Modeling and forecasting: A case study of tourist arrivals in Malaysia
Tourism industry has become one of the main sources for Malaysia's income. It affects other sectors such as hotels, retail businesses and transportations. Thus, it is important to monitor the development of tourism industry, so that proper planning can be enforced. Therefore, forecasting by usi...
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Kulliyyah of Languages and Management, International Islamic University Malaysia
2019
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iium-778752020-02-12T06:46:02Z http://irep.iium.edu.my/77875/ Modeling and forecasting: A case study of tourist arrivals in Malaysia Abd Rahman, Nur Haizum Jamal, Nur Nabilah Abd Rahman, Nur Hidayah H Social Sciences (General) HA Statistics Tourism industry has become one of the main sources for Malaysia's income. It affects other sectors such as hotels, retail businesses and transportations. Thus, it is important to monitor the development of tourism industry, so that proper planning can be enforced. Therefore, forecasting by using time series analysis, which is the Box-Jenkins method will be discussed here to provide future information to support the decision-making processes. The forecast performance has been compared by using magnitude error measurements. The empirical result shown that SARIMA (0,1,0)(0,1,1)12 is the best model in forecasting tourist arrivals with only 8% different between 12 of the actual and forecast values. Kulliyyah of Languages and Management, International Islamic University Malaysia 2019 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/77875/10/ILTC%20TOURIST%20STATISTIC.pdf Abd Rahman, Nur Haizum and Jamal, Nur Nabilah and Abd Rahman, Nur Hidayah (2019) Modeling and forecasting: A case study of tourist arrivals in Malaysia. In: 3rd International Language & Tourism Conference 2019, 18th - 19th October 2019, Pagoh Edu Hub, Muar, Johor. https://conference.iium.edu.my/iltc2019/ |
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institution_category |
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institution |
International Islamic University Malaysia |
building |
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Online Access |
language |
English |
topic |
H Social Sciences (General) HA Statistics |
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H Social Sciences (General) HA Statistics Abd Rahman, Nur Haizum Jamal, Nur Nabilah Abd Rahman, Nur Hidayah Modeling and forecasting: A case study of tourist arrivals in Malaysia |
description |
Tourism industry has become one of the main sources for Malaysia's income. It affects other sectors such as hotels, retail businesses and transportations. Thus, it is important to monitor the development of tourism industry, so that proper planning can be enforced. Therefore, forecasting by using time series analysis, which is the Box-Jenkins method will be discussed here to provide future information to support the decision-making processes. The forecast performance has been compared by using magnitude error measurements. The empirical result shown that SARIMA (0,1,0)(0,1,1)12 is the best model in forecasting tourist arrivals with only 8% different between 12 of the actual and forecast values. |
format |
Conference or Workshop Item |
author |
Abd Rahman, Nur Haizum Jamal, Nur Nabilah Abd Rahman, Nur Hidayah |
author_facet |
Abd Rahman, Nur Haizum Jamal, Nur Nabilah Abd Rahman, Nur Hidayah |
author_sort |
Abd Rahman, Nur Haizum |
title |
Modeling and forecasting: A case study of tourist arrivals in Malaysia |
title_short |
Modeling and forecasting: A case study of tourist arrivals in Malaysia |
title_full |
Modeling and forecasting: A case study of tourist arrivals in Malaysia |
title_fullStr |
Modeling and forecasting: A case study of tourist arrivals in Malaysia |
title_full_unstemmed |
Modeling and forecasting: A case study of tourist arrivals in Malaysia |
title_sort |
modeling and forecasting: a case study of tourist arrivals in malaysia |
publisher |
Kulliyyah of Languages and Management, International Islamic University Malaysia |
publishDate |
2019 |
url |
http://irep.iium.edu.my/77875/ http://irep.iium.edu.my/77875/ http://irep.iium.edu.my/77875/10/ILTC%20TOURIST%20STATISTIC.pdf |
first_indexed |
2023-09-18T21:49:48Z |
last_indexed |
2023-09-18T21:49:48Z |
_version_ |
1777413692504145920 |