International Journal Artificial Intelligent and Informatics
Vol. 1 No. 2 (2018)

Expert system for diagnosing diphtheria with k-nearest neighbor method

Chavid Syukri Fatoni (Universitas Amikom Yogyakarta)
Ema Utami (Universitas Amikom Yogyakarta)
Ferry Wahyu Wibowo (Universitas Amikom Yogyakarta)



Article Info

Publish Date
13 Dec 2018

Abstract

The Diphtheria cases have special concern by the Indonesian government and are recorded as an extraordinary case (KLB) in 2017. Diphtheria is an infectious disease and cause complications of dangerous and deadly diseases if have not any treated immediately. Along this time, the communities often underestimate the common symptoms of diseases, such as throat pain, flu, and fever. The similarity of Diphtheria symptoms with common diseases and complications such as myocarditis, obstruction on breath, Acute Kidney Injury (AKI), making Diphtheria are rather difficult to treat due to the infections spread quickly. Some complications of diphtheria can cause a death if have not treated immediately and there must be any identification early for diphtheria. Then, an expert system is needed to help the community and the government in diagnosing the diphtheria. An expert system is an information system containing knowledge from experts in order provide information to be used for consultation. The knowledge from experts in this particular system is used as a basis by the Expert System to answer the questions (consultation). The study used the K-Nearest Neighbor (KNN) method, which the method calculates the similarity value of Diphtheria disease symptom. As the result, it can provide an initial diagnosis for Diphtheria before complications occur. The output of this study is the diagnosis of diphtheria based on the symptoms with the accuracy results of 93.056%, as well as providing an initial diagnosis in order to have immediately treating the diphtheria. 

Copyrights © 2018






Journal Info

Abbrev

IJARLIT

Publisher

Subject

Computer Science & IT

Description

The journal scopes include (but are not limited to) the followings: Computer Science: Artificial Intelligence, Data Mining, Database, Data Warehouse, Big Data, Machine Learning, Operating System, Algorithm Computer Engineering: Computer Architecture, Computer Network, Computer Security, Embedded ...