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All Journal Jurnal Telematika
Elis Khatizah
Institut Pertanian Bogor
Computer Science & IT Electrical & Electronics Engineering

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Sentimen Publik Terhadap Kebijakan Pemindahan Ibu Kota Indonesia di X Menggunakan Model BiLSTM-CNN Wanda Nugraha; Mochamad Tito Julianto; Mohamad Khoirun Najib; Elis Khatizah
Jurnal Telematika Vol. 20 No. 2 (2025)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v20i2.796

Abstract

The development of Indonesia's new capital city, Ibu Kota Nusantara (IKN), is an innovative government policy that has sparked diverse public responses. This study aims to explore sentiment trends on the social media platform X to understand public perceptions of the policy. Additionally, a sentiment classification model combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) was developed and optimized through hyperparameter tuning. Exploratory analysis showed that positive sentiment dominated at 46%, followed by negative at 30% and neutral at 24%. The classification model achieved a test accuracy of 78% and an average accuracy of 81% across 10-fold cross-validation, with a standard deviation of 0.006. The achieved accuracy, together with the low cross-validation standard deviation, indicates that the BiLSTM-CNN model demonstrates stable and reliable performance.
Co-Authors Mochamad Tito Julianto Najib, Mohamad Khoirun Wanda Nugraha