Dini Handayani

International Islamic University Malaysia

Papers

Total Citations

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About

Dini Handayani is a researcher at the forefront of applied artificial intelligence, with a focus on computer vision, deep learning, and the Internet of Things (IoT). Her work is driven by the goal of creating intelligent, efficient systems that solve real-world problems in retail and education. Handayani’s most notable contribution is the development of LSR-YOLO, a lightweight and fast object detection model specifically designed for retail product identification. This innovation addresses the critical challenge of high computational cost in deep learning, making advanced computer vision practical for integration into smart city and retail environments. Her research in this area has already garnered significant early attention, with 6 citations for her 2025 paper. In parallel, Handayani has explored the intersection of IoT and facial recognition, creating the CObot system for smart classroom attendance. This work tackles the pervasive issue of attendance fraud, proposing a secure, automated solution with both educational and entrepreneurial potential. By combining rigorous technical development with a clear focus on societal impact, Dini Handayani is establishing herself as a promising voice in the push toward smarter, more secure urban and educational systems.