ANALISIS SENTIMEN ULASAN PENGGUNA APLIKASI JASA OJEK ONLINE MAXIM PADA GOOGLE PLAY DENGAN METODE NAÏVE BAYES CLASSIFIER

Abstract

In this age of digitalization, public transportation has developed, such as the creation of Online Transportation or commonly called Online Ojek.  Online transportation is clear evidence of the development of application-based technology. Now with the Online ojek service can provide convenience in ordering ojek. Currently, more and more online ojek service companies are emerging, one of which is Maxim. Maxim has been enjoyed by approximately 47 cities in Indonesia. Maxim is also famous for its relatively affordable price. With the many enthusiasts of the Maxim application, the author is interested in conducting Sentiment Analysis on this application. Sentiment Analysis is done by analyzing user reviews of the Maxim application on the Google Play Store with the Naïve Bayes Classifier method. The author conducts this research, namely to find out the opinions or opinions of users which can later be used as input for application developers so that later the Maxim application can continue to be improved in terms of quality. The results showed that the Maxim application received many positive comments, but there were also some negative comments that could be used as evaluation material for the application developer.