Authors:

Frisca Olivia Gorianto, I Gede Santi Astawa

Abstract:

“Breast cancer is still one of the leading causes of death in the world. Prevention can be done if the cancer can be recognized early on whether the cancer is malignant or benign. In this study, a comparison of malignant and benign cancer classifications was performed using two artificial neural network methods, which are the Feed-Forward Backpropagation method and the Elman Recurrent Neural Network method, before and after the feature selection of the data. The result of the study produced that Feed-Forward Backpropagation method using 2 hidden layers is better after the feature selection was performed on the data with an accuracy value of 99,26%.”

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PDF:

https://jurnal.harianregional.com/jlk/full-51874

Published

2019-12-01

How To Cite

GORIANTO, Frisca Olivia; SANTI ASTAWA, I Gede. Breast Cancer Classification Using Artificial Neural Network and Feature Selection.JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 8, n. 2, p. 113-117, dec. 2019. ISSN 2654-5101. Available at: https://ojs.unud.ac.id/index.php/JLK/article/view/51874. Date accessed: 28 Aug. 2025. doi:https://doi.org/10.24843/JLK.2019.v08.i02.p01.

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Issue

Vol 8 No 2 (2019): Jeliku Volume 8 No 2, November 2019

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License