Journal of Applied Data Sciences
Vol 1, No 2: DECEMBER 2020

Diagnosis of Preeclampsia in Pregnant Women Based on K-Nearest Neighbor Algorithm

Rifki Hidayat (Departement of Information Systems, Universitas Amikom Purwokerto, Indonesia)
Tri Astuti (Departement of Information Systems, Universitas Amikom Purwokerto, Indonesia)



Article Info

Publish Date
01 Dec 2020

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 Neighbor) algorithm, the Sensitivity performance value of 98.19%, Specificity 100%, and Accuracy 98.33%.

Copyrights © 2020






Journal Info

Abbrev

JADS

Publisher

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

Description

One of the current hot topics in science is data: how can datasets be used in scientific and scholarly research in a more reliable, citable and accountable way? Data is of paramount importance to scientific progress, yet most research data remains private. Enhancing the transparency of the processes ...