- Conference Article
3
- 10.1109/icera53111.2021.9538789
Implementation of Process Mining to Discover Student Learning Patterns using Fuzzy Miner Algorithm (Case Study: Learning Management System (LMS) Telkom University)
- Jul 29, 2021
- Larasati Valensia + 2 more +2
A learning management system is a system that supports student learning with several components. Telkom University is an institution that has an LMS called CeLOE LMS (Center for e-Learning and Open Education Learning Management System). Using LMS supports students' learning process, and lecturers can monitor what activities are carried out by their students. The pattern of learning by students can affect the success of learning in certain situations. The influence of these learning patterns makes lecturers need to pay attention to differences in student learning patterns. The data that will be used in this research are Website Application Development and Enterprise Systems courses. This study uses a process mining method with fuzzy miner algorithms to overcome the "spaghetti-like" process model into a more straightforward and easier-to-understand form. The resulting process model will then be analyzed using the graph simplification process method to obtain an accurate process model that describes the event log. In the Website Application Development course, conformance for all students Event logs is 99.93%, while conformance for students with index A event log is 99.94%. In the Enterprise System course, both event logs show the best conformance of 100%. The modeling produced by the two courses shows that the resulting model has a close alignment between the fuzzy model and the event log to reflect the behavior observed in the event log.
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