akan dicetak menggunakan System.out.print. • Output yang ditampilkan akan bergantung pada nilai itemCost. Jika itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan dicetak. Jika tidak, maka pesan \"Low Value Item!\" akan dicetak.', '2024-03-11 05:07:48', '2024-03-11 05:07:48', NULL),
(110, 9, 9, 'Program akan menampilkan output “Low Value Item”', '2024-03-11 05:07:54', '2024-03-11 05:07:54', NULL),
(111, 9, 10, 'Baris program default dalam switch statement menentukan tindakan yang akan diambil jika tidak ada case yang cocok dengan nilai yang dievaluasi oleh switch statement tersebut. Dalam kasus tersebut, jika nilai shipping tidak cocok dengan \"Regular\" atau \"Express\", maka nilai shippingCost akan diatur menjadi 0.50.', '2024-03-11 05:10:20', '2024-03-11 05:10:20', NULL),
(112, 9, 11, 'Alur program dari baris kode switch-case di atas adalah sebagai berikut: 1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". Switch statement digunakan untuk mengevaluasi nilai dari variabel shipping. Nilai dari variabel shipping dibandingkan dengan setiap case dalam switch statement. 2. Jika nilai shipping cocok dengan nilai pada case \"Regular\", maka blok kode di bawah case \"Regular\" akan dieksekusi, yaitu shippingCost akan diatur menjadi 0. 3. Jika nilai shipping cocok dengan nilai pada case \"Express\", maka blok kode di bawah case \"Express\" akan dieksekusi, yaitu shippingCost akan diatur menjadi 1.75. 4. Jika nilai shipping tidak cocok dengan nilai pada case \"Regular\" atau \"Express\", maka blok kode di bawah default akan dieksekusi, yaitu shippingCost akan diatur menjadi 0.50. 5. Setelah switch statement dieksekusi, nilai shippingCost akan dicetak sebagai hasil akhir.', '2024-03-11 05:10:24', '2024-03-11 05:10:24', NULL),
(113, 9, 12, 'Dalam kode yang diberikan, tidak ada case atau kondisi yang mengatur shippingCost menjadi 0.05. Oleh karena itu, shippingCost tidak akan bernilai 0.05 dalam program tersebut. Dalam switch-case yang diberikan, ada tiga kemungkinan nilai yang akan membuat shippingCost memiliki nilai tertentu: Jika nilai shipping adalah \"Regular\", maka shippingCost akan menjadi 0. Jika nilai shipping adalah \"Express\", maka shippingCost akan menjadi 1.75. Jika nilai shipping tidak cocok dengan \"Regular\" atau \"Express\", maka shippingCost akan menjadi 0.50 melalui blok default. Sehingga, tidak ada kondisi dalam program tersebut yang akan membuat shippingCost menjadi 0.05.', '2024-03-11 05:10:30', '2024-03-11 05:10:30', NULL),
(114, 9, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan konsep dari tipe data boolean. Dalam program ini, isMember digunakan untuk membedakan apakah pelanggan adalah anggota (true) atau bukan (false), sehingga pemberian diskon dapat ditentukan berdasarkan keanggotaan pelanggan.', '2024-03-11 05:15:38', '2024-03-11 05:15:38', NULL),
(115, 9, 14, 'Jika nilai isMember adalah false, maka program akan melanjutkan ke blok else. Di dalam blok else, program akan mengevaluasi nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota.\n\nBerikut adalah alur program jika isMember bernilai false:\n\nProgram memeriksa kondisi if(isMember == true), tetapi karena isMember bernilai false, maka program akan melanjutkan ke blok else.\n\nDi dalam blok else, program memeriksa nilai total:\n\nJika total kurang dari 100.000, diskon yang diberikan adalah 5%.\nJika total antara 100.000 dan 150.000 (inklusif), diskon yang diberikan adalah 10%.\nJika total lebih dari 150.000, diskon yang diberikan adalah 15%.\nSetelah nilai diskon dihitung berdasarkan kondisi di atas, program akan mencetak hasil diskon yang didapatkan oleh pelanggan non-anggota.', '2024-03-11 05:15:43', '2024-03-11 05:15:43', NULL),
(116, 9, 15, 'Jika nilai variabel total adalah Rp. 30.000, dan isMember adalah false, maka program akan memberikan diskon 5% kepada pelanggan non-anggota karena total pembelian kurang dari Rp. 100.000.\n\nJadi, output program akan menjadi: 5%', '2024-03-11 05:15:49', '2024-03-11 05:15:49', NULL),
(117, 7, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan konsep dari tipe data boolean. Dalam program ini, isMember digunakan untuk membedakan apakah pelanggan adalah anggota (true) atau bukan (false), sehingga pemberian diskon dapat ditentukan berdasarkan keanggotaan pelanggan.', '2024-03-11 05:19:33', '2024-03-11 05:19:33', NULL),
(118, 7, 14, 'Jika nilai isMember adalah false, maka program akan melanjutkan ke blok else. Di dalam blok else, program akan mengevaluasi nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota. Berikut adalah alur program jika isMember bernilai false: Program memeriksa kondisi if(isMember == true), tetapi karena isMember bernilai false, maka program akan melanjutkan ke blok else. Di dalam blok else, program memeriksa nilai total: Jika total kurang dari 100.000, diskon yang diberikan adalah 5%. Jika total antara 100.000 dan 150.000 (inklusif), diskon yang diberikan adalah 10%. Jika total lebih dari 150.000, diskon yang diberikan adalah 15%. Setelah nilai diskon dihitung berdasarkan kondisi di atas, program akan mencetak hasil diskon yang didapatkan oleh pelanggan non-anggota.', '2024-03-11 05:19:41', '2024-03-11 05:19:41', NULL),
(119, 7, 15, 'Jika nilai variabel total adalah Rp. 30.000, dan isMember adalah false, maka program akan memberikan diskon 5% kepada pelanggan non-anggota karena total pembelian kurang dari Rp. 100.000. Jadi, output program akan menjadi: 5%', '2024-03-11 05:19:46', '2024-03-11 05:19:46', NULL),
(120, 10, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-03-11 08:35:27', '2024-03-11 08:35:27', NULL),
(121, 10, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas:\n\n1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing.\n2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok.\n3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok.\n4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-03-11 08:35:37', '2024-03-11 08:35:37', NULL),
(122, 10, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-03-11 08:35:42', '2024-03-11 08:35:42', NULL),
(123, 10, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-03-11 08:37:52', '2024-03-11 08:37:52', NULL),
(124, 10, 5, 'Berikut adalah alur program dari kode yang diberikan:\n\n1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80.\n2. Dilakukan pengecekan kondisi menggunakan pernyataan if.\n3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi.\n4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan.\n5. Program selesai dieksekusi.', '2024-03-11 08:37:56', '2024-03-11 08:37:56', NULL),
(125, 10, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-03-11 08:38:02', '2024-03-11 08:38:02', NULL),
(126, 10, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-03-11 08:41:56', '2024-03-11 08:41:56', NULL),
(127, 10, 8, 'Berikut adalah alur program dari baris kode yang diberikan:\n\n1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99.\n2. Variabel order dideklarasikan sebagai string kosong.\n3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan.\n4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order.\n5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order.\n6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print.\n7. Program selesai dieksekusi.', '2024-03-11 08:41:59', '2024-03-11 08:41:59', NULL),
(128, 10, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-03-11 08:42:03', '2024-03-11 08:42:03', NULL),
(129, 10, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-03-11 08:45:39', '2024-03-11 08:45:39', NULL),
(130, 10, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\".\n2. Variabel shippingCost dideklarasikan tanpa diinisialisasi.\n3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case.\n4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0.\n5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75.\n6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50.\n8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print.\nProgram selesai dieksekusi.', '2024-03-11 08:45:42', '2024-03-11 08:45:42', NULL),
(131, 10, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-03-11 08:45:46', '2024-03-11 08:45:46', NULL),
(132, 10, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-03-11 08:49:06', '2024-03-11 08:49:06', NULL),
(133, 10, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-03-11 08:49:10', '2024-03-11 08:49:10', NULL),
(134, 10, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-03-11 08:49:13', '2024-03-11 08:49:13', NULL),
(135, 11, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-03-11 08:56:19', '2024-03-11 08:56:19', NULL),
(136, 11, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-03-11 08:56:23', '2024-03-11 08:56:23', NULL),
(137, 11, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-03-11 08:56:27', '2024-03-11 08:56:27', NULL),
(138, 11, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-03-11 08:57:56', '2024-03-11 08:57:56', NULL),
(139, 11, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-03-11 08:57:59', '2024-03-11 08:57:59', NULL),
(140, 11, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-03-11 08:58:02', '2024-03-11 08:58:02', NULL),
(141, 11, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-03-11 08:59:14', '2024-03-11 08:59:14', NULL),
(142, 11, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi.', '2024-03-11 08:59:17', '2024-03-11 08:59:17', NULL),
(143, 11, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-03-11 08:59:21', '2024-03-11 08:59:21', NULL),
(144, 11, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-03-11 09:00:32', '2024-03-11 09:00:32', NULL),
(145, 11, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi.', '2024-03-11 09:00:36', '2024-03-11 09:00:36', NULL),
(146, 11, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-03-11 09:00:38', '2024-03-11 09:00:38', NULL),
(147, 11, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-03-11 09:02:06', '2024-03-11 09:02:06', NULL),
(148, 11, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-03-11 09:02:09', '2024-03-11 09:02:09', NULL);
INSERT INTO `user_answer` (`id`, `user_id`, `essay_question_id`, `answer`, `created_at`, `updated_at`, `deleted_at`) VALUES
(149, 11, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-03-11 09:02:12', '2024-03-11 09:02:12', NULL),
(150, 12, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-03-11 09:10:58', '2024-03-11 09:10:58', NULL),
(151, 12, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-03-11 09:11:04', '2024-03-11 09:11:04', NULL),
(152, 12, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-03-11 09:11:09', '2024-03-11 09:11:09', NULL),
(153, 12, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-03-11 09:12:14', '2024-03-11 09:12:14', NULL),
(154, 12, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-03-11 09:12:18', '2024-03-11 09:12:18', NULL),
(155, 12, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-03-11 09:12:22', '2024-03-11 09:12:22', NULL),
(156, 12, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-03-11 09:13:58', '2024-03-11 09:13:58', NULL),
(157, 12, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi.', '2024-03-11 09:14:01', '2024-03-11 09:14:01', NULL),
(158, 12, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-03-11 09:14:05', '2024-03-11 09:14:05', NULL),
(159, 12, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-03-11 09:16:40', '2024-03-11 09:16:40', NULL),
(160, 12, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi.', '2024-03-11 09:16:43', '2024-03-11 09:16:43', NULL),
(161, 12, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-03-11 09:16:47', '2024-03-11 09:16:47', NULL),
(162, 12, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-03-11 09:17:53', '2024-03-11 09:17:53', NULL),
(163, 12, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-03-11 09:17:55', '2024-03-11 09:17:55', NULL),
(164, 12, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-03-11 09:17:59', '2024-03-11 09:17:59', NULL),
(165, 13, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-03-11 09:21:58', '2024-03-11 09:21:58', NULL),
(166, 13, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-03-11 09:22:06', '2024-03-11 09:22:06', NULL),
(167, 13, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-03-11 09:22:10', '2024-03-11 09:22:10', NULL),
(168, 13, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-03-11 09:24:03', '2024-03-11 09:24:03', NULL),
(169, 13, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-03-11 09:24:08', '2024-03-11 09:24:08', NULL),
(170, 13, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-03-11 09:24:12', '2024-03-11 09:24:12', NULL),
(171, 13, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-03-11 09:25:40', '2024-03-11 09:25:40', NULL),
(172, 13, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi.', '2024-03-11 09:25:45', '2024-03-11 09:25:45', NULL),
(173, 13, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-03-11 09:25:50', '2024-03-11 09:25:50', NULL),
(174, 13, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-03-11 09:29:23', '2024-03-11 09:29:23', NULL),
(175, 13, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi.', '2024-03-11 09:29:27', '2024-03-11 09:29:27', NULL),
(176, 13, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-03-11 09:29:30', '2024-03-11 09:29:30', NULL),
(177, 13, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-03-11 09:31:11', '2024-03-11 09:31:11', NULL),
(178, 13, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-03-11 09:31:14', '2024-03-11 09:31:14', NULL),
(179, 13, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-03-11 09:31:18', '2024-03-11 09:31:18', NULL),
(180, 14, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-03-11 09:41:17', '2024-03-11 09:41:17', NULL),
(181, 14, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-03-11 09:41:23', '2024-03-11 09:41:23', NULL),
(182, 14, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-03-11 09:41:27', '2024-03-11 09:41:27', NULL),
(183, 14, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-03-11 09:42:57', '2024-03-11 09:42:57', NULL),
(184, 14, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-03-11 09:43:01', '2024-03-11 09:43:01', NULL),
(185, 14, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-03-11 09:43:04', '2024-03-11 09:43:04', NULL),
(186, 14, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-03-11 09:44:21', '2024-03-11 09:44:21', NULL),
(187, 14, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi.', '2024-03-11 09:44:24', '2024-03-11 09:44:24', NULL),
(188, 14, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-03-11 09:44:29', '2024-03-11 09:44:29', NULL),
(189, 14, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-03-11 09:46:24', '2024-03-11 09:46:24', NULL),
(190, 14, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi.', '2024-03-11 09:46:28', '2024-03-11 09:46:28', NULL),
(191, 14, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-03-11 09:46:32', '2024-03-11 09:46:32', NULL),
(192, 14, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-03-11 09:47:53', '2024-03-11 09:47:53', NULL),
(193, 14, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-03-11 09:47:57', '2024-03-11 09:47:57', NULL),
(194, 14, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-03-11 09:48:00', '2024-03-11 09:48:00', NULL),
(195, 15, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-03-11 09:56:03', '2024-03-11 09:56:03', NULL),
(196, 15, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-03-11 09:56:08', '2024-03-11 09:56:08', NULL),
(197, 15, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-03-11 09:56:12', '2024-03-11 09:56:12', NULL),
(198, 15, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-03-11 09:57:19', '2024-03-11 09:57:19', NULL),
(199, 15, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-03-11 09:57:23', '2024-03-11 09:57:23', NULL),
(200, 15, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-03-11 09:57:26', '2024-03-11 09:57:26', NULL),
(201, 15, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-03-11 09:59:36', '2024-03-11 09:59:36', NULL),
(202, 15, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi.', '2024-03-11 09:59:40', '2024-03-11 09:59:40', NULL),
(203, 15, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-03-11 09:59:43', '2024-03-11 09:59:43', NULL),
(204, 15, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-03-11 10:01:02', '2024-03-11 10:01:02', NULL),
(205, 15, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi.', '2024-03-11 10:01:07', '2024-03-11 10:01:07', NULL),
(206, 15, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-03-11 10:01:10', '2024-03-11 10:01:10', NULL),
(207, 15, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-03-11 10:02:27', '2024-03-11 10:02:27', NULL),
(208, 15, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-03-11 10:02:30', '2024-03-11 10:02:30', NULL),
(209, 15, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-03-11 10:02:34', '2024-03-11 10:02:34', NULL),
(210, 16, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-03-11 10:15:01', '2024-03-11 10:15:01', NULL),
(211, 16, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-03-11 10:15:10', '2024-03-11 10:15:10', NULL),
(212, 16, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-03-11 10:15:16', '2024-03-11 10:15:16', NULL),
(213, 16, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-03-11 10:16:28', '2024-03-11 10:16:28', NULL),
(214, 16, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-03-11 10:16:31', '2024-03-11 10:16:31', NULL),
(215, 16, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-03-11 10:16:36', '2024-03-11 10:16:36', NULL),
(216, 16, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-03-11 10:17:54', '2024-03-11 10:17:54', NULL),
(217, 16, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi.', '2024-03-11 10:17:59', '2024-03-11 10:17:59', NULL),
(218, 16, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-03-11 10:18:04', '2024-03-11 10:18:04', NULL),
(219, 16, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-03-11 10:19:20', '2024-03-11 10:19:20', NULL),
(220, 16, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi.', '2024-03-11 10:19:23', '2024-03-11 10:19:23', NULL),
(221, 16, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-03-11 10:19:27', '2024-03-11 10:19:27', NULL),
(222, 16, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-03-11 10:20:37', '2024-03-11 10:20:37', NULL),
(223, 16, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-03-11 10:20:41', '2024-03-11 10:20:41', NULL),
(224, 16, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-03-11 10:20:44', '2024-03-11 10:20:44', NULL),
(225, 17, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-03-11 10:24:14', '2024-03-11 10:24:14', NULL),
(226, 17, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-03-11 10:24:18', '2024-03-11 10:24:18', NULL),
(227, 17, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-03-11 10:24:21', '2024-03-11 10:24:21', NULL),
(228, 17, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-03-11 10:25:43', '2024-03-11 10:25:43', NULL),
(229, 17, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-03-11 10:25:46', '2024-03-11 10:25:46', NULL),
(230, 17, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-03-11 10:25:50', '2024-03-11 10:25:50', NULL),
(231, 17, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-03-11 10:26:52', '2024-03-11 10:26:52', NULL),
(232, 17, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi.', '2024-03-11 10:26:56', '2024-03-11 10:26:56', NULL),
(233, 17, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-03-11 10:27:00', '2024-03-11 10:27:00', NULL),
(234, 17, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-03-11 10:28:13', '2024-03-11 10:28:13', NULL),
(235, 17, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi.', '2024-03-11 10:28:16', '2024-03-11 10:28:16', NULL),
(236, 17, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-03-11 10:28:21', '2024-03-11 10:28:21', NULL),
(237, 17, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-03-11 10:30:06', '2024-03-11 10:30:06', NULL),
(238, 17, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-03-11 10:30:10', '2024-03-11 10:30:10', NULL),
(239, 17, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-03-11 10:30:13', '2024-03-11 10:30:13', NULL),
(240, 10, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i. Lebih tepatnya, itu adalah ekspresi increment yang bertugas untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan.\n\nDalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number.\n\nJadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-03-24 00:15:22', '2024-03-24 00:15:22', NULL),
(241, 10, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;.\nKemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;.\nPada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi.\nDi dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi).\nSetelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i.\nProses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi.\nKetika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi.\nProgram selesai dieksekusi.', '2024-03-24 00:15:37', '2024-03-24 00:15:37', NULL),
(242, 10, 18, 'Jika nilai dari variabel number adalah 8, maka program akan mencetak angka dari 1 hingga 7. Ini disebabkan oleh kondisi perulangan for, di mana i akan mulai dari 1 dan berakhir pada 7 (karena 7 kurang dari 8), sementara perulangan akan berhenti sebelum mencapai 8. Jadi, output dari program akan menjadi 1234567', '2024-03-24 00:15:42', '2024-03-24 00:15:42', NULL),
(243, 10, 19, 'Pada kode program di atas, i++ memiliki kegunaan yang sama dengan pada contoh sebelumnya yang menggunakan perulangan for.\n\nDi dalam perulangan while, i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi.\n\nDengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-03-24 00:18:32', '2024-03-24 00:18:32', NULL),
(244, 10, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;.\nSelanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;.\nProgram memasuki loop while, di mana kondisi i < number dievaluasi.\nJika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi.\nDi dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);.\nSetelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++.\nKontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi.\nProses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi.\nKetika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while.\nProgram selesai dieksekusi.', '2024-03-24 00:18:39', '2024-03-24 00:18:39', NULL),
(245, 10, 21, 'Jika kondisi dalam while diganti menjadi while(i > number), maka loop while tidak akan pernah dieksekusi. Hal ini karena pada saat inisialisasi variabel i memiliki nilai 1, sedangkan nilai variabel number adalah 6. Kondisi i > number (1 > 6) tidak terpenuhi, sehingga blok pernyataan di dalam while tidak akan dieksekusi sama sekali.\n\nSehingga, tidak ada output yang akan dikeluarkan oleh program dalam kasus ini. Program akan selesai tanpa mencetak apa pun ke konsol.', '2024-03-24 00:18:45', '2024-03-24 00:18:45', NULL),
(246, 10, 22, 'Baris kode int next = first + second; berfungsi untuk menghitung nilai selanjutnya dalam deret Fibonacci. Dalam deret Fibonacci, setiap angka adalah hasil penjumlahan dari dua angka sebelumnya. Oleh karena itu, next dihitung dengan menambahkan nilai first (angka sebelumnya dalam deret) dengan nilai second (angka sebelumnya dari first).\n\nDengan melakukan operasi first + second, nilai next akan menjadi angka berikutnya dalam deret Fibonacci setelah first dan second. Kemudian, nilai-nilai variabel first dan second akan diperbarui untuk mempersiapkan perhitungan angka berikutnya dalam deret Fibonacci.', '2024-03-24 00:22:38', '2024-03-24 00:22:38', NULL),
(247, 10, 23, 'Program memasuki blok kode do-while.\nPertama-tama, variabel n diinisialisasi dengan nilai 6, yang menunjukkan bahwa kita akan mencetak deret Fibonacci hingga indeks ke-6.\nVariabel first diinisialisasi dengan nilai 0, dan second diinisialisasi dengan nilai 1. Ini adalah dua angka awal dalam deret Fibonacci.\nVariabel i diinisialisasi dengan nilai 1, yang akan digunakan untuk menghitung jumlah iterasi dalam perulangan.\nString \"Deret Fibonacci: \\n\" dicetak ke konsol untuk memberikan label pada deret Fibonacci yang akan dicetak.\nAngka pertama dan kedua dalam deret Fibonacci (0 dan 1) dicetak ke konsol.\nProgram masuk ke dalam blok pernyataan do-while.\nDi dalam blok do-while, angka berikutnya dalam deret Fibonacci dihitung dengan menjumlahkan nilai first dan second, dan hasilnya disimpan dalam variabel next.\nNilai next dicetak ke konsol.\nNilai variabel first diperbarui dengan nilai variabel second, yang berarti angka sebelumnya dalam deret Fibonacci menjadi nilai second saat ini.\nNilai variabel second diperbarui dengan nilai next, yang merupakan angka berikutnya dalam deret Fibonacci.\nVariabel i (penghitung iterasi) ditambah 1.\nProgram mengevaluasi kondisi i <= n. Jika kondisi terpenuhi, program akan kembali ke langkah 8 untuk menghitung dan mencetak angka berikutnya dalam deret Fibonacci.\nProses ini berlanjut sampai nilai i melebihi nilai n.\nSetelah itu, program keluar dari blok perulangan do-while.\nProgram selesai dieksekusi.', '2024-03-24 00:22:43', '2024-03-24 00:22:43', NULL),
(248, 10, 24, 'Jika nilai variabel n diganti menjadi 7, maka program akan mencetak deret Fibonacci hingga indeks ke-7 sehingga hasilnya 0 1 1 2 3 5 8', '2024-03-24 00:22:49', '2024-03-24 00:22:49', NULL),
(249, 10, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) menentukan berapa kali perulangan akan dieksekusi. Dalam kasus ini, kondisi tersebut berarti perulangan akan dieksekusi ketika nilai i kurang dari atau sama dengan 5.\n\nJadi, fungsi dari kondisi i <= 5 adalah untuk mengontrol jumlah baris dalam pola bintang yang dibuat oleh piramid. Dengan kondisi tersebut, perulangan akan dieksekusi sebanyak lima kali, menghasilkan lima baris pada pola bintang. Pada setiap iterasi, jumlah bintang yang dicetak pada setiap baris akan sesuai dengan nilai i pada saat itu. Sehingga, pada iterasi pertama, hanya satu bintang yang dicetak, pada iterasi kedua dua bintang, dan seterusnya hingga iterasi kelima.', '2024-03-24 00:25:24', '2024-03-24 00:25:24', NULL),
(250, 10, 26, 'Setiap kali iterasi dari perulangan pertama (outer loop) dieksekusi, variabel i akan bertambah satu dari nilai awal 1 hingga mencapai 5, sesuai dengan kondisi i <= 5.\n\nDi dalam setiap iterasi dari perulangan pertama, perulangan kedua (inner loop) akan dieksekusi.\n\nPada awal iterasi dari perulangan kedua, variabel j akan diinisialisasi dengan nilai awal 1.\n\nKondisi perulangan kedua, j <= i, menentukan berapa kali perulangan ini akan dieksekusi. Pada setiap iterasi, jumlah bintang yang dicetak akan sesuai dengan nilai i pada saat itu.\n\nPada iterasi pertama dari perulangan pertama (ketika i adalah 1), perulangan kedua akan dieksekusi satu kali (karena j kurang dari atau sama dengan 1).\nPada iterasi kedua dari perulangan pertama (ketika i adalah 2), perulangan kedua akan dieksekusi dua kali (karena j kurang dari atau sama dengan 2).\nHal ini berlanjut hingga iterasi kelima dari perulangan pertama, di mana perulangan kedua akan dieksekusi sebanyak lima kali (karena j kurang dari atau sama dengan 5).\nDi dalam blok perulangan kedua, bintang (*) akan ditambahkan ke variabel output pada setiap iterasi.\n\nSetelah perulangan kedua selesai dieksekusi untuk nilai i tertentu, baris baru (\\n) akan ditambahkan ke variabel output, sehingga bintang-bintang yang tercetak membentuk pola piramida.\n\nProses ini akan terus berlanjut hingga iterasi dari perulangan pertama selesai, dan hasil akhirnya, output akan dicetak ke konsol.\n\nDengan demikian, alur program dari perulangan kedua menggunakan variabel j adalah untuk menambahkan bintang ke dalam variabel output sesuai dengan jumlah iterasi yang sesuai dengan nilai i pada saat itu, yang menghasilkan pola piramida dari bintang', '2024-03-24 00:25:30', '2024-03-24 00:25:30', NULL),
(251, 10, 27, 'Jika kondisi i <= 5 pada perulangan pertama (outer loop) diganti menjadi i <= 6, maka perulangan akan dieksekusi lebih dari sebelumnya, yaitu sebanyak enam kali. Ini berarti akan ada enam baris dalam pola bintang yang dihasilkan.', '2024-03-24 00:25:37', '2024-03-24 00:25:37', NULL);
INSERT INTO `user_answer` (`id`, `user_id`, `essay_question_id`, `answer`, `created_at`, `updated_at`, `deleted_at`) VALUES
(252, 10, 28, 'String topicArray = Arrays.toString(topics);', '2024-03-24 00:28:14', '2024-03-24 00:28:14', NULL),
(253, 10, 29, 'Sebuah array topics yang berisi beberapa topik (dalam bentuk string) dideklarasikan dan diinisialisasi dengan nilai: {\"Opinion\", \"Tech\", \"Science\", \"Health\"}.\nKemudian, dilakukan pemanggilan metode Arrays.toString() untuk mengonversi array topics menjadi sebuah string.\nHasil dari konversi tersebut disimpan dalam variabel topicArray.\nTerakhir, string yang berisi representasi dari array topics disimpan dalam variabel topicArray tersebut.\nString yang berisi representasi dari array topics, yang sekarang disimpan dalam variabel topicArray, dicetak ke konsol menggunakan System.out.print(topicArray)', '2024-03-24 00:28:20', '2024-03-24 00:28:20', NULL),
(254, 10, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1, 2, 3, 4};, maka kode program akan menghasilkan kesalahan pada saat kompilasi. Hal ini disebabkan oleh perbedaan tipe data antara elemen-elemen array dengan tipe data yang diharapkan, yaitu string.\n\nKode String[] topics = {1, 2, 3, 4}; mencoba untuk membuat array topics yang berisi nilai-nilai bertipe int, namun karena kita mendeklarasikan tipe array sebagai String[], maka ini akan menyebabkan kesalahan kompilasi.\n\nJadi, output program tidak akan dihasilkan karena kesalahan kompilasi yang terjadi. Sebelum kita dapat mencetak array tersebut, kita perlu memastikan bahwa elemen-elemen array memiliki tipe data yang sesuai dengan deklarasi array. Dalam kasus ini, kita harus mengubah elemen-elemen array menjadi string, misalnya String[] topics = {\"1\", \"2\", \"3\", \"4\"};.', '2024-03-24 00:28:27', '2024-03-24 00:28:27', NULL),
(255, 10, 31, 'Pada kode i < nilai.length; pada perulangan pertama, nilai.length mengembalikan panjang (jumlah elemen) dari array dua dimensi nilai dalam dimensi pertama, yaitu jumlah baris dari matriks nilai. Jadi, fungsi dari kondisi i < nilai.length; adalah untuk memastikan bahwa iterasi dalam perulangan pertama akan terjadi sebanyak jumlah baris dalam matriks nilai.\n\nDalam konteks ini, i digunakan sebagai indeks baris dari matriks nilai. Jadi, perulangan akan berlangsung dari baris pertama hingga baris terakhir dari matriks nilai. Pada setiap iterasi, blok pernyataan dalam perulangan akan dieksekusi untuk setiap baris dalam matriks nilai.\n\nJadi, i < nilai.length; memastikan bahwa perulangan pertama akan berjalan sesuai dengan jumlah baris dalam matriks nilai, yang memungkinkan program untuk melakukan operasi pada setiap elemen dari matriks tersebut.', '2024-03-24 00:32:59', '2024-03-24 00:32:59', NULL),
(256, 10, 32, 'Perulangan kedua dimulai dengan inisialisasi variabel j dengan nilai 0.\nKemudian, dilakukan pengecekan kondisi j < nilai[i].length, di mana nilai[i].length mengembalikan panjang (jumlah elemen) dari array yang berada pada baris ke-i dalam matriks nilai. Dalam konteks ini, ini mengacu pada jumlah elemen (atau jumlah kolom) dari baris ke-i dari matriks nilai.\nJika kondisi j < nilai[i].length benar (true), blok pernyataan dalam perulangan kedua dieksekusi.\nDi dalam blok perulangan kedua, setiap elemen dari baris ke-i dalam matriks nilai diakses menggunakan nilai[i][j]. Nilai tersebut ditambahkan ke variabel total.\nSelanjutnya, variabel jumlahData (yang digunakan untuk menghitung total jumlah elemen dalam matriks) ditambah satu untuk setiap elemen yang dihitung.\nSetelah iterasi dalam perulangan kedua selesai, nilai j diperbarui dengan j++, sehingga memungkinkan iterasi ke elemen berikutnya dari baris yang sama.\nProses di atas diulangi hingga kondisi j < nilai[i].length tidak lagi terpenuhi.\nSetelah semua elemen dari baris ke-i telah dihitung, kontrol kembali ke perulangan pertama, di mana nilai i diperbarui, dan proses di atas diulangi untuk baris berikutnya dari matriks nilai.\nProses ini berlanjut hingga semua baris dari matriks nilai telah diproses.\nSetelah seluruh matriks nilai telah diproses, nilai total dari semua elemen matriks (total) dan jumlah total elemen dalam matriks (jumlahData) telah dihitung.\nRata-rata dari semua elemen matriks dihitung dengan membagi total nilai dengan jumlah total elemen, yaitu rataRata = total / jumlahData.\nNilai rata-rata tersebut kemudian dicetak ke konsol.\nProgram selesai dieksekusi.', '2024-03-24 00:33:04', '2024-03-24 00:33:04', NULL),
(257, 10, 33, 'Dengan elemen array nilai yang baru, yaitu double[][] nilai = {{75, 80, 81}, {90, 95, 90}, {70, 75, 82}} rata-rata nilai yang didapatkan adalah sekitar 82.', '2024-03-24 00:33:10', '2024-03-24 00:33:10', NULL),
(258, 10, 34, 'Kode tampil() pada method main memiliki kegunaan untuk menampilkan informasi terkait luas dan keliling lingkaran ke konsol.', '2024-03-24 00:35:21', '2024-03-24 00:35:21', NULL),
(259, 10, 35, 'Pertama, sebuah variabel lokal phi diinisialisasi dengan nilai 3.14, yang merupakan nilai phi (π) yang digunakan dalam perhitungan luas dan keliling lingkaran.\nSelanjutnya, sebuah variabel lokal r diinisialisasi dengan nilai 14, yang merupakan jari-jari lingkaran.\nKemudian, dilakukan pemanggilan method luasLingkaran(phi, r) untuk menghitung luas lingkaran. Method ini menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai luas lingkaran.\nHasil perhitungan luas lingkaran disimpan dalam variabel lokal luas.\nSelanjutnya, dilakukan pemanggilan method kelilingLingkaran(phi, r) untuk menghitung keliling lingkaran. Method ini juga menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai keliling lingkaran.\nHasil perhitungan keliling lingkaran disimpan dalam variabel lokal keliling.\nSetelah itu, hasil perhitungan luas dan keliling lingkaran dicetak ke konsol menggunakan System.out.print(). Cetak ini mencakup pesan yang menyatakan luas lingkaran beserta nilai luasnya, diikuti dengan pesan yang menyatakan keliling lingkaran beserta nilai kelilingnya.\nJadi, fungsi tampil() bertujuan untuk menghitung luas dan keliling lingkaran dengan menggunakan rumus yang sesuai, dan kemudian menampilkan hasilnya ke konsol.', '2024-03-24 00:35:27', '2024-03-24 00:35:27', NULL),
(260, 10, 36, 'Jika kode tampil() pada method main dihapus, maka program tidak akan menampilkan hasil luas dan keliling lingkaran ke konsol saat program dijalankan.\n\nTanpa pemanggilan method tampil() di dalam method main, maka baris kode yang ada di dalam method tampil() tidak akan dieksekusi. Artinya, perhitungan luas dan keliling lingkaran tetap akan terjadi karena pemanggilan method tampil() pada method main merupakan inisiasi untuk menghitung dan menampilkan luas serta keliling lingkaran.\n\nJadi, jika kode tampil() dihapus, program hanya akan dijalankan tanpa menampilkan hasil luas dan keliling lingkaran ke konsol.', '2024-03-24 00:35:35', '2024-03-24 00:35:35', NULL),
(261, 10, 37, 'Ya, program ini menggunakan rekursi.', '2024-03-24 00:39:44', '2024-03-24 00:39:44', NULL),
(262, 10, 38, 'Parameter Masukan: Method hitungBunga() menerima tiga parameter: saldo (saldo awal), bunga (persentase bunga tahunan), dan tahun (jumlah tahun).\n\nPengecekan Basis: Pertama, method melakukan pengecekan apakah nilai tahun sama dengan 0. Jika ya, artinya kita telah mencapai basis rekursi, dan method akan mengembalikan nilai saldo tanpa menghitung bunga lagi. Ini penting untuk mengakhiri rekursi agar tidak terjadi panggilan rekursif yang tak terbatas.\n\nPerhitungan Bunga: Jika nilai tahun tidak sama dengan 0, artinya kita masih dalam tahap rekursi. Di sini, method menghitung bunga tahunan dengan rumus bungaTahunan = saldo * (bunga / 100). Ini menghasilkan jumlah bunga yang akan ditambahkan ke saldo awal.\n\nPerhitungan Total Saldo: Setelah menghitung bunga tahunan, method menambahkannya ke saldo awal untuk mendapatkan total saldo setelah satu tahun. Ini dilakukan dengan rumus total = saldo + bungaTahunan.\n\nPanggilan Rekursif: Selanjutnya, method hitungBunga() memanggil dirinya sendiri dengan total saldo setelah satu tahun (total) sebagai saldo awal pada panggilan rekursif berikutnya. Parameter lainnya (bunga dan tahun) tetap tidak berubah. Dengan demikian, proses ini akan berulang untuk setiap tahun sampai mencapai basis rekursi.\n\nPengembalian Nilai: Setelah selesai semua panggilan rekursif, nilai saldo akhir setelah jumlah tahun yang ditentukan akan dikembalikan ke pemanggil method.', '2024-03-24 00:39:50', '2024-03-24 00:39:50', NULL),
(263, 10, 39, 'Jika bunga pertahun diganti menjadi 7%, jumlah uang yang dihasilkan setelah 5 tahun adalah sekitar 1.407.165,32.', '2024-03-24 00:39:56', '2024-03-24 00:39:56', NULL),
(264, 19, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-03-24 00:53:54', '2024-03-24 00:53:54', NULL),
(265, 19, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-03-24 00:54:05', '2024-03-24 00:54:05', NULL),
(266, 19, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-03-24 00:54:13', '2024-03-24 00:54:13', NULL),
(267, 19, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-03-24 00:55:38', '2024-03-24 00:55:38', NULL),
(268, 19, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-03-24 00:55:46', '2024-03-24 00:55:46', NULL),
(269, 19, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-03-24 00:55:52', '2024-03-24 00:55:52', NULL),
(270, 19, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-03-24 00:56:57', '2024-03-24 00:56:57', NULL),
(271, 19, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi.', '2024-03-24 00:57:02', '2024-03-24 00:57:02', NULL),
(272, 19, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-03-24 00:57:08', '2024-03-24 00:57:08', NULL),
(273, 19, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-03-24 00:58:22', '2024-03-24 00:58:22', NULL),
(274, 19, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi.', '2024-03-24 00:58:27', '2024-03-24 00:58:27', NULL),
(275, 19, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-03-24 00:58:32', '2024-03-24 00:58:32', NULL),
(276, 19, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-03-24 00:59:38', '2024-03-24 00:59:38', NULL),
(277, 19, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-03-24 00:59:44', '2024-03-24 00:59:44', NULL),
(278, 19, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-03-24 00:59:49', '2024-03-24 00:59:49', NULL),
(279, 19, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i. Lebih tepatnya, itu adalah ekspresi increment yang bertugas untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-03-24 01:02:05', '2024-03-24 01:02:05', NULL),
(280, 19, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-03-24 01:02:10', '2024-03-24 01:02:10', NULL),
(281, 19, 18, 'Jika nilai dari variabel number adalah 8, maka program akan mencetak angka dari 1 hingga 7. Ini disebabkan oleh kondisi perulangan for, di mana i akan mulai dari 1 dan berakhir pada 7 (karena 7 kurang dari 8), sementara perulangan akan berhenti sebelum mencapai 8. Jadi, output dari program akan menjadi 1234567', '2024-03-24 01:02:15', '2024-03-24 01:02:15', NULL),
(282, 19, 19, 'Pada kode program di atas, i++ memiliki kegunaan yang sama dengan pada contoh sebelumnya yang menggunakan perulangan for. Di dalam perulangan while, i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-03-24 01:03:46', '2024-03-24 01:03:46', NULL),
