Implementation of Apriori Algorithms to Analyze and Determine Consumer Purchase Patterns in Gadget Stores as Sales Increase Strategy
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Rahma Yuni Simanullang
*
Universitas Pembangunan Panca Budi, Medan,
Indonesia
- Khairunnisa ' Universitas Pembangunan Panca Budi, Medan, Indonesia
- Puspita Wanny Universitas Pembangunan Panca Budi, Medan, Indonesia
- Utari Utari Universitas Pembangunan Panca Budi, Medan, Indonesia
- Muhammad Syahputra Novelan Universitas Pembangunan Panca Budi, Medan, Indonesia (*) Corresponding Author
Abstract
This study aims to identify the pattern of product purchases that often occur simultaneously at a gadget store in order to develop a more effective sales strategy. The research problem focuses on how to find associations between products based on sales transaction data. The proposed solution is to apply data mining techniques, specifically a priori algorithms, to analyze transaction data and find significant association rules. The A priori algorithm is used through several stages, including the calculation of support for each item, the elimination of items with support below the minimum threshold, the formation of itemset combinations, and the calculation of confidence to generate association rules. The results showed two association rules that met the minimum confidence threshold (60%), namely: (1) If customers buy USB-C, they tend to buy Powerbank (confidence: 67%), and (2) If customers buy Smartwatches, they tend to buy Screen Protectors (confidence: 67%), and (3) If customers buy Screen Protectors, they tend to buy Smartwatches (confidence: 100%). These patterns can be used by the store for strategic product placement and bundling promotions.
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References
Khanza and R. Toyib, “Implementasi Algoritma Apriori Dalam Penentukan Pemesanan Barang Untuk Transaksi Penjualan Handphone,” J. Sci. Appl. Informatics, vol. 4, no. 2, pp. 221–235, 2021.
K. Brighton and S. Hariyanto, “Penerapan Metode Market Basket Analisis Dengan Algoritma Apriori Pada Toko Ritel Elektronik,” bit-Tech, vol. 7, no. 1, pp. 37–46, 2024, doi: 10.32877/bt.v7i1.1417.
R. N. Dianti and J. Zeniarja, “Implementasi Algoritma Apriori Untuk Analisis Pola Pembelian Konsumen Pada Toserba Yusuf Semarang,” JIPI (Jurnal Ilm. Penelit. dan Pembelajaran Inform.), vol. 9, no. 2, pp. 1013–1021, 2024, doi: 10.29100/jipi.v9i2.5421.
A. S. Sembiring and T. S. Alasi, “Penerapan Data Mining Menggunakan Algoritma Apriori Pada Peminjaman Buku di Perpustakaan Pada Pesantren Babul Ulum,” J. Armada Inform., vol. 7, no. 2, pp. 323–327, 2023.
F. Zoelfiandi and U. Budiyanto, “Penerapan Data Mining Menggunakan Algoritma Apriori Pada Toko Adelia Frozen Food,” J. Ticom Technol. Inf. Commun., vol. 11, no. 1, pp. 13–19, 2022.
P. H. Putra and M. S. Novelan, “Perancangan Aplikasi Penentuan Kualitas Sayuran Berdasarkan Warna Menggunakan Data Mining,” in Scenario (Seminar of Social Sciences Engineering and Humaniora), 2021, pp. 103–109.
Z. Setiawan et al., Buku Ajar Data Mining. PT. Sonpedia Publishing Indonesia, 2023.
E. Prayitno and D. F. Sari, “Implementasi Algoritma Apriori Untuk Pola Kombinasi Pembelian Barang,” J. Cakrawala Ilm., vol. 2, no. 2, pp. 691–696, 2022.
M. Kholid, A. F. Boy, and Y. Syahra, “Implementasi Data Mining Metode Algoritma Apriori Untuk Mengetahui Pola Pembelian Konsumen pada Transaksi Penjualan Makanan Dan Minuman (Study Kasus Restaurant JMC Medan),” J. Cyber Tech, vol. 4, no. 7, 2021.
N. Mardiyantoro, D. P. Utomo, and I. A. Ihsannuddin, “Implementasi Data Mining Untuk Menentukan Pola Penjualan Di Armada Computer Menggunakan Algoritma Apriori,” STORAGE J. Ilm. Tek. dan Ilmu Komput., vol. 2, no. 1, pp. 25–31, 2023.
H. Rodhiy and Z. Sitorus, “Data Mining Menggunakan Algoritma Apriori Dalam Menentukan Tarif Pajak Penghasilan Di Oenity,” Bull. Inf. Technol., vol. 4, no. 2, pp. 198–204, 2023.
V. Jessfry and M. Siddik, “Penerapan Data Mining Menggunakan Algortima Apriori Dalam Membangun Sistem Persediaan Barang,” J. Inf. Syst. Informatics Eng., vol. 8, no. 1, pp. 187–199, 2024.
S. M. Yaasin, N. Rahaningsih, R. Narasati, and A. R. Rinaldi, “Analis Asosiasi Data Akses E-Commerece Menggunakan Algoritma Apriori,” KOPERTIP Sci. J. Informatics Manag. Comput., vol. 5, no. 1, pp. 8–16, 2021.
P. Haryandi, Y. Widiastiwi, and N. Chamidah, “Penerapan Algoritma Apriori untuk Mencari Pola Penjualan Produk Herbal (Studi Kasus: Toko Hanawan Gemilang),” Inform. J. Ilmu Komput., vol. 17, no. 3, pp. 218–225, 2021.
N. A. Pradipta and R. D. H. Untari N, “Implementasi Algoritma Apriori Untuk Analisis Pola Pembelian Produk Donat Bolong,” Jutisi J. Ilm. Tek. Inform. dan Sist. Inf., vol. 13, no. 1, p. 268, 2024, doi: 10.35889/jutisi.v13i1.1778.
P. Salsabila, E. Wahyudin, G. Dwilestari, K. Kaslani, and F. Subhiyanto, “Penerapan Algoritma Fp-Growth Untuk Mengetahui Pola Pembelian Konsumen Di Warung Makan Dede,” JATI (Jurnal Mhs. Tek. Inform., vol. 8, no. 1, pp. 1221–1128, 2024, doi: 10.36040/jati.v8i1.8964.
B. Kustiawan, A. Apriyanto, T. Haryanti, and A. Rustam, Perilaku Konsumen: Pendekatan Strategis. PT. Sonpedia Publishing Indonesia, 2025.
K. A. A. P. H. Hilman, “Analisa Data Penjulan pada Toko Kelontong Musyawarah Menggunakan Algoritma Apriori,” J. Appl. Comput. Sci. Technol., vol. 3, no. 2, pp. 221–227, 2022.
A. N. Siangka, “Analisis Strategi Pemasaran Dalam Meningkatkan Penjualan Tiket Bus Pada PO Piposs Mamuju,” J. Ekon. Pendidik. dan Perenc. Pembang. Drh., vol. 2, no. 2, pp. 55–65, 2024.
N. T. Farah, S. Amiwantoro, F. Nikmah, and M. Ikaningtyas, “Implementasi Strategi Pemasaran Digital Dalam Pengembangan Bisnis Di Era Digitalisasi,” J. Media Akad., vol. 2, no. 4, 2024.
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