Analysis of Mango Leaf Condition Using the C-Means Method Based on Streaming Data

Cinthya Agatha Sinaga; Herlina Br Nainggolan; Paska Marto Hasugian

Authors

Cinthya Agatha Sinaga Program Studi Sains Data, Fakultas Ilmu Komputer, UNIKA Santo Thomas
Herlina Br Nainggolan Program Studi Sains Data, Fakultas Ilmu Komputer, UNIKA Santo Thomas
Paska Marto Hasugian Program Studi Sains Data, Fakultas Ilmu Komputer, UNIKA Santo Thomas

Keywords:

C-Means, Data Streaming, Leaf Condition Evaluation, Computer Vision, Mango Leaves

Abstract

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.

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