UTILIZATION OF AI-BASED DRONES FOR PLANT DISEASE IDENTIFICATION AND IMPROVING PRODUCTION EFFICIENCY OF PALM OIL FARMERS Pemanfaatan Drone Berbasis AI untuk Identifikasi Penyakit Tanaman dan Peningkatan Efisiensi Produksi Petani Sawit Section Articles

Abstract

This study aims to analyze the use of artificial intelligence (AI)-based drones for rapid, accurate, and efficient identification of oil palm diseases and to evaluate their impact on improving smallholder productivity. The research employed multispectral drone imaging, image feature extraction using deep learning algorithms, and field validation to verify the detection results. The collected data were assessed to measure the accuracy of disease identification and the overall effectiveness of the monitoring process. The findings indicate that the AI-based detection system can identify disease symptoms with an accuracy of 89– 94% and reduce inspection time by up to 60% compared to conventional manual methods. This technology also improves decision-making accuracy in disease management, which contributes to cost efficiency and higher crop yield. The study concludes that integrating drones and AI represents a significant innovation in modern oil palm plantation management. The implications of these findings highlight the need for broader adoption of digital technologies in agriculture to support production sustainability and enhance farmers’competitiveness.
Keywords: Deep Learning, Plant Disease Detection, Drone, Production Efficiency, Artificial
Intelligence