| dc.description.abstract | Student academic evaluation is part of the
learning process in order to control the student’s learning
progress. The evaluation will show whether the student will pass
or fail and for an instructor to guide for future evaluations on
performance. There are criteria such as student’s gender,
student’s age when they are registered in university, student’s
1st semester GPA, etc., which exist in academic data can be
utilized to get the student academic performance using multi-
criteria decision making. Multi-Objective Optimization by
Ratio Analysis (MOORA) and Simple Multi-Attribute Rating
(SMART) was two simple technique in multi-criteria decision
making that the criteria weight can be determined objectively
using entropy and gain values. This paper tries to evaluate the
student academic performance using MOORA and SMART
with criteria weight and sub-criteria weight resulted from
entropy and gain. Decision output out of MOORA and SMART
then compared with actual data using confusion matrix to
discover the performance of those criteria and sub-criteria
weight. The result showed that the performance of criteria
weight with accuracy was 60.9 percent and the criteria of fourth-
grade point average have the biggest impact on student
academic evaluation with 0.1589 of weight. The result of this
research can be used to help the instructor to determine the
weight of student criteria for future recommendations and
evaluations on student performance. Keywords— student, academic, evaluation, entropy, MOORA,
SMART | en_US |
