Analysis of Sequential Book Loan Data Pattern Using Generalized Sequential Pattern (GSP) Algorithm

Tri Astuti, Lisdya Anggraini

Abstract


As a center for learning and information services, STMIK Amikom Purwokerto Library is a source of learning and a source of intellectual activity that is very important for the entire academic community in supporting the achievement of the college Tridharma program. Book lending transaction data, can produce information that is important as supporting decision making when further analyzed. One useful information is that it can provide information in the form of user behavior patterns in borrowing books that are used to maintain the availability of related book stocks to be balanced. This study uses the Generalized Sequential Pattern (GSP) algorithm, which can be used to determine the behavior patterns of users in each transaction and can show relationships or associations between books, both requested simultaneously and sequentially. From the calculations that have been done, 295 frequent sequences are consisting of 3 sequence patterns that are formed from the minimum support of 0.53% or the minimum number of books borrowed, namely 2 books. Three book items have very strong linkages in book lending transactions, namely book code 6690, 2026, and 8131.

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Keywords


Data mining, Association rules, Apriori algorithm, Minimal support, Confidence.

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IJIIS: International Journal of Informatics and Information Systems

ISSN:2579-7069 (Online)
Organized by:Departement of Information System, Universitas Amikom Purwokerto, Indonesia; Faculty of Computing and Information Science, Ain Shams University, Cairo, Egypt
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