Systematic Literature Review : Machine Learning and Deep Learning Aproaches for Crop Yield Prediction Using Remote Sensing Data

Muhammad Fikri Haikal (Faculty of Computer Science, Universitas Jember)
Muhammad Ariful Furqon

Media Informatika
Vol 25 No 2 (2026)

Accurate crop yield prediction is essential for improving agricultural productivity and food security. This study presents a Systematic Literature Review (SLR) on machine learning and deep learning approaches for crop yield prediction using remote sensing data. Following PRISMA guidelines, 20 high-quality studies published between 2015 and 2025 were analyzed. The results highlight the growing dominance of deep and hybrid models, particularly when multi-source remote sensing data and phenological information are integrated.