Text Mining and Support Vector Machine for Sentiment Analysis of Tourist Reviews in Bangkalan Regency

Abstract

Abstract Tripadvisor is a travel site that offers reviews of hotels, flights, restaurants and tourist attractions. Reviews from tourists are indispensable for developing tourism, but the number of comments will complicate the owner to analyze the important aspects of the review so that the reviews should be beneficial to develop spot, overlooked or unreadable. This research aims to facilitate the owner of tourist places in the Bangkalan regency to classify negative opinion, positive opinion, and to know the target opinion using techniques sentiment analysis. The initial stage of the sentiment process analysis on this research is Web scrapping on the TripAdvisor site, the purpose of this stage to collect user review data. The review Data obtained will then be classified using the Support Vector Machine (SVM) method. Further review data classification results will be processed using the Text Mining method, to find the target opinion that is considered important in the review. Based on the research that has been done, obtained the accuracy of the classification process with SVM method of 70.22% for Indonesian-language reviews. A post-publication change was made to this article on 20 Apr 2020 as the previously published article was a duplicate.