Skripsi

KLASIFIKASI DAN DETEKSI KEMIRIPAN ARTIKEL BERBAHASA INDONESIA DI JURNAL BERKALA ILMIAH PADA GARBA RUJUKAN DIGITAL (GARUDA) MENGGUNAKAN METODE NAÏVE BAYES DAN COSINE SIMILARITY

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Penilaian

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The classification of articles into several categories has been done using the Naive Bayes method, with an F1-score result of 98% on balanced data based on titles and abstracts. The results show a high level of classification accuracy, with a processing time of less than 60 minutes. Similarity detection between articles was carried out using the Cosine Similarity method, and a similarity score of 0.071 was obtained, reflecting the low similarity level between articles. In this research, the score range used was 0 to 1, where a score close to 1 indicates the highest level of similarity. The search for similar scientific articles was conducted using the Cosine Similarity method based on titles and abstracts, by sorting articles by highest similarity score. The most similar articles are shown in the top order, and the search process takes 44 to 50 seconds to search time. The results of this research show that the method used can increase the accuracy in the classification process, similarity detection, and article search on the Garba Rujukan Digital (GARUDA) platform accurately and efficiently.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507003677	T176552	T1765522025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1765522025

Publisher

Indralaya : Program Magister Ilmu Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xi, 135 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Ilmu Komputer

Specific Detail Info

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Statement of Responsibility

MI

Other version/related

File Attachment

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