Open AccessImplementation of a priori algorithm for book lending at state high school library I Silima Pungaga-Punga Parongil
Author(s) -
Andini Yulistia Ningsih,
Volvo Sihombing,
Sahat Parulian Sitorus
Publication year - 2022
Publication title -
sinkron
Language(s) - English
Resource type - Journals
eISSN - 2541-2019
pISSN - 2541-044X
DOI - 10.33395/sinkron.v7i1.11257
Subject(s) - reading (process) , a priori and a posteriori , computer science , apriori algorithm , association (psychology) , state (computer science) , association rule learning , information retrieval , algorithm , data mining , psychology , political science , law , epistemology , philosophy , psychotherapist
The library plays a role in helping students to enjoy reading books. The availability of books in various fields motivates students to come to visit the library, students / i can read or borrow library books. For this reason, the purpose of this research was carried out including helping library officials apply the rules of how to visit the libraries.
In carrying out research methods, including conducting direct observations, conducting interviews to collect the necessary data. The pattern that will be analyzed is the pattern of borrowing what books are often borrowed so that library officials know the information of books that are often borrowed. The result obtained is with the application of a priori algorithms, book data is processed to produce a pattern of borrowing books. After all high frequency patterns are found, then the association rules are sought that meet the minimum requirement for associative confidence A→B minimum confidence = 25%. The final association rules are ordered based on minimum support and minimum confidence, if borrowing IPA, then borrowing MTK Support = 15%, Confidence = 42.8%.