Smart Farming Technologies for Indonesia Agriculture Productivity and Sustainability - Muhamad Ivan Fadilah; Khalisha Alifia Zahra (Penerbit Goodwood, 2026)
Purpose: To systematically map and review the landscape of smart farming technology in Indonesia, focusing specifically on its impact on the productivity and sustainability of the agricultural sector. Methodology/approach: This research utilizes a Systematic Literature Review (SLR) guided by the PRISMA protocol. A qualitative thematic synthesis was performed on 10 selected articles published between 2021-2025, which were sourced from the IEEE Xplore, ScienceDirect, and Emerald Insight databases. Results: The analysis shows that the Internet of Things (IoT), sensors, Big Data, and Machine Learning are the most predominantly applied technologies. Their implementation yields significant positive impacts, including enhanced plant growth (up to 26.3% taller) and more efficient resource use, such as a 4.75% savings in electrical energy. Conclusions: The strategic integration of smart farming offers great potential for revitalizing the Indonesian agriculture sector. However, its success is highly dependent on overcoming major challenges, such as high investment costs, a rural digital infrastructure gap, and low digital literacy among farmers. Limitations: This review is based on a limited set of 10 final articles, which, while relevant, may not encompass the full spectrum of smart farming applications and unpublished case studies in Indonesia. Contributions: This study provides an evidence-based foundation for Indonesian policymakers to formulate targeted policies that address economic and infrastructure barriers. It also guides researchers and practitioners in developing more affordable and locally relevant technological solutions to accelerate the digital transformation in the agricultural sector.