ANALISIS SENTIMEN TENTANG HENGKANGNYA PEPSI DI INDONESIA BERDASARKAN OPINI TWITTER MENGGUNAKAN METODE NAIVE BAYES

Twitter is one of the social media that allows users to freely comment or write tweets based on their opinions about whatever is happening, including the opinion about Pepsi's departure from Indonesia in October 2019, which is one of the hot topics discussed. The number of tweets written on twitter can be used to obtain information about public assessments regarding to the leaving of Pepsi's. In order to organize the opinions well according to the classification, this study conducted a sentiment analysis using the naive bayes method. Sentiment analysis is the process of understanding, extracting and processing textual data automatically to obtain sentiment information contained in an opinion sentence. This study divides sentiment into 3 classes, namely positive, neutral and negative. The result of this research is sentiment into neutral class is the largest sentiment with 129 sentiments. The data rate accuracy in this study of 71.85185%.
Keywords : Classification, Sentiment Analysis, Naive Bayes, The Leaving of Pepsi in
Indonesia, Twitter