Track: Industry 4.0

Abstract

Global trade competition in using technology is getting tougher in meeting customer demands. The company stores sales data such as Sukku Coffee & Space. Is a family business in the food and drink industry that has problems in using data for marketing strategy. Promotion is a communication tool to introduce company products so that they can be known to the public and attract buyers to increase company sales. Market Basket Analysis (MBA) helps businesses make scientific decisions by conducting Association Rule Mining between items purchased simultaneously by customers. Analytics helps provide product recommendations and promotions, resulting in more targeted marketing strategies and attracting more customers. The results of designing an analytical data mining model using MBA with Association Rules method using FP-Growth and clustering techniques with K-Means. The initial data set of sales transactions is 34,745 data which is pre-processed so that the data results are 32,802 data with the attributes of time, total collected, items, total items, receipt number. Clustering was carried out for processing 32,802 datasets using RFM. Then normalized with Z-Transformation processed using RapidMiner with 10 iterations of cluster 3, resulting in Cluster 0 producing 17,038 items categorized as frequently purchased, Cluster 1 producing 11,459 items categorized as sometimes purchased, Cluster 2 producing 4,305 items categorized as rare. purchased. From the data validation test, the result of the smallest performance vector value is Avg. within centroid distance_cluster_0 with a value of -0.716. The results of the MBA processing in the recommendation of product promotion, namely sukkuaren with chocolate with a support value of 0.156 and a confidence value of 0.991.