Name : Cisco Salya Wicaksana NPM : 2006596604 Study Program : Information Systems (SI) Supervisor : Prof. Dr. Dra. Kasiyah, M.Sc. Dr. Eng. Lia Sadita, S.Kom, M.Eng. Education has evolved with the rise of electronic learning applications and websites, necessitating students to adapt to a new learning style, exemplified by SCeLE, the learning management system (LMS), based on Moodle, for the Faculty of Computer Science at Universitas Indonesia. The study conducted a comparison of online learning behavior between courses available on SCeLE unlike other studies focusing on a single course, revealing four distinct engagement patterns identified through the K-Means clustering algorithm applied to SCeLE data. These patterns reflect quality students, deadliners, daily observers, and at-risk students, based on three metrics: intensity, measuring the amount of activities in a single session; frequency, counting the number of sessions or course accesses; and engagement, assessing activities deemed engaging within each session, such as uploading assignments or completing quizzes. The findings show that SCeLE implementation impacts student online learning behavior by restricting the availability of interactive features, often resulting in students accessing SCeLE more frequently than activities available. Additionally, the survey results indicate that students found SCeLE satisfactory in supplementing their learning efforts. Keywords: Online Learning Behavior, SCeLE, Clustering