Tourist Perceptions Through Sentiment Analysis to Support Tourism Development in Maluku Province
Abstract
Tourist perceptions obtained by sentiment analysis can provide an overview of tourism development in Maluku Province. This study aims to determine the perception of tourists towards destinations in Maluku based on the results of sentiment analysis. This research uses a quantitative approach by analyzing scrapping and snipping data from Facebook, Instagram, TikTok, Google Maps Review, and Trip Advisor. Sentiment analysis is done by comparing the accuracy level of the Random Forest, Naïve Bayes, and Support Vector Machine classification models. The results of the comparison of the three methods show that Random Forest has the best accuracy rate, which is 85%. The results of sentiment analysis both on the entire dataset and the results of analysis per district/city show that tourists' perceptions of tourist destinations in Maluku can be said to be good because they are dominated by negative sentiments. The existence of negative and neutral sentiments indicates that there is a need for improvement and improvement in the quality of tourist services in terms of human resources, transportation, accommodation, and infrastructure facilities.
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