Application of apriori algorithm to find relationships between courses based on student grades STMIK YMI Tegal - Hassan, Muhamad Nur; Gunawan, Gunawan; Arif, Zaenul (Institute of Computer Science (IOCS), 2024)
This research explores the application of the Apriori algorithm to investigate the relationship between courses based on student grades at STMIK YMI Tegal. This research focuses on analyzing the relationship between courses to support curriculum development that is responsive and relevant to industry needs and improves the quality of learning. The main objective of this research is to identify and understand relationship patterns between various courses based on student analysis scores using the Apriori algorithm, an effective data mining methodology for uncovering association rules between items in large datasets. By using a quantitative approach and quasi-experimental design, this research succeeded in analyzing grade data from various semesters, identifying combinations of courses that often appear together with high grades, indicating a positive correlation between related courses. The results of the analysis reveal that several basic courses play a significant role in forming a strong foundation for advanced courses, highlighting the importance of a capable curriculum structure. Although the lift scores show a neutral relationship, these findings provide important initial insights for further understanding of interactions between courses. The implication for curriculum development is the need to emphasize the integration of courses that have positive relationships to support a coherent learning process and increase student success.