Sentiment Analysis of Indonesian Presidential Candidates in the 2024 Election Using the Naïve Bayes Classifier - El Hakim, Mhd Syofior Rahman (Journal of Mathematics UNP, 2024)
In 2024, the people of Indonesia actively participated in the democratic process of electing a new president, vice president, and legislative members. This presidential election generated a wide range of public opinions across various social media platforms such as Twitter, Facebook, Instagram, and TikTok. These opinions were characterized by sentiments that were positive, negative, or neutral, directed toward the presidential candidates in the 2024 election. Consequently, this research was conducted to analyze the sentiment toward the presidential candidates based on data from Twitter. The data was gathered through a crawling process using Python with keywords "Anies," "Prabowo," and "Ganjar." After obtaining the data, it underwent cleaning and sentiment labeling using an Indonesian sentiment lexicon called InSet. Subsequently, sentiment classification was performed using the Naïve Bayes algorithm, yielding an average accuracy of 65.96%.