Application of Random Forest for Rice Plant Disease Classification
DOI:
https://doi.org/10.55927/ijis.v4i1.13477Keywords:
Rice Leaf Disease, Random Forest, Machine Learning, Disease Lassification, Agricultural ProductivityAbstract
Indonesia's agricultural sector faces significant challenges in maintaining rice production due to land conversion, pest attacks, and poor irrigation. Early detection of rice leaf diseases is critical to mitigating these challenges. This study applies the Random Forest (RF) algorithm to classify three rice leaf diseases: Bacterial Leaf Blight, Brown Spot, and Leaf Smut. The proposed method achieved an accuracy of 75%, demonstrating its effectiveness in disease detection. This research provides a foundation for integrating machine learning to improve crop management and agricultural productivity
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Copyright (c) 2025 Perani Rosyani, Anang Muhamad Lutfi, Eko Purwadi, Kamaluddin, Yusuf Ali Hanaan, Ines Heidiani Ikasari
This work is licensed under a Creative Commons Attribution 4.0 International License.
