Development of Mobile Application in Assessing Commuting Accident Risk (CommuRisk) Amongst Commuters at Klang Valley
https://doi.org/10.47836/mjmhs.19.3.14
- Author:
Nur Deana Syafiqah Abdullah
1
;
Muhammad Razif Mahadi
2
;
Mohd Rafee Baharudin
3
Author Information
1. Occupational Safety and Health, Faculty of Medicine and Health Science, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
2. Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
3. Department of Community Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
- Publication Type:Journal Article
- Keywords:
Commuting accident, Commuting risk, Risk factors, Mobile application, Commuting safety
- From:Malaysian Journal of Medicine and Health Sciences
2023;19(No.3):106-114
- CountryMalaysia
- Language:English
-
Abstract:
Introduction: Globally, commuting accident risks are always neglected in an organisation. There is a need to assess
the impact of commuting accidents based on sociodemographic, human, vehicle, road, and environmental factors
and to find suitable and effective mitigation strategies to alleviate the associated undesirable outcomes. Methods:
This research was designed to develop a mobile application to assess commuting accident risk levels using artificial
intelligence principles, as we are now in the 21st-century technology era. A total of 216 respondents from private
and government industries participated in this study. Besides, to prove the developed application’s effectiveness, the
study evaluated the effectiveness of the identified risk factor in determining the level of commuting risks predicted
by respondents with the risk level calculated by the mobile application. Results: A major contribution of this paper
is the effectiveness and accuracy of a mobile application known as CommuRisk. The app was developed using Android Studio and natively uses Java. There was a significant difference between with and without mobile applications
in determining the level of commuting risks, and the effectiveness was proven with a (p-value = 0.001) at a 95%
confidence interval with large sample size. Conclusion: Thus, this paper proved the effectiveness and accuracy of a
mobile application in calculating risk levels exposed by commuters compared to risk levels predicted by commuters.
- Full text:11.2023my1514.pdf
