Sales Analysis at Supermart to Determine Marketing Strategy Using Apriori Algorithm - Priyandini Pramithasari; Anindya Dewi Nariswari; Dhian Satria Yudha Kartika (Internasional Journal of Data Science, Engineering, and Anaylitics, 2022)
Supermart as a place to shop must have many products that are sold to consumers. Supermart has sales transaction data that occurs every time and the longer the data produces a collection of transaction data. So, it is very unfortunate if it is not analyzed again. In this study, the data used is sales data at supermarts from 2015 to 2018 as many as 9994 supermart transaction data. This data analysis can use data mining methods with a priori algorithms so that they can find new patterns that can help and support companies in understanding business better, and can predict future results. Using Association Rules with Apriori Algorithm, Supermart Grocery can find out the products with the number of sales and the relationship between products with other products or called Itemset. With the support and confidence values, researchers can find out whether the association rules are important or not, and the higher the support and confidence values, the more accurate the association rules will be. The results of the study show that the association rules with the a priori algorithm can be applied by the company in supporting decision-making in the company so that it can determine the right marketing strategy. Thus, supermart companies can analyze consumer purchasing patterns in buying a product based on a combination of 2 items/categories, so that supermarts can make bundles of these items/categories.