<![CDATA[The Covid-19 pandemic has significantly impacted the tourism sector, leading to a drastic decline in regional revenue derived from this industry. To accelerate the recovery of the tourism sector, reliable forecasting methods are required to estimate tourist arrivals. This paper presents the use of time series SARIMA and Triple Exponential Smoothing (Holt-Winters) methods to predict the number of international tourist arrivals in the post-pandemic period. The analysis reveals that the SARIMA method with ARIMA (2,0,1)(1,0,1)₅ parameters, which accounts for seasonal trends over a five-month period, provides the most accurate predictions. Evaluation is conducted using MAPE, MAE, and RMSE value. The predictions generated by these methods are expected to assist governments and tourism-related industries in developing promotion strategies, infrastructure planning, and optimal resource allocation.]]>
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