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All Journal International Journal of Advanced Multidisciplinary Siber International Journal of Digital Business
Ardanta, M Arya
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Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences

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Optimization of Business Decision Accuracy through the Application of Mathematical Economics Ardanta, M Arya; Fauzi, Achmad; Pitri Patimah; Fayza Khadijah; Yeremia Todo Sihombing; Fadia Salma Hasan; Rahmawati, Dinda
International Journal of Advanced Multidisciplinary Vol. 2 No. 4 (2024): International Journal of Advanced Multidisciplinary (January-March 2024)
Publisher : Green Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/ijam.v2i4.447

Abstract

In the dynamic landscape of contemporary business environments, the need for precise decision-making has become paramount for organizational succes. It explores the strategic integration of mathematical economics as a powerful tool for enchancing decision accuracy in business. Mathematical economics, a discipline that combines economic theories with mathematical methodologies, offers a structured framework to model, and analyze a complex business strategy decision. This study delves into a theorical foundations of mathematical economics and investigates it practical applications in real-world business decision-making processes. Through the utilization of mathematical model, optimization techniques, and statistical analyses, businesses can gain insights into market dynamics, resource allocation, and risk assessment. The objective is to establish a systematic approach that aids decision-makers in formulating well-informed strategies, minimizing uncertaintes, and maximizing overall business performance.
Human-AI Collaboration in Supply Chain Industry 5.0 to Build a Human-Centered Autonomous Ecosystem Ardanta, M Arya; Fauzi, Achmad; Patimah, Pitri; Khadijah, Fayza; Yunandi, Sheryl Rashida; Ghowe, Azka Marzuqi
Siber International Journal of Digital Business (SIJDB) Vol. 2 No. 4 (2025): (SIJDB) Siber International Journal of Digital Business (April - June 2025)
Publisher : Siber Nusantara Review & Yayasan Sinergi Inovasi Bersama (SIBER)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/sijdb.v2i4.197

Abstract

The emergence of Industry 5.0 has shifted supply chain management from full automation toward a human-Al collaborative ecosystem, where artificial intelligence (AI) enhances efficiency while retaining human decision-making and ethical considerations. This study explores the incorporation of AI-powered decision-making, autonomous systems, and sustainability strategies in modern supply chains, emphasizing their impact on efficiency, resilience, and transparency. The research highlights how Al-powered predictive analytics, real-time inventory management, and automated logistics optimize supply chain performance, reducing operational costs and minimizing waste. Case studies from Amazon, JD Logistics, and Siemens demonstrate how AI-powered solutions improve predictive demand analysis, optimize routing, and circular economy practices, leading to more sustainable and agile supply chains. Furthermore, autonomous systems, such as self-driving freight vehicles and robotic fulfillment centers, significantly improve speed and accuracy in global supply networks. Despite its advantages, Al adoption in supply chains presents challenges, including substantial implementation costs, cybersecurity threats, and workforce adaptation challenges, and ethical concerns related to automation. The study underscores the necessity of a human-centric approach, ensuring that AI enhances human expertise rather than substituting it. Organizations must prioritize Al transparency, ethical governance, and digital upskilling programs to maximize AI's potential in next-generation Industry 5.0 supply networks. This research concludes the successful integration of AI in managing supply chains will drive the next generation of self-optimizing, sustainable, and resilient supply networks. Future research should examine AI's long-term socioeconomic effects, its integration with blockchain and IoT, and the development of AI ethics in decision-making.
Co-Authors Achmad Fauzi Fadia Salma Hasan Fayza Khadijah Ghowe, Azka Marzuqi Khadijah, Fayza Patimah, Pitri Pitri Patimah Rahmawati, Dinda Yeremia Todo Sihombing Yunandi, Sheryl Rashida