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PENGELOMPOKKAN ARTIKEL ILMIAH MENGGUNAKAN MULTIBERT DAN K-MEANS

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Penilaian

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The publication rate of scientific articles has significantly increased over time. This presents a challenge for journal administrators and academics in organizing and sorting these articles to align with the journal's scope. This study aims to address this issue by developing a scientific article clustering system utilizing MultiBERT as the data representation model and K-Means for cluster identification based on the representation results. The model was tested using article data from the Science and Technology Index (SINTA) 1 journals. The evaluation results for each journal yielded a silhouette score of 0.571, indicating well-clustered representations. Furthermore, testing across two journals with diverse topics yielded clusters that accurately corresponded to their respective subject areas.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507001877	T169916	T1699162025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1699162025

Publisher

: Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xii, 65 hlm.; ill.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Teknik Informatika

Specific Detail Info

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Statement of Responsibility

EM

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