<![CDATA[Sugar production in Indonesia is still fluctuating and has not been able to meet the increasing domestic demand, so a comprehensive analysis of factors related to sugar production and accurate forecasting methods is needed. This study aims to analyze the relationship between sugarcane production and yield to sugar production in Indonesia and compare the accuracy of multiple linear regression forecasting methods and Single Exponential Smoothing (SES). The data used is secondary data obtained from the Central Statistics Agency with a total of 44 observations. The analysis was carried out using linear regression to test the relationship between variables and the SES method to forecast until 2025. The results showed that sugarcane production and yield had a significant relationship with sugar production, both partially and simultaneously, with a determination coefficient value (R²) of 0.703. The accuracy test showed that the linear regression method had a MAPE value of 11.75%, while the SES method was 8.85%, so the SES was considered more accurate. The forecast results indicate a trend to increase sugar production until 2025. Thus, the SES method is more suitable for forecasting, while linear regression is more appropriate for analyzing the relationships between variables. ]]>
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