Nasution, Abduh Maghfuri2023-05-052023-05-052023-02PerpustakaanElfitrahttps://repository.unri.ac.id/handle/123456789/10979Sentiment analysis is the process of analyzing data that will be classified according to the class of sentiment in an argument. The rise of Lesbian, Gay, Bisexual, and Transgender(LGBT) talk on the Twitter application has caused people to give positive and negative sentiments. So that the sexual culture becomes very sensitive among Indonesian people. The author uses a method for classifying with several stages, namely data collection, preprocessing, labeling, Term Frequency (TF) – Inverse Document Frequency (IDF) weighting, Support Vector Machine (SVM) classification with the Cross Validation method. Based on the stages of the method that has been carried out, a Machine Learning score is obtained with an average value of 0.776. The results of Machine Learning found 220 positive sentiments and 780 negative sentimentsenLGBTTwitterSentimentTerm Frequency (TF) – Inverse Document Frequency (IDF)Support Vector MachineArticle