IKN Public Opinion on TikTok Before and After Efficiency Policy: CNN-LSTM on Imbalanced Data
DOI:
https://doi.org/10.29408/edumatic.v9i2.30123Keywords:
budget efficiency; cnn-lstm; imbalanced data; ibu kota nusantara; sentiment analysisAbstract
Growing polarization in Ibu Kota Nusantara (IKN) stems from conventional sentiment analysis tools’ inability to decode TikTok’s contextual complexities, particularly multimodal sarcasm and vernacular-policy relationships (e.g., mangkrak for project cancellations). This study develops a policy-aware hybrid model (CNN-BiLSTM + Policy Knowledge Graph) to decode TikTok’s multimodal sarcasm and vernacular-policy links (e.g., mangkrak), enabling: youth sentiment quantification post-IKN’s 73.3% budget cuts, social criticism-socio-political reality mapping, and evidence-based interventions mitigating Global South strategic project polarization. Using the Knowledge Discovery in Databases framework, we analyzed 2,950 high-engagement TikTok comments (≥10 interactions) from verified accounts (@Polindo.id and @geraldvincentt) across two periods: pre-policy (June-August 2024) and post-policy (January-March 2025). Methodologically, slang normalization, stemming, and minority-class weighting (15×) preceded classification via a CNN-BiLSTM architecture integrated with Policy Knowledge Graphs. Results showed an 18.88% reduction in negative sentiment (83.2%-8.7%), model accuracy of 94.13% (AUC-PR 0.91), and strong correlations between vernacular terms (e.g., mandek [stagnation]) and policy outcomes (r = -0.89; p < 0.01), with investor asing mentions surging 463% post-policy. These validate deep learning-enabled social listening for real-time policy diagnostics, with implications for fiscal transparency dashboards, algorithmic bias mitigation, and context-driven policy communication prioritizing vulnerable groups in SDG infrastructure governance.
References
Aufan, M. H., Handayani, M. R., Nurjanna, A. B., & Hendro, N. C. (2025). The Perceptions Of Semarang Five Star Hotel Tourists With Support Vector Machine On Google Reviews. Jurnal Teknik Informatika (JUTIF), 5(5), 1241–1247. https://doi.org/https://doi.org/10.52436/1.jutif.2024.5.5.2025
Cheng, Z., & Li, Y. (2024). Like, Comment, And Share On TikTok: Exploring The Effect Of Sentiment And Second-Person View On The User Engagement With TikTok News Videos. Social Science Computer Review, 42(1), 201–223. https://doi.org/10.1177/08944393231178603
Cinelli, M., De Francisci Morales, G., Galeazzi, A., Quattrociocchi, W., & Starnini, M. (2021). The Echo Chamber Effect On Social Media. Proceedings of the National Academy of Sciences, 118(9). https://doi.org/10.1073/pnas.2023301118
Dias, J. L., Sott, M. K., Ferrão, C. C., Furtado, J. C., & Moraes, J. A. R. (2021). Data Mining And Knowledge Discovery In Databases For Urban Solid Waste Management: A Scientific Literature Review. Waste Management & Research: The Journal for a Sustainable Circular Economy, 39(11), 1331–1340. https://doi.org/10.1177/0734242X211042276
Fadilah, U., & Ramdani, F. A. (2025). Public Policy Ethics In The Relocation Of The National Capital: Analysis Of Social, Economic, And Environmental Issues. Journal of Law Science, 7(1), 20–29.
Faturahman, A. A., Mubarok, A. M. S., Marta, I., Fauzi, R., & Septian, M. A. (2024). Dampak Positif Dan Negatif Pemindahan Ibu Kota Negara (IKN). Jurnal Perencanaan Wilayah Dan Pembangunan, 2(1), 18–29.
