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Blockchain, Artificial Intelligence, and Future Research
Published by WISE Pendidikan Indonesia
ISSN : -     EISSN : 30896975     DOI : https://doi.org/10.70211/bafr
Core Subject : Science,
Computer Science & IT
Blockchain, Artificial Intelligence, and Future Research (BAFR) is a peer-reviewed journal dedicated to publishing high-quality research in blockchain technology, artificial intelligence (AI), and emerging trends in future digital innovations. BAFR welcomes diverse contributions, such as theoretical analyses, empirical studies, case studies, experiments, and conceptual model developments, to foster academic discourse and technological advancements. All articles are freely accessible online, ensuring open access without subscription barriers to support global knowledge dissemination.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 2 Documents
 1 
Search results for , issue "Vol. 2 No. 1 (2026): May 2026" : 2 Documents clear
AI-Driven Automation and Industrial Peace in Indonesia: Mediation Effects of Employability and Organizational Support Athiyyah Riri Syahfitri; Zdzislaw Polkowski; Majid A. Nawaz; Abu Taha Zamani
Blockchain, Artificial Intelligence, and Future Research Vol. 2 No. 1 (2026): May 2026
Publisher : WISE Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70211/bafr.v2i1.214

Abstract

This study explores the impact of AI-driven automation on job insecurity and industrial peace in Indonesia, emphasizing the mediating roles of employability and perceived organizational support (POS). As technological advancements reshape industries, employees face heightened uncertainties regarding their job security, which can undermine workplace harmony. This research utilizes a quantitative approach with data collected from 1,072 employees across various sectors in Indonesia, employing Structural Equation Modeling (SEM) to analyze the relationships among the key constructs. The findings reveal that AI-driven automation significantly increases job insecurity, which in turn negatively affects industrial peace. However, employability and POS serve as important mediators in these relationships, reducing the adverse effects of job insecurity and enhancing industrial peace. These results underscore the importance of reskilling initiatives and organizational support in maintaining a harmonious work environment during technological transitions. The study provides valuable insights for organizations navigating automation challenges and contributes to the broader literature on industrial relations and human resource management in the context of emerging technologies.
Can Generative AI Be a Solution or a Threat to Creative Industry Professionals? Assessing Readiness with the Rasch Model Rizal Furqan Ramadhan; Sultan Ahmad; Nafae Mohnna Alanazi; Korhan Cengiz
Blockchain, Artificial Intelligence, and Future Research Vol. 2 No. 1 (2026): May 2026
Publisher : WISE Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70211/bafr.v2i1.410

Abstract

This study examines the readiness of creative industry professionals, specifically in photography and filmmaking, to adopt Generative AI (GenAI) technologies, utilizing the Rasch Model to assess their perceptions, technological self-efficacy, and concerns about job displacement and ethical implications. A survey was conducted with 2,424 professionals across different continents, revealing that younger professionals and those from technologically advanced regions are more ready to adopt GenAI, while older professionals show greater resistance due to concerns about creative control and job security. The study found significant differences in readiness across job roles, with photographers more willing to embrace AI for routine tasks, while filmmakers and editors expressed more hesitations regarding the ethical and creative challenges posed by AI. The research contributes to the literature by offering a psychometrically rigorous assessment of readiness for GenAI adoption, introducing Differential Item Functioning (DIF) analysis to explore demographic variations, and providing practical recommendations for the creative industries on how to manage the integration of AI technologies. The findings emphasize the importance of tailored interventions, organizational support, and reskilling initiatives to successfully integrate AI into creative workflows while preserving human creativity.

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