<![CDATA[This study analyzes the interaction patterns between users of the Sumatra Institute of Technology (ITERA) Library through book borrowing data with a Social Network Analysis approach. A bipartite network was formed to describe the relationship between borrowers and books, then projected into two unipartite networks: the network between borrowers and between books. The network structure was analyzed using three centrality parameters, namely degree centrality, closeness, and relatedness. Community detection was performed using the Leiden algorithm, and community structure evaluation using the modularity metric. The results show a modularity value of 0.6646 in the borrower network and 0.6776 in the book network, indicating a strong community structure. These findings can be used to provide an overview of student reading tendencies in ITERA Library and a user behavior-based book recommendation system in higher education libraries.]]>
Copyrights © 2025
