Klasifikasi sentimen masyarakat terhadap proses pemindahan Ibu Kota Negara (IKN) Indonesia pada media sosial Twitter menggunakan metode Naïve Bayes

Fachreza, Moch. Reinaldy Destra, Suhartono, Suhartono and Yaqin, Muhammad Ainul (2023) Klasifikasi sentimen masyarakat terhadap proses pemindahan Ibu Kota Negara (IKN) Indonesia pada media sosial Twitter menggunakan metode Naïve Bayes. JISKA (Jurnal Informatika Sunan Kalijaga), 8 (3). pp. 243-251. ISSN 25280074

Text 19328.pdf - Published Version Available under License Creative Commons Attribution Non-commercial. Download (353kB)

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.

Item Type:	Journal Article
Keywords:	IKN; Naïve Bayes; Sentiments; Classification; Twitter
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0803 Computer Software > 080309 Software Engineering
Divisions:	Faculty of Technology > Department of Informatics Engineering
Depositing User:	Muhammad Ainul Yaqin
Date Deposited:	04 Jun 2024 15:10

Downloads

Origin of downloads

Actions (login required)

View Item