Twitter Social Media Sentiment Analysis in Tourist Destinations Using Algorithms Naive Bayes Classifier

Abstract

The current tourism destination in Indonesia has developed rapidly which is affected by the role of technology that has a major influence on freedom of access in seeking information. A tweet also has the possibility of containing information or condition about the tourist destinations that they will or have visited, such as the experience of visitors in the tour, the visitor's opinion on a tourist spot, and other tourist attractions. The Naive Bayes method employs training data in order to create the probability of each criterion for different classes; nevertheless, the probability values of the criteria can be elevated to produce sentiment analysis towards opinions on twitter. The research has been done by classifying an opinion in the form of comments into two classes, which is positive and negative with the level of accuracy that is influenced by the training process. Based on that, it can be concluded clearly that the public sentiment information to the tourist attractions included in the positive sentiment.