Klasifikasi Risiko Kehamilan Menggunakan Metode Decision Tree dan Algoritma C45
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Institusion
Politeknik Negeri Jember
Author
Septi, Kurnia Mutiara
Subject
458 - Teknik Informatika
Datestamp
2021-11-11 07:23:17
Abstract :
High-risk pregnancy is a pregnancy condition that can threaten the health and safety of the mother and fetus. This condition can be caused by complications during pregnancy, but it can also be caused by a medical condition that the mother has had since before pregnancy. In this study, there were 3 risks of pregnancy, namely low risk of pregnancy, high risk of pregnancy, and very high risk of pregnancy. There are 16 attributes in this study, namely age at first pregnancy, age of pregnant women, distance from marriage to pregnancy 1, distance from pregnancy to pregnancy, number of children, height ever, history of birth, previous caesar section, disease of pregnant women, type of twin pregnancy, babies stillbirth, preterm pregnancy, fetal position, bleeding, preeclampsia. Data mining with the C45 algorithm decision tree classification can be an alternative to classifying risks based on existing data opportunities. So that risks can be carried out accurately and help BPM Midwife Nikmaturrohma HS Amd, Keb in classifying pregnancy risks. Key words: Pregnancy Risk, C45 Algorithm, Classification
High-risk pregnancy is a pregnancy condition that can threaten the health and safety of the mother and fetus. This condition can be caused by complications during pregnancy, but it can also be caused by a medical condition that the mother has had since before pregnancy. In this study, there were 3 risks of pregnancy, namely low risk of pregnancy, high risk of pregnancy, and very high risk of pregnancy. There are 16 attributes in this study, namely age at first pregnancy, age of pregnant women, distance from marriage to pregnancy 1, distance from pregnancy to pregnancy, number of children, height ever, history of birth, previous caesar section, disease of pregnant women, type of twin pregnancy, babies stillbirth, preterm pregnancy, fetal position, bleeding, preeclampsia. Data mining with the C45 algorithm decision tree classification can be an alternative to classifying risks based on existing data opportunities. So that risks can be carried out accurately and help BPM Midwife Nikmaturrohma HS Amd, Keb in classifying pregnancy risks. Key words: Pregnancy Risk, C45 Algorithm, Classification
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