CD Skripsi
Pemodelan rata-rata lama sekolah di indonesia menggunakan regresi nonparametrik campuran truncated spline dan kernel
Indonesia faces challenges in improving the quality of education, one of which is indicated by variations in the average length of schooling between regions. This study aims to analyze the factors that influence the average length of schooling in Indonesia using a nonparametric mixed spline and kernel regression method. This approach is used to capture linear, nonlinear, and local relationships between socioeconomic and educational variables using data from the Central Statistics Agency (BPS) in 2023. The independent variables in this study consist of the percentage of poor population, school participation rate, and per capita expenditure as spline components, and the literacy rate and high school student-teacher ratio as kernel components. The kernel used is a Gaussian kernel to capture local patterns smoothly. The best model was obtained with one knot point for each spline variable and a kernel bandwidth of 3.5. The analysis results show that the model is able to explain 61.11% of the variation in the average length of schooling with a minimum Generalized Cross Validation (GCV) value of 0.014598. These findings suggest that mixed spline and kernel nonparametric regression is an effective approach to modeling the complex relationships between socioeconomic factors and education in Indonesia.
Keywords: average length of schooling, GCV, gaussian kernel, indonesia, nonparametric regression, truncated spline.
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