Application of Association Method with FP-Growth Algorithm on Transaction Data of PT John Tampi Group

Authors

  • Dhea Indahsari Universitas Singaperbangsa Karawang

DOI:

https://doi.org/10.33884/cbis.v9i2.3835

Keywords:

FP-Growth Algorithm, Data mining, Association Method, Restaurant, Transaction

Abstract

The development of business in the food sector over time is increasing and is always growing and will never stop. With the rapid growth of the food business, there is competition between business owners. Businesses in the food sector on average do not require large capital but in practice investors or developers need to know the sales pattern so that it can be used as a reference as an effective marketing and sales strategy in developing development at a later stage. Not only that, competition in the culinary world is getting tougher since the pandemic status was announced. This adds to the challenge in the culinary world competition to find strategies that can increase sales and marketing of products sold, including through the use of product sales data. The application of the data mining association method using the FP-Growth algorithm is used to help find an association rule from product sales data at PT John Tampi Group. From the results of the tests carried out, the rules with the best Confidence value reached 100%.

Published

2021-09-30