Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Biner : Jurnal Ilmu Komputer, Teknik dan Multimedia
Fithrotun Nisa, Aida
Unknown Affiliation
Humanities Computer Science & IT Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Transportation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Sistem Pakar Untuk Mendiagnosa Gangguan Pada Ibu Hamil Dengan Menggunakan Metode Case Based Reasoning Berbasis Website Fithrotun Nisa, Aida; Jupron
BINER : Jurnal Ilmu Komputer, Teknik dan Multimedia Vol. 2 No. 5 (2024): BINER : Jurnal Ilmu Komputer, Teknik dan Multimedia
Publisher : CV. Shofanah Media Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pregnancy is a condition that is vulnerable to various disorders, both at the beginning and in the last weeks of pregnancy. Some disorders that are often experienced by pregnant women include hyperemesis gravidarum, preeclampsia, anemia, ectopic pregnancy, placenta previa, placental abruption, and urinary tract infections. Pregnancy disorders cannot be considered as ordinary disorders because they involve two lives, namely the lives of the mother and the unborn baby. Based on the 2012 Indonesian Demographic and Health Survey (SDKI), the maternal mortality rate (MMR) was 359 per 100,000 live births, which has increased compared to the 2007 survey which recorded the MMR at 228 per 100,000 live births. Therefore, this research develops an expert system to diagnose disorders in pregnant women using the Case Based Reasoning (CBR) method. The CBR method uses an approach by utilizing knowledge from old cases to provide solutions to new cases. The results of this research can provide information to pregnant women about various types of pregnancy disorders, so that they can know and understand the disorders they experience early on. This system is website-based, so pregnant women can access the application anywhere and anytime as long as they are connected to the internet. The highest diagnostic value based on the old case and new case approach was 38.89% with a diagnosis of placenta previa.
Co-Authors Jupron Jupron