Sentiment Analysis of Social Media X in the 2024 Indonesian Presidential Election Using the Naive Bayes Algorithm: Candidates' Backgrounds and Political Promises

Abstract

In 2024, Indonesia holds a presidential election, and the candidates are making promises to each other to attract voters. Many people gave their opinions on X. This study uses the Naïve Bayes algorithm to analyze the sentiment of these tweets, with the aim of understanding the background of the candidates and their campaign promises. Data is collected from X by crawling technique, then data is pre-processed, trained using Naïve Bayes model, and evaluated for accuracy. Sentiments in tweets were classified as positive, negative, or neutral. The results showed that the Prabowo Subianto - Gibran Rakabuming Raka pair was the most talked about with 1005 tweets, followed by Anis Rasyid Baswedan - Muhaimin Iskandar with 707 tweets, and Ganjar Pranowo - Mohammad Mahfud M.D. with 572 tweets. The Prabowo Subianto - Gibran Rakabuming Raka pair received the most positive sentiment, which was 446 more than the other candidates.

Keywords

• sentiment analysis
• naive bayes
• social media
• 2024 presidential election