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PENERAPAN HIERARCHICAL LINEAR MODELING UNTUK MENGANALISIS DATA MULTILEVEL

Unisda Journal of Mathematics and Computer Science (UJMC)

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ISSN 2579-907X
2460-3333
 
Authentication Code dc
 
Title Statement PENERAPAN HIERARCHICAL LINEAR MODELING UNTUK MENGANALISIS DATA MULTILEVEL
 
Added Entry - Uncontrolled Name Wulandari, Dewi
Shodiqin, Ali
Aini, Aurora Nur
Universitas PGRI Semarang
Universitas PGRI Semarang
Universitas PGRI Semarang
 
Summary, etc. Multilevel data are data that are nested within the other data which are in the higher level. As an example is students are nested in the classes. The student is the level-1 variable and the class is the level-2 variable. Multilevel data are not restricted only level-2 but also more than it. As an example we have taken, school is the level-3 variable, region is the level-4 variable etc. Students in one class will be different from another class, classes in one school will be dierent from another school, etc. Because of this variation then we need Hierarchical Linear Modeling (HLM) to analyze it. This method is a complex form of OLS (Ordinary Least Square) regression. In estimating the parameters we use GLS (Generalized Least Square). In this research, we use mathematics score of Nasima junior high school student Semarang. From the analysis result which are got by using software HLM student version we can conclude that there's no signicant variation within groups or classes, then it's enough using OLS regression to analyze the factors affecting mathematics score. Hypothesis of the reason of this is the amount of unit in level-2 variables are not enough, they are only 4 units. To prove this hypothesis, we need another research.
 
Publication, Distribution, Etc. Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan
 
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http://e-jurnal.unisda.ac.id/index.php/ujmc/article/view/444
 
Data Source Entry Unisda Journal of Mathematics and Computer Science (UJMC); Vol 2 No 1 (2016): Unisda Journal of Mathematics and Computer Science
 
Language Note eng
 
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