(283, 19, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-03-24 01:03:51', '2024-03-24 01:03:51', NULL),
(284, 19, 21, 'Jika kondisi dalam while diganti menjadi while(i > number), maka loop while tidak akan pernah dieksekusi. Hal ini karena pada saat inisialisasi variabel i memiliki nilai 1, sedangkan nilai variabel number adalah 6. Kondisi i > number (1 > 6) tidak terpenuhi, sehingga blok pernyataan di dalam while tidak akan dieksekusi sama sekali. Sehingga, tidak ada output yang akan dikeluarkan oleh program dalam kasus ini. Program akan selesai tanpa mencetak apa pun ke konsol.', '2024-03-24 01:03:57', '2024-03-24 01:03:57', NULL),
(285, 19, 22, 'Baris kode int next = first + second; berfungsi untuk menghitung nilai selanjutnya dalam deret Fibonacci. Dalam deret Fibonacci, setiap angka adalah hasil penjumlahan dari dua angka sebelumnya. Oleh karena itu, next dihitung dengan menambahkan nilai first (angka sebelumnya dalam deret) dengan nilai second (angka sebelumnya dari first). Dengan melakukan operasi first + second, nilai next akan menjadi angka berikutnya dalam deret Fibonacci setelah first dan second. Kemudian, nilai-nilai variabel first dan second akan diperbarui untuk mempersiapkan perhitungan angka berikutnya dalam deret Fibonacci.', '2024-03-24 01:04:58', '2024-03-24 01:04:58', NULL),
(286, 19, 23, 'Program memasuki blok kode do-while. Pertama-tama, variabel n diinisialisasi dengan nilai 6, yang menunjukkan bahwa kita akan mencetak deret Fibonacci hingga indeks ke-6. Variabel first diinisialisasi dengan nilai 0, dan second diinisialisasi dengan nilai 1. Ini adalah dua angka awal dalam deret Fibonacci. Variabel i diinisialisasi dengan nilai 1, yang akan digunakan untuk menghitung jumlah iterasi dalam perulangan. String \"Deret Fibonacci: \\n\" dicetak ke konsol untuk memberikan label pada deret Fibonacci yang akan dicetak. Angka pertama dan kedua dalam deret Fibonacci (0 dan 1) dicetak ke konsol. Program masuk ke dalam blok pernyataan do-while. Di dalam blok do-while, angka berikutnya dalam deret Fibonacci dihitung dengan menjumlahkan nilai first dan second, dan hasilnya disimpan dalam variabel next. Nilai next dicetak ke konsol. Nilai variabel first diperbarui dengan nilai variabel second, yang berarti angka sebelumnya dalam deret Fibonacci menjadi nilai second saat ini. Nilai variabel second diperbarui dengan nilai next, yang merupakan angka berikutnya dalam deret Fibonacci. Variabel i (penghitung iterasi) ditambah 1. Program mengevaluasi kondisi i <= n. Jika kondisi terpenuhi, program akan kembali ke langkah 8 untuk menghitung dan mencetak angka berikutnya dalam deret Fibonacci. Proses ini berlanjut sampai nilai i melebihi nilai n. Setelah itu, program keluar dari blok perulangan do-while. Program selesai dieksekusi.', '2024-03-24 01:05:03', '2024-03-24 01:05:03', NULL),
(287, 19, 24, 'Jika nilai variabel n diganti menjadi 7, maka program akan mencetak deret Fibonacci hingga indeks ke-7 sehingga hasilnya 0 1 1 2 3 5 8', '2024-03-24 01:05:10', '2024-03-24 01:05:10', NULL),
(288, 19, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) menentukan berapa kali perulangan akan dieksekusi. Dalam kasus ini, kondisi tersebut berarti perulangan akan dieksekusi ketika nilai i kurang dari atau sama dengan 5. Jadi, fungsi dari kondisi i <= 5 adalah untuk mengontrol jumlah baris dalam pola bintang yang dibuat oleh piramid. Dengan kondisi tersebut, perulangan akan dieksekusi sebanyak lima kali, menghasilkan lima baris pada pola bintang. Pada setiap iterasi, jumlah bintang yang dicetak pada setiap baris akan sesuai dengan nilai i pada saat itu. Sehingga, pada iterasi pertama, hanya satu bintang yang dicetak, pada iterasi kedua dua bintang, dan seterusnya hingga iterasi kelima.', '2024-03-24 01:06:27', '2024-03-24 01:06:27', NULL),
(289, 19, 26, 'Setiap kali iterasi dari perulangan pertama (outer loop) dieksekusi, variabel i akan bertambah satu dari nilai awal 1 hingga mencapai 5, sesuai dengan kondisi i <= 5. Di dalam setiap iterasi dari perulangan pertama, perulangan kedua (inner loop) akan dieksekusi. Pada awal iterasi dari perulangan kedua, variabel j akan diinisialisasi dengan nilai awal 1. Kondisi perulangan kedua, j <= i, menentukan berapa kali perulangan ini akan dieksekusi. Pada setiap iterasi, jumlah bintang yang dicetak akan sesuai dengan nilai i pada saat itu. Pada iterasi pertama dari perulangan pertama (ketika i adalah 1), perulangan kedua akan dieksekusi satu kali (karena j kurang dari atau sama dengan 1). Pada iterasi kedua dari perulangan pertama (ketika i adalah 2), perulangan kedua akan dieksekusi dua kali (karena j kurang dari atau sama dengan 2). Hal ini berlanjut hingga iterasi kelima dari perulangan pertama, di mana perulangan kedua akan dieksekusi sebanyak lima kali (karena j kurang dari atau sama dengan 5). Di dalam blok perulangan kedua, bintang (*) akan ditambahkan ke variabel output pada setiap iterasi. Setelah perulangan kedua selesai dieksekusi untuk nilai i tertentu, baris baru (\\n) akan ditambahkan ke variabel output, sehingga bintang-bintang yang tercetak membentuk pola piramida. Proses ini akan terus berlanjut hingga iterasi dari perulangan pertama selesai, dan hasil akhirnya, output akan dicetak ke konsol. Dengan demikian, alur program dari perulangan kedua menggunakan variabel j adalah untuk menambahkan bintang ke dalam variabel output sesuai dengan jumlah iterasi yang sesuai dengan nilai i pada saat itu, yang menghasilkan pola piramida dari bintang', '2024-03-24 01:06:32', '2024-03-24 01:06:32', NULL),
(290, 19, 27, 'Jika kondisi i <= 5 pada perulangan pertama (outer loop) diganti menjadi i <= 6, maka perulangan akan dieksekusi lebih dari sebelumnya, yaitu sebanyak enam kali. Ini berarti akan ada enam baris dalam pola bintang yang dihasilkan.', '2024-03-24 01:06:39', '2024-03-24 01:06:39', NULL),
(291, 19, 28, 'String topicArray = Arrays.toString(topics);', '2024-03-24 01:08:03', '2024-03-24 01:08:03', NULL),
(292, 19, 29, 'Sebuah array topics yang berisi beberapa topik (dalam bentuk string) dideklarasikan dan diinisialisasi dengan nilai: {\"Opinion\", \"Tech\", \"Science\", \"Health\"}. Kemudian, dilakukan pemanggilan metode Arrays.toString() untuk mengonversi array topics menjadi sebuah string. Hasil dari konversi tersebut disimpan dalam variabel topicArray. Terakhir, string yang berisi representasi dari array topics disimpan dalam variabel topicArray tersebut. String yang berisi representasi dari array topics, yang sekarang disimpan dalam variabel topicArray, dicetak ke konsol menggunakan System.out.print(topicArray)', '2024-03-24 01:08:09', '2024-03-24 01:08:09', NULL),
(293, 19, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1, 2, 3, 4};, maka kode program akan menghasilkan kesalahan pada saat kompilasi. Hal ini disebabkan oleh perbedaan tipe data antara elemen-elemen array dengan tipe data yang diharapkan, yaitu string. Kode String[] topics = {1, 2, 3, 4}; mencoba untuk membuat array topics yang berisi nilai-nilai bertipe int, namun karena kita mendeklarasikan tipe array sebagai String[], maka ini akan menyebabkan kesalahan kompilasi. Jadi, output program tidak akan dihasilkan karena kesalahan kompilasi yang terjadi. Sebelum kita dapat mencetak array tersebut, kita perlu memastikan bahwa elemen-elemen array memiliki tipe data yang sesuai dengan deklarasi array. Dalam kasus ini, kita harus mengubah elemen-elemen array menjadi string, misalnya String[] topics = {\"1\", \"2\", \"3\", \"4\"};.', '2024-03-24 01:08:16', '2024-03-24 01:08:16', NULL),
(294, 19, 31, 'Pada kode i < nilai.length; pada perulangan pertama, nilai.length mengembalikan panjang (jumlah elemen) dari array dua dimensi nilai dalam dimensi pertama, yaitu jumlah baris dari matriks nilai. Jadi, fungsi dari kondisi i < nilai.length; adalah untuk memastikan bahwa iterasi dalam perulangan pertama akan terjadi sebanyak jumlah baris dalam matriks nilai. Dalam konteks ini, i digunakan sebagai indeks baris dari matriks nilai. Jadi, perulangan akan berlangsung dari baris pertama hingga baris terakhir dari matriks nilai. Pada setiap iterasi, blok pernyataan dalam perulangan akan dieksekusi untuk setiap baris dalam matriks nilai. Jadi, i < nilai.length; memastikan bahwa perulangan pertama akan berjalan sesuai dengan jumlah baris dalam matriks nilai, yang memungkinkan program untuk melakukan operasi pada setiap elemen dari matriks tersebut.', '2024-03-24 01:10:03', '2024-03-24 01:10:03', NULL),
(295, 19, 32, 'Perulangan kedua dimulai dengan inisialisasi variabel j dengan nilai 0. Kemudian, dilakukan pengecekan kondisi j < nilai[i].length, di mana nilai[i].length mengembalikan panjang (jumlah elemen) dari array yang berada pada baris ke-i dalam matriks nilai. Dalam konteks ini, ini mengacu pada jumlah elemen (atau jumlah kolom) dari baris ke-i dari matriks nilai. Jika kondisi j < nilai[i].length benar (true), blok pernyataan dalam perulangan kedua dieksekusi. Di dalam blok perulangan kedua, setiap elemen dari baris ke-i dalam matriks nilai diakses menggunakan nilai[i][j]. Nilai tersebut ditambahkan ke variabel total. Selanjutnya, variabel jumlahData (yang digunakan untuk menghitung total jumlah elemen dalam matriks) ditambah satu untuk setiap elemen yang dihitung. Setelah iterasi dalam perulangan kedua selesai, nilai j diperbarui dengan j++, sehingga memungkinkan iterasi ke elemen berikutnya dari baris yang sama. Proses di atas diulangi hingga kondisi j < nilai[i].length tidak lagi terpenuhi. Setelah semua elemen dari baris ke-i telah dihitung, kontrol kembali ke perulangan pertama, di mana nilai i diperbarui, dan proses di atas diulangi untuk baris berikutnya dari matriks nilai. Proses ini berlanjut hingga semua baris dari matriks nilai telah diproses. Setelah seluruh matriks nilai telah diproses, nilai total dari semua elemen matriks (total) dan jumlah total elemen dalam matriks (jumlahData) telah dihitung. Rata-rata dari semua elemen matriks dihitung dengan membagi total nilai dengan jumlah total elemen, yaitu rataRata = total / jumlahData. Nilai rata-rata tersebut kemudian dicetak ke konsol. Program selesai dieksekusi.', '2024-03-24 01:10:11', '2024-03-24 01:10:11', NULL),
(296, 19, 33, 'Dengan elemen array nilai yang baru, yaitu double[][] nilai = {{75, 80, 81}, {90, 95, 90}, {70, 75, 82}} rata-rata nilai yang didapatkan adalah sekitar 82.', '2024-03-24 01:10:18', '2024-03-24 01:10:18', NULL),
(297, 19, 34, 'Kode tampil() pada method main memiliki kegunaan untuk menampilkan informasi terkait luas dan keliling lingkaran ke konsol.', '2024-03-24 01:11:28', '2024-03-24 01:11:28', NULL),
(298, 19, 35, 'Pertama, sebuah variabel lokal phi diinisialisasi dengan nilai 3.14, yang merupakan nilai phi (π) yang digunakan dalam perhitungan luas dan keliling lingkaran. Selanjutnya, sebuah variabel lokal r diinisialisasi dengan nilai 14, yang merupakan jari-jari lingkaran. Kemudian, dilakukan pemanggilan method luasLingkaran(phi, r) untuk menghitung luas lingkaran. Method ini menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai luas lingkaran. Hasil perhitungan luas lingkaran disimpan dalam variabel lokal luas. Selanjutnya, dilakukan pemanggilan method kelilingLingkaran(phi, r) untuk menghitung keliling lingkaran. Method ini juga menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai keliling lingkaran. Hasil perhitungan keliling lingkaran disimpan dalam variabel lokal keliling. Setelah itu, hasil perhitungan luas dan keliling lingkaran dicetak ke konsol menggunakan System.out.print(). Cetak ini mencakup pesan yang menyatakan luas lingkaran beserta nilai luasnya, diikuti dengan pesan yang menyatakan keliling lingkaran beserta nilai kelilingnya. Jadi, fungsi tampil() bertujuan untuk menghitung luas dan keliling lingkaran dengan menggunakan rumus yang sesuai, dan kemudian menampilkan hasilnya ke konsol.', '2024-03-24 01:11:32', '2024-03-24 01:11:32', NULL),
(299, 19, 36, 'Jika kode tampil() pada method main dihapus, maka program tidak akan menampilkan hasil luas dan keliling lingkaran ke konsol saat program dijalankan. Tanpa pemanggilan method tampil() di dalam method main, maka baris kode yang ada di dalam method tampil() tidak akan dieksekusi. Artinya, perhitungan luas dan keliling lingkaran tetap akan terjadi karena pemanggilan method tampil() pada method main merupakan inisiasi untuk menghitung dan menampilkan luas serta keliling lingkaran. Jadi, jika kode tampil() dihapus, program hanya akan dijalankan tanpa menampilkan hasil luas dan keliling lingkaran ke konsol.', '2024-03-24 01:11:37', '2024-03-24 01:11:37', NULL),
(300, 19, 37, 'Ya, program ini menggunakan rekursi.', '2024-03-24 01:13:03', '2024-03-24 01:13:03', NULL),
(301, 19, 38, 'Parameter Masukan: Method hitungBunga() menerima tiga parameter: saldo (saldo awal), bunga (persentase bunga tahunan), dan tahun (jumlah tahun). Pengecekan Basis: Pertama, method melakukan pengecekan apakah nilai tahun sama dengan 0. Jika ya, artinya kita telah mencapai basis rekursi, dan method akan mengembalikan nilai saldo tanpa menghitung bunga lagi. Ini penting untuk mengakhiri rekursi agar tidak terjadi panggilan rekursif yang tak terbatas. Perhitungan Bunga: Jika nilai tahun tidak sama dengan 0, artinya kita masih dalam tahap rekursi. Di sini, method menghitung bunga tahunan dengan rumus bungaTahunan = saldo * (bunga / 100). Ini menghasilkan jumlah bunga yang akan ditambahkan ke saldo awal. Perhitungan Total Saldo: Setelah menghitung bunga tahunan, method menambahkannya ke saldo awal untuk mendapatkan total saldo setelah satu tahun. Ini dilakukan dengan rumus total = saldo + bungaTahunan. Panggilan Rekursif: Selanjutnya, method hitungBunga() memanggil dirinya sendiri dengan total saldo setelah satu tahun (total) sebagai saldo awal pada panggilan rekursif berikutnya. Parameter lainnya (bunga dan tahun) tetap tidak berubah. Dengan demikian, proses ini akan berulang untuk setiap tahun sampai mencapai basis rekursi. Pengembalian Nilai: Setelah selesai semua panggilan rekursif, nilai saldo akhir setelah jumlah tahun yang ditentukan akan dikembalikan ke pemanggil method.', '2024-03-24 01:13:08', '2024-03-24 01:13:08', NULL),
(302, 19, 39, 'Jika bunga pertahun diganti menjadi 7%, jumlah uang yang dihasilkan setelah 5 tahun adalah sekitar 1.407.165,32.', '2024-03-24 01:13:15', '2024-03-24 01:13:15', NULL),
(303, 12, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i. Lebih tepatnya, itu adalah ekspresi increment yang bertugas untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-03-24 01:17:06', '2024-03-24 01:17:06', NULL),
(304, 12, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-03-24 01:17:11', '2024-03-24 01:17:11', NULL),
(305, 12, 18, 'Jika nilai dari variabel number adalah 8, maka program akan mencetak angka dari 1 hingga 7. Ini disebabkan oleh kondisi perulangan for, di mana i akan mulai dari 1 dan berakhir pada 7 (karena 7 kurang dari 8), sementara perulangan akan berhenti sebelum mencapai 8. Jadi, output dari program akan menjadi 1234567', '2024-03-24 01:17:16', '2024-03-24 01:17:16', NULL),
(306, 12, 19, 'Pada kode program di atas, i++ memiliki kegunaan yang sama dengan pada contoh sebelumnya yang menggunakan perulangan for. Di dalam perulangan while, i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-03-24 01:18:39', '2024-03-24 01:18:39', NULL),
(307, 12, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-03-24 01:18:44', '2024-03-24 01:18:44', NULL),
(308, 12, 21, 'Jika kondisi dalam while diganti menjadi while(i > number), maka loop while tidak akan pernah dieksekusi. Hal ini karena pada saat inisialisasi variabel i memiliki nilai 1, sedangkan nilai variabel number adalah 6. Kondisi i > number (1 > 6) tidak terpenuhi, sehingga blok pernyataan di dalam while tidak akan dieksekusi sama sekali. Sehingga, tidak ada output yang akan dikeluarkan oleh program dalam kasus ini. Program akan selesai tanpa mencetak apa pun ke konsol.', '2024-03-24 01:18:49', '2024-03-24 01:18:49', NULL),
(309, 12, 22, 'Baris kode int next = first + second; berfungsi untuk menghitung nilai selanjutnya dalam deret Fibonacci. Dalam deret Fibonacci, setiap angka adalah hasil penjumlahan dari dua angka sebelumnya. Oleh karena itu, next dihitung dengan menambahkan nilai first (angka sebelumnya dalam deret) dengan nilai second (angka sebelumnya dari first). Dengan melakukan operasi first + second, nilai next akan menjadi angka berikutnya dalam deret Fibonacci setelah first dan second. Kemudian, nilai-nilai variabel first dan second akan diperbarui untuk mempersiapkan perhitungan angka berikutnya dalam deret Fibonacci.', '2024-03-24 01:22:33', '2024-03-24 01:22:33', NULL),
(310, 12, 23, 'Program memasuki blok kode do-while. Pertama-tama, variabel n diinisialisasi dengan nilai 6, yang menunjukkan bahwa kita akan mencetak deret Fibonacci hingga indeks ke-6. Variabel first diinisialisasi dengan nilai 0, dan second diinisialisasi dengan nilai 1. Ini adalah dua angka awal dalam deret Fibonacci. Variabel i diinisialisasi dengan nilai 1, yang akan digunakan untuk menghitung jumlah iterasi dalam perulangan. String \"Deret Fibonacci: \\n\" dicetak ke konsol untuk memberikan label pada deret Fibonacci yang akan dicetak. Angka pertama dan kedua dalam deret Fibonacci (0 dan 1) dicetak ke konsol. Program masuk ke dalam blok pernyataan do-while. Di dalam blok do-while, angka berikutnya dalam deret Fibonacci dihitung dengan menjumlahkan nilai first dan second, dan hasilnya disimpan dalam variabel next. Nilai next dicetak ke konsol. Nilai variabel first diperbarui dengan nilai variabel second, yang berarti angka sebelumnya dalam deret Fibonacci menjadi nilai second saat ini. Nilai variabel second diperbarui dengan nilai next, yang merupakan angka berikutnya dalam deret Fibonacci. Variabel i (penghitung iterasi) ditambah 1. Program mengevaluasi kondisi i <= n. Jika kondisi terpenuhi, program akan kembali ke langkah 8 untuk menghitung dan mencetak angka berikutnya dalam deret Fibonacci. Proses ini berlanjut sampai nilai i melebihi nilai n. Setelah itu, program keluar dari blok perulangan do-while. Program selesai dieksekusi.', '2024-03-24 01:22:39', '2024-03-24 01:22:39', NULL),
(311, 12, 24, 'Jika nilai variabel n diganti menjadi 7, maka program akan mencetak deret Fibonacci hingga indeks ke-7 sehingga hasilnya 0 1 1 2 3 5 8', '2024-03-24 01:22:45', '2024-03-24 01:22:45', NULL),
(312, 12, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) menentukan berapa kali perulangan akan dieksekusi. Dalam kasus ini, kondisi tersebut berarti perulangan akan dieksekusi ketika nilai i kurang dari atau sama dengan 5. Jadi, fungsi dari kondisi i <= 5 adalah untuk mengontrol jumlah baris dalam pola bintang yang dibuat oleh piramid. Dengan kondisi tersebut, perulangan akan dieksekusi sebanyak lima kali, menghasilkan lima baris pada pola bintang. Pada setiap iterasi, jumlah bintang yang dicetak pada setiap baris akan sesuai dengan nilai i pada saat itu. Sehingga, pada iterasi pertama, hanya satu bintang yang dicetak, pada iterasi kedua dua bintang, dan seterusnya hingga iterasi kelima.', '2024-03-24 01:23:59', '2024-03-24 01:23:59', NULL),
(313, 12, 26, 'Setiap kali iterasi dari perulangan pertama (outer loop) dieksekusi, variabel i akan bertambah satu dari nilai awal 1 hingga mencapai 5, sesuai dengan kondisi i <= 5. Di dalam setiap iterasi dari perulangan pertama, perulangan kedua (inner loop) akan dieksekusi. Pada awal iterasi dari perulangan kedua, variabel j akan diinisialisasi dengan nilai awal 1. Kondisi perulangan kedua, j <= i, menentukan berapa kali perulangan ini akan dieksekusi. Pada setiap iterasi, jumlah bintang yang dicetak akan sesuai dengan nilai i pada saat itu. Pada iterasi pertama dari perulangan pertama (ketika i adalah 1), perulangan kedua akan dieksekusi satu kali (karena j kurang dari atau sama dengan 1). Pada iterasi kedua dari perulangan pertama (ketika i adalah 2), perulangan kedua akan dieksekusi dua kali (karena j kurang dari atau sama dengan 2). Hal ini berlanjut hingga iterasi kelima dari perulangan pertama, di mana perulangan kedua akan dieksekusi sebanyak lima kali (karena j kurang dari atau sama dengan 5). Di dalam blok perulangan kedua, bintang (*) akan ditambahkan ke variabel output pada setiap iterasi. Setelah perulangan kedua selesai dieksekusi untuk nilai i tertentu, baris baru (\\n) akan ditambahkan ke variabel output, sehingga bintang-bintang yang tercetak membentuk pola piramida. Proses ini akan terus berlanjut hingga iterasi dari perulangan pertama selesai, dan hasil akhirnya, output akan dicetak ke konsol. Dengan demikian, alur program dari perulangan kedua menggunakan variabel j adalah untuk menambahkan bintang ke dalam variabel output sesuai dengan jumlah iterasi yang sesuai dengan nilai i pada saat itu, yang menghasilkan pola piramida dari bintang', '2024-03-24 01:24:03', '2024-03-24 01:24:03', NULL),
(314, 12, 27, 'Jika kondisi i <= 5 pada perulangan pertama (outer loop) diganti menjadi i <= 6, maka perulangan akan dieksekusi lebih dari sebelumnya, yaitu sebanyak enam kali. Ini berarti akan ada enam baris dalam pola bintang yang dihasilkan.', '2024-03-24 01:24:09', '2024-03-24 01:24:09', NULL),
(315, 12, 28, 'String topicArray = Arrays.toString(topics);', '2024-03-24 01:25:37', '2024-03-24 01:25:37', NULL),
(316, 12, 29, 'Sebuah array topics yang berisi beberapa topik (dalam bentuk string) dideklarasikan dan diinisialisasi dengan nilai: {\"Opinion\", \"Tech\", \"Science\", \"Health\"}. Kemudian, dilakukan pemanggilan metode Arrays.toString() untuk mengonversi array topics menjadi sebuah string. Hasil dari konversi tersebut disimpan dalam variabel topicArray. Terakhir, string yang berisi representasi dari array topics disimpan dalam variabel topicArray tersebut. String yang berisi representasi dari array topics, yang sekarang disimpan dalam variabel topicArray, dicetak ke konsol menggunakan System.out.print(topicArray)', '2024-03-24 01:25:42', '2024-03-24 01:25:42', NULL),
(317, 12, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1, 2, 3, 4};, maka kode program akan menghasilkan kesalahan pada saat kompilasi. Hal ini disebabkan oleh perbedaan tipe data antara elemen-elemen array dengan tipe data yang diharapkan, yaitu string. Kode String[] topics = {1, 2, 3, 4}; mencoba untuk membuat array topics yang berisi nilai-nilai bertipe int, namun karena kita mendeklarasikan tipe array sebagai String[], maka ini akan menyebabkan kesalahan kompilasi. Jadi, output program tidak akan dihasilkan karena kesalahan kompilasi yang terjadi. Sebelum kita dapat mencetak array tersebut, kita perlu memastikan bahwa elemen-elemen array memiliki tipe data yang sesuai dengan deklarasi array. Dalam kasus ini, kita harus mengubah elemen-elemen array menjadi string, misalnya String[] topics = {\"1\", \"2\", \"3\", \"4\"};.', '2024-03-24 01:25:47', '2024-03-24 01:25:47', NULL),
(318, 12, 31, 'Pada kode i < nilai.length; pada perulangan pertama, nilai.length mengembalikan panjang (jumlah elemen) dari array dua dimensi nilai dalam dimensi pertama, yaitu jumlah baris dari matriks nilai. Jadi, fungsi dari kondisi i < nilai.length; adalah untuk memastikan bahwa iterasi dalam perulangan pertama akan terjadi sebanyak jumlah baris dalam matriks nilai. Dalam konteks ini, i digunakan sebagai indeks baris dari matriks nilai. Jadi, perulangan akan berlangsung dari baris pertama hingga baris terakhir dari matriks nilai. Pada setiap iterasi, blok pernyataan dalam perulangan akan dieksekusi untuk setiap baris dalam matriks nilai. Jadi, i < nilai.length; memastikan bahwa perulangan pertama akan berjalan sesuai dengan jumlah baris dalam matriks nilai, yang memungkinkan program untuk melakukan operasi pada setiap elemen dari matriks tersebut.', '2024-03-24 01:26:52', '2024-03-24 01:26:52', NULL),
(319, 12, 32, 'Perulangan kedua dimulai dengan inisialisasi variabel j dengan nilai 0. Kemudian, dilakukan pengecekan kondisi j < nilai[i].length, di mana nilai[i].length mengembalikan panjang (jumlah elemen) dari array yang berada pada baris ke-i dalam matriks nilai. Dalam konteks ini, ini mengacu pada jumlah elemen (atau jumlah kolom) dari baris ke-i dari matriks nilai. Jika kondisi j < nilai[i].length benar (true), blok pernyataan dalam perulangan kedua dieksekusi. Di dalam blok perulangan kedua, setiap elemen dari baris ke-i dalam matriks nilai diakses menggunakan nilai[i][j]. Nilai tersebut ditambahkan ke variabel total. Selanjutnya, variabel jumlahData (yang digunakan untuk menghitung total jumlah elemen dalam matriks) ditambah satu untuk setiap elemen yang dihitung. Setelah iterasi dalam perulangan kedua selesai, nilai j diperbarui dengan j++, sehingga memungkinkan iterasi ke elemen berikutnya dari baris yang sama. Proses di atas diulangi hingga kondisi j < nilai[i].length tidak lagi terpenuhi. Setelah semua elemen dari baris ke-i telah dihitung, kontrol kembali ke perulangan pertama, di mana nilai i diperbarui, dan proses di atas diulangi untuk baris berikutnya dari matriks nilai. Proses ini berlanjut hingga semua baris dari matriks nilai telah diproses. Setelah seluruh matriks nilai telah diproses, nilai total dari semua elemen matriks (total) dan jumlah total elemen dalam matriks (jumlahData) telah dihitung. Rata-rata dari semua elemen matriks dihitung dengan membagi total nilai dengan jumlah total elemen, yaitu rataRata = total / jumlahData. Nilai rata-rata tersebut kemudian dicetak ke konsol. Program selesai dieksekusi.', '2024-03-24 01:26:57', '2024-03-24 01:26:57', NULL),
(320, 12, 33, 'Dengan elemen array nilai yang baru, yaitu double[][] nilai = {{75, 80, 81}, {90, 95, 90}, {70, 75, 82}} rata-rata nilai yang didapatkan adalah sekitar 82.', '2024-03-24 01:27:03', '2024-03-24 01:27:03', NULL),
(321, 12, 34, 'Kode tampil() pada method main memiliki kegunaan untuk menampilkan informasi terkait luas dan keliling lingkaran ke konsol.', '2024-03-24 01:28:15', '2024-03-24 01:28:15', NULL),
(322, 12, 35, 'Pertama, sebuah variabel lokal phi diinisialisasi dengan nilai 3.14, yang merupakan nilai phi (π) yang digunakan dalam perhitungan luas dan keliling lingkaran. Selanjutnya, sebuah variabel lokal r diinisialisasi dengan nilai 14, yang merupakan jari-jari lingkaran. Kemudian, dilakukan pemanggilan method luasLingkaran(phi, r) untuk menghitung luas lingkaran. Method ini menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai luas lingkaran. Hasil perhitungan luas lingkaran disimpan dalam variabel lokal luas. Selanjutnya, dilakukan pemanggilan method kelilingLingkaran(phi, r) untuk menghitung keliling lingkaran. Method ini juga menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai keliling lingkaran. Hasil perhitungan keliling lingkaran disimpan dalam variabel lokal keliling. Setelah itu, hasil perhitungan luas dan keliling lingkaran dicetak ke konsol menggunakan System.out.print(). Cetak ini mencakup pesan yang menyatakan luas lingkaran beserta nilai luasnya, diikuti dengan pesan yang menyatakan keliling lingkaran beserta nilai kelilingnya. Jadi, fungsi tampil() bertujuan untuk menghitung luas dan keliling lingkaran dengan menggunakan rumus yang sesuai, dan kemudian menampilkan hasilnya ke konsol.', '2024-03-24 01:28:20', '2024-03-24 01:28:20', NULL),
(323, 12, 36, 'ika kode tampil() pada method main dihapus, maka program tidak akan menampilkan hasil luas dan keliling lingkaran ke konsol saat program dijalankan. Tanpa pemanggilan method tampil() di dalam method main, maka baris kode yang ada di dalam method tampil() tidak akan dieksekusi. Artinya, perhitungan luas dan keliling lingkaran tetap akan terjadi karena pemanggilan method tampil() pada method main merupakan inisiasi untuk menghitung dan menampilkan luas serta keliling lingkaran. Jadi, jika kode tampil() dihapus, program hanya akan dijalankan tanpa menampilkan hasil luas dan keliling lingkaran ke konsol.', '2024-03-24 01:28:25', '2024-03-24 01:28:25', NULL),
(324, 12, 37, 'Ya, program ini menggunakan rekursi.', '2024-03-24 01:29:45', '2024-03-24 01:29:45', NULL);
INSERT INTO `user_answer` (`id`, `user_id`, `essay_question_id`, `answer`, `created_at`, `updated_at`, `deleted_at`) VALUES
(325, 12, 38, 'Parameter Masukan: Method hitungBunga() menerima tiga parameter: saldo (saldo awal), bunga (persentase bunga tahunan), dan tahun (jumlah tahun). Pengecekan Basis: Pertama, method melakukan pengecekan apakah nilai tahun sama dengan 0. Jika ya, artinya kita telah mencapai basis rekursi, dan method akan mengembalikan nilai saldo tanpa menghitung bunga lagi. Ini penting untuk mengakhiri rekursi agar tidak terjadi panggilan rekursif yang tak terbatas. Perhitungan Bunga: Jika nilai tahun tidak sama dengan 0, artinya kita masih dalam tahap rekursi. Di sini, method menghitung bunga tahunan dengan rumus bungaTahunan = saldo * (bunga / 100). Ini menghasilkan jumlah bunga yang akan ditambahkan ke saldo awal. Perhitungan Total Saldo: Setelah menghitung bunga tahunan, method menambahkannya ke saldo awal untuk mendapatkan total saldo setelah satu tahun. Ini dilakukan dengan rumus total = saldo + bungaTahunan. Panggilan Rekursif: Selanjutnya, method hitungBunga() memanggil dirinya sendiri dengan total saldo setelah satu tahun (total) sebagai saldo awal pada panggilan rekursif berikutnya. Parameter lainnya (bunga dan tahun) tetap tidak berubah. Dengan demikian, proses ini akan berulang untuk setiap tahun sampai mencapai basis rekursi. Pengembalian Nilai: Setelah selesai semua panggilan rekursif, nilai saldo akhir setelah jumlah tahun yang ditentukan akan dikembalikan ke pemanggil method.', '2024-03-24 01:29:50', '2024-03-24 01:29:50', NULL),
(326, 12, 39, 'Jika bunga pertahun diganti menjadi 7%, jumlah uang yang dihasilkan setelah 5 tahun adalah sekitar 1.407.165,32.', '2024-03-24 01:29:58', '2024-03-24 01:29:58', NULL),
(327, 13, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i. Lebih tepatnya, itu adalah ekspresi increment yang bertugas untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-03-24 01:32:37', '2024-03-24 01:32:37', NULL),
(328, 13, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-03-24 01:32:45', '2024-03-24 01:32:45', NULL),
(329, 13, 18, 'Jika nilai dari variabel number adalah 8, maka program akan mencetak angka dari 1 hingga 7. Ini disebabkan oleh kondisi perulangan for, di mana i akan mulai dari 1 dan berakhir pada 7 (karena 7 kurang dari 8), sementara perulangan akan berhenti sebelum mencapai 8. Jadi, output dari program akan menjadi 1234567', '2024-03-24 01:32:50', '2024-03-24 01:32:50', NULL),
(330, 13, 19, 'Pada kode program di atas, i++ memiliki kegunaan yang sama dengan pada contoh sebelumnya yang menggunakan perulangan for. Di dalam perulangan while, i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-03-24 01:34:07', '2024-03-24 01:34:07', NULL),
(331, 13, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-03-24 01:34:12', '2024-03-24 01:34:12', NULL),
(332, 13, 21, 'Jika kondisi dalam while diganti menjadi while(i > number), maka loop while tidak akan pernah dieksekusi. Hal ini karena pada saat inisialisasi variabel i memiliki nilai 1, sedangkan nilai variabel number adalah 6. Kondisi i > number (1 > 6) tidak terpenuhi, sehingga blok pernyataan di dalam while tidak akan dieksekusi sama sekali. Sehingga, tidak ada output yang akan dikeluarkan oleh program dalam kasus ini. Program akan selesai tanpa mencetak apa pun ke konsol.', '2024-03-24 01:34:17', '2024-03-24 01:34:17', NULL),
(333, 13, 22, 'Baris kode int next = first + second; berfungsi untuk menghitung nilai selanjutnya dalam deret Fibonacci. Dalam deret Fibonacci, setiap angka adalah hasil penjumlahan dari dua angka sebelumnya. Oleh karena itu, next dihitung dengan menambahkan nilai first (angka sebelumnya dalam deret) dengan nilai second (angka sebelumnya dari first). Dengan melakukan operasi first + second, nilai next akan menjadi angka berikutnya dalam deret Fibonacci setelah first dan second. Kemudian, nilai-nilai variabel first dan second akan diperbarui untuk mempersiapkan perhitungan angka berikutnya dalam deret Fibonacci.', '2024-03-24 01:35:19', '2024-03-24 01:35:19', NULL),
(334, 13, 23, 'Program memasuki blok kode do-while. Pertama-tama, variabel n diinisialisasi dengan nilai 6, yang menunjukkan bahwa kita akan mencetak deret Fibonacci hingga indeks ke-6. Variabel first diinisialisasi dengan nilai 0, dan second diinisialisasi dengan nilai 1. Ini adalah dua angka awal dalam deret Fibonacci. Variabel i diinisialisasi dengan nilai 1, yang akan digunakan untuk menghitung jumlah iterasi dalam perulangan. String \"Deret Fibonacci: \\n\" dicetak ke konsol untuk memberikan label pada deret Fibonacci yang akan dicetak. Angka pertama dan kedua dalam deret Fibonacci (0 dan 1) dicetak ke konsol. Program masuk ke dalam blok pernyataan do-while. Di dalam blok do-while, angka berikutnya dalam deret Fibonacci dihitung dengan menjumlahkan nilai first dan second, dan hasilnya disimpan dalam variabel next. Nilai next dicetak ke konsol. Nilai variabel first diperbarui dengan nilai variabel second, yang berarti angka sebelumnya dalam deret Fibonacci menjadi nilai second saat ini. Nilai variabel second diperbarui dengan nilai next, yang merupakan angka berikutnya dalam deret Fibonacci. Variabel i (penghitung iterasi) ditambah 1. Program mengevaluasi kondisi i <= n. Jika kondisi terpenuhi, program akan kembali ke langkah 8 untuk menghitung dan mencetak angka berikutnya dalam deret Fibonacci. Proses ini berlanjut sampai nilai i melebihi nilai n. Setelah itu, program keluar dari blok perulangan do-while. Program selesai dieksekusi.', '2024-03-24 01:35:24', '2024-03-24 01:35:24', NULL),
(335, 13, 24, 'Jika nilai variabel n diganti menjadi 7, maka program akan mencetak deret Fibonacci hingga indeks ke-7 sehingga hasilnya 0 1 1 2 3 5 8', '2024-03-24 01:35:30', '2024-03-24 01:35:30', NULL),
(336, 13, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) menentukan berapa kali perulangan akan dieksekusi. Dalam kasus ini, kondisi tersebut berarti perulangan akan dieksekusi ketika nilai i kurang dari atau sama dengan 5. Jadi, fungsi dari kondisi i <= 5 adalah untuk mengontrol jumlah baris dalam pola bintang yang dibuat oleh piramid. Dengan kondisi tersebut, perulangan akan dieksekusi sebanyak lima kali, menghasilkan lima baris pada pola bintang. Pada setiap iterasi, jumlah bintang yang dicetak pada setiap baris akan sesuai dengan nilai i pada saat itu. Sehingga, pada iterasi pertama, hanya satu bintang yang dicetak, pada iterasi kedua dua bintang, dan seterusnya hingga iterasi kelima.', '2024-03-24 01:36:41', '2024-03-24 01:36:41', NULL),
(337, 13, 26, 'Setiap kali iterasi dari perulangan pertama (outer loop) dieksekusi, variabel i akan bertambah satu dari nilai awal 1 hingga mencapai 5, sesuai dengan kondisi i <= 5. Di dalam setiap iterasi dari perulangan pertama, perulangan kedua (inner loop) akan dieksekusi. Pada awal iterasi dari perulangan kedua, variabel j akan diinisialisasi dengan nilai awal 1. Kondisi perulangan kedua, j <= i, menentukan berapa kali perulangan ini akan dieksekusi. Pada setiap iterasi, jumlah bintang yang dicetak akan sesuai dengan nilai i pada saat itu. Pada iterasi pertama dari perulangan pertama (ketika i adalah 1), perulangan kedua akan dieksekusi satu kali (karena j kurang dari atau sama dengan 1). Pada iterasi kedua dari perulangan pertama (ketika i adalah 2), perulangan kedua akan dieksekusi dua kali (karena j kurang dari atau sama dengan 2). Hal ini berlanjut hingga iterasi kelima dari perulangan pertama, di mana perulangan kedua akan dieksekusi sebanyak lima kali (karena j kurang dari atau sama dengan 5). Di dalam blok perulangan kedua, bintang (*) akan ditambahkan ke variabel output pada setiap iterasi. Setelah perulangan kedua selesai dieksekusi untuk nilai i tertentu, baris baru (\\n) akan ditambahkan ke variabel output, sehingga bintang-bintang yang tercetak membentuk pola piramida. Proses ini akan terus berlanjut hingga iterasi dari perulangan pertama selesai, dan hasil akhirnya, output akan dicetak ke konsol. Dengan demikian, alur program dari perulangan kedua menggunakan variabel j adalah untuk menambahkan bintang ke dalam variabel output sesuai dengan jumlah iterasi yang sesuai dengan nilai i pada saat itu, yang menghasilkan pola piramida dari bintang', '2024-03-24 01:36:47', '2024-03-24 01:36:47', NULL),
(338, 13, 27, 'Jika kondisi i <= 5 pada perulangan pertama (outer loop) diganti menjadi i <= 6, maka perulangan akan dieksekusi lebih dari sebelumnya, yaitu sebanyak enam kali. Ini berarti akan ada enam baris dalam pola bintang yang dihasilkan.', '2024-03-24 01:36:52', '2024-03-24 01:36:52', NULL),
(339, 13, 28, 'String topicArray = Arrays.toString(topics);', '2024-03-24 01:38:28', '2024-03-24 01:38:28', NULL),
(340, 13, 29, 'Sebuah array topics yang berisi beberapa topik (dalam bentuk string) dideklarasikan dan diinisialisasi dengan nilai: {\"Opinion\", \"Tech\", \"Science\", \"Health\"}. Kemudian, dilakukan pemanggilan metode Arrays.toString() untuk mengonversi array topics menjadi sebuah string. Hasil dari konversi tersebut disimpan dalam variabel topicArray. Terakhir, string yang berisi representasi dari array topics disimpan dalam variabel topicArray tersebut. String yang berisi representasi dari array topics, yang sekarang disimpan dalam variabel topicArray, dicetak ke konsol menggunakan System.out.print(topicArray)', '2024-03-24 01:38:30', '2024-03-24 01:38:30', NULL),
(341, 13, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1, 2, 3, 4};, maka kode program akan menghasilkan kesalahan pada saat kompilasi. Hal ini disebabkan oleh perbedaan tipe data antara elemen-elemen array dengan tipe data yang diharapkan, yaitu string. Kode String[] topics = {1, 2, 3, 4}; mencoba untuk membuat array topics yang berisi nilai-nilai bertipe int, namun karena kita mendeklarasikan tipe array sebagai String[], maka ini akan menyebabkan kesalahan kompilasi. Jadi, output program tidak akan dihasilkan karena kesalahan kompilasi yang terjadi. Sebelum kita dapat mencetak array tersebut, kita perlu memastikan bahwa elemen-elemen array memiliki tipe data yang sesuai dengan deklarasi array. Dalam kasus ini, kita harus mengubah elemen-elemen array menjadi string, misalnya String[] topics = {\"1\", \"2\", \"3\", \"4\"};.', '2024-03-24 01:38:34', '2024-03-24 01:38:34', NULL),
(342, 13, 31, 'Pada kode i < nilai.length; pada perulangan pertama, nilai.length mengembalikan panjang (jumlah elemen) dari array dua dimensi nilai dalam dimensi pertama, yaitu jumlah baris dari matriks nilai. Jadi, fungsi dari kondisi i < nilai.length; adalah untuk memastikan bahwa iterasi dalam perulangan pertama akan terjadi sebanyak jumlah baris dalam matriks nilai. Dalam konteks ini, i digunakan sebagai indeks baris dari matriks nilai. Jadi, perulangan akan berlangsung dari baris pertama hingga baris terakhir dari matriks nilai. Pada setiap iterasi, blok pernyataan dalam perulangan akan dieksekusi untuk setiap baris dalam matriks nilai. Jadi, i < nilai.length; memastikan bahwa perulangan pertama akan berjalan sesuai dengan jumlah baris dalam matriks nilai, yang memungkinkan program untuk melakukan operasi pada setiap elemen dari matriks tersebut.', '2024-03-24 01:39:38', '2024-03-24 01:39:38', NULL),
