Herlin Setyawan
Papers
3
Total Citations
14
H-Index
2
About
Herlin Setyawan is a forward-thinking researcher at the intersection of artificial intelligence, sustainable technology, and vocational education. His work primarily focuses on applying deep learning to environmental challenges and enhancing technical education through robotics. In his highly cited 2024 study, "Deep Learning-Based Waste Classification with Transfer Learning Using EfficientNet-B0 Model," Setyawan tackled a critical gap in modern waste management, demonstrating how AI can overcome the limitations of conventional sensor-based recycling methods—a contribution that has already garnered 10 citations. Beyond environmental AI, Setyawan is deeply invested in the future of learning. His systematic literature review on "The Impact of Robotic Technology in Vocational Education towards the Development of Industry 5.0" explores how to align educational models with the demands of the next industrial revolution. Complementing this, his work on a "Mobile Robotics Training Kit" provides a tangible solution for improving practical and problem-solving skills among industrial electrical engineering students. Through these efforts, Setyawan is not only advancing smart waste management but also shaping a more competent, hands-on workforce ready for Industry 5.0.
Research Focus
Key Achievements
Top Papers
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