The number of foreign tourists that continues to increase in North Sumatra makes the government must prepare appropriate strategies for policy-making. The data released by the Central Statistics Agency (BPS), as the responsible institution, still has shortcomings, particularly the time gap between data collection and publication. Using Google Trends as supplementary data to fill this time gap is feasible, as Google Trends data can be accessed in real time. This study aims to examine the relationship between Google Trends data and official statistical data, compare the use of SARIMA and SARIMAX models, and forecast the number of tourists for the next year. The results show a moderate correlation between the Google Trends index and official statistics, with a correlation value of 0.592. The most suitable model for this data is the Seasonal Autoregressive Integrated and Moving Average (SARIMA) (0,1,1) (1,0,1)12, with a Root Mean Square Error (RMSE) of 10.223.
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