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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Adri Triandhika Septyanto
Universitas Stikubank Semarang
Computer Science & IT

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Expert System for Diagnosing Newborn Babies Disease Using the Sorgenfrei Similarity Method Adri Triandhika Septyanto; Imam Husni Al Amin
Journal of Applied Informatics and Computing Vol 4 No 2 (2020): Desember 2020
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v4i2.2192

Abstract

Newborn neonates who are 0-28 days old. At that time the baby has a physical condition that is very weak and helpless to the surrounding environment. Newborns need special handling different from babies at the age of 1 month also above. Diagnosis also treatment is quickly required by the midwife in an emergency. Without there are still many midwives who have not been able to handle it properly, causing the baby's condition to become worse. To get fast and accurate handling information, we need a system in the form of an expert system. Expert systems can diagnose newborn diseases using the Sorgenfrei similarity algorithm. The system can display information about the type of disease, symptoms, solutions, and the percentage of similarity from the results of consulting the symptoms input. The results of testing the system with the consultation of the symptoms included got the highest percentage of similarity results 53.33%. The percentage of similarity results below 20% will be entered into the revised table which will later be corrected by experts. This expert system is built based on a website that can be accessed by all midwives who need handling information
Co-Authors Imam Husni Al Amin