Penerapan Metode Bayes Pada Aplikasi Deteksi Ketergantungan Terhadap Pengguna Game Online

Abstract

In this era, online gamems are ectends all over the world. Almost all circles of people have a very high attachment to online games. Online games are a kind of fun game for players, because the can be played not only alone (Singleplayer), but cab also be played by two more players (multiplayer) from different places and different countries. One of the problems in society is the magnitude of the influence of online games, because online games themselves have an attraction that makes people more fun playing than learning. Based on the results of observations, it is proven by the large number of teenagers spending their daily time playing online games instead of reading books and can have other negative impacts such as lack of socializing, having a negative impact on health. To solve this problem, an expert system is needed by applying the Bayes method algorithm, based on the results of interviews with a counseling teacher, the results are in the form of data based on name, 3 types of dependency levels and 18 symptom data from online games. Therefore, the Bayesian method can predict future opportunities based on previous experience. From the results of this study, students were tested by answering 18 questions for each online game dependency symptom data. From the results of this study it can be concluded that there was a student who was diagnosed with heavy dependence on the use of online games with a bayes score of 0.84% or 84%. In addition, this research produced an application for detecting dependence on online game users by applying the Bayes method and has been successfully created and running well to help reduce online game users from being dependent anymore.