Journal of Cyber Security and Risk Auditing

Unveiling the Causes of Fatal Road Accidents in Iraq: An Association Rule Mining Approach Using the Apriori Algorithm

by 

Malath Riyadh Alboalebrah ;

Salam Al-augby

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Published: 2025/04/02

Abstract

With the increase in fatal accidents in Iraq, they have become a source of concern for both authorities and the public. Therefore, it has become necessary to conduct an analysis of these road accidents. This study aims to provide recommendations to responsible authorities after assessing the frequency of fatal traffic accidents and identifying the most common causes. This will provide actionable insights for decision-makers to formulate laws that allow for the reduction of these accidents and the reduction of human and economic losses. This paper applied data mining algorithms to three years of traffic fatal accident data in Iraq, excluding the Kurdistan Region. The results showed that people without driver's licenses and with primary school certificates were more likely to fail to wear seatbelts, making them a dangerous group. Married individuals aged 36-41 were also associated with fatal accidents. Based on the results, some recommendations were made to reduce these accidents.

Keywords

Data miningAssociation ruleAprioriIraqFatal road accident

Doi Link

https://doi.org/10.63180/jcsra.thestap.2025.2.1

How to Cite the Article

Riyadh Alboalebrah, M., & Al-augby, S. (2025). Unveiling the Causes of Fatal Road Accidents in Iraq: An Association Rule Mining Approach Using the Apriori Algorithm. Journal of Cyber Security and Risk Auditing, 2025(2), 1–11.https://doi.org/10.63180/jcsra.thestap.2025.2.1

Unveiling the Causes of Fatal Road Accidents in Iraq: An Association Rule Mining Approach Using the Apriori Algorithm is licensed under CC BY 4.0CCBY

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