Analyzing the Sentiment of the 2024 Election Sirekap Application Using NaÃ¯vee Bayes Algorithm - Muhammad, Isa Ali; Rakhmawati, Desty; Wijaya, Anugerah Bagus (Universitas Budi Darma, 2024)
One of the most recent types of elections is the 2024 election, which includes the election of the president as well as legislative members. Along with the development of technology, an application called Sirekap emerged which is used to recapitulate the results of the vote. Although the app only has a one-star rating on the Play Store, reading all the user reviews to know the quality takes quite a while. Therefore, sentiment analysis can be an alternative to get an overview of user reviews so that it can help in making better decisions then, the method that will be used in conducting sentiment analysis in this study is the naÃ¯ve Bayes algorithm. This research aims to identify and categorize user sentiment, as well as evaluate the quality of the app based on reviews provided on the Playstore. This research contributes by providing an efficient method to analyze user reviews of the Sirekap app, which can assist app developers and other stakeholders in making better decisions regarding app development and improvement. In addition, the results of this study confirm that the app's one-star rating is accurate, with evaluation metrics such as precision, memory, and f1 score reaching 1.00 each.