Rekomendasi Paket Menu Angkringan Waru Tanjung Bias Dengan Algoritma Frequent Pattern Growth Berbasis Web

  • Lalu Aldila Maulana Fajar Universitas Bumigora Mataram
  • Ria Rismayati Universitas Bumigora Mataram
Keywords: Data Mining, Fp-Growth Algorithm, Assosciation, Rule, Transaction Data

Abstract

Culinary business using carts selling various kinds of heavy food, light and drinks, is favored by many people to just fill their stomachs, gather with friends and even family. Culinary businesses or culinary destinations like this are known as Angkringan which are increasingly mushrooming in the millennial generation. Angkringan Waru, located in Tanjung Bias, is a gathering destination for all people to enjoy a relaxed atmosphere on the beach. Angkringan Waru provides 85 types of menus for its customers, the many menus often confuse customers in choosing snacks while enjoying the beachside atmosphere. Starting from these problems, data mining techniques are used with the Frequent Pattern Growth (Fp-Growth) algorithm to recommend items in producing a menu package consisting of 1 snack item and 1 drink item. The dataset used is transaction data from Angkringan Waru as many as 870 transactions, the resulting output is a menu package recommendation rule and implemented in a web for Angkringan Waru. The Fp-Growth Data Mining Application by providing a minimum support value of 20% and Confident 50% with a lift ratio > 1 produces 57 rules or menu package recommendations that will be offered to Angkringan Waru customers. The results of the application in the form of 57 menu package recommendations are then used as recommendations for Angkringan Waru customers, where these menus are the favorite menus of customers at Angkringan Waru.

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Published
2021-08-10
How to Cite
Fajar, L. A. M., & Rismayati, R. (2021). Rekomendasi Paket Menu Angkringan Waru Tanjung Bias Dengan Algoritma Frequent Pattern Growth Berbasis Web. JTIM : Jurnal Teknologi Informasi Dan Multimedia, 3(2), 91-97. https://doi.org/10.35746/jtim.v3i2.138
Section
Articles