Applying Data Mining of Association Rules as Decision Making In Coffee-Shop: a Case Study

This study aims to transactions analysis from a coffee shop transaction in six months to define consumer purchases pattern with the development of a model of association rules. One of the coffee shops in Jakarta, the 8th Bean Cafe, was used as a study case in this study. The problems that occurred when deciding not based on data analysis, so they lost for 3 sales periods. This cafe has 80 menus that keep changing every time according to the owner’s wishes without knowing the favorite menu, the most frequently purchased menu, and so on. They never analyze what menu that consumers are interested in buying. Based on the results found 3 association rules, namely {CLASSIC $\Rightarrow$ SIGNATURE}, {FRIED RICE AND PASTA $\Rightarrow$ LIGHT BITES}, {LIGHT BITES FRIED RICE AND PASTA} from sales transaction data mining. The rules provide information that two types of 2-itemset combinations tend to buy together.

I. Introduction

The application of data mining and knowledge discovery has attracted all parties because of its ability to find new and useful patterns in data to acquire knowledge and apply it. One of the most important trends of modern business is the possibility to create more customized product and service offerings [1], including in the food industry.