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All Journal Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) UNP Journal of Statistics and Data Science
Novi, Yoli Marda
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Mathematics Medicine & Pharmacology Social Sciences

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Comparison of Nadaraya-Watson Method with Local Polynomial in Modeling HDI and Poverty Relationship in Java Island Novi, Yoli Marda; Fadhilah Fitri; Zamahsary Martha
UNP Journal of Statistics and Data Science Vol. 3 No. 3 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss3/380

Abstract

Poverty remains a critical issue in Indonesia, with the number of poor people reaching 24.06 million in September 2024. The Human Development Index (HDI), which indicates the level of human resource quality, is one of the factors influence poverty. This analysis focuses on the correlation involving HDI also this number of poor people in districts/cities in Java Island by comparing two kernel regresokesion methods, namely Nadaraya-Watson Estimator and Local Polynomial Estimator. Nonparametric regression was chosen thus it does not necessitate this presumption of a certain form of connection among variables, so it is more flexible in capturing complex relationship patterns. Secondary data from Statistics Indonesia (BPS) in 2024 was used in this study. Initial exploration shows, the data distribution does not have a clear pattern, so nonparametric methods are more suitable for use. Modeling is done using the optimal bandwidth obtained through the dpill function in R software. The analysis results show that the local polynomial estimator produces smoother regression curves and lower MSE values. In addition, comparison of different polynomial degrees shows that higher polynomial degrees tended to improve model performance. Among the tested polynomial degrees, the local polynomial with degree five (p=5) produced the lowest MSE value and the highest coefficient of determination. Therefore, the local polynomial estimator with degree 5 is the best method for modeling the relationship between the HDI and poverty levels in Java in 2024
Robust Spatial Autoregressive (Robust SAR) Modeling in the Case of Poverty Percentage in West Java Novi, Yoli Marda; Tessy Octavia Mukhti; Zamahsary Martha
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.61818

Abstract

Poverty is a complex problem influenced by various economic and social factors, such as the open unemployment rate, the minimum wage, population density, and the school participation rate. This study aims to model the poverty rate in West Java Province by considering spatial effects and the existence of outliers through the application of Spatial Autoregressive (SAR) and Robust Spatial Autoregressive (Robust SAR) models. Based on the Lagrange Multiplier test, the SAR model is declared suitable for use. However, the presence of outliers in the data necessitated the use of a robust approach to obtain more accurate results. The analysis showed that the Robust SAR model had a coefficient of determination of 81.53%, higher than that of the SAR model at 77.48%, making it a better model for explaining variations in poverty levels. Of the four independent variables, only School Participation Rate had a significant effect in both models, where an increase in School Participation Rate contributed to a decrease in the poverty rate. This finding confirms the importance of investment in education as a strategic effort to reduce welfare inequality between regions in West Java.
Co-Authors Fadhilah Fitri Tessy Octavia Mukhti Zamahsary Martha