Penerapan Data Mining Dalam Prediksi Penjualan Prabot Rumah Tangga Menggunakan Metode Apriori Pada Toko Hasanah Mart
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Natalia Silalahi
*
STMIK Budi Darma, Medan,
Indonesia
(*) Corresponding Author
Abstract
The application of data mining is very well done, especially in predicting transaction patterns that are very often done in the sale and purchase of household furniture, household furniture is goods that are very much in demand by many groups, especially mothers, the higher the amount of demand, the more data transactions that must be processed, dug up to obtain the desired information and needed a method approach to processing transaction patterns that are the most desirable so that a store or company can sort out the inventory of goods that must be met based on the level of market needs, appropriate methods and has been widely used in one of the sales prediction is the Apriori method is a method that uses association rules that aim to see the associative relationship between a combination of items with other items, in data mining using the a priori method can also be done with very much data from and processed with a fast time and a very good level of data prediction accuracy.
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References
B. S. Mózo, “teknologi Dunia Industri,” J. Chem. Inf. Model., vol. 53, no. 9, pp. 1689–1699, 2017, doi: 10.1017/CBO9781107415324.004.
B. R. B. Purba, N. A. Hasibuan, G. L. Ginting, and S. Suginam, “Implementasi Algoritma Apriori Untuk Mencari Relasi Pada Transaksi Pembelian Alat-Alat Kesehatan,” JURIKOM (Jurnal Ris. Komputer), vol. 5, no. 3, pp. 269–277, 2018, [Online]. Available: http://stmik-budidarma.ac.id/ejurnal/index.php/jurikom/article/view/773.
M. G. Sadewo, A. P. Windarto, and A. Wanto, “Penerapan Algoritma Clustering Dalam Mengelompokkan Banyaknya Desa/Kelurahan Menurut Upaya Antisipasi/ Mitigasi Bencana Alam Menurut Provinsi Dengan K-Means,” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 2, no. 1, pp. 311–319, 2018, doi: 10.30865/komik.v2i1.943.
S. Defiyanti, “Integrasi Metode Clustering dan Klasifikasi untuk Data Numerik,” Citee, no. July, pp. 256–261, 2017.
A. Nursikuwagus and T. Hartono, “Implementasi Algoritma Apriori Untuk Analisis Penjualan Dengan Berbasis Web,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 7, no. 2, p. 701, 2016, doi: 10.24176/simet.v7i2.784.
A. Nugroho, Analisis dan Perancangan Sistem Informasi dengan Metodologi Berorientasi Objek, Edisi Revi. Bandung: Informatika Bandung, 2005.
P. T. G. Elkington et al., “Mycobacterium tuberculosis, but not vaccine BCG, specifically upregulates matrix metalloproteinase-1,” Am. J. Respir. Crit. Care Med., vol. 172, no. 12, pp. 1596–1604, 2005, doi: 10.1164/rccm.200505-753OC.
V. N. Budiyasari, P. Studi, T. Informatika, F. Teknik, U. Nusantara, and P. Kediri, “Implementasi Data Mining Pada Penjualan Sepatu Dengan Menggunakan Algoritma Apriori,” vol. 2, no. 2, pp. 1–8, 2017.
N. Adha, L. T. Sianturi, and E. R. Siagian, “IMPLEMENTASI DATA MINING PENJUALAN SABUN DENGAN MENGGUNAKAN METODE APRIORI ( Studi Kasus : PT. Unilever),” Maj. Ilm. INTI, vol. 12, no. 2, pp. 219–223, 2017.
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