K-Means Analysis in Grouping Abilities of Battuta University Informatics Study Program Students

This study aims to identify and classify students based on the learning outcomes of visualization and animation subjects measured based on the variables of attendance, assignments, midterm exams (UTS), and final semester exams (UAS) to be further used to evaluate learning for subjects that require proficiency. good quantitative analysis. This study uses k-means cluster analysis in classifying students into three groups based on their learning outcomes. After being grouped, there are 3 categories of cluster 0 with 14 competent conditions, 9 in incompetent condition cluster 1, and 9 students in very competent condition cluster