Article Per Year (5 Year)
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All Journal Journal of Management, Economic, and Financial Journal of Village Development Innovation
Nova Yuningrat
Sekolah Tinggi Agama Islam Kuningan
Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Social Sciences

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Reskilling and Upskilling in the Digital Economy: Adaptive HRM Strategy in the Era of Industrial Revolution 5.0 Siti Munawaroh; Adhi Mustofa; Indra Raksajaya; Nova Yuningrat; Regita Anggia Ning Tyas
Journal of Village Development Innovation Vol. 2 No. 1 (2025): Journal of Village Development Innovation
Publisher : Journal of Village Development Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jvdi.v2i1.12

Abstract

In the era of Industrial Revolution 5.0, rapid technological changes require workers to have relevant and adaptive skills. Reskilling and upskilling are becoming important strategies in human resource (HR) development to ensure organizational competitiveness. However, the biggest challenge is how to design and implement effective training programs to deal with these changes. This study aims to explore and analyze how adaptive strategies in human resource management (HRM) can support the implementation of effective reskilling and upskilling programs in the digital era and Industrial Revolution 5.0. This study used a descriptive qualitative approach, with data collection methods through in-depth interviews and questionnaires distributed to HRM professionals and employees in companies that have implemented skills training programs. This study found that companies that successfully implemented reskilling and upskilling programs experienced increased productivity and competitiveness. The success of these programs relies heavily on managerial support, an organizational culture that supports learning, and adaptive leadership that is actively involved in the planning and evaluation of training programs. Reskilling and upskilling programs designed with HRM adaptive strategies can improve workforce competencies and organizational competitiveness. Organizations need to ensure full support from management and proactive leadership in supporting employee skills development to remain relevant in the face of technological challenges.
The Role of Artificial Intelligence in Systemic Risk Management: A Financial Market Perspective of Emerging and Developed Countries Nova Yuningrat
Journal of Management Economic and Financial Vol. 3 No. 2 (2025): Journal of Management, Economic and Financial
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jmef.v3i2.168

Abstract

The development of Artificial Intelligence (AI) technology has brought significant changes in the global financial sector, especially in the context of systemic risk detection and mitigation. The complexity of financial market integration and the experience of previous global crises demonstrate the urgency of leveraging AI to strengthen the resilience of the financial system. This study aims to analyze the role of AI in systemic risk management by comparing its implementation in developed and developing countries. The research method uses a systematic literature review (SLR) approach enriched with bibliometric analysis to identify global research patterns, as well as comparative analysis to compare practices between the two groups of countries. Secondary data is obtained from academic articles, reports of international institutions, and financial risk indicators such as the Volatility Index (VIX), Capital Adequacy Ratio (CAR), and Non-Performing Loan Ratio (NPL). The results show that AI consistently improves the accuracy of systemic risk detection by up to 40% compared to traditional models. Developed countries are emphasizing the use of AI in the framework of macroprudential supervision, supported by adaptive regulations and mature data infrastructure. In contrast, developing countries are leveraging AI primarily for micro-risk management, such as credit risk and liquidity, but still face regulatory limitations, data infrastructure, and human resources. The main findings of this study confirm the gap in AI implementation between developed and developing countries, while demonstrating the urgency of international collaboration for regulatory harmonization and cross-border data exchange. This research contributes to the literature by presenting a cross-border comparative perspective, as well as providing policy recommendations that emphasize AI transparency, strengthening data infrastructure, and global cooperation to strengthen financial stability in the digital age.
Co-Authors Adhi Mustofa Indra Raksajaya Regita Anggia Ning Tyas Siti Munawaroh