Classification of Pneumonia Medical Images with Convolutional Neural Networks - Ines Heidiani Ikasari; Saputra, Riski Yoga; Prasdio, Sendy; Kurniagis, Muhammad Faisal; Rosyani, Perani; Janariandana, Zainul (International Journal of Integrative Sciences, 2025)
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