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All Journal Jurnal Multidisiplin West Science West Science Interdisciplinary Studies West Science Nature and Technology
Khamaludin Khamaludin
Universitas Islam Syekh-Yusuf
Humanities Economics, Econometrics & Finance Energy Social Sciences

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Journal : West Science Interdisciplinary Studies

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The Effect of Artificial Intelligence Adoption, Demand Prediction, and Production Planning on Operational Efficiency in the Textile Industry in Jakarta Loso Judijanto; Khamaludin Khamaludin; Mahmudin Mahmudin; Devi Susiati; Hanifah Nurul Muthmainah
West Science Interdisciplinary Studies Vol. 2 No. 02 (2024): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v2i02.669

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.
The Role of IoT in Improving the Efficiency and Quality of Automated Production in Industry 4.0: A Bibliometric Review Loso Judijanto; Etika Purnamasari; Ade Suhara; Nanny Mayasari; Khamaludin Khamaludin
West Science Interdisciplinary Studies Vol. 2 No. 10 (2024): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v2i10.1341

Abstract

This bibliometric review explores the dynamic field of talent management, focusing on the integration of digital technologies and their impact on modern organizational practices. Using VOSviewer for a systematic analysis, the study maps the evolution of key themes and trends over recent years, highlighting the central role of talent management and the significant shift towards incorporating advanced technologies like IoT, data analytics, and machine learning. The findings reveal a transformation from traditional practices to a more strategic, data-driven approach that aligns talent management with competitive business objectives. This transition not only enhances operational efficiencies but also supports a culture of continuous improvement and innovation. The study also addresses the challenges and future directions in leveraging technology for effective talent management, providing insights that are crucial for organizations aiming to maintain a competitive edge in a rapidly evolving digital landscape.
Co-Authors Ade Suhara Devi Susiati Erlin Dolphina Hanifah Nurul Muthmainah Loso Judijanto Mahmudin Mahmudin Nanny Mayasari Purnamasari, Etika Sudarmanto, Eko Tirangga Ansori Vina Karina Putri