Jurnal Ilmiah Pertanian dan Peternakan

Smart Farming Technologies for Indonesia Agriculture Productivity and Sustainability

Muhamad Ivan Fadilah — 2026-01-05

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set of 10 final articles, which, while relevant, may not encompass the full spectrum of smart farming applications and unpublished case studies in Indonesia.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.

Greenshield Neem: Microencapsulation Formulation of Neem Leaves as a Sustainable Agricultural Technology for Indonesia 2045

Sulisatun Nisak — 2026-01-12

Purpose: This study proposes GreenShield Neem, a microencapsulated neem (Azadirachta indica A. Juss) formulation, as a sustainable biopesticide technology to support environmentally friendly agriculture in Indonesia toward the 2045 vision.

Research Methodology: This study used a structured literature review and a conceptual synthesis. Peer-reviewed articles published between 2014 and 2024 were screened; 42 records were initially identified, and 26 articles were selected for an in-depth review based on predefined inclusion/exclusion criteria. Data analysis was conducted using thematic coding and comparative synthesis by extracting key variables (formulation type, encapsulation method/materials, stability indicators, controlled release behavior, and reported bioefficacy). The extracted evidence was then consolidated to develop the GreenShield Neem conceptual framework and a proposed field-application scenario.

Results: The literature synthesis indicates that neem-based biopesticides possess strong insecticidal properties due to bioactive compounds such as azadirachtin, salannin, and nimbin. However, conventional neem formulations suffer from low stability. Microencapsulation technology significantly enhances the stability, persistence, and efficacy of these bioactive compounds by protecting them against ultraviolet radiation, oxidation, and environmental degradation, while enabling their controlled release in the field.

Conclusions: GreenShield Neem demonstrates strong potential as a sustainable pest-management innovation that can reduce dependence on synthetic pesticides, minimize environmental contamination, and improve the efficiency of agricultural practices.

Limitations: This study is limited to a conceptual, literature-based analysis and lacks experimental validation.

Contributions: This article advances sustainable agriculture by offering a scientifically grounded formulation concept that integrates local biological resources with modern delivery technologies, particularly for tropical agricultural systems.

Beyond Efficiency: Smart Farming, Climate Change, and the Resilience of Food Crop Productivity

Derah Sudjaniah — 2026-01-14

Purpose: This study aims to examine the effect of smart farming implementation on food crop productivity in Indonesia and analyze the moderating role of climate change on this relationship.

Research Methodology: This study used a quantitative cross-sectional survey design conducted among food crop farmers in Indonesia. Data were collected using a structured questionnaire with a five-point Likert scale. Purposive sampling was applied to 200 respondents. The analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS software to test reliability, validity, and hypothesis relationships.

Results: The findings show that the implementation of smart farming positively influences crop productivity. Climate change significantly affects crop productivity. Furthermore, climate change strengthens the relationship between smart farming and crop productivity.

Conclusions: Write the main conclusions of the research. Smart farming plays an important role in improving food crop productivity, especially under increasing climate-change pressures.

Limitations: This study relied on self-reported survey data and used a cross-sectional design, limiting long-term causal interpretation.

Contributions: This study contributes to digital agriculture and climate adaptation research by providing empirical evidence of the role of smart farming in improving productivity and resilience, supporting policymakers and farmers in developing climate-smart agricultural strategies.

Simulation of Agropasture Carrying Capacity in Supporting Cattle Production System

Fellyanus Haba Ora — 2026-01-07

Abstract

Purpose: This study aimed to simulate the carrying capacity of existing agropastures to support cattle production systems.

Research Methodology: Research materials consisted of forage vegetation in agropasture and 120 farmers respondents. This research was descriptive in nature and had a cross-sectional design. The data include both primary and secondary sources. Data collection techniques were conducted through observations and documentation. Data analysis was performed using Powersim to simulate a nine-year projection.

Results: A nine-year simulation projected a significant degradation of the cattle population, resulting in excess forage availability in agropasture. Biophysically, agropasture on Timor Island has an adequate carrying capacity; however, this potential is not optimally utilized due to inefficiencies in the cattle production system, including high mortality rates of calves and adult cattle, low reproductive performance of female cattle, cattle removals that disregard regional carrying capacity, and a high incidence of livestock disease outbreaks.

Conclusions: The existing conditions and carrying capacity of feed quantity in the agropasture of Timor Island are very low to support the cattle production system, resulting in overgrazing and disruptions to livestock production and health. If this condition persists, it will lead to the degradation of the cattle population, although it may eventually be followed by excess forage availability.

Limitations: This study did not present a dynamic system intervention simulation of the existing carrying capacity of agropastures to support the cattle production system.

Contributions: This research contributes to the planning and policy aspects of agroecosystem-based area development, particularly agropasture, in supporting livestock production systems.