ASOSIASI RULE MINING UNTUK REKOMENDASI PADA TRANSAKSI PEMINJAMAN BUKU MENGGUNAKAN FREQUENT PATTERN

The purpose of this study is to provide recommendations for grouping books at the ITB STIKOM Bali library, Jimbaran Campus. Currently, the placement of books in the ITB STIKOM Bali library, Jimbaran Campus, is still using a manual catalog. To make it easier for staff to manage books in the library, especially in terms of book data that can be borrowed, recommendations for grouping and placing books in the library are made based on the data on books that are most often borrowed together by library visitors obtained from previous borrowing data. This is done by data mining using the frequent pattern method. The use of this frequent pattern method is applied to the borrowing data of the ITB STIKOM Bali library at Jimbaran campus so that information or knowledge is obtained about recommendations for placing books that will be loaned to library members. This data mining processing is done using Weka software. The results of processing from the Association Rule data mining obtained 5 itemset combinations with confidence values ​​of 0.97, 0.96, 0.95. With the results of this data mining, the librarian obtains recommendations for grouping and placing books in the library through knowledge of the types of books that are most often borrowed.