<![CDATA[The 2024 Indonesian presidential election is one of the most talked about topics on various social media platforms, including YouTube. The comments that appear on political-themed videos can reflect public opinion towards presidential candidates. This research aims to conduct sentiment analysis of YouTube comments related to Indonesian presidential candidates in 2024 using the Naïve Bayes Classifier method. This method was chosen due to its ability to classify text data effectively and efficiently. Data was collected from a number of relevant Kompas tv videos on YouTube, then text preprocessing stages such as data cleaning, tokenization, and stemming were performed. Next, the data was classified into three sentiment categories, namely positive, negative, and neutral. The research shows that the Naïve Bayes model is able to classify sentiment with sufficient accuracy. This finding can provide an overview of public perceptions of each presidential candidate as well as input for interested parties in the fields of politics and public communication. The results of this study show that the naïve bayes classifier algorithm can analyze with an accuracy of 61 % in the evaluation process using confusion matrix. The results of this study indicate that the naïve bayes classifier algorithm can be an effective alternative for analyzing the sentiment of YouTube comments on presidential candidates.]]>
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