The Undergraduate Statistics Study Program, Department of Mathematics Education, FMIPA UNY held a Visiting Professor with the theme "Multivariate Statistics and Statistical Machine Learning" on 7, 9 and 10 November 2023. This activity was carried out by inviting Professor Osval Antonio Montesinos López, Ph.D from Universidad de Colima Mexico. Prof. Osval has an interest in high-dimensional data analysis, generalized linear mixed models, Bayesian analysis, multivariate analysis, experimental design, and survey design. This activity was attended by 5th semester students of the Multivariate Statistics and Machine Learning Statistics courses and several lecturers from the Statistics Study Program. The visiting professor participants were very enthusiastic about taking part in the event and were given the opportunity to ask questions.

On this occasion he spoke about Random Forest and Clustering. Random Forest is a method in machine learning which aims to build a model using a model base in the form of a decision tree. In the real world there are various types of data, this method can be used to solve classification and regression problems. Classification is carried out when the response used is in the form of a category, while regression is carried out when the response is continuous. When analyzing real data, we sometimes encounter data with unbalanced classes, so class balancing needs to be done. Prof. Osval conveyed several methods that can be used to balance classes in data, including oversampling and undersampling. Apart from Random Forest, he also spoke about clustering, starting from hierarchical clustering and non-hierarchical clustering. For each method, he also provides several illustrations of real data analysis using R software.