Implementation of Decision Tree and Dempster Shafer on Expert System for Lung Disease Diagnosis

Abdul Muis Alfatah, ILKOM UNNES and Riza Arifudin, ILKOM UNNES and Much Aziz Muslim, ILKOM UNNES (2018) Implementation of Decision Tree and Dempster Shafer on Expert System for Lung Disease Diagnosis. Scientific Journal of Informatics, 5 (1). pp. 50-57. ISSN 2407-7658

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Abstract

The expert system is a computer system that contains set of rules to solve problems like an expert. The lungs are one of the vulnerable respiratory organs. The purpose of this research is to implement decision tree and dempster shafer method on lung disease diagnosis and measure the accuracy of the system. The symptom was searched using forward chaining decision tree and the diagnosis was calculated using dempster shafer method. Dempster Shafer method calculates the possibility of a lung disease based on the density of probability value that possessed by each symptom. This research used 65 data obtained from medical record of Puskesmas Tegowanu Grobogan Regency. General symptoms and types of disease are used as a variable. Based on the results of the study, it can be concluded that the results of the diagnosis using dempster shafer method has an 83.08% accuracy.

Item Type:	Article
Uncontrolled Keywords:	Expert System, Lung Disease, Decision Tree, Dempster Shafer
Subjects:	T Technology > Information and Computer > Expert System T Technology > Computer Engineering
Fakultas:	Fakultas Matematika dan Ilmu Pengetahuan Alam > Ilmu Komputer, S1
Depositing User:	mahargjo hapsoro adi
Date Deposited:	04 Oct 2019 14:34
Last Modified:	04 Oct 2019 14:34
URI:	http://lib.unnes.ac.id/id/eprint/33060

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