Assosiation Rules for Product Sales Data Analysis Using The Apriori Algorithm - Pamungkas, Jarseno; Handrianto, Yopi (Politeknik Ganesha Medan, 2020)
To increase sales transactions, the company must be able to compete with other competitors so that it requires an appropriate strategy in carrying out the sales process carried out. In addition to the marketing strategy, the company must be able to analyze the products sold based on the number of sales that have occurred so that the company can see which products are more dominant in consumer demand so that the company can determine a more effective sales strategy. PT. Surya Indah City is a company engaged in the sale of various clothing and accessories. In an effort to increase sales of its products, an analysis is needed to be able to increase company revenue by utilizing sales transaction data it has. To analyze the relationship between clothing products and accessories which are more predominantly sold and other available clothing and accessories products, a data mining algorithm is used, namely the a priori algorithm. With the help of the tanagra application to carry out the calculation process, the dominant product that consumers are interested in can be determined. By using two variables that meet support and minimum confidence, it can be concluded that the most sold products are from the type of clothing, namely clothes and pants. It was concluded that the results of the known final association rules, if you buy a shirt, you will buy pants with 50% support and 75% confidence. If you buy pants, you will buy clothes with 50% support and 85% confidence.