Analisis sentimen data ulasan menggunakan metode naive bayes studi kasus the Wujil Resort & Conventions pada situs tripadvisor - Rahanto, Faris Febri; Kharisudin, Iqbal (Universitas Negeri Semarang, 2021)
The tripadvisor site provides information on visitor reviews of The Wujil Resort & Conventions. Each visitor can provide a review in the form of criticism, suggestions, or ratings of the hotel. The number of incoming reviews, it requires a special technique to extract information from these reviews. This study aims to analyze the sentiment of the review data using the Naive Bayes Classifier method. Web scraping is used to get data online on website pages, namely collecting visitor review data for The Wujil Resort & Conventions. The process of classifying the review data will be carried out using machine learning using the Naive Bayes Classifier method. Furthermore, the classification results will be analyzed using the text mining method, the main concept is to carry out extensive exploration and extraction with a large and growing number of data. So that we find facts and information that are considered important and can be useful for various fields of purpose. The classification using the Naive Bayes method shows an accuracy rate of 76.6%. In general, with the text mining method, information is obtained that there are more visitors who give positive ratings than visitors who give negative ratings.