Yogyakarta – The Department of Agricultural Socio-Economics, Faculty of Agriculture, Universitas Gadjah Mada (UGM), through its Laboratory of Agricultural and Agribusiness Socio-Economic Modeling, successfully organized two sessions of the Sapa Data (Data and Analysis Training Series) in August 2025. This initiative aims to enrich public knowledge in data analysis, particularly in the field of agricultural and agribusiness socio-economic modeling. Sapa Data 3 was held on Friday, August 15, 2025, followed by Sapa Data 4 on Friday, August 22, 2025. Both events were conducted in a hybrid format, allowing participation both online and in-person, and were open to the public free of charge.
The two sessions were led by Prof. Kismiantini, Ph.D., a Professor of Statistical Modeling from the Statistics Program at Universitas Negeri Yogyakarta (UNY). In Sapa Data 3, participants were introduced to the Basics of R Studio, with Prof. Kismiantini providing practical demonstrations, including how to create R scripts to facilitate initial data analysis. The subsequent session, Sapa Data 4, built upon the previous material, focusing on Structural Equation Modeling – Partial Least Squares (SEM-PLS) Analysis using R. The speaker delivered both theoretical insights and hands-on demonstrations, enabling participants to apply these concepts directly to their research.
Sapa Data is a new initiative by the laboratory, planned to be held regularly every few months. Prior to these events, Sapa Data 1 and 2 were successfully conducted in June 2025, with plans for Sapa Data 5 and 6 scheduled for late September 2025. Through this series, the laboratory aims to serve as a reliable source of knowledge and information on SEM-PLS data analysis for the wider community, particularly government institutions, lecturers, and students conducting research in agriculture and agribusiness. The training seeks to promote the application of advanced analytical methods to support data-driven decision-making in the agricultural sector.
This Sapa Data series aligns with several United Nations Sustainable Development Goals (SDGs), emphasizing quality education and innovation in agriculture. Specifically, it supports SDG 4 (Quality Education) by providing free and accessible training to enhance data analysis skills for lecturers, students, and the general public. Additionally, it contributes to SDG 2 (Zero Hunger) by strengthening the understanding of socio-economic modeling in agriculture, which can improve agribusiness productivity and food security. Lastly, the initiative supports SDG 9 (Industry, Innovation, and Infrastructure) through the introduction of tools like R Studio and SEM-PLS, fostering technological innovation in data analysis for sustainable agriculture.
With the success of this series, the Laboratory of Agricultural and Agribusiness Socio-Economic Modeling remains committed to supporting human resource development in agriculture through similar educational programs. For those interested in attending upcoming sessions, stay updated through the official website of the Department of Agricultural Socio-Economics, Faculty of Agriculture, UGM.