Analisis Klastering dari Data Behavior Online Gaming Menggunakan Algoritma K-Means

Salsabila Shahibah; Novita Triyasri; Adisty Anggi Inanti; Jovita Rachel; Niko Diki Pratama; Andriansyah

Analisis Klastering dari Data Behavior Online Gaming Menggunakan Algoritma K-Means

Authors

Salsabila Shahibah Institut Informatika dan Bisnis Darmajaya
Novita Triyasri Institut Informatika dan Bisnis Darmajaya
Adisty Anggi Inanti Institut Informatika dan Bisnis Darmajaya
Jovita Rachel Institut Informatika dan Bisnis Darmajaya
Niko Diki Pratama Institut Informatika dan Bisnis Darmajaya
Andriansyah Institut Informatika dan Bisnis Darmajaya

Keywords:

K-Means Algorithm, Online Game, Clustering

Abstract

Games that require an internet connection are called online games. Just like offline games, online games also have many genres. Some of them are Action, advanture, sports, RPG, and simulation. The emergence of various types of online games provides many choices to eliminate boredom in filling free time. In addition, there are also various levels such as easy, medium, and hard. The levels in this game also affect the habits of players in playing games. This study aims to find the optimal cluster in the dataset using clustering analysis using the K-Means algorithm on the RapidMiner application. The results of this study show that cluster 1 at k=3 from (k=2-7) is the best cluster compared to other clusters

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Published

2025-04-23

How to Cite

Salsabila Shahibah, Novita Triyasri, Adisty Anggi Inanti, Jovita Rachel, Niko Diki Pratama, & Andriansyah. (2025). Analisis Klastering dari Data Behavior Online Gaming Menggunakan Algoritma K-Means. JoDMApps (Journal of Data Science Methods and Applications), 1(1), 18–24. Retrieved from https://journal.darmajaya.ac.id/index.php/JoDMApps/article/view/912