Skripsi

ANALISIS KINERJA KEYBART DAN TRANSFORMER UNTUK KEYPHRASE GENERATION PADA DATASET ARTIKEL ILMIAH

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Penilaian

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Keyphrase play an important role in applications such as information retrieval, text summarization, recommendation systems, and indexing of scientific documents. However, the automated process of generating key phrases still faces major challenges, especially when faced with complex English scientific articles rich in technical terms. Transformer-based generative approaches often produce phrases that are either irrelevant or too general. This study aims to evaluate the performance of KeyBART, a variant of BART customized for the task of keyphrase generation, to overcome these problems. Using 30,000 scientific articles as training data, KeyBART's performance is compared with the standard Transformer and evaluated using the F1-Score metric. Results show that KeyBART consistently generates more accurate key phrases, with an F1@M of 20.09% and F1@5 of 24.02%. These findings suggest that KeyBART is more effective in understanding scientific context and more reliable for automatically generating key phrases in scientific articles.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507003991	T177722	T1777222025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1777222025

Publisher

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

Collation

xv, 86 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

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Edition

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Subject(s)

Teknik Informatika

Specific Detail Info

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Statement of Responsibility

MI

Other version/related

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