Implementation of Association Rule Method for Promotion Strategy Using the Apriori Algorithm: Case Study: Snada Accessories Store

One indicator of a business's success is the extent to which its products can be sold within a certain period of time. An inappropriate marketing strategy will potentially result in wasting time and money, and potentially harm the business's reputation in the eyes of customers. Snada Accessories Store sells mobile phone and computer accessories, but does not have a specific reference in designing its marketing business strategy and still relies on estimates. In addition, they have not been able to manage the growth of their data which is increasingly accumulating in large numbers, so that the data does not produce valuable information and becomes useless. This study aims to apply data mining to process sales data using the association rule method to show the associative value between the types of products purchased by customers, so that a pattern is seen in the form of what types of products are often purchased by these customers. The final result achieved is the formation of an association rule 2 itemset with a confidence value of 100 %, namely a combination of robot data cable items rdl100s robot charger rt-k8, and an association rule 3 itemset with a confidence value of 41.18 %, namely robot headset re10, robot headset re701, robot headset re101s. Both association rules have a Lift Ratio <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$&gt;1$</tex>, which means that the combination of product items is valid and can be used as discount products, product packages, and product placement for the promotional strategy development process.