Determinan pencapaian siswa bidang matematika: Perbandingan antara indonesia dan singapura
DOI:
https://doi.org/10.31980/pme.v2i1.1395Keywords:
mathematics, PISA, multivariate regression, Indonesia;, Singapore, matematika, regresi multivariat, Indonesia, SingapuraAbstract
This study investigates and compares the determinants of Indonesian and Singaporean students’ achievement in mathematics. The achievement is proxied by the PISA score of mathematics. The recent PISA 2018 data is used to answer this research question. Multivariate linear regression is used; as the dependent variable in the PISA score of mathematics, while the information concerning the student’s background is used as independent variables, student’s age, gender, learning time in mathematics, index of economic, social, and cultural status, and ICT possession at home. For all samples (Indonesia and Singapore), all independent variables are statistically significant at least at the 10% level. This shows that age, gender, learning time in mathematics, index of economic, social, and cultural status, and ICT possession at home do influence student achievement as measured by PISA mathematics scores. Several tests to test the classical assumptions, such as the residual normality test, heteroscedasticity test, and collinearity test were also carried out. According to this test, no problems occurred.
Penelitian ini menyelidiki faktor-faktor penentu (determinan) pencapaian matematika siswa Indonesia dan Singapura. Pencapaian siswa diukur dengan dengan skor PISA matematika. Data PISA terbaru tahun 2018 digunakan untuk menjawab pertanyaan penelitian ini. Regresi linier multivariat digunakan; sebagai variabel terikat adalah nilai PISA matematika, sedangkan informasi mengenai latar belakang siswa digunakan sebagai variabel bebas, yaitu usia, jenis kelamin, waktu belajar matematika, indeks status ekonomi, sosial, dan budaya, serta kepemilikan ICT di rumah. Untuk semua sampel (Indonesia dan Singapura), semua variabel bebas signifikan secara statistik dalam taraf (paling tidak) 10%. Hal ini menunjukkan bahwa usia, jenis kelamin, kepemilikan ICT di rumah, kondisi ekonomi, sosial, dan budaya, dan waktu belajar matematika waktu belajar matematika, indeks status ekonomi, sosial, dan budaya, serta kepemilikan ICT di rumah berpengaruh terhadap prestasi siswa yang diukur dengan nilai PISA matematika. Beberapa pengujian untuk menguji asumsi klasik, seperti uji normalitas residual, uji heteroskedastisitas dan uji kolinearitas juga dilakukan. Menurut tes ini, tidak ada masalah yang terjadi.
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