<![CDATA[The general election of Indonesia in the upcoming 2024 will be an interesting topic for social media users, especially Twitter. Currently, Twitter is very influential in building sentiment, preferences, and public politics. So that people's Tweets can be used to see a picture of public opinion. There are various opinions of Twitter users with positive, neutral and negative sentiments. However, classifying the sentiments of Twitter users requires quite a lot of time and effort due to the large number of tweets found. The large number of incoming tweets regarding the election encourages the need for a method that helps to view public opinion effectively. By providing the textblob library, Python, which is a programming language, is able to classify tweet data and can be used to answer these problems. The tweet data is preprocessed first where there are two processes in the initial data, namely the cleaning and stemming processes. After that, a sentiment analysis was carried out to find out how the results of the classification related to public opinion from the 2024 elections and classify them into three classes, namely positive, neutral and negative using Python. The results of this study show that Python performs sentiment analysis with the results of the proportion of positive class sentiments of 40%, 52% neutral and 8% negative about the 2024 elections so that it can be concluded that Python can classify tweets from Twitter so that we can identify public opinion about elections. The general public of Indonesia in 2024 will have neutral opinions tend to be positive]]>
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