Spatio-Temporal models with intervention effect for modelling the impact of Covid-19 on the tourism sector in Indonesia

M. Prastuti*, L. Aridinanti, W. P. Dwiningtyas

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)

Abstract

Coronavirus is a virus that attacks the respiratory system, this disease due to viral infection is called Covid-19. Since it was found at December 2019 in China, the Covid-19 outbreak has spreads to several countries, one of them is Indonesia. This causes the tourism sector in Indonesia to decline drastically. Therefore, this study aims to analyze the impact of Covid-19 outbreak on the number of foreign tourist arrivals to Indonesia especially in Jakarta, Bali, and Surabaya. This data is ordered by times from several different locations and has a relationship with each other or is called spatio-temporal data. Furthermore, the data will be added the intervention variable is time where the covid-19 outbreak found in December 2019. The data will be analyzed using a spatio-temporal models. The result shows that seasonal GSTARX-GLS models tend to give more accurate forecast than VARX and seasonal GSTARX-OLS models.

Original languageEnglish
Article number012044
JournalJournal of Physics: Conference Series
Volume1821
Issue number1
DOIs
Publication statusPublished - 29 Mar 2021
Event6th International Conference on Mathematics: Pure, Applied and Computation, ICOMPAC 2020 - Surabaya, Virtual, Indonesia
Duration: 24 Oct 2020 → …

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