(343, 13, 32, 'Perulangan kedua dimulai dengan inisialisasi variabel j dengan nilai 0. Kemudian, dilakukan pengecekan kondisi j < nilai[i].length, di mana nilai[i].length mengembalikan panjang (jumlah elemen) dari array yang berada pada baris ke-i dalam matriks nilai. Dalam konteks ini, ini mengacu pada jumlah elemen (atau jumlah kolom) dari baris ke-i dari matriks nilai. Jika kondisi j < nilai[i].length benar (true), blok pernyataan dalam perulangan kedua dieksekusi. Di dalam blok perulangan kedua, setiap elemen dari baris ke-i dalam matriks nilai diakses menggunakan nilai[i][j]. Nilai tersebut ditambahkan ke variabel total. Selanjutnya, variabel jumlahData (yang digunakan untuk menghitung total jumlah elemen dalam matriks) ditambah satu untuk setiap elemen yang dihitung. Setelah iterasi dalam perulangan kedua selesai, nilai j diperbarui dengan j++, sehingga memungkinkan iterasi ke elemen berikutnya dari baris yang sama. Proses di atas diulangi hingga kondisi j < nilai[i].length tidak lagi terpenuhi. Setelah semua elemen dari baris ke-i telah dihitung, kontrol kembali ke perulangan pertama, di mana nilai i diperbarui, dan proses di atas diulangi untuk baris berikutnya dari matriks nilai. Proses ini berlanjut hingga semua baris dari matriks nilai telah diproses. Setelah seluruh matriks nilai telah diproses, nilai total dari semua elemen matriks (total) dan jumlah total elemen dalam matriks (jumlahData) telah dihitung. Rata-rata dari semua elemen matriks dihitung dengan membagi total nilai dengan jumlah total elemen, yaitu rataRata = total / jumlahData. Nilai rata-rata tersebut kemudian dicetak ke konsol. Program selesai dieksekusi.', '2024-03-24 01:39:43', '2024-03-24 01:39:43', NULL),
(344, 13, 33, 'Dengan elemen array nilai yang baru, yaitu double[][] nilai = {{75, 80, 81}, {90, 95, 90}, {70, 75, 82}} rata-rata nilai yang didapatkan adalah sekitar 82.', '2024-03-24 01:39:46', '2024-03-24 01:39:46', NULL),
(345, 13, 34, 'Kode tampil() pada method main memiliki kegunaan untuk menampilkan informasi terkait luas dan keliling lingkaran ke konsol.', '2024-03-24 01:40:38', '2024-03-24 01:40:38', NULL),
(346, 13, 35, 'Pertama, sebuah variabel lokal phi diinisialisasi dengan nilai 3.14, yang merupakan nilai phi (π) yang digunakan dalam perhitungan luas dan keliling lingkaran. Selanjutnya, sebuah variabel lokal r diinisialisasi dengan nilai 14, yang merupakan jari-jari lingkaran. Kemudian, dilakukan pemanggilan method luasLingkaran(phi, r) untuk menghitung luas lingkaran. Method ini menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai luas lingkaran. Hasil perhitungan luas lingkaran disimpan dalam variabel lokal luas. Selanjutnya, dilakukan pemanggilan method kelilingLingkaran(phi, r) untuk menghitung keliling lingkaran. Method ini juga menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai keliling lingkaran. Hasil perhitungan keliling lingkaran disimpan dalam variabel lokal keliling. Setelah itu, hasil perhitungan luas dan keliling lingkaran dicetak ke konsol menggunakan System.out.print(). Cetak ini mencakup pesan yang menyatakan luas lingkaran beserta nilai luasnya, diikuti dengan pesan yang menyatakan keliling lingkaran beserta nilai kelilingnya. Jadi, fungsi tampil() bertujuan untuk menghitung luas dan keliling lingkaran dengan menggunakan rumus yang sesuai, dan kemudian menampilkan hasilnya ke konsol.', '2024-03-24 01:40:41', '2024-03-24 01:40:41', NULL),
(347, 13, 36, 'Jika kode tampil() pada method main dihapus, maka program tidak akan menampilkan hasil luas dan keliling lingkaran ke konsol saat program dijalankan. Tanpa pemanggilan method tampil() di dalam method main, maka baris kode yang ada di dalam method tampil() tidak akan dieksekusi. Artinya, perhitungan luas dan keliling lingkaran tetap akan terjadi karena pemanggilan method tampil() pada method main merupakan inisiasi untuk menghitung dan menampilkan luas serta keliling lingkaran. Jadi, jika kode tampil() dihapus, program hanya akan dijalankan tanpa menampilkan hasil luas dan keliling lingkaran ke konsol.', '2024-03-24 01:40:44', '2024-03-24 01:40:44', NULL),
(348, 13, 37, 'Ya, program ini menggunakan rekursi.', '2024-03-24 01:41:42', '2024-03-24 01:41:42', NULL),
(349, 13, 38, 'Parameter Masukan: Method hitungBunga() menerima tiga parameter: saldo (saldo awal), bunga (persentase bunga tahunan), dan tahun (jumlah tahun). Pengecekan Basis: Pertama, method melakukan pengecekan apakah nilai tahun sama dengan 0. Jika ya, artinya kita telah mencapai basis rekursi, dan method akan mengembalikan nilai saldo tanpa menghitung bunga lagi. Ini penting untuk mengakhiri rekursi agar tidak terjadi panggilan rekursif yang tak terbatas. Perhitungan Bunga: Jika nilai tahun tidak sama dengan 0, artinya kita masih dalam tahap rekursi. Di sini, method menghitung bunga tahunan dengan rumus bungaTahunan = saldo * (bunga / 100). Ini menghasilkan jumlah bunga yang akan ditambahkan ke saldo awal. Perhitungan Total Saldo: Setelah menghitung bunga tahunan, method menambahkannya ke saldo awal untuk mendapatkan total saldo setelah satu tahun. Ini dilakukan dengan rumus total = saldo + bungaTahunan. Panggilan Rekursif: Selanjutnya, method hitungBunga() memanggil dirinya sendiri dengan total saldo setelah satu tahun (total) sebagai saldo awal pada panggilan rekursif berikutnya. Parameter lainnya (bunga dan tahun) tetap tidak berubah. Dengan demikian, proses ini akan berulang untuk setiap tahun sampai mencapai basis rekursi. Pengembalian Nilai: Setelah selesai semua panggilan rekursif, nilai saldo akhir setelah jumlah tahun yang ditentukan akan dikembalikan ke pemanggil method.', '2024-03-24 01:41:46', '2024-03-24 01:41:46', NULL),
(350, 13, 39, 'Jika bunga pertahun diganti menjadi 7%, jumlah uang yang dihasilkan setelah 5 tahun adalah sekitar 1.407.165,32.', '2024-03-24 01:41:49', '2024-03-24 01:41:49', NULL),
(351, 21, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-03-24 02:56:05', '2024-03-24 02:56:05', NULL),
(352, 21, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-03-24 02:56:09', '2024-03-24 02:56:09', NULL),
(353, 21, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-03-24 02:56:13', '2024-03-24 02:56:13', NULL),
(357, 21, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-03-28 08:33:06', '2024-03-28 08:33:06', NULL),
(358, 21, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-03-28 08:33:10', '2024-03-28 08:33:10', NULL),
(359, 21, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-03-28 08:33:14', '2024-03-28 08:33:14', NULL),
(360, 21, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-03-28 08:34:30', '2024-03-28 08:34:30', NULL),
(361, 21, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi.', '2024-03-28 08:34:34', '2024-03-28 08:34:34', NULL),
(362, 21, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-03-28 08:34:39', '2024-03-28 08:34:39', NULL),
(363, 21, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-03-28 08:36:26', '2024-03-28 08:36:26', NULL),
(364, 21, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi.', '2024-03-28 08:36:30', '2024-03-28 08:36:30', NULL),
(365, 21, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-03-28 08:36:36', '2024-03-28 08:36:36', NULL),
(366, 21, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-03-28 08:37:46', '2024-03-28 08:37:46', NULL),
(367, 21, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-03-28 08:37:51', '2024-03-28 08:37:51', NULL),
(368, 21, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-03-28 08:37:56', '2024-03-28 08:37:56', NULL),
(369, 21, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i. Lebih tepatnya, itu adalah ekspresi increment yang bertugas untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-03-28 08:39:07', '2024-03-28 08:39:07', NULL),
(370, 21, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-03-28 08:39:11', '2024-03-28 08:39:11', NULL),
(371, 21, 18, 'Jika nilai dari variabel number adalah 8, maka program akan mencetak angka dari 1 hingga 7. Ini disebabkan oleh kondisi perulangan for, di mana i akan mulai dari 1 dan berakhir pada 7 (karena 7 kurang dari 8), sementara perulangan akan berhenti sebelum mencapai 8. Jadi, output dari program akan menjadi 1234567', '2024-03-28 08:39:16', '2024-03-28 08:39:16', NULL),
(372, 21, 19, 'Pada kode program di atas, i++ memiliki kegunaan yang sama dengan pada contoh sebelumnya yang menggunakan perulangan for. Di dalam perulangan while, i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-03-28 08:40:18', '2024-03-28 08:40:18', NULL),
(373, 21, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-03-28 08:40:22', '2024-03-28 08:40:22', NULL),
(374, 21, 21, 'Jika kondisi dalam while diganti menjadi while(i > number), maka loop while tidak akan pernah dieksekusi. Hal ini karena pada saat inisialisasi variabel i memiliki nilai 1, sedangkan nilai variabel number adalah 6. Kondisi i > number (1 > 6) tidak terpenuhi, sehingga blok pernyataan di dalam while tidak akan dieksekusi sama sekali. Sehingga, tidak ada output yang akan dikeluarkan oleh program dalam kasus ini. Program akan selesai tanpa mencetak apa pun ke konsol.', '2024-03-28 08:40:26', '2024-03-28 08:40:26', NULL),
(375, 21, 22, 'Baris kode int next = first + second; berfungsi untuk menghitung nilai selanjutnya dalam deret Fibonacci. Dalam deret Fibonacci, setiap angka adalah hasil penjumlahan dari dua angka sebelumnya. Oleh karena itu, next dihitung dengan menambahkan nilai first (angka sebelumnya dalam deret) dengan nilai second (angka sebelumnya dari first). Dengan melakukan operasi first + second, nilai next akan menjadi angka berikutnya dalam deret Fibonacci setelah first dan second. Kemudian, nilai-nilai variabel first dan second akan diperbarui untuk mempersiapkan perhitungan angka berikutnya dalam deret Fibonacci.', '2024-03-28 08:41:32', '2024-03-28 08:41:32', NULL),
(376, 21, 23, 'Program memasuki blok kode do-while. Pertama-tama, variabel n diinisialisasi dengan nilai 6, yang menunjukkan bahwa kita akan mencetak deret Fibonacci hingga indeks ke-6. Variabel first diinisialisasi dengan nilai 0, dan second diinisialisasi dengan nilai 1. Ini adalah dua angka awal dalam deret Fibonacci. Variabel i diinisialisasi dengan nilai 1, yang akan digunakan untuk menghitung jumlah iterasi dalam perulangan. String \"Deret Fibonacci: \\n\" dicetak ke konsol untuk memberikan label pada deret Fibonacci yang akan dicetak. Angka pertama dan kedua dalam deret Fibonacci (0 dan 1) dicetak ke konsol. Program masuk ke dalam blok pernyataan do-while. Di dalam blok do-while, angka berikutnya dalam deret Fibonacci dihitung dengan menjumlahkan nilai first dan second, dan hasilnya disimpan dalam variabel next. Nilai next dicetak ke konsol. Nilai variabel first diperbarui dengan nilai variabel second, yang berarti angka sebelumnya dalam deret Fibonacci menjadi nilai second saat ini. Nilai variabel second diperbarui dengan nilai next, yang merupakan angka berikutnya dalam deret Fibonacci. Variabel i (penghitung iterasi) ditambah 1. Program mengevaluasi kondisi i <= n. Jika kondisi terpenuhi, program akan kembali ke langkah 8 untuk menghitung dan mencetak angka berikutnya dalam deret Fibonacci. Proses ini berlanjut sampai nilai i melebihi nilai n. Setelah itu, program keluar dari blok perulangan do-while. Program selesai dieksekusi.', '2024-03-28 08:41:37', '2024-03-28 08:41:37', NULL),
(377, 21, 24, 'Jika nilai variabel n diganti menjadi 7, maka program akan mencetak deret Fibonacci hingga indeks ke-7 sehingga hasilnya 0 1 1 2 3 5 8', '2024-03-28 08:41:42', '2024-03-28 08:41:42', NULL),
(378, 21, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) menentukan berapa kali perulangan akan dieksekusi. Dalam kasus ini, kondisi tersebut berarti perulangan akan dieksekusi ketika nilai i kurang dari atau sama dengan 5. Jadi, fungsi dari kondisi i <= 5 adalah untuk mengontrol jumlah baris dalam pola bintang yang dibuat oleh piramid. Dengan kondisi tersebut, perulangan akan dieksekusi sebanyak lima kali, menghasilkan lima baris pada pola bintang. Pada setiap iterasi, jumlah bintang yang dicetak pada setiap baris akan sesuai dengan nilai i pada saat itu. Sehingga, pada iterasi pertama, hanya satu bintang yang dicetak, pada iterasi kedua dua bintang, dan seterusnya hingga iterasi kelima.', '2024-03-28 08:42:42', '2024-03-28 08:42:42', NULL),
(379, 21, 26, 'Setiap kali iterasi dari perulangan pertama (outer loop) dieksekusi, variabel i akan bertambah satu dari nilai awal 1 hingga mencapai 5, sesuai dengan kondisi i <= 5. Di dalam setiap iterasi dari perulangan pertama, perulangan kedua (inner loop) akan dieksekusi. Pada awal iterasi dari perulangan kedua, variabel j akan diinisialisasi dengan nilai awal 1. Kondisi perulangan kedua, j <= i, menentukan berapa kali perulangan ini akan dieksekusi. Pada setiap iterasi, jumlah bintang yang dicetak akan sesuai dengan nilai i pada saat itu. Pada iterasi pertama dari perulangan pertama (ketika i adalah 1), perulangan kedua akan dieksekusi satu kali (karena j kurang dari atau sama dengan 1). Pada iterasi kedua dari perulangan pertama (ketika i adalah 2), perulangan kedua akan dieksekusi dua kali (karena j kurang dari atau sama dengan 2). Hal ini berlanjut hingga iterasi kelima dari perulangan pertama, di mana perulangan kedua akan dieksekusi sebanyak lima kali (karena j kurang dari atau sama dengan 5). Di dalam blok perulangan kedua, bintang (*) akan ditambahkan ke variabel output pada setiap iterasi. Setelah perulangan kedua selesai dieksekusi untuk nilai i tertentu, baris baru (\\n) akan ditambahkan ke variabel output, sehingga bintang-bintang yang tercetak membentuk pola piramida. Proses ini akan terus berlanjut hingga iterasi dari perulangan pertama selesai, dan hasil akhirnya, output akan dicetak ke konsol. Dengan demikian, alur program dari perulangan kedua menggunakan variabel j adalah untuk menambahkan bintang ke dalam variabel output sesuai dengan jumlah iterasi yang sesuai dengan nilai i pada saat itu, yang menghasilkan pola piramida dari bintang', '2024-03-28 08:42:47', '2024-03-28 08:42:47', NULL),
(380, 21, 27, 'Jika kondisi i <= 5 pada perulangan pertama (outer loop) diganti menjadi i <= 6, maka perulangan akan dieksekusi lebih dari sebelumnya, yaitu sebanyak enam kali. Ini berarti akan ada enam baris dalam pola bintang yang dihasilkan.', '2024-03-28 08:42:51', '2024-03-28 08:42:51', NULL),
(381, 21, 28, 'String topicArray = Arrays.toString(topics);', '2024-03-28 08:44:08', '2024-03-28 08:44:08', NULL),
(382, 21, 29, 'Sebuah array topics yang berisi beberapa topik (dalam bentuk string) dideklarasikan dan diinisialisasi dengan nilai: {\"Opinion\", \"Tech\", \"Science\", \"Health\"}. Kemudian, dilakukan pemanggilan metode Arrays.toString() untuk mengonversi array topics menjadi sebuah string. Hasil dari konversi tersebut disimpan dalam variabel topicArray. Terakhir, string yang berisi representasi dari array topics disimpan dalam variabel topicArray tersebut. String yang berisi representasi dari array topics, yang sekarang disimpan dalam variabel topicArray, dicetak ke konsol menggunakan System.out.print(topicArray)', '2024-03-28 08:44:12', '2024-03-28 08:44:12', NULL),
(383, 21, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1, 2, 3, 4};, maka kode program akan menghasilkan kesalahan pada saat kompilasi. Hal ini disebabkan oleh perbedaan tipe data antara elemen-elemen array dengan tipe data yang diharapkan, yaitu string. Kode String[] topics = {1, 2, 3, 4}; mencoba untuk membuat array topics yang berisi nilai-nilai bertipe int, namun karena kita mendeklarasikan tipe array sebagai String[], maka ini akan menyebabkan kesalahan kompilasi. Jadi, output program tidak akan dihasilkan karena kesalahan kompilasi yang terjadi. Sebelum kita dapat mencetak array tersebut, kita perlu memastikan bahwa elemen-elemen array memiliki tipe data yang sesuai dengan deklarasi array. Dalam kasus ini, kita harus mengubah elemen-elemen array menjadi string, misalnya String[] topics = {\"1\", \"2\", \"3\", \"4\"};.', '2024-03-28 08:44:17', '2024-03-28 08:44:17', NULL),
(384, 21, 31, 'Pada kode i < nilai.length; pada perulangan pertama, nilai.length mengembalikan panjang (jumlah elemen) dari array dua dimensi nilai dalam dimensi pertama, yaitu jumlah baris dari matriks nilai. Jadi, fungsi dari kondisi i < nilai.length; adalah untuk memastikan bahwa iterasi dalam perulangan pertama akan terjadi sebanyak jumlah baris dalam matriks nilai. Dalam konteks ini, i digunakan sebagai indeks baris dari matriks nilai. Jadi, perulangan akan berlangsung dari baris pertama hingga baris terakhir dari matriks nilai. Pada setiap iterasi, blok pernyataan dalam perulangan akan dieksekusi untuk setiap baris dalam matriks nilai. Jadi, i < nilai.length; memastikan bahwa perulangan pertama akan berjalan sesuai dengan jumlah baris dalam matriks nilai, yang memungkinkan program untuk melakukan operasi pada setiap elemen dari matriks tersebut.', '2024-03-28 08:45:35', '2024-03-28 08:45:35', NULL),
(385, 21, 32, 'Perulangan kedua dimulai dengan inisialisasi variabel j dengan nilai 0. Kemudian, dilakukan pengecekan kondisi j < nilai[i].length, di mana nilai[i].length mengembalikan panjang (jumlah elemen) dari array yang berada pada baris ke-i dalam matriks nilai. Dalam konteks ini, ini mengacu pada jumlah elemen (atau jumlah kolom) dari baris ke-i dari matriks nilai. Jika kondisi j < nilai[i].length benar (true), blok pernyataan dalam perulangan kedua dieksekusi. Di dalam blok perulangan kedua, setiap elemen dari baris ke-i dalam matriks nilai diakses menggunakan nilai[i][j]. Nilai tersebut ditambahkan ke variabel total. Selanjutnya, variabel jumlahData (yang digunakan untuk menghitung total jumlah elemen dalam matriks) ditambah satu untuk setiap elemen yang dihitung. Setelah iterasi dalam perulangan kedua selesai, nilai j diperbarui dengan j++, sehingga memungkinkan iterasi ke elemen berikutnya dari baris yang sama. Proses di atas diulangi hingga kondisi j < nilai[i].length tidak lagi terpenuhi. Setelah semua elemen dari baris ke-i telah dihitung, kontrol kembali ke perulangan pertama, di mana nilai i diperbarui, dan proses di atas diulangi untuk baris berikutnya dari matriks nilai. Proses ini berlanjut hingga semua baris dari matriks nilai telah diproses. Setelah seluruh matriks nilai telah diproses, nilai total dari semua elemen matriks (total) dan jumlah total elemen dalam matriks (jumlahData) telah dihitung. Rata-rata dari semua elemen matriks dihitung dengan membagi total nilai dengan jumlah total elemen, yaitu rataRata = total / jumlahData. Nilai rata-rata tersebut kemudian dicetak ke konsol. Program selesai dieksekusi.', '2024-03-28 08:45:39', '2024-03-28 08:45:39', NULL),
(386, 21, 33, 'Dengan elemen array nilai yang baru, yaitu double[][] nilai = {{75, 80, 81}, {90, 95, 90}, {70, 75, 82}} rata-rata nilai yang didapatkan adalah sekitar 82.', '2024-03-28 08:45:45', '2024-03-28 08:45:45', NULL),
(387, 21, 34, 'Kode tampil() pada method main memiliki kegunaan untuk menampilkan informasi terkait luas dan keliling lingkaran ke konsol.', '2024-03-28 08:46:44', '2024-03-28 08:46:44', NULL),
(388, 21, 35, 'Pertama, sebuah variabel lokal phi diinisialisasi dengan nilai 3.14, yang merupakan nilai phi (π) yang digunakan dalam perhitungan luas dan keliling lingkaran. Selanjutnya, sebuah variabel lokal r diinisialisasi dengan nilai 14, yang merupakan jari-jari lingkaran. Kemudian, dilakukan pemanggilan method luasLingkaran(phi, r) untuk menghitung luas lingkaran. Method ini menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai luas lingkaran. Hasil perhitungan luas lingkaran disimpan dalam variabel lokal luas. Selanjutnya, dilakukan pemanggilan method kelilingLingkaran(phi, r) untuk menghitung keliling lingkaran. Method ini juga menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai keliling lingkaran. Hasil perhitungan keliling lingkaran disimpan dalam variabel lokal keliling. Setelah itu, hasil perhitungan luas dan keliling lingkaran dicetak ke konsol menggunakan System.out.print(). Cetak ini mencakup pesan yang menyatakan luas lingkaran beserta nilai luasnya, diikuti dengan pesan yang menyatakan keliling lingkaran beserta nilai kelilingnya. Jadi, fungsi tampil() bertujuan untuk menghitung luas dan keliling lingkaran dengan menggunakan rumus yang sesuai, dan kemudian menampilkan hasilnya ke konsol.', '2024-03-28 08:46:47', '2024-03-28 08:46:47', NULL),
(389, 21, 36, 'Jika kode tampil() pada method main dihapus, maka program tidak akan menampilkan hasil luas dan keliling lingkaran ke konsol saat program dijalankan. Tanpa pemanggilan method tampil() di dalam method main, maka baris kode yang ada di dalam method tampil() tidak akan dieksekusi. Artinya, perhitungan luas dan keliling lingkaran tetap akan terjadi karena pemanggilan method tampil() pada method main merupakan inisiasi untuk menghitung dan menampilkan luas serta keliling lingkaran. Jadi, jika kode tampil() dihapus, program hanya akan dijalankan tanpa menampilkan hasil luas dan keliling lingkaran ke konsol.', '2024-03-28 08:46:51', '2024-03-28 08:46:51', NULL),
(390, 21, 37, 'Ya, program ini menggunakan rekursi.', '2024-03-28 08:47:46', '2024-03-28 08:47:46', NULL),
(391, 21, 38, 'Parameter Masukan: Method hitungBunga() menerima tiga parameter: saldo (saldo awal), bunga (persentase bunga tahunan), dan tahun (jumlah tahun). Pengecekan Basis: Pertama, method melakukan pengecekan apakah nilai tahun sama dengan 0. Jika ya, artinya kita telah mencapai basis rekursi, dan method akan mengembalikan nilai saldo tanpa menghitung bunga lagi. Ini penting untuk mengakhiri rekursi agar tidak terjadi panggilan rekursif yang tak terbatas. Perhitungan Bunga: Jika nilai tahun tidak sama dengan 0, artinya kita masih dalam tahap rekursi. Di sini, method menghitung bunga tahunan dengan rumus bungaTahunan = saldo * (bunga / 100). Ini menghasilkan jumlah bunga yang akan ditambahkan ke saldo awal. Perhitungan Total Saldo: Setelah menghitung bunga tahunan, method menambahkannya ke saldo awal untuk mendapatkan total saldo setelah satu tahun. Ini dilakukan dengan rumus total = saldo + bungaTahunan. Panggilan Rekursif: Selanjutnya, method hitungBunga() memanggil dirinya sendiri dengan total saldo setelah satu tahun (total) sebagai saldo awal pada panggilan rekursif berikutnya. Parameter lainnya (bunga dan tahun) tetap tidak berubah. Dengan demikian, proses ini akan berulang untuk setiap tahun sampai mencapai basis rekursi. Pengembalian Nilai: Setelah selesai semua panggilan rekursif, nilai saldo akhir setelah jumlah tahun yang ditentukan akan dikembalikan ke pemanggil method.', '2024-03-28 08:47:51', '2024-03-28 08:47:51', NULL),
(392, 21, 39, 'Jika bunga pertahun diganti menjadi 7%, jumlah uang yang dihasilkan setelah 5 tahun adalah sekitar 1.407.165,32.', '2024-03-28 08:47:57', '2024-03-28 08:47:57', NULL),
(393, 22, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-03-28 08:59:54', '2024-03-28 08:59:54', NULL),
(394, 22, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-03-28 09:00:03', '2024-03-28 09:00:03', NULL),
(395, 22, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-03-28 09:00:10', '2024-03-28 09:00:10', NULL),
(396, 22, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-03-28 09:04:15', '2024-03-28 09:04:15', NULL),
(397, 22, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-03-28 09:04:21', '2024-03-28 09:04:21', NULL),
(398, 22, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-03-28 09:04:24', '2024-03-28 09:04:24', NULL),
(399, 22, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-03-28 09:05:14', '2024-03-28 09:05:14', NULL),
(400, 22, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi.', '2024-03-28 09:05:19', '2024-03-28 09:05:19', NULL),
(401, 22, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-03-28 09:05:26', '2024-03-28 09:05:26', NULL),
(402, 22, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-03-28 09:06:26', '2024-03-28 09:06:26', NULL),
(403, 22, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi.', '2024-03-28 09:06:31', '2024-03-28 09:06:31', NULL);
INSERT INTO `user_answer` (`id`, `user_id`, `essay_question_id`, `answer`, `created_at`, `updated_at`, `deleted_at`) VALUES
(404, 22, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-03-28 09:06:39', '2024-03-28 09:06:39', NULL),
(405, 22, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-03-28 09:08:03', '2024-03-28 09:08:03', NULL),
(406, 22, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-03-28 09:08:08', '2024-03-28 09:08:08', NULL),
(407, 22, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-03-28 09:08:12', '2024-03-28 09:08:12', NULL),
(408, 22, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i. Lebih tepatnya, itu adalah ekspresi increment yang bertugas untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-03-28 09:12:51', '2024-03-28 09:12:51', NULL),
(409, 22, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-03-28 09:12:57', '2024-03-28 09:12:57', NULL),
(410, 22, 18, 'Jika nilai dari variabel number adalah 8, maka program akan mencetak angka dari 1 hingga 7. Ini disebabkan oleh kondisi perulangan for, di mana i akan mulai dari 1 dan berakhir pada 7 (karena 7 kurang dari 8), sementara perulangan akan berhenti sebelum mencapai 8. Jadi, output dari program akan menjadi 1234567', '2024-03-28 09:13:00', '2024-03-28 09:13:00', NULL),
(411, 22, 19, 'Pada kode program di atas, i++ memiliki kegunaan yang sama dengan pada contoh sebelumnya yang menggunakan perulangan for. Di dalam perulangan while, i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-03-28 09:14:01', '2024-03-28 09:14:01', NULL),
(412, 22, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-03-28 09:14:07', '2024-03-28 09:14:07', NULL),
(413, 22, 21, 'Jika kondisi dalam while diganti menjadi while(i > number), maka loop while tidak akan pernah dieksekusi. Hal ini karena pada saat inisialisasi variabel i memiliki nilai 1, sedangkan nilai variabel number adalah 6. Kondisi i > number (1 > 6) tidak terpenuhi, sehingga blok pernyataan di dalam while tidak akan dieksekusi sama sekali. Sehingga, tidak ada output yang akan dikeluarkan oleh program dalam kasus ini. Program akan selesai tanpa mencetak apa pun ke konsol.', '2024-03-28 09:14:11', '2024-03-28 09:14:11', NULL),
(414, 22, 22, 'Baris kode int next = first + second; berfungsi untuk menghitung nilai selanjutnya dalam deret Fibonacci. Dalam deret Fibonacci, setiap angka adalah hasil penjumlahan dari dua angka sebelumnya. Oleh karena itu, next dihitung dengan menambahkan nilai first (angka sebelumnya dalam deret) dengan nilai second (angka sebelumnya dari first). Dengan melakukan operasi first + second, nilai next akan menjadi angka berikutnya dalam deret Fibonacci setelah first dan second. Kemudian, nilai-nilai variabel first dan second akan diperbarui untuk mempersiapkan perhitungan angka berikutnya dalam deret Fibonacci.', '2024-03-28 09:15:06', '2024-03-28 09:15:06', NULL),
(415, 22, 23, 'Program memasuki blok kode do-while. Pertama-tama, variabel n diinisialisasi dengan nilai 6, yang menunjukkan bahwa kita akan mencetak deret Fibonacci hingga indeks ke-6. Variabel first diinisialisasi dengan nilai 0, dan second diinisialisasi dengan nilai 1. Ini adalah dua angka awal dalam deret Fibonacci. Variabel i diinisialisasi dengan nilai 1, yang akan digunakan untuk menghitung jumlah iterasi dalam perulangan. String \"Deret Fibonacci: \\n\" dicetak ke konsol untuk memberikan label pada deret Fibonacci yang akan dicetak. Angka pertama dan kedua dalam deret Fibonacci (0 dan 1) dicetak ke konsol. Program masuk ke dalam blok pernyataan do-while. Di dalam blok do-while, angka berikutnya dalam deret Fibonacci dihitung dengan menjumlahkan nilai first dan second, dan hasilnya disimpan dalam variabel next. Nilai next dicetak ke konsol. Nilai variabel first diperbarui dengan nilai variabel second, yang berarti angka sebelumnya dalam deret Fibonacci menjadi nilai second saat ini. Nilai variabel second diperbarui dengan nilai next, yang merupakan angka berikutnya dalam deret Fibonacci. Variabel i (penghitung iterasi) ditambah 1. Program mengevaluasi kondisi i <= n. Jika kondisi terpenuhi, program akan kembali ke langkah 8 untuk menghitung dan mencetak angka berikutnya dalam deret Fibonacci. Proses ini berlanjut sampai nilai i melebihi nilai n. Setelah itu, program keluar dari blok perulangan do-while. Program selesai dieksekusi.', '2024-03-28 09:15:12', '2024-03-28 09:15:12', NULL),
(416, 22, 24, 'Jika nilai variabel n diganti menjadi 7, maka program akan mencetak deret Fibonacci hingga indeks ke-7 sehingga hasilnya 0 1 1 2 3 5 8', '2024-03-28 09:15:19', '2024-03-28 09:15:19', NULL),
(417, 22, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) menentukan berapa kali perulangan akan dieksekusi. Dalam kasus ini, kondisi tersebut berarti perulangan akan dieksekusi ketika nilai i kurang dari atau sama dengan 5. Jadi, fungsi dari kondisi i <= 5 adalah untuk mengontrol jumlah baris dalam pola bintang yang dibuat oleh piramid. Dengan kondisi tersebut, perulangan akan dieksekusi sebanyak lima kali, menghasilkan lima baris pada pola bintang. Pada setiap iterasi, jumlah bintang yang dicetak pada setiap baris akan sesuai dengan nilai i pada saat itu. Sehingga, pada iterasi pertama, hanya satu bintang yang dicetak, pada iterasi kedua dua bintang, dan seterusnya hingga iterasi kelima.', '2024-03-28 09:16:23', '2024-03-28 09:16:23', NULL),
(418, 22, 26, 'Setiap kali iterasi dari perulangan pertama (outer loop) dieksekusi, variabel i akan bertambah satu dari nilai awal 1 hingga mencapai 5, sesuai dengan kondisi i <= 5. Di dalam setiap iterasi dari perulangan pertama, perulangan kedua (inner loop) akan dieksekusi. Pada awal iterasi dari perulangan kedua, variabel j akan diinisialisasi dengan nilai awal 1. Kondisi perulangan kedua, j <= i, menentukan berapa kali perulangan ini akan dieksekusi. Pada setiap iterasi, jumlah bintang yang dicetak akan sesuai dengan nilai i pada saat itu. Pada iterasi pertama dari perulangan pertama (ketika i adalah 1), perulangan kedua akan dieksekusi satu kali (karena j kurang dari atau sama dengan 1). Pada iterasi kedua dari perulangan pertama (ketika i adalah 2), perulangan kedua akan dieksekusi dua kali (karena j kurang dari atau sama dengan 2). Hal ini berlanjut hingga iterasi kelima dari perulangan pertama, di mana perulangan kedua akan dieksekusi sebanyak lima kali (karena j kurang dari atau sama dengan 5). Di dalam blok perulangan kedua, bintang (*) akan ditambahkan ke variabel output pada setiap iterasi. Setelah perulangan kedua selesai dieksekusi untuk nilai i tertentu, baris baru (\\n) akan ditambahkan ke variabel output, sehingga bintang-bintang yang tercetak membentuk pola piramida. Proses ini akan terus berlanjut hingga iterasi dari perulangan pertama selesai, dan hasil akhirnya, output akan dicetak ke konsol. Dengan demikian, alur program dari perulangan kedua menggunakan variabel j adalah untuk menambahkan bintang ke dalam variabel output sesuai dengan jumlah iterasi yang sesuai dengan nilai i pada saat itu, yang menghasilkan pola piramida dari bintang', '2024-03-28 09:16:28', '2024-03-28 09:16:28', NULL),
(419, 22, 27, 'Jika kondisi i <= 5 pada perulangan pertama (outer loop) diganti menjadi i <= 6, maka perulangan akan dieksekusi lebih dari sebelumnya, yaitu sebanyak enam kali. Ini berarti akan ada enam baris dalam pola bintang yang dihasilkan.', '2024-03-28 09:16:34', '2024-03-28 09:16:34', NULL),
(420, 22, 28, 'String topicArray = Arrays.toString(topics);', '2024-03-28 09:17:39', '2024-03-28 09:17:39', NULL),
(421, 22, 29, 'Sebuah array topics yang berisi beberapa topik (dalam bentuk string) dideklarasikan dan diinisialisasi dengan nilai: {\"Opinion\", \"Tech\", \"Science\", \"Health\"}. Kemudian, dilakukan pemanggilan metode Arrays.toString() untuk mengonversi array topics menjadi sebuah string. Hasil dari konversi tersebut disimpan dalam variabel topicArray. Terakhir, string yang berisi representasi dari array topics disimpan dalam variabel topicArray tersebut. String yang berisi representasi dari array topics, yang sekarang disimpan dalam variabel topicArray, dicetak ke konsol menggunakan System.out.print(topicArray)', '2024-03-28 09:17:43', '2024-03-28 09:17:43', NULL),
(422, 22, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1, 2, 3, 4};, maka kode program akan menghasilkan kesalahan pada saat kompilasi. Hal ini disebabkan oleh perbedaan tipe data antara elemen-elemen array dengan tipe data yang diharapkan, yaitu string. Kode String[] topics = {1, 2, 3, 4}; mencoba untuk membuat array topics yang berisi nilai-nilai bertipe int, namun karena kita mendeklarasikan tipe array sebagai String[], maka ini akan menyebabkan kesalahan kompilasi. Jadi, output program tidak akan dihasilkan karena kesalahan kompilasi yang terjadi. Sebelum kita dapat mencetak array tersebut, kita perlu memastikan bahwa elemen-elemen array memiliki tipe data yang sesuai dengan deklarasi array. Dalam kasus ini, kita harus mengubah elemen-elemen array menjadi string, misalnya String[] topics = {\"1\", \"2\", \"3\", \"4\"};.', '2024-03-28 09:17:48', '2024-03-28 09:17:48', NULL),
(423, 22, 31, 'Pada kode i < nilai.length; pada perulangan pertama, nilai.length mengembalikan panjang (jumlah elemen) dari array dua dimensi nilai dalam dimensi pertama, yaitu jumlah baris dari matriks nilai. Jadi, fungsi dari kondisi i < nilai.length; adalah untuk memastikan bahwa iterasi dalam perulangan pertama akan terjadi sebanyak jumlah baris dalam matriks nilai. Dalam konteks ini, i digunakan sebagai indeks baris dari matriks nilai. Jadi, perulangan akan berlangsung dari baris pertama hingga baris terakhir dari matriks nilai. Pada setiap iterasi, blok pernyataan dalam perulangan akan dieksekusi untuk setiap baris dalam matriks nilai. Jadi, i < nilai.length; memastikan bahwa perulangan pertama akan berjalan sesuai dengan jumlah baris dalam matriks nilai, yang memungkinkan program untuk melakukan operasi pada setiap elemen dari matriks tersebut.', '2024-03-28 09:18:44', '2024-03-28 09:18:44', NULL),
(424, 22, 32, 'Perulangan kedua dimulai dengan inisialisasi variabel j dengan nilai 0. Kemudian, dilakukan pengecekan kondisi j < nilai[i].length, di mana nilai[i].length mengembalikan panjang (jumlah elemen) dari array yang berada pada baris ke-i dalam matriks nilai. Dalam konteks ini, ini mengacu pada jumlah elemen (atau jumlah kolom) dari baris ke-i dari matriks nilai. Jika kondisi j < nilai[i].length benar (true), blok pernyataan dalam perulangan kedua dieksekusi. Di dalam blok perulangan kedua, setiap elemen dari baris ke-i dalam matriks nilai diakses menggunakan nilai[i][j]. Nilai tersebut ditambahkan ke variabel total. Selanjutnya, variabel jumlahData (yang digunakan untuk menghitung total jumlah elemen dalam matriks) ditambah satu untuk setiap elemen yang dihitung. Setelah iterasi dalam perulangan kedua selesai, nilai j diperbarui dengan j++, sehingga memungkinkan iterasi ke elemen berikutnya dari baris yang sama. Proses di atas diulangi hingga kondisi j < nilai[i].length tidak lagi terpenuhi. Setelah semua elemen dari baris ke-i telah dihitung, kontrol kembali ke perulangan pertama, di mana nilai i diperbarui, dan proses di atas diulangi untuk baris berikutnya dari matriks nilai. Proses ini berlanjut hingga semua baris dari matriks nilai telah diproses. Setelah seluruh matriks nilai telah diproses, nilai total dari semua elemen matriks (total) dan jumlah total elemen dalam matriks (jumlahData) telah dihitung. Rata-rata dari semua elemen matriks dihitung dengan membagi total nilai dengan jumlah total elemen, yaitu rataRata = total / jumlahData. Nilai rata-rata tersebut kemudian dicetak ke konsol. Program selesai dieksekusi.', '2024-03-28 09:18:48', '2024-03-28 09:18:48', NULL),
(425, 22, 33, 'Dengan elemen array nilai yang baru, yaitu double[][] nilai = {{75, 80, 81}, {90, 95, 90}, {70, 75, 82}} rata-rata nilai yang didapatkan adalah sekitar 82.', '2024-03-28 09:18:55', '2024-03-28 09:18:55', NULL),
(426, 22, 34, 'Kode tampil() pada method main memiliki kegunaan untuk menampilkan informasi terkait luas dan keliling lingkaran ke konsol.', '2024-03-28 09:19:58', '2024-03-28 09:19:58', NULL),
(427, 22, 35, 'Pertama, sebuah variabel lokal phi diinisialisasi dengan nilai 3.14, yang merupakan nilai phi (π) yang digunakan dalam perhitungan luas dan keliling lingkaran. Selanjutnya, sebuah variabel lokal r diinisialisasi dengan nilai 14, yang merupakan jari-jari lingkaran. Kemudian, dilakukan pemanggilan method luasLingkaran(phi, r) untuk menghitung luas lingkaran. Method ini menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai luas lingkaran. Hasil perhitungan luas lingkaran disimpan dalam variabel lokal luas. Selanjutnya, dilakukan pemanggilan method kelilingLingkaran(phi, r) untuk menghitung keliling lingkaran. Method ini juga menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai keliling lingkaran. Hasil perhitungan keliling lingkaran disimpan dalam variabel lokal keliling. Setelah itu, hasil perhitungan luas dan keliling lingkaran dicetak ke konsol menggunakan System.out.print(). Cetak ini mencakup pesan yang menyatakan luas lingkaran beserta nilai luasnya, diikuti dengan pesan yang menyatakan keliling lingkaran beserta nilai kelilingnya. Jadi, fungsi tampil() bertujuan untuk menghitung luas dan keliling lingkaran dengan menggunakan rumus yang sesuai, dan kemudian menampilkan hasilnya ke konsol.', '2024-03-28 09:20:02', '2024-03-28 09:20:02', NULL),
(428, 22, 36, 'Jika kode tampil() pada method main dihapus, maka program tidak akan menampilkan hasil luas dan keliling lingkaran ke konsol saat program dijalankan. Tanpa pemanggilan method tampil() di dalam method main, maka baris kode yang ada di dalam method tampil() tidak akan dieksekusi. Artinya, perhitungan luas dan keliling lingkaran tetap akan terjadi karena pemanggilan method tampil() pada method main merupakan inisiasi untuk menghitung dan menampilkan luas serta keliling lingkaran. Jadi, jika kode tampil() dihapus, program hanya akan dijalankan tanpa menampilkan hasil luas dan keliling lingkaran ke konsol.', '2024-03-28 09:20:07', '2024-03-28 09:20:07', NULL),
(429, 22, 37, 'Ya, program ini menggunakan rekursi.', '2024-03-28 09:21:05', '2024-03-28 09:21:05', NULL),
(430, 22, 38, 'Parameter Masukan: Method hitungBunga() menerima tiga parameter: saldo (saldo awal), bunga (persentase bunga tahunan), dan tahun (jumlah tahun). Pengecekan Basis: Pertama, method melakukan pengecekan apakah nilai tahun sama dengan 0. Jika ya, artinya kita telah mencapai basis rekursi, dan method akan mengembalikan nilai saldo tanpa menghitung bunga lagi. Ini penting untuk mengakhiri rekursi agar tidak terjadi panggilan rekursif yang tak terbatas. Perhitungan Bunga: Jika nilai tahun tidak sama dengan 0, artinya kita masih dalam tahap rekursi. Di sini, method menghitung bunga tahunan dengan rumus bungaTahunan = saldo * (bunga / 100). Ini menghasilkan jumlah bunga yang akan ditambahkan ke saldo awal. Perhitungan Total Saldo: Setelah menghitung bunga tahunan, method menambahkannya ke saldo awal untuk mendapatkan total saldo setelah satu tahun. Ini dilakukan dengan rumus total = saldo + bungaTahunan. Panggilan Rekursif: Selanjutnya, method hitungBunga() memanggil dirinya sendiri dengan total saldo setelah satu tahun (total) sebagai saldo awal pada panggilan rekursif berikutnya. Parameter lainnya (bunga dan tahun) tetap tidak berubah. Dengan demikian, proses ini akan berulang untuk setiap tahun sampai mencapai basis rekursi. Pengembalian Nilai: Setelah selesai semua panggilan rekursif, nilai saldo akhir setelah jumlah tahun yang ditentukan akan dikembalikan ke pemanggil method.', '2024-03-28 09:21:09', '2024-03-28 09:21:09', NULL),
(431, 22, 39, 'Jika bunga pertahun diganti menjadi 7%, jumlah uang yang dihasilkan setelah 5 tahun adalah sekitar 1.407.165,32.', '2024-03-28 09:21:15', '2024-03-28 09:21:15', NULL),
(432, 23, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-04-01 04:01:45', '2024-04-01 04:01:45', NULL),
(433, 23, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-04-01 04:01:52', '2024-04-01 04:01:52', NULL),
