AI Research for Potato Farmers Secures Prestigious Funding, UNM PhD Student Delivers Real Innovation
Universitas Nusa Mandiri (UNM), as a Digital Business Campus, has once again reaffirmed its commitment to delivering impactful research through an impressive achievement at the doctoral level.
Sri Hadianti, M.Kom, a student in the Informatics Doctoral Programme (S3), has successfully obtained prestigious funding through the 2026 Doctoral Dissertation Research Fellowship Programme.
This success was achieved with an innovative research proposal titled “Development of High-Precision Image Interpolation Methods and Adaptive Loss Functions to Stabilise Deep Learning-Based Potato Pest Detection Models”, which offers technological solutions for Indonesia’s agricultural sector.
The research focuses on utilising deep learning to detect pests and diseases in potato plants more accurately.
The main problem addressed is the low accuracy of detection systems due to varying image quality in the field, such as uneven lighting to limited camera resolution.
To tackle these challenges, Sri developed two main approaches: high-precision image interpolation methods to enhance the visual quality of plant leaves, and adaptive loss functions to stabilise the AI model when dealing with imbalanced data.
UNM Rector, Prof Dr Dwiza Riana, expressed appreciation for the achievement. “This is proof that research at UNM excels not only academically but also provides concrete solutions to societal problems. We continue to encourage the birth of technology-based innovations that have direct impact, including in strategic sectors like agriculture,” she stated in a comment quoted on Sunday (26/4/2026).
Sri revealed that this research is expected to be widely implemented, especially for farmers in rural areas. “Through this research, I want to provide solutions that farmers can truly use, particularly in early pest detection. The hope is that this technology helps reduce the risk of crop failure and improves farmers’ welfare,” she said.
In her research process, Sri received guidance from experts, namely Prof Dr Dwiza Riana as senior supervisor and Dr Eng Muhammad Haris as assistant supervisor. This collaboration was key to producing methodologically robust and implementation-relevant research.
Overall, this research has the potential to produce an AI-based pest detection system that can be integrated into mobile devices. Thus, it is easily accessible to farmers in various regions, including remote areas.
This achievement also strengthens UNM’s role in consistently promoting technology-based research development, as well as making real contributions to supporting national food security through digital innovation.
With this accomplishment, UNM is optimistic about continuing to produce researchers and innovators capable of addressing global challenges through practical and sustainable technology-based solutions.