Case-Based Reasoning untuk Diagnosis Penyakit Jantung
Abstract: Case Based Reasoning
(CBR) is a computer system that used for reasoning old knowledge to solve new
problems. It works by looking at the closest old case to the new case. This
research attempts to establish a system of CBR
for diagnosing heart disease. The diagnosis process is done by inserting new cases containing
symptoms into the system, then the
similarity value calculation between cases
uses the nearest neighbor method similarity, minkowski distance
similarity and euclidean distance similarity.
Case taken is the case with the highest similarity value. If a case does
not succeed in the diagnosis or threshold <0.80, the case will be revised by
experts. Revised successful cases are stored to add the systemknowledge. Method
with the best diagnostic result accuracy will be used in building the CBR
system for heart disease diagnosis.
The test results using medical records data validated by expert indicate
that the system is able to recognize diseases heart using nearest neighbor
similarity method, minskowski distance similarity and euclidean distance
similarity correctly respectively of 100%. Using nearest neighbor get accuracy
of 86.21%, minkowski 100%, and euclidean 94.83%
Keywords: case-based
reasoning; nearest neighbor similarity; minkowski distance similarity;
euclidean distance similarity
Penulis: Eka Wahyudi
Kode Jurnal: jptinformatikadd170111