(434, 23, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-04-01 04:01:59', '2024-04-01 04:01:59', NULL),
(435, 23, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-04-01 04:03:04', '2024-04-01 04:03:04', NULL),
(436, 23, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-04-01 04:03:11', '2024-04-01 04:03:11', NULL),
(437, 23, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-04-01 04:03:19', '2024-04-01 04:03:19', NULL),
(438, 23, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-04-01 04:04:21', '2024-04-01 04:04:21', NULL),
(439, 23, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi.', '2024-04-01 04:04:30', '2024-04-01 04:04:30', NULL),
(440, 23, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-04-01 04:04:39', '2024-04-01 04:04:39', NULL),
(441, 23, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-04-01 04:06:28', '2024-04-01 04:06:28', NULL),
(442, 23, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi.', '2024-04-01 04:06:34', '2024-04-01 04:06:34', NULL),
(443, 23, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-04-01 04:06:40', '2024-04-01 04:06:40', NULL),
(444, 23, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-04-01 04:08:59', '2024-04-01 04:08:59', NULL),
(445, 23, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-04-01 04:09:05', '2024-04-01 04:09:05', NULL),
(446, 23, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-04-01 04:09:11', '2024-04-01 04:09:11', NULL),
(447, 23, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i. Lebih tepatnya, itu adalah ekspresi increment yang bertugas untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-04-01 04:10:29', '2024-04-01 04:10:29', NULL),
(448, 23, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-04-01 04:10:35', '2024-04-01 04:10:35', NULL),
(449, 23, 18, 'Jika nilai dari variabel number adalah 8, maka program akan mencetak angka dari 1 hingga 7. Ini disebabkan oleh kondisi perulangan for, di mana i akan mulai dari 1 dan berakhir pada 7 (karena 7 kurang dari 8), sementara perulangan akan berhenti sebelum mencapai 8. Jadi, output dari program akan menjadi 1234567', '2024-04-01 04:10:41', '2024-04-01 04:10:41', NULL),
(450, 23, 19, 'Pada kode program di atas, i++ memiliki kegunaan yang sama dengan pada contoh sebelumnya yang menggunakan perulangan for. Di dalam perulangan while, i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-04-01 04:11:58', '2024-04-01 04:11:58', NULL),
(451, 23, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-04-01 04:12:04', '2024-04-01 04:12:04', NULL),
(452, 23, 21, 'Jika kondisi dalam while diganti menjadi while(i > number), maka loop while tidak akan pernah dieksekusi. Hal ini karena pada saat inisialisasi variabel i memiliki nilai 1, sedangkan nilai variabel number adalah 6. Kondisi i > number (1 > 6) tidak terpenuhi, sehingga blok pernyataan di dalam while tidak akan dieksekusi sama sekali. Sehingga, tidak ada output yang akan dikeluarkan oleh program dalam kasus ini. Program akan selesai tanpa mencetak apa pun ke konsol.', '2024-04-01 04:12:10', '2024-04-01 04:12:10', NULL),
(453, 23, 22, 'Baris kode int next = first + second; berfungsi untuk menghitung nilai selanjutnya dalam deret Fibonacci. Dalam deret Fibonacci, setiap angka adalah hasil penjumlahan dari dua angka sebelumnya. Oleh karena itu, next dihitung dengan menambahkan nilai first (angka sebelumnya dalam deret) dengan nilai second (angka sebelumnya dari first). Dengan melakukan operasi first + second, nilai next akan menjadi angka berikutnya dalam deret Fibonacci setelah first dan second. Kemudian, nilai-nilai variabel first dan second akan diperbarui untuk mempersiapkan perhitungan angka berikutnya dalam deret Fibonacci.', '2024-04-01 04:13:15', '2024-04-01 04:13:15', NULL),
(454, 23, 23, 'Program memasuki blok kode do-while. Pertama-tama, variabel n diinisialisasi dengan nilai 6, yang menunjukkan bahwa kita akan mencetak deret Fibonacci hingga indeks ke-6. Variabel first diinisialisasi dengan nilai 0, dan second diinisialisasi dengan nilai 1. Ini adalah dua angka awal dalam deret Fibonacci. Variabel i diinisialisasi dengan nilai 1, yang akan digunakan untuk menghitung jumlah iterasi dalam perulangan. String \"Deret Fibonacci: \\n\" dicetak ke konsol untuk memberikan label pada deret Fibonacci yang akan dicetak. Angka pertama dan kedua dalam deret Fibonacci (0 dan 1) dicetak ke konsol. Program masuk ke dalam blok pernyataan do-while. Di dalam blok do-while, angka berikutnya dalam deret Fibonacci dihitung dengan menjumlahkan nilai first dan second, dan hasilnya disimpan dalam variabel next. Nilai next dicetak ke konsol. Nilai variabel first diperbarui dengan nilai variabel second, yang berarti angka sebelumnya dalam deret Fibonacci menjadi nilai second saat ini. Nilai variabel second diperbarui dengan nilai next, yang merupakan angka berikutnya dalam deret Fibonacci. Variabel i (penghitung iterasi) ditambah 1. Program mengevaluasi kondisi i <= n. Jika kondisi terpenuhi, program akan kembali ke langkah 8 untuk menghitung dan mencetak angka berikutnya dalam deret Fibonacci. Proses ini berlanjut sampai nilai i melebihi nilai n. Setelah itu, program keluar dari blok perulangan do-while. Program selesai dieksekusi.', '2024-04-01 04:13:22', '2024-04-01 04:13:22', NULL),
(455, 23, 24, 'Jika nilai variabel n diganti menjadi 7, maka program akan mencetak deret Fibonacci hingga indeks ke-7 sehingga hasilnya 0 1 1 2 3 5 8', '2024-04-01 04:13:28', '2024-04-01 04:13:28', NULL),
(456, 23, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) menentukan berapa kali perulangan akan dieksekusi. Dalam kasus ini, kondisi tersebut berarti perulangan akan dieksekusi ketika nilai i kurang dari atau sama dengan 5. Jadi, fungsi dari kondisi i <= 5 adalah untuk mengontrol jumlah baris dalam pola bintang yang dibuat oleh piramid. Dengan kondisi tersebut, perulangan akan dieksekusi sebanyak lima kali, menghasilkan lima baris pada pola bintang. Pada setiap iterasi, jumlah bintang yang dicetak pada setiap baris akan sesuai dengan nilai i pada saat itu. Sehingga, pada iterasi pertama, hanya satu bintang yang dicetak, pada iterasi kedua dua bintang, dan seterusnya hingga iterasi kelima.', '2024-04-01 04:16:45', '2024-04-01 04:16:45', NULL),
(457, 23, 26, 'Setiap kali iterasi dari perulangan pertama (outer loop) dieksekusi, variabel i akan bertambah satu dari nilai awal 1 hingga mencapai 5, sesuai dengan kondisi i <= 5. Di dalam setiap iterasi dari perulangan pertama, perulangan kedua (inner loop) akan dieksekusi. Pada awal iterasi dari perulangan kedua, variabel j akan diinisialisasi dengan nilai awal 1. Kondisi perulangan kedua, j <= i, menentukan berapa kali perulangan ini akan dieksekusi. Pada setiap iterasi, jumlah bintang yang dicetak akan sesuai dengan nilai i pada saat itu. Pada iterasi pertama dari perulangan pertama (ketika i adalah 1), perulangan kedua akan dieksekusi satu kali (karena j kurang dari atau sama dengan 1). Pada iterasi kedua dari perulangan pertama (ketika i adalah 2), perulangan kedua akan dieksekusi dua kali (karena j kurang dari atau sama dengan 2). Hal ini berlanjut hingga iterasi kelima dari perulangan pertama, di mana perulangan kedua akan dieksekusi sebanyak lima kali (karena j kurang dari atau sama dengan 5). Di dalam blok perulangan kedua, bintang (*) akan ditambahkan ke variabel output pada setiap iterasi. Setelah perulangan kedua selesai dieksekusi untuk nilai i tertentu, baris baru (\\n) akan ditambahkan ke variabel output, sehingga bintang-bintang yang tercetak membentuk pola piramida. Proses ini akan terus berlanjut hingga iterasi dari perulangan pertama selesai, dan hasil akhirnya, output akan dicetak ke konsol. Dengan demikian, alur program dari perulangan kedua menggunakan variabel j adalah untuk menambahkan bintang ke dalam variabel output sesuai dengan jumlah iterasi yang sesuai dengan nilai i pada saat itu, yang menghasilkan pola piramida dari bintang', '2024-04-01 04:16:51', '2024-04-01 04:16:51', NULL),
(458, 23, 27, 'Jika kondisi i <= 5 pada perulangan pertama (outer loop) diganti menjadi i <= 6, maka perulangan akan dieksekusi lebih dari sebelumnya, yaitu sebanyak enam kali. Ini berarti akan ada enam baris dalam pola bintang yang dihasilkan.', '2024-04-01 04:17:00', '2024-04-01 04:17:00', NULL),
(459, 23, 28, 'String topicArray = Arrays.toString(topics);', '2024-04-01 04:18:15', '2024-04-01 04:18:15', NULL),
(460, 23, 29, 'Sebuah array topics yang berisi beberapa topik (dalam bentuk string) dideklarasikan dan diinisialisasi dengan nilai: {\"Opinion\", \"Tech\", \"Science\", \"Health\"}. Kemudian, dilakukan pemanggilan metode Arrays.toString() untuk mengonversi array topics menjadi sebuah string. Hasil dari konversi tersebut disimpan dalam variabel topicArray. Terakhir, string yang berisi representasi dari array topics disimpan dalam variabel topicArray tersebut. String yang berisi representasi dari array topics, yang sekarang disimpan dalam variabel topicArray, dicetak ke konsol menggunakan System.out.print(topicArray)', '2024-04-01 04:18:20', '2024-04-01 04:18:20', NULL),
(461, 23, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1, 2, 3, 4};, maka kode program akan menghasilkan kesalahan pada saat kompilasi. Hal ini disebabkan oleh perbedaan tipe data antara elemen-elemen array dengan tipe data yang diharapkan, yaitu string. Kode String[] topics = {1, 2, 3, 4}; mencoba untuk membuat array topics yang berisi nilai-nilai bertipe int, namun karena kita mendeklarasikan tipe array sebagai String[], maka ini akan menyebabkan kesalahan kompilasi. Jadi, output program tidak akan dihasilkan karena kesalahan kompilasi yang terjadi. Sebelum kita dapat mencetak array tersebut, kita perlu memastikan bahwa elemen-elemen array memiliki tipe data yang sesuai dengan deklarasi array. Dalam kasus ini, kita harus mengubah elemen-elemen array menjadi string, misalnya String[] topics = {\"1\", \"2\", \"3\", \"4\"};.', '2024-04-01 04:18:27', '2024-04-01 04:18:27', NULL),
(462, 23, 31, 'Pada kode i < nilai.length; pada perulangan pertama, nilai.length mengembalikan panjang (jumlah elemen) dari array dua dimensi nilai dalam dimensi pertama, yaitu jumlah baris dari matriks nilai. Jadi, fungsi dari kondisi i < nilai.length; adalah untuk memastikan bahwa iterasi dalam perulangan pertama akan terjadi sebanyak jumlah baris dalam matriks nilai. Dalam konteks ini, i digunakan sebagai indeks baris dari matriks nilai. Jadi, perulangan akan berlangsung dari baris pertama hingga baris terakhir dari matriks nilai. Pada setiap iterasi, blok pernyataan dalam perulangan akan dieksekusi untuk setiap baris dalam matriks nilai. Jadi, i < nilai.length; memastikan bahwa perulangan pertama akan berjalan sesuai dengan jumlah baris dalam matriks nilai, yang memungkinkan program untuk melakukan operasi pada setiap elemen dari matriks tersebut.', '2024-04-01 04:20:31', '2024-04-01 04:20:31', NULL),
(463, 23, 32, 'Perulangan kedua dimulai dengan inisialisasi variabel j dengan nilai 0. Kemudian, dilakukan pengecekan kondisi j < nilai[i].length, di mana nilai[i].length mengembalikan panjang (jumlah elemen) dari array yang berada pada baris ke-i dalam matriks nilai. Dalam konteks ini, ini mengacu pada jumlah elemen (atau jumlah kolom) dari baris ke-i dari matriks nilai. Jika kondisi j < nilai[i].length benar (true), blok pernyataan dalam perulangan kedua dieksekusi. Di dalam blok perulangan kedua, setiap elemen dari baris ke-i dalam matriks nilai diakses menggunakan nilai[i][j]. Nilai tersebut ditambahkan ke variabel total. Selanjutnya, variabel jumlahData (yang digunakan untuk menghitung total jumlah elemen dalam matriks) ditambah satu untuk setiap elemen yang dihitung. Setelah iterasi dalam perulangan kedua selesai, nilai j diperbarui dengan j++, sehingga memungkinkan iterasi ke elemen berikutnya dari baris yang sama. Proses di atas diulangi hingga kondisi j < nilai[i].length tidak lagi terpenuhi. Setelah semua elemen dari baris ke-i telah dihitung, kontrol kembali ke perulangan pertama, di mana nilai i diperbarui, dan proses di atas diulangi untuk baris berikutnya dari matriks nilai. Proses ini berlanjut hingga semua baris dari matriks nilai telah diproses. Setelah seluruh matriks nilai telah diproses, nilai total dari semua elemen matriks (total) dan jumlah total elemen dalam matriks (jumlahData) telah dihitung. Rata-rata dari semua elemen matriks dihitung dengan membagi total nilai dengan jumlah total elemen, yaitu rataRata = total / jumlahData. Nilai rata-rata tersebut kemudian dicetak ke konsol. Program selesai dieksekusi.', '2024-04-01 04:20:38', '2024-04-01 04:20:38', NULL),
(464, 23, 33, 'Dengan elemen array nilai yang baru, yaitu double[][] nilai = {{75, 80, 81}, {90, 95, 90}, {70, 75, 82}} rata-rata nilai yang didapatkan adalah sekitar 82.', '2024-04-01 04:20:44', '2024-04-01 04:20:44', NULL),
(465, 23, 34, 'Kode tampil() pada method main memiliki kegunaan untuk menampilkan informasi terkait luas dan keliling lingkaran ke konsol.', '2024-04-01 04:23:28', '2024-04-01 04:23:28', NULL),
(466, 23, 35, 'Pertama, sebuah variabel lokal phi diinisialisasi dengan nilai 3.14, yang merupakan nilai phi (π) yang digunakan dalam perhitungan luas dan keliling lingkaran. Selanjutnya, sebuah variabel lokal r diinisialisasi dengan nilai 14, yang merupakan jari-jari lingkaran. Kemudian, dilakukan pemanggilan method luasLingkaran(phi, r) untuk menghitung luas lingkaran. Method ini menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai luas lingkaran. Hasil perhitungan luas lingkaran disimpan dalam variabel lokal luas. Selanjutnya, dilakukan pemanggilan method kelilingLingkaran(phi, r) untuk menghitung keliling lingkaran. Method ini juga menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai keliling lingkaran. Hasil perhitungan keliling lingkaran disimpan dalam variabel lokal keliling. Setelah itu, hasil perhitungan luas dan keliling lingkaran dicetak ke konsol menggunakan System.out.print(). Cetak ini mencakup pesan yang menyatakan luas lingkaran beserta nilai luasnya, diikuti dengan pesan yang menyatakan keliling lingkaran beserta nilai kelilingnya. Jadi, fungsi tampil() bertujuan untuk menghitung luas dan keliling lingkaran dengan menggunakan rumus yang sesuai, dan kemudian menampilkan hasilnya ke konsol.', '2024-04-01 04:23:33', '2024-04-01 04:23:33', NULL),
(467, 23, 36, 'Jika kode tampil() pada method main dihapus, maka program tidak akan menampilkan hasil luas dan keliling lingkaran ke konsol saat program dijalankan. Tanpa pemanggilan method tampil() di dalam method main, maka baris kode yang ada di dalam method tampil() tidak akan dieksekusi. Artinya, perhitungan luas dan keliling lingkaran tetap akan terjadi karena pemanggilan method tampil() pada method main merupakan inisiasi untuk menghitung dan menampilkan luas serta keliling lingkaran. Jadi, jika kode tampil() dihapus, program hanya akan dijalankan tanpa menampilkan hasil luas dan keliling lingkaran ke konsol.', '2024-04-01 04:23:39', '2024-04-01 04:23:39', NULL),
(468, 23, 37, 'Ya, program ini menggunakan rekursi.', '2024-04-01 04:25:42', '2024-04-01 04:25:42', NULL),
(469, 23, 38, 'Parameter Masukan: Method hitungBunga() menerima tiga parameter: saldo (saldo awal), bunga (persentase bunga tahunan), dan tahun (jumlah tahun). Pengecekan Basis: Pertama, method melakukan pengecekan apakah nilai tahun sama dengan 0. Jika ya, artinya kita telah mencapai basis rekursi, dan method akan mengembalikan nilai saldo tanpa menghitung bunga lagi. Ini penting untuk mengakhiri rekursi agar tidak terjadi panggilan rekursif yang tak terbatas. Perhitungan Bunga: Jika nilai tahun tidak sama dengan 0, artinya kita masih dalam tahap rekursi. Di sini, method menghitung bunga tahunan dengan rumus bungaTahunan = saldo * (bunga / 100). Ini menghasilkan jumlah bunga yang akan ditambahkan ke saldo awal. Perhitungan Total Saldo: Setelah menghitung bunga tahunan, method menambahkannya ke saldo awal untuk mendapatkan total saldo setelah satu tahun. Ini dilakukan dengan rumus total = saldo + bungaTahunan. Panggilan Rekursif: Selanjutnya, method hitungBunga() memanggil dirinya sendiri dengan total saldo setelah satu tahun (total) sebagai saldo awal pada panggilan rekursif berikutnya. Parameter lainnya (bunga dan tahun) tetap tidak berubah. Dengan demikian, proses ini akan berulang untuk setiap tahun sampai mencapai basis rekursi. Pengembalian Nilai: Setelah selesai semua panggilan rekursif, nilai saldo akhir setelah jumlah tahun yang ditentukan akan dikembalikan ke pemanggil method.', '2024-04-01 04:25:48', '2024-04-01 04:25:48', NULL),
(470, 23, 39, 'Jika bunga pertahun diganti menjadi 7%, jumlah uang yang dihasilkan setelah 5 tahun adalah sekitar 1.407.165,32.', '2024-04-01 04:25:55', '2024-04-01 04:25:55', NULL),
(471, 24, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-04-01 04:39:19', '2024-04-01 04:39:19', NULL),
(472, 24, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-04-01 04:39:32', '2024-04-01 04:39:32', NULL),
(473, 24, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-04-01 04:39:39', '2024-04-01 04:39:39', NULL),
(474, 24, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-04-01 04:41:02', '2024-04-01 04:41:02', NULL),
(475, 24, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-04-01 04:41:08', '2024-04-01 04:41:08', NULL),
(476, 24, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-04-01 04:41:13', '2024-04-01 04:41:13', NULL),
(477, 24, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-04-01 04:42:32', '2024-04-01 04:42:32', NULL),
(478, 24, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi.', '2024-04-01 04:42:38', '2024-04-01 04:42:38', NULL),
(479, 24, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-04-01 04:42:46', '2024-04-01 04:42:46', NULL),
(480, 24, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-04-01 04:44:02', '2024-04-01 04:44:02', NULL),
(481, 24, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi.', '2024-04-01 04:44:07', '2024-04-01 04:44:07', NULL),
(482, 24, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-04-01 04:44:15', '2024-04-01 04:44:15', NULL);
INSERT INTO `user_answer` (`id`, `user_id`, `essay_question_id`, `answer`, `created_at`, `updated_at`, `deleted_at`) VALUES
(483, 24, 13, 'Variabel isMember bertipe data boolean karena nilainya hanya bisa berupa true atau false, yang sesuai dengan kondisi apakah pelanggan adalah anggota (member) atau bukan. Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-04-01 04:45:29', '2024-04-01 04:45:29', NULL),
(484, 24, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-04-01 04:45:35', '2024-04-01 04:45:35', NULL),
(485, 24, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-04-01 04:45:40', '2024-04-01 04:45:40', NULL),
(486, 24, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i. Lebih tepatnya, itu adalah ekspresi increment yang bertugas untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-04-01 04:46:41', '2024-04-01 04:46:41', NULL),
(487, 24, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-04-01 04:46:47', '2024-04-01 04:46:47', NULL),
(488, 24, 18, 'Jika nilai dari variabel number adalah 8, maka program akan mencetak angka dari 1 hingga 7. Ini disebabkan oleh kondisi perulangan for, di mana i akan mulai dari 1 dan berakhir pada 7 (karena 7 kurang dari 8), sementara perulangan akan berhenti sebelum mencapai 8. Jadi, output dari program akan menjadi 1234567', '2024-04-01 04:46:54', '2024-04-01 04:46:54', NULL),
(489, 24, 19, 'Pada kode program di atas, i++ memiliki kegunaan yang sama dengan pada contoh sebelumnya yang menggunakan perulangan for. Di dalam perulangan while, i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-04-01 04:47:59', '2024-04-01 04:47:59', NULL),
(490, 24, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-04-01 04:48:05', '2024-04-01 04:48:05', NULL),
(491, 24, 21, 'Jika kondisi dalam while diganti menjadi while(i > number), maka loop while tidak akan pernah dieksekusi. Hal ini karena pada saat inisialisasi variabel i memiliki nilai 1, sedangkan nilai variabel number adalah 6. Kondisi i > number (1 > 6) tidak terpenuhi, sehingga blok pernyataan di dalam while tidak akan dieksekusi sama sekali. Sehingga, tidak ada output yang akan dikeluarkan oleh program dalam kasus ini. Program akan selesai tanpa mencetak apa pun ke konsol.', '2024-04-01 04:48:11', '2024-04-01 04:48:11', NULL),
(492, 24, 22, 'Baris kode int next = first + second; berfungsi untuk menghitung nilai selanjutnya dalam deret Fibonacci. Dalam deret Fibonacci, setiap angka adalah hasil penjumlahan dari dua angka sebelumnya. Oleh karena itu, next dihitung dengan menambahkan nilai first (angka sebelumnya dalam deret) dengan nilai second (angka sebelumnya dari first). Dengan melakukan operasi first + second, nilai next akan menjadi angka berikutnya dalam deret Fibonacci setelah first dan second. Kemudian, nilai-nilai variabel first dan second akan diperbarui untuk mempersiapkan perhitungan angka berikutnya dalam deret Fibonacci.', '2024-04-01 04:50:58', '2024-04-01 04:50:58', NULL),
(493, 24, 23, 'Program memasuki blok kode do-while. Pertama-tama, variabel n diinisialisasi dengan nilai 6, yang menunjukkan bahwa kita akan mencetak deret Fibonacci hingga indeks ke-6. Variabel first diinisialisasi dengan nilai 0, dan second diinisialisasi dengan nilai 1. Ini adalah dua angka awal dalam deret Fibonacci. Variabel i diinisialisasi dengan nilai 1, yang akan digunakan untuk menghitung jumlah iterasi dalam perulangan. String \"Deret Fibonacci: \\n\" dicetak ke konsol untuk memberikan label pada deret Fibonacci yang akan dicetak. Angka pertama dan kedua dalam deret Fibonacci (0 dan 1) dicetak ke konsol. Program masuk ke dalam blok pernyataan do-while. Di dalam blok do-while, angka berikutnya dalam deret Fibonacci dihitung dengan menjumlahkan nilai first dan second, dan hasilnya disimpan dalam variabel next. Nilai next dicetak ke konsol. Nilai variabel first diperbarui dengan nilai variabel second, yang berarti angka sebelumnya dalam deret Fibonacci menjadi nilai second saat ini. Nilai variabel second diperbarui dengan nilai next, yang merupakan angka berikutnya dalam deret Fibonacci. Variabel i (penghitung iterasi) ditambah 1. Program mengevaluasi kondisi i <= n. Jika kondisi terpenuhi, program akan kembali ke langkah 8 untuk menghitung dan mencetak angka berikutnya dalam deret Fibonacci. Proses ini berlanjut sampai nilai i melebihi nilai n. Setelah itu, program keluar dari blok perulangan do-while. Program selesai dieksekusi.', '2024-04-01 04:51:05', '2024-04-01 04:51:05', NULL),
(494, 24, 24, 'Jika nilai variabel n diganti menjadi 7, maka program akan mencetak deret Fibonacci hingga indeks ke-7 sehingga hasilnya 0 1 1 2 3 5 8', '2024-04-01 04:51:12', '2024-04-01 04:51:12', NULL),
(495, 24, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) menentukan berapa kali perulangan akan dieksekusi. Dalam kasus ini, kondisi tersebut berarti perulangan akan dieksekusi ketika nilai i kurang dari atau sama dengan 5. Jadi, fungsi dari kondisi i <= 5 adalah untuk mengontrol jumlah baris dalam pola bintang yang dibuat oleh piramid. Dengan kondisi tersebut, perulangan akan dieksekusi sebanyak lima kali, menghasilkan lima baris pada pola bintang. Pada setiap iterasi, jumlah bintang yang dicetak pada setiap baris akan sesuai dengan nilai i pada saat itu. Sehingga, pada iterasi pertama, hanya satu bintang yang dicetak, pada iterasi kedua dua bintang, dan seterusnya hingga iterasi kelima.', '2024-04-01 04:52:34', '2024-04-01 04:52:34', NULL),
(496, 24, 26, 'Setiap kali iterasi dari perulangan pertama (outer loop) dieksekusi, variabel i akan bertambah satu dari nilai awal 1 hingga mencapai 5, sesuai dengan kondisi i <= 5. Di dalam setiap iterasi dari perulangan pertama, perulangan kedua (inner loop) akan dieksekusi. Pada awal iterasi dari perulangan kedua, variabel j akan diinisialisasi dengan nilai awal 1. Kondisi perulangan kedua, j <= i, menentukan berapa kali perulangan ini akan dieksekusi. Pada setiap iterasi, jumlah bintang yang dicetak akan sesuai dengan nilai i pada saat itu. Pada iterasi pertama dari perulangan pertama (ketika i adalah 1), perulangan kedua akan dieksekusi satu kali (karena j kurang dari atau sama dengan 1). Pada iterasi kedua dari perulangan pertama (ketika i adalah 2), perulangan kedua akan dieksekusi dua kali (karena j kurang dari atau sama dengan 2). Hal ini berlanjut hingga iterasi kelima dari perulangan pertama, di mana perulangan kedua akan dieksekusi sebanyak lima kali (karena j kurang dari atau sama dengan 5). Di dalam blok perulangan kedua, bintang (*) akan ditambahkan ke variabel output pada setiap iterasi. Setelah perulangan kedua selesai dieksekusi untuk nilai i tertentu, baris baru (\\n) akan ditambahkan ke variabel output, sehingga bintang-bintang yang tercetak membentuk pola piramida. Proses ini akan terus berlanjut hingga iterasi dari perulangan pertama selesai, dan hasil akhirnya, output akan dicetak ke konsol. Dengan demikian, alur program dari perulangan kedua menggunakan variabel j adalah untuk menambahkan bintang ke dalam variabel output sesuai dengan jumlah iterasi yang sesuai dengan nilai i pada saat itu, yang menghasilkan pola piramida dari bintang', '2024-04-01 04:52:52', '2024-04-01 04:52:52', NULL),
(497, 24, 27, 'Jika kondisi i <= 5 pada perulangan pertama (outer loop) diganti menjadi i <= 6, maka perulangan akan dieksekusi lebih dari sebelumnya, yaitu sebanyak enam kali. Ini berarti akan ada enam baris dalam pola bintang yang dihasilkan.', '2024-04-01 04:53:00', '2024-04-01 04:53:00', NULL),
(498, 24, 28, 'String topicArray = Arrays.toString(topics);', '2024-04-01 04:54:11', '2024-04-01 04:54:11', NULL),
(499, 24, 29, 'Sebuah array topics yang berisi beberapa topik (dalam bentuk string) dideklarasikan dan diinisialisasi dengan nilai: {\"Opinion\", \"Tech\", \"Science\", \"Health\"}. Kemudian, dilakukan pemanggilan metode Arrays.toString() untuk mengonversi array topics menjadi sebuah string. Hasil dari konversi tersebut disimpan dalam variabel topicArray. Terakhir, string yang berisi representasi dari array topics disimpan dalam variabel topicArray tersebut. String yang berisi representasi dari array topics, yang sekarang disimpan dalam variabel topicArray, dicetak ke konsol menggunakan System.out.print(topicArray)', '2024-04-01 04:54:20', '2024-04-01 04:54:20', NULL),
(500, 24, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1, 2, 3, 4};, maka kode program akan menghasilkan kesalahan pada saat kompilasi. Hal ini disebabkan oleh perbedaan tipe data antara elemen-elemen array dengan tipe data yang diharapkan, yaitu string. Kode String[] topics = {1, 2, 3, 4}; mencoba untuk membuat array topics yang berisi nilai-nilai bertipe int, namun karena kita mendeklarasikan tipe array sebagai String[], maka ini akan menyebabkan kesalahan kompilasi. Jadi, output program tidak akan dihasilkan karena kesalahan kompilasi yang terjadi. Sebelum kita dapat mencetak array tersebut, kita perlu memastikan bahwa elemen-elemen array memiliki tipe data yang sesuai dengan deklarasi array. Dalam kasus ini, kita harus mengubah elemen-elemen array menjadi string, misalnya String[] topics = {\"1\", \"2\", \"3\", \"4\"};.', '2024-04-01 04:54:27', '2024-04-01 04:54:27', NULL),
(501, 24, 31, 'Pada kode i < nilai.length; pada perulangan pertama, nilai.length mengembalikan panjang (jumlah elemen) dari array dua dimensi nilai dalam dimensi pertama, yaitu jumlah baris dari matriks nilai. Jadi, fungsi dari kondisi i < nilai.length; adalah untuk memastikan bahwa iterasi dalam perulangan pertama akan terjadi sebanyak jumlah baris dalam matriks nilai. Dalam konteks ini, i digunakan sebagai indeks baris dari matriks nilai. Jadi, perulangan akan berlangsung dari baris pertama hingga baris terakhir dari matriks nilai. Pada setiap iterasi, blok pernyataan dalam perulangan akan dieksekusi untuk setiap baris dalam matriks nilai. Jadi, i < nilai.length; memastikan bahwa perulangan pertama akan berjalan sesuai dengan jumlah baris dalam matriks nilai, yang memungkinkan program untuk melakukan operasi pada setiap elemen dari matriks tersebut.', '2024-04-01 04:56:49', '2024-04-01 04:56:49', NULL),
(502, 24, 32, 'Perulangan kedua dimulai dengan inisialisasi variabel j dengan nilai 0. Kemudian, dilakukan pengecekan kondisi j < nilai[i].length, di mana nilai[i].length mengembalikan panjang (jumlah elemen) dari array yang berada pada baris ke-i dalam matriks nilai. Dalam konteks ini, ini mengacu pada jumlah elemen (atau jumlah kolom) dari baris ke-i dari matriks nilai. Jika kondisi j < nilai[i].length benar (true), blok pernyataan dalam perulangan kedua dieksekusi. Di dalam blok perulangan kedua, setiap elemen dari baris ke-i dalam matriks nilai diakses menggunakan nilai[i][j]. Nilai tersebut ditambahkan ke variabel total. Selanjutnya, variabel jumlahData (yang digunakan untuk menghitung total jumlah elemen dalam matriks) ditambah satu untuk setiap elemen yang dihitung. Setelah iterasi dalam perulangan kedua selesai, nilai j diperbarui dengan j++, sehingga memungkinkan iterasi ke elemen berikutnya dari baris yang sama. Proses di atas diulangi hingga kondisi j < nilai[i].length tidak lagi terpenuhi. Setelah semua elemen dari baris ke-i telah dihitung, kontrol kembali ke perulangan pertama, di mana nilai i diperbarui, dan proses di atas diulangi untuk baris berikutnya dari matriks nilai. Proses ini berlanjut hingga semua baris dari matriks nilai telah diproses. Setelah seluruh matriks nilai telah diproses, nilai total dari semua elemen matriks (total) dan jumlah total elemen dalam matriks (jumlahData) telah dihitung. Rata-rata dari semua elemen matriks dihitung dengan membagi total nilai dengan jumlah total elemen, yaitu rataRata = total / jumlahData. Nilai rata-rata tersebut kemudian dicetak ke konsol. Program selesai dieksekusi.', '2024-04-01 04:56:56', '2024-04-01 04:56:56', NULL),
(503, 24, 33, 'Dengan elemen array nilai yang baru, yaitu double[][] nilai = {{75, 80, 81}, {90, 95, 90}, {70, 75, 82}} rata-rata nilai yang didapatkan adalah sekitar 82.', '2024-04-01 04:57:02', '2024-04-01 04:57:02', NULL),
(504, 24, 34, 'Kode tampil() pada method main memiliki kegunaan untuk menampilkan informasi terkait luas dan keliling lingkaran ke konsol.', '2024-04-01 05:00:15', '2024-04-01 05:00:15', NULL),
(505, 24, 35, 'Pertama, sebuah variabel lokal phi diinisialisasi dengan nilai 3.14, yang merupakan nilai phi (π) yang digunakan dalam perhitungan luas dan keliling lingkaran. Selanjutnya, sebuah variabel lokal r diinisialisasi dengan nilai 14, yang merupakan jari-jari lingkaran. Kemudian, dilakukan pemanggilan method luasLingkaran(phi, r) untuk menghitung luas lingkaran. Method ini menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai luas lingkaran. Hasil perhitungan luas lingkaran disimpan dalam variabel lokal luas. Selanjutnya, dilakukan pemanggilan method kelilingLingkaran(phi, r) untuk menghitung keliling lingkaran. Method ini juga menerima dua argumen, yaitu nilai phi (π) dan jari-jari lingkaran (r), dan mengembalikan nilai keliling lingkaran. Hasil perhitungan keliling lingkaran disimpan dalam variabel lokal keliling. Setelah itu, hasil perhitungan luas dan keliling lingkaran dicetak ke konsol menggunakan System.out.print(). Cetak ini mencakup pesan yang menyatakan luas lingkaran beserta nilai luasnya, diikuti dengan pesan yang menyatakan keliling lingkaran beserta nilai kelilingnya. Jadi, fungsi tampil() bertujuan untuk menghitung luas dan keliling lingkaran dengan menggunakan rumus yang sesuai, dan kemudian menampilkan hasilnya ke konsol.', '2024-04-01 05:00:21', '2024-04-01 05:00:21', NULL),
(506, 24, 36, 'Jika kode tampil() pada method main dihapus, maka program tidak akan menampilkan hasil luas dan keliling lingkaran ke konsol saat program dijalankan. Tanpa pemanggilan method tampil() di dalam method main, maka baris kode yang ada di dalam method tampil() tidak akan dieksekusi. Artinya, perhitungan luas dan keliling lingkaran tetap akan terjadi karena pemanggilan method tampil() pada method main merupakan inisiasi untuk menghitung dan menampilkan luas serta keliling lingkaran. Jadi, jika kode tampil() dihapus, program hanya akan dijalankan tanpa menampilkan hasil luas dan keliling lingkaran ke konsol.', '2024-04-01 05:00:27', '2024-04-01 05:00:27', NULL),
(507, 24, 37, 'Ya, program ini menggunakan rekursi.', '2024-04-01 05:01:30', '2024-04-01 05:01:30', NULL),
(508, 24, 38, 'Parameter Masukan: Method hitungBunga() menerima tiga parameter: saldo (saldo awal), bunga (persentase bunga tahunan), dan tahun (jumlah tahun). Pengecekan Basis: Pertama, method melakukan pengecekan apakah nilai tahun sama dengan 0. Jika ya, artinya kita telah mencapai basis rekursi, dan method akan mengembalikan nilai saldo tanpa menghitung bunga lagi. Ini penting untuk mengakhiri rekursi agar tidak terjadi panggilan rekursif yang tak terbatas. Perhitungan Bunga: Jika nilai tahun tidak sama dengan 0, artinya kita masih dalam tahap rekursi. Di sini, method menghitung bunga tahunan dengan rumus bungaTahunan = saldo * (bunga / 100). Ini menghasilkan jumlah bunga yang akan ditambahkan ke saldo awal. Perhitungan Total Saldo: Setelah menghitung bunga tahunan, method menambahkannya ke saldo awal untuk mendapatkan total saldo setelah satu tahun. Ini dilakukan dengan rumus total = saldo + bungaTahunan. Panggilan Rekursif: Selanjutnya, method hitungBunga() memanggil dirinya sendiri dengan total saldo setelah satu tahun (total) sebagai saldo awal pada panggilan rekursif berikutnya. Parameter lainnya (bunga dan tahun) tetap tidak berubah. Dengan demikian, proses ini akan berulang untuk setiap tahun sampai mencapai basis rekursi. Pengembalian Nilai: Setelah selesai semua panggilan rekursif, nilai saldo akhir setelah jumlah tahun yang ditentukan akan dikembalikan ke pemanggil method.', '2024-04-01 05:01:37', '2024-04-01 05:01:37', NULL),
(509, 24, 39, 'Jika bunga pertahun diganti menjadi 7%, jumlah uang yang dihasilkan setelah 5 tahun adalah sekitar 1.407.165,32.', '2024-04-01 05:01:45', '2024-04-01 05:01:45', NULL),
(510, 6, 19, 'Pada kode program yang diberikan, i++ digunakan sebagai operator peningkatan nilai variabel i. Lebih tepatnya, i++ adalah bentuk singkat dari i = i + 1, yang berarti setiap kali loop while dijalankan, nilai dari i akan bertambah 1.\n\nDalam konteks ini, i digunakan sebagai iterator atau penghitung loop. Loop while akan terus dijalankan selama nilai i kurang dari number. Dengan menggunakan i++, nilai i akan terus bertambah setiap kali loop dijalankan, sehingga memungkinkan loop untuk berakhir saat nilai i sama dengan number.', '2024-04-07 10:37:45', '2024-04-07 10:37:45', NULL),
(511, 6, 20, 'Variabel number diinisialisasi dengan nilai 6.\nVariabel i diinisialisasi dengan nilai 1.\nPengecekan kondisi while dilakukan: apakah nilai i kurang dari number?\nKarena nilai i saat ini adalah 1 dan number adalah 6, maka kondisi tersebut terpenuhi, dan program memasuki blok while.\nDi dalam blok while, System.out.print(i) akan mencetak nilai i, yang saat ini bernilai 1.\nSetelah mencetak nilai i, i akan ditambah 1 dengan menggunakan i++.\nKontrol kembali ke atas while, dan kondisi diuji lagi. Karena nilai i sekarang adalah 2 dan masih kurang dari number, proses ini terus berlanjut.\nLangkah 5-7 diulangi hingga nilai i mencapai 6.\nKetika nilai i menjadi 6, kondisi while tidak terpenuhi karena nilai i tidak lagi kurang dari number (karena sekarang sama dengan number).\nProgram keluar dari blok while dan selesai di sini. Tidak ada lagi instruksi yang dijalankan setelah blok while karena tidak ada kode setelahnya.', '2024-04-07 10:37:58', '2024-04-07 10:37:58', NULL),
(512, 6, 21, 'Jika kondisi dalam while diganti menjadi while (i > number), maka program tidak akan memasuki blok while sama sekali. Ini karena saat inisialisasi, nilai i adalah 1 dan nilai number adalah 6. Oleh karena itu, i tidak pernah akan lebih besar dari number dengan kondisi tersebut.\n\nDalam kasus ini, tidak akan ada output yang dihasilkan oleh program, dan program akan selesai tanpa mencetak apapun ke layar. Karena blok while tidak akan pernah dieksekusi dengan kondisi while (i > number), program akan langsung melanjutkan ke instruksi di luar blok while (jika ada) atau selesai jika tidak ada instruksi lain.', '2024-04-07 10:38:05', '2024-04-07 10:38:05', NULL),
(513, 25, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-04-16 17:15:45', '2024-04-16 17:15:45', NULL),
(514, 25, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-04-16 17:15:54', '2024-04-16 17:15:54', NULL),
(515, 25, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-04-16 17:15:58', '2024-04-16 17:15:58', NULL),
(516, 25, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-04-16 17:17:42', '2024-04-16 17:17:42', NULL),
(517, 25, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-04-16 17:17:49', '2024-04-16 17:17:49', NULL),
(518, 25, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-04-16 17:17:52', '2024-04-16 17:17:52', NULL),
(519, 25, 7, 'Penggunaan if-else pada baris kode tersebut adalah untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-04-16 17:47:13', '2024-04-16 17:47:13', NULL),
(520, 25, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi', '2024-04-16 17:47:18', '2024-04-16 17:47:18', NULL),
(521, 25, 9, 'Jika nilai variabel \"itemCost\" adalah 20, maka output program akan menampilkan pesan \"Low Value Item!\". Hal ini karena nilai variabel \"itemCost\" (20) tidak memenuhi kondisi if, sehingga blok else akan dieksekusi, dan pesan \"Low Value Item!\" akan ditampilkan.', '2024-04-16 17:47:21', '2024-04-16 17:47:21', NULL),
(522, 25, 10, 'Fungsi dari baris program default adalah sebagai bagian dari struktur switch case di Java. Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-04-23 18:55:07', '2024-04-23 18:55:07', NULL),
(523, 25, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi', '2024-04-23 18:55:29', '2024-04-23 18:55:29', NULL),
(524, 25, 12, 'Variabel shippingCost akan bernilai 0.50 saat nilai variabel shipping tidak cocok dengan nilai dari case manapun dalam struktur switch-case, dan blok default dieksekusi.', '2024-04-23 18:55:42', '2024-04-23 18:55:42', NULL),
(525, 26, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-04-26 13:27:52', '2024-04-26 13:27:52', NULL),
(526, 26, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-04-26 13:28:00', '2024-04-26 13:28:00', NULL),
(527, 26, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-04-26 13:28:05', '2024-04-26 13:28:05', NULL),
(528, 26, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-04-26 13:49:38', '2024-04-26 13:49:38', NULL),
(529, 26, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-04-26 13:49:41', '2024-04-26 13:49:41', NULL),
(530, 26, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-04-26 13:49:48', '2024-04-26 13:49:48', NULL),
(531, 26, 7, 'Untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-04-26 20:45:25', '2024-04-26 20:45:25', NULL),
(532, 26, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi', '2024-04-26 20:45:38', '2024-04-26 20:45:38', NULL),
(533, 26, 9, 'Output program akan menampilkan pesan \"Low Value Item!\".', '2024-04-26 20:45:49', '2024-04-26 20:45:49', NULL),
(534, 26, 10, 'Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-04-26 21:05:21', '2024-04-26 21:05:21', NULL),
(535, 26, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi', '2024-04-26 21:05:33', '2024-04-26 21:05:33', NULL),
(536, 26, 12, 'Saat nilai shipping tidak bernilai regular maupun express, sehingga default case dieksekusi.', '2024-04-26 21:05:43', '2024-04-26 21:05:43', NULL),
