Santoso, Leo Willyanto and Yulia, (2018) Predicting Student Performance Using Data Mining. In: 5th International Conference on Communication and Computer Engineering, 19-07-2018 - 19-07-2018, Malacca - Malaysia.
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Abstract
Supporting the goal of higher education to produce graduation who will be a professional leader is a crucial. Most of universities implement intelligent information system to support in achieving their vision and mission. One of the features of Intelligent Information System is student performance prediction. By implementing data mining method, this feature could precisely predict the student’ grade for their enrolled subjects. Moreover, it can identify students that are at risk in failing a course and allow top educational management to take corrective actions. In this research, linear multi regression model was proposed to build model for every student. Based on the testing result on large set of students, courses, and activities shows that these models are capable of improving the performance prediction accuracy by over 15%
Item Type: | Conference or Workshop Item (Paper) |
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Uncontrolled Keywords: | education; student; data mining; prediction |
Subjects: | L Education > LB Theory and practice of education > LB2300 Higher Education |
Divisions: | Faculty of Industrial Technology > Informatics Engineering Department |
Depositing User: | Admin |
Date Deposited: | 01 Aug 2018 17:20 |
Last Modified: | 07 Sep 2018 17:04 |
URI: | https://repository.petra.ac.id/id/eprint/18007 |
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