APPLICATION OF ASSOCIATION RULE MINING FOR ANALYSIS OF BOOK LAYOUT PLACEMENT IN THE LIBRARY USING THE APRIORI ALGORITHM

Abstract

A library is a building that has a collection of library materials (books, magazines and other media) which are organized or organized in a certain way so that they can be easily used by users quickly and precisely. The Tangerang Regency Regional Library has 60,583 titles and 335,745 books. Based on the results of interviews in placing books in libraries, books are placed based on book categories which have been given a numbering called Dewey Decimal Classification (DDC). However, the placement of books has not been regulated by looking at the frequency of visitors borrowing books. Apart from that, end users have difficulty finding the whereabouts of books that are often borrowed. To overcome this problem, in this research the author will look for books that are often borrowed simultaneously by visitors, by analyzing book borrowing transaction data using the association rule mining method. This research uses the Apriori algorithm. From data from 1,550 book borrowing transactions over 3 years that have been processed to produce 4 rules with the largest item combination being the religious and social science book categories which are often borrowed simultaneously with a support value of 11.71% and confidence of 41.43%. Apart from that, the technology and social science book categories are often borrowed simultaneously with a support value of 13.8% and confidence of 40.75%. Based on these results, it is recommended to librarians to place these books on adjacent shelves based on book categories.