@thesis{thesis,
		author={ALDILA MAULANA FAJAR  Lalu},
		title ={Implementasi Algoritma Frequent Pattern Growth Untuk Rekomendasi Item Paket Menu di Angkringan Waru Tanjung Bias},
		year={2021},
		url={http://repository.universitasbumigora.ac.id/783/},
		abstract={Angkringan is a place that sells various kinds of drinks and food. One of them is Angkringan Waru which has several types of food, drinks, and snacks. Angkringan waru wants a menu package containing the best-selling items that make it easier for their customers to find their favorite menu from 85 types of menu items in one menu package containing two items. To solve this problem, data mining techniques are used, namely the association with the Frequent Pattern Growth (FP-Growth) algorithm which will be implemented into a website-shaped program, the output of the application that is built is information in the form of a rule consisting of two itemset with a correlation value, so that it can used as a menu package recommendation. The transaction data used are 870 which uses a minimum support value of 20%, a minimum confidence level of 50%, which will result in 57 rules and a lift ratio value exceeding 1.0 consisting of 2 itemset.}
		}