Work

Time series forecasting of road accident in Malaysia by using Box-Jenkins and univariate model / Nur Farah Bahiah Mohd Zarmi, Nur Balqish Zainal and Norliana Mohd Lip

Year: 2024

Type: article

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.

Source: UiTM Institutional Repositories (Universiti Teknologi MARA)

Authors: Mohd Zarmi, Nur Farah Bahiah, Zainal, Nur Balqish, Mohd Lip, Norliana

Institution: Universiti Teknologi MARA

Language: English

Topic: Forecasting Techniques and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W6987588548

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