Uncovering patterns in online database usage at UiTM Negeri Sembilan: a data mining approach/ Mohd Aizat Abd Halim and Safawi Abdul Rahman

This study investigates online database usage patterns at Universiti Teknologi MARA (UiTM) Negeri Sembilan through a data mining approach, specifically utilizing association rule mining and the Apriori algorithm. The primary objective is to analyze user behavior in accessing 23 subscribed online databases, aiming to uncover correlations between academic programs and database access patterns. Findings reveal significant associations among databases, indicating that certain programs are more likely to access specific databases together. For instance, students enrolled in Library Management and Food Technology programs frequently accessed both Emerald Insight and ScienceDirect. The study highlights a concerning trend of decreased database usage despite rising subscription costs, emphasizing the need for improved user engagement strategies. By profiling users based on their database access, the library can tailor its services to better meet the needs of its community, ultimately enhancing the academic experience. The research underscores the importance of data mining in optimizing resource allocation and improving library services in the digital age.