Seasonal autoregressive integrated moving average model for forecasting tourist arrivals in Malaysia

Yen, Phoong Seuk

QR Code Link :
Type :	article
Subject :	Q Science (General)
ISSN :	2146-0353
Main Author :	Yen, Phoong Seuk
Title :	Seasonal autoregressive integrated moving average model for forecasting tourist arrivals in Malaysia

Place of Production :	Tanjung Malim
Publisher :	Fakulti Sains dan Matematik
Year of Publication :	2021
Notes :	Review of International Geographical Education Online
Corporate Name :	Universiti Pendidikan Sultan Idris
Web Link :	Click to view web link

Abstract : Universiti Pendidikan Sultan Idris

Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied for fitting and forecasting the number of tourist arrivals in Malaysia. The time series data that applied in this study was 120 periods, which obtained from January 2008 until December 2017 for models testing and 24 periods include January 2018 to December 2020 for forecasting. The procedure in SARIMA model involving the identification of different SARIMA models, parameter estimation and diagnostic checking, that aims to identify the appropriate model for forecasting. The Akaike Information Criterion (AIC), Schwartz Criterion (SC) and Sum of Square Residual (SSR) are used to investigate the most plausible model that fit with the data. Therefore, SARIMA (1,1,1) (1,1,1)12 model was selected for forecasting tourist arrivals in Malaysia. ? 2021 RIGEO. All Rights Reserved.

This material may be protected under Copyright Act which governs the making of photocopies or reproductions of copyrighted materials.
You may use the digitized material for private study, scholarship, or research.

Back to previous page