ALGORITMA APRIORI DALAM MENENTUKAN POLA KONSUMEN TERHADAP TATA LETAK BARANG

Abstract

The world of trade competition requires managers to improve strategies to survive in competition, as well as the Great Stationery Store that sells stationery and office supplies. With sales transactions carried out every day, the data stack is only stored as an archive. Data Mining is a solution for decision making in developing a business. One of them is to arrange the layout of goods which greatly affects the level of sales seen from the way consumers buy goods outside of planning. By utilizing data on sales transactions that accumulate, it will produce consumer patterns to find out shopping habits and consumer buying interest. The effective data mining method for preparing the goods layout uses the Apriori algorithm association method. By using the Apriori algorithm it can produce a combination of goods purchased simultaneously from consumer patterns and produce high association rules. Sales transaction data processing using Apriori algorithm will be tested using RapidMiner software to find accurate association rules. The results of this study found 4 association rules with a minimum value of 5% support and 50% confidence which are expected to be able to recommend businesses in the preparation of the layout of goods to improve sales strategies.