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

Ryan Clifford Larraquel Perez

doi:10.46223/HCMCOUJS.tech.en.13.2.2831.2023

13(2)2023

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

Author - Affiliation:

Ryan Clifford Larraquel Perez - Marinduque State College, Tanza, Boac, Marinduque

Corresponding author: Ryan Clifford Larraquel Perez - ryancliffordperez@gmail.com

DOI:10.46223/HCMCOUJS.tech.en.13.2.2831.2023

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

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.

Keywords

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

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Cite this paper as:

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. doi:10.46223/HCMCOUJS.tech.en.13.2.2831.2023

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DOI: https://doi.org/10.46223/HCMCOUJS.tech.en.13.2.2831.2023