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All Journal Jurnal Aplikasi Statistika & Komputasi Statistik
Verhasselt, Anneleen
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

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Unveiling Spatial Disparities: Exploring High-Risk Diarrhea Among Children Under Five Using Geographically Weighted Quantile Regression Syukrilla, Wara Alfa; Andriyana, Yudhie; Verhasselt, Anneleen
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 15 No 2 (2023): Journal of Statistical Application and Computational Statistics
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v15i2.536

Abstract

We investigate the impact of the percentage of clean water access, the percentage of handwashing habits, and the toilet category factors on the upper quantile of toddlers’ diarrhea risks in Bandung City, Indonesia, using the Geographically Weighted Quantile Regression model on the 75th percentile. The breusch-Pagan test was used to detect spatial heterogeneity. The results show that the significance, strength, and direction of the relationship between diarrhea and its risk factors depend on the location. At the upper quantile, the Panyileukan district is predicted to have the highest diarrhea risk. In this district, all three predictors significantly affect the toddlers’ diarrhea risk, with the variable of the percentage of houses practicing hand washing habits observed to reduce diarrhea risk the most. In conclusion, clean water access, handwashing habits, and toilet category are the potential risk factors for high-risk childhood diarrhea. This method is powerful as it would allow the decision maker to handle the diarrhea problem aptly based on which predictor has a substantial effect at a specific district of interest. And it can be used to investigate the effect of various intervention strategies and effectively allocate the limited available resources according to the most important locations.
Co-Authors Syukrilla, Wara Alfa Yudhie Andriyana