eprintid: 8103
rev_number: 8
eprint_status: archive
userid: 46
dir: disk0/00/00/81/03
datestamp: 2024-08-29 07:40:34
lastmod: 2024-08-29 07:40:34
status_changed: 2024-08-29 07:40:34
type: thesis
metadata_visibility: show
creators_name: Yudiansyah, Yudiansyah
creators_name: Anggraeni, Irma
creators_name: Denih, Asep
creators_NPM: 065117089
contributors_type: http://www.loc.gov/loc.terms/relators/THS
contributors_type: http://www.loc.gov/loc.terms/relators/THS
contributors_type: http://www.loc.gov/loc.terms/relators/TRC
contributors_name: Yudiansyah, Yudiansyah
contributors_name: Anggraeni, Irma
contributors_name: Denih, Asep
contributors_NIDN: 0418018902
contributors_NIDN: 0406097101
corp_creators: Universitas Pakuan
corp_creators: Fakultas Matematika dan Ilmu Pengetahuan Alam
corp_creators: Program Studi Ilmu Komputer
title: Sistem Rekomendasi Menu Makanan dan Minuman dengan 
Metode K- MEANS dan FP-GROWTH
ispublished: pub
subjects: QK
divisions: sch_ecs
full_text_status: public
abstract: Sistem Rekomendasi Menu Makanan dan Minuman dengan 
Metode K- MEANS dan FP-GROWTH pada Cafe Milarian
Asep Denih1)
, Irma Anggraeni 2)
, Yudiansyah3)
1,2,3 Program Studi Ilmu Komputer, Fakultas Matematika dan Ilmu Pengetahuan Alam, 
Universitas Pakuan
1,2,3 Jl. Pakuan No.1, Ciheuleut, Bogor, 16143
Email: 1asep.denih@unpak.ac.id, 
2
irma.anggraeni@unpak.ac.id, 
3
yudiansyah04@gmail.com
Research aims to enhance operational efficiency and customer experience in a cafe 
through the implementation of data mining-based technology. The two main methods used 
in this study are K-Means Clustering and the FP-Growth Algorithm. K-Means is 
employed to group customers based on their menu preferences and purchasing behavior, 
while FP-Growth is used to analyze frequently occurring purchase patterns. The 
implementation of K-Means enables the cafe to devise more targeted marketing 
strategies, adjusting menus and promotions to meet customer needs. Additionally, FP�Growth aids in identifying relationships between frequently co-purchased menu items, 
allowing the cafe to create more enticing bundled offers and boost cross-menu sales. The 
implementation of this technology is expected to have a positive impact on customer 
satisfaction, increase sales, and optimize inventory management in the cafe. By 
combining these two methods, cafes can improve operational efficiency, provide a better 
customer experience, and compete effectively in the increasingly competitive cafe 
industry.
Keyword : Caffe Technology Efficiency, K-Means, FP-Growth, Product 
Recommendation
date: 2024-01-28
date_type: published
pages: 35
institution: Universitas Pakuan
department: Fakultas Matematika dan Ilmu Pengetahuan Alam
thesis_type: Skripsi
thesis_name: Sarjana
citation:   Yudiansyah, Yudiansyah and Anggraeni, Irma and Denih, Asep  (2024) Sistem Rekomendasi Menu Makanan dan Minuman dengan Metode K- MEANS dan FP-GROWTH.  Skripsi thesis, Universitas Pakuan.   
document_url: http://eprints.unpak.ac.id/8103/1/LAPORAN%20SIDANG%20SKRIPSI%20-%20065117089%20-%20Yudiansyah.pdf
document_url: http://eprints.unpak.ac.id/8103/2/HALAMAN%20PENGESAHAN%20%281%29.pdf