SCHOOL MANAGEMENT SYSTEM 2: AUTOMATED GRADUATION PHOTOGRAPHY MANAGEMENT SYSTEM: STREAMLINING SOCIAL MEDIA SCHEDULING, STUDIO VERIFICATION, AND STATUS TRACKING FOR STUDENT DOCUMENTATION

Abstract

The Automated Graduation Photography Management System was created to solve the difficulties encountered by the Social Media (Socmed) Department in handling student documentation and graduation photography. Previously, the department relied on manual processes—including renaming photo files and entering student information by hand—that were both time-consuming and prone to errors. These inefficiencies led to significant challenges, especially as the workload increased. The new system is designed to automate and simplify these tasks, thereby improving accuracy and boosting overall workflow efficiency. The Agile Scrum is employed as a methodology to develop the Automated Graduation Photography Management System for the Social Media (Socmed) project. By organizing work into structured sprints, conducting daily stand-ups, and holding regular sprint reviews, we maintained consistent progress and quickly adapted to evolving requirements. Collaborating closely with department staff as Product Owners, we continuously gathered feedback to ensure the system met actual operational needs. This approach enabled us to efficiently deliver a user-centered solution that streamlined social media scheduling, studio verification, and student status tracking—ultimately enhancing workflow and service delivery. The Automated Graduation Photography Management System successfully resolved the inefficiencies present in the Social Media (Socmed) Department's manual workflow. By automating essential tasks like file renaming, social media scheduling, and student documentation tracking, the system greatly increased operational efficiency. This automation improved accuracy, reduced the manual workload, and streamlined processes, resulting in notable enhancements in overall workflow management. The study suggests that integrating Artificial Intelligence (AI) into the Automated Graduation Photography Management System could greatly enhance photo automation and overall efficiency. Advanced features like facial recognition and intelligent scheduling have the potential to further streamline operations. However, concerns about data privacy and security may pose challenges to implementation. Future development should prioritize strengthening data protection measures while utilizing advanced analytics to optimize system performance.