Universitas Gadjah Mada Leverages Big Data and AI for More Accurate Oil Palm Production Prediction
Utilizing Big Data in Oil Palm Plantations for Production Prediction Using Deep Neural Network Models
Yogyakarta – An innovative study led by Andri Prima Nugroho, STP., M.Sc., Ph.D., IPU, ASEAN Eng., APEC Eng., from the Department of Agricultural Technology at Universitas Gadjah Mada (UGM), has successfully utilized Big Data technology and Deep Neural Network (DNN) models to predict oil palm production. Completed in 2022, this research aims to integrate climate, soil, and agronomic data to produce more accurate production estimates and support precision plantation management planning.
This collaborative research with external partners highlights the importance of leveraging advanced technologies in the agricultural sector, particularly in oil palm plantations. Andri Prima Nugroho explained that challenges in predicting oil palm production often arise from environmental variability and data complexity. “By integrating large volumes of data from various sources such as climate, soil characteristics, and agronomic practices, we can build more comprehensive prediction models,” he stated.
The application of Deep Neural Networks (DNN) enables the system to learn from complex data patterns, allowing it to provide production estimates that are not only accurate but also adaptive to dynamic environmental changes. The results of this study are expected to serve as a strategic decision-support tool for oil palm plantation managers in making informed decisions related to harvesting, resource allocation, and cultivation strategies. This innovation also aligns with the research themes of AI for Food & Agriculture and Big Data Analytics.
This innovation marks a significant step forward in applying artificial intelligence and Big Data analytics to enhance efficiency and productivity in the oil palm industry, while also supporting precision agriculture in Indonesia.
