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.