Sentiment analysis of the 2024 election using the naïve bayes method using data x - Zidan, Ahmad Halim Faizal; Handayani, Irma; Anggara, Afwan (Jurnal Mandiri IT, 2025)
Text mining is a process for utilizing the vast amounts of data generated in today’s digital era. The rapid growth of social media usage has produced extensive textual data, one of which can be analyzed through sentiment analysis. This study uses the social media platform X to analyze public opinions regarding the 2024 Indonesian General Election. The analysis was conducted using 126 user comments as the dataset and 103 reviews as the testing data, which were then processed using the Naive Bayes method. Text mining with the Naive Bayes algorithm can be applied to examine public opinions and sentiments toward the 2024 election on X. The results of the analysis classify sentiments into positive, negative, and neutral categories.