Robust Data Processing System at Automotive Company Using RAD Method

Abstract

This study presents the development of a Robust Data Processing System for an Electric Automotive Company using the Rapid Application Development (RAD) methodology. The system is designed to enhance data integration, processing speed, and reliability across multiple departments. The research employs a mathematically formulated RAD approach, in which iterative prototype, feedback, and optimization cycles are modeled to minimize data latency and maximize processing robustness. System usability and performance were evaluated through functional and usability testing using the System Usability Scale (SUS), which achieved an overall score of 87.6, indicating a “Very Good” level of user satisfaction. Functional testing results also demonstrated a 100% success rate across all operational modules, confirming the system’s stability and effectiveness. Experimental results show measurable improvements in data accuracy, synchronization efficiency, and reporting responsiveness compared to traditional development approaches. The proposed system contributes to advancing data-driven decision-making and operational scalability in Indonesia’s electric automotive industry. Future work will focus on integrating predictive analytics and machine learning components to further enhance data intelligence and automation within the system