PENGELOMPOKKAN ARTIKEL ILMIAH MENGGUNAKAN MULTIBERT DAN K-MEANS

ARMANSYAH, RISKY and Yusliani, Novi and Rachmatullah, Muhammad Naufal (2025) PENGELOMPOKKAN ARTIKEL ILMIAH MENGGUNAKAN MULTIBERT DAN K-MEANS. Undergraduate thesis, Sriwijaya University.

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Abstract

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.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Scientific Article Clustering, MultiBert, K-Means, Silhouette Score
Subjects:	P Language and Literature > P Philology. Linguistics > P98-98.5 Computational linguistics. Natural language processing Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.D343 Data mining. Database searching. Big data. T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Risky Armansyah
Date Deposited:	23 Mar 2025 22:59
Last Modified:	23 Mar 2025 22:59
URI:	http://repository.unsri.ac.id/id/eprint/169916

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