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ANALYSIS OF FACTORS AFFECTING PNEUMONIA IN INDONESIAN TODDLERS USING NONPARAMETRIC REGRESSION WITH LEAST SQUARE SPLINE AND FOURIER SERIES METHODS

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 20 No. 1 (2025) · hlm. 0087–0104

DOI
10.30598/barekengvol20iss1pp0087-0104
ISSN
2615-3017, 1978-7227
Terbit
2025-11-24
Penerbit
PATTIMURA UNIVERSITY
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Pneumonia is the leading cause of death among children under five, with the highest prevalence in Indonesia found in West Papua Province (75%) and the lowest in North Sulawesi (0.3%). This study aims to analyze the factors influencing the prevalence of pneumonia in Indonesian toddlers using nonparametric regression approach by comparing Least Square Spline (LS-Spline) and Fourier Series. Data sourced from the Indonesian Ministry of Health website, consisting of 34 provinces in Indonesia in 2023, with one response variable (Y) and five predictor variables (X). The analyzed factors include the coverage of vitamin A supplementation, malnutrition rates, low birth weight prevalence, measles immunization coverage, and exclusive breastfeeding rates. The analysis was conducted by modeling with nonparametric Least Square Spline regression using up to three optimal knot points, then performing analysis using nonparametric regression with the Fourier series approach. The two methods were compared based on GCV and R², with the best model having lower GCV and higher R². The results showed that LS-Spline was better than Fourier Series, with a GCV value of 233.16 and a coefficient of determination of 92.5%. The findings reveal that the relationships between predictor factors and pneumonia prevalence are nonlinear, with varying influence patterns across different variable ranges. These results indicate that LS-Spline has a strong ability to explain data variability. The Fourier series is limited in this study because it is best suited for periodic data, unlike pneumonia data and its causal factors which do not show such patterns. The weakness of the Fourier Series in this study lies in its suitability for periodic data, while pneumonia cases and their causal factors do not follow such patterns. This study offers insights into health policy making to reduce pneumonia cases, improve their lives, in line with the SDGs target on Good Health and Well-being.

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  • Universitas Airlangga
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Rekan penulisOrganisasiArtikel bersama
Nur ChamidahUniversitas Airlangga7
Dita AmeliaUniversitas Airlangga4
Galuh Cahya NugrahaUniversitas Airlangga3
Rien RecyliaUniversitas Airlangga2
Najwa Khoir AldawiyahUniversitas Airlangga2
Nina AuliyahUniversitas Airlangga2
Fatiha Nadia SalsabilaUniversitas Airlangga2
Mubadi'ul FitrianiUniversitas Airlangga2
Azizatul KholidiyahUniversitas Airlangga2
Fildzah Tri Januar ArianiUniversitas Airlangga2
Sediono SedionoUniversitas Airlangga2
Hanny ValidaUniversitas Airlangga2
Muhammad Hafidzuddin NaharUniversitas Airlangga2
Regina FortunataUniversitas Airlangga2
Gabriella Agnes BudijonoUniversitas Airlangga2
Azizah Atsariyyah ZhafiraUniversitas Airlangga2
Belindha Ayu ArdhaniUniversitas Airlangga1
Atikah FaizaUniversitas Airlangga1
Zidni Ilmatun NurrohmahUniversitas Airlangga1
Laili PuspasariUniversitas Airlangga1
Ardi KurniawanUniversitas Airlangga1
Mochammad Bayu FirmansyahUniversitas Airlangga1
Idrus SyahzaqiUniversitas Airlangga1
Aurellia Calista AnggakusumaUniversitas Airlangga1
Ezha Easyfa WieldyanisaUniversitas Airlangga1
Muhammad Fariz Fadillah MardiantoUniversitas Airlangga1
Marisa RifadaUniversitas Airlangga1
Karina Rubita MakhbubahUniversitas Airlangga1
Devira Thania RamadhantyUniversitas Airlangga1
Any Tsalasatul FitriyahUniversitas Airlangga1
Maria Setya DewantiUniversitas Airlangga1
Aurelia Islami AzisUniversitas Airlangga1
Billy Christandy SuyonoUniversitas Airlangga1

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Sumber metadata: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc)
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	<dc:title xml:lang="en-US">ANALYSIS OF FACTORS AFFECTING PNEUMONIA IN INDONESIAN TODDLERS USING NONPARAMETRIC REGRESSION WITH LEAST SQUARE SPLINE AND FOURIER SERIES METHODS</dc:title>
	<dc:creator>Saifudin, Toha</dc:creator>
	<dc:creator>Suliyanto, Suliyanto</dc:creator>
	<dc:creator>Nurdin, Nabila</dc:creator>
	<dc:creator>Christiano Ginzel, Bryan Given</dc:creator>
	<dc:creator>Oktavia, Sabrina Salsa</dc:creator>
	<dc:creator>Ariyawan, Jovansha</dc:creator>
	<dc:creator>Ubadah, Mohammad Noufal</dc:creator>
	<dc:description xml:lang="en-US">Pneumonia is the leading cause of death among children under five, with the highest prevalence in Indonesia found in West Papua Province (75%) and the lowest in North Sulawesi (0.3%). This study aims to analyze the factors influencing the prevalence of pneumonia in Indonesian toddlers using nonparametric regression approach by comparing Least Square Spline (LS-Spline) and Fourier Series. Data sourced from the Indonesian Ministry of Health website, consisting of 34 provinces in Indonesia in 2023, with one response variable (Y) and five predictor variables (X). The analyzed factors include the coverage of vitamin A supplementation, malnutrition rates, low birth weight prevalence, measles immunization coverage, and exclusive breastfeeding rates. The analysis was conducted by modeling with nonparametric Least Square Spline regression using up to three optimal knot points, then performing analysis using nonparametric regression with the Fourier series approach. The two methods were compared based on GCV and R², with the best model having lower GCV and higher R². The results showed that LS-Spline was better than Fourier Series, with a GCV value of 233.16 and a coefficient of determination of 92.5%. The findings reveal that the relationships between predictor factors and pneumonia prevalence are nonlinear, with varying influence patterns across different variable ranges. These results indicate that LS-Spline has a strong ability to explain data variability. The Fourier series is limited in this study because it is best suited for periodic data, unlike pneumonia data and its causal factors which do not show such patterns. The weakness of the Fourier Series in this study lies in its suitability for periodic data, while pneumonia cases and their causal factors do not follow such patterns. This study offers insights into health policy making to reduce pneumonia cases, improve their lives, in line with the SDGs target on Good Health and Well-being.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2025-11-24</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/17625</dc:identifier>
	<dc:identifier>10.30598/barekengvol20iss1pp0087-0104</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application; 0087-0104</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol20iss1year2026</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/17625/11731</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Toha Saifudin, Suliyanto Suliyanto, Nabila Nurdin, Bryan Given Christiano Ginzel, Sabrina Salsa Oktavia, Jovansha Ariyawan, Mohammad Noufal Ubadah</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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