https://rmrj.usjr.edu.ph/rmrj/index.php/RMRJ/issue/feed 2024-11-11T00:00:00+08:00 Jessica Magallon-Avenido, LPT, Ph.D. recoletos_journal@usjr.edu.ph Open Journal Systems <p>The Recoletos Multidisciplinary Research Journal (RMRJ) is the official bi-annual journal of the University of San Jose-Recoletos (USJ-R) Center for Policy, Research, and Development Studies (CPRDS). Being an <strong><em>internationally peer-reviewed journal</em></strong>, RMRJ adopts the double-blind review process wherein the reviewer/s and the author/s do not know each other's identity.</p> <p><strong> </strong><strong>Aims</strong></p> <p>RMRJ is dedicated to the promotion of knowledge through high-quality research publication in various disciplines. It adheres to the policy that all articles contained therein must meet the rigors of an independent double-blind peer-reviewing system and editing to ensure that the publication possesses scientific and academic merit.</p> <p><strong>Scope</strong></p> <p>RMRJ welcomes submission of quality researches in any of the following academic domains:</p> <ul> <li class="show">Accountancy, Business and Management, and Finance;</li> <li class="show">Communication, Humanities, Psychology, and Religion;</li> <li class="show">Education and Educational Management;</li> <li class="show">Engineering, Mathematics, Statistics, and Technology;</li> <li class="show">Environment, Health, and Natural Sciences;</li> <li class="show">Philosophical and Mathematical Reviews; and</li> <li class="show">Politics and Governance, and Social Sciences.</li> </ul> https://rmrj.usjr.edu.ph/rmrj/index.php/RMRJ/article/view/1964 2024-06-14T19:39:50+08:00 Epifelward Niño Amora ninyohamora2017@gmail.com Jovelyn Cuizon jvlync@gmail.com

<p>This study developed a software application that integrates Internet of Things (IoT) devices and weather data to visualize prime fishing locations using advanced spatial data techniques. The application features a dashboard that processes and displays real-time data, providing insights into fishing trends, fisherman activities, boat locations, and environmental conditions. The application uses the Graham scan method to generate a GIS grid heatmap for visualizing fish populations and trends, enhancing fisheries management capabilities. Comprehensive testing and refinement ensured the application's usability and adaptability. The results demonstrated high user satisfaction, with a 91% rating in usability and accuracy. The Graham Scan method successfully mapped fishing zones, achieving a 97.96% overlap in spatial-temporal data analysis, proving essential for data-driven decision-making in sustainable fisheries management.</p>

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