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A dempster-shafer approach to an expert system design in diagnosis of febrile disease

Pratama, Vincentius Andrew and Natalia, Friska (2018) A dempster-shafer approach to an expert system design in diagnosis of febrile disease. In: 4th International Conference on New Media Studies, 8-10 Nov. 2017, Yogyakarta, Indonesia.

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Official URL: https://ieeexplore.ieee.org/abstract/document/8266...

Abstract

In the past few decades, the use of expert system in information systems has become popular in many fields, such as in the health to diagnose some disease. Fever is a disease that is often considered common by the community as evidenced by data from a study where it was found that typhoid fever infected 800 to 100 thousand Indonesians citizen during 2008, while data collected by the Ministry of Health of the Republic of Indonesia in 2013, there have been 112,511 dengue cases Fever in 34 provinces in Indonesia and there were 871 people who died In order to help this cohort make decisions, our study proposed a design an expert system application to help rapid diagnose a disease with symptoms of fever by considering three kind of diseases: Typhoid Fever, Dengue Fever, and Measles. In this study, the system model gained from the Demspter Shafer method is shown in the implementation by using an example with mobile application.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Diseases , Expert systems , Mathematical model , Tongue , Stomach , Image color analysis , Information systems
Subjects: 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming
600 Technology (Applied Sciences) > 600 Technology > 600 Technology
600 Technology (Applied Sciences) > 610 Medicine and Health > 616 Diseases
T Technology > T Technology (General) > T55 Industrial engineering. Management engineering > T70 Information System
Divisions: Fakultas Teknik Informatika > Program Studi Sistem Informasi
Depositing User: mr admin umn
Date Deposited: 23 Nov 2021 05:31
Last Modified: 23 Nov 2021 05:31
URI: http://kc.umn.ac.id/id/eprint/19253

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