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

Tanggal

2014-08-11

Abstraksi

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.

References

Referensi Referensi utama adalah jurnal internasional Data yang digunakan dalam penelitian ini menggunakan data sumber dari Pap Smear Benchmark Data for Pattern Classification J.Jantzen l, J.Norup, G. Dounias and B.Bjerregaard, University Hospital Dept. of Pathology Harlev Ringvej 75, DK-2730 Harlev Denmark dan juga data penelitian dari Klasifikasi Statistikal Tekstur Sel Pap Smear Dengan Decision Tree T.Arifin, D.Riana and G.I.Hapsari, University BSI Bandung.