PENGELOMPOKAN DATA NILAI SISWA MADRASAH TA’HILIYAH MENGGUNAKAN METODE K-MEANS CLUSTERING - Fahrillah Fahrillah; Zaehol Fatah (CV. Denasya Smart Publisher, 2025)
Data mining, or data mining is the process of collecting and processing data to extract important information. The stages in the data mining process are useful for finding a particular pattern from a large amount of assessment data. This goal is to find out and form student data clusters based on grades so that they become a cluster, so that the results of student clusters can be a reference in improving student grades in the next learning process. The results of the evaluation and assessment of students are carried out by teaching staff or teachers in conducting assessments during the learning process. In the learning process there are 2 assessment categories, namely UTS and UAS student grades. The results of grouping student grade data using the K-Means clustering method show that based on the results of student data clusters in one semester, cluster 0 is obtained with 7 students, cluster 1 is 3. The results of testing using rapid miner show that there are 7 students who have grades with a good average and there are 3 students with a poor average grade.