Penerapan Algoritma Association Rules Dalam Penentuan Pola Pembelian Berdasarkan Hasil Clustering
DOI:
https://doi.org/10.30865/mib.v7i3.6129Keywords:
Association Rule Mining, Apriori, Davies Index Bouldin, FP-Growth, K-MedoidAbstract
Zanafa Bookstore is one of the bookstores in Pekanbaru city that is required to meet customer needs and has the right focus in developing sales strategies every day. During the new school year there is an increase in sales, it is known that in July there are the most purchase transactions which are the beginning of the new school year for students and students. In addition, the placement of the book layout is only based on the employee's estimated shelf so that it will affect the convenience of consumers in choosing and finding books if the books are arranged far apart. By placing the layout in accordance with consumer purchasing patterns, it can improve the quality of customer service in bookstores. The book layout can also be used as a reference when adding book stock, information is needed by utilizing transaction data using data mining, namely by using Association rules commonly called Market Basket Analysis. This research uses K-Medoid for clustering on Apriori and FP-Growth in generating rule patterns on large-scale data. Several experiments were conducted on K-Medoid starting from cluster 2 to cluster 7, each of which will be applied to Apriori and FP-Growth with 30% support and 70% confidence. By comparing the evaluation results of each algorithm with each other, it is known that FP-Growth has superior results to Apriori with a total strength of rules of 1.2012. So that the results of the association rules obtained can be used as a reference in the placement of book layouts in the Zanafa bookstore.References
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