PENGELOMPOKAN ARTIKEL ILMIAH MENGGUNAKAN ROBERTA DAN K-MEANS

JAHROO, JIHAAN JASMINE and Yusliani, Novi and Rodiah, Desty (2025) PENGELOMPOKAN ARTIKEL ILMIAH MENGGUNAKAN ROBERTA DAN K-MEANS. Undergraduate thesis, Sriwijaya University.

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Abstract

The significant increase in the number of scientific articles published each year presents challenges in managing and utilizing information efficiently. This research aims to develop an automatic scientific article clustering system using a combination of RoBERTa method and K-Means algorithm, as well as evaluate its performance based on the Silhouette Score. The research data consists of 8,675 scientific articles collected through scraping techniques from 12 Sinta-accredited journals (ranks 1-4). The results show variations in clustering performance, with the highest Silhouette Score of 0.8834 for the Obsession Journal: Early Childhood Education Journal and the lowest of 0.5523 for the Journal of Business and Accounting. Data injection testing was conducted to evaluate the relevance between journals, where articles were classified as in-scope or out-scope based on their distance to the cluster centroid.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Jurnal Ilmiah, Pengelompokan Artikel Ilmiah, RoBERTa, 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:	Jihaan Jasmine Jahroo
Date Deposited:	13 Mar 2025 02:39
Last Modified:	13 Mar 2025 02:39
URI:	http://repository.unsri.ac.id/id/eprint/168528

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