Apriori Method for sales optimization of rafin's snack product as UMKM - Alvin Bryan Saputra; Erza Sofian (International Journal of Education, Information Technology, and Others, 2023)
This research is a quantitative research using a descriptive method that adopts CRISP-DM as a research stage. The purpose of this research is to find out what snack products sell the most and determine marketing strategies from the association rules obtained to increase sales. The data source used is primary data, namely sales transaction data for the period January 2021 to December 2021 obtained from the owner of Rafin's Snack house. The results of this study show that the apriori algorithm can be used to find association rules and determine the most sold snack products and can determine sales strategies, with a minimum Support and minimum Confidence determined, namely Support 30% and Confidence 50%. The association rules found, it is known that the most sold snack products are Salted Egg and Hot Bomb, and the right marketing strategy is to bundle products. The a priori algorithm is influential in knowing what snack products sell the most and can determine marketing strategies, from the association rules obtained, it is known that if consumers buy Salted Egg, 67% (certainty that consumers buy items) will buy Hot Bomb, and if consumers buy Hot Bomb, 75% will buy Salted Egg, and marketing strategies by bundling Salted Egg and Hot Bomb products with products that are less attractive to consumers, namely, shredded catfish, coffee, and banana sale.