Implementation Of Data Mining Using Algorithms A Priori in Determining The Pattern Of Product Purchases Perfume Sold Case Study On (Rafflesia Aromatic Professional Perfume)

Abstract

At the rafflesia aromatic professional perfume store, we have not used a special application in determining the purchase pattern of perfume products sold and still use manual data processing such as writing in books, and do not utilize existing sales data and sales data only as an archive. So tejadi accumulation of data that is not in the know the benefits. Basically, the data set has useful information to make a decision about the pattern of perfume sales that are sold. One method that can solve the above problems is the Apriori algorithm method. Because the apriori algorithm is a suitable algorithm used to determine the search for Frequent itemsets using the Assciation rule technique with transaction data that is used for 1 month (January 1, 2022 – January 30, 2022).With the amount of 25 data from 15 transactions, support items can be displayed minimum support Value = 10% as many as 10 perfumes consisting of Celebrity, Citra Edition , Alasca , Topaza , Rock Star ,Be Delicitions , La Verne , B Agua Marine, Jasmin Note , and garuda. For a combination of 2 itemset is to use support 15% which consists of, Celebrity-Citra Edition, Celebrity-Alasca, Topaza-Rock Star, Rock Star-be Delicitionse, La Verne-B aqua Marine, B aqua Marine- Jasmine Note, then look for the rules of association that can meet the minimum requirement for confidence is to calculate the confidence associative rules based on a ❸ ( ❸ ) B with a minimum value of support taken is 20%, then that meets that there is a perfume most purchased by consumers is Citra edication, celebrity, alasca ,celebrity topaza, rock star the minimum value of support taken is 20%, then that there is a perfume most purchased by consumers is Citra edication, celebrity, alasca ,celebrity topaza, rock star.