Sociotechnical Readiness for AI and Big Data-Based Educational Planning in PTKIS: A Case Study of STIT Rakeyan Santang

Zulfa - Fadilah(1*), Mulyawan Safwandy Nugraha(2),


(1) UIN Sunan Gunung Djati Bandung
(2) UIN Sunan Gunung Djati Bandung
(*) Corresponding Author

Abstract


Abstract :

The rapid development of Artificial Intelligence (AI) and Big Data has reshaped educational planning in higher education, shifting the focus from mere technology adoption to sociotechnical readiness. This study conceptualizes sociotechnical readiness as the dynamic interaction between technical subsystems, social subsystems, and their alignment in institutional contexts. This research focuses on Islamic religious higher education institutions (PTKIS), a case study of STIT Rakeyan Santang Karawang. This study uses a qualitative approach with a case study design. Data was collected through interviews, observations, and documentation studies of university leaders, as well as academic managers, who were selected deliberately. Data analysis was carried out themattically by referring to the three dimensions of STS, namely technical system, social system, and socio-technical suitability. The results of the study show that technical systems are still at the basic digitalization stage, which is characterized by limited analytics infrastructure, weak data governance, the absence of formal standard operating procedures (SOPs) related to data protection and privacy, and data conditions that are still fragmented on various learning platforms such as Learning Management System (LMS), Google Classroom, and interactive quiz applications. In the social dimension, digital competencies and organizational culture have not been evenly distributed and have not been institutionalized in a sustainable manner. This condition has an impact on the low sociotechnical compatibility between user needs and technological capabilities. This study concludes that the implementation of AI and Big Data-based learning in PTKIS depends on technical social readiness, which requires an educational planning strategy that integrates technical subsystems, social subsystems, and their alignment through the principle of joint optimization within the framework of the Technical Social System (STS), as evidenced by the case of STIT Rakeyan Santang.

Keywords: AI, Big Data, Digital Transformation Readiness, Sociotechnical Alignment

Abstrak :

Perkembangan pesat Kecerdasan Buatan (AI) dan Big Data telah membentuk kembali perencanaan pendidikan di pendidikan tinggi, mengalihkan fokus dari adopsi teknologi belaka ke kesiapan sosioteknis. Studi ini mengkonseptualisasikan kesiapan sosioteknis sebagai interaksi dinamis antara subsistem teknis, subsistem sosial, dan penyelarasannya dalam konteks kelembagaan. Penelitian ini berfokus pada lembaga pendidikan tinggi agama Islam (PTKIS), studi kasus STIT Rakeyan Santang Karawang. Penelitian ini menggunakan pendekatan kualitatif dengan desain studi kasus. Data dikumpulkan melalui wawancara, observasi, dan studi dokumentasi pimpinan universitas, serta manajer akademik, yang diseleksi dengan sengaja. Analisis data dilakukan secara tematik dengan mengacu pada tiga dimensi STS, yaitu sistem teknis, sistem sosial, dan kesesuaian sosial teknis. Hasil penelitian menunjukkan bahwa sistem teknis masih pada tahap digitalisasi dasar, yang ditandai dengan keterbatasan infrastruktur analitik, tata kelola data yang lemah, tidak adanya standar operasional prosedur (SOP) formal terkait perlindungan data dan privasi, serta kondisi data yang masih terfragmentasi pada berbagai platform pembelajaran seperti Learning Management System (LMS), Google Classroom, dan aplikasi kuis interaktif. Dalam dimensi sosial, kompetensi digital dan budaya organisasi belum merata dan belum dilembagakan secara berkelanjutan. Kondisi ini berdampak pada rendahnya kompatibilitas sosioteknis antara kebutuhan pengguna dan kemampuan teknologi. Penelitian ini menyimpulkan bahwa penerapan pembelajaran berbasis AI dan Big Data di PTKIS bergantung pada kesiapan sosial teknis, yang membutuhkan strategi perencanaan pendidikan yang mengintegrasikan subsistem teknis, subsistem sosial, dan penyelarasannya melalui prinsip optimasi bersama dalam kerangka Sistem Sosial Teknis (STS), terbukti dengan kasus STIT Rakeyan Santang.

