Open AccessKombinasi Transaksi Penjualan (Merk Beras) Menggunakan Algoritma Apriori (Studi Kasus di UD. SRD)
Author(s) -
Iwan Ady Prabowo,
Wawan Laksito Yuly Saptomo,
Nungky Kurnia Candra
Publication year - 2021
Publication title -
jurnal teknologi informasi dan komunikasi sinar nusantara
Language(s) - English
Resource type - Journals
eISSN - 2620-7532
pISSN - 2338-4018
DOI - 10.30646/tikomsin.v9i1.543
Subject(s) - database transaction , apriori algorithm , value (mathematics) , association rule learning , business , advertising , computer science , agricultural science , database , mathematics , data mining , statistics , environmental science
UD. SRD is an individual company that produces and sells rice with various brands. UD. SRD is an individual company that produces and sells rice with various brands. Rice brands sold include C4 Kelapa, C4 Raja, C4 Merak, Nogo Hitam, Nogo Merah, Nogo Hijau, Pandan Wangi, Mentik Wangi and Rojo Lele. In processing sales data is still done manually that is only using notes or receipts, so the data only serves as an archive. In this study, the data amounted to 404 rice sales transactions from January to September 2016. The purpose of this research is the creation of Apriori algorithm system to predict combination of rice brand in sales transaction in UD. SRD so as to help the company know the sales of the most frequently purchased rice brands simultaneously. The result of combination rice brand is getting using Apriori Algorithm which supported minimum 30% and confidence minimum 70%. It appears from thus statements "If buy C4R, it will buy C3M with 51.54% support and 77.31% confidence", "If buy MW , It will buy C4M with the value of support 48.27% and the value of confidence 79.92% "," If buy C45 and C4M, it will buy MW with the value of support 32.43% and the value of confidence 71.20% "and" If buy MW and C4R , It will buy C4M with the value of support 32.43% and the value of confidence 82.91%".Keywords: Rice Transaction, Selling, Data mining, Association Rule, Apriori Algorithm