AI-Powered Service Quality Management for Next-Generation Industrial IoT in Indonesia

Authors

  • Loso Judijanto IPOSS Jakarta, Indonesia
  • Jadiaman Parhusip Universitas Palangka Raya
  • Moh Gifari Sono Universitas Muhammadiyah Luwuk

DOI:

https://doi.org/10.58812/j0q44416

Keywords:

AI-powered service quality, Industrial Internet of Things (IIoT), qualitative analysis, Indonesia, NVIVO

Abstract

This study explores the integration of AI-powered service quality management in next-generation Industrial Internet of Things (IIoT) environments in Indonesia using a qualitative research approach. Drawing insights from five informants across diverse industries, the study investigates perceptions, challenges, organizational readiness, and the impact of AI technologies. Findings reveal that AI significantly enhances service quality through real-time monitoring, predictive analytics, and automation, leading to improved operational efficiency and customer satisfaction. However, challenges such as inadequate infrastructure, skill gaps, and data privacy concerns hinder widespread adoption, especially for small and medium enterprises (SMEs). The study emphasizes the importance of digital infrastructure development, workforce upskilling, and robust data security frameworks to fully realize the benefits of AI in IIoT environments. These findings contribute valuable insights for policymakers, industry practitioners, and researchers, providing a foundation for addressing contextual challenges and optimizing AI-driven service quality management in Indonesia.

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Published

2025-03-28

Issue

Vol. 3 No. 01 (2025): West Science Nature and Technology

Section

Articles

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Copyright (c) 2025 Loso Judijanto, Jadiaman Parhusip, Moh Gifari Sono

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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

How to Cite

AI-Powered Service Quality Management for Next-Generation Industrial IoT in Indonesia (L. Judijanto, J. . Parhusip, & M. G. . Sono , Trans.). (2025). West Science Nature and Technology, 3(01), 1-6. https://doi.org/10.58812/j0q44416