DIAGNOSIS PREEKLAMSIA PADA IBU HAMIL BERDASARKAN ALGORITME K- NEAREST NEIGHBOUR

Hidayat, Rifki (2020) DIAGNOSIS PREEKLAMSIA PADA IBU HAMIL BERDASARKAN ALGORITME K- NEAREST NEIGHBOUR. Other thesis, Universitas Amikom Purwokerto.

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Abstract

Maternal deaths are divided into two namely direct and indirect deaths. Globally 80% of direct maternal deaths, preeclampsia are included in direct maternal deaths. Preeclampsia conditions of pregnancy with hypertension occur after the 20th week in women who previously had normal blood pressure. Preeclampsia can also be characterized by hypertension (systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg) accompanied by proteinuria (≥ 300 mg / dl in tamping urine 24 hours). In this study, an analysis of medical records in the Purbalingga and Banyumas areas using 8 attributes, namely age, body weight, blood pressure, edema, multiple pregnancy, history of hypertension, how many children, urine protein, and preeclampsia class. From calculations using the K-NN (K-Nearest Neighbour) algorithm, the Sensitivity performance value of 98.19%, Specificity 100%, and Accuracy 98.33%.

Item Type: Thesis (Other)
Additional Information: Dosen Pembimbing: Tri Astuti, S.Kom., M.Eng.
Uncontrolled Keywords: Data Mining, K-NN Algorithm, Preeclampsia
Subjects: N Fine Arts > N Visual arts (General) For photography, see TR
T Technology > T Technology (General)
Depositing User: UPT Perpustakaan Pusat Universitas Amikom Purwokerto
Date Deposited: 08 Apr 2021 07:56
Last Modified: 08 Apr 2021 07:56
URI: http://eprints.amikompurwokerto.ac.id/id/eprint/871

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