Implementation of the FP-Growth Algorithm in Sales Transactions for Menu Package Recommendations at Warung Oemah Tani

Implementation of the FP-Growth Algorithm in Sales Transactions for Menu Package Recommendations at Warung Oemah Tani

FP-Growth

Data Mining

Rekomendasi Menu

customer

Sale

Along with the rapid development of the culinary industry, business competition is also getting tougher. Warung Oemah Tani serves a variety of menus and drinks, but to provide satisfying service to customers, business people must try to develop new products. Under these circumstances, the menu recommendations for Warung Oemah Tani need to be analyzed so that the recommendations made are right on target. This study aims to analyze the sales of Warung Oemah Tani using the FP Growth algorithm. This algorithm identifies the data set with the highest frequency of concurrent sales (frequent itemset). The results of the association rules show that the highest support value is 0.520 and the highest confidence value is 0.929, with a minimum support of 30% and a minimum confidence of 80%. Obtained 14 rule associations that meet the minimum support and minimum confidence.

Triana, Latifah Adi

Khoerida, Nur Isnaeni

Widiawati, Neta Tri

Tahyudin, Imam

Internet of Things and Artificial Intelligence Journal; Vol. 2 No. 2 (2022): Volume 2, Issue 2, 2022 [May]; 111-121

2774-4353

Association for Scientific Computing, Electronics, and Engineering (ASCEE)

2022-05-19

Copyright (c) 2022 ascee.org

https://ascee.org/

application/pdf

eng

info:eu-repo/semantics/article

info:eu-repo/semantics/publishedVersion