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All Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Indar Kusmanto
Universitas Tomakaka, Mamuju
Computer Science & IT Decision Sciences, Operations Research & Management

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Implementasi Metode Long Short-Term Memory (LSTM) untuk Klasifikasi Berita Online Berdasarkan Konten Teks Indar Kusmanto; Musliadi KH; Hidayat Hidayat; Kristian Kristian
Journal of Information System Research (JOSH) Vol 7 No 2 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i2.8628

Abstract

This study aims to classify Indonesian-language news using the Long Short-Term Memory (LSTM) method and to evaluate its performance through accuracy, precision, recall, and F1-score metrics. The dataset consists of 48,634 news titles collected from various national and regional portals, covering five main categories: finance, travel, health, food, and sports. The research process involves several text preprocessing stages-tokenization, stop-word removal, normalization, and stemming-followed by feature representation using word embedding and the design of the LSTM model architecture. The model's performance is assessed using a confusion matrix along with additional validation through cross-validation to ensure result consistency. The LSTM model demonstrates strong performance, achieving 90% accuracy, 89% precision, 88% recall, and 89% F1-score, indicating its capability to capture semantic patterns and contextual dependencies in textual data effectively. In addition, LSTM outperforms the baseline method with a 6% increase in accuracy, reinforcing its reliability for Indonesian text classification tasks. Overall, the findings confirm that the combination of optimal preprocessing techniques and a well-designed LSTM architecture enhances the performance of the news classification system and offers significant potential for various text analysis applications in the digital information era.
Co-Authors Hidayat Hidayat Kristian Kristian Musliadi K H