• UNY Statistics Undergraduate Study Program Achieves UNGGUL Accreditation Rating from LAMSAMA
    Post date: 20/06/2025 - 14:00

    The Statistics Undergraduate Study Program of Universitas Negeri Yogyakarta has successfully obtained an accreditation rating of “UNGGUL” from the Independent Accreditation Institution for Natural Sciences and Formal Sciences (LAMSAMA) based on LAMSAMA Decree Number 103/SK/LAMSAMA/Akred/S/V/2025. This accreditation certificate is valid from May 19, 2025 to May 18, 2030. A brilliant achievement from hard work, collaboration, and commitment to continue to provide quality education. May the Statistics Study Program of Yogyakarta State University be even more...

  • Training on Educational and Social Science Data Analysis with a Nonparametric Approach Using the JASP Program
    Post date: 20/06/2025 - 10:00

    The Statistics Study Program of Universitas Negeri Yogyakarta (UNY) in collaboration with the Mathematics Education Study Program of Universitas Sarjanawiyata Tamansiswa (UST) has successfully held a Community Service (PkM) activity entitled "Training on Educational and Social Science Data Analysis with a Nonparametric Approach Using the JASP Program". This activity took place for three days in June 2025 and was part of the PkM scheme for Professor and/or Structural Lecturer Assignments funded by UNY. The training was held on June 11, 12, and 19, 2025, at the UST...

  • Third Day Workshop on Statistical Machine Learning Methods for Genomic Prediction Using R Program
    Post date: 19/06/2025 - 15:00

    The third day of the Workshop on Statistical Machine Learning Methods for Genomic Prediction Using R Program was held on Thursday, June 19, 2025, at 10:00-13:00 WIB in the FMIPA UNY Ballroom. In this session, Professor Osval continued the material from the previous day by discussing the application of the ridge regression and lasso regression methods to several datasets, namely Trouser, Dog, and Toy EYT using the help of Rstudio software. In addition, he also explained the mixed models method for genomic prediction, Bayesian ridge regression, and Bayesian...

  • Second Day Workshop on Statistical Machine Learning Methods for Genomic Prediction Using R Program
    Post date: 18/06/2025 - 15:00

    On Wednesday, June 18, 2025, the Workshop on Statistical Machine Learning Methods for Genomic Prediction Using R Program on the second day started at 10:00-13:00 WIB in the FMIPA UNY Ballroom. In this workshop, Professor Osval Antonio Montesinos López, Ph.D. from Universidad de Colima, Mexico delivered advanced materials covering three main materials. First, computational genetics material that discusses genetic markers from genotype data, the process of recoding marker information according to the rules, to calculating the Minor Allele Frequency (MAF). Second...

  • First Day Workshop on Statistical Machine Learning Methods for Genomic Prediction Using R Program
    Post date: 17/06/2025 - 15:00

    Statistics Study Program of Universitas Negeri Yogyakarta held a workshop as a continuation of the Visiting Professor program, presenting Professor Osval Antonio Montesinos López, Ph.D. from Universidad de Colima, Mexico. This activity lasted for five days, namely on June 17, 18, 19, 20, and 23, 2025, with the theme "Statistical Machine Learning Methods for Genomic Prediction Using R Program". Workshop participants included students of Statistics, Mathematics, Physics and Biology Study Programs, FMIPA UNY.

    The first day of...

  • Visiting Professor with Prof. Osval Antonio Montesinos López, Ph.D. General Lecture Session 3
    Post date: 13/06/2025 - 09:00

    On Thursday, June 12, 2025, the Statistics Study Program, FMIPA UNY again held a third general lecture session with Visiting Professor Prof. Osval Antonio Montesinos López, Ph.D from Universidad de Colima, Mexico. The activity took place at 10.00–11.00 WIB in Meeting Room 3, FMIPA UNY. In his lecture themed "Applications of Artificial Intelligence (AI) in Agriculture", he discussed various applications of Artificial Intelligence (AI) in the agricultural sector, starting from techniques and analysis methods using relevant AI, the benefits of implementing AI to...

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