Management Information System Based on IoT and Big Data Technology for Optimization of Supply Chain - Muqorobin Muqorobin; Farid Fitriyadi (Institut Teknologi Bisnis AAS Indonesia, 2025)
This paper explores the integration of Internet of Things (IoT) and Big Data Analytics for optimizing supply chain management. With increasing complexity in global supply chains, traditional information systems fall short in providing real-time visibility, accurate forecasting, and agile decision-making. IoT technology facilitates real-time data collection through sensors embedded in goods, vehicles, and production systems, while Big Data analytics processes these high-volume, real-time data streams to generate actionable insights. By integrating these technologies into a Management Information System (MIS), this paper proposes a framework that enhances supply chain visibility, forecasting accuracy, and responsiveness. The study examines how IoT-enabled sensors and big data analytics improve logistics, inventory management, and risk mitigation. Key challenges, including data security, interoperability, and infrastructure costs, are also addressed. The proposed MIS architecture offers a foundation for building smart, adaptive, and resilient supply chains, transforming decision-making from reactive to proactive. The findings suggest significant improvements in operational efficiency and supply chain agility. This paper concludes with implications for practitioners and calls for further empirical research to validate the proposed system in real-world settings.