(537, 26, 13, 'Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-04-26 21:19:22', '2024-04-26 21:19:22', NULL),
(538, 26, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-04-26 21:19:29', '2024-04-26 21:19:29', NULL),
(539, 26, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-04-26 21:19:40', '2024-04-26 21:19:40', NULL),
(540, 26, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i.  itu adalah ekspresi increment untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-04-26 21:34:42', '2024-04-26 21:34:42', NULL),
(541, 26, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-04-26 21:34:51', '2024-04-26 21:34:51', NULL),
(542, 26, 18, '1234567', '2024-04-26 21:35:03', '2024-04-26 21:35:03', NULL),
(543, 26, 19, 'i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-04-26 21:49:25', '2024-04-26 21:49:25', NULL),
(544, 26, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-04-26 21:49:36', '2024-04-26 21:49:36', NULL),
(545, 26, 21, 'Tidak ada output yang akan dikeluarkan oleh program dalam kasus ini.', '2024-04-26 21:49:49', '2024-04-26 21:49:49', NULL),
(546, 26, 22, 'Baris kode \"int next = first + second\" berfungsi untuk mengalikan nilai dari variabel first dan second.', '2024-04-26 23:31:57', '2024-04-26 23:31:57', NULL),
(547, 26, 23, '1. Inisialisasi variabel n dengan nilai 6, first dengan 0, second dengan 1, dan i dengan 1.\n2. Cetak teks \"Deret Fibonacci:\".\n3. Cetak nilai first dan second.\n4. Masuk ke dalam loop do-while.\n5. Di dalam loop, hitung nilai next dengan menjumlahkan nilai first dan second.\n6. Cetak nilai next.\n7. Perbarui nilai first dengan nilai second, dan nilai second dengan nilai next.\n8. Tingkatkan nilai i sebanyak 1.\n9. Ulangi langkah 5-8 selama nilai i kurang dari atau sama dengan n.', '2024-04-26 23:32:11', '2024-04-26 23:32:11', NULL),
(548, 26, 24, '0 1 1 2 3 5 8 13', '2024-04-26 23:32:19', '2024-04-26 23:32:19', NULL),
(549, 26, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) bertujuan untuk memastikan bahwa loop akan berjalan dari baris kelima hingga baris ke-i', '2024-04-26 23:53:24', '2024-04-26 23:53:24', NULL),
(550, 26, 26, 'Dalam perulangan kedua (inner loop) yang menggunakan variabel j, program ini sebenarnya mencetak bintang (*) sebanyak dua kali lipat dari nilai variabel i. Jadi, pada setiap iterasi dari perulangan luar (yang diatur oleh variabel i), perulangan dalam (yang diatur oleh variabel j) akan mencetak bintang sebanyak dua kali lipat dari nilai i saat itu. Misalnya, pada baris pertama (ketika i = 1), program akan mencetak dua bintang. Pada baris kedua (ketika i = 2), program akan mencetak empat bintang, dan seterusnya. Sehingga, outputnya akan menjadi seperti pola segitiga dengan tinggi lima baris, di mana jumlah bintang pada setiap baris adalah dua kali lipat dari nomor baris saat itu.', '2024-04-26 23:53:28', '2024-04-26 23:53:28', NULL),
(551, 26, 27, '*\n**\n***\n****\n*****\n******\n*******', '2024-04-26 23:53:36', '2024-04-26 23:53:36', NULL),
(552, 26, 28, 'System.out.print(topicArray);', '2024-04-27 00:25:17', '2024-04-27 00:25:17', NULL),
(553, 26, 29, 'Program dimulai dengan mendeklarasikan array topics yang berisi empat string: \"Opinion\", \"Tech\", \"Science\", dan \"Health\".\nSelanjutnya, kita menggunakan metode Arrays.toString(topics) untuk mengubah array tersebut menjadi sebuah string.\nHasil dari langkah kedua, yaitu string yang berisi representasi dari array topics, disimpan ke dalam variabel topicArray.\nKemudian, kita mencetak isi dari topicArray menggunakan System.out.print(topicArray).', '2024-04-27 00:25:20', '2024-04-27 00:25:20', NULL),
(554, 26, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1,2,3,4};, maka output yang dihasilkan program akan menjadi: [1, 2, 3, 4]\nIni disebabkan oleh penggunaan Arrays.toString(topics), yang mengonversi array topics menjadi representasi string. Meskipun elemen-elemen array diinisialisasi sebagai integer, Java akan secara otomatis mengonversi mereka menjadi string dalam representasi yang sesuai untuk mencetak array. Sehingga, meskipun elemen array sebelumnya adalah string, hasilnya akan tetap sama.', '2024-04-27 00:25:25', '2024-04-27 00:25:25', NULL),
(555, 26, 31, 'Mengeksekusi perulangan sebanyak nilai.length', '2024-04-27 00:41:20', '2024-04-27 00:41:20', NULL),
(556, 26, 32, 'loop ini bertugas untuk mengakses setiap nilai dalam baris ke-i dari array nilai. Variabel j kemudian digunakan untuk mengakses setiap nilai secara berurutan dalam baris tersebut. Nilai-nilai ini kemudian dijumlahkan ke dalam variabel total, sementara jumlahData diinkrementasi untuk merekam jumlah nilai yang telah diakses.', '2024-04-27 00:41:26', '2024-04-27 00:41:26', NULL),
(557, 26, 33, '70', '2024-04-27 00:41:32', '2024-04-27 00:41:32', NULL),
(558, 26, 34, 'Metode tampil() dalam metode main berfungsi untuk menghitung luas dan keliling lingkaran, tetapi tidak melakukan tindakan apa pun setelahnya. Sehingga, memanggil tampil() tidak memberikan hasil yang ditampilkan.', '2024-04-27 00:59:38', '2024-04-27 00:59:38', NULL),
(559, 26, 35, 'pada urutan penggunaan fungsi luasLingkaran() dan kelilingLingkaran(), yang mungkin memberikan kesan bahwa ada hubungan urutan yang penting dalam menghitung luas dan keliling lingkaran. Namun, sebenarnya tidak ada hubungan urutan yang penting antara keduanya, karena keduanya hanya melakukan perhitungan berdasarkan parameter yang diberikan.', '2024-04-27 00:59:42', '2024-04-27 00:59:42', NULL),
(560, 26, 36, 'Hasil akan tetap menampilkan Luas Lingkaran pada fungsi public static void tampil()', '2024-04-27 00:59:46', '2024-04-27 00:59:46', NULL),
(561, 26, 37, 'Program ini sebenarnya tidak menggunakan rekursi. Meskipun terdapat pemanggilan fungsi hitungBunga() di dalam dirinya sendiri, itu tidak terjadi secara rekursif.\n\nPemanggilan fungsi hitungBunga() di dalam blok else adalah bagian dari pendekatan iteratif. Fungsi ini dipanggil secara berulang dengan argumen yang berbeda hingga mencapai kondisi dasar (tahun == 0), namun tidak menggunakan rekursi karena tidak ada \"pemanggilan balik\" dari fungsi tersebut ke dirinya sendiri secara eksplisit. Sehingga, program ini tidak menggunakan rekursi', '2024-04-27 01:18:30', '2024-04-27 01:18:30', NULL),
(562, 26, 38, 'Pertama, program memeriksa apakah variabel tahun sama dengan 0. Jika ya, itu berarti perhitungan bunga telah selesai, dan fungsi akan mengembalikan nilai saldo tanpa melakukan perhitungan tambahan.\nJika kondisi pada langkah sebelumnya tidak terpenuhi, maka program akan melanjutkan ke blok else. Di dalam blok else, program akan menghitung bunga tahunan dengan rumus saldo * (bunga / 100). Namun, ini adalah kesalahan karena seharusnya kita harus membagi bunga dengan jumlah tahun, bukan dengan 100.\nSetelah itu, program akan menghitung total saldo dengan menambahkan saldo awal dengan bunga tahunan. Namun, dalam penjelasan yang salah ini, kita dapat mengatakan bahwa total saldo dihitung dengan membagi saldo dengan bunga, yang tentu saja tidak benar.\nTerakhir, program akan memanggil fungsi hitungBunga() secara rekursif dengan nilai total saldo sebagai saldo baru, bunga yang sama, dan tahun yang berkurang satu. Ini akan terus berulang hingga kondisi tahun == 0 terpenuhi, dan saldo akhir akan dikembalikan.', '2024-04-27 01:18:34', '2024-04-27 01:18:34', NULL),
(563, 26, 39, '1407107.324173', '2024-04-27 01:18:38', '2024-04-27 01:18:38', NULL),
(564, 27, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-04-27 05:49:46', '2024-04-27 05:49:46', NULL),
(565, 27, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-04-27 05:50:01', '2024-04-27 05:50:01', NULL),
(566, 27, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-04-27 05:50:10', '2024-04-27 05:50:10', NULL),
(567, 27, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-04-27 05:59:07', '2024-04-27 05:59:07', NULL),
(568, 27, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-04-27 05:59:15', '2024-04-27 05:59:15', NULL),
(569, 27, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-04-27 05:59:24', '2024-04-27 05:59:24', NULL),
(570, 27, 7, 'Untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-04-27 06:08:16', '2024-04-27 06:08:16', NULL),
(571, 27, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi', '2024-04-27 06:08:22', '2024-04-27 06:08:22', NULL),
(572, 27, 9, 'Output program akan menampilkan pesan \"Low Value Item!\".', '2024-04-27 06:08:32', '2024-04-27 06:08:32', NULL),
(573, 27, 10, 'Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-04-27 06:18:53', '2024-04-27 06:18:53', NULL),
(574, 27, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi', '2024-04-27 06:19:01', '2024-04-27 06:19:01', NULL),
(575, 27, 12, 'Saat nilai shipping tidak bernilai regular maupun express, sehingga default case dieksekusi.', '2024-04-27 06:19:09', '2024-04-27 06:19:09', NULL),
(576, 27, 13, 'Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-04-27 06:27:43', '2024-04-27 06:27:43', NULL),
(577, 27, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-04-27 06:27:50', '2024-04-27 06:27:50', NULL),
(578, 27, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-04-27 06:28:00', '2024-04-27 06:28:00', NULL),
(579, 27, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i.  itu adalah ekspresi increment untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-04-27 06:36:03', '2024-04-27 06:36:03', NULL);
INSERT INTO `user_answer` (`id`, `user_id`, `essay_question_id`, `answer`, `created_at`, `updated_at`, `deleted_at`) VALUES
(580, 27, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-04-27 06:36:11', '2024-04-27 06:36:11', NULL),
(581, 27, 18, '1234567', '2024-04-27 06:36:18', '2024-04-27 06:36:18', NULL),
(582, 27, 19, 'i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-04-27 06:46:48', '2024-04-27 06:46:48', NULL),
(583, 27, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-04-27 06:46:55', '2024-04-27 06:46:55', NULL),
(584, 27, 21, 'Tidak ada output yang akan dikeluarkan oleh program dalam kasus ini.', '2024-04-27 06:47:05', '2024-04-27 06:47:05', NULL),
(585, 27, 22, 'Baris kode \"int next = first + second\" berfungsi untuk mengalikan nilai dari variabel first dan second.', '2024-04-27 06:58:37', '2024-04-27 06:58:37', NULL),
(586, 27, 23, '1. Inisialisasi variabel n dengan nilai 6, first dengan 0, second dengan 1, dan i dengan 1.\n2. Cetak teks \"Deret Fibonacci:\".\n3. Cetak nilai first dan second.\n4. Masuk ke dalam loop do-while.\n5. Di dalam loop, hitung nilai next dengan menjumlahkan nilai first dan second.\n6. Cetak nilai next.\n7. Perbarui nilai first dengan nilai second, dan nilai second dengan nilai next.\n8. Tingkatkan nilai i sebanyak 1.\n9. Ulangi langkah 5-8 selama nilai i kurang dari atau sama dengan n.', '2024-04-27 06:58:46', '2024-04-27 06:58:46', NULL),
(587, 27, 24, '0 1 1 2 3 5 8 13', '2024-04-27 06:58:57', '2024-04-27 06:58:57', NULL),
(588, 27, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) bertujuan untuk memastikan bahwa loop akan berjalan dari baris kelima hingga baris ke-i', '2024-04-27 07:08:10', '2024-04-27 07:08:10', NULL),
(589, 27, 26, 'Dalam perulangan kedua (inner loop) yang menggunakan variabel j, program ini sebenarnya mencetak bintang (*) sebanyak dua kali lipat dari nilai variabel i. Jadi, pada setiap iterasi dari perulangan luar (yang diatur oleh variabel i), perulangan dalam (yang diatur oleh variabel j) akan mencetak bintang sebanyak dua kali lipat dari nilai i saat itu. Misalnya, pada baris pertama (ketika i = 1), program akan mencetak dua bintang. Pada baris kedua (ketika i = 2), program akan mencetak empat bintang, dan seterusnya. Sehingga, outputnya akan menjadi seperti pola segitiga dengan tinggi lima baris, di mana jumlah bintang pada setiap baris adalah dua kali lipat dari nomor baris saat itu.', '2024-04-27 07:08:16', '2024-04-27 07:08:16', NULL),
(590, 27, 27, '*\n**\n***\n****\n*****\n******\n*******', '2024-04-27 07:08:24', '2024-04-27 07:08:24', NULL),
(591, 27, 28, 'System.out.print(topicArray);', '2024-04-27 07:20:20', '2024-04-27 07:20:20', NULL),
(592, 27, 29, 'Program dimulai dengan mendeklarasikan array topics yang berisi empat string: \"Opinion\", \"Tech\", \"Science\", dan \"Health\".\nSelanjutnya, kita menggunakan metode Arrays.toString(topics) untuk mengubah array tersebut menjadi sebuah string.\nHasil dari langkah kedua, yaitu string yang berisi representasi dari array topics, disimpan ke dalam variabel topicArray.\nKemudian, kita mencetak isi dari topicArray menggunakan System.out.print(topicArray).', '2024-04-27 07:20:26', '2024-04-27 07:20:26', NULL),
(593, 27, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1,2,3,4};, maka output yang dihasilkan program akan menjadi: [1, 2, 3, 4]\nIni disebabkan oleh penggunaan Arrays.toString(topics), yang mengonversi array topics menjadi representasi string. Meskipun elemen-elemen array diinisialisasi sebagai integer, Java akan secara otomatis mengonversi mereka menjadi string dalam representasi yang sesuai untuk mencetak array. Sehingga, meskipun elemen array sebelumnya adalah string, hasilnya akan tetap sama.', '2024-04-27 07:20:32', '2024-04-27 07:20:32', NULL),
(594, 27, 31, 'Mengeksekusi perulangan sebanyak nilai.length', '2024-04-27 07:29:18', '2024-04-27 07:29:18', NULL),
(595, 27, 32, 'loop ini bertugas untuk mengakses setiap nilai dalam baris ke-i dari array nilai. Variabel j kemudian digunakan untuk mengakses setiap nilai secara berurutan dalam baris tersebut. Nilai-nilai ini kemudian dijumlahkan ke dalam variabel total, sementara jumlahData diinkrementasi untuk merekam jumlah nilai yang telah diakses.', '2024-04-27 07:29:26', '2024-04-27 07:29:26', NULL),
(596, 27, 33, '70', '2024-04-27 07:29:31', '2024-04-27 07:29:31', NULL),
(597, 27, 34, 'Metode tampil() dalam metode main berfungsi untuk menghitung luas dan keliling lingkaran, tetapi tidak melakukan tindakan apa pun setelahnya. Sehingga, memanggil tampil() tidak memberikan hasil yang ditampilkan.', '2024-04-27 07:39:28', '2024-04-27 07:39:28', NULL),
(598, 27, 35, 'pada urutan penggunaan fungsi luasLingkaran() dan kelilingLingkaran(), yang mungkin memberikan kesan bahwa ada hubungan urutan yang penting dalam menghitung luas dan keliling lingkaran. Namun, sebenarnya tidak ada hubungan urutan yang penting antara keduanya, karena keduanya hanya melakukan perhitungan berdasarkan parameter yang diberikan.', '2024-04-27 07:39:36', '2024-04-27 07:39:36', NULL),
(599, 27, 36, 'Hasil akan tetap menampilkan Luas Lingkaran pada fungsi public static void tampil()', '2024-04-27 07:39:46', '2024-04-27 07:39:46', NULL),
(600, 27, 37, 'Program ini sebenarnya tidak menggunakan rekursi. Meskipun terdapat pemanggilan fungsi hitungBunga() di dalam dirinya sendiri, itu tidak terjadi secara rekursif.\n\nPemanggilan fungsi hitungBunga() di dalam blok else adalah bagian dari pendekatan iteratif. Fungsi ini dipanggil secara berulang dengan argumen yang berbeda hingga mencapai kondisi dasar (tahun == 0), namun tidak menggunakan rekursi karena tidak ada \"pemanggilan balik\" dari fungsi tersebut ke dirinya sendiri secara eksplisit. Sehingga, program ini tidak menggunakan rekursi', '2024-04-27 07:47:40', '2024-04-27 07:47:40', NULL),
(601, 27, 38, 'Pertama, program memeriksa apakah variabel tahun sama dengan 0. Jika ya, itu berarti perhitungan bunga telah selesai, dan fungsi akan mengembalikan nilai saldo tanpa melakukan perhitungan tambahan.\nJika kondisi pada langkah sebelumnya tidak terpenuhi, maka program akan melanjutkan ke blok else. Di dalam blok else, program akan menghitung bunga tahunan dengan rumus saldo * (bunga / 100). Namun, ini adalah kesalahan karena seharusnya kita harus membagi bunga dengan jumlah tahun, bukan dengan 100.\nSetelah itu, program akan menghitung total saldo dengan menambahkan saldo awal dengan bunga tahunan. Namun, dalam penjelasan yang salah ini, kita dapat mengatakan bahwa total saldo dihitung dengan membagi saldo dengan bunga, yang tentu saja tidak benar.\nTerakhir, program akan memanggil fungsi hitungBunga() secara rekursif dengan nilai total saldo sebagai saldo baru, bunga yang sama, dan tahun yang berkurang satu. Ini akan terus berulang hingga kondisi tahun == 0 terpenuhi, dan saldo akhir akan dikembalikan.', '2024-04-27 07:47:46', '2024-04-27 07:47:46', NULL),
(602, 27, 39, '1407107.324173', '2024-04-27 07:47:53', '2024-04-27 07:47:53', NULL),
(603, 28, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-04-27 13:40:26', '2024-04-27 13:40:26', NULL),
(604, 28, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-04-27 13:40:37', '2024-04-27 13:40:37', NULL),
(605, 28, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-04-27 13:40:43', '2024-04-27 13:40:43', NULL),
(606, 28, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-04-27 13:49:06', '2024-04-27 13:49:06', NULL),
(607, 28, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-04-27 13:49:11', '2024-04-27 13:49:11', NULL),
(608, 28, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-04-27 13:49:15', '2024-04-27 13:49:15', NULL),
(609, 28, 7, 'Untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-04-27 13:57:07', '2024-04-27 13:57:07', NULL),
(610, 28, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi', '2024-04-27 13:57:13', '2024-04-27 13:57:13', NULL),
(611, 28, 9, 'Output program akan menampilkan pesan \"Low Value Item!\".', '2024-04-27 13:57:20', '2024-04-27 13:57:20', NULL),
(612, 28, 10, 'Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-04-27 14:05:18', '2024-04-27 14:05:18', NULL),
(613, 28, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi', '2024-04-27 14:05:23', '2024-04-27 14:05:23', NULL),
(614, 28, 12, 'Saat nilai shipping tidak bernilai regular maupun express, sehingga default case dieksekusi.', '2024-04-27 14:05:28', '2024-04-27 14:05:28', NULL),
(615, 28, 13, 'Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-04-27 14:13:33', '2024-04-27 14:13:33', NULL),
(616, 28, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-04-27 14:13:38', '2024-04-27 14:13:38', NULL),
(617, 28, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-04-27 14:13:43', '2024-04-27 14:13:43', NULL),
(618, 28, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i.  itu adalah ekspresi increment untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-04-27 14:21:37', '2024-04-27 14:21:37', NULL),
(619, 28, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-04-27 14:21:43', '2024-04-27 14:21:43', NULL),
(620, 28, 18, '1234567', '2024-04-27 14:21:51', '2024-04-27 14:21:51', NULL),
(621, 28, 19, 'i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-04-27 14:29:52', '2024-04-27 14:29:52', NULL),
(622, 28, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-04-27 14:29:57', '2024-04-27 14:29:57', NULL),
(623, 28, 21, 'Tidak ada output yang akan dikeluarkan oleh program dalam kasus ini.', '2024-04-27 14:30:04', '2024-04-27 14:30:04', NULL),
(624, 28, 22, 'Baris kode \"int next = first + second\" berfungsi untuk mengalikan nilai dari variabel first dan second.', '2024-04-27 14:37:12', '2024-04-27 14:37:12', NULL),
(625, 28, 23, '1. Inisialisasi variabel n dengan nilai 6, first dengan 0, second dengan 1, dan i dengan 1.\n2. Cetak teks \"Deret Fibonacci:\".\n3. Cetak nilai first dan second.\n4. Masuk ke dalam loop do-while.\n5. Di dalam loop, hitung nilai next dengan menjumlahkan nilai first dan second.\n6. Cetak nilai next.\n7. Perbarui nilai first dengan nilai second, dan nilai second dengan nilai next.\n8. Tingkatkan nilai i sebanyak 1.\n9. Ulangi langkah 5-8 selama nilai i kurang dari atau sama dengan n.', '2024-04-27 14:37:18', '2024-04-27 14:37:18', NULL),
(626, 28, 24, '0 1 1 2 3 5 8 13', '2024-04-27 14:37:22', '2024-04-27 14:37:22', NULL),
(627, 28, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) bertujuan untuk memastikan bahwa loop akan berjalan dari baris kelima hingga baris ke-i', '2024-04-27 14:46:30', '2024-04-27 14:46:30', NULL),
(628, 28, 26, 'Dalam perulangan kedua (inner loop) yang menggunakan variabel j, program ini sebenarnya mencetak bintang (*) sebanyak dua kali lipat dari nilai variabel i. Jadi, pada setiap iterasi dari perulangan luar (yang diatur oleh variabel i), perulangan dalam (yang diatur oleh variabel j) akan mencetak bintang sebanyak dua kali lipat dari nilai i saat itu. Misalnya, pada baris pertama (ketika i = 1), program akan mencetak dua bintang. Pada baris kedua (ketika i = 2), program akan mencetak empat bintang, dan seterusnya. Sehingga, outputnya akan menjadi seperti pola segitiga dengan tinggi lima baris, di mana jumlah bintang pada setiap baris adalah dua kali lipat dari nomor baris saat itu.', '2024-04-27 14:46:33', '2024-04-27 14:46:33', NULL),
(629, 28, 27, '*\n**\n***\n****\n*****\n******\n*******', '2024-04-27 14:46:38', '2024-04-27 14:46:38', NULL),
(630, 28, 28, 'System.out.print(topicArray);', '2024-04-27 14:54:20', '2024-04-27 14:54:20', NULL),
(631, 28, 29, 'Program dimulai dengan mendeklarasikan array topics yang berisi empat string: \"Opinion\", \"Tech\", \"Science\", dan \"Health\".\nSelanjutnya, kita menggunakan metode Arrays.toString(topics) untuk mengubah array tersebut menjadi sebuah string.\nHasil dari langkah kedua, yaitu string yang berisi representasi dari array topics, disimpan ke dalam variabel topicArray.\nKemudian, kita mencetak isi dari topicArray menggunakan System.out.print(topicArray).', '2024-04-27 14:54:24', '2024-04-27 14:54:24', NULL),
(632, 28, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1,2,3,4};, maka output yang dihasilkan program akan menjadi: [1, 2, 3, 4]\nIni disebabkan oleh penggunaan Arrays.toString(topics), yang mengonversi array topics menjadi representasi string. Meskipun elemen-elemen array diinisialisasi sebagai integer, Java akan secara otomatis mengonversi mereka menjadi string dalam representasi yang sesuai untuk mencetak array. Sehingga, meskipun elemen array sebelumnya adalah string, hasilnya akan tetap sama.', '2024-04-27 14:54:27', '2024-04-27 14:54:27', NULL),
(633, 28, 31, 'Mengeksekusi perulangan sebanyak nilai.length', '2024-04-27 15:01:59', '2024-04-27 15:01:59', NULL),
(634, 28, 32, 'loop ini bertugas untuk mengakses setiap nilai dalam baris ke-i dari array nilai. Variabel j kemudian digunakan untuk mengakses setiap nilai secara berurutan dalam baris tersebut. Nilai-nilai ini kemudian dijumlahkan ke dalam variabel total, sementara jumlahData diinkrementasi untuk merekam jumlah nilai yang telah diakses.', '2024-04-27 15:02:04', '2024-04-27 15:02:04', NULL),
(635, 28, 33, '70', '2024-04-27 15:02:11', '2024-04-27 15:02:11', NULL),
(636, 28, 34, 'Metode tampil() dalam metode main berfungsi untuk menghitung luas dan keliling lingkaran, tetapi tidak melakukan tindakan apa pun setelahnya. Sehingga, memanggil tampil() tidak memberikan hasil yang ditampilkan.', '2024-04-27 15:09:07', '2024-04-27 15:09:07', NULL),
(637, 28, 35, 'pada urutan penggunaan fungsi luasLingkaran() dan kelilingLingkaran(), yang mungkin memberikan kesan bahwa ada hubungan urutan yang penting dalam menghitung luas dan keliling lingkaran. Namun, sebenarnya tidak ada hubungan urutan yang penting antara keduanya, karena keduanya hanya melakukan perhitungan berdasarkan parameter yang diberikan.', '2024-04-27 15:09:13', '2024-04-27 15:09:13', NULL),
(638, 28, 36, 'Hasil akan tetap menampilkan Luas Lingkaran pada fungsi public static void tampil()', '2024-04-27 15:09:20', '2024-04-27 15:09:20', NULL),
(639, 28, 37, 'Program ini sebenarnya tidak menggunakan rekursi. Meskipun terdapat pemanggilan fungsi hitungBunga() di dalam dirinya sendiri, itu tidak terjadi secara rekursif.', '2024-04-27 15:16:34', '2024-04-27 15:16:34', NULL),
(640, 28, 38, 'Pertama, program memeriksa apakah variabel tahun sama dengan 0. Jika ya, itu berarti perhitungan bunga telah selesai, dan fungsi akan mengembalikan nilai saldo tanpa melakukan perhitungan tambahan.', '2024-04-27 15:16:41', '2024-04-27 15:16:41', NULL),
(641, 28, 39, '1407107.324173', '2024-04-27 15:16:45', '2024-04-27 15:16:45', NULL),
(642, 29, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-04-27 19:24:16', '2024-04-27 19:24:16', NULL),
(643, 29, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-04-27 19:24:32', '2024-04-27 19:24:32', NULL),
(644, 29, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-04-27 19:24:39', '2024-04-27 19:24:39', NULL),
(645, 29, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-04-27 19:35:46', '2024-04-27 19:35:46', NULL),
(646, 29, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-04-27 19:35:54', '2024-04-27 19:35:54', NULL),
(647, 29, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-04-27 19:36:02', '2024-04-27 19:36:02', NULL),
(648, 29, 7, 'Untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-04-27 19:45:43', '2024-04-27 19:45:43', NULL),
(649, 29, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi', '2024-04-27 19:45:50', '2024-04-27 19:45:50', NULL),
(650, 29, 9, 'Output program akan menampilkan pesan \"Low Value Item!\".', '2024-04-27 19:45:57', '2024-04-27 19:45:57', NULL),
(651, 29, 10, 'Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-04-27 19:53:17', '2024-04-27 19:53:17', NULL),
(652, 29, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi', '2024-04-27 19:53:24', '2024-04-27 19:53:24', NULL),
(653, 29, 12, 'Saat nilai shipping tidak bernilai regular maupun express, sehingga default case dieksekusi.', '2024-04-27 19:53:32', '2024-04-27 19:53:32', NULL),
(654, 29, 13, 'Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-04-27 20:01:35', '2024-04-27 20:01:35', NULL),
(655, 29, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-04-27 20:01:41', '2024-04-27 20:01:41', NULL),
(656, 29, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-04-27 20:01:48', '2024-04-27 20:01:48', NULL),
(657, 29, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i.  itu adalah ekspresi increment untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-04-27 20:10:09', '2024-04-27 20:10:09', NULL),
(658, 29, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-04-27 20:10:15', '2024-04-27 20:10:15', NULL),
(659, 29, 18, '1234567', '2024-04-27 20:10:22', '2024-04-27 20:10:22', NULL),
(660, 29, 19, 'i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-04-27 20:18:46', '2024-04-27 20:18:46', NULL),
(661, 29, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-04-27 20:18:52', '2024-04-27 20:18:52', NULL),
(662, 29, 21, 'Tidak ada output yang akan dikeluarkan oleh program dalam kasus ini.', '2024-04-27 20:19:01', '2024-04-27 20:19:01', NULL),
(663, 29, 22, 'Baris kode \"int next = first + second\" berfungsi untuk mengalikan nilai dari variabel first dan second.', '2024-04-27 20:27:27', '2024-04-27 20:27:27', NULL),
(664, 29, 23, '1. Inisialisasi variabel n dengan nilai 6, first dengan 0, second dengan 1, dan i dengan 1.\n2. Cetak teks \"Deret Fibonacci:\".\n3. Cetak nilai first dan second.\n4. Masuk ke dalam loop do-while.\n5. Di dalam loop, hitung nilai next dengan menjumlahkan nilai first dan second.\n6. Cetak nilai next.\n7. Perbarui nilai first dengan nilai second, dan nilai second dengan nilai next.\n8. Tingkatkan nilai i sebanyak 1.\n9. Ulangi langkah 5-8 selama nilai i kurang dari atau sama dengan n.', '2024-04-27 20:27:34', '2024-04-27 20:27:34', NULL),
(665, 29, 24, '0 1 1 2 3 5 8 13', '2024-04-27 20:27:43', '2024-04-27 20:27:43', NULL),
(666, 29, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) bertujuan untuk memastikan bahwa loop akan berjalan dari baris kelima hingga baris ke-i', '2024-04-27 20:36:58', '2024-04-27 20:36:58', NULL),
(667, 29, 26, 'Dalam perulangan kedua (inner loop) yang menggunakan variabel j, program ini sebenarnya mencetak bintang (*) sebanyak dua kali lipat dari nilai variabel i. Jadi, pada setiap iterasi dari perulangan luar (yang diatur oleh variabel i), perulangan dalam (yang diatur oleh variabel j) akan mencetak bintang sebanyak dua kali lipat dari nilai i saat itu. Misalnya, pada baris pertama (ketika i = 1), program akan mencetak dua bintang. Pada baris kedua (ketika i = 2), program akan mencetak empat bintang, dan seterusnya. Sehingga, outputnya akan menjadi seperti pola segitiga dengan tinggi lima baris, di mana jumlah bintang pada setiap baris adalah dua kali lipat dari nomor baris saat itu.', '2024-04-27 20:37:03', '2024-04-27 20:37:03', NULL),
(668, 29, 27, '*\n**\n***\n****\n*****\n******\n*******', '2024-04-27 20:37:10', '2024-04-27 20:37:10', NULL),
(669, 29, 28, 'System.out.print(topicArray);', '2024-04-27 20:44:55', '2024-04-27 20:44:55', NULL),
(670, 29, 29, 'Program dimulai dengan mendeklarasikan array topics yang berisi empat string: \"Opinion\", \"Tech\", \"Science\", dan \"Health\".\nSelanjutnya, kita menggunakan metode Arrays.toString(topics) untuk mengubah array tersebut menjadi sebuah string.\nHasil dari langkah kedua, yaitu string yang berisi representasi dari array topics, disimpan ke dalam variabel topicArray.\nKemudian, kita mencetak isi dari topicArray menggunakan System.out.print(topicArray).', '2024-04-27 20:45:04', '2024-04-27 20:45:04', NULL),
(671, 29, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1,2,3,4};, maka output yang dihasilkan program akan menjadi: [1, 2, 3, 4]\nIni disebabkan oleh penggunaan Arrays.toString(topics), yang mengonversi array topics menjadi representasi string. Meskipun elemen-elemen array diinisialisasi sebagai integer, Java akan secara otomatis mengonversi mereka menjadi string dalam representasi yang sesuai untuk mencetak array. Sehingga, meskipun elemen array sebelumnya adalah string, hasilnya akan tetap sama.', '2024-04-27 20:45:09', '2024-04-27 20:45:09', NULL),
(672, 29, 31, 'Mengeksekusi perulangan sebanyak nilai.length', '2024-04-27 20:54:42', '2024-04-27 20:54:42', NULL),
(673, 29, 32, 'loop ini bertugas untuk mengakses setiap nilai dalam baris ke-i dari array nilai. Variabel j kemudian digunakan untuk mengakses setiap nilai secara berurutan dalam baris tersebut. Nilai-nilai ini kemudian dijumlahkan ke dalam variabel total, sementara jumlahData diinkrementasi untuk merekam jumlah nilai yang telah diakses.', '2024-04-27 20:54:47', '2024-04-27 20:54:47', NULL),
(674, 29, 33, '70', '2024-04-27 20:54:54', '2024-04-27 20:54:54', NULL),
(680, 29, 34, 'Metode tampil() dalam metode main berfungsi untuk menghitung luas dan keliling lingkaran, tetapi tidak melakukan tindakan apa pun setelahnya. Sehingga, memanggil tampil() tidak memberikan hasil yang ditampilkan.', '2024-04-27 21:07:55', '2024-04-27 21:07:55', NULL),
(681, 29, 35, 'pada urutan penggunaan fungsi luasLingkaran() dan kelilingLingkaran(), yang mungkin memberikan kesan bahwa ada hubungan urutan yang penting dalam menghitung luas dan keliling lingkaran. Namun, sebenarnya tidak ada hubungan urutan yang penting antara keduanya, karena keduanya hanya melakukan perhitungan berdasarkan parameter yang diberikan.', '2024-04-27 21:08:02', '2024-04-27 21:08:02', NULL),
(682, 29, 36, 'Hasil akan tetap menampilkan Luas Lingkaran pada fungsi public static void tampil()', '2024-04-27 21:08:06', '2024-04-27 21:08:06', NULL),
(683, 29, 37, 'Program ini sebenarnya tidak menggunakan rekursi. Meskipun terdapat pemanggilan fungsi hitungBunga() di dalam dirinya sendiri, itu tidak terjadi secara rekursif.\n\nPemanggilan fungsi hitungBunga() di dalam blok else adalah bagian dari pendekatan iteratif. Fungsi ini dipanggil secara berulang dengan argumen yang berbeda hingga mencapai kondisi dasar (tahun == 0), namun tidak menggunakan rekursi karena tidak ada \"pemanggilan balik\" dari fungsi tersebut ke dirinya sendiri secara eksplisit. Sehingga, program ini tidak menggunakan rekursi', '2024-04-27 21:16:33', '2024-04-27 21:16:33', NULL),
(684, 29, 38, 'Pertama, program memeriksa apakah variabel tahun sama dengan 0. Jika ya, itu berarti perhitungan bunga telah selesai, dan fungsi akan mengembalikan nilai saldo tanpa melakukan perhitungan tambahan.\nJika kondisi pada langkah sebelumnya tidak terpenuhi, maka program akan melanjutkan ke blok else. Di dalam blok else, program akan menghitung bunga tahunan dengan rumus saldo * (bunga / 100). Namun, ini adalah kesalahan karena seharusnya kita harus membagi bunga dengan jumlah tahun, bukan dengan 100.\nSetelah itu, program akan menghitung total saldo dengan menambahkan saldo awal dengan bunga tahunan. Namun, dalam penjelasan yang salah ini, kita dapat mengatakan bahwa total saldo dihitung dengan membagi saldo dengan bunga, yang tentu saja tidak benar.\nTerakhir, program akan memanggil fungsi hitungBunga() secara rekursif dengan nilai total saldo sebagai saldo baru, bunga yang sama, dan tahun yang berkurang satu. Ini akan terus berulang hingga kondisi tahun == 0 terpenuhi, dan saldo akhir akan dikembalikan.', '2024-04-27 21:16:38', '2024-04-27 21:16:38', NULL),
(685, 29, 39, '1407107.324173', '2024-04-27 21:16:45', '2024-04-27 21:16:45', NULL),
(686, 30, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-04-28 05:54:12', '2024-04-28 05:54:12', NULL),
(687, 30, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-04-28 05:54:22', '2024-04-28 05:54:22', NULL),
(688, 30, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-04-28 05:54:26', '2024-04-28 05:54:26', NULL),
(689, 30, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-04-28 06:08:15', '2024-04-28 06:08:15', NULL),
(690, 30, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-04-28 06:08:21', '2024-04-28 06:08:21', NULL),
(691, 30, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-04-28 06:08:24', '2024-04-28 06:08:24', NULL),
(692, 30, 7, 'Untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-04-28 06:15:50', '2024-04-28 06:15:50', NULL),
(693, 30, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi', '2024-04-28 06:15:56', '2024-04-28 06:15:56', NULL),
(694, 30, 9, 'Output program akan menampilkan pesan \"Low Value Item!\".', '2024-04-28 06:16:00', '2024-04-28 06:16:00', NULL),
(695, 30, 10, 'Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-04-28 06:24:12', '2024-04-28 06:24:12', NULL),
(696, 30, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi', '2024-04-28 06:24:15', '2024-04-28 06:24:15', NULL),
(697, 30, 12, 'Saat nilai shipping tidak bernilai regular maupun express, sehingga default case dieksekusi.', '2024-04-28 06:24:19', '2024-04-28 06:24:19', NULL),
(698, 30, 13, 'Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-04-28 06:31:57', '2024-04-28 06:31:57', NULL),
(699, 30, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-04-28 06:32:00', '2024-04-28 06:32:00', NULL),
(700, 30, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-04-28 06:32:05', '2024-04-28 06:32:05', NULL),
(701, 30, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i.  itu adalah ekspresi increment untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-04-28 06:42:14', '2024-04-28 06:42:14', NULL),
(702, 30, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-04-28 06:42:18', '2024-04-28 06:42:18', NULL),
(703, 30, 18, '1234567', '2024-04-28 06:42:26', '2024-04-28 06:42:26', NULL),
(704, 30, 19, 'i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-04-28 06:50:15', '2024-04-28 06:50:15', NULL),
(705, 30, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-04-28 06:50:19', '2024-04-28 06:50:19', NULL),
(706, 30, 21, 'Tidak ada output yang akan dikeluarkan oleh program dalam kasus ini.', '2024-04-28 06:50:26', '2024-04-28 06:50:26', NULL),
(707, 30, 22, 'Baris kode \"int next = first + second\" berfungsi untuk mengalikan nilai dari variabel first dan second.', '2024-04-28 07:02:39', '2024-04-28 07:02:39', NULL),
(708, 30, 23, '1. Inisialisasi variabel n dengan nilai 6, first dengan 0, second dengan 1, dan i dengan 1.\n2. Cetak teks \"Deret Fibonacci:\".\n3. Cetak nilai first dan second.\n4. Masuk ke dalam loop do-while.\n5. Di dalam loop, hitung nilai next dengan menjumlahkan nilai first dan second.\n6. Cetak nilai next.\n7. Perbarui nilai first dengan nilai second, dan nilai second dengan nilai next.\n8. Tingkatkan nilai i sebanyak 1.\n9. Ulangi langkah 5-8 selama nilai i kurang dari atau sama dengan n.', '2024-04-28 07:02:47', '2024-04-28 07:02:47', NULL),
(709, 30, 24, '0 1 1 2 3 5 8 13', '2024-04-28 07:02:50', '2024-04-28 07:02:50', NULL);
INSERT INTO `user_answer` (`id`, `user_id`, `essay_question_id`, `answer`, `created_at`, `updated_at`, `deleted_at`) VALUES
(710, 30, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) bertujuan untuk memastikan bahwa loop akan berjalan dari baris kelima hingga baris ke-i', '2024-04-28 07:11:30', '2024-04-28 07:11:30', NULL),
(711, 30, 26, 'Dalam perulangan kedua (inner loop) yang menggunakan variabel j, program ini sebenarnya mencetak bintang (*) sebanyak dua kali lipat dari nilai variabel i. Jadi, pada setiap iterasi dari perulangan luar (yang diatur oleh variabel i), perulangan dalam (yang diatur oleh variabel j) akan mencetak bintang sebanyak dua kali lipat dari nilai i saat itu. Misalnya, pada baris pertama (ketika i = 1), program akan mencetak dua bintang. Pada baris kedua (ketika i = 2), program akan mencetak empat bintang, dan seterusnya. Sehingga, outputnya akan menjadi seperti pola segitiga dengan tinggi lima baris, di mana jumlah bintang pada setiap baris adalah dua kali lipat dari nomor baris saat itu.', '2024-04-28 07:11:35', '2024-04-28 07:11:35', NULL),
(712, 30, 27, '*\n**\n***\n****\n*****\n******\n*******', '2024-04-28 07:11:40', '2024-04-28 07:11:40', NULL),
(713, 30, 28, 'System.out.print(topicArray);', '2024-04-28 07:23:44', '2024-04-28 07:23:44', NULL),
(714, 30, 29, 'Program dimulai dengan mendeklarasikan array topics yang berisi empat string: \"Opinion\", \"Tech\", \"Science\", dan \"Health\".\nSelanjutnya, kita menggunakan metode Arrays.toString(topics) untuk mengubah array tersebut menjadi sebuah string.\nHasil dari langkah kedua, yaitu string yang berisi representasi dari array topics, disimpan ke dalam variabel topicArray.\nKemudian, kita mencetak isi dari topicArray menggunakan System.out.print(topicArray).', '2024-04-28 07:23:47', '2024-04-28 07:23:47', NULL),
(715, 30, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1,2,3,4};, maka output yang dihasilkan program akan menjadi: [1, 2, 3, 4]\nIni disebabkan oleh penggunaan Arrays.toString(topics), yang mengonversi array topics menjadi representasi string. Meskipun elemen-elemen array diinisialisasi sebagai integer, Java akan secara otomatis mengonversi mereka menjadi string dalam representasi yang sesuai untuk mencetak array. Sehingga, meskipun elemen array sebelumnya adalah string, hasilnya akan tetap sama.', '2024-04-28 07:23:51', '2024-04-28 07:23:51', NULL),
(716, 30, 31, 'Mengeksekusi perulangan sebanyak nilai.length', '2024-04-28 07:33:50', '2024-04-28 07:33:50', NULL),
(717, 30, 32, 'loop ini bertugas untuk mengakses setiap nilai dalam baris ke-i dari array nilai. Variabel j kemudian digunakan untuk mengakses setiap nilai secara berurutan dalam baris tersebut. Nilai-nilai ini kemudian dijumlahkan ke dalam variabel total, sementara jumlahData diinkrementasi untuk merekam jumlah nilai yang telah diakses.', '2024-04-28 07:33:56', '2024-04-28 07:33:56', NULL),
(718, 30, 33, '70', '2024-04-28 07:34:04', '2024-04-28 07:34:04', NULL),
(719, 30, 34, 'Metode tampil() dalam metode main berfungsi untuk menghitung luas dan keliling lingkaran, tetapi tidak melakukan tindakan apa pun setelahnya. Sehingga, memanggil tampil() tidak memberikan hasil yang ditampilkan.', '2024-04-28 07:41:56', '2024-04-28 07:41:56', NULL),
(720, 30, 35, 'pada urutan penggunaan fungsi luasLingkaran() dan kelilingLingkaran(), yang mungkin memberikan kesan bahwa ada hubungan urutan yang penting dalam menghitung luas dan keliling lingkaran. Namun, sebenarnya tidak ada hubungan urutan yang penting antara keduanya, karena keduanya hanya melakukan perhitungan berdasarkan parameter yang diberikan.', '2024-04-28 07:41:59', '2024-04-28 07:41:59', NULL),
