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IJSTR >> Volume 8 - Issue 7, July 2019 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Sentiment Analysis Of Traveloka App Using Naive Bayes Classifier Method

[Full Text]



Ronal Watrianthos, Sudi Suryadi, Deci Irmayani, Marnis Nasution, Elida F. S. Simanjorang



App Store, Feedback, Machine Learning, Naïve Bayes Classifier, Sentiment Analysis,Text Mining, Vmap.



Traveloka is currently the most popular startup in Indonesia with share traffic reaching 78.49% using smartphone and monthly visits which reached 28.92 million based on a report in similarweb.com in May 2019. Traveloka, based on record, has been downloaded 10 million times since 2014 with rating reaches 4.4 out of 5 stars. As of May 2019, there were 386,646 reviews from users in the PlayStore, ranging from positive and negative reviews. However, it is necessary to analyze with certain methods to summarize the review. Every review given will get a conclusion after collected, and sentiment analysis will provide user experiences from the Traveloka application within certain period. This research was conducted using the Naïve Bayes Classifier method based on a review from the playstore to determine service quality. The purpose of this study is to find out the perceptions of users based on the measurement of service quality so that the results can be an evaluation for Traveloka in improving services. Studies show that during this period public opinion produced negative sentiments with Vmap value of 0.31020 greater than positive sentiment with a value of 0.16132.



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