Digital Transformation of Human Resource (HR) Cloud Data Transaction for Quality Management Practices with AI-based Document Authenticator

Abstract

To enhance quality management practices, a digital transformation of human resources was proposed as a key strategic initiative. This study centered on developing a cloud-based data transaction system for HR management, specifically focusing on learning and development, and incorporating AI-powered document authentication tailored for particular LUCs in NCR.  The shift from traditional HR systems to a cloud-enabled platform offered improved precision, security, and accessibility. This transition aligns with the progressive developments in artificial intelligence, machine learning, and cloud computing, generally leading to more streamlined HR processes, particularly in document verification, data management, and quality assurance.  Employing Agile methodologies, the HR cloud data transaction system was developed through iterative sprints, addressing user authentication, document management, automated workflows, and AI-driven verification using convolutional neural networks (CNN). The system's evaluation, based on the ISO 25010 software quality model, involved gathering feedback from HR professionals and administrators in specified NCR LUCs, assessing various aspects including functionality, performance, and security.  The research combined descriptive and developmental approaches to examine current HR practices, identify challenges, and determine system requirements. The resulting HR cloud data transaction system successfully met the LUCs' specific needs, enhancing HR business processes by minimizing manual interventions while bolstering document authentication security through AI.  The AI and CNN-based document authentication system demonstrated effectiveness in validating digital signatures and improving data transactions within HR environments. Users noted significant improvements in data accuracy and usability, coupled with enhanced accessibility.