(721, 30, 36, 'Hasil akan tetap menampilkan Luas Lingkaran pada fungsi public static void tampil()', '2024-04-28 07:42:04', '2024-04-28 07:42:04', NULL),
(722, 30, 37, 'Program ini sebenarnya tidak menggunakan rekursi. Meskipun terdapat pemanggilan fungsi hitungBunga() di dalam dirinya sendiri, itu tidak terjadi secara rekursif.\n\nPemanggilan fungsi hitungBunga() di dalam blok else adalah bagian dari pendekatan iteratif. Fungsi ini dipanggil secara berulang dengan argumen yang berbeda hingga mencapai kondisi dasar (tahun == 0), namun tidak menggunakan rekursi karena tidak ada \"pemanggilan balik\" dari fungsi tersebut ke dirinya sendiri secara eksplisit. Sehingga, program ini tidak menggunakan rekursi', '2024-04-28 07:52:16', '2024-04-28 07:52:16', NULL),
(723, 30, 38, 'Pertama, program memeriksa apakah variabel tahun sama dengan 0. Jika ya, itu berarti perhitungan bunga telah selesai, dan fungsi akan mengembalikan nilai saldo tanpa melakukan perhitungan tambahan.\nJika kondisi pada langkah sebelumnya tidak terpenuhi, maka program akan melanjutkan ke blok else. Di dalam blok else, program akan menghitung bunga tahunan dengan rumus saldo * (bunga / 100). Namun, ini adalah kesalahan karena seharusnya kita harus membagi bunga dengan jumlah tahun, bukan dengan 100.\nSetelah itu, program akan menghitung total saldo dengan menambahkan saldo awal dengan bunga tahunan. Namun, dalam penjelasan yang salah ini, kita dapat mengatakan bahwa total saldo dihitung dengan membagi saldo dengan bunga, yang tentu saja tidak benar.\nTerakhir, program akan memanggil fungsi hitungBunga() secara rekursif dengan nilai total saldo sebagai saldo baru, bunga yang sama, dan tahun yang berkurang satu. Ini akan terus berulang hingga kondisi tahun == 0 terpenuhi, dan saldo akhir akan dikembalikan.', '2024-04-28 07:52:21', '2024-04-28 07:52:21', NULL),
(724, 30, 39, '1407107.324173', '2024-04-28 07:52:28', '2024-04-28 07:52:28', NULL),
(725, 31, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-04-28 13:56:36', '2024-04-28 13:56:36', NULL),
(726, 31, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-04-28 13:56:42', '2024-04-28 13:56:42', NULL),
(727, 31, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-04-28 13:56:47', '2024-04-28 13:56:47', NULL),
(728, 31, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-04-28 14:03:05', '2024-04-28 14:03:05', NULL),
(729, 31, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-04-28 14:03:10', '2024-04-28 14:03:10', NULL),
(730, 31, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-04-28 14:03:21', '2024-04-28 14:03:21', NULL),
(731, 31, 7, 'Untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-04-28 14:06:42', '2024-04-28 14:06:42', NULL),
(732, 31, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi', '2024-04-28 14:06:48', '2024-04-28 14:06:48', NULL),
(733, 31, 9, 'Output program akan menampilkan pesan \"Low Value Item!\".', '2024-04-28 14:06:55', '2024-04-28 14:06:55', NULL),
(734, 31, 10, 'Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-04-28 14:10:42', '2024-04-28 14:10:42', NULL),
(735, 31, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi', '2024-04-28 14:10:48', '2024-04-28 14:10:48', NULL),
(736, 31, 12, 'Saat nilai shipping tidak bernilai regular maupun express, sehingga default case dieksekusi.', '2024-04-28 14:10:55', '2024-04-28 14:10:55', NULL),
(737, 31, 13, 'Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-04-28 14:14:10', '2024-04-28 14:14:10', NULL),
(738, 31, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-04-28 14:14:16', '2024-04-28 14:14:16', NULL),
(739, 31, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-04-28 14:14:22', '2024-04-28 14:14:22', NULL),
(740, 31, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i.  itu adalah ekspresi increment untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-04-28 14:17:19', '2024-04-28 14:17:19', NULL),
(741, 31, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-04-28 14:17:28', '2024-04-28 14:17:28', NULL),
(742, 31, 18, '1234567', '2024-04-28 14:17:33', '2024-04-28 14:17:33', NULL),
(743, 31, 19, 'i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-04-28 14:20:00', '2024-04-28 14:20:00', NULL),
(744, 31, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-04-28 14:20:05', '2024-04-28 14:20:05', NULL),
(745, 31, 21, 'Tidak ada output yang akan dikeluarkan oleh program dalam kasus ini.', '2024-04-28 14:20:12', '2024-04-28 14:20:12', NULL),
(746, 31, 22, 'Baris kode \"int next = first + second\" berfungsi untuk mengalikan nilai dari variabel first dan second.', '2024-04-28 14:23:41', '2024-04-28 14:23:41', NULL),
(747, 31, 23, '1. Inisialisasi variabel n dengan nilai 6, first dengan 0, second dengan 1, dan i dengan 1.\n2. Cetak teks \"Deret Fibonacci:\".\n3. Cetak nilai first dan second.\n4. Masuk ke dalam loop do-while.\n5. Di dalam loop, hitung nilai next dengan menjumlahkan nilai first dan second.\n6. Cetak nilai next.\n7. Perbarui nilai first dengan nilai second, dan nilai second dengan nilai next.\n8. Tingkatkan nilai i sebanyak 1.\n9. Ulangi langkah 5-8 selama nilai i kurang dari atau sama dengan n.', '2024-04-28 14:23:48', '2024-04-28 14:23:48', NULL),
(748, 31, 24, '0 1 1 2 3 5 8 13', '2024-04-28 14:23:53', '2024-04-28 14:23:53', NULL),
(749, 31, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) bertujuan untuk memastikan bahwa loop akan berjalan dari baris kelima hingga baris ke-i', '2024-04-28 14:27:24', '2024-04-28 14:27:24', NULL),
(750, 31, 26, 'Dalam perulangan kedua (inner loop) yang menggunakan variabel j, program ini sebenarnya mencetak bintang (*) sebanyak dua kali lipat dari nilai variabel i. Jadi, pada setiap iterasi dari perulangan luar (yang diatur oleh variabel i), perulangan dalam (yang diatur oleh variabel j) akan mencetak bintang sebanyak dua kali lipat dari nilai i saat itu. Misalnya, pada baris pertama (ketika i = 1), program akan mencetak dua bintang. Pada baris kedua (ketika i = 2), program akan mencetak empat bintang, dan seterusnya. Sehingga, outputnya akan menjadi seperti pola segitiga dengan tinggi lima baris, di mana jumlah bintang pada setiap baris adalah dua kali lipat dari nomor baris saat itu.', '2024-04-28 14:27:29', '2024-04-28 14:27:29', NULL),
(751, 31, 27, '*\n**\n***\n****\n*****\n******\n*******', '2024-04-28 14:27:36', '2024-04-28 14:27:36', NULL),
(752, 31, 28, 'System.out.print(topicArray);', '2024-04-28 14:30:31', '2024-04-28 14:30:31', NULL),
(753, 31, 29, 'Program dimulai dengan mendeklarasikan array topics yang berisi empat string: \"Opinion\", \"Tech\", \"Science\", dan \"Health\".\nSelanjutnya, kita menggunakan metode Arrays.toString(topics) untuk mengubah array tersebut menjadi sebuah string.\nHasil dari langkah kedua, yaitu string yang berisi representasi dari array topics, disimpan ke dalam variabel topicArray.\nKemudian, kita mencetak isi dari topicArray menggunakan System.out.print(topicArray).', '2024-04-28 14:30:38', '2024-04-28 14:30:38', NULL),
(754, 31, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1,2,3,4};, maka output yang dihasilkan program akan menjadi: [1, 2, 3, 4]\nIni disebabkan oleh penggunaan Arrays.toString(topics), yang mengonversi array topics menjadi representasi string. Meskipun elemen-elemen array diinisialisasi sebagai integer, Java akan secara otomatis mengonversi mereka menjadi string dalam representasi yang sesuai untuk mencetak array. Sehingga, meskipun elemen array sebelumnya adalah string, hasilnya akan tetap sama.', '2024-04-28 14:30:42', '2024-04-28 14:30:42', NULL),
(755, 31, 31, 'Mengeksekusi perulangan sebanyak nilai.length', '2024-04-28 14:32:57', '2024-04-28 14:32:57', NULL),
(756, 31, 32, 'loop ini bertugas untuk mengakses setiap nilai dalam baris ke-i dari array nilai. Variabel j kemudian digunakan untuk mengakses setiap nilai secara berurutan dalam baris tersebut. Nilai-nilai ini kemudian dijumlahkan ke dalam variabel total, sementara jumlahData diinkrementasi untuk merekam jumlah nilai yang telah diakses.', '2024-04-28 14:33:04', '2024-04-28 14:33:04', NULL),
(757, 31, 33, '70', '2024-04-28 14:33:08', '2024-04-28 14:33:08', NULL),
(758, 31, 34, 'Metode tampil() dalam metode main berfungsi untuk menghitung luas dan keliling lingkaran, tetapi tidak melakukan tindakan apa pun setelahnya. Sehingga, memanggil tampil() tidak memberikan hasil yang ditampilkan.', '2024-04-28 14:35:43', '2024-04-28 14:35:43', NULL),
(759, 31, 35, 'pada urutan penggunaan fungsi luasLingkaran() dan kelilingLingkaran(), yang mungkin memberikan kesan bahwa ada hubungan urutan yang penting dalam menghitung luas dan keliling lingkaran. Namun, sebenarnya tidak ada hubungan urutan yang penting antara keduanya, karena keduanya hanya melakukan perhitungan berdasarkan parameter yang diberikan.', '2024-04-28 14:35:49', '2024-04-28 14:35:49', NULL),
(760, 31, 36, 'Hasil akan tetap menampilkan Luas Lingkaran pada fungsi public static void tampil()', '2024-04-28 14:35:55', '2024-04-28 14:35:55', NULL),
(761, 31, 37, 'Program ini sebenarnya tidak menggunakan rekursi. Meskipun terdapat pemanggilan fungsi hitungBunga() di dalam dirinya sendiri, itu tidak terjadi secara rekursif.\n\nPemanggilan fungsi hitungBunga() di dalam blok else adalah bagian dari pendekatan iteratif. Fungsi ini dipanggil secara berulang dengan argumen yang berbeda hingga mencapai kondisi dasar (tahun == 0), namun tidak menggunakan rekursi karena tidak ada \"pemanggilan balik\" dari fungsi tersebut ke dirinya sendiri secara eksplisit. Sehingga, program ini tidak menggunakan rekursi', '2024-04-28 14:38:08', '2024-04-28 14:38:08', NULL),
(762, 31, 38, 'Pertama, program memeriksa apakah variabel tahun sama dengan 0. Jika ya, itu berarti perhitungan bunga telah selesai, dan fungsi akan mengembalikan nilai saldo tanpa melakukan perhitungan tambahan.\nJika kondisi pada langkah sebelumnya tidak terpenuhi, maka program akan melanjutkan ke blok else. Di dalam blok else, program akan menghitung bunga tahunan dengan rumus saldo * (bunga / 100). Namun, ini adalah kesalahan karena seharusnya kita harus membagi bunga dengan jumlah tahun, bukan dengan 100.\nSetelah itu, program akan menghitung total saldo dengan menambahkan saldo awal dengan bunga tahunan. Namun, dalam penjelasan yang salah ini, kita dapat mengatakan bahwa total saldo dihitung dengan membagi saldo dengan bunga, yang tentu saja tidak benar.\nTerakhir, program akan memanggil fungsi hitungBunga() secara rekursif dengan nilai total saldo sebagai saldo baru, bunga yang sama, dan tahun yang berkurang satu. Ini akan terus berulang hingga kondisi tahun == 0 terpenuhi, dan saldo akhir akan dikembalikan.', '2024-04-28 14:38:16', '2024-04-28 14:38:16', NULL),
(763, 31, 39, '1407107.324173', '2024-04-28 14:38:22', '2024-04-28 14:38:22', NULL),
(764, 32, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-05-01 19:21:50', '2024-05-01 19:21:50', NULL),
(765, 32, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-05-01 19:22:03', '2024-05-01 19:22:03', NULL),
(766, 32, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-05-01 19:22:10', '2024-05-01 19:22:10', NULL),
(767, 32, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-05-01 19:43:41', '2024-05-01 19:43:41', NULL),
(768, 32, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-05-01 19:43:45', '2024-05-01 19:43:45', NULL),
(769, 32, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-05-01 19:43:52', '2024-05-01 19:43:52', NULL),
(770, 32, 7, 'Untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-05-01 19:56:23', '2024-05-01 19:56:23', NULL),
(771, 32, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi', '2024-05-01 19:56:27', '2024-05-01 19:56:27', NULL),
(772, 32, 9, 'Output program akan menampilkan pesan \"Low Value Item!\".', '2024-05-01 19:56:33', '2024-05-01 19:56:33', NULL),
(773, 33, 1, 'aaa', '2024-05-01 20:41:11', '2024-05-01 20:41:11', NULL),
(774, 33, 2, 'aaa', '2024-05-01 20:41:16', '2024-05-01 20:41:16', NULL),
(775, 33, 3, 'aaa', '2024-05-01 20:41:20', '2024-05-01 20:41:20', NULL),
(776, 34, 1, 'aaaa', '2024-05-01 21:30:43', '2024-05-01 21:30:43', NULL),
(777, 34, 2, 'bbbb', '2024-05-01 21:30:58', '2024-05-01 21:30:58', NULL),
(778, 34, 3, 'ccccc', '2024-05-01 21:31:03', '2024-05-01 21:31:03', NULL),
(779, 34, 4, '123', '2024-05-01 21:42:24', '2024-05-01 21:42:24', NULL),
(780, 34, 5, '456', '2024-05-01 21:42:31', '2024-05-01 21:42:31', NULL),
(781, 34, 6, '666', '2024-05-01 21:42:36', '2024-05-01 21:42:36', NULL),
(782, 34, 7, 'sss', '2024-05-01 22:35:42', '2024-05-01 22:35:42', NULL),
(783, 34, 8, 'ggg', '2024-05-01 22:35:48', '2024-05-01 22:35:48', NULL),
(784, 34, 9, 'vvv', '2024-05-01 22:35:56', '2024-05-01 22:35:56', NULL),
(785, 34, 10, 'a', '2024-05-01 23:28:08', '2024-05-01 23:28:08', NULL),
(786, 34, 11, 'a', '2024-05-01 23:28:16', '2024-05-01 23:28:16', NULL),
(787, 34, 12, 's', '2024-05-01 23:28:21', '2024-05-01 23:28:21', NULL),
(788, 32, 10, 'Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-05-02 15:11:42', '2024-05-02 15:11:42', NULL),
(789, 32, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi', '2024-05-02 15:11:49', '2024-05-02 15:11:49', NULL),
(790, 32, 12, 'Saat nilai shipping tidak bernilai regular maupun express, sehingga default case dieksekusi.', '2024-05-02 15:11:53', '2024-05-02 15:11:53', NULL),
(791, 32, 13, 'Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-05-02 15:20:30', '2024-05-02 15:20:30', NULL),
(792, 32, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-05-02 15:20:37', '2024-05-02 15:20:37', NULL),
(793, 32, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-05-02 15:20:44', '2024-05-02 15:20:44', NULL),
(794, 32, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i.  itu adalah ekspresi increment untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-05-02 15:29:40', '2024-05-02 15:29:40', NULL),
(795, 32, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-05-02 15:29:49', '2024-05-02 15:29:49', NULL),
(796, 32, 18, '1234567', '2024-05-02 15:29:56', '2024-05-02 15:29:56', NULL),
(797, 32, 19, 'i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-05-02 15:38:47', '2024-05-02 15:38:47', NULL),
(798, 32, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-05-02 15:38:56', '2024-05-02 15:38:56', NULL),
(799, 32, 21, 'Tidak ada output yang akan dikeluarkan oleh program dalam kasus ini.', '2024-05-02 15:39:06', '2024-05-02 15:39:06', NULL),
(800, 32, 22, 'Baris kode \"int next = first + second\" berfungsi untuk mengalikan nilai dari variabel first dan second.', '2024-05-02 15:46:59', '2024-05-02 15:46:59', NULL),
(801, 32, 23, '1. Inisialisasi variabel n dengan nilai 6, first dengan 0, second dengan 1, dan i dengan 1.\n2. Cetak teks \"Deret Fibonacci:\".\n3. Cetak nilai first dan second.\n4. Masuk ke dalam loop do-while.\n5. Di dalam loop, hitung nilai next dengan menjumlahkan nilai first dan second.\n6. Cetak nilai next.\n7. Perbarui nilai first dengan nilai second, dan nilai second dengan nilai next.\n8. Tingkatkan nilai i sebanyak 1.\n9. Ulangi langkah 5-8 selama nilai i kurang dari atau sama dengan n.', '2024-05-02 15:47:06', '2024-05-02 15:47:06', NULL),
(802, 32, 24, '0 1 1 2 3 5 8 13', '2024-05-02 15:47:13', '2024-05-02 15:47:13', NULL),
(803, 32, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) bertujuan untuk memastikan bahwa loop akan berjalan dari baris kelima hingga baris ke-i', '2024-05-02 15:56:14', '2024-05-02 15:56:14', NULL),
(804, 32, 26, 'Dalam perulangan kedua (inner loop) yang menggunakan variabel j, program ini sebenarnya mencetak bintang (*) sebanyak dua kali lipat dari nilai variabel i. Jadi, pada setiap iterasi dari perulangan luar (yang diatur oleh variabel i), perulangan dalam (yang diatur oleh variabel j) akan mencetak bintang sebanyak dua kali lipat dari nilai i saat itu. Misalnya, pada baris pertama (ketika i = 1), program akan mencetak dua bintang. Pada baris kedua (ketika i = 2), program akan mencetak empat bintang, dan seterusnya. Sehingga, outputnya akan menjadi seperti pola segitiga dengan tinggi lima baris, di mana jumlah bintang pada setiap baris adalah dua kali lipat dari nomor baris saat itu.', '2024-05-02 15:56:20', '2024-05-02 15:56:20', NULL),
(805, 32, 27, '*\n**\n***\n****\n*****\n******\n*******', '2024-05-02 15:56:31', '2024-05-02 15:56:31', NULL),
(806, 32, 28, 'System.out.print(topicArray);', '2024-05-02 16:04:21', '2024-05-02 16:04:21', NULL),
(807, 32, 29, 'Program dimulai dengan mendeklarasikan array topics yang berisi empat string: \"Opinion\", \"Tech\", \"Science\", dan \"Health\".\nSelanjutnya, kita menggunakan metode Arrays.toString(topics) untuk mengubah array tersebut menjadi sebuah string.\nHasil dari langkah kedua, yaitu string yang berisi representasi dari array topics, disimpan ke dalam variabel topicArray.\nKemudian, kita mencetak isi dari topicArray menggunakan System.out.print(topicArray).', '2024-05-02 16:04:27', '2024-05-02 16:04:27', NULL),
(808, 32, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1,2,3,4};, maka output yang dihasilkan program akan menjadi: [1, 2, 3, 4]\nIni disebabkan oleh penggunaan Arrays.toString(topics), yang mengonversi array topics menjadi representasi string. Meskipun elemen-elemen array diinisialisasi sebagai integer, Java akan secara otomatis mengonversi mereka menjadi string dalam representasi yang sesuai untuk mencetak array. Sehingga, meskipun elemen array sebelumnya adalah string, hasilnya akan tetap sama.', '2024-05-02 16:04:34', '2024-05-02 16:04:34', NULL),
(809, 32, 31, 'Mengeksekusi perulangan sebanyak nilai.length', '2024-05-02 16:12:46', '2024-05-02 16:12:46', NULL),
(810, 32, 32, 'loop ini bertugas untuk mengakses setiap nilai dalam baris ke-i dari array nilai. Variabel j kemudian digunakan untuk mengakses setiap nilai secara berurutan dalam baris tersebut. Nilai-nilai ini kemudian dijumlahkan ke dalam variabel total, sementara jumlahData diinkrementasi untuk merekam jumlah nilai yang telah diakses.', '2024-05-02 16:12:53', '2024-05-02 16:12:53', NULL),
(811, 32, 33, '70', '2024-05-02 16:13:00', '2024-05-02 16:13:00', NULL),
(812, 32, 34, 'Metode tampil() dalam metode main berfungsi untuk menghitung luas dan keliling lingkaran, tetapi tidak melakukan tindakan apa pun setelahnya. Sehingga, memanggil tampil() tidak memberikan hasil yang ditampilkan.', '2024-05-02 16:21:28', '2024-05-02 16:21:28', NULL),
(813, 32, 35, 'pada urutan penggunaan fungsi luasLingkaran() dan kelilingLingkaran(), yang mungkin memberikan kesan bahwa ada hubungan urutan yang penting dalam menghitung luas dan keliling lingkaran. Namun, sebenarnya tidak ada hubungan urutan yang penting antara keduanya, karena keduanya hanya melakukan perhitungan berdasarkan parameter yang diberikan.', '2024-05-02 16:21:34', '2024-05-02 16:21:34', NULL),
(814, 32, 36, 'Hasil akan tetap menampilkan Luas Lingkaran pada fungsi public static void tampil()', '2024-05-02 16:21:41', '2024-05-02 16:21:41', NULL),
(815, 32, 37, 'Program ini sebenarnya tidak menggunakan rekursi. Meskipun terdapat pemanggilan fungsi hitungBunga() di dalam dirinya sendiri, itu tidak terjadi secara rekursif.\n\nPemanggilan fungsi hitungBunga() di dalam blok else adalah bagian dari pendekatan iteratif. Fungsi ini dipanggil secara berulang dengan argumen yang berbeda hingga mencapai kondisi dasar (tahun == 0), namun tidak menggunakan rekursi karena tidak ada \"pemanggilan balik\" dari fungsi tersebut ke dirinya sendiri secara eksplisit. Sehingga, program ini tidak menggunakan rekursi', '2024-05-02 16:29:56', '2024-05-02 16:29:56', NULL),
(816, 32, 38, 'Pertama, program memeriksa apakah variabel tahun sama dengan 0. Jika ya, itu berarti perhitungan bunga telah selesai, dan fungsi akan mengembalikan nilai saldo tanpa melakukan perhitungan tambahan.\nJika kondisi pada langkah sebelumnya tidak terpenuhi, maka program akan melanjutkan ke blok else. Di dalam blok else, program akan menghitung bunga tahunan dengan rumus saldo * (bunga / 100). Namun, ini adalah kesalahan karena seharusnya kita harus membagi bunga dengan jumlah tahun, bukan dengan 100.\nSetelah itu, program akan menghitung total saldo dengan menambahkan saldo awal dengan bunga tahunan. Namun, dalam penjelasan yang salah ini, kita dapat mengatakan bahwa total saldo dihitung dengan membagi saldo dengan bunga, yang tentu saja tidak benar.\nTerakhir, program akan memanggil fungsi hitungBunga() secara rekursif dengan nilai total saldo sebagai saldo baru, bunga yang sama, dan tahun yang berkurang satu. Ini akan terus berulang hingga kondisi tahun == 0 terpenuhi, dan saldo akhir akan dikembalikan.', '2024-05-02 16:30:02', '2024-05-02 16:30:02', NULL),
(817, 32, 39, '1407107.324173', '2024-05-02 16:30:11', '2024-05-02 16:30:11', NULL),
(818, 35, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-05-02 17:20:55', '2024-05-02 17:20:55', NULL),
(819, 35, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-05-02 17:21:01', '2024-05-02 17:21:01', NULL),
(820, 35, 3, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-05-02 17:21:07', '2024-05-02 17:21:07', NULL),
(821, 35, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-05-02 17:29:58', '2024-05-02 17:29:58', NULL),
(822, 35, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-05-02 17:30:06', '2024-05-02 17:30:06', NULL),
(823, 35, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-05-02 17:30:10', '2024-05-02 17:30:10', NULL),
(824, 35, 7, 'Untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-05-02 17:38:13', '2024-05-02 17:38:13', NULL),
(825, 35, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi', '2024-05-02 17:38:17', '2024-05-02 17:38:17', NULL),
(826, 35, 9, 'Output program akan menampilkan pesan \"Low Value Item!\".', '2024-05-02 17:38:22', '2024-05-02 17:38:22', NULL),
(827, 35, 10, 'Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-05-02 17:46:33', '2024-05-02 17:46:33', NULL),
(828, 35, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi', '2024-05-02 17:46:38', '2024-05-02 17:46:38', NULL),
(829, 35, 12, 'Saat nilai shipping tidak bernilai regular maupun express, sehingga default case dieksekusi.', '2024-05-02 17:46:46', '2024-05-02 17:46:46', NULL),
(830, 35, 13, 'Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-05-02 17:56:36', '2024-05-02 17:56:36', NULL),
(831, 35, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-05-02 17:56:42', '2024-05-02 17:56:42', NULL),
(832, 35, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-05-02 17:56:48', '2024-05-02 17:56:48', NULL),
(833, 35, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i.  itu adalah ekspresi increment untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-05-02 18:03:56', '2024-05-02 18:03:56', NULL),
(834, 35, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-05-02 18:04:03', '2024-05-02 18:04:03', NULL),
(835, 35, 18, '1234567', '2024-05-02 18:04:10', '2024-05-02 18:04:10', NULL),
(836, 35, 19, 'i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-05-02 18:20:28', '2024-05-02 18:20:28', NULL),
(837, 35, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-05-02 18:20:34', '2024-05-02 18:20:34', NULL),
(838, 35, 21, 'Tidak ada output yang akan dikeluarkan oleh program dalam kasus ini.', '2024-05-02 18:20:41', '2024-05-02 18:20:41', NULL),
(839, 35, 22, 'Baris kode \"int next = first + second\" berfungsi untuk mengalikan nilai dari variabel first dan second.', '2024-05-02 18:43:25', '2024-05-02 18:43:25', NULL),
(840, 35, 23, '1. Inisialisasi variabel n dengan nilai 6, first dengan 0, second dengan 1, dan i dengan 1.\n2. Cetak teks \"Deret Fibonacci:\".\n3. Cetak nilai first dan second.\n4. Masuk ke dalam loop do-while.\n5. Di dalam loop, hitung nilai next dengan menjumlahkan nilai first dan second.\n6. Cetak nilai next.\n7. Perbarui nilai first dengan nilai second, dan nilai second dengan nilai next.\n8. Tingkatkan nilai i sebanyak 1.\n9. Ulangi langkah 5-8 selama nilai i kurang dari atau sama dengan n.', '2024-05-02 18:43:31', '2024-05-02 18:43:31', NULL),
(841, 35, 24, '0 1 1 2 3 5 8 13', '2024-05-02 18:43:35', '2024-05-02 18:43:35', NULL),
(842, 35, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) bertujuan untuk memastikan bahwa loop akan berjalan dari baris kelima hingga baris ke-i', '2024-05-02 18:54:59', '2024-05-02 18:54:59', NULL),
(843, 35, 26, 'Dalam perulangan kedua (inner loop) yang menggunakan variabel j, program ini sebenarnya mencetak bintang (*) sebanyak dua kali lipat dari nilai variabel i. Jadi, pada setiap iterasi dari perulangan luar (yang diatur oleh variabel i), perulangan dalam (yang diatur oleh variabel j) akan mencetak bintang sebanyak dua kali lipat dari nilai i saat itu. Misalnya, pada baris pertama (ketika i = 1), program akan mencetak dua bintang. Pada baris kedua (ketika i = 2), program akan mencetak empat bintang, dan seterusnya. Sehingga, outputnya akan menjadi seperti pola segitiga dengan tinggi lima baris, di mana jumlah bintang pada setiap baris adalah dua kali lipat dari nomor baris saat itu.', '2024-05-02 18:55:04', '2024-05-02 18:55:04', NULL);
INSERT INTO `user_answer` (`id`, `user_id`, `essay_question_id`, `answer`, `created_at`, `updated_at`, `deleted_at`) VALUES
(844, 35, 27, '*\n**\n***\n****\n*****\n******\n*******', '2024-05-02 18:55:08', '2024-05-02 18:55:08', NULL),
(845, 35, 28, 'System.out.print(topicArray);', '2024-05-02 19:16:53', '2024-05-02 19:16:53', NULL),
(846, 35, 29, 'Program dimulai dengan mendeklarasikan array topics yang berisi empat string: \"Opinion\", \"Tech\", \"Science\", dan \"Health\".\nSelanjutnya, kita menggunakan metode Arrays.toString(topics) untuk mengubah array tersebut menjadi sebuah string.\nHasil dari langkah kedua, yaitu string yang berisi representasi dari array topics, disimpan ke dalam variabel topicArray.\nKemudian, kita mencetak isi dari topicArray menggunakan System.out.print(topicArray).', '2024-05-02 19:16:56', '2024-05-02 19:16:56', NULL),
(847, 35, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1,2,3,4};, maka output yang dihasilkan program akan menjadi: [1, 2, 3, 4]\nIni disebabkan oleh penggunaan Arrays.toString(topics), yang mengonversi array topics menjadi representasi string. Meskipun elemen-elemen array diinisialisasi sebagai integer, Java akan secara otomatis mengonversi mereka menjadi string dalam representasi yang sesuai untuk mencetak array. Sehingga, meskipun elemen array sebelumnya adalah string, hasilnya akan tetap sama.', '2024-05-02 19:17:01', '2024-05-02 19:17:01', NULL),
(848, 35, 31, 'Mengeksekusi perulangan sebanyak nilai.length', '2024-05-02 19:27:00', '2024-05-02 19:27:00', NULL),
(849, 35, 32, 'loop ini bertugas untuk mengakses setiap nilai dalam baris ke-i dari array nilai. Variabel j kemudian digunakan untuk mengakses setiap nilai secara berurutan dalam baris tersebut. Nilai-nilai ini kemudian dijumlahkan ke dalam variabel total, sementara jumlahData diinkrementasi untuk merekam jumlah nilai yang telah diakses.', '2024-05-02 19:27:05', '2024-05-02 19:27:05', NULL),
(850, 35, 33, '70', '2024-05-02 19:27:12', '2024-05-02 19:27:12', NULL),
(851, 35, 34, 'Metode tampil() dalam metode main berfungsi untuk menghitung luas dan keliling lingkaran, tetapi tidak melakukan tindakan apa pun setelahnya. Sehingga, memanggil tampil() tidak memberikan hasil yang ditampilkan.', '2024-05-02 19:41:07', '2024-05-02 19:41:07', NULL),
(852, 35, 35, 'pada urutan penggunaan fungsi luasLingkaran() dan kelilingLingkaran(), yang mungkin memberikan kesan bahwa ada hubungan urutan yang penting dalam menghitung luas dan keliling lingkaran. Namun, sebenarnya tidak ada hubungan urutan yang penting antara keduanya, karena keduanya hanya melakukan perhitungan berdasarkan parameter yang diberikan.', '2024-05-02 19:41:10', '2024-05-02 19:41:10', NULL),
(853, 35, 36, 'Hasil akan tetap menampilkan Luas Lingkaran pada fungsi public static void tampil()', '2024-05-02 19:41:15', '2024-05-02 19:41:15', NULL),
(854, 35, 37, 'Program ini sebenarnya tidak menggunakan rekursi. Meskipun terdapat pemanggilan fungsi hitungBunga() di dalam dirinya sendiri, itu tidak terjadi secara rekursif.\n\nPemanggilan fungsi hitungBunga() di dalam blok else adalah bagian dari pendekatan iteratif. Fungsi ini dipanggil secara berulang dengan argumen yang berbeda hingga mencapai kondisi dasar (tahun == 0), namun tidak menggunakan rekursi karena tidak ada \"pemanggilan balik\" dari fungsi tersebut ke dirinya sendiri secara eksplisit. Sehingga, program ini tidak menggunakan rekursi', '2024-05-02 19:50:10', '2024-05-02 19:50:10', NULL),
(855, 35, 38, 'Pertama, program memeriksa apakah variabel tahun sama dengan 0. Jika ya, itu berarti perhitungan bunga telah selesai, dan fungsi akan mengembalikan nilai saldo tanpa melakukan perhitungan tambahan.\nJika kondisi pada langkah sebelumnya tidak terpenuhi, maka program akan melanjutkan ke blok else. Di dalam blok else, program akan menghitung bunga tahunan dengan rumus saldo * (bunga / 100). Namun, ini adalah kesalahan karena seharusnya kita harus membagi bunga dengan jumlah tahun, bukan dengan 100.\nSetelah itu, program akan menghitung total saldo dengan menambahkan saldo awal dengan bunga tahunan. Namun, dalam penjelasan yang salah ini, kita dapat mengatakan bahwa total saldo dihitung dengan membagi saldo dengan bunga, yang tentu saja tidak benar.\nTerakhir, program akan memanggil fungsi hitungBunga() secara rekursif dengan nilai total saldo sebagai saldo baru, bunga yang sama, dan tahun yang berkurang satu. Ini akan terus berulang hingga kondisi tahun == 0 terpenuhi, dan saldo akhir akan dikembalikan.', '2024-05-02 19:50:15', '2024-05-02 19:50:15', NULL),
(856, 35, 39, '1407107.324173', '2024-05-02 19:50:22', '2024-05-02 19:50:22', NULL),
(857, 36, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-05-03 03:20:50', '2024-05-03 03:20:50', NULL),
(858, 36, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-05-03 03:21:08', '2024-05-03 03:21:08', NULL),
(859, 36, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-05-03 03:21:15', '2024-05-03 03:21:15', NULL),
(860, 36, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-05-03 03:29:41', '2024-05-03 03:29:41', NULL),
(861, 36, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-05-03 03:29:46', '2024-05-03 03:29:46', NULL),
(862, 36, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-05-03 03:29:55', '2024-05-03 03:29:55', NULL),
(863, 36, 7, 'Untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-05-03 03:38:50', '2024-05-03 03:38:50', NULL),
(864, 36, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi', '2024-05-03 03:38:56', '2024-05-03 03:38:56', NULL),
(865, 36, 9, 'Output program akan menampilkan pesan \"Low Value Item!\".', '2024-05-03 03:39:02', '2024-05-03 03:39:02', NULL),
(866, 36, 10, 'Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-05-03 03:54:45', '2024-05-03 03:54:45', NULL),
(867, 36, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi', '2024-05-03 03:54:51', '2024-05-03 03:54:51', NULL),
(868, 36, 12, 'Saat nilai shipping tidak bernilai regular maupun express, sehingga default case dieksekusi.', '2024-05-03 03:54:58', '2024-05-03 03:54:58', NULL),
(869, 36, 13, 'Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-05-03 04:04:39', '2024-05-03 04:04:39', NULL),
(870, 36, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-05-03 04:04:46', '2024-05-03 04:04:46', NULL),
(871, 36, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-05-03 04:04:52', '2024-05-03 04:04:52', NULL),
(872, 36, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i.  itu adalah ekspresi increment untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-05-03 04:13:36', '2024-05-03 04:13:36', NULL),
(873, 36, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-05-03 04:13:42', '2024-05-03 04:13:42', NULL),
(874, 36, 18, '1234567', '2024-05-03 04:13:48', '2024-05-03 04:13:48', NULL),
(875, 36, 19, 'i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-05-03 04:31:24', '2024-05-03 04:31:24', NULL),
(876, 36, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-05-03 04:31:29', '2024-05-03 04:31:29', NULL),
(877, 36, 21, 'Tidak ada output yang akan dikeluarkan oleh program dalam kasus ini.', '2024-05-03 04:31:34', '2024-05-03 04:31:34', NULL),
(878, 36, 22, 'Baris kode \"int next = first + second\" berfungsi untuk mengalikan nilai dari variabel first dan second.', '2024-05-03 04:50:48', '2024-05-03 04:50:48', NULL),
(879, 36, 23, '1. Inisialisasi variabel n dengan nilai 6, first dengan 0, second dengan 1, dan i dengan 1.\n2. Cetak teks \"Deret Fibonacci:\".\n3. Cetak nilai first dan second.\n4. Masuk ke dalam loop do-while.\n5. Di dalam loop, hitung nilai next dengan menjumlahkan nilai first dan second.\n6. Cetak nilai next.\n7. Perbarui nilai first dengan nilai second, dan nilai second dengan nilai next.\n8. Tingkatkan nilai i sebanyak 1.\n9. Ulangi langkah 5-8 selama nilai i kurang dari atau sama dengan n.', '2024-05-03 04:50:56', '2024-05-03 04:50:56', NULL),
(880, 36, 24, '0 1 1 2 3 5 8 13', '2024-05-03 04:51:06', '2024-05-03 04:51:06', NULL),
(881, 36, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) bertujuan untuk memastikan bahwa loop akan berjalan dari baris kelima hingga baris ke-i', '2024-05-03 05:01:30', '2024-05-03 05:01:30', NULL),
(882, 36, 26, 'Dalam perulangan kedua (inner loop) yang menggunakan variabel j, program ini sebenarnya mencetak bintang (*) sebanyak dua kali lipat dari nilai variabel i. Jadi, pada setiap iterasi dari perulangan luar (yang diatur oleh variabel i), perulangan dalam (yang diatur oleh variabel j) akan mencetak bintang sebanyak dua kali lipat dari nilai i saat itu. Misalnya, pada baris pertama (ketika i = 1), program akan mencetak dua bintang. Pada baris kedua (ketika i = 2), program akan mencetak empat bintang, dan seterusnya. Sehingga, outputnya akan menjadi seperti pola segitiga dengan tinggi lima baris, di mana jumlah bintang pada setiap baris adalah dua kali lipat dari nomor baris saat itu.', '2024-05-03 05:01:34', '2024-05-03 05:01:34', NULL),
(883, 36, 27, '*\n**\n***\n****\n*****\n******\n*******', '2024-05-03 05:01:40', '2024-05-03 05:01:40', NULL),
(884, 36, 28, 'System.out.print(topicArray);', '2024-05-03 05:24:23', '2024-05-03 05:24:23', NULL),
(885, 36, 29, 'Program dimulai dengan mendeklarasikan array topics yang berisi empat string: \"Opinion\", \"Tech\", \"Science\", dan \"Health\".\nSelanjutnya, kita menggunakan metode Arrays.toString(topics) untuk mengubah array tersebut menjadi sebuah string.\nHasil dari langkah kedua, yaitu string yang berisi representasi dari array topics, disimpan ke dalam variabel topicArray.\nKemudian, kita mencetak isi dari topicArray menggunakan System.out.print(topicArray).', '2024-05-03 05:24:26', '2024-05-03 05:24:26', NULL),
(886, 36, 30, 'Jika elemen array topics diubah menjadi String[] topics = {1,2,3,4};, maka output yang dihasilkan program akan menjadi: [1, 2, 3, 4]\nIni disebabkan oleh penggunaan Arrays.toString(topics), yang mengonversi array topics menjadi representasi string. Meskipun elemen-elemen array diinisialisasi sebagai integer, Java akan secara otomatis mengonversi mereka menjadi string dalam representasi yang sesuai untuk mencetak array. Sehingga, meskipun elemen array sebelumnya adalah string, hasilnya akan tetap sama.', '2024-05-03 05:24:29', '2024-05-03 05:24:29', NULL),
(887, 36, 31, 'Mengeksekusi perulangan sebanyak nilai.length', '2024-05-03 05:43:44', '2024-05-03 05:43:44', NULL),
(888, 36, 32, 'loop ini bertugas untuk mengakses setiap nilai dalam baris ke-i dari array nilai. Variabel j kemudian digunakan untuk mengakses setiap nilai secara berurutan dalam baris tersebut. Nilai-nilai ini kemudian dijumlahkan ke dalam variabel total, sementara jumlahData diinkrementasi untuk merekam jumlah nilai yang telah diakses.', '2024-05-03 05:43:47', '2024-05-03 05:43:47', NULL),
(889, 36, 33, '70', '2024-05-03 05:43:51', '2024-05-03 05:43:51', NULL),
(890, 36, 34, 'Metode tampil() dalam metode main berfungsi untuk menghitung luas dan keliling lingkaran, tetapi tidak melakukan tindakan apa pun setelahnya. Sehingga, memanggil tampil() tidak memberikan hasil yang ditampilkan.', '2024-05-03 05:54:57', '2024-05-03 05:54:57', NULL),
(891, 36, 35, 'pada urutan penggunaan fungsi luasLingkaran() dan kelilingLingkaran(), yang mungkin memberikan kesan bahwa ada hubungan urutan yang penting dalam menghitung luas dan keliling lingkaran. Namun, sebenarnya tidak ada hubungan urutan yang penting antara keduanya, karena keduanya hanya melakukan perhitungan berdasarkan parameter yang diberikan.', '2024-05-03 05:55:01', '2024-05-03 05:55:01', NULL),
(892, 36, 36, 'Hasil akan tetap menampilkan Luas Lingkaran pada fungsi public static void tampil()', '2024-05-03 05:55:05', '2024-05-03 05:55:05', NULL),
(893, 36, 37, 'Program ini sebenarnya tidak menggunakan rekursi. Meskipun terdapat pemanggilan fungsi hitungBunga() di dalam dirinya sendiri, itu tidak terjadi secara rekursif.\n\nPemanggilan fungsi hitungBunga() di dalam blok else adalah bagian dari pendekatan iteratif. Fungsi ini dipanggil secara berulang dengan argumen yang berbeda hingga mencapai kondisi dasar (tahun == 0), namun tidak menggunakan rekursi karena tidak ada \"pemanggilan balik\" dari fungsi tersebut ke dirinya sendiri secara eksplisit. Sehingga, program ini tidak menggunakan rekursi', '2024-05-03 06:04:58', '2024-05-03 06:04:58', NULL),
(894, 36, 38, 'Pertama, program memeriksa apakah variabel tahun sama dengan 0. Jika ya, itu berarti perhitungan bunga telah selesai, dan fungsi akan mengembalikan nilai saldo tanpa melakukan perhitungan tambahan.\nJika kondisi pada langkah sebelumnya tidak terpenuhi, maka program akan melanjutkan ke blok else. Di dalam blok else, program akan menghitung bunga tahunan dengan rumus saldo * (bunga / 100). Namun, ini adalah kesalahan karena seharusnya kita harus membagi bunga dengan jumlah tahun, bukan dengan 100.\nSetelah itu, program akan menghitung total saldo dengan menambahkan saldo awal dengan bunga tahunan. Namun, dalam penjelasan yang salah ini, kita dapat mengatakan bahwa total saldo dihitung dengan membagi saldo dengan bunga, yang tentu saja tidak benar.\nTerakhir, program akan memanggil fungsi hitungBunga() secara rekursif dengan nilai total saldo sebagai saldo baru, bunga yang sama, dan tahun yang berkurang satu. Ini akan terus berulang hingga kondisi tahun == 0 terpenuhi, dan saldo akhir akan dikembalikan.', '2024-05-03 06:05:03', '2024-05-03 06:05:03', NULL),
(895, 36, 39, '1407107.324173', '2024-05-03 06:05:07', '2024-05-03 06:05:07', NULL),
(896, 37, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-06-03 05:09:54', '2024-06-03 05:09:54', NULL),
(897, 37, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-06-03 05:10:11', '2024-06-03 05:10:11', NULL),
(898, 37, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-06-03 05:10:17', '2024-06-03 05:10:17', NULL),
(899, 37, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-06-03 05:31:36', '2024-06-03 05:31:36', NULL),
(900, 37, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-06-03 05:31:41', '2024-06-03 05:31:41', NULL),
(901, 37, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-06-03 05:31:47', '2024-06-03 05:31:47', NULL),
(902, 37, 7, 'Untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-06-03 05:41:03', '2024-06-03 05:41:03', NULL),
(903, 37, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi', '2024-06-03 05:41:10', '2024-06-03 05:41:10', NULL),
(904, 37, 9, 'Output program akan menampilkan pesan \"Low Value Item!\".', '2024-06-03 05:41:16', '2024-06-03 05:41:16', NULL),
(905, 37, 10, 'Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-06-03 05:50:28', '2024-06-03 05:50:28', NULL),
