Evaluation of student academic performance using e-learning with the association rules method and the importance of performance analysis
Date
2020-04-01Author
Ramadiani, Ramadiani
Kurniawan, Adi
Arifin, Zainal
Jundillah, Muhammad Labib
Azainil, Azainil
Alex, Rasni
Hidayanto, Achmad Nizar
Metadata
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Abstract. In managing the student study process, there is a pattern that occurs repeatedly every
year. The recurring data will produce information in the form of student profiles, entry paths,
student academic results, study period, average graduate-level and much other information as
long as students take the process of teaching and learning activities. This research was conducted
to predict student performance and e-learning satisfaction at the Computer Science department
in Mulawarman University using the Association Rules method and Importance Performance
Analysis. The sample in this study was 389 data of computer science graduate students. Based
on the results of the research that has been done, it can be concluded that the graduation rate of
computer science students of the Faculty of Computer Science and Information Technology, as
follows; students who have graduated most have a GPA interval of 2.76 - 3.50 with male gender
and take a study period of more than 6 years which has a support value of 0.321 and a confidence
value of 0.628. Their perception of e-learning according to IPA coordinates community,
collaboration, materials, social media, knowledge, synthesis, application, understanding,
multimedia, evaluation, video, and news in quadrant II has a high level of importance with a
relatively high level of performance and must be maintained.
URI
https://iopscience.iop.org/article/10.1088/1742-6596/1524/1/012107/pdfhttp://repository.unmul.ac.id/handle/123456789/4817