Authors :
Enrique Raphael Versoza; Sofia Elaine Romarate; Aboy,Jacque Bon-Isaac
Volume/Issue :
Volume 5 - 2020, Issue 9 - September
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/3mhqmwD
DOI :
10.38124/IJISRT20SEP081
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
This paper investigates the rise of South
Korean tourism in the Philippines from 2014 to 2018
and explain its behavior year-to-year, and the other
part is to forecast it’s growth or decline in the next
following years; all of this is done through a Seasonal
ARIMA (SARIMA) modelling framework. Results
reveal that Korean arrivals were best modelled through
a ARIMA(1,0,0)(2,1,0)₁₂ model, with residuals that are
randomly distributed and contain no autocorrelations
and an AICc value of -36.18, the lowest among the
tested variations of the model, the model is the most
appropriate to forecast the data for a 3-year period.
Keywords :
South Korean arrivals; SARIMA; Philippine tourism; prediction
This paper investigates the rise of South
Korean tourism in the Philippines from 2014 to 2018
and explain its behavior year-to-year, and the other
part is to forecast it’s growth or decline in the next
following years; all of this is done through a Seasonal
ARIMA (SARIMA) modelling framework. Results
reveal that Korean arrivals were best modelled through
a ARIMA(1,0,0)(2,1,0)₁₂ model, with residuals that are
randomly distributed and contain no autocorrelations
and an AICc value of -36.18, the lowest among the
tested variations of the model, the model is the most
appropriate to forecast the data for a 3-year period.
Keywords :
South Korean arrivals; SARIMA; Philippine tourism; prediction
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