Vision of Social-Based Robotics: Leveraging Computer Data and Social Media for Adaptive Industrial Robotics

Authors

  • Adjie Bangsawan Universitas Muria Kudus, Jawa Tengah, Indonesia
  • Ahmad Farid Universitas Muria Kudus, Jawa Tengah, Indonesia
  • Maulana Wijayanto Universitas Muria Kudus, Jawa Tengah, Indonesia
  • Nabilla Mutiara Tsani Universitas Muria Kudus, Jawa Tengah, Indonesia
  • Yuniar Satrio Wibowo Universitas Muria Kudus, Jawa Tengah, Indonesia

DOI:

https://doi.org/10.51903/pt4vff36

Keywords:

Adaptive Robotics, Machine Learning, Human-Robot Interaction

Abstract

The rapid evolution of industrial robotics has been significantly influenced by the integration of computational data and social media, enabling robots to become more adaptive and responsive in collaborative work environments. This study investigates the role of social media and computational data in enhancing the adaptability of industrial robotics by applying machine learning techniques. By integrating sentiment analysis from social media with sensor data from industrial robots, this study examines how real-time data functions can improve robot decision-making and human-robot collaboration. Experimental results show a 23% increase in operational efficiency, an 89% accuracy rate in social interaction classification, and a 15% reduction in prediction errors. Furthermore, 62% of public sentiment toward adaptive robots is positive, highlighting the growing acceptance despite concerns over the impact of automation on jobs. These findings suggest that leveraging social media and computational data can significantly enhance the adaptability of robots, leading to a more efficient and socially conscious industrial ecosystem.

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Published

2025-05-31

Issue

Vol. 4 No. 2 (2025): Mei : Jurnal Ilmiah Sistem Informasi

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