Pola Pembelian Produk Parfum Menggunakan Algoritma Apriori Berdasarkan Data Mining Rule Asosiasi
Abstract
As technology evolves and trends change, perfume products continue to face challenges to remain relevant and attractive to an ever-evolving market. Data mining allows companies to identify customer segments based on consumer behaviors, preferences, and characteristics. The purpose of this study is to identify the purchase pattern of perfume products based on the tendency of consumers to buy products at the same time. The method used in this study is quantitative, based on transaction data. The programming language used in this study is PHP 5. The use of an a priori algorithm makes it easier to determine the association rules based on the support and confidence values. The association pattern is formed with a minimum of 15% support. It is found that the most frequently sold goods have a total of 5 item transactions, so the most frequently purchased perfume product itemsets at the same time are Jasmine and Fantasy.
References
Agrawal, R., & Srikant, R. (1994). Fast Algorithms for Mining Association Rules. Proceedings Og The 20th International Conference on Very Large Data Bases (VLDB), 487–499. https://doi.org/10.1109/ICSESS.2014.6933618
Albab, M. U., & Hidayatullah, D. (2022). Penerapan Algoritma Apriori pada Sistem Informasi Inventori Toko. Jurnal Media Informatika Budidarma, 6(3), 1321–1328. https://doi.org/10.30865/mib.v6i3.4160
Ariska, Wahyuddin. (2022). PENERAPAN KRIPTOGRAFI MENGGUNAKAN ALGORITMA DES. Jurnal sintaks logika.
Dewi, S. P., Nurwati, N., & Rahayu, E. (2022). Penerapan Data Mining Untuk Prediksi Penjualan Produk Terlaris Menggunakan Metode K-Nearest Neighbor. Building of Informatics, Technology and Science (BITS), 3(4), 639–648. https://doi.org/10.47065/bits.v3i4.1408
Hidayat, A. A., Hendrastuty, N., & Styawati, S. (2023). Penerapan Algoritma Apriori Pada Apotek Shaqeena Untuk Memprediksi Penjualan Berbasis Android. Jurnal Teknologi Dan Sistem Informasi, 4(3), 302–312. https://doi.org/10.33365/jtsi.
Khanza, M., Toyib, R., & Onsardi, O. (2021). Implementasi Algoritma Apriori Dalam Penentukan Pemesanan Barang Untuk Transaksi Penjualan Handphone. Journal Scientific and Applied Informatics, 4(2), 221–235.
Listanto, S., & Kristania, Y. M. (2022). Implementasi Data Mining Terhadap Data Penjualan dengan Algoritma Apriori pada PT. Duta Kencana Swaguna. Jurnal Teknoinfo, 16(2), 364–372. https://doi.org/10.33365/jti.v16i2.1973
Pratiwi, A. G. (2024). Implementasi Data Mining Menggunakan Metode Association Rule Pada Register User Kompas.ID. Universitas Islam Negeri Maulana Malik Ibrahim.
Saputra, B. (2020). Aplikasi Pemilihan Parfum. 19(5), 1–23.
Setiawan, A., & Putri, F. P. (2020). Implementasi Algoritma Apriori untuk Rekomendasi Kombinasi Produk Penjualan. Ultimatics : Jurnal Teknik Informatika, 12(1), 66–71. https://doi.org/10.31937/ti.v12i1.1644
Sidik, A. D. W. M., Ilman, H. K., Anang, S., Edwinanto, E., Artiyasa, M., & Junfithrana, A. P. (2020). Gambaran Umum Metode Klasifikasi Data Mining. FIDELITY : Jurnal Teknik Elektro, 2(2), 34–38. https://doi.org/10.52005/fidelity.v2i2.111
Soepriyono, G., & Triayudi, A. (2023). Implementasi Data Mining dengan Algoritma Apriori dalam Menentukan Pola Pembelian Aksesoris Laptop. Jurnal Media Informatika Budidarma, 7(4), 2087–2096. https://doi.org/10.30865/mib.v7i4.6555
Syahriani, S. (2022). Penerapan Data Mining Untuk Menentukan Pola Penjualan Sepatu Menggunakan Metode Algoritma Apriori. Bina Insani Ict Journal, 9(1), 43. https://doi.org/10.51211/biict.v9i1.1758
Syahril, M., Erwansyah, K., & Yetri, M. (2020). Penerapan Data Mining Untuk Menentukan Pola Penjualan Peralatan Sekolah Pada Brand Wigglo Dengan Menggunakan Algoritma Apriori. Jurnal Teknologi Sistem Informasi Dan Sistem Komputer TGD, 3(1), 118. https://doi.org/10.53513/jsk.v3i1.202
Verano, D. A. (2016). Assosiasi Rules Dan Moving Average Untuk Memprediksi Persediaan Bahan Baku Produksi. Annual Research Seminar, 2(1), 438–444. http://ars.ilkom.unsri.ac.id438
Copyright (c) 2024 Fadhlan Agus Setiawan, Hamra, Masnur

This work is licensed under a Creative Commons Attribution 4.0 International License.