The Infant Mortality Rate (IMR) is one of the main components to determining the degree of health and welfare people in the country. Indonesia is quite high IMR rate compared to Southeast Asian for of yellow fever. This fever usually appears in babies called new born jaundice. Babies can experience physiological and pathological depending on the symptoms. Parents often have difficulty distinguishing the difference between normal and severe fever without further examination, so that they do wrong in the initial treatment. Responding to the problems, it is necessary to conduct research on" Application of Fuzzy Logic Sugeno Methods for Diagnosis Yellow Fever". The aim of this research to minimizing IMR because this application can be used anytime and anywhere before being taken to the hospital. Sugeno Fuzzy logic is suitable method because it is very flexible to accepts tolerance for data that is not completely correct or wrong when they confused in determining the level of severity. This application will be carried out with an evaluation by expert using UAT (User Acceptance Testing) method to validation and verification. The output of this application is able to provide information about the percentage of the severity of yellow fever, history of diagnosis so that the condition of each user who uses the system can be monitored, initial treatment solutions.
Angka Kematian Bayi (AKB) di Indonesia masih tergolong cukup tinggi dibandingkan negara – negara Asia Tenggara. Hal tersebut perlu mendapatkan perhatian karena suatu negara dapat dinilai tingkat kesehatannya dari AKB. Salah satu penyebab AKB yang masih tinggi yaitu penyakit kuning pada bayi (Ikterus Neonatorum). Bayi dapat mengalami ikterus fisiologis (normal) maupun patologis (parah) bergantung dari gejala yang ditimbulkan. Dari kedua jenis ikterus tersebut sulit membedakan antara ikterus normal dan parah tanpa melakukan pemeriksaan lebih lanjut sehingga sebagian besar masyarakat salah dalam melakukan penanganan awal. Berdasarkan permasalahan tersebut, penulis akan membuat sistem informasi untuk diagnosis Ikterus Neonatorum. Dengan sistem tersebut, masyarakat mendapatkan edukasi mengenai ikterus neonatorum dan dapat mengetahui tingkat keparahan yang diderita oleh bayi. Sistem juga memberikan alternatif solusi yang dapat dilakukan saat bayi mengalami ikterus sesuai dengan tingkat keparahan. Penulis menggunakan logika fuzzy dengan metode sugeno untuk membantu melakukan diagnosis. Hasil yang ditampilkan yaitu berupa prosentase tingkat keparahan ikterus neonatorum. Setelah melakukan pengujian blackbox didapatkan hasil bahwa sistem sudah dapat bejalan sesuai dengan skenario yang diharapkan. Untuk pengujian UAT (User Acceptance Testing) didapatkan hasil sebesar 77,86 % yang dapat diartikan bahwa sistem sudah bisa diterima dengan baik oleh pengguna.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.