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All Journal Inferensi Parameter: Journal of Statistics
Etis Sunandi
Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Bengkulu, Bengkulu, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Social Sciences

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Estimation of Stunting and Wasting in Sumatra 2022 with Nadaraya-Watson Kernel and Penalized Spline Cinta Rizki Oktarina; Sigit Nugroho; Idhia Sriliana; Pepi Novianti; Etis Sunandi; Reza Pahlepi
Inferensi Vol 8 No 3 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i3.23330

Abstract

This study aims to estimate the prevalence of Stunting and Wasting in Sumatra in 2022 using nonparametric regression methods, specifically the Nadaraya-Watson Kernel and Penalized Spline regression models. Both models were applied to assess the relationship between these two correlated response variables and various predictor variables, such as low birth weight, sanitary facilities, poor population, and exclusive breastfeeding. The results showed that the Nadaraya-Watson Kernel regression, particularly using the Gaussian kernel, provided the best fit with minimal prediction error, as indicated by its low Generalized Cross-Validation (GCV) value of 0.024 and high R-squared values (0.9992 for Stunting and 0.9995 for Wasting). In contrast, the Epanechnikov kernel and Biweight kernel produced higher GCV values (0.110 and 0.356, respectively), indicating less optimal performance. For the Penalized Spline model, optimal parameters were determined with a smoothing parameter λ of 5 and 3 knots, which balanced model flexibility and smoothness. This research underscores the potential of nonparametric regression techniques in capturing complex relationships in health data and provides insights for improving interventions aimed at addressing child malnutrition in Indonesia.
ANALYSIS OF THE RELATIONSHIP BETWEEN REGION, SEX, AND MARITAL STATUS USING A FOUR-DIMENSIONAL LOG-LINIER IN BENGKULU PROVINCE IN 2022 Putri Damayanti; Gita Sonia; Novelisa Syendra Wanti; Rada Nur Aisa; Etis Sunandi; Pepi Novianti
Parameter: Journal of Statistics Vol. 6 No. 1 (2026)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2026.v6.i1.17901

Abstract

This study analyzes the relationship among four categorical variables age group, gender, marital status, and region of residence among individuals aged 10–24 years in Bengkulu Province in 2022. The analysis employed a four-dimensional log-linear model to examine complex associations between these variables. Data were obtained from the Central Bureau of Statistics (BPS) and organized into a four-way contingency table representing all possible combinations of the observed factors. Model parameters were estimated using the maximum likelihood method, and model fit was assessed using the Pearson Chi-Square test and the Akaike Information Criterion (AIC). The results indicated that models involving only two or three factors did not fit the data adequately. In contrast, the saturated model that included all four factors provided the best fit, with a p-value of 1. These findings suggest that there are strong and complex interactions among age, gender, marital status, and region. Therefore, the relationships among these demographic factors cannot be explained independently but require a comprehensive model that incorporates all interactions.
Co-Authors Cinta Rizki Oktarina Gita Sonia Idhia Sriliana Novelisa Syendra Wanti Pepi Novianti Putri Damayanti Rada Nur Aisa Reza Pahlepi Sigit Nugroho