<![CDATA[This study aims to analyze Yield Efficiency and Loss Rate in an Industry 4.0-based plywood manufacturing supply chain to improve production efficiency and support sustainable supply chain performance. A descriptive quantitative approach with a case study was employed in a plywood manufacturing industry located in Kediri, Indonesia. The data consisted of monthly production records from January to December 2024, including total logs, super-grade logs, and downgraded logs. Forecasting methods applied in this study were the 3-Month Moving Average and Single Exponential Smoothing with a smoothing constant (α) of 0.9. The performance of both methods was evaluated using Mean Squared Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), the Shapiro-Wilk normality test, significance testing, and a 95% confidence interval. The results indicate that the 3-Month Moving Average method provides better forecasting accuracy, with an MSE of 12,742,092, an RMSE of 4,113.77, and a MAPE of 22.70%, which are lower than those obtained using Single Exponential Smoothing. Statistical test results reveal that the residuals are normally distributed and exhibit no significant bias, indicating that the forecasting model is valid. Furthermore, the findings demonstrate that the implementation of the Industry 4.0 approach supports Yield Efficiency control and minimizes Loss Rate, thereby enhancing the sustainable performance of the plywood manufacturing supply chain.]]>
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