PENERAPAN DATA MINING UNTUK MEMPREDIKSI PENJUALAN KAIN TENUN MNGGUNAKAN REGRESI LINEAR - Firda Widia; Wafiah Murniati; Saikin (Pusat Riset dan Inovasi Nasional, 2022)
Abstract Weaving craft is one of the handicrafts located in Lombok, West Nusa Tenggara. Weaving is one of the MSMEs that is very close to the tourism industry and has good economic potential because it absorbs a lot of labor, opens up business fields, and increases the country's foreign exchange. The problem that is often faced by entrepreneurs of woven fabrics is the difficulty in estimating customer demand, so that some of the products requested by customers are not available. It is necessary for sales analysis of woven fabric products to be able to predict customer demand, by means of analyzing past sales data to predict future sales. The research that will be carried out is to predict sales of woven fabric products by processing sales data in the past by modeling the Linear Regression method, and for testing the algorithm is by Mean Square Error (MSE), Mean Square Error (MSE) and Root Mean Square Error. (RMSE). From the results of linear regression modeling the score obtained is 0.8041320270845731. and the test results mean Mean Square Error (MSE) the error value obtained is too high, namely 47,377, and the Root Mean Square Error (RMSE) value is 6.883125, while the MAE score is 3.373572.