Mujiarto Mujiarto
Papers
2
Total Citations
37
H-Index
2
About
Mujiarto Mujiarto is a researcher whose work sits at the intersection of robotics, intelligent control systems, and educational technology. His primary research areas include adaptive neuro-fuzzy inference systems (ANFIS), microcontroller-based robotics, and image processing for object detection. His most cited paper, "Colored object detection using 5 dof robot arm based adaptive neuro-fuzzy method" (2019, 26 citations), presents a novel application of ANFIS on an Arduino microcontroller to control a 5-DOF robot arm, using MATLAB for real-time color-based object detection. This work demonstrates a practical fusion of fuzzy logic and neural networks for dynamic robotic control. Beyond technical contributions, Mujiarto is also dedicated to STEM education. His paper on Android-based robotics training for junior high school students (11 citations) highlights his commitment to fostering innovation and creativity through accessible, hands-on robotics workshops. By integrating Proteus simulations with Arduino hardware and Android control, he creates a bridge between theoretical simulation and tangible robotic systems. Mujiarto’s work is notable for its dual impact: advancing adaptive control methodologies while simultaneously democratizing robotics education for young learners.
Research Focus
Key Achievements
Top Papers
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