Implementasi Algoritma C5.0 Untuk Klasifikas Penyakit Gagal Ginjal Kronik

  • Setyowati Nurhaningsih Universitas Sebelas Maret
  • Yuliana Susanti Universitas Sebelas Maret
  • Sri Sulistijowati Handajani Universitas Sebelas Maret
Keywords: C5.0, Classification Tree, Accuracy Value

Abstract

Chronic kidney failure is one of the deadly diseases in many countries, including in In-donesia. This disease has a prevalence value increasing with the increasing population. Method that can be used to predict chronic kidney failure in the form of classification trees, namely C5.0. The purpose of this study is to apply the C5.0 to the classification of chronic kidney failure and to calculate the accuracy. Method C5.0 is a classification method in selecting its attributes to be processed using gain information. The independ-ent variables that are influential in this study are erythrocytes, urea, creatine, and plate-lets. The results of this study are in the form of a classification tree for chronic kidney failure. The C5.0 method produces 6 classification segments with an accuracy value of 99.3%.

References

Amalia, H, 2018, Perbandingan Metode Data Mining SVM dan NN untuk Klasifikasi Penyakit Ginjal Kronis, Jurnal Pilar Nusa Mandiri, Vol. 14 pp. 1, 1-5.

Loh, W. and Shih, T., 2001, Selection Methods for Classification Trees, Statistica Sinica 7, pp. 815-840.

Ocal, N., Ercan M. K., and Kadioglu, E., 2015, Predicting Financial Failure Using Decision Tree Algorithms: An Empirical Test on the Manufacturing Industry at Borsa Istanbul, International Journal of Economics and Finance, Vol. 7 pp. 189-206

Patil N, Lathi R, Chitre V, 2012, Customer Card Classification Based on C5.0 & CART Algorithms, International Journal of Engineering Research & Technology (IJERT), Vol. 2 pp. 164-167

Revathy, R and Lawrance, R., 2017, Comparative Analysis of C4.5 and C5.0 Algorithms on Crop Pest Data, International Journal of Innovative Research in Com-puter and Communication Engineering, Vol. 5 pp. 50-58

Riskesdas, 2013, Laporan Hasil Riset Kesehatan Dasar (Riskesdas), Badan Penelitian dan Pengembangan Kesehatan Kementerian RI, Jakarta

Smeltzer dan Bare, 2008, Buku Ajar Keperawatan Medikal Bedah, EGC, Ja-karta

Published
2019-05-30
How to Cite
Nurhaningsih, S., Susanti, Y., & Handajani, S. S. (2019). Implementasi Algoritma C5.0 Untuk Klasifikas Penyakit Gagal Ginjal Kronik. INTEK : Jurnal Informatika Dan Teknologi Informasi, 2(1), 26-31. https://doi.org/10.37729/intek.v2i1.89
Section
Articles