Implementasi Data Mining Untuk Memprediksi Penyakit Hipertensi Dalam Kehamilan Menggunakan Algoritma C4.5 (Study Kasus: Puskesmas Rimba Melintang, Rokan Hilir)

Widhiastuti, Efrika (2021) Implementasi Data Mining Untuk Memprediksi Penyakit Hipertensi Dalam Kehamilan Menggunakan Algoritma C4.5 (Study Kasus: Puskesmas Rimba Melintang, Rokan Hilir). Other thesis, Universitas Islam Riau.

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Abstract

Health is the most important aspect in every life, one of which is for pregnant women. There are so many pregnant women who are diagnosed with hypertension in pregnancy but it has not been properly recorded so that the treatment is not optimal. To predict hypertension in pregnancy in pregnant women at the Rimba Melintang Health Center, it takes a method commonly used to predict the disease, which is commonly known as data mining. In this study, the data analysis used in data mining uses a decision tree (decision tree) using the C4.5 algorithm and the accuracy test uses a confusion matrix. In this study, the information entered into the system is in the form of criteria for gestational hypertension. Testing the accuracy of the pregnancy hypertension prediction system is 82% so that it can be implemented.

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