<![CDATA[This study aims to analyze book borrowing patterns in the Faculty of Engineering Library, Malikussaleh University in order to determine the optimal book layout. Book borrowing patterns are analyzed using the FP-growth algorithm method, a data mining technique that is efficient in finding association patterns or relationships between items in large databases. The data used in this study include book borrowing records from January to April 2024. The results of the analysis show that there are several significant borrowing patterns between certain book categories, for example, books on programming are often borrowed together with books on information systems. Based on these findings, book layout recommendations are proposed so that books that are often borrowed together are placed close together, thus facilitating access for users and increasing the efficiency of the library layout. The use of the FP-growth algorithm in this study has proven effective in identifying hidden patterns in book borrowing data. Keywords: Library, Data Mining, FP-growth Algorithm, Web]]>
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