Kata Kunci: AI, Big Data, Kesiapan Transformasi Digital, Penyelarasan Sosioteknis


Full Text:

PDF

References


REFERENCES

Anshori, I., Yansyah, D., Nasiroh, U., & Ismail, H. A. B. (2023). Integration of Artificial Intelligence in Education Management Systems to Improve the Quality of Islamic Education. Thawalib: Jurnal Kependidikan Islam, 6(2), 1–15. https://doi.org/10.54150/thawalib.v6i2.616

Bulut, O., Beiting-Parrish, M., Casabianca, J. M., & others. (2024). The Rise of Artificial Intelligence in Educational Measurement: Opportunities and Ethical Challenges. arXiv. https://arxiv.org/abs/2406.18900

Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165–1188. https://doi.org/10.2307/41703503

Cherns, A. (1976). The principles of sociotechnical design. Human Relations, 29(8), 783–792.

Emery, F. E., & Trist, E. L. (1960). Socio-technical systems. Tavistock Institute.

Hasan, M., & Abdullah, M. (2020). Digital readiness of Islamic higher education institutions in Indonesia. Journal of Islamic Education Studies, 8(1), 45–60.

Kaplan, A. M., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2019.01.001

Kementerian Agama Republik Indonesia. (2024). Laporan transformasi digital pendidikan tinggi keagamaan Islam 2023–2024. Direktorat Pendidikan Tinggi Keagamaan Islam. https://pendis.kemenag.go.id/direktorat-perguruan-tinggi-keagamaan-islam/kemenag-komitmen-hadirkan-layanan-digital-yang-cepat-dan-transparan

Laal, M. (2011). Knowledge management in higher education. Procedia Computer Science, 3, 544–549. https://doi.org/10.1016/j.procs.2010.12.090

Mahajan, P. (2025). What is Ethical: AIHED Driving Humans or Human-Driven AIHED? arXiv. https://arxiv.org/abs/2503.04751

Mallik, S., & Gangopadhyay, A. (2023). Proactive and Reactive Engagement of Artificial Intelligence Methods for Education: A Review. arXiv. https://arxiv.org/abs/2301.10231

Moleong, L. J. (2017). Metodologi penelitian kualitatif (Edisi revisi). Remaja Rosdakarya.

OECD. (2024). Artificial intelligence in higher education: Trends, analytics, and institutional transformation. OECD Publishing. https://doi.org/10.1787/ai-edu-2024-en

Rahardja, U., Rakhmansyah, M., Wijaya, S., & Anjani, S. A. (2025). Integration of Business Intelligence and Predictive Analytics for Student Success Based on Blockchain. Technomedia Journal, 10(1), 1–14. https://doi.org/10.33050/tmj.v10i1.2389

Rahmawati, S. (2021). Pemanfaatan big data analytics dalam evaluasi pembelajaran perguruan tinggi. Jurnal Teknologi Pendidikan, 23(2), 101–112.

Setiyo, H., Hadiati, E., & Setianingrum, D. A. (2025). AI and Digital Media: Enhancing Islamic Studies and Advancing Communication in Higher Education. KnE Social Sciences, 10(14), 1–8. https://doi.org/10.18502/kss.v10i14.19069

Trist, E. L., & Bamforth, K. W. (1951). Some social and psychological consequences of the longwall method of coal-getting. Human Relations, 4(1), 3–38. https://doi.org/10.1177/001872675100400101.

UNESCO. (2023). Global education monitoring report 2023: Technology in education—A tool on whose terms? UNESCO Publishing. https://doi.org/10.18356/9789210028660




DOI: 10.24235/jiem.v10i1.23722

Article Metrics

Abstract view : 0 times
PDF - 0 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2026 Zulfa - Fadilah, Mulyawan Safwandy Nugraha

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.