Visi Robotika Berbasis Sosial: Memanfaatkan Data Komputer dan Media Sosial untuk Robotika Industri Adaptif
Year: 2025
Type: article
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 through 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.
Source: Jurnal Ilmiah Sistem Informasi
DOI: 10.51903/pt4vff36
Institution: Muria Kudus University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4410966681