Analysis of Student Achievement with K-Means on Socioeconomic, Behavioral, and Psychological Factors

Abstract

This study aims to analyze students' academic achievement based on socio-economic, behavioral, and psychological factors using the K-Means clustering method. The data used include various variables such as family income, internet access, learning motivation, stress levels, and student attendance. The results of the analysis show that students can be grouped into three different clusters: Cluster 1 consists of students with good socio-economic backgrounds, high motivation, and better academic achievement; Cluster 2 shows students with higher levels of stress that affect their achievement even though they have adequate access to education; and Cluster 3 reflects students from less supportive socio-economic backgrounds, with limited internet access and low study time, so their achievement is lower than other clusters. The Davies-Bouldin Index (DBI) calculation result of 0.63 shows a fairly good cluster separation. This analysis reveals that socio-economic factors have a significant impact on students' academic achievement, while psychological aspects such as motivation and stress levels also play an important role in determining learning success. Intervention programs focused on stress management and increasing access to education are recommended for students from Cluster 2 and Cluster 3 to improve their academic outcomes. This study provides insight into the importance of socio-economic and psychological factors in shaping students' academic achievement.