Indian Journal of Science and Technology
Year: 2018, Volume: 11, Issue: 39, Pages: 1-7
Sumitra Nuanmeesri1 and Wongkot Sriurai2
1 Suan Sunandha Rajabhat University, Faculty of Science and Technology, Bangkok, Thailand; [email protected]
2Ubon Ratchathani University, Ubon Ratchathani, Thailand; [email protected]
*Author for correspondence
Suan Sunandha Rajabhat University, Faculty of Science and Technology, Bangkok, Thailand; [email protected]
Objective: To examine the relationship of courses and tendency to attain weak study outcome to assist and protect students from school expulsion in higher education. Statistical Analysis: The data used for operating the Apriori algorithm in association rule was the grade points of the students from the Department of Information Technology, Faculty of Science and Technology, Suan Sunandha Rajabhat University, who each studied 23 courses in the general education category and the information technology category in total. This data had been recorded between 2011 and 2016 (3,200 records). Findings: The accuracy of thirty association rules with test data of 1,200 student records was real study outcome of all students from academic year of 2017 to 2018. Data from these 2 academic years were not used to formulate the rules. According to evaluation of rules’ efficiency defined by accuracy was 89%. Application/Improvement: The association rules to provide, assistance, approaches and mentorship to students with risk via online social media. These students would be able to adapt themselves and attained better study outcome.
Keywords: Academic Support, Apriori Algorithm, Educational, Prediction
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