Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal INFOKUM
Nur Hayati
Universitas Potensi Utama
Computer Science & IT

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

Found 1 Documents
Search
Journal : INFOKUM

 1 
Applications Based on Expert Systems For Early Diagnosing Anemia in Pregnant Women Meizar Abdul; Nur Hayati; Utami Utami
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (292.718 KB)

Abstract

Anemia in pregnant women is commonly called iron deficiency anemia with hemoglobin levels in red blood cells 10.0 grams/100 milliliters (10 grams/deciliter). This type of anemia is prone to be experienced by pregnant women because pregnant women must require very high oxygen levels. This type of anemia is not so dangerous but can be dangerous if there are congenital abnormalities of the body. Therefore, the authors feel it is important to identify this type of anemia early because there is a dangerous potential. The author makes an application based on an expert system that early diagnoses a pregnant woman with iron deficiency anemia or not. The method used is Bayes' theorem. The results obtained are efficiency and speed in early diagnosis of anemia in pregnant women used in hospitals. Coal Inalum. With a situation where the hospital only has one doctor serving many pregnant women patients. With the application of an expert system for early diagnosis of anemia in pregnant women, it can help users (doctors) in knowing the early symptoms of whether a pregnant woman has iron deficiency anemia or not.
Co-Authors Utami Utami