Global warming in Malaysia: Forecasting for the next five years / Muhammad Shahrin Nadzir Zulkifle, Nur Izatul Ain A Malik and Nurul Ain Azizan
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 s...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Student Project |
| Language: | English |
| Published: |
2021
|
| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/59363/1/59363.pdf https://ir.uitm.edu.my/id/eprint/59363/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
my.uitm.ir.59363 |
|---|---|
| record_format |
eprints |
| spelling |
my.uitm.ir.593632022-05-13T07:10:47Z https://ir.uitm.edu.my/id/eprint/59363/ Global warming in Malaysia: Forecasting for the next five years / Muhammad Shahrin Nadzir Zulkifle, Nur Izatul Ain A Malik and Nurul Ain Azizan Zulkifle, Muhammad Shahrin Nadzir A Malik, Nur Izatul Ain Azizan, Nurul Ain HA Statistics Statistical data Analysis Analytical methods used in the solution of physical problems 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. 2021 Student Project NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/59363/1/59363.pdf (2021) Global warming in Malaysia: Forecasting for the next five years / Muhammad Shahrin Nadzir Zulkifle, Nur Izatul Ain A Malik and Nurul Ain Azizan. [Student Project] (Unpublished) |
| institution |
Universiti Teknologi Mara |
| building |
Tun Abdul Razak Library |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Teknologi Mara |
| content_source |
UiTM Institutional Repository |
| url_provider |
http://ir.uitm.edu.my/ |
| language |
English |
| topic |
HA Statistics Statistical data Analysis Analytical methods used in the solution of physical problems |
| spellingShingle |
HA Statistics Statistical data Analysis Analytical methods used in the solution of physical problems Zulkifle, Muhammad Shahrin Nadzir A Malik, Nur Izatul Ain Azizan, Nurul Ain Global warming in Malaysia: Forecasting for the next five years / Muhammad Shahrin Nadzir Zulkifle, Nur Izatul Ain A Malik and Nurul Ain Azizan |
| description |
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. |
| format |
Student Project |
| author |
Zulkifle, Muhammad Shahrin Nadzir A Malik, Nur Izatul Ain Azizan, Nurul Ain |
| author_facet |
Zulkifle, Muhammad Shahrin Nadzir A Malik, Nur Izatul Ain Azizan, Nurul Ain |
| author_sort |
Zulkifle, Muhammad Shahrin Nadzir |
| title |
Global warming in Malaysia: Forecasting for the next five years / Muhammad Shahrin Nadzir Zulkifle, Nur Izatul Ain A Malik and Nurul Ain Azizan |
| title_short |
Global warming in Malaysia: Forecasting for the next five years / Muhammad Shahrin Nadzir Zulkifle, Nur Izatul Ain A Malik and Nurul Ain Azizan |
| title_full |
Global warming in Malaysia: Forecasting for the next five years / Muhammad Shahrin Nadzir Zulkifle, Nur Izatul Ain A Malik and Nurul Ain Azizan |
| title_fullStr |
Global warming in Malaysia: Forecasting for the next five years / Muhammad Shahrin Nadzir Zulkifle, Nur Izatul Ain A Malik and Nurul Ain Azizan |
| title_full_unstemmed |
Global warming in Malaysia: Forecasting for the next five years / Muhammad Shahrin Nadzir Zulkifle, Nur Izatul Ain A Malik and Nurul Ain Azizan |
| title_sort |
global warming in malaysia: forecasting for the next five years / muhammad shahrin nadzir zulkifle, nur izatul ain a malik and nurul ain azizan |
| publishDate |
2021 |
| url |
https://ir.uitm.edu.my/id/eprint/59363/1/59363.pdf https://ir.uitm.edu.my/id/eprint/59363/ |
| _version_ |
1732948393380020224 |
| score |
13.211869 |