PEMODELAN REGRESI LOGISTIK ORDINAL PROPORTIONAL ODDS MODEL (Studi Kasus : Faktor-Faktor yang Mempengaruhi Status Gizi Balita di Puskesmas Umbulharjo I Yogyakarta 2022)

Nurul Amni, NIM.: 18106010018 (2022) PEMODELAN REGRESI LOGISTIK ORDINAL PROPORTIONAL ODDS MODEL (Studi Kasus : Faktor-Faktor yang Mempengaruhi Status Gizi Balita di Puskesmas Umbulharjo I Yogyakarta 2022). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Ordinal Logistic Regression is an analysis that describes the relationship between the dependent variable and the independent variable. The dependent variable in ordinal logistic regression amounts to more than two consecutive categories and the independent variables are categorical or continuous data with two or more variables. The model that is often used in ordinal logistic regression is a model that meets the assumption of parallel lines, which is called a proportional odds model. The proportional odds model is a model in which each cumulative logit has its own intercept, and has the same number of parameters. This study aims to model and determine the factors that have a significant effect on the assessment of the nutritional status of children under five at the Umbulharjo I Health Center in Yogyakarta in 2022. The data used is secondary data from 245 children under five based on an anthropometric assessment of body weight for age (W/U). with Very Low Weight, Low Weight, Normal Weight, and Over Weight categories. The results of the descriptive analysis show that out of 245 toddlers at the Umbulharjo I Yogyakarta Health Center in 2022, 76.73% have normal weight, 13.47% have a greater risk of weight, 8.57% have less weight, and 1.22 % are very underweight. Furthermore, the factors that significantly affect the nutritional status of toddlers at the Umbulharjo I Yogyakarta Health Center are birth length (OR=13.52), age (OR=0.73), current baby weight (OR=6.22), and gender (OR = 0.30).

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