Pemanfaatan Metode Asosiasi Apriori dalam Menentukan Pola Penjualan Sembako
(1) STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
(2) STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
(3) STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
(*) Corresponding Author
Abstract
Sembako is an abbreviation of nine basic ingredients consisting of various food and beverage ingredients that are generally needed by humans, especially the Indonesian people. Good layout arrangement of goods at a wholesaler can increase time efficiency in terms of service to consumers and increase consumer buying interest at the wholesaler. The sales transaction data for basic necessities that are owned have not been used properly by wholesalers. The a priori algorithm is one of the methods found in data mining that is often used to find the occurrence/frequency of interconnected data patterns. The a priori algorithm can be used to find patterns of association relationships that exist in sales patterns. Based on this background, the purpose of this research is to use the a priori association method to determine the pattern of food sales. Based on calculations using the a priori algorithm, there are 5 association rules formed with a minimum amount of 30% support and a minimum confidence of 70%, and the highest association rule is that if you buy LPG, you will probably also buy Dolphin salt.
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B. Sudarsono, U. Faddillah, A. Asistyasari, and Y. Nuryaman, Analisa Penjualan Perlengkapan Olahraga Pada HS Sport Menggunakan Metode Apriori, INOVTEK Polbeng - Seri Inform., vol. 6, no. 2, p. 205, 2021, doi: 10.35314/isi.v6i2.2066.
M. M. Muchlis, I. Fitri, and R. Nuraini, Rancang Bangun Aplikasi Data Mining pada Penjualan Distro Bloods Berbasis Web menggunakan Algoritma Apriori, J. JTIK (Jurnal Teknol. Inf. dan Komunikasi), vol. 4, no. 2, p. 26, 2021, doi: 10.35870/jtik.v5i1.197.
L. H. Andre Valerian, Implementasi Algoritma Apriori Untuk Prediksi Stok Peralatan Tulis Pada Toko XYZ, vol. V, no. 1, pp. 1822, 2018.
P. Alkhairi and A. P. Windarto, Penerapan K-Means Cluster pada Daerah Potensi Pertanian Karet Produktif di Sumatera Utara, Semin. Nas. Teknol. Komput. Sains, pp. 762767, 2019.
Nola Ritha, E. Suswaini, and W. Pebriadi, Penerapan Association Rule Menggunakan Algoritma Apriori Pada Poliklinik Penyakit Dalam (Studi Kasus: Rumah Sakit Umum Daerah Bintan), J. Sains dan Inform., vol. 7, no. 2, pp. 222230, 2021, doi: 10.34128/jsi.v7i2.329.
H. Indriyawati and T. Winarti, Pemodelan Data Mining Pola Kelayakan Kemampuan Lulusan Dengan Kebutuhan Stakeholder Menggunakan Algoritma Apriori, JITSI J. Ilm. Teknol. Sist. Inf., vol. 2, no. 3, pp. 7884, 2021, doi: 10.30630/jitsi.2.3.40.
Calvin Andrew Suwandi, Robi Yanto, Deni Apriadi, Implementasi Metode Apriori Pada Data Mining Untuk Pola Pembelian Barang, J. Ilm. Bin. STMIK Bina Nusant. Jaya Lubuklinggau, vol. 3, no. 1, pp. 1521, 2021, doi: 10.52303/jb.v3i1.42.
A. Nurfajiah, T. Hartati, and D. Rizki Amalia, Integrated Library System untuk Meningkatkan Efektivitas Layanan Perpustakaan Dengan Menggunakan Metode Algoritma Apriori, J. Inf. Technol., vol. 3, no. 1, pp. 3944, 2021, doi: 10.47292/joint.v3i1.55.
R. SARI, Implementasi Algoritma Apriori Pada Data Mining Untuk Pola Peminjaman Buku Di Perpustakaan Uin Raden Fatah Palembang, pp. 67, 2018.
I. S. M. Safar, Penerapan Algoritma Apriori Dalam Analisis Data Penjualan Di Koperasi Cendekia Man Insan Cendekia Jambi, vol. 2, no. 1, pp. 187193, 2021.
E. E. Cathrine Naomi Siregar, Market Basket Analysis Dengan Algoritma Apriori Pada Jacks Mart, vol. 01, pp. 339351, 2008, doi: 10.1007/978-0-387-72579-6_13.
D. S. Purnia and A. I. Warnilah, Implementasi Data Mining Pada Penjualan Kacamata Menggunakan Algoritma Apriori, vol. 2, no. 2, pp. 3139, 2017.
W. Warisa, S. Aminah, and K. Karmila, Studi Kasus Penjualan Kosmetik Menggunakan Metode Association Rule (Apriori), Technol. J. Ilm., vol. 12, no. 4, p. 218, 2021, doi: 10.31602/tji.v12i4.5630.
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, p. 218, 2021, doi: 10.52958/iftk.v17i3.3655.
S. Styawati, A. Nurkholis, and K. N. Anjumi, Analisis Pola Transaksi Pelanggan Menggunakan Algoritme Apriori, vol. 5, no. September, pp. 619626, 2021.
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