Fakultas Teknologi Informasi

KLASIFIKASI SEL TUNGGAL PAP SMEAR BERDASARKAN ANALISIS FITUR DAN ANALISIS TEKSTUR TERSELEKSI MENGGUNAKAN CORRELATION-BASED FEATURES SELECTION BERBASIS DECISION TREE J48

Penulis
Dosen:
  1. ASTI HERLIANA
Eksternal:
  1. Dwiza Riana
Tanggal Terbit
03 Maret 2014
Kategori
Seminar Nasional [Lainnya]
Penerbit
Konferensi Nasional Ilmu Sosial dan Teknologi
Kota / Negara
Jakarta / Indonesia
Halaman
144-147
URL
https://seminar.bsi.ac.id/knist/index.php/UnivBSI/article/view/231
Abstrak
This research presents the texture classification of single cells Pap Smear. The single cells of Pap Smear have many kind of texture parameter that have been discovered by giffary, et al on 2012 research. By using the Correlation-based Features Selection (CFS) to select the texture parameter that produce correlation135, energy0, deviation and brightness as the best parameter to increase the classification result. In this research, the best parameter of texture was combined with Kerne_A and Cyto_A from the features parameter that has been discovered from Martin(2003) and Jantzen et al (2005). By using the method of Decision Tree Classifier to the six selected parameter (Correlation135, Energy0, Deviation, Brightness, Kerne_A and Cyto_A)result the accuracy about 90% for the two classes and about 67,87% for the seven classes.