The Multivariate Generalized Linear Model applies a lot in data science. However, this model is still less discussed in education, specifically in data analysis in the Program for International Student Assessment (PISA), which has complex structure data. This study aims to analyze the factors that influence the PISA's scores of Indonesian students simultaneously covering the three subjects of the PISA assessment, namely mathematics literacy, science literacy, and reading literacy. The complexity of PISA data which involves multivariate response variables which assumes a correlation between response variables, adds to the complexity of the analysis. One approach is the Multivariate Generalized Linear Model with the Quasi Likelihood estimation method. Took the data sources from the PISA survey was conducted by Organization for Economic Cooperation and Development in 2018. This study indicates that the factors that influence the PISA's scores of Indonesian students simultaneously are the class taken, parental education, facilities at home, student discipline, teacher feedback during learning, age of entering kindergarten, and failing a grade during elementary school. Based on the model diagnostic, it can conclude that Multivariate Generalized Linear Model produces a model that fits in modeling the PISA's scores of Indonesian students.
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4 January 2023
THE FIRST INTERNATIONAL CONFERENCE ON NEUROSCIENCE AND LEARNING TECHNOLOGY (ICONSATIN 2021)
18–19 September 2021
Jember, Indonesia
Research Article|
January 04 2023
Modeling the PISA’s score of Indonesian students using multivariate generalized linear model
Vera Maya Santi;
Vera Maya Santi
a)
1
Statistics Study Programme, Faculty of Mathematics and Natural Science, Universitas Negeri Jakarta
, Kampus A Universitas Negeri Jakarta, Jalan Rawamangun Muka, Jakarta Timur, Postcode 13220, DKI Jakarta, Indonesia
a)Corresponding author: [email protected]
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Mirzha Faradiba;
Mirzha Faradiba
b)
1
Statistics Study Programme, Faculty of Mathematics and Natural Science, Universitas Negeri Jakarta
, Kampus A Universitas Negeri Jakarta, Jalan Rawamangun Muka, Jakarta Timur, Postcode 13220, DKI Jakarta, Indonesia
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Dania Siregar;
Dania Siregar
c)
1
Statistics Study Programme, Faculty of Mathematics and Natural Science, Universitas Negeri Jakarta
, Kampus A Universitas Negeri Jakarta, Jalan Rawamangun Muka, Jakarta Timur, Postcode 13220, DKI Jakarta, Indonesia
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Dian Handayani;
Dian Handayani
d)
1
Statistics Study Programme, Faculty of Mathematics and Natural Science, Universitas Negeri Jakarta
, Kampus A Universitas Negeri Jakarta, Jalan Rawamangun Muka, Jakarta Timur, Postcode 13220, DKI Jakarta, Indonesia
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Widyanti Rahayu
Widyanti Rahayu
e)
1
Statistics Study Programme, Faculty of Mathematics and Natural Science, Universitas Negeri Jakarta
, Kampus A Universitas Negeri Jakarta, Jalan Rawamangun Muka, Jakarta Timur, Postcode 13220, DKI Jakarta, Indonesia
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a)Corresponding author: [email protected]
AIP Conf. Proc. 2679, 020001 (2023)
Citation
Vera Maya Santi, Mirzha Faradiba, Dania Siregar, Dian Handayani, Widyanti Rahayu; Modeling the PISA’s score of Indonesian students using multivariate generalized linear model. AIP Conf. Proc. 4 January 2023; 2679 (1): 020001. https://doi.org/10.1063/5.0111321
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