Deni Tri Laksono

Papers

Total Citations

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About

Deni Tri Laksono is an emerging researcher whose work sits at the intersection of marine biology, artificial intelligence, and robotics. His primary research focus is the application of machine learning and computer vision to solve pressing problems in aquaculture and marine resource management. His most cited work, "Analysis of Ice-Ice Disease on Seaweed Using the K-Nearest Neighbor Algorithm in Vision Robot Technology," introduces a novel, automated approach to detecting a devastating disease in seaweed crops. By integrating a K-Nearest Neighbor (KNN) algorithm into vision-equipped robotic systems, Laksono’s research moves beyond traditional, imprecise manual inspection methods. This contribution offers a scalable, data-driven solution for real-time monitoring of seaweed health, directly addressing a critical bottleneck in the sustainable cultivation of this economically vital resource. While his citation count is currently modest—a reflection of his early-career stage—the practical implications of his work for precision aquaculture are significant. Laksono’s research represents a promising step toward the fusion of intelligent robotics and environmental stewardship, marking him as a researcher to watch in the field of applied AI for agriculture.