Diagnosis of Tuberculosis By Artificial Neural Network Algorithm

Authors

  • Amrin Amrin Universitas Bina Sarana Informatika

DOI:

10.33395/sinkron.v3i2.10028

Keywords:

Jaringan Syaraf Tiruan, confusion matrix, kurva ROC

Abstract

Sangat penting bagi dokter untuk melakukan diagnosa secara dini penyakit tuberculosis agar dapat mengurangi penularan penyakit tersebut kepada masyarakat luas.  Pada penelitian ini, penulis akan menerapkan metode klasifikasi data mining, yaitu Algoritma Jaringan Syaraf Tiruan untuk mendiagnosa penyakit tuberculosis. Berdasarkan hasil pengukuran performa dari model tersebut dengan  menggunakan  metode pengujian Cross Validation, Confusion Matrix dan Kurva ROC, diketahui bahwa algoritma jaringan syaraf tiruan memiliki tingkat akurasi sebesar 89,89% dan nilai area under the curva (AUC) sebesar 0,975. Hal ini menunjukkan bahwa model yang dihasilkan termasuk katagori klasifikasi  sangat baik karena memiliki nilai AUC antara 0.90-1.00.

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How to Cite

Amrin, A. (2019). Diagnosis of Tuberculosis By Artificial Neural Network Algorithm. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 3(2), 223-228. https://doi.org/10.33395/sinkron.v3i2.10028