Application of Fuzzy Logic Sugeno Method for Diagnosis Yellow Fever
- DOI
- https://doi.org/10.2991/assehr.k.210101.028How to use a DOI?
- Keywords
- application, detection, fuzzy Sugeno
- Abstract
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.
- Copyright
- © 2021, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Trismayanti Dwi Puspitasari AU - Ria Chandra Kartika AU - Jazil Ramadhanty PY - 2021 DA - 2021/01/02 TI - Application of Fuzzy Logic Sugeno Method for Diagnosis Yellow Fever BT - Proceedings of the First International Conference on Social Science, Humanity, and Public Health (ICOSHIP 2020) PB - Atlantis Press SP - 129 EP - 133 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.210101.028 DO - https://doi.org/10.2991/assehr.k.210101.028 ID - Puspitasari2021 ER -