Abstract
This study aims to predict future road accidents in Malaysia using time series forecasting techniques. The objectives are to determine the best model between Box-Jenkins and Univariate methods, and to forecast road accident numbers based on the model with the lowest error measures of MAPE and RMSE. The study analyzes Malaysia’s historical and current traffic accident trends to provide insights for forecasters, government agencies, and transportation firms. Researchers can also build upon the findings to further investigate traffic accident prediction in Malaysia. The results show that the Double Exponential Smoothing model provides the most accurate forecasts for 2024 road accident numbers in Malaysia. This information can help authorities implement targeted interventions to improve road safety and reduce the significant human and economic toll of traffic accidents.
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Mohd Zarmi, Nur Farah Bahiah UNSPECIFIED Zainal, Nur Balqish UNSPECIFIED Mohd Lip, Norliana UNSPECIFIED |
Subjects: | L Education > L Education (General) Q Science > QA Mathematics |
Divisions: | Universiti Teknologi MARA, Negeri Sembilan > Seremban Campus |
Journal or Publication Title: | Journal of Exploratory Mathematical Undergraduate Research (JEMUR) |
ISSN: | 3030-5411 |
Volume: | 2 |
Keywords: | Box-Jenkins, ARIMA, Univariate Model, Single Exponential Smoothing (SES), Double Exponential Smoothing (DES) |
Date: | October 2024 |
URI: | https://ir.uitm.edu.my/id/eprint/106038 |