Forecasting Foreign Tourist Visits in North Sumatra Province Using the SARIMA Model with Step Function Intervention

Abstract. Time series analysis is a method for identifying trends, patterns, and fluctuations in data. Its interpretation can be used for forecasting, such as the number of foreign tourist visits in the tourism sector. The Indonesian tourism sector contributes positively to the national economy with a contribution value of 3.79% of the total foreign exchange worth 146.6 billion USD in December 2023. North Sumatra Province as one of the provinces that contributes to the local economy, through landscape diversity and easy access through Kuala Namu Airport (KNO) as a Passenger Exit Survey (PES) makes North Sumatra Province a priority scale destination. Foreign tourist visits to North Sumatra from January 2017 to March 2020 fluctuated, but in April 2020 there was a significant decline due to Covid-19 and social restriction policies. The purpose of this study was to forecast foreign tourist arrivals in North Sumatra from August 2023 to March 2024 using the SARIMA model with step function intervention analysis. The results showed that the number of tourist visits will increase according to the ARIMA (0,1,1)(1,0,1)12 model with the intervention orders b = r = s = 0. The forecasting evaluation obtained is AIC 447.38 and MAPE 9.91%.