Market basket analysis using apriori algorithm to find consumer patterns in buying goods through transaction data (case study of Mizan computer retail stores)

Abstract

Mizan Computer Shop is a shop that is engaged in the trading sector, especially in the field of selling computers and supporting accessories. Growing and increasing number of business actors in the computer sector, can makes the players challenged to be able to create unique differentiation and clear positioning. So, that consumers can differentiate from their competitors. Competitive and dynamic market conditions make every company should always observe competition in their business environment. Retail stores need to use all of available resources including data. Data processing is expected to be able to provide information that can be used to support marketing strategies. One of the data processing methods that are often used in marketing strategies is the use of data mining techniques i.e Market Basket Analysis using a priori algorithm. The application is designed using the waterfall method which starts from analyzing user needs, designing a process using UML which consists of: Use Case Diagrams, Activity Diagrams and Sequence Diagrams . This Market Basket Analysis application was built using the PHP programming language. From the results of the analysis in this research, it can be concluded that for the combination of 2 items with the highest confidence value 100% and the lift ratio value 3.39 i.e if a consumer buys a Laptop Charger, he will also buy a keyboard and for a combination of 3 items with the highest confidence value 100% and the lift ratio value 2.17 i.e if a consumer buys a Joystick and Laptop, he will also buy a mouse.

Chinese Brand Identity Management Based on Never-Ending Learning and Knowledge Graphs

“…Apriori is a classic association mining algorithm, which is used to explore the association relationship between various data in the data set [20]. Apriori has three metrics: support, confidence, and lift.…”

A Study on the Use of Data Mining in the Planning of Investment Field

“…Nan and Chen (2020), using the physical fitness test data of university and college students, discovered the potential relationship between the Apriori algorithm and the indicators in the physical fitness tests, and offered suggestions for improving performance in this way. Qisman et al (2021) searched for association rules among the products sold using data from the computer store, and presented the 22 most preferred rules. Zeng et al (2021), using data obtained from 2,621 USGS indicators in the United States between 1981 and 2016, determined the relationships between annual stream flow trends and precipitation trends with the Apriori algorithm.…”

Research on Shopping Mall Sales Based on Apriori Association Rule Mining Algorithm

“…Based on the fact that the current merchants have increased sales to obtain higher profits, and customers have the purchase demand for related products, this paper mainly uses the Apriori algorithm mined by the correlation rules to explore the implicit laws between commodities and commodities [6]. By analyzing the data of a large number of customers to buy goods, we help customers make purchases, and at the same time optimize the layout of shopping mall goods, thereby helping shopping malls to improve profits.…”