Implementing Association Rules Technique to Predict Student Result based on Historical Data

Abdul Aziz, Azwa and Jusoh, Julaily Aida (2012) Implementing Association Rules Technique to Predict Student Result based on Historical Data. In: 3rd Annual International Conference on Infocomm Technologies in Competitive Strategies (ICT 2012), 17-18 September 2012, Bali Indonesia.

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Abstract

University or Higher Learning Institution is a platform to train students in specific domain area that will become an asset for a country. One of the critical issues in University is to avoid dropout students. Educational Data Mining (EDM) is an emergent discipline in developing methods to explore the unique types of data from the educational context. One of techniques apply in EDM is Association Rules (AR) in order to find a pattern of one element that influence other element. In this paper, we are applying AR technique to predict students results based on a group of previous students results. Clustering method is used to classified specific subject category. Finally, a system known as Result Prediction System (REPS) is develops to perform AR analysis on academic data automatically using PHP and MYSQL databases.

Item Type: Conference or Workshop Item (Paper)
Keywords: Association Rules, Educational Data Mining,Educational Intelligence
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Institute: Faculty of Informatics & Computing
Depositing User: Mr. Azwa bin Aziz
Date Deposited: 20 May 2014 00:47
Last Modified: 20 May 2014 00:47
URI: http://erep.unisza.edu.my/id/eprint/1112

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