Analysis and Application of The Mining Process to Identify Student Learning Behaviour On The Use of E-Learning After The Covid-19 Pandemic

Abstract

SMK Telkom Malang is a vocational high school in the field of Technology and Information Technology that implements technological advances and developments in the system, distance learning. E-learning is one of the learning media supported by computer and internet technology, which contains learning content. Student learning behavior in machine learning or E-Learning has a strong relationship in its use. The higher the quality of the application of learning in machine learning or E-Learning, the higher the achievement in obtaining data on student learning behavior in the use of e-learning recorded in the event log. This research uses Disco and ProM tools using the Heuristic Miner. Heuristic Miner is used because it is most suitable for handling process mining on event logs from Learning Management System because heuristic miners can express event logs well and reveal main events recorded in event logs and are able to handle data that has noise. The use of Petri Net in ProM tools helps in analyzing the process model to provide an overview of student learning behavior towards e-learning the actual Result of heuristic miner can model the event log into the process model well, seen from the average fitness of the RPL majors shows a value of 0.970.