Journal of Data Science Methods and Applications
Vol. 1 No. 1 (2025)

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

Salsabila Shahibah (Unknown)
Novita Triyasri (Unknown)
Adisty Anggi Inanti (Unknown)
Jovita Rachel (Unknown)
Niko Diki Pratama (Unknown)
Andriansyah (Unknown)

Article Info

Publish Date
23 Apr 2025

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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Journal Info
Journal of Data Science Methods and Applications
Website

Abbrev

JoDMApps

Publisher

Institut Informatika dan Bisnis Darmajaya

Subject

Biochemistry, Genetics & Molecular Biology Computer Science & IT Engineering Library & Information Science

Description

Theoretical Foundations: Architecture, Management and Process for Data Science Artificial Intelligence Classification and Clustering Data Pre-Processing, Sampling and Reduction Deep Learning Educational Data Mining Forecasting High Performance Computing for Data Analytics Learning Classifiers ...