abdussalam@stmiki.ac.id +6281260272238 Online Submission Open
Vol. 3 No. 2 (2026) • Articles
Open Access

Analisis Pola Pembelian Menu Coffee Shop Menggunakan Algoritma FP-Growth sebagai Dasar Rekomendasi Menu pada Sistem Kasir

Martianova Lusia Sihombing
Universitas Methodist Indonesia
Marchel Hamonangan Ritonga
Universitas Methodist Indonesia
Darwis Robinson Manalu
Universitas Methodist Indonesia
Published: September 28, 2026 Pages: 52-63
Original Full-Text Article
Download published version for reading and archiving
Download PDF
Abstract

Transaction data in cash register systems has the potential to serve not only as sales records but also to identify customer purchasing patterns that can support business decision-making. Unfortunately, the utilization of transaction data in coffee shops is often limited to sales reports, resulting in suboptimal use of the relationships between menu items. This study aims to analyze menu purchasing patterns using the Frequent Pattern Growth (FP-Growth) algorithm and to interpret the resulting association rules as a basis for menu recommendations in the cash register system. Employing a quantitative approach and descriptive methods, this research analyzes the public dataset The Bread Basket, which contains over 9,000 transactions. Data preprocessing was conducted using RapidMiner Studio through attribute selection and transformation stages. The FP-Growth algorithm was applied with a minimum support parameter of 5% and a minimum confidence of 20%, yielding two association rules: Bread → Coffee and Cake → Coffee. The Cake → Coffee rule demonstrates a positive relationship with a support value of 0.055 and confidence of 0.527, while Bread → Coffee does not indicate a positive association despite having a higher support value. These findings suggest that the FP-Growth algorithm is effective in identifying purchasing patterns that support menu recommendation logic.

Keywords:
Association Rule Mining FP-Growth Market Basket Analysis Menu Recommendation Cash Register System
Article Metrics & Downloads Graph
Monthly Download Trends:
Author Biographies
Martianova Lusia Sihombing Universitas Methodist Indonesia

Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Methodist Indonesia, Kota Medan, Provinsi Sumatera Utara, Indonesia.

Marchel Hamonangan Ritonga Universitas Methodist Indonesia

Program Studi Teknik Informatika, Fakultas Ilmu Komputer, Universitas Methodist Indonesia, Kota Medan, Provinsi Sumatera Utara, Indonesia.

Darwis Robinson Manalu Universitas Methodist Indonesia

Program Studi Teknik Informatika, Fakultas Ilmu Komputer, Universitas Methodist Indonesia, Kota Medan, Provinsi Sumatera Utara, Indonesia.

How to Cite
Sihombing, M. L., Ritonga, M. H., & Manalu, D. R. (2026). Analisis Pola Pembelian Menu Coffee Shop Menggunakan Algoritma FP-Growth sebagai Dasar Rekomendasi Menu pada Sistem Kasir. Jurnal Ilmu Komputer Dan Teknologi Informasi, 3(2), 52-63. https://doi.org/10.63447/jikti.v3i2.1960
License

This work is licensed under a Copyright (c) 2026 Jurnal Ilmu Komputer dan Teknologi Informasi .

Creative Commons Attribution 4.0 International License (CC BY 4.0)

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License .

  • Share: You are free to copy, distribute, and transmit the work in any medium or format.
  • Adapt: You are free to remix, transform, and build upon the work for any purpose, even commercially.
  • Attribution: You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
Copyright & Retention: Authors retain copyright without restrictions and grant this journal the right of first publication under an open-access model. The journal retains non-exclusive publishing rights for archiving, indexing, and scholarly dissemination.

