Sentiment Analysis of Restaurant Customer Reviews on TripAdvisor using Naïve Bayes

Abstract

Sentiment analysis is one method for classifying documents to identify positive or negative opinions. Customer satisfaction has an essential point for customer service. Customer behaviour is currently doing a lot of reviews in online media such as on trip advisor. A restaurant is a business that requires more attention in the service to consumers by improving service to customers continuously. This study tries to classify Surabaya restaurant customer satisfaction using Naïve Bayes. Data sampling is crawling by using WebHarvy Tools. The result from this research shows that these two methods get the customer response accurately and Naïve Bayes method is more accurate than TextBlob sentiment analysis with a different accuracy of 2.9%.