DATA MINING UNTUK MENENTUKAN PRODUK TERLARIS MENGGUNAKAN METODE NAIVE BAYES

  • Sidik Rahmatullah STMIK Dian Cipta Cendikia Kotabumi
  • Mukrim Mukrim
  • Monica Nindy Pramitha
Keywords: Data Mining, Best Selling Products, Borland Delphi, Naive Bayes Classifier, waterfall

Abstract

PT. Cipta Niaga Semesta is one of the companies part of the Mayora group which is engaged in the distribution of food and soft drink products that gradually increase the number of sales of the products they need. To help this company become more sophisticated, a system that will help the business advance in choosing product sales, so that sought to conduct a study of the product data of PT. Cipta Niaga Semesta Supporting Branches using the Naive Bayes Classifier method In this study the authors used the data analysis method of interviews (interviews), Observation methods, Documentation methods and Literature studies as well as system development methods using the Waterfall Method. 2010. The best-selling product application built using the Naive Bayes Classifier method provides product data, Naive Bayes clusters and reporting. Data Mining To Determine the Best Selling Products Using the Naive Bayes Method at PT. Cipta Niaga Semesta Kotabumi Sub Branch helps in the classification system on best-selling products and helps the Head of Operational Supervisory Area (AOS) of PT. CiptaNiagaSemestaSub Branch Kotabumi in the selection of best-selling products. This system produces a selection of best-selling products with 8 attributes taken from sales data for the past 2 years.

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Published
2019-10-24
How to Cite
[1]
S. Rahmatullah, M. Mukrim, and M. Pramitha, “DATA MINING UNTUK MENENTUKAN PRODUK TERLARIS MENGGUNAKAN METODE NAIVE BAYES”, Jurnal Informasi dan Komputer, vol. 7, no. 2, pp. 57-64, Oct. 2019.