Comparison of Apriori and Fp-Growth Algorithms in Determining Package Menus at Sate Perawan Restaurant Sawangan Raya

The culinary creative industry holds promising prospects as it is a necessity for society. However, the variety of menu items and high customer demand lead to slow ordering processes, which hinder service at Rumah Makan Sate Perawan. Additionally, some menu items are less popular among customers. To address these issues, a system is needed to assist in determining food and beverage package menus based on association rules. This system aims to facilitate business owners in organizing packages and improving sales. This study employs the Apriori and FP-Growth algorithms, using sales transaction data collected over a four-month period. The research applies a minimum support of 0.1 for food, 0.01 for beverages, and a minimum confidence of 0.6 for both categories. The results indicate that there is no significant difference between the two algorithms in terms of the generated packages, lift ratio evaluation, and runtime. In the food category, 5 association rules were generated with an average lift ratio of 1.1929, while in the beverage category, 2 rules were generated with an average lift ratio of 1.8990.