Analisis Pola Pembelian Konsumen pada Swalayan Surya Menggunakan Algoritma Apriori

Abstract

Data mining is a technique for extracting new information from data sets. Information is considered very important and valuable as it can help achieve desired goals. Therefore, not only individuals compete for information, but also trading businesses such as Swalayan Surya. This supermarket is strategically located in a residential area, which of course affects the level of sales there. With sales transaction activities every day, transaction data continues to grow and cause data accumulation. Unfortunately, Swalayan Surya has never analyzed the sales patterns made to consumers, even though this analysis can provide very important strategic information. This information can be used to increase profits and optimize product control in the decision-making process. Sales pattern analysis can help in various aspects, such as ensuring the availability of products that are always on the shelves, identifying products that are closely related to other products, and placing these products strategically to make it easier for consumers to find and buy the products they need. Thus, Swalayan Surya can provide a better shopping experience to consumers while improving operational efficiency and store profits. However, until now, this transaction data has only been used as an archive and has not been properly utilized, even though the dataset contains very useful information. The association method using the Apriori Algorithm is one of the data mining techniques that is useful for finding association patterns based on consumer shopping patterns so that it can be seen what product items are commonly purchased together by consumers. The results of this study show that the combination of Aqua and ABC Milk Coffee products has the highest support value of 50% and a confidence value of 60%, with a lift ratio value of 2.50 which shows a positive (strong) correlation.