<![CDATA[The 2024 Election in Indonesia is an interesting topic for social media users. Social media has a big impact in building public political opinions, views, sentiments and preferences. Many political figures have been nominated for President based on public opinion. There are various opinions of media social users with negative, positive and neutral sentiments. However, determining the sentiment of social media users requires quite a lot of effort and time. The large number of incoming opinions regarding presidential election candidates encourages the need for methods that help to see public opinion effectively. Python is a programming language that can be used to answer these problems. By providing a standard library that is open source and has a wide range of applications in various fields. Classification will be carried out using the Naïve Bayes Classifier to determine the level of accuracy of the classification process carried out. Sentiment analysis in this research is a process carried out to find out what the results of sentiment analysis are regarding the public's response to the presidential candidates for the upcoming 2024 election and classify them into three classes using the Naïve Bayes method using Python. The results of this research showed that Python carried out sentiment analysis with the sentiment percentage results for candidate Anies Muhaimin with a positive class of 64.91%, neutral 28.07% and negative 7.02% with a Naïve Bayes accuracy value of 75%. For candidate Prabowo Gibran, the positive class is 12.38%, neutral 6.67% and negative 80.95% with a Naïve Bayes accuracy value of 81%. Meanwhile, the candidate Ganjar Mahfud has a positive class of 40%, neutral 50.67% and negative 9.33% with a Naïve Bayes accuracy value of 60%. So that we can identify public opinion about presidential candidates for the 2024 election using the Naïve Bayes method using Python.]]>
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