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All Journal Zero : Jurnal Sains, Matematika, dan Terapan
Danang Ariyanto
Department of Mathematics, Universitas Brawijaya, Malang, 65145, Indonesia
Agriculture, Biological Sciences & Forestry Chemistry Mathematics Physics

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Comparing Adaptive Kernels in Geographically and Temporally Weighted Regression for Stunting in East Nusa Tenggara, 2021–2023 Danang Ariyanto; Henny Pramoedyo; Atiek Iriany; Isnani Darti
ZERO: Jurnal Sains, Matematika dan Terapan Vol 10, No 2 (2026): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v10i2.30987

Abstract

Stunting remains a major public health challenge in East Nusa Tenggara, Indonesia. This study compares Gaussian, Bisquare, and Exponential adaptive kernels in Geographically and Temporally Weighted Regression (GTWR) to model spatiotemporal variation in stunting determinants. District-level panel data from 22 districts/municipalities during 2021-2023 were used, yielding 66 space-time observations. Models were evaluated using R², RMSE, spatial-temporal parameter tests, and a spatial-only GWR baseline. The Bisquare adaptive GTWR produced the strongest in-sample fit (R² = 98.58%; RMSE = 0.7647), improving over the Bisquare GWR baseline (R² = 46.98%; RMSE = 4.6703), although this high fit should be interpreted cautiously. GRDP per capita, poverty rate, and maternal education showed significant spatial-temporal variability, while the sanitation and clean water access variable was not significant (F₃ = 1.0938; p = 0.4771). GTWR may serve as an exploratory tool for identifying local stunting patterns.
Co-Authors Atiek Iriany Henny Pramoedyo Isnani Darti