Representation of Social Support in Social Media: Big Data Analysis to Understand the Cultivation of Religious and Ethical Character Values in the Digital Era

Authors

  • Muammar Khadapi STMIK KAPUTAMA
  • Hafizhah Hamim Nasution STKIP Budidaya Binjai

DOI:

https://doi.org/10.59934/jaiea.v5i2.2203

Keywords:

Character Education, Big Data Analytics, IndoBERT, Aggressive Social Support, Digital Ethics

Abstract

The digital transformation in the Society 5.0 era has altered the landscape of character education, wherein conflicts between teachers, students, and bureaucratic systems are now openly exposed in the digital public sphere. This study aims to deconstruct public perception and moral responses regarding the issue of teacher criminalization through a Computational Sociology approach. Utilizing Big Data Analytics methods, this research analyzes 2,803 digital interactions (comments) on the YouTube platform related to conflict cases involving honorary teachers.

The analysis was conducted using Deep Learning algorithms (IndoBERT) for sentiment classification and Latent Dirichlet Allocation (LDA) for topic modeling, with a model validation rate reaching 75%. The results indicate a phenomenon of digital ethical paradox, where 70.3% of public responses were dominated by negative sentiments. However, topic analysis reveals that this negativity is not a form of hatred toward the teaching profession, but rather a manifestation of "Aggressive Social Support." Public outrage is polarized around three crucial issues: resistance to illegal levy practices, criticism regarding the degradation of student/parental etiquette (adab), and demands for school leadership accountability.

This research concludes that society's digital footprint is an authentic reflection of collective unrest regarding structural injustices within education. The implications of this study emphasize the need for a redefinition of character education that not only focuses on students but also encompasses digital ethical literacy for the school ecosystem and legal protection reform for the teaching profession.

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References

M. Khadapi and V. M. Pakpahan, “Analisis Sentimen Berbasis Jaringan LSTM dan BERT terhadap Diskusi,” vol. 6, pp. 130–137, 2024.

B. Hasbullah, I. Rahayu, and D. G. Saputra, “The Role of Character Education in Building Ethics and Morality among Students in the Digital Age,” vol. 04, no. 01, pp. 33–39, 2025, doi: 10.55299/ijere.v4i1.1224.

I. W. E. Sudarmawan, M. A. Wardana, and I. M. H. Purnantara, “Enrichment : Journal of Management Stress coping mediates between social support and religiosity against family resilience in driver travel agents in Sanur,” vol. 12, no. 5, 2022.

W. B. Zulfikar, A. R. Atmadja, and S. F. Pratama, “Sentiment Analysis on Social Media Against Public Policy Using Multinomial Naive Bayes,” vol. 10, no. 1, pp. 25–34, 2023, doi: 10.15294/sji.v10i1.39952.

H. H. Nasution, “PKN DALAM KONTEKS EMBEDDING VALUE DAN KARAKTER BANGSA,” vol. 12, no. 2, pp. 54–60, 2023.

K. P. Sagala, L. Naibaho, and D. A. Rantung, “Tantangan Pendidikan karakter di era digital,” vol. 06, no. 1, pp. 1–8, 2024.

H. H. Nasution, S. F. Dewi, and A. Ananda, “Pengaruh Motivasi Belajar dan Lingkungan Keluarga terhadap Hasil Belajar PPKn Siswa,” vol. 7, no. 1, pp. 295–302, 2023.

S. Sumatra, “The Role of Teachers in the Development of Digital Literacy,” vol. 4, no. 2, pp. 538–552, 2025.

H. H. Nasution, “PENGARUH KOMPETENSI PEDAGOGIK GURU TERHADAP HASIL BELAJAR PPKn SISWA KELAS VIII MTsS NURUL FURQOON KOTA BINJAI,” vol. 12, no. 2, 2023.

F. Abdillah, G. Marhaenis, and H. Putro, “Digital Ethics : The Use of Social Media in Gen Z Glasses Etika Digital : Penggunaan Media Sosial pada Kacamata Gen Z,” pp. 158–171, 2022.

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Published

2026-02-15

How to Cite

Muammar Khadapi, & Nasution, H. H. (2026). Representation of Social Support in Social Media: Big Data Analysis to Understand the Cultivation of Religious and Ethical Character Values in the Digital Era. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 5(2), 3399–3404. https://doi.org/10.59934/jaiea.v5i2.2203