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.

Highlights

  • Expert systems are part of the high-level software or high-level programming language which attempt to duplicate the expert functionality in a particular area of expertise [1]

  • Dempster shafer method and decision tree is a method to calculate the uncertainty of a problem, this uncertainty is due to the addition of new facts

  • Dempster shafer can optimize the diagnosis that is produced because the system is based on the rule but has a value

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Summary

Introduction

Expert systems are part of the high-level software or high-level programming language which attempt to duplicate the expert functionality in a particular area of expertise [1]. It can be used to overcome multiple problems by giving some advice like an expert knowledge [2]. The problem that needs to be solved is the algorithm and the expert-field problem that is difficult to understand [3]. The expert system is software-based systems that create or evaluate decisions based on rules defined in the software [5]. The purpose of the expert system is not to replace human role, but to represent a human knowledge into a system form, so that it can be used by many people [6]. Expert system provides good results for solving cases that use complex data, such as skin disease diagnosis, pregnancy illness diagnosis, asset damage analysis and digestive disease diagnosis [710]

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