Text

PENGELOMPOKKAN ARTIKEL ILMIAH MENGGUNAKAN MULTIBERT DAN K-MEANS

---

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.

---

Availability

Detail Information

Series Title

-

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

-

Classification

004.07

Content Type

-

Media Type

-

Carrier Type

-

Edition

-

Subject(s)

Teknik Informatika

Specific Detail Info

-

Statement of Responsibility

EM

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment