Preeclampsia Classification Modeling Based on Fuzzy Rules

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Rizky Davit Nugroho, Agustinus Bimo Gumelar, Immah Inayati, Gerardo Agung Kridanto Laksono, Paul L. Tahalele, Eleonora Sianty Dewi, Benedictus T. R. Prabantoro, Alphonsus Warsanto, Febri Dwi Cahaya Putra, Randy Anwar Romadhonny, Wahyu Putra Adi Setiawan

2019 Proceedings - 2019 International Seminar on Application for Technology of Information and Communication: Industry 4.0: Retrospect, Prospect, and Challenges, iSemantic 2019 Conference paper Cited by 4 Quartile

Abstract

One of the main causes of maternal and infant mortality worldwide is Preeclampsia (PE). PE is a pregnancy disorder that affects 2% to 8% of all pregnancies. Early detection is an effort to prevent the occurrence of PE. PE can be identified through several risk factors. According to the National High Blood Pressure Education Working, PE can be classified as mild and severe. This study will make a classification model that can be used to identify PE by making fuzzy rules following PE risk factors. We use four variables as risk factors. These variables are systolic blood pressure, diastolic blood pressure, proteinuria, and gestational age. The first step in developing this model rule is to classify four variables that have been determined, the next step is to build a rule model based on the fuzzy set and membership function. The results of the development of this rule model get 51 rules that can be used to diagnose PE in pregnant women. © 2019 IEEE.

Affiliations

Fakultas Ilmu Komputer, Universitas Narotama, Surabaya, Indonesia; Faculty of Medicine, Widya Mandala Catholic University, Surabaya, Indonesia; Department of Surgery, Faculty of Medicine, Widya Mandala Catholic University, Surabaya, Indonesia; Department of Obstetrics and Gynecology, Faculty of Medicine, Widya Mandala Catholic University, Surabaya, Indonesia