Improving Naïve Bayes in Sentiment Analysis For Hotel Industry in Indonesia
Tata Sutabri, Agung Suryatno, Dedi Setiadi, Edi Surya Negara · 2018 Third International Conference on Informatics and Computing (ICIC) · 2018
In the online ordering process, sometimes purchasing services often face problems in determining the services chosen closest to the characteristics of the user. Ratings used by some marketplace are sometimes not objective with the content of reviews provided by users. This will reduce the level of trust the user provides in the ratings provided by the service. Therefore, this study will try to produce a comprehensive analysis, by reading and analyzing any reviews related to certain services. The burden for users is the number of reviews that are not small and the use of very different language styles. This study proposes a method that can provide a rating that is more in line with the content of the review in connection with the sentiments in the review. The method developed using the corpus on the topic model on the hotel management site. Sentiment analysis was obtained using the Naïve Bayesian method and the use of probabilistic values of the corpus. The test results showed the success rate of the method in analyzing sentiment was 89%. The results of sentiment analysis are used as a standard for calculating rating.