Arif Nur Afandi
Papers
3
Total Citations
17
H-Index
3
About
Arif Nur Afandi is a researcher whose work bridges intelligent robotics and smart city infrastructure, with a focus on applying computational intelligence to real-world systems. His key research areas include reinforcement learning for autonomous navigation and the Internet of Things (IoT) for urban development. One of his most notable contributions is the exploration of Genetic Network Programming combined with two-stage reinforcement learning to improve mobile robot navigation in unfamiliar environments, a study that has garnered 8 citations for its novel approach to adaptive decision-making. Afandi has also made significant strides in smart city design, particularly through his work on a Banyumas Smart City framework that leverages IoT and fog computing architecture to enhance urban services like traffic light control. This project, cited 6 times, demonstrates his commitment to practical, community-oriented technology. With a growing body of work that merges theoretical innovation with applied engineering, Afandi is establishing himself as a thoughtful contributor to the fields of autonomous systems and smart infrastructure, offering valuable insights for students and researchers interested in the intersection of machine learning and IoT.
Research Focus
Key Achievements
Top Papers
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