Crashlytics:
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Date
2024-12
Journal Title
Journal ISSN
Volume Title
Publisher
Don Mariano Marcos Memorial State University – Mid La Union Campus
Abstract
This study aimed to analyze accident-prone areas in San Fernando City, La Union, Philippines, using a web-based system developed with Association Rule Mining. It provides valuable insights to inform interventions and policies to reduce vehicular accidents in the region. The research follows the CRISP-DM methodology, which includes six phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. System development was based on the Rapid Application Development (RAD) model, which enabled iterative prototyping with user feedback. The system integrated the FP-Growth algorithm for Association Rule Mining to identify accident patterns and was coupled with an interactive map for enhanced visualization and decision-making. Usability testing revealed an average System Usability Scale (SUS) score of 87.14, indicating "Best Imaginable" usability and high user satisfaction.
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Keywords
Association rule mining, Traffic accidents, Traffic accidents--Research, Traffic accidents--Mathematical models, Drinking and traffic accidents--Prevention, Drinking and traffic accidents--Prevention--Technological innovations, Vehicular ad hoc networks (Computer networks)
Citation
Madayag, M. B., Asejo, R. J. P., Bucsit, J. V., & Gameng, K. J. G. (2024). Crashlytics: Vehicular black spot analysis using association rule mining. [Unpublished Undergraduate Thesis]. Don Mariano Marcos Memorial State University - Mid La Union Campus, City of San Fernando, La Union. Lakasa ti Sirib, DMMMSU Institutional Repository.