Penerapan Algoritma Apriori Terhadap Data Penjualan Di Swalayan Koperasi Bappenas Jakarta Pusat
Abstract
Supermarkets are a place to supply daily necessities ranging from nine basic
commodities to household needs. Every day there are several sales transactions,
which that data will increase continue. Usually these sales data are only used as
store archives, actually in sales data there are information that can be used to find
out the most sales simultaneously so that a method is needed to find out which
products has selling well using apriori algorithm and tools rapid miner help. From
the results of analyzing the sales data, consumers who conduct basic needs product
transactions obtained from the purchase of dominating item combinations are a
combination of Indocafe Jar 200g and Kapal Api 165g items with the highest support
value of 0,213. Then, the buyers of item combination which dominates Max Creamer
450gr item and Kapal Api 165gr confidence value are 0,958 and the buyrs
combination of Gulaku Kuning and Kapal Api 165g support value are 0,259 From
these results, concluded every consumer buys Indocafe Jar 200g there is an
indication that consumers will also buying Api Kapal Api 165gr as well as Gulaku
Kuning with Kapal api 165g and Max Creamer 450gr and Kapal Api 165gr.
Keywords
Full Text:
PDF (Bahasa Indonesia)References
Nofriansyah, D. (2014). Konsep Data Mining Vs Sistem Pendukung Keputusan. Yogyakarta: Deepublish.
Siregar, S. R. (2014). Implementasi Data Mining Pada Penjualan Tiket Pesawat Menggunakan Algoritma Apriori ( Studi Kasus : Jumbo Travel Medan ), 152, 152–156.
Syahdan, S. Al, & Anita, S. (2018). Data Mining Penjualan Produk Dengan Metode Apriori Pada Indomaret Galang Kota. Nasional Komputasi Dan Teknologi Informasi, 1, 56–63.
Wijaya, K. N. (2017). Analisa Pola Frekuensi Keranjang Belanja Dengan Algoritma Apriori, 3(1), 9–12.
DOI: https://doi.org/10.31294/p.v21i2.6205
Copyright (c) 2019 Siti Aisyah, Normah Normah
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
ISSN: 2579-3500