Analysis of Mango Leaf Condition Using the C-Means Method Based on Streaming Data - Sinaga, Cinthya Agatha; Nainggolan, Herlina Br; Hasugian, Paska Marto (Sean Institute, 2025)
Efficiency in the agricultural sector is often hampered by conventional and manual plant identification processes. This study implements an automatic mango leaf condition evaluation system capable of live data acquisition, contour-based autocropping, and classification using the C-Means algorithm in a data streaming environment. The system extracts key features such as color (RGB), saturation, and contrast. Numerical data is normalized using Z-Score transformation before being grouped into three categories: Fresh, Sick, and Dry. The results show that the system is able to effectively distinguish biological conditions through automatic mapping. This research provides a responsive solution for real-time plant health monitoring.