• Khalilah Nurfadilah Mathematics Study Program, Islamic State University of Alauddin Makassar, Indonesia
  • Muhammad Nur Aidi Department of Statistics, IPB University, Indonesia
  • Khairil A. Notodiputro Department of Statistics, IPB University, Indonesia
  • Budi Susetyo Department of Statistics, IPB University, Indonesia
Keywords: Multilevel Regression, Mean Score of UN, Nested


National Exam known as UN score is the final evaluation to determine the achievement of national graduate competency standards in the school. The determinants of the achievement of the standards can’t be separated from the role of schools and local governments in which this regard is known as nested. In the field of statistics, this phenomenon can be described with a multilevel model, where level-1 is the school while level-2 is the district where the school is located. Several multilevel models are used to describe the phenomenon, the result shows that the two-level regression model without interaction is selected as the best model and the variables which affect the UN average scores significantly at level-1 are school status , the ratio between laboratories and students , while the variable at level-2 is expenditure per capita of district/city . From this study, that educational institutions' steps in achieving a graduation standard can be right on the target.


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How to Cite
K. Nurfadilah, M. Aidi, K. Notodiputro, and B. Susetyo, “MULTILEVEL REGRESSIONS FOR MODELING MEAN SCORES OF NATIONAL EXAMINATIONS”, BAREKENG: J. Math. & App., vol. 18, no. 1, pp. 0323-0332, Mar. 2024.