About 22 results for “Machine Learning”

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PDF SKONEK: A LOCAL YOUTH COUNCIL PROJECT MANAGEMENT AND PERFORMANCE MONITORING SYSTEM

by Ervin Beltran Mendoza; Mary Claire Ricalde Consigo • 2024

One major problem encountered by the Local Youth Development Office (LYDO) is the difficulty in monitoring and managing SK officials due to their reliance on manual document monitoring processes. These manual methods often lead to inefficiencies, delays, and challenges in tracking the performance of officials. To resolve these issues, the SKONEK: A Local Youth Council Project Management and Performance Monitoring System was developed as an automated solution to streamline project management, improve performance tracking, and enhance overall operational efficiency for local youth councils. In developing SKONEK, the Agile methodology was employed, ensuring a flexible, collaborative, and iterative approach that allowed for continuous refinement based on stakeholder feedback. This ensured the system met the specific needs of the LYDO and its users. The results of the study show a highly positive outcome. The system was evaluated as highly acceptable, with users expressing strong satisfaction with its functionality, usability, and overall effectiveness. These findings highlight the system's potential to significantly improve the LYDO's document management processes and enhance the management and monitoring of youth council projects.

PDF GUARDIAN WATCH: DEVELOPMENT OF QUICK RESPONSE AND EFFICIENT CASE MANAGEMENT FOR MINOR CRIMES AT NASUGBU MUNICIPAL POLICE STATION

by Karen G. Hernandez; Lovely P. Gonzales; Michael Darren G. Arroyo; Jazmine Kaye S. Revilla • 2024

Crime reporting is essential for law enforcement agencies, yet many still rely on manual processes that hinder efficiency, delay responses, and limit accessibility for the community. To address these challenges, this study developed a digital crime reporting system specifically tailored for the Nasugbu Municipal Police Station (MPS). The system incorporates features such as digitized crime reporting for streamlined submission and tracking of incidents, real-time emergency reporting and response mechanisms to facilitate prompt action during critical situations, notifications and alerts to improve communication between police and residents, and location-based incident mapping to monitor and analyze crime occurrences effectively. Designed using the descriptive-developmental research method and Agile framework to ensure adaptability and user-focused development, the system was evaluated through structured feedback from 20 law enforcers, 120 residents from high-crime areas, and 10 IT experts. Results showed high user satisfaction with the system's functionality and usability, particularly in streamlining reporting and emergency responses, though suggestions for improving follow-up mechanisms, privacy, and security were noted. The study highlights the potential of digital tools to modernize crime reporting, enhance public safety, and improve law enforcement efficiency.