FORECASTING NUMBER OF INTERNATIONAL TOURIST ARRIVALS USING MULTI INPUT INTERVENTION ARIMA MODEL
Abstract
In 2020, the Covid-19 pandemic caused a very significant impact resulting in the drastic decline in the number of international tourist visits. As the Covid-19 pandemic ends, the government reopen international flight to Indonesia in early 2022 to remark the revival of the tourism industry. To determine how big the impact of the Covid-19 pandemic as well as the recovery process on international tourist visits through Soekarno-Hatta, Ngurah-Rai, and Kualanamu airports in the coming period, forecasting is needed. The forecasting method utilized in this study is multi-input intervention analysis. The first input is caused by the outbreak of Covid-19 pandemic, while the second input is due to the international flight reopening. The type of intervention variable chosen is a step function because both inputs give permanent effect to the international tourist arrivals. The data used in this study are monthly international tourist arrivals based on the entrances to Soekarno-Hatta, Ngurah-Rai, and Kualanamu International Airports from January 2008 to September 2023, taken from the Central Bureau of Statistics website. Based on the results, it was found that the number of international tourist arrivals entering Soekarno-Hatta airport can be modelled using SARIMA (0,1,1)(0,1,0)12 with (b=2, s=1, r=0) and (b=2, s=[3], r=0) for first and second input of intervention variable, respectively. Furthermore, the number of international tourist visits through Ngurah-Rai airport was more appropriate to be modelled using SARIMA (1,1,1)(0,1,1)12 with intervention inputs (b=1, s=[2], r=0) and (b=4, s=0, r=1). In Kualanamu airport, the first intervention order is equal to that in Ngurah-Rai airport, with (b=3, s=[3], r=0) for second intervention input and SARIMA (0,1,1)(1,1,1)12 for pre-intervention data. The forecast results show that the number of international tourist arrivals entering Soekarno-Hatta, Ngurah-Rai, and Kualanamu international airports are already recovered to pre-pandemic conditions at a quick pace
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Copyright (c) 2024 Hidayatul Khusna, Muhammad Mashuri, Muhammad Ahsan, Wibawati Wibawati, Diaz Fitra Aksioma, Novri Suhermi
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