<![CDATA[The tourism sector in North Sulawesi Province has experienced significant fluctuations due to the impact of the COVID-19 pandemic since 2020, followed by a recovery phase up to 2025. This condition highlights the importance of accurate forecasting methods to support tourism planning and policy formulation. This study aims to compare the accuracy of two forecasting methods, namely Simple Moving Average (SMA) and Single Exponential Smoothing (SES), in predicting tourist arrivals. The study employs time series data on tourist arrivals obtained from the Central Statistics Agency (BPS) of North Sulawesi Province for the period 2020–2025. The performance of both methods is evaluated using the Mean Absolute Percentage Error (MAPE) as the forecasting accuracy measure. The results indicate that the Single Exponential Smoothing method, with an appropriately selected α parameter, produces lower forecasting errors compared to the Simple Moving Average method. Therefore, SES is considered more suitable for forecasting tourist arrivals in North Sulawesi Province, which is characterized by dynamic and unstable data patterns.]]>
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