Classification of community opinion on the use of the Transjakarta bus based on twitter social network using naïve bayes method

Abstract

At this time, social networking is becoming a very popular communication tool among Indonesians ranging from children to adults. One of them is Twitter, which has quite a lot of users. This social network is used by users to write their opinions on a matter. One of the topics discussed in the Twitter social network is the Trans-Jakarta bus. In this study, the opinions of Trans-Jakarta bus users listed on Twitter are only limited to positive and negative opinions. An application designed to predict positive or negative opinions using the Naïve Bayes algorithm. The Naïve Bayes algorithm was chosen because it only requires a small amount of training data to estimate averages and variable variations. The developed application can make it easier for decision-makers towards Trans-Jakarta to find out public opinion on Trans-Jakarta bus services. The resulting system accuracy is 73% because the amount of training data used is only 62.5% of the total data of 50 data. While the test data that has been used are only 30 data. The proportions of the training and testing data affect the level of accuracy, so if you want a higher level of accuracy you can reproduce the training data used.