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Mistakes in choosing a study program specialization by students are a problem that can affect their academic results and academic future. This research aims to overcome this problem by applying data mining methods using the Apriori algorithm in the context of identifying association patterns between courses in the Informatics Engineering study program at Harapan University, Medan, Faculty of Engineering and Computers. By using this algorithm, this research provides a solution for designing a curriculum that is more efficient and relevant to the needs of students and industry. The research results show that the Apriori algorithm is able to identify patterns of association between course choice and student interest with a high level of confidence. An example is the correlation between student standards and the choice of certain study programs such as Multimedia and Networking. This analysis provides valuable insight for universities in optimizing curriculum preparation to better suit students' interests and needs, thereby improving the quality of higher education. By using the Apriori formula, the algorithm steps are carried out by looking for Itemset Frequency, Support, Confidence, Pruning, and Generate Association Rules. This research found an association between stambuk and students' choice of study program at Harapan University, Medan, Faculty of Engineering and Computers. For example, there is a significant association between the 2021 standard and the Multimedia study program, where 40% of students with the 2021 standard also chose the Multimedia study program, with a confidence level of 76.67%.
Keywords: Data Mining, Students, Apriori, Study Program.
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