Published: 2026-04-01
Implementasi Metode Asosiasi Transaksi Penjualan Menggunakan Algoritma Apriori pada Studi Kasus Toko Sembako Ibu Siti
DOI: 10.35870/jtik.v10i2.5245
Wieko Wieko, Tri Wahyudi
- Wieko Wieko: Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika
- Tri Wahyudi: Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika
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Abstract
This research aims to implement the transaction association method using the Apriori Algorithm in the case study of Ibu Siti's Grocery Store. In a retail environment, understanding customer purchasing patterns is crucial for effective marketing strategies and product arrangement. The Apriori Algorithm was chosen for its capability to discover association rules from large transaction datasets, which will yield valuable information regarding relationships between sales items. The implementation process includes data pre-processing, candidate itemset generation, and the calculation of support, confidence, and lift to extract significant association rules. The results of this research are expected to provide strategic recommendations for Ibu Siti's Grocery Store in arranging product layouts, planning package promotions, and managing product inventory more efficiently. Thus, the application of this algorithm is expected to increase the store's profit and competitiveness.
Keywords
Transaction Association ; Apriori Algorithm ; Sales ; Grocery Store ; Association Rules
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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.
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Issue: Vol. 10 No. 2 (2026)
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Section: Computer & Communication Science
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Published: %750 %e, %2026
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License: CC BY 4.0
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Copyright: © 2026 Authors
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DOI: 10.35870/jtik.v10i2.5245
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Wieko Wieko
Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.
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Akhtar, M. F., et al. (2025). Implementation and performance evaluation of machine learning-based Apriori algorithm to detect non-technical losses in distribution systems. IEEE Access, 13. https://doi.org/10.1109/ACCESS.2025.3541722.
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Alwendi, Mandopa, A. S., & Hasibuan, E. A. (2023). Aplikasi data mining untuk menentukan masa studi mahasiswa menggunakan metode association rule. Jurnal Pendidikan Dewantara, 2(1). https://doi.org/10.58222/dewantara.v2i1.24
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Andika, A. M., Suarna, N., & Dana, R. D. (2023). Analisa dataset asosiasi penjualan menggunakan metode FP-Growth. Jurnal Teknologi Ilmu Komputer, 2(1). https://doi.org/10.56854/jtik.v2i1.108.
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-
-
-
-
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Lewis, A., Zarlis, M., & Situmorang, Z. (2021). Penerapan data mining menggunakan task market basket analysis pada transaksi penjualan barang di AB Mart dengan algoritma Apriori. Jurnal Media Informatika Budidarma, 5(2), 203–210. https://doi.org/10.30865/mib.v5i2.2934.
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Liandi, Z. (2020). Research on e-commerce potential client mining applied to Apriori association rule algorithm. In Proceedings of ICITBS. https://doi.org/10.1109/ICITBS49701.2020.00146.
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Muchlis, M. M., Fitri, I., & Nuraini, R. (2021). Rancang bangun aplikasi data mining pada penjualan Distro Bloods berbasis web menggunakan algoritma Apriori. Jurnal JTIK, 5(1). https://doi.org/10.35870/jtik.v5i1.197.
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Mushleh, M., & Testiana, G. (2023). Studi kasus asosiasi pembelian produk teknologi pada toko elektronik dengan metode Apriori. JDMIS, 1(2). https://doi.org/10.54259/jdmis.v1i2.1718.
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Parinduri, R. D., Defit, S., & Nurcahyo, G. W. (2024). Implementasi algoritma Apriori dalam data mining untuk optimalisasi stok obat di apotik. KomtekInfo, 11(3). https://doi.org/10.35134/komtekinfo.v11i3.544.
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Riszky, A. R., & Sadikin, M. (2019). Data mining menggunakan algoritma Apriori untuk rekomendasi produk bagi pelanggan. Jurnal Teknologi dan Sistem Komputer, 7(3). https://doi.org/10.14710/jtsiskom.7.3.2019.103-108.
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Sahara, W., Saragih, S. D., & Windarto, A. P. (2022). Teknik asosiasi data mining dalam menentukan pola penjualan dengan metode Apriori. Terapan Informatika Nusantara, 2(12). https://doi.org/10.47065/tin.v2i12.1577.
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Triayudi, A., & Iskandar, A. (2022). Penerapan data mining dalam penentuan prioritas pemesanan produk berdasarkan data penjualan barang menggunakan algoritma Apriori. JoSYC, 4(1). https://doi.org/10.47065/josyc.v4i1.2523.
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