WORKSHOP MACHINE LEARNING KLASIFIKASI TUMOR OTAK PADA CITRA MRI MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DAN SUPPORT VECTOR MACHINE

  • Agus Eko Minarno Universitas Muhammadiyah Malang
  • Denar Regata Akbi Universitas Muhammadiyah Malang
  • Yuda Munarko Universitas Muhammadiyah Malang

Abstract

The brain is one of the organs that very important role for humans. Brain tumors can be a threat for humans. So that The researchers developed a CNN method that was tested effective for detecting brain tumors. CNN is a method that is quite popular, in its application it is used for image classification and several other image processing cases. CNN can be used to detect and recognize objects in an image better on an Artificial Neural Network. In addition, many researchers also use the SVM method, SVM can be applied to perform pattern recognition in the case of image processing. Brain tumors can be caused by the spread of cancer in parts of the other body. According to a report by the World Health Organization (WHO) brain cancer accounts for less than 2% of other cancers, but the severe morbidity and resulting complications are enormous. Brain cancer requires multidisciplinary treatment, so a professional standard policy is needed for optimal treatment. This activity proposes a Machine Learning Workshop on Brain Tumor Classification in MRI Imagery using CNN and SVM, in CNN activities can be divided into several parts such as CNN modeling, data preprocessing, building, and implementing CNN models in The SVM teaches how to build a hyperplane. This activity was delivered by expert speakers in their fields from alumni of the University of Muhammadiyah Malang.

Published
2022-09-16
How to Cite
[1]
A. Minarno, D. Akbi, and Y. Munarko, “WORKSHOP MACHINE LEARNING KLASIFIKASI TUMOR OTAK PADA CITRA MRI MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DAN SUPPORT VECTOR MACHINE”, PEDULI, vol. 6, no. 1, pp. 107-117, Sep. 2022.
Section
Articles