Open AccessTHE OPTIMIZE OF ASSOCIATION RULE METHOD FOR THE BEST BOOK PLACEMENT PATTERNS IN LIBRARY: A MONTHLY TRIAL
Author(s) -
Tariq Husain,
Nuzulul Hidayati
Publication year - 2021
Publication title -
teknokom : jurnal teknologi dan rekayasa sistem komputer/teknokom
Language(s) - English
Resource type - Journals
eISSN - 2686-3219
pISSN - 2621-8070
DOI - 10.31943/teknokom.v4i2.63
Subject(s) - documentation , association rule learning , computer science , information retrieval , value (mathematics) , process (computing) , key (lock) , data science , association (psychology) , service (business) , data collection , data mining , world wide web , psychology , statistics , mathematics , computer security , economy , machine learning , economics , psychotherapist , programming language , operating system
Data mining is the process of finding interesting patterns and knowledge from large amounts of data. Sources of information service, especially in the library, include books, reference books, serials, scientific gray literature (newsletters, reports, proceedings, dissertations, theses, and others). The importance of this research being carried out in the library in this study aims to implement data mining with the association rule method to solve problems, especially in the placement of shelves based on the category of the printed version of the book collection. This research method uses a qualitative research approach. Data was collected using documentation techniques and deep analysis of existing weaknesses to identify user needs whose information was obtained through observation and interviews with key informants (admin, user, etc.). For example, the determination of the best book placement patterns can be done by looking at the results of the tendency of visitors to borrow books based on a combination of 2 item sets with 60 percent of confidence value every month or week and must be evaluated or take a calculate again.