Design of a Video Game Review System Using Naïve Bayes Algorithm - Diny Anggraini Adnas; Eric Sanjaya (Universitas Internasional Batam, 2024)
The rapid development of the technology marks the emergence of social medias. Collaboration, two-way communication, and friendships with other social media users are facilitated through functions such as comments (comment/retweet) and likes or dislikes. This research aims to examine how video game reviews are perceived within a system based on data obtained from Kaggle. Data mining processes will be conducted using machine learning methods, specifically the Naïve Bayes Classifier algorithm. This classification method is based on probability and Bayes' theorem, assuming attribute independence. The research results indicate that the use of Naïve Bayes shows a significance level of 0.46%.