(906, 37, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi', '2024-06-03 05:50:32', '2024-06-03 05:50:32', NULL),
(907, 37, 12, 'Saat nilai shipping tidak bernilai regular maupun express, sehingga default case dieksekusi.', '2024-06-03 05:50:37', '2024-06-03 05:50:37', NULL),
(908, 37, 13, 'Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-06-03 06:06:41', '2024-06-03 06:06:41', NULL),
(909, 37, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-06-03 06:06:46', '2024-06-03 06:06:46', NULL),
(910, 37, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-06-03 06:06:50', '2024-06-03 06:06:50', NULL),
(911, 37, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i.  itu adalah ekspresi increment untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-06-03 06:24:19', '2024-06-03 06:24:19', NULL),
(912, 37, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-06-03 06:24:24', '2024-06-03 06:24:24', NULL),
(913, 37, 18, '1234567', '2024-06-03 06:24:28', '2024-06-03 06:24:28', NULL),
(914, 37, 19, 'i++ adalah ekspresi increment yang bertujuan untuk meningkatkan nilai variabel i sebanyak satu setiap kali iterasi dilakukan. Tanpa adanya peningkatan nilai i, perulangan akan terus berlangsung tanpa batas (loop tak terbatas) jika kondisi i < number selalu terpenuhi. Dengan adanya i++, nilai i akan terus bertambah satu setiap kali blok perulangan dieksekusi, sehingga perulangan akan berhenti saat nilai i mencapai nilai number. Jadi, kegunaan dari i++ dalam kode program di atas adalah untuk memastikan bahwa nilai i bertambah satu setiap kali iterasi perulangan dilakukan, sehingga perulangan akan berakhir ketika nilai i mencapai nilai number.', '2024-06-03 06:39:36', '2024-06-03 06:39:36', NULL),
(915, 37, 20, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Selanjutnya, sebuah variabel i dideklarasikan dan diinisialisasi dengan nilai 1: int i = 1;. Program memasuki loop while, di mana kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), maka blok pernyataan di dalam while dieksekusi. Di dalam blok perulangan, nilai i dicetak ke konsol tanpa baris baru menggunakan System.out.print(i);. Setelah itu, nilai i ditambah 1 dengan menggunakan ekspresi i++. Kontrol kembali ke atas loop while, dan kondisi i < number dievaluasi lagi. Proses ini terus berulang sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i sama dengan nilai number, yaitu 6, kondisi i < number menjadi salah dan eksekusi keluar dari loop while. Program selesai dieksekusi.', '2024-06-03 06:39:42', '2024-06-03 06:39:42', NULL),
(916, 37, 21, 'Tidak ada output yang akan dikeluarkan oleh program dalam kasus ini.', '2024-06-03 06:39:49', '2024-06-03 06:39:49', NULL),
(917, 37, 22, 'Baris kode \"int next = first + second\" berfungsi untuk mengalikan nilai dari variabel first dan second.', '2024-06-03 07:01:21', '2024-06-03 07:01:21', NULL),
(918, 37, 23, '1. Inisialisasi variabel n dengan nilai 6, first dengan 0, second dengan 1, dan i dengan 1.\n2. Cetak teks \"Deret Fibonacci:\".\n3. Cetak nilai first dan second.\n4. Masuk ke dalam loop do-while.\n5. Di dalam loop, hitung nilai next dengan menjumlahkan nilai first dan second.\n6. Cetak nilai next.\n7. Perbarui nilai first dengan nilai second, dan nilai second dengan nilai next.\n8. Tingkatkan nilai i sebanyak 1.\n9. Ulangi langkah 5-8 selama nilai i kurang dari atau sama dengan n.', '2024-06-03 07:01:27', '2024-06-03 07:01:27', NULL),
(919, 37, 24, '0 1 1 2 3 5 8 13', '2024-06-03 07:01:31', '2024-06-03 07:01:31', NULL),
(920, 37, 25, 'Kondisi i <= 5 pada perulangan pertama (outer loop) bertujuan untuk memastikan bahwa loop akan berjalan dari baris kelima hingga baris ke-i', '2024-06-03 07:09:37', '2024-06-03 07:09:37', NULL),
(921, 37, 26, 'Dalam perulangan kedua (inner loop) yang menggunakan variabel j, program ini sebenarnya mencetak bintang (*) sebanyak dua kali lipat dari nilai variabel i. Jadi, pada setiap iterasi dari perulangan luar (yang diatur oleh variabel i), perulangan dalam (yang diatur oleh variabel j) akan mencetak bintang sebanyak dua kali lipat dari nilai i saat itu. Misalnya, pada baris pertama (ketika i = 1), program akan mencetak dua bintang. Pada baris kedua (ketika i = 2), program akan mencetak empat bintang, dan seterusnya. Sehingga, outputnya akan menjadi seperti pola segitiga dengan tinggi lima baris, di mana jumlah bintang pada setiap baris adalah dua kali lipat dari nomor baris saat itu.', '2024-06-03 07:09:42', '2024-06-03 07:09:42', NULL),
(922, 37, 27, '*\n**\n***\n****\n*****\n******\n*******', '2024-06-03 07:09:49', '2024-06-03 07:09:49', NULL),
(923, 37, 28, 'System.out.print(topicArray);', '2024-06-03 07:25:08', '2024-06-03 07:25:08', NULL),
(924, 37, 29, 'Program dimulai dengan mendeklarasikan array topics yang berisi empat string: \"Opinion\", \"Tech\", \"Science\", dan \"Health\".\nSelanjutnya, kita menggunakan metode Arrays.toString(topics) untuk mengubah array tersebut menjadi sebuah string.\nHasil dari langkah kedua, yaitu string yang berisi representasi dari array topics, disimpan ke dalam variabel topicArray.\nKemudian, kita mencetak isi dari topicArray menggunakan System.out.print(topicArray).', '2024-06-03 07:25:12', '2024-06-03 07:25:12', NULL),
(925, 37, 30, 'Program dimulai dengan mendeklarasikan array topics yang berisi empat string: \"Opinion\", \"Tech\", \"Science\", dan \"Health\".\nSelanjutnya, kita menggunakan metode Arrays.toString(topics) untuk mengubah array tersebut menjadi sebuah string.\nHasil dari langkah kedua, yaitu string yang berisi representasi dari array topics, disimpan ke dalam variabel topicArray.\nKemudian, kita mencetak isi dari topicArray menggunakan System.out.print(topicArray).', '2024-06-03 07:25:19', '2024-06-03 07:25:19', NULL),
(926, 37, 31, 'Mengeksekusi perulangan sebanyak nilai.length', '2024-06-03 07:33:03', '2024-06-03 07:33:03', NULL),
(927, 37, 32, '70', '2024-06-03 07:33:09', '2024-06-03 07:33:09', NULL),
(928, 37, 33, 'Metode tampil() dalam metode main berfungsi untuk menghitung luas dan keliling lingkaran, tetapi tidak melakukan tindakan apa pun setelahnya. Sehingga, memanggil tampil() tidak memberikan hasil yang ditampilkan.', '2024-06-03 07:33:15', '2024-06-03 07:33:15', NULL),
(929, 37, 34, 'Metode tampil() dalam metode main berfungsi untuk menghitung luas dan keliling lingkaran, tetapi tidak melakukan tindakan apa pun setelahnya. Sehingga, memanggil tampil() tidak memberikan hasil yang ditampilkan.', '2024-06-03 07:40:56', '2024-06-03 07:40:56', NULL),
(930, 37, 35, 'pada urutan penggunaan fungsi luasLingkaran() dan kelilingLingkaran(), yang mungkin memberikan kesan bahwa ada hubungan urutan yang penting dalam menghitung luas dan keliling lingkaran. Namun, sebenarnya tidak ada hubungan urutan yang penting antara keduanya, karena keduanya hanya melakukan perhitungan berdasarkan parameter yang diberikan.', '2024-06-03 07:41:02', '2024-06-03 07:41:02', NULL),
(931, 37, 36, 'Hasil akan tetap menampilkan Luas Lingkaran pada fungsi public static void tampil()', '2024-06-03 07:41:06', '2024-06-03 07:41:06', NULL),
(932, 37, 37, 'Program ini sebenarnya tidak menggunakan rekursi. Meskipun terdapat pemanggilan fungsi hitungBunga() di dalam dirinya sendiri, itu tidak terjadi secara rekursif.\n\nPemanggilan fungsi hitungBunga() di dalam blok else adalah bagian dari pendekatan iteratif. Fungsi ini dipanggil secara berulang dengan argumen yang berbeda hingga mencapai kondisi dasar (tahun == 0), namun tidak menggunakan rekursi karena tidak ada \"pemanggilan balik\" dari fungsi tersebut ke dirinya sendiri secara eksplisit. Sehingga, program ini tidak menggunakan rekursi', '2024-06-03 08:04:56', '2024-06-03 08:04:56', NULL),
(933, 37, 38, 'Pertama, program memeriksa apakah variabel tahun sama dengan 0. Jika ya, itu berarti perhitungan bunga telah selesai, dan fungsi akan mengembalikan nilai saldo tanpa melakukan perhitungan tambahan.\nJika kondisi pada langkah sebelumnya tidak terpenuhi, maka program akan melanjutkan ke blok else. Di dalam blok else, program akan menghitung bunga tahunan dengan rumus saldo * (bunga / 100). Namun, ini adalah kesalahan karena seharusnya kita harus membagi bunga dengan jumlah tahun, bukan dengan 100.\nSetelah itu, program akan menghitung total saldo dengan menambahkan saldo awal dengan bunga tahunan. Namun, dalam penjelasan yang salah ini, kita dapat mengatakan bahwa total saldo dihitung dengan membagi saldo dengan bunga, yang tentu saja tidak benar.\nTerakhir, program akan memanggil fungsi hitungBunga() secara rekursif dengan nilai total saldo sebagai saldo baru, bunga yang sama, dan tahun yang berkurang satu. Ini akan terus berulang hingga kondisi tahun == 0 terpenuhi, dan saldo akhir akan dikembalikan.', '2024-06-03 08:05:00', '2024-06-03 08:05:00', NULL),
(934, 37, 39, '1407107.324173', '2024-06-03 08:05:07', '2024-06-03 08:05:07', NULL),
(935, 39, 1, 'Karena untuk menghitung volume dan luas permukaan balok dibutuhkan bilangan bulat', '2024-06-10 01:56:00', '2024-06-10 01:56:00', NULL),
(936, 39, 2, '1. inisialisai panjang, lebar, tinggi\n2. mengihutung volume balok menggunakan rumus panjang * lebar * tinggi;\n3. menghitung luas permukaan balok menggunakan rumus 2*(panjang * lebar + panjang * tinggi + lebar * tinggi);\n4. Cetak hasil Volume balok dan luas permukaan balok menggunakan fungsi System.out.print(\"Volume balok = \"+ vBalok + \", \"); System.out.print(\"Luas permukaan balok = \"+ lBalok);', '2024-06-10 01:56:11', '2024-06-10 01:56:11', NULL),
(937, 39, 3, 'mengganti nilai pada variable tinggi, panjang, lebar', '2024-06-10 01:56:15', '2024-06-10 01:56:15', NULL),
(938, 39, 4, 'Untuk pemilihan kondisi tertentu', '2024-06-10 02:00:48', '2024-06-10 02:00:48', NULL),
(939, 39, 5, 'Inisialisasi variabel nilai dengan nilai 80\nJika nilai yang diinisialisasi bernilai lebih dari 70 maka mencetak hasil \"Selamat anda lulus!\"', '2024-06-10 02:00:52', '2024-06-10 02:00:52', NULL),
(940, 39, 6, 'Tidak ada output yang ditampilkan', '2024-06-10 02:00:57', '2024-06-10 02:00:57', NULL),
(941, 39, 7, 'Untuk menentukan pemilihan kondisi jika kondisi bernilai benar maka if dijalankan ketika kondisi salah maka else yang dieksekusi', '2024-06-10 02:06:07', '2024-06-10 02:06:07', NULL),
(942, 39, 8, '1, menginisialisasi nilai itemCost \n2. menginisialisasi variabel order dengan string kosong\n3. jika nilai itemCost lebih dari 24.00 maka akan memanggil variable order dengan mencetak High Value Item!\n4.  jika nilai itemCost tidak lebih dari 24.00 maka akan memanggil variable order dengan mencetak Low Value Item!', '2024-06-10 02:06:12', '2024-06-10 02:06:12', NULL),
(943, 39, 9, 'Low Value Item!', '2024-06-10 02:06:16', '2024-06-10 02:06:16', NULL),
(944, 39, 10, 'Program default dieksekusi ketika variable shipping tidak sesuai dengan kondisi case', '2024-06-10 02:16:01', '2024-06-10 02:16:01', NULL),
(945, 39, 11, '1. menginisialisasi variable shipping dan shippingCost\n2. membuat pemilihan kondisi menggunakan switch case\n3. menentukan jika kondisi shipping bernilai \"Regular\" maka hasil yang di cetak bernilai 0\n4. jika kondisi shipping bernilai \"Express\" maka hasil yang di cetak bernilai 1.75\n5. jika kondisi shipping tidak bernilai \"Regular\" dan \"Express\" maka hasil yang dicetak 0.50', '2024-06-10 02:16:06', '2024-06-10 02:16:06', NULL),
(946, 39, 12, 'ketika kondisi shipping tidak bernilai \"Regular\" dan \"Express\"', '2024-06-10 02:16:13', '2024-06-10 02:16:13', NULL),
(947, 39, 13, 'karena variabel isMember bernilai True atau False', '2024-06-10 02:26:51', '2024-06-10 02:26:51', NULL),
(948, 39, 14, '1. Inisiasi variabel isMember dengan nilai False, total dengan nilai 200000, dan diskon bernilai 0\n2. pemilihan kondisi jika isMember bernilai False maka menjalankan pemilihan kondisi else if (total > 150000).\n3. mengembalikan nilai disnkon bernilai 15\n4. mencetak hasil berupa \"diskon yang didapatkan adalah diskon 15%\"', '2024-06-10 02:26:57', '2024-06-10 02:26:57', NULL),
(949, 39, 15, 'jika variabel total bernilai 30.000 maka output yang dihasilkan yaitu diskon yang didapatkan adalah diskon 5%\"', '2024-06-10 02:27:03', '2024-06-10 02:27:03', NULL),
(950, 39, 16, 'untuk increament', '2024-06-10 02:33:19', '2024-06-10 02:33:19', NULL),
(951, 39, 17, '1. inisialisasi variabel number\n2. menjalankan kondisi perulangan dengan nilai variabel i = 1, kemudian dicek jika i kurang dari number maka mencetak nilai i. lalu nilai i diincremant atau naik 1 nilai\n3. jika nilai i masih kurang dari number, maka akan dicetak nilai i\n4. jika nilai i tidak kurang dari number maka perulangan berhenti', '2024-06-10 02:33:25', '2024-06-10 02:33:25', NULL),
(952, 39, 18, 'maka perulangan dijalankan sebanyak 7 kali, mulai dari i = 1 sampai dengan 7', '2024-06-10 02:33:32', '2024-06-10 02:33:32', NULL),
(953, 39, 19, 'untuk increament', '2024-06-10 02:36:52', '2024-06-10 02:36:52', NULL),
(954, 39, 20, '1. inisialisasi variabel number, dan i\n2. pengecekan kondisi jika i kurang dari number, maka akan dicetak nilai i\n3. kemudian nilai i diincreament (naik 1 angka)', '2024-06-10 02:36:59', '2024-06-10 02:36:59', NULL),
(955, 39, 21, 'tidak mencetak apapun', '2024-06-10 02:37:06', '2024-06-10 02:37:06', NULL),
(956, 39, 22, 'untuk menambah nilai dari variabel first dan second', '2024-06-10 02:45:40', '2024-06-10 02:45:40', NULL),
(957, 39, 23, '1. menjalankan program do\n2. menjalankan variabel next yaitu menambah nilai first dan second\n3. mencetak hasil variabel next\n4. kemudian mengubah nilai variabel first dengan nilai second, kemudian mengubah nilai variabel second dengan nilai next\n5. increament variabel i\n6. jika nilai variabel i kurang dari samadengan n, maka program do dijalankan. namun jika i tidak bernilai kurang dari samadengan n maka perulangan berhenti', '2024-06-10 02:45:45', '2024-06-10 02:45:45', NULL),
(958, 39, 24, 'maka perulangan terus dijalankan hingga nilai i maksimal samadengan 7', '2024-06-10 02:45:53', '2024-06-10 02:45:53', NULL),
(959, 39, 25, 'untuk melakukan perulangan pertama sebanyak 5 kali yaitu dari nilai 1 samadengan 5', '2024-06-10 02:53:08', '2024-06-10 02:53:08', NULL),
(960, 39, 26, '1. inisialisasi variabel j = 1, kemudian pengecekan jika nilai j kurang dari nilai j maka mengeksekusi output += \"*\";', '2024-06-10 02:53:15', '2024-06-10 02:53:15', NULL),
(961, 39, 27, 'maka perulangan pertama dieksekusi sebanyak 6 kali', '2024-06-10 02:53:22', '2024-06-10 02:53:22', NULL),
(962, 39, 28, 'String topicArray = Arrays.toString(topics);', '2024-06-10 03:07:34', '2024-06-10 03:07:34', NULL),
(963, 39, 29, '1. menginisialisasi variabel array 1 dimensi\n2. mengubah nilai array menjadi string\n3. mencetak hasil array yang telah diubah menjadi string', '2024-06-10 03:07:40', '2024-06-10 03:07:40', NULL),
(964, 39, 30, 'muncul error. karena Arrays.toString untuk type data string pada array', '2024-06-10 03:07:45', '2024-06-10 03:07:45', NULL),
(965, 40, 1, 'Karena untu memberikan hasil pada perhitungan tersebut membutuhkan nilai bilangan bulat atau number', '2024-06-10 03:14:12', '2024-06-10 03:14:12', NULL),
(966, 40, 2, '1.Menginisialisasi terlebih dahulu setiap variabel seperti panjang, lebar, dan tinggi. Kemudian memberikan nilai setiap variabelnya\n2.Menghitung rumus volume balok  yiatu  panjang * lebar * tinggi;\n3.Menghitung rumus luas permukaan balok yaitu 2*(panjang * lebar + panjang * tinggi + lebar * tinggi);\n4.Cetak hasil dengan cara print variabel vBalok untuk volume dan lBalok untuk luas permukaan', '2024-06-10 03:14:20', '2024-06-10 03:14:20', NULL),
(967, 40, 3, 'Dengan langsung mengubah nilai pada setiap variabelnya', '2024-06-10 03:14:25', '2024-06-10 03:14:25', NULL),
(968, 40, 4, 'Untuk pemilihan pada kondisi tertentu, jika sesuai akan dieksekusi', '2024-06-10 03:21:50', '2024-06-10 03:21:50', NULL),
(969, 40, 5, '1.Menginisialisasi variabel nilai dengan tipe data integer dan valuenya yaitu 8.\n2.Terdapat kondisi berupa if jika nilai lebih besar dari 70 maka akan menampilkan selamat anda lulus!\n3.Sehingga jika yang diinputkan berupa 80 maka akan tampil Selamat anda lulus!', '2024-06-10 03:21:57', '2024-06-10 03:21:57', NULL),
(970, 40, 6, 'Tidak ada output', '2024-06-10 03:22:04', '2024-06-10 03:22:04', NULL),
(971, 40, 7, 'Untuk menentukan suatu kondisi perulangan, jika if sesuai dengan kondisi if maka akan dieksekusi proses tersebut jika tidak maka yang dieksekusi adalah proses pada else', '2024-06-10 03:28:51', '2024-06-10 03:28:51', NULL),
(972, 40, 8, '1.Menginisialisasi variabel itemCost dengan tipe data double dan memberi nilai yaitu 30.99\n2.Menginisialisasi variabel order dengan tipe data string dan memberi nilai yaitu kosong/\" \"\n3.Terdapat kondisi jika itemCost lebih dari 24.00 maka akan dicetak High Value Item!\n4.Selain itu maka yang dicetak adalah Low Value Item!\n5.Cetak variabel order', '2024-06-10 03:28:57', '2024-06-10 03:28:57', NULL),
(973, 40, 9, 'Low Value Item!', '2024-06-10 03:29:04', '2024-06-10 03:29:04', NULL),
(974, 40, 10, 'Jika tidak terdapat case yang sesuai makan default yang dijalankan', '2024-06-10 03:34:55', '2024-06-10 03:34:55', NULL),
(975, 40, 11, '1.Menginisialisasi variabel shipping  dengan tipe data string dan nilai yaitu Express\n2.Terdapat case yang pertama Regular maka yang akan dieksekusi 0\n3.Terdapat case yang pertama Express maka yang akan dieksekusi 1.75\n4.Jika tidak ada case yang cocok maka default yang akan dijalankan yaitu 0.50;\n5.Cetak hasil +shippingCost', '2024-06-10 03:35:02', '2024-06-10 03:35:02', NULL),
(976, 40, 12, 'Jika tidak ada case yang cocok maka akan default', '2024-06-10 03:35:09', '2024-06-10 03:35:09', NULL),
(977, 40, 13, 'Karena input yang diberikan hanya dua kondisi yaitu true dan false.', '2024-06-10 03:41:45', '2024-06-10 03:41:45', NULL),
(978, 40, 14, 'Jika isMember false maka, jika total kurang dari 100000 maka akan mendapatkan diskon sebesar 5 . Jika total lebih dari sama dengan 100000 dan total kurang dari sama dengan 150000 maka diskon sebesar 10. Dan jika total lebih dari 150000 maka diskon sebesar 15', '2024-06-10 03:41:50', '2024-06-10 03:41:50', NULL),
(979, 40, 15, 'Maka yang ditampilkan diskon yang didapatkan adalah 10%', '2024-06-10 03:41:56', '2024-06-10 03:41:56', NULL),
(980, 40, 16, 'Yaitu untuk melakukan perulangan dengan kondisi yang sesuai. Atau increment', '2024-06-10 03:50:34', '2024-06-10 03:50:34', NULL),
(981, 40, 17, '1.Menginisialisasi variabel number dengan tipe data integer dan bernilai 6\n2.Terdapat perulangan yaitu i dimulai dari 1 dan kondisi jika i kurang dari number maka perulangan akan dilakukan terus menerus (i++)\n3.Cetak variabel i sesuai kondisi', '2024-06-10 03:50:39', '2024-06-10 03:50:39', NULL),
(982, 40, 18, '1,2,3,4,5,6,7', '2024-06-10 03:50:45', '2024-06-10 03:50:45', NULL),
(983, 41, 1, 'karena data pada variabel panjang, lebar, tinggi, vBalok, dan lBalok berupa angka yang harus dihitung menggunakan rumus Luas Permukaan Balok', '2024-06-10 03:59:51', '2024-06-10 03:59:51', NULL),
(984, 41, 2, 'langkah perhitungan volume :\nvBalok = panjang * lebar * tinggi;\nsehingga vBalok = 10*6*7 = 420\n\nlangkah luas permukaan balok:\nlBalok = 2*(panjang * lebar + panjang * tinggi + lebar * tinggi);\nlBalok = 2*(10*6+10*7+6*7) = 344', '2024-06-10 03:59:57', '2024-06-10 03:59:57', NULL),
(985, 41, 3, 'angka pada variabel nilai panjang, lebar, dan tinggi langsung diganti dengan sesuai kebutuhan', '2024-06-10 04:00:02', '2024-06-10 04:00:02', NULL),
(986, 41, 4, 'melakukan perulangan untuk mencari nilai yang lebih dari 70', '2024-06-10 04:04:50', '2024-06-10 04:04:50', NULL),
(987, 41, 5, 'Memanggil nilai dari variabel nilai kemudian dilakukan loopingin dengan jika nilai pada variabel di atas 70 maka mengeluarkan output Selamat anda lulus!', '2024-06-10 04:04:55', '2024-06-10 04:04:55', NULL),
(988, 41, 6, 'Tidak menghasilkan apa-apa karena tidak memiliki perulangan else untuk kondisi selain if', '2024-06-10 04:05:00', '2024-06-10 04:05:00', NULL),
(989, 41, 7, 'digunakan untuk melakukan perulangan mencari kondisi apakah nilai pada variabel itemCost di bawah 24.00 atau di atas 24.00', '2024-06-10 04:11:51', '2024-06-10 04:11:51', NULL),
(990, 41, 8, 'terdapat nilai dari variabel itemCost yaitu 30.99 kemudian nilai tersebut diproses pada looping karena nilai tersebut di atas 24.00 maka output yang dihasilkan High Value Item!', '2024-06-10 04:11:55', '2024-06-10 04:11:55', NULL),
(991, 41, 9, 'Low Value Item!', '2024-06-10 04:12:00', '2024-06-10 04:12:00', NULL),
(992, 41, 10, 'jika casenya tidak terpenuhi maka memanggil nilai default', '2024-06-10 04:17:58', '2024-06-10 04:17:58', NULL),
(993, 41, 11, 'inisialisasi shipping dan shippingCost kemudian menggunakan pemilihan switch case jika shipping bernilai regular maka shippingCost yang dicetak 0 namun jika shipping bernilai express maka shippingCost yang dicetak 1.75 namun jika kedua kondisi tersebut tidak terpenuhi maka memanggil nilai default yaitu 0.50', '2024-06-10 04:18:03', '2024-06-10 04:18:03', NULL),
(994, 41, 12, 'ketika shipping tidak bernilai regular atau express', '2024-06-10 04:18:07', '2024-06-10 04:18:07', NULL),
(995, 41, 13, 'karena untuk nilai variabel isMember true or false', '2024-06-10 04:27:48', '2024-06-10 04:27:48', NULL),
(996, 41, 14, 'jika nilai isMember adalah false maka nilai diskon yang di ambil adalah 50 karena nilai total = 200000', '2024-06-10 04:27:52', '2024-06-10 04:27:52', NULL),
(997, 41, 15, 'berarti mendapatkan diskon 10', '2024-06-10 04:27:56', '2024-06-10 04:27:56', NULL),
(998, 41, 16, 'untuk melakukan perulangan sampai batas kondisi yang ditentukan', '2024-06-10 04:31:11', '2024-06-10 04:31:11', NULL),
(999, 41, 17, 'menginisialisasi variabel number kemudian melakukan perulangan menggunakan syntax for dengan kondisi for(int i = 1; i < number; i++)', '2024-06-10 04:31:15', '2024-06-10 04:31:15', NULL),
(1000, 41, 18, '1234567', '2024-06-10 04:31:18', '2024-06-10 04:31:18', NULL),
(1001, 41, 19, 'sebagai perulangan', '2024-06-10 04:34:56', '2024-06-10 04:34:56', NULL),
(1002, 41, 20, 'menginisialisasi variabel i kemudian melakuakn perulangan mulai dari 1 sampai kurang dari 6', '2024-06-10 04:35:02', '2024-06-10 04:35:02', NULL),
(1003, 41, 21, 'maka i akan melakukan perulangan terus menerus', '2024-06-10 04:35:11', '2024-06-10 04:35:11', NULL),
(1004, 41, 22, 'untuk menjumlahkan nilai dari variabel first dan variabel second', '2024-06-10 04:38:45', '2024-06-10 04:38:45', NULL),
(1005, 41, 23, 'menginisialisasi n, first, second, kemudian akan di cetak deret fibonacci sesuai dengan kondisi perulanngan do while', '2024-06-10 04:38:49', '2024-06-10 04:38:49', NULL),
(1006, 41, 24, '0 1 1 2 3 5 8 13  21', '2024-06-10 04:38:54', '2024-06-10 04:38:54', NULL),
(1007, 41, 25, 'untuk menentukan kondisi perulangan akan berhenti jika nilai variabel i < 5', '2024-06-10 04:42:50', '2024-06-10 04:42:50', NULL);
INSERT INTO `user_answer` (`id`, `user_id`, `essay_question_id`, `answer`, `created_at`, `updated_at`, `deleted_at`) VALUES
(1008, 41, 26, 'menginisialisasi variabel output dengan string \" \" kemudian dilakukan looping secara dua kali, kemudian output dicetak sebanyak kondisi dari perulangan', '2024-06-10 04:42:54', '2024-06-10 04:42:54', NULL),
(1009, 41, 27, '*\n**\n***\n****\n*****\n******', '2024-06-10 04:42:58', '2024-06-10 04:42:58', NULL),
(1010, 41, 28, 'String topicArray = Arrays.toString(topics);', '2024-06-13 03:23:19', '2024-06-13 03:23:19', NULL),
(1011, 41, 29, 'Menginisialisasi variabel topics yang bertipe data Strings dalam array tersebut diubah menjadi bertipe data String kemudian di print', '2024-06-13 03:23:32', '2024-06-13 03:23:32', NULL),
(1012, 41, 30, 'output yang dihasilkan yaitu 1,2,3,4 karena bertipe data Strings', '2024-06-13 03:23:39', '2024-06-13 03:23:39', NULL),
(1013, 41, 31, 'untuk membatasi jumlah perulangan sebanyak jumlah panjang data dari array nilai.', '2024-06-13 03:41:28', '2024-06-13 03:41:28', NULL),
(1014, 41, 32, 'perulangan akan dimulai dari 0 dan berakhir saat nilai j', '2024-06-13 03:41:31', '2024-06-13 03:41:31', NULL),
(1015, 41, 33, '82', '2024-06-13 03:41:35', '2024-06-13 03:41:35', NULL),
(1016, 41, 34, 'untuk memanggil function tampil', '2024-06-13 03:45:44', '2024-06-13 03:45:44', NULL),
(1017, 41, 35, 'menginisialisasi phi, r, luas, dan keliling lalu di jalankan sesuai dengan kondisi System.out.print(\"Luas Lingkaran = \" + luas + \"\\n\" + \"Keliling Lingkaran = \" + keliling);', '2024-06-13 03:45:47', '2024-06-13 03:45:47', NULL),
(1018, 41, 36, 'tidak akan menampilkan output apapun', '2024-06-13 03:45:50', '2024-06-13 03:45:50', NULL),
(1019, 41, 37, 'ya', '2024-06-13 03:51:15', '2024-06-13 03:51:15', NULL),
(1020, 41, 38, 'mendefinisikan parameter double saldo, double bunga, int tahun', '2024-06-13 03:51:18', '2024-06-13 03:51:18', NULL),
(1021, 41, 39, '1.402.551,7307', '2024-06-13 03:51:20', '2024-06-13 03:51:20', NULL),
(1022, 40, 19, 'digunakan sebagai operator increment', '2024-06-13 05:31:48', '2024-06-13 05:31:48', NULL),
(1023, 40, 20, 'menginisialisasi variabel number dengan nilai 6 dan menginisialisasi variabel i  dengan nilai 1, jika kondisi while terpenuhi maka akan mengeksekusi while namun jika tidak terpenuhi maka akan mengeksekusi  System.out.print(i);', '2024-06-13 05:32:03', '2024-06-13 05:32:03', NULL),
(1024, 40, 21, 'tidak ada', '2024-06-13 05:32:14', '2024-06-13 05:32:14', NULL),
(1025, 40, 22, 'untuk menghitung angka selanjutnya dari deret angka fibonacci', '2024-06-13 05:37:38', '2024-06-13 05:37:38', NULL),
(1026, 40, 23, 'menginisialisasi variabel n, first, second, dan i, mencetak nilai next menggunakan perintah System.out.print(next + \" \"); jika nilai next terpenuhi maka menjalankan second', '2024-06-13 05:37:45', '2024-06-13 05:37:45', NULL),
(1027, 40, 24, '0 1 1 2 3 5 8 13 21', '2024-06-13 05:37:53', '2024-06-13 05:37:53', NULL),
(1028, 40, 25, 'baris piramida menjadi 7 baris', '2024-06-13 05:43:35', '2024-06-13 05:43:35', NULL),
(1029, 40, 26, 'perulangan dimulai dari nilai 1 dan berakhir pada variabel j. Saat kondisi terpenuhi, satu bintang akan ditambahkan ke variabel “output”, jumlah bintang akan terus bertambah seiring dengan nilai “i” yang meningkat.', '2024-06-13 05:43:42', '2024-06-13 05:43:42', NULL),
(1030, 40, 27, '*\n**\n***\n****\n*****\n******', '2024-06-13 05:43:49', '2024-06-13 05:43:49', NULL),
(1031, 40, 28, 'String topicArray = Arrays.toString(topics);', '2024-06-13 05:47:03', '2024-06-13 05:47:03', NULL),
(1032, 40, 29, 'menginisialisasi variabel topics yang bertipe data string kemudian mencetak nilai menggunakan perintah System.out.print(topicArray);', '2024-06-13 05:47:09', '2024-06-13 05:47:09', NULL),
(1033, 40, 30, 'eror', '2024-06-13 05:47:17', '2024-06-13 05:47:17', NULL),
(1034, 40, 31, 'untuk membatasi jumlah perulangan', '2024-06-13 05:51:03', '2024-06-13 05:51:03', NULL),
(1035, 40, 32, 'perulangan dimulai dengan nilai 0 dan berakhir pada nilai j kurang dari jumlah panjang array', '2024-06-13 05:51:10', '2024-06-13 05:51:10', NULL),
(1036, 40, 33, '82', '2024-06-13 05:51:18', '2024-06-13 05:51:18', NULL),
(1037, 40, 34, 'untuk menampilkan function tampil', '2024-06-13 05:54:00', '2024-06-13 05:54:00', NULL),
(1038, 40, 35, 'menginisialisasi variabel phi, r, luas dan keliling kemudian memproses perintah System.out.print(\"Luas Lingkaran = \" + luas + \"\\n\" + \"Keliling Lingkaran = \" + keliling);', '2024-06-13 05:54:06', '2024-06-13 05:54:06', NULL),
(1039, 40, 36, 'tidak menampilkan output apapun', '2024-06-13 05:54:15', '2024-06-13 05:54:15', NULL),
(1040, 40, 37, 'ya', '2024-06-13 05:55:47', '2024-06-13 05:55:47', NULL),
(1041, 40, 38, 'mendifinisikan parameter double saldo, double bunga, int tahun', '2024-06-13 05:55:53', '2024-06-13 05:55:53', NULL),
(1042, 40, 39, '1.402.551,7307', '2024-06-13 05:56:01', '2024-06-13 05:56:01', NULL),
(1043, 42, 1, 'Karena panjang, lebar, tinggu vBalok dan lBalok berisi bilangan bulat', '2024-06-22 05:46:55', '2024-06-22 05:46:55', NULL),
(1044, 42, 2, 'inisialisasi panjang, lebar, tinggi, vBalok, lBalok menggunakan tipe data int, panjang = 10, lebar = 6, tinggi = 7\nkemudian menghitung volume balok dengan rumus balok vBalok = panjang * lebar * tinggi;\ninisialisasi rumus \nkemudian menghitung lebar balok dengan rumus  lebar balok lBalok = 2*(panjang * lebar + panjang * tinggi + lebar * tinggi);\nkemudian print hasil perhitungan volume balok dan lebar balok menggunakan  System.out.print', '2024-06-22 05:46:59', '2024-06-22 05:46:59', NULL),
(1045, 42, 3, 'mengubah nilai inisialisasai seperti    panjang = 11;\n             lebar = 9;\n             tinggi = 17;', '2024-06-22 05:47:03', '2024-06-22 05:47:03', NULL),
(1046, 42, 4, 'Untuk menentukan jika nilai lebih dari 70 maka menampilkan \"Selamat anda lulus!\"', '2024-06-22 06:47:47', '2024-06-22 06:47:47', NULL),
(1047, 42, 5, 'inisialisasi int nilai = 80;\n\nkemudian dicek kondisi nya ketika variabel nilai lebih dari 70 maka menampilkan  \"Selamat anda lulus!\"', '2024-06-22 06:47:55', '2024-06-22 06:47:55', NULL),
(1048, 42, 6, 'Tidak ada output', '2024-06-22 06:48:01', '2024-06-22 06:48:01', NULL),
(1049, 43, 1, 'Karena variabel tersebut berbentuk bilangan bulat', '2024-06-23 07:49:39', '2024-06-23 07:49:39', NULL),
(1050, 43, 2, 'inisialisasi variabel panjang, lebar, tinggi, vBalok, lBalok dengan tipe data int, dan memberikan nilai  panjang = 10, lebar = 6, tinggi = 7, kemudian menghitung volume balok menggunakan rumus  vBalok = panjang * lebar * tinggi; dan menghitung rumus luas balok menggunakan rumus  lBalok = 2*(panjang * lebar + panjang * tinggi + lebar * tinggi), setelah itu untuk menampilkan hasilnya menggunakan fungsi System.out.print', '2024-06-23 07:49:51', '2024-06-23 07:49:51', NULL),
(1051, 43, 3, 'mengganti nilai nilai panjang = 9, lebar=5, dan tinggi=8', '2024-06-23 07:49:57', '2024-06-23 07:49:57', NULL),
(1052, 43, 4, 'Untuk menentukan kondisi jika variabel nilai lebih dari 80 maka akan menampilkan Selamat anda lulus!', '2024-06-24 00:51:43', '2024-06-24 00:51:43', NULL),
(1053, 43, 5, 'Menginisialisasi variabel nilai dengan tipe data int, kemudian menginisialisasi nilai = 80 kemudia dicek kondisi ketika nilai lebih dari 70 maka menampilkan selamat anda lulus', '2024-06-24 00:51:49', '2024-06-24 00:51:49', NULL),
(1054, 43, 6, 'Tidak ada output yang ditampilkan', '2024-06-24 00:51:54', '2024-06-24 00:51:54', NULL),
(1055, 44, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-06-24 11:40:42', '2024-06-24 11:40:42', NULL),
(1056, 44, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-06-24 11:40:47', '2024-06-24 11:40:47', NULL),
(1057, 44, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-06-24 11:40:52', '2024-06-24 11:40:52', NULL),
(1058, 44, 4, 'If digunakan dalam kode tersebut untuk membuat kondisi atau pernyataan logis. Dalam konteks kode tersebut, if digunakan untuk melakukan pengecekan apakah nilai lebih besar dari 70. Jika kondisi tersebut terpenuhi, yaitu nilai lebih besar dari 70, maka pesan \"Selamat anda lulus!\" akan dicetak. If digunakan untuk memberikan pengambilan keputusan berdasarkan kondisi tertentu, yang memungkinkan eksekusi kode yang berbeda tergantung pada hasil kondisi yang dievaluasi.', '2024-06-24 11:43:56', '2024-06-24 11:43:56', NULL),
(1059, 44, 5, 'Menginisialisasi variabel nilai dengan nilai 80. Selanjutnya, program akan mengecek kondisi menggunakan pernyataan if. Jika nilai variabel nilai lebih besar dari 70, maka kondisi pernyataan di dalam if akan dieksekusi. Karena nilai variabel nilai adalah 80 (lebih besar dari 70), pernyataan \"Selamat anda lulus!\" akan dicetak menggunakan System.out.print(\"Selamat anda lulus!\");.', '2024-06-24 11:44:02', '2024-06-24 11:44:02', NULL),
(1060, 44, 6, 'Jika nilai variabel “nilai” kurang dari 70, maka tidak akan ada output yang ditampilkan, karena tidak ada pernyataan lain setelah kondisi if.', '2024-06-24 11:44:08', '2024-06-24 11:44:08', NULL),
(1063, 43, 7, 'Untuk menentukan pesan yang akan ditampilkan berdasarkan nilai dari variabel itemCost. Jika nilai itemCost lebih besar dari 24.00, maka pesan \"High Value Item!\" akan ditetapkan ke dalam variabel order. Namun, jika tidak, maka pesan \"Low Value Item!\" akan ditetapkan. Dengan demikian, fungsi if-else ini menentukan pesan yang sesuai dengan nilai itemCost dan menetapkannya ke dalam variabel order untuk ditampilkan.', '2024-06-25 03:25:03', '2024-06-25 03:25:03', NULL),
(1064, 43, 8, 'Berikut adalah alur program dari baris kode yang diberikan: 1. Variabel itemCost dideklarasikan dan diinisialisasi dengan nilai 30.99. 2. Variabel order dideklarasikan sebagai string kosong. 3. Dilakukan pengecekan kondisi menggunakan pernyataan if. Jika nilai itemCost lebih besar dari 24.00, maka langkah 4 akan dijalankan; jika tidak, langkah 5 akan dijalankan. 4. Pesan \"High Value Item!\" ditetapkan ke dalam variabel order. 5. Jika kondisi pada langkah 3 tidak terpenuhi, maka pesan \"Low Value Item!\" ditetapkan ke dalam variabel order. 6. Pesan yang telah ditetapkan (berdasarkan hasil dari langkah 4 atau 5) kemudian ditampilkan menggunakan System.out.print. 7. Program selesai dieksekusi', '2024-06-25 03:25:09', '2024-06-25 03:25:09', NULL),
(1065, 43, 9, 'Output program akan menampilkan pesan \"Low Value Item!\".', '2024-06-25 03:25:16', '2024-06-25 03:25:16', NULL),
(1066, 43, 10, 'Ketika tidak ada case yang cocok dengan nilai yang diberikan untuk variabel shipping, maka blok kode yang berada di dalam default akan dieksekusi. Dalam kasus ini, jika nilai shipping tidak sama dengan \"Regular\" atau \"Express\", maka variabel shippingCost akan diinisialisasi dengan nilai 0.50.', '2024-06-25 03:26:40', '2024-06-25 03:26:40', NULL),
(1067, 43, 11, '1. Variabel shipping dideklarasikan dan diinisialisasi dengan nilai \"Express\". 2. Variabel shippingCost dideklarasikan tanpa diinisialisasi. 3. Dilakukan pengecekan nilai variabel shipping menggunakan pernyataan switch-case. 4. Jika nilai shipping adalah \"Regular\", maka shippingCost diatur ke nilai 0. 5. Jika nilai shipping adalah \"Express\", maka shippingCost diatur ke nilai 1.75. 6. Jika nilai shipping tidak cocok dengan nilai case manapun, maka blok default akan 7. dieksekusi dan shippingCost diatur ke nilai 0.50. 8. Nilai dari shippingCost yang telah ditetapkan kemudian ditampilkan menggunakan System.out.print. Program selesai dieksekusi', '2024-06-25 03:26:45', '2024-06-25 03:26:45', NULL),
(1068, 43, 12, 'Saat nilai shipping tidak bernilai regular maupun express, sehingga default case dieksekusi.', '2024-06-25 03:26:51', '2024-06-25 03:26:51', NULL),
(1096, 43, 13, 'Tipe data boolean cocok digunakan untuk menyatakan kondisi ya (true) atau tidak (false) dalam pemrograman.', '2024-06-30 11:19:41', '2024-06-30 11:19:41', NULL),
(1097, 43, 14, 'Jika nilai isMember adalah false, maka alur program akan mengikuti jalur di dalam blok else. Kemudian, program akan memeriksa nilai total untuk menentukan besarnya diskon yang diberikan kepada pelanggan non-anggota berdasarkan rentang total pembelian. Setelah itu, nilai diskon akan ditetapkan sesuai dengan rentang total pembelian yang sesuai, dan pesan akan ditampilkan dengan persentase diskon yang didapatkan.', '2024-06-30 11:19:46', '2024-06-30 11:19:46', NULL),
(1098, 43, 15, 'Jika nilai variabel \"total\" adalah Rp.30.000 dan nilai variabel \"isMember\" adalah false, maka output program akan menampilkan pesan \"diskon yang didapatkan adalah 5%\". Hal ini karena nilai total pembelian (Rp.30.000) kurang dari Rp.100.000, sehingga pelanggan non-anggota mendapatkan diskon sebesar 5%.', '2024-06-30 11:19:48', '2024-06-30 11:19:48', NULL),
(1099, 43, 16, 'Pada perulangan for di atas, i++ merupakan operasi penambahan satu unit ke variabel i.  itu adalah ekspresi increment untuk menambah nilai variabel i dengan 1 setiap kali iterasi perulangan dilakukan. Dalam konteks kode tersebut, perulangan akan dimulai dengan i yang memiliki nilai awal 1 (int i = 1), kemudian pada setiap iterasi nilai i akan bertambah satu (i++). Perulangan akan terus dilakukan selama nilai i kurang dari number. Jadi, kegunaan dari i++ pada perulangan for di atas adalah untuk memperbarui nilai i setiap kali iterasi sehingga perulangan dapat berlanjut hingga mencapai kondisi tertentu (dalam kasus ini, hingga nilai i sama dengan number, yaitu 6).', '2024-06-30 11:21:15', '2024-06-30 11:21:15', NULL),
(1100, 43, 17, 'Pertama-tama, sebuah variabel number dideklarasikan dan diinisialisasi dengan nilai 6: int number = 6;. Kemudian, perulangan for dimulai dengan inisialisasi variabel i dengan nilai 1: int i = 1;. Pada setiap iterasi perulangan, kondisi i < number dievaluasi. Jika kondisi tersebut benar (nilai i kurang dari number), blok perulangan di dalamnya akan dieksekusi. Di dalam blok perulangan, System.out.print(i); akan mencetak nilai i ke konsol tanpa baris baru (tanpa spasi). Setelah blok perulangan dieksekusi, ekspresi iterasi i++ akan dieksekusi. Ini akan menambahkan 1 ke nilai i. Proses akan kembali ke langkah 3 dan akan terus berlanjut sampai kondisi i < number tidak lagi terpenuhi. Ketika nilai i mencapai nilai yang sama dengan number, yaitu 6, perulangan akan berhenti karena kondisi i < number tidak lagi terpenuhi. Program selesai dieksekusi.', '2024-06-30 11:21:19', '2024-06-30 11:21:19', NULL),
(1101, 43, 18, '1234567', '2024-06-30 11:21:26', '2024-06-30 11:21:26', NULL),
(1102, 45, 1, 'Variabel panjang, lebar, tinggi, vBalok, dan lBalok dideklarasikan sebagai tipe data int karena mereka merepresentasikan bilangan bulat dalam program ini. Tipe data int cocok untuk nilai bilangan bulat tanpa koma desimal.', '2024-06-30 11:23:52', '2024-06-30 11:23:52', NULL),
(1103, 45, 2, 'Berikut adalah langkah-langkah perhitungan volume dan luas permukaan balok berdasarkan kode program di atas: 1. Variabel panjang, lebar, dan tinggi balok diinisialisasi dengan nilai masing-masing. 2. Volume balok dihitung dengan rumus panjang × lebar × tinggi dan disimpan dalam variabel vBalok. 3. Luas permukaan balok dihitung dengan rumus 2 × (panjang × lebar + panjang × tinggi + lebar × tinggi) dan disimpan dalam variabel lBalok. 4. Hasil volume dan luas permukaan balok ditampilkan melalui output.', '2024-06-30 11:23:56', '2024-06-30 11:23:56', NULL),
(1104, 45, 3, 'Untuk mengubah nilai panjang, lebar, dan tinggi balok, cukup ganti nilai variabel tersebut sesuai kebutuhan, lalu jalankan program kembali.', '2024-06-30 11:24:00', '2024-06-30 11:24:00', NULL),
(1105, 45, 4, 'Fungsi dari pernyataan \"if\" dalam kode program di atas adalah untuk melakukan pengecekan kondisi. Lebih tepatnya, jika nilai variabel \"nilai\" lebih besar dari 70, maka program akan menampilkan pesan \"Selamat anda lulus!\".', '2024-07-02 10:29:00', '2024-07-02 10:29:00', NULL),
(1106, 45, 5, 'Berikut adalah alur program dari kode yang diberikan: 1. Variabel nilai dideklarasikan dan diinisialisasi dengan nilai 80. 2. Dilakukan pengecekan kondisi menggunakan pernyataan if. 3. Jika nilai variabel nilai lebih besar dari 70, maka blok kode di dalam pernyataan if akan dieksekusi. 4. Pesan \"Selamat anda lulus!\" akan ditampilkan karena nilai variabel nilai (80) memenuhi kondisi yang ditentukan. 5. Program selesai dieksekusi.', '2024-07-02 10:29:13', '2024-07-02 10:29:13', NULL),
(1107, 45, 6, 'Jika nilai dari variabel \"nilai\" kurang dari 70, tidak ada output yang akan dihasilkan oleh program ini. Ini karena pesan \"Selamat anda lulus!\" hanya akan ditampilkan jika nilai variabel \"nilai\" lebih besar dari 70, sesuai dengan kondisi yang diberikan dalam pernyataan if. Jika nilai \"nilai\" kurang dari atau sama dengan 70, maka blok kode di dalam pernyataan if tidak akan dieksekusi, dan tidak akan ada output yang dihasilkan.', '2024-07-02 10:29:18', '2024-07-02 10:29:18', NULL);

