Analisis data stunting berdasarkan data SSGI dan e-PPGBM di Kabupaten Tanggamus
Ind
DOI: https://doi.org/10.33024/hjk.v20i6.3448
Data Management E-PPGBM Nutritional Surveillance SSGI Stunting
Abstract
Background: Stunting is a chronic nutritional issue affecting child growth and development, particularly during the first 1,000 days of life. Discrepancies in stunting prevalence data between the Indonesian Nutritional Status Study and the electronic Community-Based Nutrition Recording and Reporting system can impact the accuracy of program planning and evaluation. This study aims to analyze and compare stunting prevalence data from the Indonesian Nutritional Status Study and the electronic Community-Based Nutrition Recording and Reporting system in Tanggamus Regency.
Purpose: To analyze the discrepancies between the Indonesian Nutritional Status Study and the electronic Community-Based Nutrition Recording and Reporting system stunting data and to identify strategies for optimizing stunting data management and reporting systems.
Method: This study employs a qualitative approach with a case study design. Research informants include Health Office officials, village heads, Integrated Health Post cadres, representatives from the Family Welfare Empowerment program, and the district-level Stunting Reduction Acceleration Team. Data were collected through in-depth interviews, observation, and a review of the Indonesian Nutritional Status Study and the electronic Community-Based Nutrition Recording and Reporting system documentation. Data validity was ensured through source and method triangulation, while thematic analysis was used to identify the causes of data discrepancies and determine data governance strategies. The study was conducted at the Tanggamus Regency Health Office between September and October 2025.
Results: Findings indicate discrepancies between the Indonesian Nutritional Status Study and the electronic Community-Based Nutrition Recording and Reporting system stunting prevalence data, caused by differences in data collection methods, variations in the technical capacity of field personnel, limitations in validation and supervision processes, the absence of cross-sectoral data reconciliation mechanisms, and a lack of specific regulations governing stunting data integration. The study identifies the need for an integrated approach to improve data accuracy and utilization.
Conclusion: The Indonesian Nutritional Status Study shows fluctuating stunting prevalence, whereas the electronic Community-Based Nutrition Recording and Reporting system shows a downward trend from 2022 to 2024. The discrepancy between the two sources stems from differences in data collection methods, human resource capacity, and data validation. Strengthening data governance, through cross-sectoral reconciliation, standardization of anthropometric measurements, capacity building, and integrated information systems is crucial for improving data quality and supporting targeted stunting interventions.
Keywords: Data Management; Nutritional Surveillance; E-PPGBM; SSGI; Stunting.
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References
Adityaningrum, A., Arsad, N., & Jusuf, H. (2023). Faktor penyebab stunting di Indonesia: Analisis data sekunder data SSGI tahun 2021. Jambura Journal of Epidemiology, 2(1), 1-10.
Amirul, D., Elyasari, E., & Arsulfa, A. (2023). Temuan dari Survei Sosial Ekonomi Indonesia dan Survei Status Gizi Indonesia pada Faktor yang Mempengaruhi Prevalensi Stunting. Health Information: Jurnal Penelitian, 15(2), e902-e902.
Black, R. E., Victora, C. G., Walker, S. P., Bhutta, Z. A., Christian, P., De Onis, M., & Uauy, R. (2013). Maternal and child undernutrition and overweight in low-income and middle-income countries. The lancet, 382(9890), 427-451.
Dinas Kesehatan Kabupaten Tanggamus. (2024). Laporan Dinas Kesehatan Kabupaten Tanggamus Tahun 2023 [Laporan tidak dipublikasikan].
Development Initiatives. (2022). 2022 Global nutrition report: The state of global nutrition. https://globalnutritionreport.org/reports/2022-global-nutrition-report/
Duri, I. D., Nastiti, H. R. R., & Widiyanto, S. D. (2025). Nutritional Status Analysis of Toddlers (0-2 Years) for Stunting Prevention Based on E-PPGBM. Jurnal Manajemen Informasi Kesehatan (Health Information Management), 10(1), 173-178.
Gibson, R. S. (2005). Principles of nutritional assessment. Oxford University Press.
Green, L. W., & Kreuter, M. W. (2005). Health program planning: An educational and ecological approach (4th ed., Vols. 1–2). McGraw-Hill Education.
Health Metrics Network, & World Health Organization. (2008). Framework and standards for country health information system release and assessment (2nd ed.). Diakses dari: https://www.who.int/publications/i/item/9789241595940
Kahn, M. G., Callahan, T. J., Barnard, J., Bauck, A. E., Brown, J., Davidson, B. N., & Schilling, L. (2016). A harmonized data quality assessment terminology and framework for the secondary use of electronic health record data. Egems, 4(1), 1244.
