Sentiment Analysis on Customer Perception towards Products and Services of Restaurant in Labuan Bajo

Abstract

Analysis of consumer sentiment towards restaurant products and services in the form of reviews on various digital platforms such as Tripadvisor determines business sustainability and the image of tourist destinations. This study aims to classify visitor sentiments as Tripadvisor users towards Happy Banana Komodo, MadeInItaly, Mediterraneo, and La Cucina restaurants in Labuan Bajo. The research stages are divided into three parts, namely the stages of data collection, data processing, classification and evaluation of model performance, and interpretation of data and information. At the data collection stage, Tripadvisor user reviews of products and services at each restaurant are mined using the Webharvy application based on the configuration of the customer name, date of examination, rating, review title, and review. The data mining results are cleaned and prepared to be managed using the RapidMiner application at the data processing stage. The classification and evaluation stage of model performance is the implementation and testing of classification algorithms that are relevant to the dataset, namely Decision Tree (DT), Naïve Bayes (NB), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN). The findings of this study indicate the implementation of the positive and negative sentiment classification method for the comprehensive review data from the Tripadvisor website for the products and services of restaurants Happy Banana Komodo, MadeInITaly, Mediterraneo, and La Cucina Restaurants are relevant with k-Nearest Neighbor (k-NN) with accuracy value of 99.27% ​​, a precision value of 100%, and a recall of 98.53%.