| Autor: |
Mohamed, Norizan, Bakar, Maharani A., Razali, Siti Nurfarahanim Mohd, Mazlan, Nur Khalisa, Idrus, Nurfarahin, Aleng, Nor Azlida, Yusof, Yusnita |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2023, Vol. 2746 Issue 1, p1-11, 11p |
| Abstrakt: |
Tourism industry has become an important sector for Malaysian economy through foreign exchange earnings and employment opportunities where generally increases the economic development of the country. Due to significant effect to Malaysia economy, it motivated us to come up with the best model for forecasting both outbound and inbound tourists in Malaysia. Hence, this paper aims to develop the best model for forecasting outbound and inbound tourists in Malaysia by using Box-Jenkins SARIMA model and multilayer feedforward neural network (MFNN) model. The dataset used was monthly basis, recorded from January 2010 to December 2019, and was split into in-sample data from January 2010 to December 2017 and out-sample data from January 2018 to December 2019. The accuracy of the models was measured by using MAPE. By applying SARIMA and MFNN to the dataset, results shown MFNN model is more accurate than the SARIMA model to forecast outbound and inbound tourists in Malaysia. The paper provides implications for policy makers and suggestions for future tourism forecasting models. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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