Peran Artificial Intelligence dalam Mendukung Inovasi Bisnis Digital Generasi Z di Jakarta Barat
Keywords:
Kecerdasan Buatan, Inovasi Bisnis Digital, Generasi ZAbstract
Penelitian ini bertujuan menganalisis faktor-faktor yang memengaruhi niat adopsi kecerdasan buatan (AI) untuk inovasi bisnis di kalangan pengusaha Generasi Z di Jakarta Barat. Berlandaskan Technology Acceptance Model (TAM), penelitian kuantitatif ini menggunakan data survei dari 100 responden yang dianalisis dengan regresi linear berganda. Hasil penelitian menunjukkan bahwa persepsi kegunaan (perceived usefulness) dan persepsi kemudahan penggunaan (perceived ease of use) secara simultan maupun parsial berpengaruh positif dan signifikan terhadap niat perilaku untuk mengadopsi AI. Model ini mampu menjelaskan 63,5% varian niat adopsi.
References
Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). SAGE Publications.
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems (Doctoral dissertation, Massachusetts Institute of Technology, Sloan School of Management).
Goforth, C. (2015, November 16). Using and interpreting Cronbach's alpha. University of Virginia Library. https://library.virginia.edu/data/articles/using-and-interpreting-cronbachs-alpha
Institute for Digital Research and Education. (2024). Regression analysis: SPSS annotated output. UCLA: Statistical Methods and Data Analytics. Retrieved from https://stats.oarc.ucla.edu/spss/output/regression-analysis/
Meiryani, M., Tandyopranoto, C. D., Emanuel, J., Lindawati, A. S. L., Fahlevi, M., Aljuaid, M., & Hasan, F. (2022). The effect of global price movements on the energy sector commodity on bitcoin price movement during the COVID-19 pandemic. Heliyon, 8(10), e10820. https://doi.org/10.1016/j.heliyon.2022.e10820
Sastroasmoro, S., & Ismael, S. (2014). Dasar-dasar metodologi penelitian klinis. Sagung Seto.
Sirse, S., Khanzode, S., & Bhide, A. (2023). ERP: SAP S/4HANA Cloud RISE Enterprise Solution Automation with Artificial Intelligence Features. International Journal for Research in Applied Science and Engineering Technology.
Song, Y., Qiu, X., & Liu, J. (2025). The Impact of Artificial Intelligence Adoption on Organizational Decision-Making: An Empirical Study Based on the Technology Acceptance Model in Business Management. Systems, 13(8), 683. https://doi.org/10.3390/systems13080683
The Ohio State University, College of Education and Human Ecology, Quantitative Methodology Center. (2024). Basic research design. Retrieved from https://u.osu.edu/qmc/basic-research-design/
Ursavaş, Ö. F., Yalçın, Y., İslamoğlu, H., Bakır-Yalçın, E., & Cukurova, M. (2025). Rethinking the importance of social norms in generative AI adoption: investigating the acceptance and use of generative AI among higher education students. International Journal of Educational Technology in Higher Education, 22(38)
Vagias, W. M. (2006). Likert-type scale response anchors. Clemson International Institute for Tourism & Research Development, Department of Parks, Recreation and Tourism Management, Clemson University.
Vanessa, V. (2025). Customer value and its impact on purchase decisions in online shopping. Husnayain Business Review, 5(1), 13–20.
Wang, C., Ahmad, S. F., Ayassrah, A. Y. A. B. A., Awwad, E. M., Irshad, M., Ali, Y. A., Al-Razgan, M., Khan, Y., & Han, H. (2023). RETRACTED: An empirical evaluation of technology acceptance model for Artificial Intelligence in E-commerce. Heliyon, 9(8), e18349. https://doi.org/10.1016/j.heliyon.2023.e18349
Wicaksono, S. R. (2022). Teori Dasar Technology Acceptance Model. CV Seribu Bintang
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