ONLINE EMERGENCY RESPONSE MANAGEMENT SYSTEM FOR CITY DISASTER RISK REDUCTION MANAGEMENT OFFICE OF CALAMBA CITY, LAGUNA
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Abstract
This study presents the development of an Online Emergency Response Management System for the City Disaster Risk Reduction and Management Office of Calamba City, Laguna. The system integrates Geographic Information Systems, Machine Learning, and Decision Support Systems to enhance disaster preparedness through real-time hazard monitoring, spatial analysis, and data-driven decision-making. A key feature is the use of Natural Language Processing and TF-IDF to analyze incident reports and generate actionable recommendations for resource allocation and evacuation planning. The research employed a developmental design and stratified sampling, involving CDRRMO personnel, GIS experts, and IT professionals. System evaluation followed the ISO 25010 software quality model and Technology Acceptance Model. The ISO evaluation yielded an overall mean score of 4.61, with Compatibility 4.61, Security 4.56, and Reliability 4.53 receiving the highest marks. The TAM results indicated high user satisfaction: Perceived Usefulness 6.69, Ease of Use 6.68, Attitude Toward Using 6.83, and Behavioral Intention 6.65. These findings confirm the system’s effectiveness in improving resource coordination, user engagement, and emergency response. Future improvements include expanding to cover scenarios like wildfires and enhancing user accessibility. Overall, the OERMS proves to be a robust, scalable, and user-validated tool for disaster resilience.
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