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Jurnal SINTA 2

Peringkasan Dokumen Bahasa Indonesia Berbasis Non-Negative Matrix Factorization (NMF)

Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 1 No. 1 (2014) · pp. 39–44

DOI
10.25126/jtiik.201411104
ISSN
2528-6579, 2355-7699
Published
2014-07-12
Publisher
Fakultas Ilmu Komputer, Universitas Brawijaya
Language
en

Abstract

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

Collaboration network of the authors

10 authors · 17 co-authorship links

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  • University of Brawijaya
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
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Co-authorOrganisationJoint articles
Novanto YudistiraUniversity of Brawijaya2
Indriati .Affiliation unknown1
Fitra Abdurrachman BachtiarUniversity of Brawijaya1
Raga S. H. IstantoUniversity of Brawijaya1
Alvin Tarisa AkbarUniversity of Brawijaya1
Mohammad Alfiano Rizky MahardikaUniversity of Brawijaya1
Wayan Firdaus MahmudyUniversity of Brawijaya1
Nashi WidodoUniversity of Brawijaya1
Muhaimin Rifa’iUniversity of Brawijaya1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://jtiik.ub.ac.id/index.php/jtiik/en/oai, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="id">Peringkasan Dokumen Bahasa Indonesia Berbasis Non-Negative Matrix Factorization (NMF)</dc:title>
	<dc:creator xml:lang="en">Ridok, Achmad</dc:creator>
	<dc:description xml:lang="id">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</dc:description>
	<dc:publisher xml:lang="en">Fakultas Ilmu Komputer, Universitas Brawijaya</dc:publisher>
	<dc:date>2014-07-12</dc:date>
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	<dc:identifier>10.25126/jtiik.201411104</dc:identifier>
	<dc:source xml:lang="id">Jurnal Teknologi Informasi dan Ilmu Komputer; Vol 1 No 1: April 2014; 39-44</dc:source>
	<dc:source xml:lang="en">Jurnal Teknologi Informasi dan Ilmu Komputer; Vol. 1 No. 1: April 2014; 39-44</dc:source>
	<dc:source>2528-6579</dc:source>
	<dc:source>2355-7699</dc:source>
	<dc:source>10.25126/jtiik.201411</dc:source>
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