MEASURING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT EFFICIENCY AND PRODUCTION OUTPUT INCREASE: A STATISTICAL ANALYSIS OF BATIK SMES IN THE TANGERANG REGION: A Statistical Analysis of Batik Smes in The Tangerang Region

Ani Ratnasari; Mardiyana; Rika Nurhidayah

doi:10.33474/jimmu.v10i2.24257

Authors

Ani Ratnasari Universitas Tangerang Raya
Mardiyana Universitas Tangerang Raya, Indonesia
Rika Nurhidayah Universitas Tangerang Raya, Indonesia

DOI:

https://doi.org/10.33474/jimmu.v10i2.24257

Keywords:

Artificial Intelligence, Efficiency, Production Output, HRM

Abstract

Abstract

The integration of Artificial Intelligence (AI) in small and medium enterprises (SMEs) is a transformative leap in modern business operations, with significant potential for traditional industries like batik manufacturing. Traditional batik SMEs face challenges in optimizing production efficiency and human resource management. This research is the first to comprehensively analyze the indirect effects of AI implementation on production output through HR management efficiency mediation in batik SMEs. It fills a crucial gap in understanding how AI technologies specifically benefit traditional craft industries through improved human resource utilization. A quantitative explanatory design was employed involving 47 batik SMEs in Tangerang using census sampling. Data collection utilized structured questionnaires with 5-point Likert scales measuring AI Implementation (8 indicators), HR Management Efficiency (9 indicators), and Production Output (7 indicators). Analysis was conducted using Structural Equation Modeling with Partial Least Squares (PLS-SEM) through SmartPLS 4.0. Results demonstrate that AI implementation significantly enhances HR management efficiency, which subsequently improves production output. The mediation analysis reveals that HR management efficiency serves as a crucial intermediary mechanism through which AI technologies influence production performance in batik SMEs. The research findings on the indirect enhancement of production output through improved HR management efficiency in batik SMEs due to AI implementation are significant. This mediation relationship suggests that successful AI adoption requires strategic focus on human resource optimization to maximize production benefits, offering valuable insights for the future of AI in traditional SME modernization strategies. This research bridges a critical gap by demonstrating that AI's impact on traditional SMEs operates through HR management efficiency rather than direct technological effects. It extends technology-adoption theory by establishing human capital optimization as the key mediating mechanism in labor-intensive craft industries. This research contributes valuable insights on inclusive digitalization in heritage industries, showing AI enhances rather than replaces human resources.

References

AL Daradkeh, H., & AL-Zoubi, K. Y. (2024). The Impact Of Artificial Intelligence On Improving Human Resources Competencies In The King Hussein Business Park. Educational Administration: Theory and Practice, 30(5), 8755–8761. https://doi.org/10.53555/kuey.v30i5.4458

Alshahrani, S. T., Choukir, J., Albelali, S., & AlShalhoob, A. A. (2025). Perceptions of the Impact of AI on Human Resource Management Practices Among Human Resource Managers Working in the Chemical Industry in Saudi Arabia. Sustainability (Switzerland), 17(13). https://doi.org/10.3390/su17135815

Anastasya, P. Y. (2025). Effective Strategies in Human Resource Management to Improve Productivity. Digital Innovation : International Journal of Management, 2(2), 58–66. https://doi.org/10.61132/digitalinnovation.v2i2.229

Anh, N. T. (2025). SUSTAINABLE STARTUP AND INNOVATION. 1(2), 1–10.

Bação, P., Gaudêncio Lopes, V., & Simões, M. (2023). AI, Demand and the Impact of Productivity-enhancing Technology on Jobs: Evidence from Portugal. In Eastern European Economics (Vol. 61, Issue 4). https://doi.org/10.1080/00128775.2022.2064307

Benabou, A., & Touhami, F. (2025). Empowering human resource management through artificial intelligence: a systematic literature review and bibliometric analysis. International Journal of Production Management and Engineering, 13(1), 59–76. https://doi.org/10.4995/ijpme.2025.21900

Blaga, P., & Jozsef, B. (2024). Increasing Human Resource Efficiency in the Production Process. Procedia Technology, 12, 469–475. https://doi.org/10.1016/j.protcy.2013.12.516

Czarnitzki, D., Fernández, G. P., & Rammer, C. (2023). Artificial intelligence and firm-level productivity. Journal of Economic Behavior and Organization, 211, 188–205. https://doi.org/10.1016/j.jebo.2023.05.008

Ekram Yawar, M., & Qurban Hakimi, M. (2025). The Impact of Artificial Intelligence Technology on Human Resources Performance in Organizations. EuroGlobal Journal of Linguistics and Language Education, 2(1), 96–108. https://doi.org/10.69760/egjlle.2500013

Eloh, B., Arthawati, S. N., & Andaristi, F. (2024). THE ROLE OF HUMAN RESOURCE MANAGEMENT IN INCREASING PRODUCTIVITY Eloh. International Journal of Society Reviews (INJOSER), 2(February), 4–6.

