Course Selection Pattern Analysis Using Apriori Algorithm
DOI:
https://doi.org/10.56127/juit.v4i3.2326Keywords:
Data mining, Association Rule, Apriori, FP Growth, WekaAbstract
This research discusses Association Rules as one of the data mining functions implemented using the Apriori Algorithm. The Institute for Computerization Development (LePKom) is a unit at Gunadarma University that organizes courses and workshops. The course and workshop participants are Gunadarma University students from the following undergraduate and diploma programs: Bachelor of Information Systems (S1-SI), Bachelor of Computer Systems (S1-SK), Diploma in Information Management (D3-MI), Diploma in Computer Engineering (D3-TK), and Bachelor of Informatics Engineering (S1-TI). New students must select three course topics from the six fundamental courses available at the Institute for Computerization Development (LePKom), and from these three choices, students will be assigned one course each semester. Association rules can be generated using the Apriori Algorithm to identify patterns of which course topics are most frequently selected together by new students each semester, as well as to optimize course infrastructure requirements.
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