The research was conducted by Arissaryadin, Agustia Dwi Pamujiati, and Reksa Nanda Prayoga from the Faculty of Agriculture at Kadiri University. Their findings highlight a growing challenge in agricultural modernization: advanced digital technologies alone are not enough to improve rural economies if farmers lack the skills to use them effectively.
The study focused on Bima Regency in West Nusa Tenggara, one of Indonesia’s largest corn-producing regions. According to government statistics cited in the paper, Bima produced around 724,000 tons of corn in 2023, making it one of the country’s major agricultural centers. Despite high production levels, many farmers continue to face unstable incomes, limited bargaining power, and weak market access.
Researchers argue that the biggest obstacle is no longer production capacity, but inefficiencies in distribution systems and limited access to digital markets.
Farming Technology Expands Faster Than Farmer Skills
Agriculture worldwide is rapidly adopting digital technologies such as artificial intelligence, drones, Internet of Things (IoT) systems, big data analytics, and digital market platforms. These tools are designed to help farmers improve crop monitoring, reduce waste, and make more accurate production decisions.
However, the Kadiri University study found that many farmers in developing agricultural regions still struggle to benefit from these innovations because of low digital literacy, weak internet infrastructure, and limited training opportunities.
The researchers surveyed 140 corn farmers across 18 districts in Bima Regency between December 2025 and April 2026. They also conducted in-depth interviews and focus group discussions with 10 key informants involved in the local agribusiness system.
The study examined three major factors affecting agribusiness performance:
- technology adoption,
- digital literacy,
- market access.
Agribusiness performance was measured through indicators such as productivity, operational efficiency, and farmer income.
Digital Literacy Became the Strongest Predictor
The statistical analysis revealed that all three factors positively affected agribusiness performance, but digital literacy had the strongest impact.
The regression model showed:
- Digital literacy: β = 0.428
- Technology adoption: β = 0.312
- Market access: β = 0.267
The overall model explained 68 percent of variations in agribusiness performance among farmers.
Researchers also applied a machine learning approach using a random forest model to identify broader data patterns. The predictive model achieved an accuracy rate of 81 percent and again identified digital literacy as the most influential variable, contributing 34 percent to agribusiness performance.
The consistency between traditional statistical analysis and machine learning strengthened the reliability of the findings.
According to the study, this demonstrates that the effectiveness of digital farming depends less on the availability of technology and more on farmers’ ability to understand, interpret, and apply digital information in real-world farming activities.
“Digital farming is not primarily driven by the availability of technology, but by farmers’ capacity to understand and utilize digital tools effectively,” the researchers from Kadiri University wrote in their discussion section.
Structural Problems Continue to Limit Farmers
The research also revealed a significant digital divide in rural farming communities.
Among the respondents:
- 55 percent were between 31 and 50 years old,
- 85 percent had only primary or secondary education,
- 84 percent showed low to moderate digital literacy levels.
Many farmers reported relying heavily on traditional middlemen because they lacked access to transparent pricing systems and digital market information.
During harvest seasons, oversupply often causes sharp price drops, weakening farmers’ bargaining positions. Farmers interviewed in the study said they frequently struggle to determine the best selling time because real-time market information is unavailable or difficult to access.
Participants also highlighted several barriers to adopting digital farming systems:
- limited technical training,
- unstable internet connectivity,
- weak institutional support,
- inadequate agricultural extension services.
The study concluded that technological tools alone cannot transform agricultural systems unless they are supported by stronger human capacity and institutional readiness.
Implications for Agricultural Policy and Rural Development
The findings carry important implications for governments, agribusiness companies, and rural development agencies across Indonesia and other developing countries.
The researchers recommend prioritizing digital literacy programs for farmers alongside investments in rural internet infrastructure and integrated digital marketing systems.
They also emphasized the importance of building inclusive agricultural ecosystems that combine:
- digital skills training,
- market transparency,
- institutional support,
- data-based distribution systems.
According to the study, sustainable agribusiness transformation requires balance between technology, human capacity, and efficient market systems.
The researchers argue that improving production alone will not significantly improve farmer welfare if distribution and market access remain inefficient.
The study also contributes to global academic discussions about digital transformation in agriculture by combining quantitative analysis, qualitative interviews, and machine learning approaches within a single research framework. This mixed-methods approach allowed the researchers to examine both statistical patterns and the social realities experienced by farmers.
Author Profile
Arissaryadin is a researcher and academic affiliated with the Faculty of Agriculture at Kadiri University, Indonesia. His work focuses on agribusiness systems, agricultural extension, digital farming, and rural development.
Agustia Dwi Pamujiati specializes in agricultural development and digital transformation in farming systems.
Reksa Nanda Prayoga conducts research on agribusiness performance, technology adoption, and sustainable agriculture.
Source
Article title: Integrating Mixed Methods and Big Data Analytics in Digital Farming to Improve Corn Agribusiness Performance in Bima Regency, Indonesia
Journal: International Journal of Sustainability in Research (IJSR) Vol. 4, No. 3 Tahun 2026
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