PEMERINGKATAN HALAMAN WEB PADA MESIN PENCARI INTERNET MENGGUNAKAN RANTAI MARKOV

Authors

  • Danny Irwan
  • Mahdhivan Syafwan
  • Monika Rianti Helmi

DOI:

https://doi.org/10.25077/jmu.8.2.181-187.2019

Abstract

Pemeringkatan halaman web didasarkan pada banyaknya jumlah kunjungan ke halaman web tersebut. Namun cara ini tidak efektif dilakukan untuk webgraph dengan skala besar. Untuk mengatasi permasalahan tersebut, digunakan rantai Markov. Masalah baru muncul ketika suatu webgraph memuat beberapa halaman web yang tidak mempunyai tautan luar ke halaman lainnya, sehingga hasil pemeringkatannya menjadi tidak realistis. Oleh karena itu, teknik dasar yang digunakan mesin pencari internet dalam pemeringkatan halaman web yaitu dengan metode rantai Markov menggunakan faktor redaman. Pada makalah ini dibahas langkah-langkah dalam pemeringkatan halaman web. Sebagai contoh, metode rantai Markov dengan faktor redaman diterapkan pada webgraph yang diperoleh dari EECS Instructional and Electronic Support University of California Berkeley. Dari hasil pemeringkatan diperoleh halaman dengan situs encyclopedia.com memiliki peringkat tertinggi karena berisi rangkuman informasi dari semua cabang ilmu pengetahuan.

Kata Kunci: Rantai Markov, Webgraph, Faktor Redaman

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Published

15-07-2019

Issue

Vol. 8 No. 2 (2019)

Section

Articles

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