Penerapan K-Means dengan Evaluasi Davies-Bouldin Index untuk Pengelompokan Kelas Unggulan SMP Wijaya Sukodono - Feny Anggraeny; Ade Eviyanti; Sumarno (SMATIKA JURNAL : STIKI Informatika Jurnal, 2025)
This research was conducted at Wijaya Sukodono Middle School, one of the largest schools in Sukodono District which seeks to improve the quality of education by utilizing student academic data. The main objective of this research is to group students based on academic scores using the K-Means Clustering method, which aims to divide students into two categories: Superior Class and Regular Class. The Flagship Class is defined as a group of students with high academic performance, while the Regular Class includes students with lower academic performance. The research method involves collecting report value data, processing, and data transformation, followed by the application of the K-Means algorithm. Evaluation was carried out using the Davies-Bouldin Index (DBI) to assess the quality of clustering. The analysis results show that of the 576 students, 488 students are included in the Superior Class and 88 students are in the Regular Class. The two cluster configuration provides optimal results with a DBI value of 0.337, indicating a good level of inter-cluster certification. This research concludes that the K-Means method is effective in grouping students based on academic performance. These results provide insight into strategies for schools in developing more targeted learning programs to improve the quality of education. Further development can be done by including non-academic variables or exploring other clustering methods for more comprehensive results