文章基本信息

标题：BAGGING CLASSIFICATION TREES UNTUK PREDIKSI RISIKO PREEKLAMPSIA (Studi Kasus : Ibu Hamil Kategori Penerima Jampersal di RSUD Dr. Moewardi Surakarta)
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作者：Moch. Abdul Mukid ; Triastuti Wuryandari ; Desy Ratnaningrum 等
期刊名称：MEDIA STATISTIKA
印刷版ISSN：1979-3693
电子版ISSN：2477-0647
出版年度：2015
卷号：8
期号：2
页码：111-120
DOI：10.14710/medstat.8.2.111-120
语种：English
出版社：MEDIA STATISTIKA
摘要：Preeclampsia is a spesific pregnancy disease in which hypertency and proteinuria occurs after 20 weeks of pregnancy. Classification Trees is a statistical method that can be used to identify potency of expectant women suffering from preeclampsia. This research aim to predict the risk of preeclampsia based on some individual variables. They are parity, work status, history of hypertension of preeclampsia, body mass index, education and income. To improve the stability and accuracy of the prediction were used the Bootstrap Aggregating Classification Trees method. By the method, classification accuracy reach to 86%. Keywords : Pre-eclampsia, Bagging CART, Classification Accuracy
其他摘要：Preeclampsia is a spesific pregnancy disease in which hypertency and proteinuria occurs after 20 weeks of pregnancy. Classification Trees is a statistical method that can be used to identify potency of expectant women suffering from preeclampsia. This research aim to predict the risk of preeclampsia based on some individual variables. They are parity, work status, history of hypertension of preeclampsia, body mass index, education and income. To improve the stability and accuracy of the prediction were used the Bootstrap Aggregating Classification Trees method. By the method, classification accuracy reach to 86%. Keywords : Pre-eclampsia, Bagging CART, Classification Accuracy