Data Mining Menggunakan Algoritma K-means Untuk Menentukan Game Terpopuler Pada Platform Steam Dengan Rapidminer

Deryl Iman Condro Baskoro (Universitas Pamulang)
I Putu Ganesa Weda Pratama (Universitas Pamulang)
Aryo Chandra Ray Hash (Universitas Pamulang)
Muhammad Fakih (Universitas Pamulang)
Muhammad Fauzan (Universitas Pamulang)
Maulana Fansyuri (Universitas Pamulang)

Journal of Information Technology and Informatics Engineering
Vol 1 No 1 (2025): Journal of Information Technology and Informatics Engineering (JITIE)

With the number of games increasing every year, it is a challenge to determine which games are the most popular on the Steam platform. This study uses the K-Means clustering algorithm in RapidMiner to group games based on their popularity. Ratings and estimated number of game downloads are the variables used in this study. Data were collected from the top game sales dataset on the Steam platform. Clustering produces two clusters: less dan most populer, indicate the level of game popularity. This study can help game developers and publishers understand what features users are most interested in in a game.