IMPLEMENTASI ASSOCIATION RULE UNTUK REKOMENDASI PAKET PROMOSI PENJUALAN BERDASARKAN DATA TRANSAKSI (Studi kasus: CV Agro Sukses Abadi Yogyakarta)
Sri Andayani, Universitas Negeri Yogyakarta, Indonesia
Abstract
The development of the retail business in Indonesia is currently so rapid accompanied by competition in the sale of various types of products. The number of products sold in a certain period of time is one measure of the company's success. These conditions encourage business actors to maintain their business. One effort that can be done is to carry out promotions. Sellers often experience difficulties about what promotional packages should be sold in order to increase profits. This can be done by processing sales transaction data, so that a conclusion is obtained that the product that is most in demand by customers is known as an association pattern. One of the algorithms that can be used to form association rules is the a priori algorithm. The data used is sales transaction history data for CV Agro Sukses Abadi for one year, from July 2021 to June 2022, totaling 2,523 transactions. The results of forming association rules using the a priori algorithm show that 801 rules are obtained with a minimum support of 0.001 and a minimum confidence of 0.5. The most sold product was Organic Diabetic Rice and the least sold was Sukkari dates Based on these rules, 4 product sales package recommendations were obtained that could increase profits, one of which was Blackfit and Organic Black Rice.
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