Journal of Agricultural Economy and Technology Development

Economic Impact Analysis of the Implementation of Agricultural Technology 4.0 on National Food Security

Chiska Nova Harsela — 2025-07-01

The implementation of Agricultural Technology 4.0 has become an important strategy in facing national food security challenges amidst population growth, climate change, and land limitations. This study aims to analyze the economic impact of the adoption of modern agricultural technologies such as the Internet of Things (IoT), artificial intelligence (AI), and data-driven digital systems on improving production efficiency, distribution, and farmer satisfaction. Using a qualitative approach, data was collected through in-depth interviews, participatory observation, and questionnaires in three key agricultural regions: Sleman, Subang, and Jember. The results show that the use of technology can reduce production costs by up to 30%, significantly increase yields, and expand digital market access. However, challenges such as limited technological literacy and digital infrastructure still constrain implementation. This research confirms the importance of synergy between technology, farmer training and public policy in realizing sustainable food security. The practical implications of this study provide a policy basis to support the overall digital transformation of agriculture in Indonesia.

Evaluation of the Effectiveness of Digital Training Program for Farmers in Increasing the Adoption of Modern Agricultural

Indi Millatul Maula — 2025-07-02

Digital transformation in the agricultural sector is an important agenda in increasing the productivity and efficiency of farming, especially in the era of the Industrial Revolution 4.0. This study aims to evaluate the effectiveness of digital training programs organized for farmers in increasing the adoption of modern agricultural technology. The method used is a qualitative approach with a case study design. Data were collected through in-depth interviews, direct observations, and distributing questionnaires to 20 farmers who participated in the digital training program in Banyumas Regency, Central Java. The results showed that digital training had a positive impact on improving digital literacy, confidence, and technology adoption behaviors, such as the use of weather applications, digital record keeping, and online farm marketing platforms. Findings also showed that technology adoption tended to be higher among farmers who received post-training assistance. However, challenges such as device limitations, networks, and technological complexity remain as barriers. This research suggests that digital training programs should be designed in a contextual and sustainable manner so that digital agricultural transformation can be implemented effectively and inclusively.

Integration of Internet of Everything (IoE) in Precision Agriculture: A Case Study on Rice Commodity in West Java

Sherina Prahitaningtyas — 2025-07-02

Technology-based precision agriculture is increasingly becoming a necessity in system the challenges of climate change, resource efficiency, and increased productivity. This study aims to analyze the implementation of the Internet of Everything (IoE) in precision agriculture systems on rice commodities in West Java. Using a qualitative case study approach, data were collected through in-depth interviews, field observations, and questionnaires with farmers and extension workers in three rice center districts: Indramayu, Subang, and Karawang. The results show that the application of IoE technologies such as soil sensors, automated irrigation systems, and land monitoring drones can increase water use efficiency by 30% and crop productivity by 17%. However, there are constraints in technology adoption including limited digital literacy, network infrastructure, and initial investment costs. This study concludes that the successful integration of IoE in precision agriculture requires the support of a technology ecosystem, continuous training, and inclusive government policies. This study contributes to the development of a strategy for data-driven agricultural digitalization in Indonesia.

Development of a Blockchain-Based Sustainable Agriculture Supply Chain System: A Study on Horticultural Commodities

Aen Fariah — 2025-07-01

This research aims to study and develop a sustainable horticultural supply chain system based on blockchain technology in Indonesia. The background of the research is based on the urgent need for transparency, efficiency, and sustainability in managing the distribution of horticultural products that have been facing various challenges, such as data manipulation and limited product tracking. Using a descriptive qualitative approach through case studies in Bandung and Garut Regencies, data was obtained through in-depth interviews, participatory observation, and questionnaires with farmers, distributors, agritech providers, and policy makers. The results showed that blockchain implementation was able to improve traceability by 95%, distribution efficiency by 15%, and reduce operational costs by 25%. The blockchain system is also proven to strengthen trust between supply chain actors and increase transaction accountability. However, there are still obstacles in the form of low understanding of technology at the grassroots level and limited digital infrastructure. This research recommends the integration of blockchain with digital training and cross-sector collaboration to create an inclusive, adaptive, and sustainable agricultural system.

Utilization of Artificial Intelligence and Remote Sensing for Yield Prediction and Irrigation Management in Drylands

Ginna Novarianti Dwi Putri Pramesti — 2025-07-01

Drylands face serious challenges in the agricultural sector, especially in terms of water availability and accurate crop yield prediction. This study aims to assess the utilization of artificial intelligence (AI) and remote sensing technology in supporting crop yield prediction and efficient irrigation management in drylands. Using a descriptive qualitative approach, data were collected through in-depth interviews, structured questionnaires, participatory observation, and documentation studies in five villages in Belu District, East Nusa Tenggara. The results showed that the integration of AI and remote sensing was able to improve water distribution efficiency by 30% and the accuracy of crop yield prediction reached more than 85%. Respondents such as extension workers and technicians showed a high level of satisfaction with the technology, although some farmers still face digital literacy barriers. Observational findings also confirmed that vegetation in technologically advanced fields had a higher plant health index (NDVI). This study suggests the importance of technology training for farmers as well as the provision of supportive digital infrastructure as strategic steps in the implementation of sustainable precision agriculture.