Penerapan Data Mining pada Penjualan Produk MS Glow Menggunakan Metode Naive Bayes untuk Strategi Pemasaran

Abstract

MS Glow Cirebon Store is a store that sells beauty products with sales orders every month in 2021 uncertain. Probably due to competition factors from several oyher stores that sell MS Glow products as well. Responding to this it takes innovation steps by analyzing product sales to generate new knowledge that will the be used for marketing strategy.so that the target market is in accordance with the expected. The method used in this study is the Naïve Bayes method the calculates the probability value of each attribute studied. The purpose og this study can provide a useful information such as the results of the prediction of marketing strategy that efektiv and efficiency of marketing and increase sales. With the 2021 sales data colletion, there are 240 data the based on Book Code attributes, Book Date, Month, Product Name, Price Sold, Initial Stock, Incoming Stock, Final Stock, and Restock. The results of prediction calculation using Naïve Bayes algorithms produce a prediction accuray rate of 92.50%, with precission clas that is “YA” 95.71%, “TIDAK” 88.00% and for class recall that is “YA” 91.78% and “TIDAK” 93.62%