Prediksi Tumor Otak Menggunakan Metode Convolutional Neural Network

Muhammad Nafi Maula Hakim, Arif Bagus Nugroho, Agus Eko Minarno

Abstract


Berkembangnya suatu teknologi membuat banyak pengaruh bagi beberapa sektor di bidang kesehatan.salah satunya adalah tumor otak. Klasifikasi tumor otak merupakan suatu penilitian yang penting untuk memprediksi hasil antara terinfeksi atau tidak. Pada penelitian ini dilakukan klasifikasi tumor otak dengan dataset berjumlah 300. Hasil yang diperoleh adalah akurasi sebesar 76% untuk model ANN dan 85% untuk model CNN].


Keywords


Convolutional Neural Network, Artificial Neural Network, Tumor Otak, Prekdiksi, Citra

Full Text:

PDF

References


Crowther, P. S., & Cox, R. J. (2005). A method for optimal division of data sets for use in neural networks. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3684 LNAI, 1–7. https://doi.org/10.1007/11554028_1

Goncharov, M., Pisov, M., Shevtsov, A., Shirokikh, B., Kurmukov, A., Blokhin, I., Chernina, V., Solovev, A., Gombolevskiy, V., Morozov, S., & Belyaev, M. (2021). CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification. Medical Image Analysis, 71, 102054. https://doi.org/10.1016/j.media.2021.102054

Harjoseputro, Y. (2018). Convolutional Neural Network (Cnn) Untuk Pengklasifikasian Aksara Jawa. Buana Informatika, 23.

Ilahiyah, S., & Nilogiri, A. (2018). Implementasi Deep Learning Pada Identifikasi Jenis Tumbuhan Berdasarkan Citra Daun Menggunakan Convolutional Neural Network. JUSTINDO (Jurnal Sistem Dan Teknologi Informasi Indonesia), 3(2), 49–56.

Irsyad, A., & Tjandrasa, H. (2021). Detection of COVID-19 from Chest CT Images Using Deep Transfer Learning. International Conference On Information & Communication Technology And System (ICTS).

Lu, H., Li, Y., Chen, M., Kim, H., & Serikawa, S. (2018). Brain Intelligence: Go beyond Artificial Intelligence. Mobile Networks and Applications, 23(2), 368–375. https://doi.org/10.1007/s11036-017-0932-8

Saood, A., & Hatem, I. (2021). COVID-19 lung CT image segmentation using deep learning methods: U-Net versus SegNet. BMC Medical Imaging, 21(1), 1–10. https://doi.org/10.1186/s12880-020-00529-5

Susmikanti, M. (2010). Pengenalan Pola Berbasis Jaringan Syaraf Tiruan Dalam Analisa Ct Scan Tumor Otak Beligna. 2010(Snati), 26–31.

Suta, I. B. L. M., Hartati, R. S., & Divayana, Y. (2019). Diagnosa Tumor Otak Berdasarkan Citra MRI (Magnetic Resonance Imaging). Majalah Ilmiah Teknologi Elektro, 18(2). https://doi.org/10.24843/mite.2019.v18i02.p01

Wahid, R. R., Anggraeni, F. T., & Nugroho, B. (2020). Implementasi Metode Extreme Learning Machine untuk Klasifikasi Tumor Otak pada Citra Magnetic Resonance Imaging. 1, 16–20.




DOI: http://dx.doi.org/10.30872/jim.v17i1.5246

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer

Editor Informatika Mulawarman Address:
ISSN 1858-4853 (Print) | ISSN 2597-4963 (Online)

Published by: Mulawarman University
Managed by : Informatika Department
Jalan Sambaliung No.9 Sempaja Selatan Samarinda Utara,
Kalimantan Timur 75117
 - Indonesia
E-mail: jim.unmul@gmail.com
OJS: http://e-journals.unmul.ac.id/index.php/JIM
Contact Person: Gubtha Mahendra Putra

 Creative Commons License

Informatika Mulawarman by http://e-journals.unmul.ac.id/index.php/JIM/index is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Under the CC BY-SA license, authors and other users are able to reprint, distribute or use the material for commercial purposes so long as they give attribution to the journal Informatika Mulawarman and license the republished material under the same license.