Statistical Analysis of Infant Malnutrition Cases in North Sumatra Before and After COVID-19 Using the Wilcoxon Test
DOI:
https://doi.org/10.33005/jasid.v1i2.16Keywords:
Wilcoxon, Malnourisment, Covid-19, North Sumatera.Abstract
Child malnutrition remains a very important public health issue in Indonesia. Malnutrition is a condition of deficiency in energy and essential nutrients that can lead to impaired physical growth, mental development, and an increased risk of mortality in children. The prevalence of malnutrition among toddlers in Indonesia is still quite high and shows disparities between regions, especially in provinces with high poverty rates. One province of concern is North Sumatra, which, according to data from the Ministry of Health, has had a significant incidence of malnutrition in the last five years. This condition was exacerbated by the emergence of the COVID-19 pandemic at the end of 2019, which has had a major impact on various sectors of life, including family health and economy. The pandemic caused significant disruptions to primary healthcare systems, including a decrease in posyandu activities, immunizations, and monitoring of children's nutritional status. The decline in household income during the pandemic made it difficult for families to meet their balanced nutritional food needs. A UNICEF study showed an increased risk of acute malnutrition in children during the pandemic, especially in previously vulnerable areas. To measure the impact of the COVID-19 pandemic on the incidence of child malnutrition, a statistical approach that can compare data before and after the pandemic is needed. This study aims to analyze the difference in the incidence of child malnutrition before and after the COVID-19 pandemic in North Sumatra Province using the Wilcoxon test method. Using the Wilcoxon Signed-rank Test statistical method, a comparative analysis was performed between the medians of the data from 2018 and 2023. The results of the study showed that there was a difference between the medians of the two data sets.
References
Leviana, S. and Agustina, Y., 2023. Analisis Pola Makan dengan Status Gizi pada Siswa Kelas V SDN Jatiwaringin Bekasi. “Malahayati Nursing Journal”, 5(2), pp. 12–20.
Sinaga, T., Naibaho, D. and Pasaribu, I., 2017. Pengaruh Pendidikan Gizi Terhadap Pengetahuan, Praktik Gizi Seimbang dan Status Gizi pada Anak SD. Jurnal Gizi Indonesia, 6(2), pp. 35–43.
Briliannita, A., Lestaluhu, S. A. and Supu, L., 2022. Pengaruh Pemberian Makanan Padat Gizi Terhadap Perubahan Berat Badan Anak Usia 5–6 Tahun. “Ghidza: Jurnal Gizi dan Kesehatan”, 4(1), pp. 45–53.
Santi, N. P. E. C., Wulandari, I. A. and Suarmini, N. K. A., 2023. Hubungan Status Gizi dengan Kejadian Anemia pada Anak Usia 6–59 Bulan. “Jurnal Ilmiah Permas: Jurnal Ilmiah STIKES Kendal”, 13(2),
pp. 78–85.
Fitri, D., Sulistiyani and Antika, R. B., 2022. Pola Asuh Gizi terhadap Status Gizi Anak Balita Usia 6–24 Bulan. “Jurnal Kesehatan Polije”, 8(1), pp. 10–17.
Sinaga, S. E. N., 2023. Peningkatan Status Gizi Pada Siswa SMP Mardi Yuana Rangkasbitung. “Jurnal Skolastik Keperawatan”, 4(1), pp. 22–29.
Rizona, F., 2018. Pengaruh Edukasi terhadap Pengetahuan dan Sikap Jajanan Sehat Pada Anak Sekolah. “Jurnal Keperawatan Sriwijaya”, 5(1), pp. 56–63.
Ghozali, I., 2018. “Aplikasi Analisis Multivariate dengan Program IBM SPSS 25”. Semarang: Badan Penerbit UNDIP, pp. 100–112.
Trihendradi, C., 2011. “Statistik Nonparametrik dengan SPSS”. Yogyakarta: Andi Publisher, pp. 75–89.
World Health Organization, 2020. “Nutrition and Food Security During the COVID‑19 Pandemic”. Geneva: WHO, pp. 5–30.
FAO and WFP, 2021. “Impact of COVID‑19 on Food Security and Nutrition”. Rome: FAO, pp. 15–48.
Kementerian Koordinator PMK RI, 2022. “Laporan Dampak Sosial‑Ekonomi COVID‑19 Terhadap Kesejahteraan Anak”. Jakarta: Kemenko PMK, pp. 40–65.
E. Tarigan, A. J. Hadi, dan J. Sitorus, “Dampak Covid-19 Terhadap Angka Kejadian Stunting di Wilayah Kerja Puskesmas Batunadua Kota Padang Sidempuan,” Media Publikasi Promosi Kesehatan Indonesia (MPPKI), vol. 6, no. 2, pp. 157–164, 2023.
S. S. M. Wara, A. F. Adziima , M. Nasrudin and A. R. Pratama , "Predictive Analysis of Government Application Comment on Playstore with Clustered Support Vector Machine ," 2024 IEEE 10 th Information Technology International Seminar (ITIS), Surabaya, Indonesia, 2024, pp. 84-88, doi: 10. 1109/ITIS64716.2024.10845453.
A. Muhaimin, D. D. Prastyo and H. Horng-Shing Lu, "Forecasting with Recurrent Neural Network in Intermittent Demand Data," 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence), Noida, India, 2021, pp. 802-809, doi: 10.1109/Confluence51648.2021.9376880.
