Algoritma Apriori Dalam Identifikasi Pola Pembelian Konsumen Pada Produk Minuman

Abstract

Competition between companies is getting tougher and entrepreneurs indirectly need a better product marketing strategy. Inventory management system is a very popular business in Indonesia, especially in the beverage industry. Related to inventory, there is a technique in the development of science today, one of which is data mining techniques or mining techniques. In data mining, a priori algorithms contain a type of association rules that aim to find interesting relationships between combinations of elements hidden within the dataset. The application of a priori algorithm in this study can help Pekopen tavern managers find the right consumer buying behaviour . So that it can be used as material for business decision-makers  to determine marketing strategies and optimize sales of menu variants, especially for several types that are in great demand. These results are used to find new information to determine a better product marketing strategy. Data processing using apriori algorithm is carried out by conducting the highest frequency analysis based on the minimum support value followed by determining the association rules based on the confidence value and then continued with the evaluation process through determining the lift ratio. There are 2000 sales transaction data processed from the data processing process obtained from a combination of itemset {Chizu Redvelvet, Cokolateh} with a support value of 40% and a confidence value of 67%.