Cover
Vol. 19 No. 2 (2023)

Published: December 31, 2023

Pages: 25-34

Original Article

Fairness Analysis in the Assessment of Several Online Parallel Classes using Process Mining

Rachmadita Andreswari 1 Ismail Syahputra 2
1Department of Information System - Telkom University, Bandung, Indonesia
2Department of Information System - Widyatama University, Bandung, Indonesia
History
  • Received: December 21, 2022
  • Revised: January 21, 2023
  • Accepted: January 27, 2023
  • Available Online: April 8, 2023
DOI

https://doi.org/10.37917/ijeee.19.2.4

Abstract

The learning process in online lectures through the Learning Management System (LMS) will produce a learning flow according to the event log. Assessment in a group of parallel classes is expected to produce the same assessment point of view based on the semester lesson plan. However, it does not rule out the implementation of each class to produce unequal fairness. Some of the factors considered to influence the assessment in the classroom include the flow of learning, different lecturers, class composition, time and type of assessment, and student attendance. The implementation of process mining in fairness assessment is used to determine the extent to which the learning flow plays a role in the assessment of ten parallel classes, including international classes. Moreover, a decision tree algorithm will also be applied to determine the root cause of the student assessment analysis based on the causal factors. As a result, there are three variables that have effects on student graduation and assessment, i.e attendance, class and gender. Variable lecturer does not have much impact on the assessment, but has an influence on the learning flow.

Keywords

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