Diagnosis of the type of delivery of pregnant women at Semen Padang Hospital Using the C4.5 Method

Rama Novialdi, D. Permana, Dodi Vionanda, F. Fitri
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Abstract

ABSTRACT The health of the mother and fetus is very important, but there are many challenges and risks associated with pregnancy and childbirth. According to WHO, in 2020 there were 287,000 cases of women dying during pregnancy and childbirth. Causative factors that affect the type of delivery include the age of pregnant women, MGG, systole, diastole, and pulse. One method that can be used to group the types of childbirth of pregnant women is classification. C4.5 is one of the methods used in forming decision trees to produce decisions. The purpose of C4.5 is to obtain attributes that will be the main criteria in the classification. Based on optimal tree results, the attribute that is the main criterion in classifying the type of delivery of pregnant women who give birth by cesarean section and normal delivery at Semen Padang Hospital is MGG. Determination of classification results using confusion matrix resulted in an accuracy value of 74%, sensitivity of 80% to classify the type of delivery of pregnant women who gave birth caesarean, and specificity of 66.67% to classify the type of delivery of pregnant women who gave birth normally.
使用 C4.5 方法诊断 Semen Padang 医院孕妇的分娩类型
ABSTRACT 母亲和胎儿的健康非常重要,但与怀孕和分娩相关的挑战和风险也很多。据世界卫生组织统计,2020 年将有 28.7 万名妇女死于妊娠和分娩。影响分娩类型的致病因素包括孕妇年龄、MGG、收缩期、舒张期和脉搏。对孕妇分娩类型进行分组的一种方法是分类法。C4.5 是形成决策树以产生决策的方法之一。C4.5 的目的是获得作为分类主要标准的属性。根据最优树的结果,在对三门巴东医院剖腹产和顺产孕妇的分娩类型进行分类时,作为主要标准的属性是 MGG。使用混淆矩阵确定分类结果的准确率为 74%,对剖腹产孕妇分娩类型分类的灵敏度为 80%,对顺产孕妇分娩类型分类的特异性为 66.67%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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