Implementasi Data Mining Dengan Metode FP-Growth Terhadap Data Penjualan Barang Sebagai Strategi Penjualan Pada CV. A & A Copier
Keywords:FP-Growth algorithm; Rule Association; Sales strategy; Sales Data; Data Mining
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..
H. Subing and F. Saputra, “Analisis Strategi Pemasaran Untuk Meningkatkan Penjualan Motor Merk Mio J CW FI Pada PT. Bahana Pagar Alam Di Bandar Lampung.,” Jurnal Manajemen dan Bisnis Universitas Bandar Lampung, vol. 4, no. 2, p. 112194, 2014.
A. Muzakir and L. Adha, “Market Basket Analysis (Mba) Pada Situs Web E-Commerce Zakiyah Collection,” Simetris?: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer, vol. 7, no. 2, p. 459, 2016, doi: 10.24176/simet.v7i2.755.
S. S. Weng and M. J. Liu, “Feature-based recommendations for one-to-one marketing,” Expert Systems with Applications, vol. 26, no. 4, pp. 493–508, 2004, doi: 10.1016/j.eswa.2003.10.008.
Y. L. Chen, K. Tang, R. J. Shen, and Y. H. Hu, “Market basket analysis in a multiple store environment,” Decision Support Systems, vol. 40, no. 2, pp. 339–354, 2005, doi: 10.1016/j.dss.2004.04.009.
S. Istiqomah and T. S. Yanti, “Penggunaan Algoritma Novel Utility Frequent Itemset Mining dalam Market Basket Analysis ( Kasus Data Transaksional dan Data Profit di PT . XYZ Kota Malang ) informasi yang berguna dari gudang penyimpanan data dalam format bukan lagi menjadi satu pekerjaan,” Prosiding Statiska, vol. 5, pp. 32–39, 2019.
S. Raj, D. Ramesh, and K. K. Sethi, “A Spark-based Apriori algorithm with reduced shuffle overhead,” Journal of Supercomputing, vol. 77, no. 1, pp. 133–151, 2021, doi: 10.1007/s11227-020-03253-7.
A. Abdullah, “Rekomendasi Paket Produk Guna Meningkatkan Penjualan Dengan Metode FP-Growth,” Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika, vol. 4, no. 1, p. 21, 2018, doi: 10.23917/khif.v4i1.5794.
A. N. S. Putro and R. I. Gunawan, “Implementasi Algoritma FP-Growth Untuk Strategi Pemasaran Ritel Hidroponik (Studi Kasus?: PT. HAB),” Jurnal Buana Informatika, vol. 10, no. 1, p. 11, 2019, doi: 10.24002/jbi.v10i1.1746.
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