Implementasi K-Modes Clustering Untuk Pengelompokan Data Bermain Game Pada Mahasiswa Ditinjau Dari Durasi Belajarnya - Kustanto, Yoga; Ratna Arumi, Endah; Dimas Sasongko; Ully Artha, Emilya; Agung Prabowo, Nugroho (KLIK: Kajian Ilmiah Informatika dan Komputer, 2024)
The development of the internet has created a new means of entertainment, namely online games. Problems in learning motivation among students can be related to addiction to playing online games. This can be seen from students who often play games both during the lecture process and when they have finished studying. The problem with learning motivation is that there are students who experience a decline in achievement and experience problems with their personality, so this research aims to group students who play games according to the duration of playing games and the duration of studying. This research uses the K-Modes Clustering method to analyze the relationship between game addiction and learning motivation based on the duration spent playing games and studying. Data obtained through an online questionnaire survey of Muhammadiyah University of Magelang students includes information about the time students spend playing games and studying. The results of analysis on 90 student data using the k-modes clustering algorithm obtained good clustering results. The number of clusters produced was 2 clusters with cluster 1 totaling 63 members while cluster 2 had 27 members with a Cost value of 323. The results of clustering on game playing data required determining optimal clusters so this research used the Elbow method which obtained the optimal number of clusters of 6 clusters. with a cost value of 250. Apart from that, the clustering results were analyzed by looking at the distance from each cluster using the Silhouette Score whose value was 0.1531955 and the relationship between variables using a matrix obtained negative results.