Faktor-Faktor yang Mempengaruhi Kejadian Stunting terhadap Balita menggunakan Analisis Regresi Logistik
DOI:
https://doi.org/10.31102/zeta.2022.7.2.47-52Keywords:
Binary Logistic Regression, Determination Value, Stunting, Toddler NutritionAbstract
Stunting is a condition of failure to thrive in toddlers due to chronic malnutrition, resulting in toddlers or children being too short for their age standards. The purpose of the study was to determine the factors that influence the incidence of stunting to toddlers at the Public Health Center Kasih Ibu airtiris, kampar. The method used in this study is the binary logistic regression method. Based on the results of the study indicate that the factors that influence the incidence of stunting in toddlers at Public Health Center Kasih Ibu airtiris, kampar namely the nutritional status of body weight based on age. The binary logistic equation with the resulting logit function is . The value of the determination of the classification of stunting events using binary logistic regression is 83,6%.
Downloads
References
Anindita Putri. 2018. Hubungan Tingkat Pendidikan Ibu, Pendapatan Keluarga, Kecukupan Protein & Zinc Dengan Stunting (Pendek) Pada Balita Usia 6-35 Bulan Di Kecamatan Tembalang Kota Semarang. Jurnal Kesehatan Masyarakat, Vol. 1, no. 2, hlmn. 617–626.
D.W. Hosmer and S. Lemeshow. (2000). Applied Logistic Regression, Second edi. Canada.
Faqih Achmad. (2020). Analisis Faktor Risiko Stunting menggunakan Regresi Logistik Biner. Skripsi, Uin Sunan Ampel, Surabaya.
Kemenkes RI. (2018). Situasi Balita Pendek (Stunting) di Indonesia, Jakarta Pusat Data dan Informasi Kemenkes RI, 2019. Laporan Pelaksanaan Integrasi Susenas Maret 2019 dan SSGBI Tahun 2019, Jakarta Badan Pusat Statistika.
Ramli, dkk. (2013). Perbandingan Metode Klasifikasi Regresi Logistik Dengan Jaringan Saraf Tiruan. Jurnal Eksponensia, Vol. 4, no. 1.
UNICEF. (2019). Improving Child Nutrition the Achievable Impreative for Global Progress, Plaza. New York.
WHO. (2010). Nutrition landscape information sytem (NLIS) country profile indicators : Interpretation guide, Wold Health. Geneva.
