This thesis aims to analyze sentiment towards the Criminal Code Bill Article 353 Paragraph 1 from data taken from Twitter using the Naive Bayes Classifier method. This research was conducted to find out the public's view of the controversial article. The data taken is in the form of tweets containing keywords related to the Criminal Code Bill for a certain period. The Naive Bayes Classifier method is used to classify tweets into positive or negative categories based on gender, age, and level of education as well as the impact of public sentiment on this article on the sustainability of democracy in Indonesia. The data used in this study is data from the online media Twitter. This study uses a quantitative method with a descriptive approach. The results of the sentiment analysis are expected to provide an overview of the public's perception of the article.
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