MSMEs are one of the important sectors to support economic growth. In the midst of increasingly tight competition, business actors need to implement effective strategies to anticipate fluctuations in market demand so that accurate demand forecasting is a crucial step to ensure optimal stock availability. Currently, MSMEs only make predictions based on instinct and experience, not based on mathematical calculations, so that sometimes there is overstock or understock of the goods produced. This study analyzes the demand for sandals and shoes at MSME Mulyaharja, Bogor City using the moving average and exponential smoothing methods. The purpose of this study is to determine the most accurate forecasting method to optimize inventory management and minimize the risk of shortages or excess stock. Historical sales data for one year is used as the basis for the analysis. The results of the comparative analysis of forecasting errors show that the Moving average method with 2 periods provides the most accurate results, with a Mean Absolute Deviation (MAD) value of 54, Mean Squared Error (MSE) of 3380, and Mean Absolute Percentage Error (MAPE) of 18%. The conclusion of this study is that the 2-period Moving average method is the best method to be applied to Mulyaharja UMKM, by applying this forecasting method, overstock and understock of product inventory can be reduced because the amount of production produced is close to the amount of customer demand.