Analisis Marketplace Shopee Untuk Memprediksi Penjualan dengan Algoritma Regresi Linier - Syakir, Yusuf; Hermanto, Teguh Iman; Ramadhan, Yudhi Raymond (STIKOM Tunas Bangsa Pematangsiantar, 2022)
Many methods can be used to predict sales, one of which is the processing of sales data using the method of data mining with a linear regression algorithm. The data in this study used is data on sales of the Ariqa Collection Boutique in the Shopee marketplace starting from May 2020 to April 2022. By using a linear regression algorithm, the Ariqa Collection Boutique can predict sales estimates based on total visitors and total orders. The data mining method used is SEMMA (Sample, Explore, Modify, Model, Assess). With the Rapidminer Studio 9.10 tools the test results Mean Square Error (MSE) value is 5.172.628.212.404, Root Mean Square Error (RMSE) is 2.274.341, and Mean Absolute Percentage Error (MAPE) is 4.34%. Based on the MAPE value obtained, the accuracy of the linear regression algorithm in predicting sales of Ariqa Collection Boutique in the Shopee marketplace provides high accuracy