Classification of Pneumonia Medical Images with Convolutional Neural Networks
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
Authors
- Ines Heidiani Ikasari (ORCID: https://orcid.org/0000-0002-8463-6318)
- Perani Rosyani (ORCID: https://orcid.org/0000-0002-4032-0901)
- Randy Erfa Saputra (ORCID: https://orcid.org/0000-0002-8537-2086)
- Sendy Prasdio
- Muhammad Faisal Kurniagis
- Zainul Janariandana
Institutions
- Universitas Pamulang (ID)
Publication Details
- Journal
- International Journal of Integrative Sciences
- Published
- 2025-02-12
- DOI
- https://doi.org/10.55927/ijis.v4i1.13511
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00