Forecasting Cookies Sales at the "Sweetnest" Business Using the Simple Moving Average Method

Peramalan Penjualan Cookies pada Usaha Cookies Sweetnest Menggunakan Metode Simple Moving Average

Abstract

Abstract— Sweetnest Cookies Business is a business that sells various types of cookies. In this business operation, there are challenges that the Sweetnest cookie business must face, namely product stock management. To overcome this problem, research was conducted on sales forecasting using the Simple Moving Average (SMA) forecasting method. The Simple Moving Average (SMA) method was chosen because of its suitability in predicting trends and simple variations that match the characteristics of Sweetnest Cookies sales data. The SEMMA data mining flow is used in data analysis and forecasting calculations, with cookie sales data recorded in detail on the integrated POS system. Data analysis software such as Minitab and Microsoft Excel were used as the main research instruments. Visual Studio Code and Anaconda programming applications were used in system design, with the Python, JavaScript and HTML programming languages ​​to develop interactive web interfaces. The research results show that the Simple Moving Average (SMA) method with a period length of 2 has good performance in predicting cookie sales at Sweetnest Cookies. Evaluation using forecasting accuracy metrics shows a MAPE value of 30,847, a MAD value of 24,071, and an MSD value of 930,429.