References
Total: 18 References
  1. Alfitra, D., Afdal, M., Fronita, M., & Saputra, E. (2024). Analisa keranjang belanja untuk menentukan tata letak barang menggunakan algoritma FP-Growth. Jurnal Sistem Informasi, 13(4), 1651–1661. https://doi.org/10.32520/stmsi.v13i4.4268
  2. Amelia, R., Darmansyah, & Rismadin, A. M. (2024). Perbandingan algoritma Apriori dan FP-Growth dalam pengaplikasian market basket analysis untuk strategi bisnis retail. Building of Informatics, Technology and Science (BITS), 6(1), 279–288. https://doi.org/10.47065/bits.v6i1.5388
  3. Annur, H., Serwin, S., & Anisa, I. N. (2025). Analisis keranjang belanja pelanggan coffee shop menggunakan algoritma FP-Growth. JSAI (Journal Scientific and Applied Informatics), 8(3), 723–728. https://doi.org/10.36085/jsai.v8i3.8835
  4. Badan Pusat Statistik. (2025). Statistik penyediaan makanan minuman 2024. https://www.bps.go.id/id/publication/2025/12/31/e46a55af756331ede8016b91/statistik-penyediaan-makanan-minuman-2024.html
  5. Fahreza, M. Z., Jaman, J. H., & Maulana, I. (2025). Penerapan market basket analysis untuk rekomendasi paket menu menggunakan algoritma FP-Growth (Studi kasus: Kafe Shans Juice). Jurnal Informatika Dan Teknik Elektro Terapan, 13(3), 129–141. https://doi.org/10.23960/jitet.v13i3S1.7527
  1. Fernandez-Basso, C., Ruiz, M. D., & Martin-Bautista, M. J. (2024). New Spark solutions for distributed frequent itemset and association rule mining algorithms. Cluster Computing, 27(2), 1217–1234. https://doi.org/10.1007/s10586-023-04014-w
  2. Hery, & Widjaja, A. E. (2024). Analysis of Apriori and FP-Growth algorithms for market basket insights: A case study of The Bread Basket bakery sales. Journal of Digital Market and Digital Currency, 1(1), 63–83. https://doi.org/10.47738/jdmdc.v1i1.2
  3. Hewage, U. H. W. A., Sinha, R., & Naeem, M. A. (2023). Privacy-preserving data (stream) mining techniques and their impact on data mining accuracy: A systematic literature review. Artificial Intelligence Review, 56(9), 10427–10464. https://doi.org/10.1007/s10462-023-10425-3
  4. Hidayatullah, F. Z., Surorejo, S., Andriani, W., & Gunawan, G. (2024). Application of association rule for prediction of menu ordered at café Minapadi. Jurnal Mandiri IT, 12(4), 208–214.
  5. Jr Iztok, F., Fister, I., Fister, D., Podgorelec, V., & Salcedo-Sanz, S. (2023). A comprehensive review of visualization methods for association rule mining: Taxonomy, challenges, open problems and future ideas. Expert Systems with Applications, 233. https://doi.org/10.1016/j.eswa.2023.120901
  6. Lin, K.-C., Liao, I.-E., & Chen, Z.-S. (2011). An improved frequent pattern growth method for mining association rules. Expert Systems with Applications, 38(5), 5154–5161. https://doi.org/10.1016/j.eswa.2010.10.047
  7. Merliani, N. N., Khoerida, N. I., Triana, L. A., & Subarkah, P. (2022). Penerapan algoritma Apriori pada transaksi penjualan untuk rekomendasi menu makanan dan minuman. Jurnal Nasional Teknologi Dan Sistem Informasi, 8(1), 9–16. https://doi.org/10.25077/TEKNOSI.v8i3.2022.009-016
  8. Mittal, A. (n.d.). The Bread Basket. Retrieved June 6, 2026, from https://www.kaggle.com/datasets/mittalvasu95/the-bread-basket
  9. Mokkadem, A., Pelletier, M., & Raimbault, L. (2023). Association rules and decision rules. Statistical Analysis and Data Mining: The ASA Data Science Journal, 16, 411–435. https://doi.org/10.1002/sam.11620
  10. Putra, R. A., Putri, M. A. M., Sinaga, S. M., Octavia, S. F., & Rachman, R. C. (2024). Implementation of association rules algorithm to identify popular topping combinations in orders. Public Research Journal of Engineering, Data Technology and Computer Science, 1(2), 95–101. https://doi.org/10.57152/predatecs.v1i2.863
  11. Saputra, J. P. B., Rahayu, S. A., & Hariguna, T. (2023). Market basket analysis using FP-Growth algorithm to design marketing strategy by determining consumer purchasing patterns. Journal of Applied Data Sciences, 4(1), 38–49. https://doi.org/10.47738/jads.v4i1.83
  12. Srirahayu, A., & Pribadie, L. S. (2023). Review paper data mining klasifikasi data mining. Jurnal Ilmiah Informatika Global, 14(1). https://doi.org/10.36982/jiig.v14i1.2981
  13. Wulandari, U. M., Suseno, A. T., & Kholilurrahman, M. (2025). Market basket analysis using FP-Growth and Apriori on distro store sales transaction. Jurnal Ilmu Komputer Dan Teknologi Informasi, 17(1), 12–18. https://doi.org/10.18860/mat.v17i1.28820