Implementation of Data Mining on Sales of Badminton Equipment Using the Apriori Method

IMPLEMENTASI DATA MINING PENJUALAN PERALATAN BADMINTON DENGAN MENGGUNAKAN METODE APRIORI

Abstract

Sales of badminton equipment are increasingly needed, with sales transaction activities every day the data will increase over time, to find out which types of goods are most in demand an a priori algorithm is needed. The a priori algorithm is a type of association rule in data mining. One of the related stages of pattern analysis that has attracted the attention of many researchers to develop efficient algorithms is high-frequency pattern analysis. The importance of associations can be recognized with support and confidence. Support is the probability that consumers will buy several products at once from the number of transactions, while confidence is the strength of the relationship between items in the association rules. The determination of the itemset used is a combination of 1, 2, and 3 with a minimum support of 40% and a minimum confidence of 70%. A priori algorithms help develop marketing strategies.