Factors Influencing Stunting in Indonesia 2018 With Geographically Weighted Regression Analysis

Stunting is a health issue with long-term effects on human resource quality. This study analyzes factors influencing stunting prevalence in Indonesia using the Geographically Weighted Regression (GWR) approach. Using 2018 provincial-level data, the study examines the impact of social, health, and education factors on stunting rates, categorized by gender. Analysis employs Global Regression to identify key explanatory variables before applying GWR to capture spatial variations. Results reveal significant regional differences, where factors such as Insurance, Participation School, Immunization, Happiness, Water, and Years School exhibit varying influences. The GWR model outperforms global regression, achieving R-squared values of 0.6641 (males) and 0.6589 (females), with AIC values of 506.871 and 499.160, respectively. These findings highlight the importance of localized policies to address stunting effectively.

Authors

Institutions

Publication Details

Journal
International Journal of Scientific Research in Science Engineering and Technology
Published
2025-03-28
DOI
https://doi.org/10.32628/ijsrset25122143
Primary Topic
Public Health and Nutrition
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Factors Influencing Stunting in Indonesia 2018 With Geographically Weighted Regression Analysis

Elisa Diana Julianti, Muhammad Nur Aidi, Fitrah Ernawati, Yekti Widodo et al.
International Journal of Scientific Research in Science Engineering and Technology
Public Health and Nutrition
article

Factors Influencing Stunting in Indonesia 2018 With Geographically Weighted Regression Analysis

Elisa Diana Julianti, Muhammad Nur Aidi, Fitrah Ernawati, Yekti Widodo, Aya Yuriestia Arifin, Rizqi Dwi Yuniarsyih, Hakim Zoelva Mahesa, I Putu Gde Inov Bagus Prasetya, Syella Zignora Limba
article en

Abstract

Stunting is a health issue with long-term effects on human resource quality. This study analyzes factors influencing stunting prevalence in Indonesia using the Geographically Weighted Regression (GWR) approach. Using 2018 provincial-level data, the study examines the impact of social, health, and education factors on stunting rates, categorized by gender. Analysis employs Global Regression to identify key explanatory variables before applying GWR to capture spatial variations. Results reveal significant regional differences, where factors such as Insurance, Participation School, Immunization, Happiness, Water, and Years School exhibit varying influences. The GWR model outperforms global regression, achieving R-squared values of 0.6641 (males) and 0.6589 (females), with AIC values of 506.871 and 499.160, respectively. These findings highlight the importance of localized policies to address stunting effectively.

International Journal of Scientific Research in Science Engineering and TechnologyVol. 12(2)
IPB University (ID), National Research, Development and Innovation Office (HU), National Research and Innovation Agency (ID)
Openalex Percentile: Top 92%
Public Health and Nutrition
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.