Moch. Reinaldy Destra Fachreza, Suhartono Suhartono, M. Ainul Yaqin
{"title":"使用天真Bayes的方法,将印尼首都(IKN)在Twitter上的社交媒体上对其情绪的分类","authors":"Moch. Reinaldy Destra Fachreza, Suhartono Suhartono, M. Ainul Yaqin","doi":"10.14421/jiska.2023.8.3.243-251","DOIUrl":null,"url":null,"abstract":"Some time ago, the House of Representatives passed Law (UU) Number 3 of 2022 concerning the National Capital City on January 18, 2022. Then, President Joko Widodo officially signed the IKN Law on February 15, 2022. Thus, the Indonesian capital will be moved to Penajam Paser Utara Regency and Kutai Kartanegara Regency, East Kalimantan Province. The public's response to the decision varies; many respond with supportive sentiments, but some react with unsupportive ideas. Nowadays, there are many ways to observe information collected on social media. Various responses submitted through social media can be used as sentiment classification research data. The Naïve Bayes method is commonly used for this type of research. Data was collected between February 15-25, 2023, with as many as 500 tweets. This research uses the Gaussian Naïve Bayes type because of the independence assumption made by this method. Features that do not significantly contribute to the classification can be ignored, thus reducing the impact of irrelevant features. This study aims to measure public sentiment on Twitter towards the process of moving the nation's capital. The system created provides the best trial results at 80% feature usage with 82.0% accuracy, 76.9% precision, and 100% recall.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Klasifikasi Sentimen Masyarakat Terhadap Proses Pemindahan Ibu Kota Negara (IKN) Indonesia pada Media Sosial Twitter Menggunakan Metode Naïve Bayes\",\"authors\":\"Moch. Reinaldy Destra Fachreza, Suhartono Suhartono, M. Ainul Yaqin\",\"doi\":\"10.14421/jiska.2023.8.3.243-251\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Some time ago, the House of Representatives passed Law (UU) Number 3 of 2022 concerning the National Capital City on January 18, 2022. Then, President Joko Widodo officially signed the IKN Law on February 15, 2022. Thus, the Indonesian capital will be moved to Penajam Paser Utara Regency and Kutai Kartanegara Regency, East Kalimantan Province. The public's response to the decision varies; many respond with supportive sentiments, but some react with unsupportive ideas. Nowadays, there are many ways to observe information collected on social media. Various responses submitted through social media can be used as sentiment classification research data. The Naïve Bayes method is commonly used for this type of research. Data was collected between February 15-25, 2023, with as many as 500 tweets. This research uses the Gaussian Naïve Bayes type because of the independence assumption made by this method. Features that do not significantly contribute to the classification can be ignored, thus reducing the impact of irrelevant features. This study aims to measure public sentiment on Twitter towards the process of moving the nation's capital. The system created provides the best trial results at 80% feature usage with 82.0% accuracy, 76.9% precision, and 100% recall.\",\"PeriodicalId\":34216,\"journal\":{\"name\":\"JISKA Jurnal Informatika Sunan Kalijaga\",\"volume\":\"2013 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JISKA Jurnal Informatika Sunan Kalijaga\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14421/jiska.2023.8.3.243-251\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JISKA Jurnal Informatika Sunan Kalijaga","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14421/jiska.2023.8.3.243-251","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
不久前,众议院于2022年1月18日通过了关于国家首都的2022年第3号法。随后,佐科·维多多总统于2022年2月15日正式签署了《国际注册法》。因此,印尼首都将迁移到东加里曼丹省的Penajam Paser Utara Regency和Kutai Kartanegara Regency。公众对这一决定的反应各不相同;许多人的反应是支持的情绪,但有些人的反应是不支持的想法。如今,有很多方法可以观察社交媒体上收集的信息。通过社交媒体提交的各种回复可以作为情绪分类研究数据。Naïve贝叶斯方法通常用于这类研究。数据是在2023年2月15日至25日之间收集的,其中多达500条推文。本研究使用高斯Naïve贝叶斯类型,因为该方法做出了独立性假设。可以忽略对分类没有显著贡献的特征,从而减少不相关特征的影响。这项研究旨在衡量推特上公众对国家首都迁移过程的情绪。所创建的系统在80%的特征使用率下提供了最佳的试验结果,准确率为82.0%,精度为76.9%,召回率为100%。
Klasifikasi Sentimen Masyarakat Terhadap Proses Pemindahan Ibu Kota Negara (IKN) Indonesia pada Media Sosial Twitter Menggunakan Metode Naïve Bayes
Some time ago, the House of Representatives passed Law (UU) Number 3 of 2022 concerning the National Capital City on January 18, 2022. Then, President Joko Widodo officially signed the IKN Law on February 15, 2022. Thus, the Indonesian capital will be moved to Penajam Paser Utara Regency and Kutai Kartanegara Regency, East Kalimantan Province. The public's response to the decision varies; many respond with supportive sentiments, but some react with unsupportive ideas. Nowadays, there are many ways to observe information collected on social media. Various responses submitted through social media can be used as sentiment classification research data. The Naïve Bayes method is commonly used for this type of research. Data was collected between February 15-25, 2023, with as many as 500 tweets. This research uses the Gaussian Naïve Bayes type because of the independence assumption made by this method. Features that do not significantly contribute to the classification can be ignored, thus reducing the impact of irrelevant features. This study aims to measure public sentiment on Twitter towards the process of moving the nation's capital. The system created provides the best trial results at 80% feature usage with 82.0% accuracy, 76.9% precision, and 100% recall.