Implementasi Relevant Feedback Menggunakan Algoritma Genetika pada Dokumen Bahasa Indonesia (Implementation of Relevant Feedback Using Genetic Algorithm in Indonesian Documents)
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Abstract
Mesin pencarian telah banyak digunakan untuk membantu user dalam mendapatkan informasi yang dibutuhkan. Pada mesin pencarian saat ini, terdapat keterbatasan pada query. Sering kali, query tidak tepat tetapi user beranggapan bahwa informasi yang dibutuhkan ada pada mesin pencarian. Hasilnya, mesin pencarian akan menampilkan hasil meskipun query kurang spesifik. Oleh karena itu, untuk dapat memenuhi kebutuhan pengguna dalam menemukan dokumen yang sesuai, dibutuhkan mesin pencarian informasi baru. Pada penelitian ini, diterapkan metode relevance feedback menggunakan algoritma genetika untuk meningkatkan pencarian dokumen dengan memperbaiki query. Terdapat dua metode seleksi yang digunakan, yaitu roulette wheel selection dan tournament selection. Dengan menggunakan 1000 data, diperoleh hasil 58% rata - rata precision , 89% rata - rata recall, dan 59% rata-rata F-Measure pada roulette wheel selection. Adapun pada tournament selection diperoleh 57% rata - rata precision, 92% rata-rata recall, dan 60% rata-rata f-measure. Waktu komputasi roullete wheel selection rata-rata 10,23 detik, sedangkan untuk tournament selection adalah 5,97 detik.
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