Publication:
Analysis of international visitor arrivals in Bali: Modeling and forecasting with seasonality and intervention

dc.contributor.authorJoy Melchisedec Pierre Mangindaanen_US
dc.contributor.authorTipaluck Krityakierneen_US
dc.contributor.otherMahidol Universityen_US
dc.contributor.otherCommission on Higher Educationen_US
dc.date.accessioned2019-08-28T06:56:21Z
dc.date.available2019-08-28T06:56:21Z
dc.date.issued2018-12-10en_US
dc.description.abstract© Published under licence by IOP Publishing Ltd. This work aims to develop a time series forecasting model for the number of international visitor arrivals to Bali. Tourism sector in Bali is expected to grow since it is considered as the most prepared sector in terms of facilities and infrastructure compared to other sectors. However, Bali has faced some problems related to government policies, unrests, economic and political instability, natural disasters and terrorism which obstruct the growth of the number of international visitor arrivals. Uncovering these social and environmental influences, and incorporating them into the model can lead to a better forecasting model. The data obtained from 2000 to 2016 and in 2017 were used as modeling and validation periods, respectively. The best fitted ARIMAX model is then used to forecast the visitor arrivals for the period 2018-2023. The results show that the number of international visitor arrivals in Bali will continue to grow.en_US
dc.identifier.citationJournal of Physics: Conference Series. Vol.1132, No.1 (2018)en_US
dc.identifier.doi10.1088/1742-6596/1132/1/012069en_US
dc.identifier.issn17426596en_US
dc.identifier.issn17426588en_US
dc.identifier.other2-s2.0-85058626031en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/47358
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85058626031&origin=inwarden_US
dc.subjectPhysics and Astronomyen_US
dc.titleAnalysis of international visitor arrivals in Bali: Modeling and forecasting with seasonality and interventionen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85058626031&origin=inwarden_US

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