Megat Muhammad Afif, Megat Muainuddin (2021) Time arrival in series forecasting model for tourist National Park Kuala Tahan, Pahang. Masters thesis, Universiti Malaysia Pahang (Contributors, UNSPECIFIED: UNSPECIFIED).
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Abstract
Tourism forecasting can lead to an important element in tourism industry to ensure that each investment by individuals, companies and government is profitable. From economy perspective, eco-tourism is a growing business and it is an important indicator to the tourism industry. It also generates income revenue to the owner and surrounding communities. This research aims to forecast the eco-tourism demand based on number of tourist arrival for both local and foreign tourist at National Park Kuala Tahan, Pahang. The forecasting models used are seasonal autoregressive integrated moving average (SARIMA) and exponential smoothing. Both forecasting models are compared and assessed using Mean absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute error (MAE). The result demonstrated that the best model to forecast the number of tourist arrival in National Park Kuala Tahan, Pahang is SARIMA (1,0,0)(1,0,1) 12 which is based on the smallest value of MAPE, RMSE and MSE. Hence, the exponential smoothing is not as good as the SARIMA model in forecasting tourist arrival for the data used. In future study, SARIMA model can be used to compare between the local and foreign tourist arrival for eco-tourism destination.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | Thesis (Master of Science (Mathematics) -- Universiti Malaysia Pahang – 2021, SV: DR. NORATIKAH BINTI ABU, NO.CD: 12956 |
| Uncontrolled Keywords: | series forecasting |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics |
| Faculty/Division: | Institute of Postgraduate Studies Center for Mathematical Science |
| Depositing User: | Mr. Nik Ahmad Nasyrun Nik Abd Malik |
| Date Deposited: | 14 Oct 2022 02:54 |
| Last Modified: | 14 Oct 2022 02:54 |
| URI: | http://umpir.ump.edu.my/id/eprint/34964 |
| Download Statistic: | View Download Statistics |
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