Penerapan Algoritma Apriori pada Transaksi Penjualan Produk Cat untuk Meningkatkan Strategi Bisnis
-
Sabar Mulyati
*
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru,
Indonesia
- Alwis Nazir Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia
- Elvia Budianita Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia
- Eka Pandu Cynthia Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia (*) Corresponding Author
Abstract
Data mining is a combination of data analysis techniques and determining important patterns in the data. Data mining can also be used to improve business progress. In this research, data mining is used to improve sales business strategies at CV. Sumber Tirta Anugerah in the last 1 year. Previously CV. Sumber Tirta Anugerah does not apply the a priori method to sales, causing product stock to pile up. Data mining is assisted by an a priori algorithm to determine the frequency of itemsets in looking for patterns of items that are usually purchased by customers at the same time. In this research, several items were used such as Lippo coupons, Lippo Emultion, Lektone Emultion, Lippo waterproof, Japanese Duco paint, Kansai Tropical, Beta Chemie, Flalit, and cable clamps, synthetic property, Tajima New putty and Bioton Emultion. Based on the research that has been carried out, the largest support value is 32.18% for 1 itemset. Then for the 2 itemsets the largest support was found at 9.32%. Next, the 3 itemsets obtained the largest support of 1.94%. So based on the overall data, the confidence is 72.97% and the lift ratio test value is 2.22%.
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