Sentiment Analysis of Twitter Users Ahead of the 2024 Election Using the Naive Bayes Method - Subasar, Andi (Association for Scientific Computing, Electronics, and Engineering (ASCEE), 2024)
Elections are pivotal moments in a democratic nation, where citizens can express their opinions and political preferences. In today's digital era, social media, particularly Twitter, has become a crucial platform for expressing sentiments related to elections. This research aims to analyze Twitter users' sentiments towards the 2024 election using the Naive Bayes method, Knowing the public's views, especially on the Twitter platform, regarding the 2024 election and implementing the Naive Bayes method to classify sentiment. The research method itself consists of data collection from Twitter using the Twitter API, data preprocessing including data cleaning, removal of URLs, hashtags, duplicate words, normalization of words, tokenization, and removing meaningless words using the Rapid Miner application, then testing using training data and testing data in the Naive Bayes method., the data obtained from the keyword