Klasifikasi Komentar Judol pada Media Sosial dengan Menggunakan Metode Recurrent Neural Network dan Long Short-Term Memory

Abstract
The proliferation of online gambling promotional comments on Indonesian social media has become a serious issue requiring fast and accurate automated handling. This study aims to implement a Hybrid Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) method to classify online gambling comments and compare its performance with standalone RNN and LSTM models. The research utilized a dataset of 10,230 comments subjected to comprehensive preprocessing stages, including the normalization of non-standard language using a slang dictionary. Testing was conducted across three data-splitting scenarios: 90:10, 80:20, and 70:30. Experimental results demonstrate that the standalone LSTM model achieved the highest average accuracy of 97.45%. However, the Hybrid RNN–LSTM model showed significant superiority in terms of performance stability, yielding the lowest standard deviation (0.0027) and the smallest Coefficient of Variation (0.28%) across all scenarios. These findings indicate that while the LSTM architecture is highly effective at capturing short-text context, the Hybrid approach provides better robustness against fluctuations in data proportions, making it highly relevant for implementation as an automated detection system on social media.
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How to Cite

Ilham Saputra & Anita Qoiriah (2026). Klasifikasi Komentar Judol pada Media Sosial dengan Menggunakan Metode Recurrent Neural Network dan Long Short-Term Memory. Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika, 4(2). https://doi.org/10.61132/merkurius.v4i2.1565

Ilham Saputra; Anita Qoiriah, "Klasifikasi Komentar Judol pada Media Sosial dengan Menggunakan Metode Recurrent Neural Network dan Long Short-Term Memory," Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika, vol. 4, no. 2, 2026.

Ilham Saputra; Anita Qoiriah. "Klasifikasi Komentar Judol pada Media Sosial dengan Menggunakan Metode Recurrent Neural Network dan Long Short-Term Memory." Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika, vol. 4, no. 2, 2026.

Ilham Saputra; Anita Qoiriah. "Klasifikasi Komentar Judol pada Media Sosial dengan Menggunakan Metode Recurrent Neural Network dan Long Short-Term Memory." Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika 4, no. 2 (2026).

Ilham Saputra & Anita Qoiriah (2026) 'Klasifikasi Komentar Judol pada Media Sosial dengan Menggunakan Metode Recurrent Neural Network dan Long Short-Term Memory', Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika, 4(2). doi: 10.61132/merkurius.v4i2.1565.

Ilham Saputra; Anita Qoiriah. Klasifikasi Komentar Judol pada Media Sosial dengan Menggunakan Metode Recurrent Neural Network dan Long Short-Term Memory. Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika. 2026;4(2).

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