SENTIMENT ANALYSIS OF POTENTIAL 2024 PRESIDENTIAL CANDIDATES ON TWITTER SOCIAL MEDIA USING METHODS NAIVE BAYES MULTINOMIAL

Abstract

This research aims to conduct sentiment analysis regarding potential presidential candidates in 2024, so that we can identify candidates who have positive, neutral and negative images in the view of the public on Twitter social media. This sentiment analysis helps candidates understand People's aspirations and adapt their communications accordingly. This research uses the naïve Bayes multinomial method and utilizes crawling technology on Twitter social media, data is collected and analyzed efficiently. The results of this research obtained 6000 comment data with each candidate having 2000 comments. Ganjar Pranowo had the highest positive sentiment (39%), followed by Anies Baswedan (35.8%) and Prabowo Subianto (25.9%). Ganjar also leads in neutral sentiment (38.8%). The highest number of negative sentiments was held by Prabowo Subianto (39.3%), Anies Baswedan (30.5%), Ganjar Pranowo (21.3%). So from these results, Ganjar Pranowo has the best electability based on public comments on Twitter social media.