IMPLEMENTASI ALGORITMA FP-GROWTH DAN APRIORI UNTUK PERSEDIAAN PRODUK

Dewi Anisa Istiqomah; Yuli Astuti; Siti Nurjanah

doi:10.33795/jip.v8i2.845

Dewi Anisa Istiqomah Universitas Amikom Yogyakarta
Yuli Astuti Universitas Amikom Yogyakarta
Siti Nurjanah Universitas Amikom Yogyakarta

DOI: https://doi.org/10.33795/jip.v8i2.845

Keywords: Apriori, FP-Growth, association rules, RapidMiner, product inventory

Abstract

Product inventory is an important thing that must be managed in a business, especially a retail business. Product inventory is Emyra Bedding Store's concern to maximize its services. Product inventory at the Emyra Bedding Store has not been managed properly, so several problems arise. If one of the ordered products is not available, then customer demand for a product will be hampered. In addition, sales transaction data continues to accumulate in large quantities every day and is only stored as data of unknown benefit. This study aims to determine the relationship between products with the Apriori and FP-Growth algorithms using the RapidMiner application. With this, it is expected to be a solution in managing product inventory. The research stages are data collection, data preprocessing, modeling with Apriori and FP-Growth algorithms, and evaluation of results. This study uses 150 transaction data and 17 products. The results of this study indicate that both algorithms can be used to determine association rules that can determine product linkages at the Emyra Bedding Store. The association rules generated by the Apriori algorithm are also generated by the FP-Growth algorithm. The Apriori algorithm produces 2 association rules and the FP-Growth algorithm produces 10 association rules with a minimum support of 0.05 and a minimum confidence of 0.7. The resulting relationship pattern can help the Emyra Bedding Store to monitor the stock of goods frequently purchased by customers so that there will be no supply shortage.

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