Association Rules for Taking Students’ Subject Using Apriori Algorithm on Higher Education

Sari, Vivi Nila and Sarjon, Defit (2021) Association Rules for Taking Students’ Subject Using Apriori Algorithm on Higher Education. International Journal of Grid and Distributed Computing, 14 (1). pp. 313-324. ISSN 2005-4262

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Abstract

Information technology at University of Putra Indonesia Yptk Padang has advanced and has been following technological developments in the current 4.0 Revolution era. Almost all lecturers follow and master the development of information technology to support its quality in the process of teaching, research and community service in accordance with the Tri Dharma of Higher Education which must be worked by a lecturer. In the learning process, a lot of data that will be stored without exception is the student grade data. One of the highlights is the application of data mining to determine the pattern of each value with another value. Data mining aims to find relationships between one item and another in a data set. In this research, data mining that will be used is using the Association Rule Apriori algorithm. The Apriori method will generate Support, List, and Confident values. The values generated by Apriori will determine the formation of a pattern. This study resulted in 12 new rules that meet the minimum support value (25%) and minimum confidence (50%). Based on the data on the value data of the UPI Yptk Padang management students, the pattern found is the relationship between the value of one course and the value of other courses.

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