Peringkasan Dokumen Bahasa Indonesia Berbasis Non-Negative Matrix Factorization (NMF)
DOI:
https://doi.org/10.25126/jtiik.201411104Abstrak
Abstrak
Peningkatan teknologi informasi telah memicu peningkatan dokumen teks digital secara massif termasuk dokumen berbahasa Indonesia. Penggalian informasi dari dokumen berupa ringkasan secara otomatis sangat dibutuhkan. Pada penelitian ini peringkasan otomatis menggunakan Nonnegatif Matrix Factorization (NMF) telah dikembangkan. Sistem dievaluasi dengan membandingkan ringkasan sistem dengan ringkasan dari 3 orang pakar terhadap 100 dokumen bahasa Indonesia . Hasil evaluasi menunjukkan ringkasan sistem mempunyai rata-rata presisi dan recall masing-masing 0.19724 dan 0.34085. Sedangkan evaluasi ringkasan antar pakar mempunyai rata-rata presisi dan recall masing-masing 0.68667 dan 0.70642..
Kata kunci: peringkasan dokumen, NMF
Abstract
Improvement of information technology has led to increased massively digital text documents, including documents of Indonesian language. Extracting information from documents such as automatic summary is needed. In this study peringkasan automatically using non-negative Matrix Factorization (NMF) has been developed. The system was evaluated by comparing summary of system with summary of of three experts on 100 Indonesian documents. The evaluation shows summary of the system has an average precision and recall respectively 0.19724 and 0.34085. While the summary of an expert evaluation had an average precision and recall respectively 0.68667 and 0.70642.
Keywords: text summarization, NMF
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Referensi
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