Feng, Z., & Ahn, J. (2024). the Impact of Artificial Intelligence on Human Resource Management Processes. Journal of Theoretical and Applied Information Technology, 102(23), 8513–8529.

Filippucci, F., Gal, P., Jona-Lasinio, C., Leandro, A., Nicoletti, G., Ramirez Bulos, C., Dougherty, S., Marcolin, L., Vitale, C., Turban, S., Betin, M., Paula Caldas, M., & Hanspach, P. (2024). The impact of Artificial Intelligence on productivity, distribution and growth: Key mechanisms, initial evidence and policy challenges. OECD Publishing, 1, 64. www.oecd.org/termsandconditions

Gao, X., & Feng, H. (2023). AI-Driven Productivity Gains: Artificial Intelligence and Firm Productivity. Sustainability (Switzerland), 15(11). https://doi.org/10.3390/su15118934

Kassa, B. Y., & Worku, E. K. (2025). The impact of artificial intelligence on organizational performance: The mediating role of employee productivity. Journal of Open Innovation: Technology, Market, and Complexity, 11(1), 100474. https://doi.org/10.1016/j.joitmc.2025.100474

Khan, M. I., Parahyanti, E., & Hussain, S. (2024). The Role Generative AI in Human Resource Management: Enhancing Operational Efficiency, Decision-Making, and Addressing Ethical Challenges. Asian Journal of Logistics Management, 3(2), 104–125. https://doi.org/10.14710/ajlm.2024.24671

Liu, J., Jiang, X., Shi, M., & Yang, Y. (2024). Impact of Artificial Intelligence on Manufacturing Industry Global Value Chain Position. Sustainability (Switzerland), 16(3), 1–17. https://doi.org/10.3390/su16031341

Lodhi, S. K., Gill, A. Y., & Hussain, I. (2024). AI-Powered Innovations in Contemporary Manufacturing Procedures: An Extensive Analysis. International Journal of Multidisciplinary Sciences and Arts, 3(4), 15–25. https://doi.org/10.47709/ijmdsa.v3i4.4616

Luo, Y., Yang, Z., Ren, Y., Škare, M., & Qin, Y. (2024). Evaluating the Impact of AI Research on Industry Productivity: A Dynamic Qualitative Comparative Analysis Approach. Journal of Competitiveness, 16(3), 187–203. https://doi.org/10.7441/joc.2024.03.09

Murugesan, U., Subramanian, P., Srivastava, S., & Dwivedi, A. (2023). A study of Artificial Intelligence impacts on Human Resource Digitalization in Industry 4.0. Decision Analytics Journal, 7(May), 100249. https://doi.org/10.1016/j.dajour.2023.100249

Natsir, I., Ode, H., Irfana, T. B., Pulungan, D. R., & Sihite, M. (2024). An Analysis of the Role of Human Resource Management in Enhancing Organizational Efficiency and Effectiveness. International Journal of Economics (IJEC), 3(2), 1089–1097. https://doi.org/10.55299/ijec.v3i2.1097

Ncube, T. R., Sishi, K. K., & Skinner, J. P. (2025). The impact of artificial intelligence on human resource management practices: An investigation. SA Journal of Human Resource Management, 23(June), 0–11. https://doi.org/10.4102/sajhrm.v23i0.2960

Necula, S. C., Fotache, D., & Rieder, E. (2024). Assessing the Impact of Artificial Intelligence Tools on Employee Productivity: Insights from a Comprehensive Survey Analysis. Electronics (Switzerland), 13(18). https://doi.org/10.3390/electronics13183758

Okolie, U. C., & Egbon, T. N. (2023). Effectiveness and Difficulties of Artificial Intelligence Application in Human Resource Management. Jurnal Transparansi Publik (JTP), 3(2), 53–59. https://ojs.unimal.ac.id/index.php/jtp/article/view/13506

Puri, V. (2024). Measuring the Impact of AI Initiatives on Organizational Productivity: Best Practices and Tips. International Research Journal of Engineering and Technology, August. www.irjet.net

Widodo, S. T., & Poltak Sinambela, L. (2025). Transformation of Human Resource Management to Increase Work Process Efficiency at Indonesian Quarantine Agency (A Study on The Implementation of Lean Management in Human Resource Management). International Journal of Management Science and Information Technology, 5(1), 11–19. https://doi.org/10.35870/ijmsit.v5i1.3618

Wishah, R. H., Zakzouk, F., Rawashdeh, L., & Ahmed, E. (2025). Utilizing Artificial Intelligence to Enhance Employee Experience and Improve Human Resource Management Efficiency: A Performance Analysis of Companies. Journal of Ecohumanism, 4(1), 5355–5379. https://doi.org/10.62754/joe.v4i1.6469