Rule-Based Classification of Student Performance using Apriori Method

Author(s)	Mr. Sushil Kumar Verma, Dr. Dinesh Kumar Sahu, Dr. Varsha Namdeo
Country	India
Abstract	Researchers have increasingly utilized data mining techniques to uncover hidden patterns and extract meaningful insights from raw data. In recent years, data mining has been effectively applied in various domains, including education, to enhance the quality of learning and institutional performance. Within the educational context, data mining facilitates the categorization of student performance by analysing academic data stored in institutional databases. Student performance is categorized based on multiple academic parameters. The categorization of student performance enables educators to identify academically weak students early in the semester.
Keywords	Data mining, Educational data mining, Association rule mining, Apriori algorithm, Data Transform.
Field	Engineering
Published In	Volume 6, Issue 5, September-October 2025
Published On	2025-10-23
DOI	https://doi.org/10.63363/aijfr.2025.v06i05.1677
Short DOI	https://doi.org/g97v6v

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