Application Of Data Mining On Hijab Sales In Elzatta Gallery Pondok Ungu Permai Using Apriori Algorithm

Abstract

At the Elzatta Gallery branch in Pondok Ungu Permai Bekasi, sales information is not well organized, so the data is only an archive and will not be processed in the future, so it is useless, the date of purchase and the products that consumers buy are. not well organized making it challenging to find the best-selling products. Utilization of this data is done through data mining to find correlations with consumer purchasing habits, which products are sold the most at the same time, or what can be called associations between products. It is necessary to apply an application to group data according to trends that occur simultaneously at events using the a priori algorithm. It is expected that the application of the a priori algorithm in this study can find patterns in the form of products that are often purchased together. In the data mining method, researchers use an a priori algorithm to find products that can be purchased simultaneously to find out the relationship between goods and to find out which products sell the most, therefore researchers conduct sales research. data such as sample studies. In the Rapidminer test, it is shown that the highest support and trust scores are achieved when you buy a bottom, you buy an internal head, which has 56.6% 98.1% support. And when you buy a tunic, buy the hem with 50% 97.8% confidence backing.