MODEL REGRESI LOGISTIK BINER PADA KEJADIAN BALITA STUNTING DI KECAMATAN LAWANG KIDUL KABUPATEN MUARA ENIM SUMATERA SELATAN

MAHARANI, AULIA MIFTA and Cahyawati S, Dian and Zayanti, Des Alwine (2024) MODEL REGRESI LOGISTIK BINER PADA KEJADIAN BALITA STUNTING DI KECAMATAN LAWANG KIDUL KABUPATEN MUARA ENIM SUMATERA SELATAN. Undergraduate thesis, Sriwijaya University.

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Abstract

This study aims to determine the binary logistic regression model and the variables that significantly affect the incidence of stunting in Lawang Kidul sub-district. The method used is binary logistic regression analysis for the dependent variable which is categorized into two, namely not stunted and stunted. The data analyzed were respondents aged 0-59 month who had stunted and normal nutritional status in three villages included in the Lawang Kidul District as many as 120 respondents. Some independent variables that are thought to affect the incidence of stunting are child gender, child birth weight, child immunization status, diseases that hinder the absorption of nutrients in children, early breastfeeding initiation in children, exclusive breastfeeding, complementary foods, formula milk consumption in children, mother's height, supplementary feeding in children, mother's latest education, mother's working status, family income and physical quality of clean water. The results of modelling using binary logistic regression for the incidence of stunting toddlers in logit form are g(x)=0,372-1,314X_2+4,233X_4(1) +1,543X_13(1) +2,493X_(14(1)). The model obtained was statistically significant at α=10%. The significant independent variables are child birth weight, diseases that prevent nutrient absorption in children, family income and physical quality of clean water. Furthermore, the Nagelkerke R^2 value of 0.601 was also obtained, which states that the ability of the independent variables to explain the variables affecting the incidence of stunting is 60.1%. The model provides a level of classification accuracy of prediction results of 89.17% where the classification results are in the Good Classification category, meaning that the model obtained has a very high accuracy in estimating the incidence of stunted toddlers in Lawang Kidul District.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Stunting, Ketepatan Klasifikasi, Regresi Logistik Biner
Subjects: Q Science > QA Mathematics > QA1-43 General
Divisions: 08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User: Aulia Mifta Maharani
Date Deposited: 25 Nov 2024 01:44
Last Modified: 25 Nov 2024 01:44
URI: http://repository.unsri.ac.id/id/eprint/159790

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