Pengembangan Model Prediktif untuk Manajemen Risiko dalam Rantai Pasok Global Menggunakan Big Data Analytics - Kesuma, Hendrie Prima; Wulandari, Mery (LPPM Akper Kebonjati, 2025)
Global supply chains face various risks that can interfere with smooth operations and business efficiency. With increasing complexity and uncertainty, companies need to implement advanced technologies such as Big Data Analytics to manage and mitigate risks. This research aims to develop a predictive model based on Big Data Analytics that can improve the resilience of global supply chains through early detection and real-time risk mitigation. The research method involves collecting and analyzing historical data and applying machine learning algorithms to build prediction models. The results show that the use of big data-based predictive models can improve accuracy in identifying risks and accelerate strategic decision-making.