SYSTEMATIC LITERATURE REVIEW IOT UNTUK PERTANIAN PRESISI DAN KESEHATAN TANAH - Sirotujanah, Retno Sari; Aros , Desfi Silvia; Prasetyo, Tri Ferga (SEMINAR TEKNOLOGI MAJALENGKA (STIMA), 2025)
The utilization of Internet of Things (IoT) and Artificial Intelligence (AI) technologies in agriculture has advanced significantly; however, challenges related to the adoption of these technologies remain substantial, particularly concerning the implementation of efficient precision irrigation systems. This study aims to address the issues of low water-use efficiency in traditional irrigation systems and the limited early detection of crop diseases, an area not fully exploited by current technologies. Using a Systematic Literature Review (SLR) approach, this research identifies IoT and AI-based solutions to enhance agricultural productivity with an emphasis on more efficient and environmentally sustainable resource management. The SLR methodology employed follows the PRISMA guidelines, encompassing stages of identification, screening, and eligibility assessment of 1,248 relevant articles, which were subsequently narrowed down to 43 articles that met the inclusion criteria. The analysis reveals that the integration of IoT and AI can significantly improve precision irrigation efficiency and early disease detection, ultimately leading to reductions in water usage and pesticide application, while enhancing agricultural yield sustainability. The study concludes that while these technologies offer substantial solutions to key challenges in agriculture, successful implementation will require supportive policies and adequate training for farmers to fully harness these advancements.