Implementasi Data Mining Dengan Metode FP-Growth Terhadap Data Penjualan Barang Sebagai Strategi Penjualan Pada CV. A & A Copier


Authors

  • Anandi Ayu STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Agus Perdana Windarto STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Dedi Suhendro AMIK Tunas Bangsa, Pematangsiantar, Indonesia

Keywords:

FP-Growth algorithm; Rule Association; Sales strategy; Sales Data; Data Mining

Abstract

If the seller wants to increase sales, the diversity of consumers will undoubtedly be an impediment in selecting the product to be purchased. Another issue is that vendors/decision makers struggle to select products to be re-marketed in accordance with the diversity of consumers. It is necessary to process sales data in the form of goods transactions in order to generate useful information that can be used to determine the best strategy for increasing sales. The study's goal is to analyze the FP-Growth algorithm on data sales of goods in order to make recommendations in providing sales packages for consumers as a sales strategy at CV. A & A. Data sources gathered through direct observations and interviews with the CV. A & A Copier Pematangsiantar Store. The FP-Growth algorithm is employed. RapidMiner software is used in the analysis process. 5 rules were generated from 50 transaction data records using the Market Basket Analysis application on FP-Growth on data on sales of goods, with a minimum support value of 0.4 (40 percent) and confidence of 0.95 (95 percent ). It is hoped that the research findings will provide benefits in the form of information that will assist sellers (the Stores) in selecting the best product marketing strategy to increase sales..

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Submitted: 2021-11-08
Published: 2021-11-30
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