Analisis Eksploratif Persepsi Risiko dan Regulasi dalam Adopsi AI pada Pelaku Industri Kreatif Batam

Authors

  • Winan Kristin Tambunan Universitas Universal
  • Giovanny Engellika Universitas Universal
  • Ivan Rusliyanto Universitas Universal
  • Mulyono Sutanto Universitas Universal
  • Vina Vina Universitas Universal

DOI:

https://doi.org/10.61132/jumbidter.v3i1.1219

Keywords:

AI Adoption, AI Regulation, Creative Industry, Product Innovation, Risk Perception

Abstract

The rapid development of generative Artificial Intelligence (AI) technology offers significant efficiency opportunities across various sectors; however, empirical research within the local Indonesian context, particularly in Batam City, remains scarce. This exploratory study aims to analyze the influence of positive perception, negative perception, and AI regulation understanding on technology adoption trends, as well as productivity and product innovation opportunities among creative industry players. The creative industry is a focal point due to the inherent tension between technological efficiency and the preservation of human originality in the creative process. This research employs a quantitative causal approach, utilizing a sample of 30 respondents reached through snowball sampling techniques. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS software. The findings reveal that only positive perception has a significant direct impact on product innovation (p=0.004), while AI regulation and technical adoption do not show significant effects. This suggests that a positive technology mindset is a more decisive factor for innovation than technical mastery or current regulatory compliance. These results underscore the urgent need for local government socialization of AI policies and enhanced digital literacy for Batam's creative practitioners to transform them from mere users into strategic AI-driven innovators.

Downloads

Download data is not yet available.

References

Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3). https://doi.org/10.30935/cedtech/13152

Amankwah-Amoah, J., Abdalla, S., Mogaji, E., Elbanna, A., & Dwivedi, Y. K. (2024a). The impending disruption of creative industries by generative AI: Opportunities, challenges, and research agenda. International Journal of Information Management, 79, 102759. https://doi.org/10.1016/j.ijinfomgt.2024.102759

Amankwah-Amoah, J., Abdalla, S., Mogaji, E., Elbanna, A., & Dwivedi, Y. K. (2024b). The impending disruption of creative industries by generative AI: Opportunities, challenges, and research agenda. International Journal of Information Management, 79, 102759. https://doi.org/10.1016/j.ijinfomgt.2024.102759

Brilianty, T., & Alamiyah, S. S. (2019). Persepsi animator terhadap penggunaan generative AI dalam produksi iklan komersial di YouTube. Nusantara: Jurnal Ilmu Pengetahuan Sosial, 1–14.

Ghozali, I. (2011). Aplikasi analisis multivariat dengan program IBM SPSS (PDF).

Grilli, L., & Pedota, M. (2024a). Creativity and artificial intelligence: A multilevel perspective. Creativity and Innovation Management, 33(2), 234–247. https://doi.org/10.1111/caim.12580

Grilli, L., & Pedota, M. (2024b). Creativity and artificial intelligence: A multilevel perspective. Creativity and Innovation Management, 33(2), 234–247. https://doi.org/10.1111/caim.12580

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R. Springer. https://doi.org/10.1007/978-3-030-80519-7

Hanifa, A. S., & F. A. (2023). Peran artificial intelligence terhadap industri kreatif Indonesia. Business Law Binus, 7(2), 33–48. https://doi.org/10.59188/jcs.v2i7.446

Hastuti, J. (2025). Pengaruh fitur TikTok affiliate terhadap perkembangan bisnis digital mahasiswa di Kabupaten Nagan Raya pada era Society 5.0. RIGGS, 4(3). https://doi.org/10.31004/riggs.v4i3.2631

Pinarbasi, F., Sonmez Cakir, F., Güner Gültekin, D., Yazici, M., & Adiguzel, Z. (2023). Examination of the effects of value creation, intellectual property and organizational creativity on artificial intelligence focused enterprises. Business Process Management Journal, 30(1), 317–337. https://doi.org/10.1108/BPMJ-07-2023-0551

Prasetyo, H., & Sutopo, W. (2024). Industry 4.0: Study of aspect classification and research development direction. Industrial Engineering Journal, 13(1), 17.

Ringle, C. M., da Silva, D., & Bido, D. D. S. (2014). Modelagem de equações estruturais com utilização do SmartPLS. Revista Brasileira de Marketing, 13(2), 56–73. https://doi.org/10.5585/remark.v13i2.2717

Sekaran, U., & Bougie, R. (2013). Research methods for business: A skill-building approach (6th ed.). Wiley. https://doi.org/10.1108/LODJ-06-2013-0079

Subhaktiyasa, P. G. (2024). Menentukan populasi dan sampel: Pendekatan metodologi penelitian kuantitatif dan kualitatif. Jurnal Ilmiah Profesi Pendidikan, 9(4), 2721–2731. https://doi.org/10.29303/jipp.v9i4.2657

Sugiyono. (2019). Metodologi penelitian kuantitatif, kualitatif, dan R&D. Alfabeta.

Tigre Moura, F., Castrucci, C., & Hindley, C. (2023). Artificial intelligence creates art? An experimental investigation of value and creativity perceptions. Journal of Creative Behavior, 57(4), 534–549. https://doi.org/10.1002/jocb.600

Wilczek, B., Thäsler-Kordonouri, S., & Eder, M. (2025). Government regulation or industry self-regulation of AI? Investigating the relationships between uncertainty avoidance, people’s AI risk perceptions, and their regulatory preferences in Europe. AI & Society, 40(5), 3797–3811. https://doi.org/10.1007/s00146-024-02138-0

Downloads

Published

2026-01-27