Classification Of Students Based On Factors That Affect Student Learning Achievement Using The K-Means Clustering Algorithm (Case Study: STMIK Kaputama Binjai)

Abstract

In the world of education, students are the main object of every educational implementation that always prioritizes disciplines that are beneficial to the students themselves. However, in lecture activities there are students who are diligent in participating in lecture activities and there are also those who rarely participate in lecture activities, this can be caused by internal and external factors, so that there can be significant variations in student learning achievements, with some achieving high grades, while others face difficulties in achieving the same achievements. Based on the description of the problem, the researcher conducted a study that aimed to group students based on factors that affect student learning achievement using the k-means clustering algorithm. The results of the research conducted produced 3 clusters with cluster 1 there were 5 data, the group of students with a very satisfactory predicate GPA (3.50-4.00), supported by both internal and external factors (interval 3.1-4). Cluster 2 has 3 data, the group of students with a satisfactory predicate GPA (3.00-3.49), supported by both internal and external factors (interval 2.1-3), and cluster 3 has 5 data, the group of students with a satisfactory predicate GPA (3.00-3.49), supported by both internal and external factors (interval 3.1-4).