Abstract
Global warming affect some human activities such as construction and agriculture. These activities affect the climate change and rising in temperature. In 2050, the world temperature was estimated to increase by 1.5◦C. Hence, this research was conducted to model and forecast monthly temperature of specific area in Malaysia which are Cameron Highland and Petaling Jaya observed from January 1990 to December 2019. The Seasonal Autoregressive Integrated Moving Average (SARIMA) were applied to the monthly temperature for both places for modeling and forecasting purposes. The best models were evaluated by Akaike’s Information Criterion (AIC), Bayesian’s Information Criterion (BIC) and error measures; Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The model that satisfied all criterion is the chosen one. The best model to forecast monthly temperature of Cameron Highland is SARIMA(2,1,1)(3,1,1)12, while for monthly temperature of Petaling, SARIMA(1,0,4)(3,1,2)12 is the most suitable SARIMA model. The result of forecasting show that the monthly temperatures for both places are expected to increase for the next five years and become an alarm for higher authorities for further actions.
Metadata
Item Type: | Student Project |
---|---|
Creators: | Creators Email / ID Num. Zulkifle, Muhammad Shahrin Nadzir UNSPECIFIED A Malik, Nur Izatul Ain UNSPECIFIED Azizan, Nurul Ain UNSPECIFIED |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Khairol Azmi, Dr Nurul Nisa’ UNSPECIFIED |
Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > Statistical data Q Science > QA Mathematics > Analysis Q Science > QA Mathematics > Analysis > Analytical methods used in the solution of physical problems |
Divisions: | Universiti Teknologi MARA, Negeri Sembilan > Seremban Campus > Faculty of Computer and Mathematical Sciences |
Programme: | Bachelor of Science (Hons.) Statistics |
Keywords: | Global warming, Cameron Highland, Petaling Jaya |
Date: | 2021 |
URI: | https://ir.uitm.edu.my/id/eprint/59363 |
Download
59363.pdf
Download (83kB)