Ferdinand, A., Idris, A. S., Nurmiyati, N., Ding, I., Alaydrus, A., Jauchar B, J. B., Hastira, M. F., & Effendi, S. N. (2025). The Government’s Cultural Approach To Indigenous Communities In The Context Of Strengthening The Legitimacy Of Development Policies Of The Ibu Kota Nusantara (IKN). SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5077517
Fuentes, C., de Cea, M., & Miranda, C. (2025). A divided society: social perceptions about indigenous peoples’ rights in Chile. Canadian Journal of Latin American and Caribbean Studies / Revue Canadienne Des Études Latino-Américaines et Caraïbes, 50(1), 23–42. https://doi.org/10.1080/08263663.2024.2421120
Gupta, D., Bhargava, A., Agarwal, D., Alsharif, M. H., Uthansakul, P., Uthansakul, M., & Aly, A. A. (2024). Deep Learning-Based Truthful And Deceptive Hotel Reviews. Sustainability, 16(11), 4514. https://doi.org/10.3390/su16114514
Kalalinggi, R., Hisdar, M., Sarmiasih, M., & Wijaya, A. K. (2023). Forecasting The Development Of IKN (New National Capital) In Sustainable Development, Indonesia. Journal of Governance and Public Policy, 10(1), PRESS. https://doi.org/10.18196/jgpp.v10i1.16786
Kubin, E., & von Sikorski, C. (2021). The Role Of Social Media In Political Polarization: A Systematic Review. Annals of the International Communication Association, 45(3), 188–206. https://doi.org/10.1080/23808985.2021.1976070
Li, P., Zhang, J., & Krebs, P. (2022). Prediction Of Flow Based On A CNN-LSTM Combined Deep Learning Approach. Water, 14(6), 993. https://doi.org/10.3390/w14060993
Literat, I., Boxman-Shabtai, L., & Kligler-Vilenchik, N. (2023). Protesting The Protest Paradigm: TikTok As A Space For Media Criticism. The International Journal of Press/Politics, 28(2), 362–383. https://doi.org/10.1177/19401612221117481
Phalaagae, P., Zungeru, A. M., Yahya, A., Sigweni, B., & Rajalakshmi, S. (2025). A Hybrid CNN-LSTM Model With Attention Mechanism For Improved Intrusion Detection In Wireless IoT Sensor Networks. IEEE Access, 13, 57322–57341. https://doi.org/10.1109/ACCESS.2025.3555861
Plotnikova, V., Dumas, M., & Milani, F. (2020). Adaptations Of Data Mining Methodologies: A Systematic Literature Review. PeerJ Computer Science, 6, e267. https://doi.org/10.7717/peerj-cs.267
Rahman, R. I., Paramita, B. P., Putra, M. T. M., & Wulandari, S. N. R. (2024). The Legality of Tiktok in Indonesia. Jurisprudentie, 11(1), 37–46. https://doi.org/10.24252/jurisprudentie.v11i1.46577
Sánchez, A., Vidal-Silva, C., Mancilla, G., Tupac-Yupanqui, M., & Rubio, J. M. (2023). Sustainable E-Learning By Data Mining—Successful Results In A Chilean University. Sustainability, 15(2), 895. https://doi.org/10.3390/su15020895
Setiawan, A., & Suryono, R. R. (2024). Analisis Sentimen Ibu Kota Nusantara Menggunakan Algoritma Support Vector Machine Dan Naïve Bayes. Edumatic: Jurnal Pendidikan Informatika, 8(1), 183–192. https://doi.org/10.29408/edumatic.v8i1.25667
Shu, X., & Ye, Y. (2023). Knowledge Discovery: Methods From Data Mining And Machine Learning. Social Science Research, 110, 102817. https://doi.org/10.1016/j.ssresearch.2022.102817
Wang, Y.-C., Houng, Y.-C., Chen, H.-X., & Tseng, S.-M. (2023). Network Anomaly Intrusion Detection Based On Deep Learning Approach. Sensors, 23(4), 2171. https://doi.org/10.3390/s23042171
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