<![CDATA[Indonesia is one of the countries that adheres to a democratic system. The democratic system of governmentprioritizes the people. So that when the election of the people's representatives is carried out, the people havethe highest right to go through elections that take place freely. In 2024, the Indonesian presidential electionwill be held. Every moment of the presidential election or presidential general election, there are manyopinions from the public about the rumored presidential candidate. However, in practice, there are manynegative comments that are "hate speech," which can trigger social conflict and damage the politicalenvironment. This research aims to build a classification model of public comments into "haters" and "non-haters" categories in Indonesian using the Naïve Bayes algorithm. This research uses data totaling 1000, withdetails of training data of 800 and test data of 200. With the stages of data collection, data pre-processing,classification with Naïve Bayes, Evaluation, and Deployment. The results obtained an accuracy value of83.5%, a precision value of 82%, and a recall value of 90%.Keywords: Presidential Election; Classification; Naive Bayes.]]>
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