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All Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Haidar Natsir Amrullah
Shipbuilding Institute of Polytechnic Surabaya
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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An application of ANFIS for Lung Diseases Early Detection System Mochamad Yusuf Santoso; Am Maisarah Disrinama; Haidar Natsir Amrullah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 1, February 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (500.802 KB) | DOI: 10.22219/kinetik.v5i1.996

Abstract

Indonesian Basic Health Research in 2018 showed the prevalence of pneumonia, pulmonary tuberculosis (TB) and lung cancer in Indonesia 4.0% 0.4% and 0.18%, respectively. However, the number of lung specialists is small. According to the Indonesian Lung Specialist Association webpage, the number of doctors joined in the association up to 2008 were 452. This amount is very less when compared with existing lung disease cases. Thus, the handling of lung disease will be too late. The use of ANFIS for early detection of lung disease is growing. However, the systems designed are need preprocessing data to be executed and still applied for one type of disease. This paper will design a desktop application based on ANFIS expert system to detect lung disease early, i.e. for pneumonia, pulmonary TB and lung cancer. The system will work based on simple symptoms expressed by the patient. Subtractive clustering is used for clustering process. The results of the training showed that the models were able to give better performance compared to the model built using conventional clustering methods. The test results show that those three models have comparable performance compared to their counterpart. Software validation shows that the it gives 94.00% succeed for training data and up to 100% for testing data. This application is not intended to replace the role of a doctor, but to help diagnose the patient's condition earlier.
Co-Authors Am Maisarah Disrinama Mochamad Yusuf Santoso