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Hendri Noviyanto
Program Studi Sistem Komputer, Politeknik Pratama Mulia Surakarta
Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering

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Pencarian Fitur Optimal Halaman Web Menggunakan Kombinasi Algoritme Genetika dan Naive Bayes untuk Klasifikasi Hendri Noviyanto
Politeknosains Vol 18 No 1 (2019): Jurnal Politeknosains Volume 18 Nomor 1 - Maret 2019
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Politeknik Pratama Mulia Surakarta

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Abstract

The process of classification of web pages has problems in the selection of relevant features that affect the acquisition of value accuracy. These problems can be handled using feature selection techniques. Feature selection method works by evaluating and selecting relevant and informative features of each web page document. Features are a token or informative words that often appear on web pages. In this study, the method used is the genetic algorithm and decision tree incorporated in the wrapper technique. Genetic algorithms are used as subset selection and decision tree as attribute evaluators. The proposed method is able to reduce features by 45.39% for the WebKB dataset and 56.71% for the r8 dataset. Overall, the results of the classification process increased although not too significant.
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