Penerapan K-Means untuk Pengelompokan Hasil Belajar Informatika - Rahman, Taufik; Ahmad Sahroni, Abdul (The Indonesian Journal of Computer Science, 2025)
This study was conducted at SMK Kesehatan Prima Indonesia, which integrates informatics subjects into its curriculum, although the main focus is on developing students' health competencies. The main challenge faced is the management of informatics learning outcomes, especially in grouping students based on their understanding and achievements, which has been done manually and inefficiently. This study aims to identify groups of student learning outcomes using the K-Means Clustering method and describe the differences between the groups formed. This study is an exploratory study with a quantitative approach. The results of the clustering analysis on grade 10 students showed the formation of three groups: high score groups (24 students), medium score groups (51 students), and low score groups (42 students). In addition, learning interest and use of IT devices were shown to have a significant influence on informatics learning outcomes. These findings confirm that the application of the K-Means algorithm can improve the effectiveness of teaching strategies by grouping students in a more structured manner based on their learning outcomes.