The Community Service (PkM) Team of the Statistics Study Program, Faculty of Mathematics and Natural Sciences, Yogyakarta State University (UNY), in collaboration with the Business Administration Study Program, Faculty of Social and Political Sciences, University of Muhammadiyah Mataram (UMMAT), held a data analysis training using Jeffreys' Amazing Statistics Program (JASP) software. The training was held online on April 2, 2026, and continued offline on April 13–14, 2026, with approximately 30 participants, including lecturers and students. The training aimed to improve participants' understanding and skills in data analysis, particularly factor analysis techniques widely used in social and business research.

The event began with remarks from representatives of both study programs, followed by a training session covering several key topics: an introduction to JASP, descriptive statistics using JASP, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA). The material was delivered by expert speakers in their fields, namely Luthfia Hanun Yuli Arini, S.Stat., M.Stat., Andika Putri Ratnasari, S.Stat., M.Sc., Ezra Putranda Setiawan, M.Sc., and Prof. Kismiantini, Ph.D., using an interactive and practical approach.

During the offline session, participants were given the opportunity to practice directly using case data with intensive guidance from the resource team. Participants appeared enthusiastic in each session, particularly in understanding the steps of factor analysis, from testing data validity to interpreting results. The use of JASP, as open-source software, provided added value due to its ease of use, rapid output, and the absence of a paid license.

Through this activity, participants are expected to be able to apply descriptive statistical techniques and factor analysis, both exploratory and confirmatory, in their research more accurately and comprehensively. In addition, the collaboration between the Statistics Study Program, FMIPA UNY and the Business Administration Study Program, FISIPOL UMMAT is expected to continue in various other academic activities to support the improvement of scientific capacity and data analysis skills.