IMPLEMENTASI DATA MINING MENGGUNAKAN ALGORITMA APRIORI PADA TOKO RUMAH SKINCARE 88

Abstract

The purpose of this research is to implement the apriori algorithm on sales transaction data of cosmetic products at Rumah Skincare 88 store so that it can help develop marketing strategies and increase sales at the store. The results of this study are that the apriori algorithm was successfully implemented on the sale of cosmetic products at the RumahSkincare88 store.  The support values used are 3% and 10% and the minimum confidence values are 30% and 50%. The number of association rules generated is 17 with the highest support value of 14% and the highest confidence of 53.4%. The resulting association rule with the highest support and confidence value is if consumers buy Powder/Foundation then they will also buy Lips. The recommended marketing strategies are Cross-Selling and Bundling. For Cross-Selling strategy that can be applied is if consumers buy Powder/Foundation, then when they want to pay the cashier can offer to buy Lips as well. As for Bundling, the strategy that can be applied is to sell Face Serum and Sunscreen in one package at a special price.