Infection in pregnant women is common and one of the highest causes of death in Indonesia. Reducing infection conditions through early infection prevention needs to be done, one of which is by knowing the characteristics that contribute to the incidence of infection in pregnant women in Indonesia. This study used the Classification and Regression Tree (CART) method to determine the pregnant women with infections and not infections characteristics and classify them. The results of the CART analysis found that seven variables contributed to separating infected and not-infected status in pregnant women, they are nutritional status based on Body Mass Index (BMI), history of anemia, pregnancy distance, Chronic Energy Deficiency (CED) status, ages, socioeconomic and gestational age. Characteristics of the highest incidence of infection, namely 79%, occurred in the group of pregnant women with overweight -obese (BMI>25.0), anemia and pregnancy distance <3 years. The classification analysis of the CART method in this study resulted in the accuracy of identification performance which was still not good, with an accuracy value of 52.78%. It is necessary analysis with other classification methods such as the Chisquare Automatic Interaction Detection (CHAID) in the future.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.