Open AccessApp Review Sentiment Analysis Shopee Application In Google Play Store Using Naive Bayes Algorithm
Author(s) -
Dany Pratmanto,
Rousyati Rousyati,
Fanny Fatma Wati,
Andrian Eko Widodo,
Suleman Suleman,
Ragil Wijianto
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1641/1/012043
Subject(s) - sentiment analysis , computer science , naive bayes classifier , variety (cybernetics) , field (mathematics) , world wide web , service (business) , data science , artificial intelligence , support vector machine , mathematics , business , marketing , pure mathematics
An online marketplace site is a shopping place that is currently popular with the community because it offers a variety of convenience and one of the marketplace apps is Shopee. Some people are satisfied with the service provided by the Shopee app. But unisex some people who give complaints about this application. User-provided response to Shopee app in the Comments field of Shopee Google Play Store can be analyzed for negative and positive sentiments. This research aims to assist Shopee’s management of the positive or negative opinions of application users and can provide empirical evidence for related theories so that it can be used as a donation of thought for the development of theories Next. With the number of reviews shown, you need an analysis that can classify these reviews into positive or negative classes. The method used for the sentiment analysis of Shopee app reviews is the Naive Bayes algorithm obtaining an accuracy yield of 96,667%