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Journal : Proceeding of the Electrical Engineering Computer Science and Informatics

Building Student’s Study Path using Markov Chain Process with Apriori Cross Join Pearson Correlation Tekad Matulatan; Martaleli Bettiza
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 2: EECSI 2015
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (991.889 KB) | DOI: 10.11591/eecsi.v2.787

Abstract

Student’s study path could be advised by using bestpossible path from Markov Chain rule based on student’sacademic performance records with several assumption on thecurrent curriculum. Finding the Markov’s rule is crucial processbecause it will determine study path’s scenarios which rely onstudent current performance to choose the next best possiblepath. The rule would be built using the whole student’s academicperformance on the same curriculum by implementing AprioriCross Join Pearson Correlation Test on two consecutivesemesters. It will then create path consist of paired courses A->B with Pearson value that would be implemented as rule in Markov Process