THE IMPLEMENTATION OF ASSOCIATION RULES IN ANALYZING THE SALES OF AMIGO GROUP

Abstract

A retail company usually produce large sales transactions data. These data can be utilized with the application of data mining, which is also known as knowledge data discovery. Association rules is one of the most famous data mining study that can be used to generate items that frequently purchased together in sales transactions.

This project is a web-based data mining project for a company called Amigo Group. The algorithm used for association rules implementation is called FP-Growth algorithm. This algorithm will form a data structure called FP-Tree and extract the rules based on its FP-Tree. The result of this application will be used to help Amigo Group’s managers understand about customers buying behavior and analyze pattern of items which are usually purchased together. Then, the manager can create marketing strategies in order to increase sales of the items.

Key Words: Data Mining, FP-Growth, FP-Tree.