Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan
Idris, Nurul Fadillah
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
COMPARISON OF MARS AND BINARY LOGISTIC REGRESSION MODELS FOR IDENTIFYING STUNTING RISK FACTORS IN TODDLERS IN TELUK WARU, EAST SERAM REGENCY Bension, Johan Bruiyf; Kondo Lembang, Ferry; Idris, Nurul Fadillah; Lewaherilla, Norisca
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1541-1556

Abstract

In 2022, the prevalence of chronic stunting in Indonesia reached 21.6%, surpassing the World Health Organization (WHO) threshold of 20%. East Seram Regency reported an even higher prevalence of 24.1%, with Teluk Waru District identified as one of the areas most affected due to low compliance with healthy lifestyle practices. This study aimed to compare the performance of Multivariate Adaptive Regression Splines (MARS) and Binary Logistic Regression in analyzing risk factors for toddler stunting in Teluk Waru District, East Seram Regency. Data were collected through direct anthropometric measurements at the Integrated Health Post (Posyandu) of Teluk Waru Health Center with 60 respondents. The findings revealed that Binary Logistic Regression outperformed MARS, achieving R2 = 72.7% accuracy in predicting stunting. Significant determinants of toddler stunting included a history of illness, provision of supplementary food for pregnant women, and iron tablet consumption during pregnancy. The novelty of this study lies in the application of a comparative modeling approach—MARS versus Binary Logistic Regression—in identifying stunting risk factors at a district level with high prevalence. Practically, the results can assist local health authorities in prioritizing maternal nutrition and disease prevention programs to reduce stunting.
Co-Authors Bension, Johan Bruiyf Ferry Kondo Lembang Lewaherilla, Norisca