Educational Data Clustering Menggunakan K-Means pada Seleksi Penerimaan Peserta Didik Baru Madrasah Aliyah Negeri Unggulan

Noor Wahyudi (Universitas Islam Negeri Sunan Ampel)
Yunita Ardilla (Universitas Islam Negeri Sunan Ampel)
Nanik Puji Hastuti (Direktorat Kurikulum, Sarana, Kelembagaan, dan Kesiswaan Madrasah Kementerian Agama)

Systemic: Information System and Informatics Journal
Vol. 7 No. 2 (2021): Desember

The National Students admissions (SNPDB) for Madrasah Aliyah is managed by the Directorate of Madrasah Curriculum, Facilities, Institutions and Student Affairs. It is essential for the Directorate and Madrasah to explore patterns and knowledge from admission data in formulating policies and programs from to MAN. Educational Data Clustering (EDC) is a data mining method that is implemented in the education area. K-means is applied to group students based on the results of learning potential and academic potential tests that will be used for development program and student admission policies at MAN-IC. The best results from the experiments tested with Silhouette dividing the data into 2 clusters are excellent and good. The Silhouete value indicates the cluster structure in the medium predicate.. The results present the distribution of clusters in 23 MAN-IC, distribution of personality profiles of prospective students, as well as recommendations for conducting tests in Madrasah.