<mets:mets OBJID="eprint_11067" LABEL="Eprints Item" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mets="http://www.loc.gov/METS/" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mets:metsHdr CREATEDATE="2026-08-05T08:29:15Z"><mets:agent ROLE="CUSTODIAN" TYPE="ORGANIZATION"><mets:name>Repository Universitas Pakuan</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_eprint_11067_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:titleInfo><mods:title>ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI&#13;
KEJADIAN BALITA STUNTING DI INDONESIA&#13;
MENGGUNAKAN REGRESI SEMIPARAMETRIK SPLINE</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">Saskia Yety</mods:namePart><mods:namePart type="family">Ocsiella</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI&#13;
KEJADIAN BALITA STUNTING DI INDONESIA&#13;
MENGGUNAKAN REGRESI SEMIPARAMETRIK SPLINE&#13;
Sakia Yety Ocsiella*, Yasmin Erika Faridhan, Hagni Wijayanti&#13;
FMIPA, Universitas Pakuan, Jl. Pakuan, RT.02/RW.06, Tegallega, Kecamatan Bogor Tengah,&#13;
Kota Bogor, Jawa Barat 16129&#13;
e-mail: sakiayocsiella@gmail.com&#13;
Abstract: This study aims to model the percentage of stunting and to analyze the factors influencing stunting&#13;
prevalence in Indonesia. The explanatory variables considered include the percentage of animal-source&#13;
complementary feeding (MPASI), child nutritional status (weight-for-age), access to improved sanitation,&#13;
access to unimproved drinking water, and the percentage of pregnant women consuming iron&#13;
supplementation (TTD). The scatter plots between the response and explanatory variables indicate nonlinear patterns; therefore, a semiparametric spline regression approach is employed. Semiparametric&#13;
spline regression offers flexibility in capturing both linear and non-linear relationships through the use of&#13;
knot points. In this study, models are constructed using one, two, three, four, and a combination of knot&#13;
points. The optimal model is selected based on the minimum value of Generalized Cross Validation (GCV).&#13;
The data used are secondary data obtained from the Ministry of Villages, Development of Disadvantaged&#13;
Regions, and Transmigration, covering 38 provinces in Indonesia in 2023. The results show that the best&#13;
model is achieved using a combination of knot points (2,3,4), with a minimum GCV value of 30.5424 and&#13;
a coefficient of determination (R²) of 89.42%. The findings indicate that all explanatory variables&#13;
significantly influence the percentage of stunting. In conclusion, the semiparametric spline regression&#13;
model is effective in modeling stunting prevalence in Indonesia and provides a flexible approach to&#13;
capturing complex relationships between variables.&#13;
Keywords: stunting, semiparametric regression, spline, GCV, explanatory variables</mods:abstract><mods:classification authority="lcc">Matematika</mods:classification><mods:originInfo><mods:dateIssued encoding="iso8061">2025</mods:dateIssued></mods:originInfo><mods:originInfo><mods:publisher>Universitas Pakuan;Fakultas Matematika dan Pengetahuan Alam</mods:publisher></mods:originInfo><mods:genre>Thesis</mods:genre></mets:xmlData></mets:mdWrap></mets:dmdSec><mets:amdSec ID="TMD_eprint_11067"><mets:rightsMD ID="rights_eprint_11067_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:useAndReproduction>
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