Data Mining technique: Application of Apriori algorithm for road accident analysis

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DOI:

10.46223/HCMCOUJS.tech.en.13.2.2831.2023

Keywords:

apriori; association rule analysis; CRISP-DM; data mining; road accidents

Abstract

Road accidents can happen due to various factors. These factors that contribute to road accidents have cost damage to properties, injuries or deaths and most road accidents are attributable to the lack of knowledge on road safety. To provide safe driving and road safety plans, critical analysis of road accident data is needed, to identify the causes of road accidents. Annually, 1,250,000 people die and 50,000,000 are injured in road accidents worldwide, and fatal road accidents are caused by human error. Improving road conditions is not sufficient, but significantly understanding human errors that cause road accidents, and negligence of corrective and safety driving protocols provided by the concerned government agencies or private organizations. The study aimed to help get insights about the causes of road accidents, and to provide knowledge of road accidents for road safety using Association Rule Mining with the application of the Apriori Algorithm. Association rule mining using the Apriori Algorithm produces significant patterns and insights that help identify the causes of road accidents.

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References

Ager, M. (2016). 10,000 vehicular accidents in first 4 months of 2016 - police. Retrieved October 10, 2022, from Inquirer.Net. website: https://newsinfo.inquirer.net/821966/10000-vehicular-accidents-in-first-4-months-of-2016-police

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Atnafu, B., & Kaur, G. (2017b). Survey on analysis and prediction of road traffic accident severity levels using data mining techniques in Maharashtra, India. International Journal of Current Engineering and Technology, 7(6), 2277-4106.

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Received: 05-07-2023
Accepted: 07-09-2023
Published: 31-10-2023

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How to Cite

Perez, R. C. L. (2023). Data Mining technique: Application of Apriori algorithm for road accident analysis. HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ENGINEERING AND TECHNOLOGY, 13(2), 60–68. https://doi.org/10.46223/HCMCOUJS.tech.en.13.2.2831.2023

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Copyright (c) 2023 Ryan Clifford Larraquel Perez

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