Accuracy of Kidney Disease Expert System Based On Certainty Factor and Dempster Shafer Algorithm

  • Agussalim
  • Nani Astuti Triana Informatika STMIK Handayani Makassar
  • Eristya Maya Safitri Program Studi Sistem Informasi, Fakultas Ilmu Komputer Universitas Pembangunan Nasional “Veteran” Jawa Timur
  • Anita Wulansari Program Studi Sistem Informasi, Fakultas Ilmu Komputer Universitas Pembangunan Nasional “Veteran” Jawa Timur
  • Seftin Fitri Ana Wati Program Studi Sistem Informasi, Fakultas Ilmu Komputer Universitas Pembangunan Nasional “Veteran” Jawa Timur
Keywords: Certainty-Factor, Dempster Shafer, Expert System, Kidney Disease, Accuracy

Abstract

The information technology developments today resulted in several innovations, including the existence of an Expert System. The systems help diagnose diseases without directly meeting with experts/doctors. Many researchers have proposed algorithms to improve the accuracy of the expert system to approach the diagnosis by experts/doctors, including certainty factor and dempster shader. This study compares the algorithm's accuracy with the results of expert diagnosis of kidney disease. The expert system was developed using UML and a web-based version. From the comparison results, the dempster shaver algorithm has an accuracy rate of 80%, while the certainty factor is 60% compared to expert diagnoses.

Published
2022-06-05
Section
Articles