The Implementation of Fuzzy Logic Algorithm In Android-Based Typhoid Fever Diagnostic Application

Suryani; Ahyuna; Magfirah; Michael  Oktavianus; Erni  Marlina; Asrul  Syam; Faizal

doi:10.47709/cnahpc.v5i1.2064

Authors

Suryani Universitas Dipa Makassar
Ahyuna Universitas Dipa Makassar
Magfirah Universitas Dipa Makassar
Michael Oktavianus Universitas Dipa Makassar
Erni Marlina Universitas Dipa Makassar
Asrul Syam Universitas Dipa Makassar
Faizal Universitas Dipa Makassar

DOI:

10.47709/cnahpc.v5i1.2064

Keywords:

Typhoid fever, Diagnosis, Application, Android, Fuzzy Logic

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Abstract

Typhoid fever is an infectious disease that causes death in Indonesia. This endemic disease has a high incidence rate and is a health problem related to the environment and sanitation. Problems due to limited time to consult directly with specialist doctors, it is not easy to consult with doctors at any time, and limited medical knowledge and experience, so it is difficult for the community to know and make an early diagnosis of the disease with symptoms of typhoid fever. This study created an Android-based application using a fuzzy logic algorithm for diagnosing typhoid fever. The application was built by adopting expert knowledge related to general and clinical symptoms that are often experienced by patients with typhoid fever, and data on the level of typhoid disease. Data collection was carried out through direct observation at the hospital and direct interviews with doctors. The data was processed to produce output in the form of diagnostic results and solution data recommended by the system. The application consists of 3 user levels, namely Admin who can process user data, Users who can diagnose their disease by inputting answers to questions in the application, and Experts who can process symptom data, disease level, and solution data. The research results are in the form of an application that can be used anytime as an alternative consultant that helps the community in diagnosing typhoid fever with output in the form of diagnostic results (negative typhoid, positive typhoid, or strong positive typhoid).

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