LOW BIRTH WEIGHT MODELING WITH LOGISTIC REGRESSION IN CENTRAL BUTON

Abstract

Low Birth Weight (LBW) is a baby's weight at birth less than 2,500 grams. The birth of LBW babies is a major contributor to both short and long term neonatal morbidity and death. The number of LBW in Central Buton Regency reported in 2021 is getting worse than in 2020. Therefore, Logistic Regression Analysis in needed to identify and model the factors that influence LBW cases in Central Buton district. The data used in this study is secondary data on the population of birth weight in infants during the period January – June 2022. Data was obtained from the Medical Record of Puskesmas in Central Buton district, Mawasangka district area and Gu district area. The number of samples in the study was 327 infants. The model produced in this study is ĝ(x) = -37535 + 2,3562X1 + 1,2097X2 + 1,4590X4. From this model, it is known that the factors that significantly affect LBW in Buton Tengah Regency are gestational age (X1), Hb levels (X2) and pregnancy complications (X4) with an accuracy value of 90,51%.
Keywords: Low Birth Weight, Logistic Regression Analysis