PREDIKSI PENYAKIT HATI DENGAN MENGGUNAKAN MODEL ALGORITMA NEURAL NETWORK

  • Wati Erawati (1*) Manajemen Informatika AMIK BSI Jakarta

  • (*) Corresponding Author
Keywords: Liver disease, Neural Network, Prediction

Abstract

The liver is one of the vital organs of the human body. Hepatosit is the main important part of a liver which is a unique epitel cell configuration. The liver disease should be predicted based on clinically tested because sometimes a doctor usually making a decision by using his/her intuition rather than to collect hidden data in a database. This problem causing refraction missed diagnostic, and over medical payment that influences service quality of a patient. Therefore, medically automatic diagnose system will be useful to carry on those problems. In this research, the Neural Network algorithm method is used to get liver disease prediction, Neural Network algorithm will be improved by using Adaboost method which is implemented into a patient who suffers from liver disease. The result of this experiment method is divided into 80%, 70%, and 60%, the accuracy points are 70.99%, 69.60%, 68.57%.

References

Anbarasi, M., Anupriya, E., & Iyengar, N. (2010). Enhanced Prediction of Heart

Disease with Feature Subset Selection using Genetic Algorithm. InternationalJournal of Engineering Science and Technology Vol. 2(10), 2010, 5370-53,5370-5376.

Janosi, A., & Steinbrunn, W. (2011, November 2013.UCI Machine Learning Repository. Retrieved from UCI MAchine Repository.

Karlik, Bekir. 2011. Hepatitis Disease Diagnosis Using Backpropagation and the Naïve Bayes Classifier. Konya. Turkey.

Lumongga, Fitriani. 2008. Struktur Liver. Medan

Purnomo, M. H., & Kurniawan, A. (2006). Supervised Neural Network dan Aplikasinya. Yogyakarta: Graha Ilmu.

Rohman, Abdul. 2009. Penerapan Algoritma C4.5 Berbasis Adaboost Untuk Prediksi Penyakit Jantung. Medan

Santoso, B. 2007. Data Mining Teknik Pemanfaatan Data untuk Keperluan Bisnis.Yogyakarta: Graha Ilmu.

Shukla, A., Tiwari, R., & Kala, R. 2010. Real Life Applications of Soft Computing.United States of America on: Taylor and Francis Group, LLC.

Wu, X., & Kumar, V. 2009. The Top Ten Algorithms in Data Mining. Boca Raton,London, New York: Taylor & Francis Group, LLC.

Wu, X., & Kumar, V. 2009. The Top Ten Algorithms in Data Mining. Boca Raton,London, New York: Taylor & Francis Group, LLC.
Published
2015-09-15
How to Cite
Erawati, W. (2015). PREDIKSI PENYAKIT HATI DENGAN MENGGUNAKAN MODEL ALGORITMA NEURAL NETWORK. Jurnal Techno Nusa Mandiri, 12(2), 157-166. https://doi.org/10.33480/techno.v12i2.446
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