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Evaluation of Anthropometric Data Quality for Children from Electronic-Based Nutrition Surveillance: A Case Study in Magelang Regency, Central Java, Indonesia

Media Kesehatan Masyarakat Indonesia · Vol. 21 No. 4 (2025) · hlm. 298–311

DOI
10.30597/mkmi.v21i4.43510
ISSN
2356-4067, 0216-2482
Terbit
2025-12-17
Penerbit
Faculty of Public Health, Hasanuddin University, Makassar
Bahasa
en
Lisensi
creativecommons.org/licenses/by-nc-sa/4.0/

Abstrak

Data quality regarding the nutritional status of children under five is crucial for developing strategies to address nutritional issues. This study aims to develop indicators and assess the quality of anthropometric data from community-based nutrition surveillance using the EPPGBM application in Magelang Regency. The research employed an observational design with a quantitative approach. Data quality indicators were defined based on expert consensus using the Delphi method. These indicators were also used to construct an anthropometric data quality index (IKDA). The WPS Office spreadsheet was utilized to assess data quality and perform IKDA calculations. Nine data quality indicators were identified, categorized into four domains: representation, completeness, accuracy, and external consistency. Evaluation of the EPPGBM data revealed that indicators for representation and completeness were categorized as good quality. In contrast, within the accuracy domain, only the z-score accuracy indicator met the “good” standard, while the digit preference indicator showed poor quality. Specifically, digit preference accounted for 24.2% of weight measurements and 62.8% of height measurements, with clustering around digits 0 and 5. In the external consistency domain, the stunting prevalence from the EPPGBM results was lower than the 2022 SSGI results. The IKDA score for the data was 85.8. Overall, the evaluation identified that the EPPGBM data quality in Magelang Regency demonstrated strong representation and completeness but exhibited limitations in accuracy and external consistency. To improve data accuracy, relevant stakeholders should implement targeted interventions, including capacity-building through training of cadres, standardization of measurement procedures and instruments, and reinforcement of supervisory mechanisms.

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  • Universitas Gadjah Mada
  • National Research and Innovation Agency
  • Universitas PGRI Madiun
  • IPB University
  • Islamic University of Indonesia
  • Universitas Ahmad Dahlan
  • University of Indonesia
  • Organisasi lain
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Rekan penulisOrganisasiArtikel bersama
Sri AnardaniUniversitas PGRI Madiun1
Dimas SetiawanUniversitas PGRI Madiun1
Faridah BarorohUniversitas Ahmad Dahlan1
Dwi EndartiUniversitas Gadjah Mada1
Shinta PrawitasariUniversitas Gadjah Mada1
Nova Lidia SitorusAfiliasi tidak diketahui1
Charisma DilantikaAfiliasi tidak diketahui1
Siti HelmyatiUniversitas Gadjah Mada1
Renita RenitaUniversitas Gadjah Mada1
Rizal RizalUniversity of Indonesia1
Rio HermantaraUniversitas Gadjah Mada1
Fransiscus Fiano Anthony KeransUniversitas Gadjah Mada1
Elizabeth Henny HerningtyasUniversitas Gadjah Mada1
Taufik DjatnaIPB University1
Imas Sukaesih SitanggangIPB University1
Tika Dewi AtikahNational Research and Innovation Agency1
Muhammad Thesa GhozaliMuhammadiyah University of Yogyakarta1
Zullies IkawatiUniversitas Gadjah Mada1
Wasilah RochmahUniversitas Gadjah Mada1
Riksa Wibawa ResnaAfiliasi tidak diketahui1
Sri WerdatiUniversitas Alma Ata1
Titik KuntariIslamic University of Indonesia1
Agus WijanarkaPoltekkes Kemenkes Yogyakarta1
Ina KusriniNational Research and Innovation Agency1
Taufiq HidayatNational Research and Innovation Agency1
Marizka KhairunnisaNational Research and Innovation Agency1
Sidiq PurwokoNational Research and Innovation Agency1
Sri SupadmiNational Research and Innovation Agency1
Tri SuwarnoIslamic University of Indonesia1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/mkmi/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">Evaluation of Anthropometric Data Quality for Children from Electronic-Based Nutrition Surveillance: A Case Study in Magelang Regency, Central Java, Indonesia</dc:title>
	<dc:creator xml:lang="en">Riyanto, Slamet</dc:creator>
	<dc:creator xml:lang="en">Purwaningrum, Digna Niken</dc:creator>
	<dc:creator xml:lang="en">Lazuardi , Lutfan</dc:creator>
	<dc:subject xml:lang="en">Anthropometric</dc:subject>
	<dc:subject xml:lang="en">EPPGBM</dc:subject>
	<dc:subject xml:lang="en">Data Quality</dc:subject>
	<dc:subject xml:lang="en">Nutritional Status</dc:subject>
	<dc:subject xml:lang="en">Surveillance</dc:subject>
	<dc:description xml:lang="en">Data quality regarding the nutritional status of children under five is crucial for developing strategies to address nutritional issues. This study aims to develop indicators and assess the quality of anthropometric data from community-based nutrition surveillance using the EPPGBM application in Magelang Regency. The research employed an observational design with a quantitative approach. Data quality indicators were defined based on expert consensus using the Delphi method. These indicators were also used to construct an anthropometric data quality index (IKDA). The WPS Office spreadsheet was utilized to assess data quality and perform IKDA calculations. Nine data quality indicators were identified, categorized into four domains: representation, completeness, accuracy, and external consistency. Evaluation of the EPPGBM data revealed that indicators for representation and completeness were categorized as good quality. In contrast, within the accuracy domain, only the z-score accuracy indicator met the “good” standard, while the digit preference indicator showed poor quality.  Specifically, digit preference accounted for 24.2% of weight measurements and 62.8% of height measurements, with clustering around digits 0 and 5. In the external consistency domain, the stunting prevalence from the EPPGBM results was lower than the 2022 SSGI results. The IKDA score for the data was 85.8. Overall, the evaluation identified that the EPPGBM data quality in Magelang Regency demonstrated strong representation and completeness but exhibited limitations in accuracy and external consistency. To improve data accuracy, relevant stakeholders should implement targeted interventions, including capacity-building through training of cadres, standardization of measurement procedures and instruments, and reinforcement of supervisory mechanisms.</dc:description>
	<dc:publisher xml:lang="en">Faculty of Public Health, Hasanuddin University, Makassar</dc:publisher>
	<dc:date>2025-12-17</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/mkmi/article/view/43510</dc:identifier>
	<dc:identifier>10.30597/mkmi.v21i4.43510</dc:identifier>
	<dc:source xml:lang="en">Media Kesehatan Masyarakat Indonesia; Vol. 21 No. 4: DECEMBER 2025; 298-311</dc:source>
	<dc:source>2356-4067</dc:source>
	<dc:source>0216-2482</dc:source>
	<dc:source>10.30597/mkmi.v21i4</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/mkmi/article/view/43510/13887</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 by author</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by-nc-sa/4.0/</dc:rights>
</oai_dc:dc>