Published: 2025-04-01
Penerapan Algoritma FP-Growth untuk Strategi Penjualan Toko Kelontong Cipta Lestari
DOI: 10.35870/jtik.v9i2.3278
Downloads
Abstract
This research uses the FP-Growth algorithm to identify sales patterns at the Cipta Lestari convenience store to support inventory management efficiency and marketing strategies. The data used in this research consists of daily sales transaction data that includes product types and the quantities sold. This analysis employs a support parameter of 0.95 and a confidence level of 0.8, with a maximum limit of 100,000 items. The results indicate that products such as Kchoco, sambal sauce, and tea 3350ml are often purchased together with Torabika coffee, soy sauce, and instant fried noodles. This combination pattern enables the store to create more effective product promotions and optimize inventory. The goal of this research is to develop business strategies that are more responsive to customer needs, enhance satisfaction with the right product offerings, and strengthen competitive marketing. This research is expected to contribute to the development of traditional marketing strategies and serve as a reference for analyzing consumer purchasing patterns in future studies.
Keywords
Grocery store ; Cipta Lestari ; FP-Growth ; Sale ; Data Mining
Article Information
This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
-
Issue: Vol. 9 No. 2 (2025)
-
Section: Computer & Communication Science
-
Published: %750 %e, %2025
-
License: CC BY 4.0
-
Copyright: © 2025 Authors
-
DOI: 10.35870/jtik.v9i2.3278
AI Research Hub
This article is indexed and available through various AI-powered research tools and citation platforms. Our AI Research Hub ensures that scholarly work is discoverable, accessible, and easily integrated into the global research ecosystem. By leveraging artificial intelligence for indexing, recommendation, and citation analysis, we enhance the visibility and impact of published research.
Tarwoto
Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Amikom Purwokerto, Kabupaten Banyumas, Provinsi Jawa Tengah, Indonesia.
Ahnaf Vanning AL-Haq
Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Amikom Purwokerto, Kabupaten Banyumas, Provinsi Jawa Tengah, Indonesia.
Anindya Fidela
Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Amikom Purwokerto, Kabupaten Banyumas, Provinsi Jawa Tengah, Indonesia.
Wini Audiana
Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Amikom Purwokerto, Kabupaten Banyumas, Provinsi Jawa Tengah, Indonesia.
Zulfa Ummu Hani
Program Studi Sistem Informasi, Fakultas Ilmu Komputer, Universitas Amikom Purwokerto, Kabupaten Banyumas, Provinsi Jawa Tengah, Indonesia.
-
Akmar, M., Matulatan, T., & Ritha, N. (2022). Penerapan Algoritma Fp-Growth Untuk Menganalisapola Transaksi Pembelian Obat Oleh Kosumen. Student Online J, 3(1), 124-138.
-
Anas, A. (2020). Penerapan Algoritma Fp-Growth Dalam Menentukan Perilaku Konsumen Ghania Mart Muara Bulian. Jurnal Ilmiah Media Sisfo, 14(2), 120-129. https://doi.org/10.33998/mediasisfo.2020.14.2.879.
-
Arta, I. K. J., Indrawan, G., & Dantes, G. R. (2016). Data Mining Rekomendasi Calon Mahasiswa Berprestasi Di Stmik Denpasar Menggunakan Metode Technique for Others Reference By Similarity To Ideal Solution. JST (Jurnal Sains Dan Teknologi), 5(2).
-
Fayyad, U. M., Piatetsky-Shapiro, G., & Smyth, P. (1996, August). Knowledge Discovery and Data Mining: Towards a Unifying Framework. In KDD (Vol. 96, pp. 82-88).
-
Habibah, A. S., Solehudin, A., & Primajaya, A. (2022). Analisis Persediaan Stok Barang Warung Menggunakan Data Mining Dengan Algoritma Fp-Growth (Studi Kasus: Warung Bu Nani). Jurnal Ilmiah Wahana Pendidikan, 8(17), 46-58. https://doi.org/10.5281/zenodo.7069512.
-
Lestari, L. M., & Ali, I. (2023). Penerapan Algoritma FP-Growth Untuk Menentukan Pola Penjualan Toko Ellia Umami. Journal of Student Research, 1(3), 367-378.
-
Lestari, Y. D. (2015). Penerapan Data Mining Menggunakan Algoritma Fp-Tree Dan Fp-Growth Pada Data Transaksi Penjualan Obat.
-
Mardi, Y. (2017). Data mining: Klasifikasi menggunakan algoritma c4. 5. Jurnal Edik Informatika Penelitian Bidang Komputer Sains dan Pendidikan Informatika, 2(2), 213-219. https://doi.org/10.22202/ei.2016.v2i2.1465.
-
Maulidiya, H., & Jananto, A. (2020). Asosiasi Data Mining Menggunakan Algoritma Apriori Dan Fpgrowth Sebagai Dasar Pertimbangan Penentuan Paket Sembako.
-
Miraldi, R. N., Christanto, A. R., & Susanto, B. (2014). Implementasi algoritma fp-growth untuk sistem rekomendasi buku di perpustakaan UKDW. Informatika: Jurnal Teknologi Komputer dan Informatika, 10(1), 65360. https://doi.org/10.21460/inf.2014.101.323.
-
Pratama, R. Z., Sihombing, M., & Ambarita, I. (2024). Application of Data Mining to Measure the Level of Satisfaction with Public Facilities and Services at STMIK Kaputama Binjai Using Linear Regression Method. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 4(1), 411-418.
-
Sari, M. U., & Asmendri, A. U. (2020). Natural Science: Jurnal Penelitian Bidang IPA dan Pendidikan IPA Website. Natural Science, 6(1).
-
Susanto, H., & Sudiyatno, S. (2014). Data mining untuk memprediksi prestasi siswa berdasarkan sosial ekonomi, motivasi, kedisiplinan dan prestasi masa lalu. Jurnal pendidikan vokasi, 4(2). https://doi.org/10.21831/jpv.v4i2.2547.
-
Trivaika, E., & Senubekti, M. A. (2022). Perancangan Aplikasi Pengelola Keuangan Pribadi Berbasis Android. Nuansa Informatika, 16(1), 33-40. https://doi.org/10.25134/nuansa.v16i1.4670.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright and Licensing Agreement
Authors who publish with this journal agree to the following terms:
1. Copyright Retention and Open Access License
- Authors retain full copyright of their work
- Authors grant the journal right of first publication under the Creative Commons Attribution 4.0 International License (CC BY 4.0)
- This license allows unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
2. Rights Granted Under CC BY 4.0
Under this license, readers are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, including commercial use
- No additional restrictions — the licensor cannot revoke these freedoms as long as license terms are followed
3. Attribution Requirements
All uses must include:
- Proper citation of the original work
- Link to the Creative Commons license
- Indication if changes were made to the original work
- No suggestion that the licensor endorses the user or their use
4. Additional Distribution Rights
Authors may:
- Deposit the published version in institutional repositories
- Share through academic social networks
- Include in books, monographs, or other publications
- Post on personal or institutional websites
Requirement: All additional distributions must maintain the CC BY 4.0 license and proper attribution.
5. Self-Archiving and Pre-Print Sharing
Authors are encouraged to:
- Share pre-prints and post-prints online
- Deposit in subject-specific repositories (e.g., arXiv, bioRxiv)
- Engage in scholarly communication throughout the publication process
6. Open Access Commitment
This journal provides immediate open access to all content, supporting the global exchange of knowledge without financial, legal, or technical barriers.