Analisis Sentimen Ulasan Pengguna Game Pubg Di Google Play Store Menggunakan Algoritma Naïve Bayes
DOI:
https://doi.org/10.30865/json.v5i3.7264Keywords:
Sentiment Analysis, PUBG, Algoritma Naive Bayes, Confusion Matrix, Play StoreAbstract
In today's digital era, technological development is very rapid and sophisticated. The online gaming industry has also evolved. Online games are a variant of video games that are played online via the internet. When users connect with other users, users can interact and work together. Battle rolaye games, such as Player Unknown's Battlegrounds (PUBG) have become one of the most popular of the many online games available. PUBG games offer a large-scale gaming experience that creates a dynamic gaming experience. One of the advantages of the PUBG game is that it has an attractive visual design and high quality graphics so that the game feels more realistic. However, this cannot guarantee satisfaction for users. To find out user sentiment towards the PUBG game, sentiment analysis using the Naïve Bayes Algorithm is carried out which aims to find out how accurate the Naïve Bayes Algorithm is used in classification. Data is taken using web scrapping techniques as many as 1000 user reviews in the Google Play Store review column. After going through preprocessing, the data is divided into 50% training data and 50% testing data. Prediction results tend to be positive with 578 positive sentiments and 232 negative sentiments. Based on evaluation using confusion matrix, the results are 83.95% for accuracy, 88.10% for precision, and 89.62% for recall.
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