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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control)
Poniman, S.
Physics Faculty Of Mathematics And Natural Sciences, Udayana University, Denpasar, Indonesia
Computer Science & IT Electrical & Electronics Engineering

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The Utilization of Physics Parameter to Classify Histopathology Types of Invasive Ductal Carcinoma (IDC) and Invasive Lobular Carcinoma (ILC) by using K-Nearest Neighbourhood (KNN) Method Anak Agung Ngurah Gunawan; I Wayan Supardi; S. Poniman; Bagus G. Dharmawan
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (614.86 KB) | DOI: 10.11591/ijece.v8i4.pp2442-2450

Abstract

Medical imaging process has evolved since 1996 until now. The forming of Computer Aided Diagnostic (CAD) is very helpful to the radiologists to diagnose breast cancer. KNN method is a method to do classification toward the object based on the learning data which the range is nearest to the object. We analysed two types of cancers IDC dan ILC. 10 parameters were observed in 1-10 pixels distance in 145 IDC dan 7 ILC. We found that the Mean of Hm(yd,d) at 1-5 pixeis the only significant parameters that distingguish IDC and ILC. This parameter at 1-5 pixels should be applied in KNN method. This finding need to be tested in diffrerent areas before it will be applied in cancer diagnostic.
Classification of breast cancer grades using physical parameters and K-nearest neighbor method Anak Agung Ngurah Gunawan; S. Poniman; I. Wayan Supardi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.9797

Abstract

Breast cancer is a health problem in the world. To overcome this problem requires early detection of breast cancer. The purpose of this study is to classify early breast cancer grades. Combination of physical parameters with k-nearest neighbor Method is proposed to detect early breast cancer grades. The experiments were performed on 87 mammograms consisting of 12 mammograms of grade 1,41 mammograms of grade 2 and 34 mammogram of grade 3. The proposed method was effective to classify the grades of breast cancer by an accuracy of 64.36%, 50% sensitivity and 73,5% specitifity. Physical parameters can be used to classify grades of breast cancer. The results of this study can be used to complement the diagnosis of breast mammography examination.
Co-Authors A. A. Ngurah Gunawan Artawan, Made Dwi Bagus G. Dharmawan Gusti Ngurah Sutapa I Wayan Putu Sutirta Yasa I Wayan Supardi I Wayan Wisnawa Saputra Ida Bagus Made Suryatika Ida Bagus Putra Manuaba Made Dwi Artawan Made Hendra Hadinata Mahayani, Ni Wayan Dewi Ni Kadek Nova Anggarani Ni Wayan Dewi Mahayani Saputra, I Wayan Wisnawa Windarjoto Windarjoto