Sentiment Analysis of Restaurant Review with Classification Approach in the Decision Tree-J48 Algorithm

In the increasingly fierce restaurant business competition, many restaurants compete to provide the best quality for consumers. The quality of the restaurant includes food and drink, environment, place and service. The condition affects the restaurant brand image that is marked whether consumers are satisfied or not. One of review restaurant website called TripAdvisor is chosen as the data source because it contains User-Generated Content features (UGC). The advantage of using UGC is to ensure the authenticity of consumer comment data. English texts classification is used in this study to determine dissatisfaction (negative) and satisfaction (positive) of consumers based on their comment or review. This paper utilises Decision Tree-J48 as the classification method in this study. Data retrieval is done by crawling data using WebHarvy. The overall performance of the Decision Tree-J48 method is the average value of Precision 48.7%, Recall 36.8%, F-Measure 41.40% and accuracy 45.6%. The benefit of this classification results is as a recommendation for consumers to choose the best restaurant.