Kementerian Kesehatan Republik Indonesia. (2024). Panduan Hari Gizi Nasional ke 64 Tahun 2024. Ayo Sehat Kemkes. Diakses dari: https://ayosehat.kemkes.go.id/panduan-hari-gizi-nasional-ke-64-tahun-2024
Kementerian Kesehatan Republik Indonesia. (2020). Peraturan Menteri Kesehatan Republik Indonesia Nomor 2 Tahun 2020 tentang Standar Antropometri Anak. Diakses dari: https://jdih.kemkes.go.id/documents/peraturan-menteri-kesehatan-nomor-2-tahun-2020
Kementerian Kesehatan Republik Indonesia. (2015). Petunjuk pelaksanaan surveilans gizi (Edisi ke-4). Diakses dari: https://repository.kemkes.go.id/book/581
Larasati, E. N., Dieny, F. F., Rahadiyani, A., & Purwanti, R. (2025). Utilization of E-PPGBM for analysing the relation between Posyandu visits post-covid-19 adaptation and low body weight history with stunting among toddlers in semarang city. Jurnal Gizi Indonesia (The Indonesian Journal of Nutrition), 13(2), 105-116.
Manjilala, M., & Ipa, A. (2024). Visualisasi data e-PPGBM menggunakan Google Data Studio. Media Gizi Pangan, 31(2).
Notoatmodjo, S. (2018). Metodologi penelitian kesehatan. Rineka Cipta.
Nutbeam, D., & Bauman, A. (2006). Evaluation in a nutshell: A practical guide to the evaluation of health promotion programs. McGraw-Hill.
Nurmandhani, R., Iqbal, M., Pradana, F. K., Wardoyo, A., Rimawati, E., & Setyawati, V. A. V. (2023). Pemetaan Distribusi Wasting dan Stunting di Wilayah Lokus Stunting Kabupaten Temanggung. Jurnal Manajemen Kesehatan Yayasan RS. Dr. Soetomo, 9(2), 321-331.
Prendergast, A. J., & Humphrey, J. H. (2014). The stunting syndrome in developing countries. Paediatrics and international child health, 34(4), 250-265.
Presiden Republik Indonesia. (2021). Peraturan Presiden Nomor 72 Tahun 2021 tentang Percepatan Penurunan Stunting. Diakses dari: https://peraturan.bpk.go.id/Details/174964/perpres-no-72%20tahun2021
Surmita, S., Sekartini, R., Kekalih, A., & Chandra, D. N. (2025). The role of dietary diversity and other factors to stunting among infants and toddlers in West Java, Indonesia. Egyptian Pediatric Association Gazette, 73(1), 71.
United Nations Children's Fund. (2021a). Data quality framework. Diakses dari: https://data.unicef.org/resources/data-quality-framework/
United Nations Children's Fund, World Health Organization, & World Bank Group. (2021). Levels and trends in child malnutrition: Key findings of the 2021 edition of the Joint Child Malnutrition Estimates. World Health Organization. Diakses dari: https://data.unicef.org/wp-content/uploads/2021/07/JME-2021-UNICEF-regions-web2.pdf
United Nations Children's Fund. (2021b). Strengthening nutrition information systems: Improving nutrition data for decision-making. Diakses dari: https://data.unicef.org/resources/strengthening-nutrition-information-systems/
World Bank Group. (2017). An investment framework for nutrition: Reaching the global targets for stunting, anemia, breastfeeding, and wasting. Diakses dari: https://www.worldbank.org/en/topic/nutrition/publication/investment-framework-nutrition
World Health Organization. (2021). Global strategy on digital health 2020–2025. Diakses dari: https://www.who.int/publications/i/item/9789240020924
World Health Organization, & United Nations Children's Fund. (2019). Recommendations for data collection, analysis and reporting on anthropometric indicators in children under 5 years old. World Health Organization. Diakses dari: https://www.who.int/publications/i/item/9789241515559
World Health Organization. (2022). Strengthening health information systems. Diakses dari: https://www.who.int/europe/teams/data-and-digital-health/strengthening-health-information-systems
World Health Organization. (2006). WHO child growth standards: Length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: Methods and development. https://www.who.int/publications/i/item/924154693X
Yushananta, P., Muslim, A., & Rusli, Y. (2023). Specific Determinants of Stunting Toddlers in Lampung Province: Spatial Data Analysis. Jurnal Kesehatan, 14(3), 462-474.
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