Kartamanah, Fatih Fauzan (2025) Analyzing PEGASUS Model Performance with ROUGE on Indonesian News Summarization. Analyzing PEGASUS Model Performance with ROUGE on Indonesian News Summarization, 9 (1). pp. 31-42. ISSN 2541-2019
|
Text
14303-Article Text-20847-1-10-20250108.pdf Download (478kB) | Preview |
Abstract
Text summarization technology has been rapidly advancing, playing a vital role in improving information accessibility and reducing reading time within Natural Language Processing (NLP) research. There are two primary approaches to text summarization: extractive and abstractive. Extractive methods focus on selecting key sentences or phrases directly from the source text, while abstractive summarization generates new sentences that capture the essence of the content. Abstractive summarization, although more flexible, poses greater challenges in maintaining coherence and contextual relevance due to its complexity. This study aims to enhance automated abstractive summarization for Indonesian-language online news articles by employing the PEGASUS (Pre-training with Extracted Gap-sentences Sequences for Abstractive Summarization) model, which leverages an encoder-decoder architecture optimized for summarization tasks. The dataset utilized consists of 193,883 articles from Liputan6, a prominent Indonesian news platform. The model was fine-tuned and evaluated using the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) metric, focusing on F-1 scores for ROUGE-1, ROUGE-2, and ROUGE-L. The results demonstrated the model's ability to generate coherent and informative summaries, achieving ROUGE-1, ROUGE-2, and ROUGE-L scores of 0.439, 0.183, and 0.406, respectively. These findings underscore the potential of the PEGASUS model in addressing the challenges of abstractive summarization for low-resource languages like Indonesian language, offering a significant contribution to summarization quality for online news content.
| Item Type: | Article |
|---|---|
| Subjects: | Special Computer Methods Special Computer Methods > Artificial Intelligence Special Computer Methods > Blogs Mathematics Mathematics > Data Processing and Analysis of Mathematics Mathematics > Research Methods of Mathematics Technology, Applied Sciences Engineering Engineering > Engineers Engineering > Other Engineering Materials |
| Divisions: | Fakultas Sains dan Teknologi > Program Studi Teknik Informatika |
| Depositing User: | Fatih Fauzan Kartamanah |
| Date Deposited: | 11 Feb 2025 08:38 |
| Last Modified: | 11 Feb 2025 08:38 |
| URI: | https://digilib.uinsgd.ac.id/id/eprint/104259 |
Actions (login required)
 |
View Item |
