Andri Prima Nugroho, Ph.D


Welcome, You have reached the academic personal website of Andri Prima Nugroho, Academic staff and researcher of Agricultural Informatics with Department of Agricultural and Biosystems Engineering at Universitas Gadjah Mada.


Head of Laboratory of Agricultural Structures & Environmental Engineering (2021 – 2025)
Chairman of Indonesian Society of Agricultural Engineers Yogyakarta Branch (2018 – 2022)
Leader and Founder of Smart Agriculture Research Group, Department of Agricultural and Biosystems Engineering UGM (Since 2016)

Official Address

Department of Agricultural and Biosystems Engineering
Faculty of Agricultural Technology, Universitas Gadjah Mada
Flora No. 1, Bulaksumur, Yogyakarta 55281 INDONESIA
Position: Academic staff and Researcher
Phone/Fax: +62-274-563-542
E-mail: andrew{at}; andrew.nugroho{at}


STP./B. Agr. Tech. in System Design, Energy and Agricultural Machinery, Department of Agricultural Engineering (2008), Universitas Gadjah Mada, Indonesia
M.Sc in Agricultural Informatics, Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, Japan (2013). Thesis: “Development of Monitoring and Actuation Framework for Informatization Agriculture and Verification of its Validity”
Ph.D in Agricultural Informatics, Kyushu University, Japan (2016). Dissertation: “Development of Smart Agriculture Framework and Its Application to Tropical Horticulture”


– Information Technology in Bio-Production Engineering
– Precision Agriculture
– Agricultural Information System
– Electronics and Communication Engineering
– Knowledge Management

Professional Affiliations

Indonesian Association of Agricultural Engineering (ISAE)
Japanese Society of Agricultural Machinery and Food Engineer (JSAM)
Japanese Geotechnical Society (JGS)


Smart Agriculture Research

To introduce a smart agriculture framework as an application of information and communication technology (ICT) to improve the conventional farming management in tropical agriculture production.

The framework is implementing a cloud technology as a backbone, which can be extended with various knowledge such as data science, plant biology, plant physiology, bio-physical and bio-mechanical (agricultural robotics). To achieve the research objective above, we break down our work into 4 research themes as follows:

Schematic diagram of Smart Agriculture Framework

Environmental Monitoring

1-environmental-monitoringEnvironmental monitoring is the foundation of modern agriculture. By collecting the periodical weather data both real-time and long-term evaluation, the behavior and variation of hourly, daily, monthly, and yearly could be quantified for precise farming decision support.

Environmental Assessment

2-environmental-assesmentEnvironmental assessment is the second step in the utilization of smart agriculture framework in the tropical agriculture production. It is important to interpret the collected environmental data as a factor to support the decision making on farming management.

Environmental Control

3-environmental-controlThe suitable environmental condition is necessary to obtain the maximum plant growth during the agriculture cultivation. To achieve appropriate environmental condition, we consider the implementation of environmental control. In tropical agriculture, irrigation control is one of the applications that can be established by the smart agriculture framework for flexible and simple operation [1].

Plant Monitoring & Assessment

4-plant-monitoringPlant monitoring and assessment is the activity to get responses of the environmental treatment from plant behavior’s view. Leaf motion is one of physical indicator that has been used to investigate the existence of plant motion, representing the internal movement triggered by the circadian clock even under the constant environment [2].

Knowledge Management

Appropriate adaptation of PA and knowledge management system to support the learning process on the implementation of PA in tropical agriculture is necessary to be addressed. The objective of this study was to present the knowledge management framework for supporting the learning process at the farmer level on the implementation of PA in tropical agriculture. The framework was manifested as a cloud-based application for sharing best-practices on practical PA among the farmer, documentation of question and answer, discussion forum, multimedia tutorial, etc. The framework facilitates data-to-knowledge transformation, assisted by the expert involving in summarizing the topics and troubleshoot in a specific case.