Profit Prediction for Skincare Resellers Using the Exponential Smoothing Method

This research elucidates the application of the exponential smoothing method in forecasting profit figures for Lutfia MS Glow Skincare. This method was chosen due to its capability to adapt data using the alpha value, along with continual refinement based on exponentially smoothed historical averages. With an explanatory purpose, the study collected profit data from 2020 to 2022 at Lutfia MS Glow Skincare. The single exponential smoothing technique was employed to develop a profit prediction system, enabling the identification of sales trends and evaluation through metrics like Mean Absolute Error (MAE) and Mean Squared Error (MSE). The approach offers simplicity in implementation while providing relatively accurate results, especially for short-term forecasting. This makes it particularly useful in retail and skincare business contexts, where sales figures can be volatile due to seasonal demands or market fluctuations. By utilizing exponential smoothing, the research helps reduce forecasting errors and provides actionable insights for business planning. The result of the analysis showed a reasonably low error margin with a Mean Absolute Percentage Error (MAPE) of 3.65%, indicating high prediction accuracy. The research outcomes furnish skincare resellers and decision-makers with practical guidance in planning inventory, managing supply chains, and executing marketing strategies, ultimately supporting better data-driven decisions in a competitive industry.