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All Journal e-Jurnal Apresiasi Ekonomi Multidisciplinary Indonesian Center Journal
Andini Nurwulandari
National University
Religion Humanities Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Other

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A TRANSFORMATIONAL LEADERSHIP, REWARD, AND PUNISHMENT PHYSICAL WORK ENVIRONMENT AND ITS INFLUENCE ON EMPLOYEE PERFORMANCE THROUGH EMPLOYEE WORK MOTIVATION Dimas Prayoga; Andini Nurwulandari
Jurnal Apresiasi Ekonomi Vol 13, No 1 (2025)
Publisher : Institut Teknologi dan Ilmu Sosial Khatulistiwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31846/jae.v13i1.845

Abstract

This study aims to find out the influences of determine consist of Transformational Leadership, Reward and Punishment, and Physical Work Environment on the Employee Work Motivation of the RGD, Corp. Then, this research analyzes the influence of Transformational Leadership, Reward and Punishment, and Physical Work Environment towards Employee Performance through Employee Work Motivation of the RGD, Corp. This type of research is associative with a quantitative approach. The amount of samples in this study is 100 respondents. The data analysis technique used a structural equation model (SEM). Transformational Leadership has a positive and non-significant influence on Employee Work Motivation and Employee Performance. Reward and Punishment have a positive and significant influence on Employee Work Motivation and Employee Performance. Physical Work Environment has a positive and significant influence on Employee Work Motivation, while has a negative on Employee Performance. Employee Work Motivation has a negative and significant influence on Employee Performance. Each Reward and Punishment, then the Physical Work Environment has a significant influence on Employee Performance through Employee Work Motivation, but Transformational Leadership has a negative and non-significant influence on the Employee Performance of RGD, Corp.Keywords: Reward and punishment, Physical work environment, employee work motivation, employee performance
ARTIFICIAL INTELLIGENCE IN FINANCIAL RISK MANAGEMENT: A SYSTEMATIC LITERATURE REVIEW ON ENHANCING ORGANIZATIONAL RESILIENCE FOR FUTURE GLOBAL FINANCIAL CRISES Yonghwa Han; Andini Nurwulandari; Hasanudin; Aghnia Wulandari
Multidisciplinary Indonesian Center Journal (MICJO) Vol. 3 No. 1 (2026): Vol. 3 No. 1 Edisi Januari 2026
Publisher : PT. Jurnal Center Indonesia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62567/micjo.v3i1.1572

Abstract

This study explores how incorporating artificial intelligence improves institutional resilience and overcomes the rigidity of conventional, data-based methods to alter financial risk management. To find patterns in AI applications, resilience theory, and integration pathways, a qualitative systematic literature review was carried out utilizing theme synthesis in accordance with PRISMA peer-reviewed protocols. Findings show that AI techniques, machine learning for tail-risk detection, deep learning for high-frequency forecasting, and explainable AI for transparent decisions, yield up to 28% reductions in forecasting errors and halve recovery times during crises. The hybrid CNN Transformer architectures and transformer-based NLP models significantly enhance predictive accuracy and forward-looking insights. The study suggests financial institutions adopt integrated AI frameworks, invest in data quality and human–AI collaboration, and implement principle-based governance to balance innovation with fairness and stability. Limitations include reliance on published literature and limited representation of emerging AI models, warranting future longitudinal and context-specific empirical research.
Co-Authors Aghnia Wulandari Dimas Prayoga Hasanudin Yonghwa Han