Analysis of Comment Classification on President Jokowi on Twitter Using Text Mining with the Naïve Bayes Classifier Algorithm

Abstract

Indonesia is led by a president. As a political figure and also head of state, a president will always have various comments from the public. In today's digital era, people channel these comments through the president's official social media, Twitter directly. Comments that often appear are about people's opinions on presidential performance issues. Because this comment is very much, so it is very difficult to group each comment thoroughly. To deal with this, a system is created that can automatically group comment data about the president on Twitter. Tweets will be acquired and processed using text mining. Grouping comment data using the Naïve Bayes Classifier algorithm. Text mining techniques and the Naive Bayes Classifier algorithm were successfully adapted to this system in categorizing and analyzing sentiments towards the president. This categorization has the best accuracy at 11 times the appearance of the word attribute, which has an accuracy of 79.70%.