The Effect of Artificial Intelligence Adoption, Demand Prediction, and Production Planning on Operational Efficiency in the Textile Industry in Jakarta

Authors

  • Loso Judijanto IPOSS Jakarta, Indonesia
  • Khamaludin Khamaludin Universitas Islam Syekh-Yusuf
  • Mahmudin Mahmudin Universitas Islam Syekh-Yusuf
  • Devi Susiati Universitas 45 Surabaya
  • Hanifah Nurul Muthmainah Universitas Siber Muhammadiyah

DOI:

https://doi.org/10.58812/wsis.v2i02.669

Keywords:

Artificial Intelligence Adoption, Demand Prediction, Production Planning, Operational Efficiency, Textile Industry in Jakarta

Abstract

This research investigates the impact of Artificial Intelligence (AI) adoption, demand prediction, and production planning on operational efficiency within the textile industry in Jakarta. A quantitative approach, employing surveys and statistical analysis, was undertaken with a diverse sample of 150 participants representing various company sizes and industry tenures. The study reveals a moderate level of AI adoption, with machine learning algorithms and predictive analytics being prevalent. While perceived benefits include improved production efficiency and enhanced quality control, challenges such as initial investment costs and the need for skilled personnel underscore the nuanced landscape of AI integration. The effectiveness of demand prediction is moderate, with traditional methods prevailing but advanced analytics demonstrating higher efficacy. Production planning strategies exhibit a positive correlation with Industry 4.0 principles, showcasing their role in enhancing operational efficiency. Participants perceive operational efficiency positively, with significant correlations identified between AI adoption, demand prediction, production planning, and perceived efficiency. Key factors contributing to operational efficiency include streamlined processes, effective resource utilization, and adaptive production planning. The findings provide actionable insights for industry stakeholders, emphasizing the importance of a holistic approach to technology adoption and strategic planning.

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Published

2024-02-26

How to Cite

Judijanto, L., Khamaludin, K., Mahmudin, M., Susiati, D., & Muthmainah , H. N. (2024). The Effect of Artificial Intelligence Adoption, Demand Prediction, and Production Planning on Operational Efficiency in the Textile Industry in Jakarta. West Science Interdisciplinary Studies, 2(02), 415–422. https://doi.org/10.58812/wsis.v2i02.669

Issue

Vol. 2 No. 02 (2024): West Science Interdisciplinary Studies

Section

Articles

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Copyright (c) 2024 Loso Judijanto, Khamaludin Khamaludin, Mahmudin Mahmudin, Devi Susiati, Hanifah Nurul Muthmainah

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