Data Mining Technique to Determine the Pattern of Fruits Sales & Supplies Using Apriori Algorithm

Abstract

Advances in technological developments in the current 4.0 era require retail businesses to increase sales and develop marketing strategies. Determination of which products are widely sold and which products will be propagated in inventory is very important for retail businesses to prevent data accumulation. Data Mining has been widely used to conduct analysis, determine patterns and associations. In this paper, we propose a basic methodology for calculating association analysis with apriori algorithms used to process the most sold products and which products will be propagated in the sales inventory. The results of this study are the calculation model of high-frequency pattern analysis and the formation of association rules and item set combination patterns resulting from the sale of fruit products from retail with the highest support and confidence of the most sold fruit products. Therefore the apriori algorithm can help develop sales strategies.