PENERAPAN ALGORITMA APRIORI UNTUK REKOMENDASI BUKU PADA AMIKOM RESOURCE CENTER
Keywords:apriori, Association Rules, Data Mining, Book Recommendations
Amikom Resource Center each time producing recorded data, the activity is carried out for years so that it makes Big Data. The big data has the opportunity to produce information that can be useful for borrower and library management.
One of the data mining techniques that can be used is the Apriori algorithm with the association rules technique. By using book lending transaction data, apriori algorithm will form association rules between books which are then used to determine book recommendations. In addition, the results of apriori analysis can also be used by the library as information to findout which books are often borrowed, the placement of the book layout in the Amikom library.
The results showed that the association rules formed from 562 book lending transaction data in November 2019 used a minimum book frequency of 4 or a minimum support value of 0.7% and a minimum confidence of 80% resulting in 10 association rules with all rules having a positive correlation so that it can be used as a reference for giving book recommendations.