Analisa Sentimen Pada Twitter Terhadap Kenaikan Tarif Dasar Listrik Dengan Metode Naïve Bayes

Abstract

Along with the development of internet technology, the use of social media has also mushroomed. The most popular social media is Twitter. Twitter provides services for its users to send and read tweets that have been shared, so people prefer to express their opinions through social media rather than expressing it directly. Public opinion expressed in Twitter social media in the form of perception, both positive and negative. The abundance of public opinion can be used as research material to find information. The utilization of this information requires appropriate analytical techniques so that the information generated can assist many parties in making a decision. To overcome the above problems used the right data mining technique, namely sentiment analysis. Therefore, this research tries to do sentiment analysis to see people's perception of the issue of increasing electricity tariffs on social media Twitter using the Naïve Bayes method by classifying sentiments to be positive, negative, and neutral. From the results of research that has been done, it can be seen that the most negative sentiment is formed in response to the issue of the increase in electricity tariffs.

Keywords: Sentimen Analisis, Twitter, Klasifikasi, Naive Bayes