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Ni'matuzzahroh, Ludia
YPPI Rembang University
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Social Sciences

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A Nonparametric Regression Approach Address Poverty Problems in East Nusa Tenggara Province Adrianingsih, Narita Yuri; Mungkabel, Mariana; Dani, Andrea Tri Rian; Ni'matuzzahroh, Ludia
Inferensi Vol 8, No 1 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i1.20508

Abstract

The administration is focused on reducing poverty, which is still a significant issue. Since the regression curve is unknown and the truncated spline nonparametric regression approach offers a high degree of flexibility, the study was conducted to determine what factors influence it, particularly in the East Nusa Tenggara area. The goal of this study is to develop a nonparametric regression model. The average length of schooling, life expectancy, percentage of the illiterate population aged 15 and over, labor force participation rate, percentage of households based on the information source, and population density affect poverty in the East Nusa Tenggara area. With a minimum GCV of 39.57, it was determined that 1 knot point were the ideal knot point. To some extent, the characteristics that influenced poverty were life expectancy, labor force participation rate, percentage of households with a proper light source, and population density. The best model met these criteria with an R2 of 81.28%. The findings suggest that targeted interventions to improve these factors can significantly reduce poverty in East Nusa Tenggara.
Nonparametric Regression Modeling with Multivariable Fourier Series Estimator on Average Length of Schooling in Central Java in 2023 Ni'matuzzahroh, Ludia; Dani, Andrea Tri Rian
Inferensi Vol 7, No 2 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i2.20219

Abstract

One of the benchmarks to see the quality of education and human resources in Indonesia is the average length of schooling. If the school average is higher, it can positively impact Indonesian society, enabling it to compete globally. There are several factors, both economic and educational factors, that influence the low average length of schooling in Central Java Province. Therefore, this research aims to model and determine what variables can influence the average length of schooling in Central Java in 2023 using a nonparametric regression approach with a multivariable Fourier series estimator. This approach is used when the form of the relationship pattern is unknown and tends to have recurring patterns. The Fourier series estimator depends on the number of oscillations, so in this study, 1 to 4 oscillations were tried, where the minimum GCV value determined the optimal oscillation. The best model was obtained on the analysis results, producing the smallest GCV value, namely the model with 3 oscillations with a GCV value of 1.027. The results of simultaneous and partial hypothesis testing showed that all predictor variables used in this research were proven to influence the Average Length of Schooling. This is also supported by the coefficient of determination value of 85.464%.
Co-Authors Adrianingsih, Narita Yuri Dani, Andrea Tri Rian Mungkabel, Mariana