Case Based Reasoning untuk Diagnosis Penyakit Jantung Menggunakan Metode Minkowski Distance

  • Eka Wahyudi Politeknik Negeri Ketapang
  • Novi Indah Pradasari Politeknik Negeri Ketapang

Abstract

Case Based Reasoning 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 minkowski distance similarity. Case taken is the case with the highest similarity value. If a case does not succeed in the diagnosis or threshold less than 0.80, the case will be revised by experts. Revised successful cases are stored to add the system knowledge. 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 minskowski distance similarity correctly of 100 percent. Using minkowski get accuracy of 100 percent.

 Keywords : Case Based Reasoning, Minkowski Distance Similarity.

References

Aamodt, A., dan Plaza, E (1994). Case Based Reasoning: Foundation Issues Methodological Variations. and Sistem Approaches, AI Communication IOS Press. 7, 1, 39-59.

Instalasi Catatan Medis. (2014). Data Rekam Medis. RS. Dr. Sardjito Yogyakarta. Yogyakarta.

Pal, S.K., dan Shiu, S.C.K.. (2004). Fondation of Soft Case-Based Reasoning. John Willey and Sons, Inc. New Jersey.

Hastie, T., Tibshirani, R., dan Friedman, J. (2009). The Element of Statistical Learning : Data Mining, Inference, and
Prediction, Springer Series in Statistic, 2. Springer-Verlag, Inc. New York.

Jha, M.K., Pakhira, D., dan Chakraborty, B. (2013). Diabetes Detection and Care Applying CBR Techniques. IJSCE, 6, 2. 132-137.

Mergio, J.M., dan Casanovas, M. (2008). The Induced Minkowski Ordered Weighted Averaging Distance Operator, ESTYLF08, Cuencas Mineras (Mieres-Langreo). Congreso Espanol sobre Tecnologiasy Logica Fuzzy. pp 35-41.

Nurdiansyah, Y., dan Hartati, S. (2014). Case-Based Reasoning untuk Pendukung Diagnosa Gangguan pada Anak Autis. Thesis. Prodi S2/S3 Ilmu Komputer, Universitas Gadjah Mada, Yogyakarta.

Witten, I.H., dan Frank, E. (2005). Data Mining : Practical Machine Learning Tools and Techniques, 2. Morgan Kaufmann Publisher. San Fransisco.
Published
2018-03-23
How to Cite
Wahyudi, E., & Pradasari, N. (2018). Case Based Reasoning untuk Diagnosis Penyakit Jantung Menggunakan Metode Minkowski Distance. INTECOMS: Journal of Information Technology and Computer Science, 1(1), 119-123. https://doi.org/https://doi.org/10.31539/intecoms.v1i1.170
Abstract viewed = 69 times
PDF downloaded = 55 times