Perbandingan Metode Double Exponential Smoothing dan Double Moving Average dalam Penjualan Produk Herbal HNI - Tanjung, Sunilfa Maharani; Ikhwan, Ali (Forum Kerjasama Pendidikan Tinggi (FKPT), 2024)
Predicting sales of herbal products is the main challenge faced in this research. Currently, forecasting is done solely based on previous sales records, which often prove to be inaccurate. As a result, the company frequently experiences unstable sales and faces difficulties in optimizing inventory and planning product orders efficiently to meet high customer demand. This situation often leads to significant cost losses, forcing the company to reduce capital costs for certain products to cover these losses. The problem arises because the company has not yet implemented an appropriate forecasting method, resulting in estimates that are not supported by a reliable system. This research aims to design and implement a Sales Management Information System for Herbal Products, focusing on the use of the Double Exponential Smoothing (DES) and Double Moving Average (DMA) methods. Additionally, this study aims to compare the two methods in predicting sales by analyzing and calculating the Mean Absolute Percentage Error (MAPE) value for each method. The research uses 200 sales data points from 8 best-selling products, including one of the best-selling products, HNI HEALTH, with data collected from April 2022 to April 2024. The MAPE results from the sales data were then calculated by summing all the MAPE values and dividing them according to the number of MAPEs with an alpha of 0.3. It was found that the DES method is more accurate, with an average Mean Absolute Percentage Error (MAPE) value of 0.285, compared to the DMA method, which has an average MAPE value of 0.292. The DES method is considered more accurate because its MAPE value is smaller than that of the DMA method.