Similaritas Dokumen Tugas Akhir Menggunakan Metode Rocchio

Authors

Keywords:

Dokumen Abstrak, Rocchio Relevance Feedback, Similaritas, TF-IDF

Abstract

Berkembangnya teknologi informasi yang sangat pesat memungkinkan pengolahan data semakin mudah dilakukan untuk dijadikan informasi yang bermanfaat bagi mahasiswa terutama dalam proses pembuatan tugas akhir. Sangat penting bagi mahasiswa untuk menghindari adanya kemiripan dokumen tugas akhir antara satu dengan lainnya. Penelitian ini menggunakan metode Rocchio karena memiliki konsep umum pada dokumen yang relevan dan non-relevan sebagai sarana meningkatkan pencarian untuk mengetahui kemiripan dokumen abstrak tugas akhir dengan dokumen abstrak lainnya. Tahapan dari penelitian ini terdiri dari proses case folding, filtering, tokenizing dan term weighting. Pada tahap term weighting atau pembobotan menggunakan metode TF-IDF. Setelah dilakukan pembobotan kata tiap dokumen abstrak, selanjutnya menghitung tingkat kemiripan dokumen abstrak dengan perhitungan modifikasi query berdasarkan persamaan rocchio relevance feedback. Berdasarkan hasil perhitungan kemiripan diperoleh ranking dokumen abstrak tugas akhir dengan nilai kemiripan tertinggi yaitu pada Dokumen 4 (D4) dengan nilai 48,1514. Dengan metode ini kedepannya dapat di implementasikan ke dalam pembuatan aplikasi.

References

Mandala, Rila dan Hendra Setiawan, “Peningkatan Performansi Sistem

Temu-Kembali Informasi dengan Perluasan Query Secara Otomatis” Laboratorium Keahlian Informatika Teori Departemen Sistem Informasi, Institut Teknologi Bandung, 2006.

Mandala Rila, The Exploration and Analysis of Using Multiple Types of Thesaurus for Query Expansion in Information Retrieval, Journal of Natural Language Processing, Volume 7, Number 2, pp.117-140, 2000

Mandala Rila, Improving Information Retrieval System Performance by Combining Text-Mining Techniques, International Journal of Intelligent Data Analysis, Volume 4, Number 6, pp. 489-511, IOS Press, ISSN : 1088-467X, 2000.

Salton G. and Buckley C., Improving Retrieval Performance by Relevance Feedback, Journal of American Society for Information Science 41(4) (1990), pp. 299-297.

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Published

2018-04-02

Issue

Vol. 3 No. 1 (2018): Prosiding Seminar Nasional Ilmu Komputer dan Teknologi Informasi (SAKTI)

Section

Articles

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