Sentiment Analysis System Of Bali Tourism Using Naive Bayes Algorithm And Web Framework - Utami, Nengah Widya; Purnama, I Nyoman; Prayoga, I Made Ari (Jurnal Info Sains : Informatika dan Sains, 2024)
To obtain trends and impacts that may occur in the Bali tourism industry after the pandemic requires tourism actors to maintain the existence of the tourist beauty and culture they have. This research aims to develop a sentiment analysis system in the Bali tourism sector using the Naive Bayes algorithm and the Web Framework. This research stages carried out include Data Collection (Scraping), Data Cleaning, Feature Extraction, Modeling, and Web Platform Development. The data used was 2779 review data. The results show that most of the visitor reviews are in the "Very Positive" category, namely 1244. Next, 776 reviews are in the "Positive" category, 328 "Neutral”. The words that appeared most frequently included “place”, “walk”, “beautiful”, “nice”. The evaluation results show that the Bayes algorithm shows an accuracy value of 71%, which means Naive Bayes produces sufficient accuracy for sentiment analysis. In this research, we succeeded in developing a website with a web framework to predict the sentiment of a review in real time and it is hoped that it can help related parties understand and respond to reviews more effectively, improve the tourist experience, and advance the tourism sector in Bali.