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Analisis Kemiripan Judul Skripsi Menggunakan Pembobotan TF-IDF dan Metode Cosine Similarity Untuk Mencegah Duplikasi

SemanTIK: Teknik Informasi · Vol. 12 No. 1 (2026) · pp. 33–42

DOI
10.55679/semantik.v12i1.259
ISSN
2502-8928, 2460-1446
Published
2026-04-26
Publisher
Informatics Engineering Department of Halu Oleo University
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Kemiripan judul skripsi merupakan masalah yang kerap muncul pada tahap awal penyusunan tugas akhir mahasiswa, berpotensi menurunkan kebaruan penelitian dan menyulitkan proses bimbingan. Penelitian ini merancang dan mengimplementasikan sistem pendeteksi kemiripan judul skripsi berbasis web menggunakan Cosine Similarity dengan pembobotan TF-IDF. Sistem diimplementasikan menggunakan PHP dan MySQL. Data judul dikumpulkan secara manual dari para peneliti/mahasiswa di berbagai fakultas Universitas Sembilanbelas November Kolaka. Evaluasi penerimaan pengguna dilakukan dengan model Technology Acceptance Model (TAM) yang dimodifikasi dengan konstruk Trust & Perceived Accuracy. Hasil pengujian pada 45 responden menunjukkan nilai rata-rata PU = 4,09; PEOU = 4,03; TPA = 3,79; ATU = 3,97; BI = 3,88 (kategori: Tinggi). Sistem mampu mendeteksi kemiripan judul dengan cepat dan memberikan keluaran skor kemiripan yang dapat membantu proses validasi akademik. Rekomendasi pengembangan meliputi integrasi pendekatan semantik dan mekanisme pembaruan basis data otomatis. Title similarity among undergraduate theses reduces novelty and complicates supervision and assessment processes in higher education. This research designs and implements a web-based title similarity detection system using Cosine Similarity with TF-IDF weighting. The system is implemented using standard PHP and MySQL as the database. Thesis title data were collected manually from researchers and students across faculties at Universitas Sembilanbelas November Kolaka. User acceptance was evaluated using the Technology Acceptance Model (TAM) augmented with a Trust & Perceived Accuracy construct. The system demonstrates fast processing and reliable similarity scoring; TAM results (N = 45) indicate high acceptance across constructs (PU = 4.09; PEOU = 4.03; TPA = 3.79; ATU = 3.97; BI = 3.88). The proposed solution can support academic administration by early detection of title duplication and guiding revision processes. Recommendations for future work include semantic similarity integration and automated indexing for continuous database growth.

Keywords

Collaboration network of the authors

11 authors · 22 co-authorship links · 5 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Sembilanbelas November Kolaka
  • Politeknik Baubau
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
La SudarmanPoliteknik Baubau1
Poniasih LelawattyPoliteknik Baubau1
Sariani Nur ZunaisAffiliation unknown1
La SudarmanPoliteknik Baubau1
Abel HaryantoPoliteknik Baubau1
Eva EvaPoliteknik Baubau1

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://semantik.uho.ac.id/index.php/journal/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Analisis Kemiripan Judul Skripsi Menggunakan Pembobotan TF-IDF dan Metode Cosine Similarity Untuk Mencegah Duplikasi </dc:title>
	<dc:creator>Sarimuddin, Sarimuddin</dc:creator>
	<dc:creator>Nur Azlina</dc:creator>
	<dc:creator>Anggun, Anggun</dc:creator>
	<dc:creator>Khalifah , Vadilla Nur</dc:creator>
	<dc:creator>Nasarudin, Nasarudin</dc:creator>
	<dc:subject xml:lang="en-US">Cosine Similarity</dc:subject>
	<dc:subject xml:lang="en-US">TF-IDF</dc:subject>
	<dc:subject xml:lang="en-US">Kemiripan Judul Skripsi</dc:subject>
	<dc:subject xml:lang="en-US">TAM</dc:subject>
	<dc:description xml:lang="en-US">Kemiripan judul skripsi merupakan masalah yang kerap muncul pada tahap awal penyusunan tugas akhir mahasiswa, berpotensi menurunkan kebaruan penelitian dan menyulitkan proses bimbingan. Penelitian ini merancang dan mengimplementasikan sistem pendeteksi kemiripan judul skripsi berbasis web menggunakan Cosine Similarity dengan pembobotan TF-IDF. Sistem diimplementasikan menggunakan PHP dan MySQL. Data judul dikumpulkan secara manual dari para peneliti/mahasiswa di berbagai fakultas Universitas Sembilanbelas November Kolaka. Evaluasi penerimaan pengguna dilakukan dengan model Technology Acceptance Model (TAM) yang dimodifikasi dengan konstruk Trust &amp;amp; Perceived Accuracy. Hasil pengujian pada 45 responden menunjukkan nilai rata-rata PU = 4,09; PEOU = 4,03; TPA = 3,79; ATU = 3,97; BI = 3,88 (kategori: Tinggi). Sistem mampu mendeteksi kemiripan judul dengan cepat dan memberikan keluaran skor kemiripan yang dapat membantu proses validasi akademik. Rekomendasi pengembangan meliputi integrasi pendekatan semantik dan mekanisme pembaruan basis data otomatis.
Title similarity among undergraduate theses reduces novelty and complicates supervision and assessment processes in higher education. This research designs and implements a web-based title similarity detection system using Cosine Similarity with TF-IDF weighting. The system is implemented using standard PHP and MySQL as the database. Thesis title data were collected manually from researchers and students across faculties at Universitas Sembilanbelas November Kolaka. User acceptance was evaluated using the Technology Acceptance Model (TAM) augmented with a Trust &amp;amp; Perceived Accuracy construct. The system demonstrates fast processing and reliable similarity scoring; TAM results (N = 45) indicate high acceptance across constructs (PU = 4.09; PEOU = 4.03; TPA = 3.79; ATU = 3.97; BI = 3.88). The proposed solution can support academic administration by early detection of title duplication and guiding revision processes. Recommendations for future work include semantic similarity integration and automated indexing for continuous database growth.</dc:description>
	<dc:publisher xml:lang="en-US">Informatics Engineering Department of Halu Oleo University</dc:publisher>
	<dc:date>2026-04-26</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://semantik.uho.ac.id/index.php/journal/article/view/259</dc:identifier>
	<dc:identifier>10.55679/semantik.v12i1.259</dc:identifier>
	<dc:source xml:lang="en-US">SemanTIK : Teknik Informasi; Vol. 12 No. 1 (2026): Vol. 12 No. 1 (2026): SemanTIK Teknik Informasi; 33-42</dc:source>
	<dc:source>2502-8928</dc:source>
	<dc:source>2460-1446</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://semantik.uho.ac.id/index.php/journal/article/view/259/61</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Sarimuddin Sarimuddin, Nur Azlina, Anggun Anggun, Vadilla Nur Khalifah , Nasarudin Nasarudin</dc:rights>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>