Implementation of Naive Bayes classifier algorithm on social media (Twitter) to the teaching of Indonesian hate speech

Twitter is a social media that is widely used as a sharing medium on the internet. There are tweets containing sentences shared by the user, thus they can be read by the other users. A lot of information can be obtained from Twitter. Twitter users can connect with the other Twitter users in an international scale. Technology that is growing as today can be used for various things, especially regarding the information distributed in social media, specifically Twitter. One of the problems derived from social media is that Twitter tweets containing speechesin the form of both positive and negative utterances. From the problems above, a research is required to classify tweets that contain positive and negative speeches orutterances using naive bayes classifier method. The results of this study are implemented into a system that can classify tweets on Twitter. The system is built using js Node technology and Naive Bayes classifier as the calculation method of classification. Based on the tests performed, the best accuracy generated by the systems using the Naive Bayes Classifier is 93%.