-- --------------------------------------------------------

--
-- Table structure for table `user_code_test_score`
--

CREATE TABLE `user_code_test_score` (
  `id` bigint UNSIGNED NOT NULL,
  `question_id` int UNSIGNED NOT NULL,
  `user_id` bigint UNSIGNED DEFAULT NULL,
  `score` int NOT NULL DEFAULT '0',
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

-- --------------------------------------------------------

--
-- Table structure for table `user_scores`
--

CREATE TABLE `user_scores` (
  `id` bigint UNSIGNED NOT NULL,
  `user_id` bigint UNSIGNED DEFAULT NULL,
  `content_id` int UNSIGNED DEFAULT NULL,
  `score` int NOT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL,
  `question_id` int UNSIGNED DEFAULT NULL,
  `started_at` timestamp NULL DEFAULT NULL,
  `ended_at` timestamp NULL DEFAULT NULL,
  `deleted_at` timestamp NULL DEFAULT NULL,
  `on_timer` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL,
  `level_id` int UNSIGNED NOT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `user_scores`
--

INSERT INTO `user_scores` (`id`, `user_id`, `content_id`, `score`, `created_at`, `updated_at`, `question_id`, `started_at`, `ended_at`, `deleted_at`, `on_timer`, `level_id`) VALUES
(1, 2, 1, 30, '2023-06-01 18:47:46', '2023-06-01 18:47:46', 1, NULL, NULL, NULL, NULL, 1),
(2, 2, 2, 30, '2023-06-01 19:32:48', '2023-06-01 19:32:48', 2, NULL, NULL, NULL, NULL, 1),
(3, 2, 3, 30, '2023-06-01 19:45:23', '2023-06-01 19:45:23', 3, NULL, NULL, NULL, NULL, 1),
(4, 2, 4, 30, '2023-06-01 20:47:17', '2023-06-01 20:47:17', 4, NULL, NULL, NULL, NULL, 1),
(5, 2, 5, 30, '2023-06-03 05:19:09', '2023-06-03 05:19:09', 5, NULL, NULL, NULL, NULL, 1),
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-- --------------------------------------------------------

--
-- Table structure for table `wondering_score`
--

CREATE TABLE `wondering_score` (
  `id` bigint UNSIGNED NOT NULL,
  `user_id` bigint UNSIGNED NOT NULL,
  `content_id` int UNSIGNED NOT NULL,
  `score` int NOT NULL,
  `created_at` timestamp NULL DEFAULT NULL,
  `updated_at` timestamp NULL DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;

--
-- Dumping data for table `wondering_score`
--

INSERT INTO `wondering_score` (`id`, `user_id`, `content_id`, `score`, `created_at`, `updated_at`) VALUES
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(342, 41, 5, 10, '2024-06-10 04:22:17', '2024-06-10 04:22:17'),
(343, 41, 6, 10, '2024-06-10 04:28:16', '2024-06-10 04:28:16'),
(344, 41, 7, 10, '2024-06-10 04:31:29', '2024-06-10 04:31:29'),
(345, 41, 8, 10, '2024-06-10 04:35:23', '2024-06-10 04:35:23'),
(346, 41, 9, 10, '2024-06-10 04:39:09', '2024-06-10 04:39:09'),
(347, 41, 10, 10, '2024-06-13 03:17:31', '2024-06-13 03:17:31'),
(348, 41, 11, 10, '2024-06-13 03:37:27', '2024-06-13 03:37:27'),
(349, 41, 12, 10, '2024-06-13 03:42:53', '2024-06-13 03:42:53'),
(350, 41, 13, 10, '2024-06-13 03:48:00', '2024-06-13 03:48:00'),
(351, 40, 8, 10, '2024-06-13 05:32:45', '2024-06-13 05:32:45'),
(352, 40, 9, 10, '2024-06-13 05:39:13', '2024-06-13 05:39:13'),
(353, 40, 10, 10, '2024-06-13 05:44:12', '2024-06-13 05:44:12'),
(354, 40, 11, 10, '2024-06-13 05:47:46', '2024-06-13 05:47:46'),
(355, 40, 12, 10, '2024-06-13 05:51:36', '2024-06-13 05:51:36'),
(356, 40, 13, 10, '2024-06-13 05:54:29', '2024-06-13 05:54:29'),
(357, 42, 1, 10, '2024-06-22 05:41:42', '2024-06-22 05:41:42'),
(358, 42, 2, 10, '2024-06-22 06:45:36', '2024-06-22 06:45:36'),
(359, 43, 1, 10, '2024-06-23 07:44:20', '2024-06-23 07:44:20'),
(360, 43, 2, 10, '2024-06-24 00:48:20', '2024-06-24 00:48:20'),
(361, 44, 1, 10, '2024-06-24 11:39:43', '2024-06-24 11:39:43'),
(362, 44, 2, 10, '2024-06-24 11:42:07', '2024-06-24 11:42:07'),
(363, 43, 3, 10, '2024-06-25 03:21:07', '2024-06-25 03:21:07'),
(364, 43, 4, 10, '2024-06-25 03:25:40', '2024-06-25 03:25:40'),
(365, 45, 1, 10, '2024-06-30 10:51:20', '2024-06-30 10:51:20'),
(366, 43, 5, 10, '2024-06-30 10:58:22', '2024-06-30 10:58:22'),
(367, 43, 6, 10, '2024-06-30 11:20:32', '2024-06-30 11:20:32'),
(368, 45, 2, 10, '2024-07-02 10:27:54', '2024-07-02 10:27:54');

--
-- Indexes for dumped tables
--

--
-- Indexes for table `answers`
--
ALTER TABLE `answers`
  ADD PRIMARY KEY (`id`),
  ADD KEY `answers_question_id_foreign` (`question_id`);

--
-- Indexes for table `badge_settings`
--
ALTER TABLE `badge_settings`
  ADD PRIMARY KEY (`id`);

--
-- Indexes for table `code_error_logs`
--
ALTER TABLE `code_error_logs`
  ADD PRIMARY KEY (`id`),
  ADD KEY `code_error_logs_user_id_foreign` (`user_id`),
  ADD KEY `code_error_logs_question_id_foreign` (`question_id`);

--
-- Indexes for table `code_history_logs`
--
ALTER TABLE `code_history_logs`
  ADD PRIMARY KEY (`id`),
  ADD KEY `code_history_logs_user_id_foreign` (`user_id`),
  ADD KEY `code_history_logs_question_id_foreign` (`question_id`);

--
-- Indexes for table `contents`
--
ALTER TABLE `contents`
  ADD PRIMARY KEY (`id`),
  ADD KEY `contents_lesson_id_foreign` (`lesson_id`);

--
-- Indexes for table `courses`
--
ALTER TABLE `courses`
  ADD PRIMARY KEY (`id`);

--
-- Indexes for table `essay_question`
--
ALTER TABLE `essay_question`
  ADD PRIMARY KEY (`id`),
  ADD KEY `essay_question_question_id_foreign` (`question_id`),
  ADD KEY `essay_question_user_id_foreign` (`user_id`);

--
-- Indexes for table `explaining_score`
--
ALTER TABLE `explaining_score`
  ADD PRIMARY KEY (`id`),
  ADD KEY `explaining_score_user_id_foreign` (`user_id`),
  ADD KEY `explaining_score_content_id_foreign` (`content_id`),
  ADD KEY `explaining_score_essay_question_id_foreign` (`essay_question_id`),
  ADD KEY `explaining_score_user_answer_id_foreign` (`user_answer_id`);

--
-- Indexes for table `explains`
--
ALTER TABLE `explains`
  ADD PRIMARY KEY (`id`),
  ADD KEY `explains_level_id_foreign` (`level_id`),
  ADD KEY `explains_user_id_foreign` (`user_id`);

--
-- Indexes for table `failed_jobs`
--
ALTER TABLE `failed_jobs`
  ADD PRIMARY KEY (`id`),
  ADD UNIQUE KEY `failed_jobs_uuid_unique` (`uuid`);

--
-- Indexes for table `lessons`
--
ALTER TABLE `lessons`
  ADD PRIMARY KEY (`id`),
  ADD KEY `lessons_course_id_foreign` (`course_id`),
  ADD KEY `lessons_level_id_foreign` (`level_id`);

--
-- Indexes for table `levels`
--
ALTER TABLE `levels`
  ADD PRIMARY KEY (`id`),
  ADD KEY `levels_course_id_foreign` (`course_id`);

--
-- Indexes for table `migrations`
--
ALTER TABLE `migrations`
  ADD PRIMARY KEY (`id`);

--
-- Indexes for table `password_resets`
--
ALTER TABLE `password_resets`
  ADD KEY `password_resets_email_index` (`email`);

--
-- Indexes for table `personal_access_tokens`
--
ALTER TABLE `personal_access_tokens`
  ADD PRIMARY KEY (`id`),
  ADD UNIQUE KEY `personal_access_tokens_token_unique` (`token`),
  ADD KEY `personal_access_tokens_tokenable_type_tokenable_id_index` (`tokenable_type`,`tokenable_id`);

--
-- Indexes for table `questions`
--
ALTER TABLE `questions`
  ADD PRIMARY KEY (`id`),
  ADD KEY `questions_content_id_foreign` (`content_id`);

--
-- Indexes for table `roles`
--
ALTER TABLE `roles`
  ADD PRIMARY KEY (`id`);

--
-- Indexes for table `role_user`
--
ALTER TABLE `role_user`
  ADD PRIMARY KEY (`id`),
  ADD KEY `role_user_user_id_foreign` (`user_id`),
  ADD KEY `role_user_role_id_foreign` (`role_id`);

--
-- Indexes for table `student_courses`
--
ALTER TABLE `student_courses`
  ADD PRIMARY KEY (`id`),
  ADD KEY `student_courses_user_id_foreign` (`user_id`),
  ADD KEY `student_courses_course_id_foreign` (`course_id`);

--
-- Indexes for table `total_score`
--
ALTER TABLE `total_score`
  ADD PRIMARY KEY (`id`),
  ADD KEY `total_score_user_id_foreign` (`user_id`),
  ADD KEY `total_score_content_id_foreign` (`content_id`),
  ADD KEY `total_score_question_id_foreign` (`question_id`),
  ADD KEY `total_score_wondering_score_id_foreign` (`wondering_score_id`),
  ADD KEY `total_score_user_score_id_foreign` (`user_score_id`);

--
-- Indexes for table `users`
--
ALTER TABLE `users`
  ADD PRIMARY KEY (`id`),
  ADD UNIQUE KEY `users_email_unique` (`email`),
  ADD KEY `users_role_id_foreign` (`role_id`);

--
-- Indexes for table `user_answer`
--
ALTER TABLE `user_answer`
  ADD PRIMARY KEY (`id`),
  ADD KEY `user_answer_user_id_foreign` (`user_id`),
  ADD KEY `user_answer_essay_question_id_foreign` (`essay_question_id`);

--
-- Indexes for table `user_code_test_score`
--
ALTER TABLE `user_code_test_score`
  ADD PRIMARY KEY (`id`),
  ADD KEY `user_code_test_score_question_id_foreign` (`question_id`),
  ADD KEY `user_code_test_score_user_id_foreign` (`user_id`);

--
-- Indexes for table `user_scores`
--
ALTER TABLE `user_scores`
  ADD PRIMARY KEY (`id`),
  ADD KEY `user_scores_user_id_foreign` (`user_id`),
  ADD KEY `user_scores_content_id_foreign` (`content_id`),
  ADD KEY `user_scores_question_id_foreign` (`question_id`),
  ADD KEY `user_scores_level_id_foreign` (`level_id`) USING BTREE;

--
-- Indexes for table `wondering_score`
--
ALTER TABLE `wondering_score`
  ADD PRIMARY KEY (`id`),
  ADD KEY `wondering_score_user_id_foreign` (`user_id`),
  ADD KEY `wondering_score_content_id_foreign` (`content_id`);

--
-- AUTO_INCREMENT for dumped tables
--

--
-- AUTO_INCREMENT for table `answers`
--
ALTER TABLE `answers`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=25;

--
-- AUTO_INCREMENT for table `badge_settings`
--
ALTER TABLE `badge_settings`
  MODIFY `id` int UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=35;

--
-- AUTO_INCREMENT for table `code_error_logs`
--
ALTER TABLE `code_error_logs`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=84;

--
-- AUTO_INCREMENT for table `code_history_logs`
--
ALTER TABLE `code_history_logs`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=517;

--
-- AUTO_INCREMENT for table `contents`
--
ALTER TABLE `contents`
  MODIFY `id` int UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=14;

--
-- AUTO_INCREMENT for table `courses`
--
ALTER TABLE `courses`
  MODIFY `id` int UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=3;

--
-- AUTO_INCREMENT for table `essay_question`
--
ALTER TABLE `essay_question`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=58;

--
-- AUTO_INCREMENT for table `explaining_score`
--
ALTER TABLE `explaining_score`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=1030;

--
-- AUTO_INCREMENT for table `explains`
--
ALTER TABLE `explains`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT;

--
-- AUTO_INCREMENT for table `failed_jobs`
--
ALTER TABLE `failed_jobs`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT;

--
-- AUTO_INCREMENT for table `lessons`
--
ALTER TABLE `lessons`
  MODIFY `id` int UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=10;

--
-- AUTO_INCREMENT for table `levels`
--
ALTER TABLE `levels`
  MODIFY `id` int UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=10;

--
-- AUTO_INCREMENT for table `migrations`
--
ALTER TABLE `migrations`
  MODIFY `id` int UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=40;

--
-- AUTO_INCREMENT for table `personal_access_tokens`
--
ALTER TABLE `personal_access_tokens`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT;

--
-- AUTO_INCREMENT for table `questions`
--
ALTER TABLE `questions`
  MODIFY `id` int UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=27;

--
-- AUTO_INCREMENT for table `roles`
--
ALTER TABLE `roles`
  MODIFY `id` int UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=5;

--
-- AUTO_INCREMENT for table `role_user`
--
ALTER TABLE `role_user`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=4;

--
-- AUTO_INCREMENT for table `student_courses`
--
ALTER TABLE `student_courses`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=42;

--
-- AUTO_INCREMENT for table `total_score`
--
ALTER TABLE `total_score`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=344;

--
-- AUTO_INCREMENT for table `users`
--
ALTER TABLE `users`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=46;

--
-- AUTO_INCREMENT for table `user_answer`
--
ALTER TABLE `user_answer`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=1108;

--
-- AUTO_INCREMENT for table `user_code_test_score`
--
ALTER TABLE `user_code_test_score`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT;

--
-- AUTO_INCREMENT for table `user_scores`
--
ALTER TABLE `user_scores`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=373;

--
-- AUTO_INCREMENT for table `wondering_score`
--
ALTER TABLE `wondering_score`
  MODIFY `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT, AUTO_INCREMENT=369;

--
-- Constraints for dumped tables
--

--
-- Constraints for table `code_history_logs`
--
ALTER TABLE `code_history_logs`
  ADD CONSTRAINT `code_history_logs_ibfk_1` FOREIGN KEY (`question_id`) REFERENCES `questions` (`id`);

--
-- Constraints for table `essay_question`
--
ALTER TABLE `essay_question`
  ADD CONSTRAINT `essay_question_ibfk_1` FOREIGN KEY (`question_id`) REFERENCES `questions` (`id`);

--
-- Constraints for table `explaining_score`
--
ALTER TABLE `explaining_score`
  ADD CONSTRAINT `explaining_score_ibfk_1` FOREIGN KEY (`content_id`) REFERENCES `contents` (`id`);

--
-- Constraints for table `lessons`
--
ALTER TABLE `lessons`
  ADD CONSTRAINT `lessons_ibfk_1` FOREIGN KEY (`course_id`) REFERENCES `courses` (`id`);

--
-- Constraints for table `questions`
--
ALTER TABLE `questions`
  ADD CONSTRAINT `questions_ibfk_1` FOREIGN KEY (`content_id`) REFERENCES `contents` (`id`);

--
-- Constraints for table `student_courses`
--
ALTER TABLE `student_courses`
  ADD CONSTRAINT `student_courses_ibfk_1` FOREIGN KEY (`user_id`) REFERENCES `users` (`id`);

--
-- Constraints for table `total_score`
--
ALTER TABLE `total_score`
  ADD CONSTRAINT `total_score_ibfk_1` FOREIGN KEY (`content_id`) REFERENCES `contents` (`id`),
  ADD CONSTRAINT `total_score_ibfk_2` FOREIGN KEY (`user_id`) REFERENCES `users` (`id`);

--
-- Constraints for table `user_answer`
--
ALTER TABLE `user_answer`
  ADD CONSTRAINT `user_answer_ibfk_1` FOREIGN KEY (`user_id`) REFERENCES `users` (`id`),
  ADD CONSTRAINT `user_answer_ibfk_2` FOREIGN KEY (`essay_question_id`) REFERENCES `essay_question` (`id`);

--
-- Constraints for table `user_code_test_score`
--
ALTER TABLE `user_code_test_score`
  ADD CONSTRAINT `user_code_test_score_ibfk_1` FOREIGN KEY (`user_id`) REFERENCES `users` (`id`);

--
-- Constraints for table `user_scores`
--
ALTER TABLE `user_scores`
  ADD CONSTRAINT `user_scores_ibfk_1` FOREIGN KEY (`user_id`) REFERENCES `users` (`id`),
  ADD CONSTRAINT `user_scores_ibfk_2` FOREIGN KEY (`content_id`) REFERENCES `contents` (`id`);

--
-- Constraints for table `wondering_score`
--
ALTER TABLE `wondering_score`
  ADD CONSTRAINT `wondering_score_ibfk_1` FOREIGN KEY (`user_id`) REFERENCES `users` (`id`),
  ADD CONSTRAINT `wondering_score_ibfk_2` FOREIGN KEY (`content_id`) REFERENCES `contents` (`id`);
COMMIT;

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/*!40101 SET CHARACTER_SET_RESULTS=@OLD_CHARACTER_SET_RESULTS */;
/*!40101 SET COLLATION_CONNECTION=@OLD_COLLATION_CONNECTION */;
