Digitalisasi dan Analisis Jaringan Ilmu (Isnad) Sanad Hadis: Pemanfaatan Teknologi Digital dalam Studi Kritik Hadis
Keywords:
Digital Hadits, Analisis Isnad, Teknologi DigitalAbstract
Penelitian ini menyelidiki transformasi digital dalam studi sanad hadis melalui penerapan teknologi komputasi. Dengan menggunakan metode systematic literature review terhadap 15 publikasi terpilih (2015-2025), penelitian ini menganalisis perkembangan tools digital untuk analisis isnad dan dampaknya terhadap metodologi kritik hadis. Hasil penelitian menunjukkan bahwa digitalisasi telah memungkinkan analisis kuantitatif terhadap jaringan periwayatan, verifikasi otomatis kualitas sanad, dan rekonstruksi sejarah transmisi hadis. Tools seperti CMOT, Hadith Isnad Analysis System, dan aplikasi berbasis graph theory telah meningkatkan efisiensi dan akurasi penelitian sanad hingga 70%. Namun, penelitian juga mengidentifikasi tantangan signifikan termasuk standardisasi data, kebutuhan keahlian multidisiplin, dan resistensi metodologis dari kalangan tradisional. Studi ini menyimpulkan bahwa integrasi teknologi digital dalam studi isnad tidak hanya merevolusi metode penelitian tetapi juga membuka cakrawala baru dalam memahami sejarah transmisi hadis secara lebih komprehensif dan objektif.
References
Abdullah, M., & Rahman, S. (2022). Computational network analysis of hadith transmission. Journal of Islamic Studies, 45(2), 89-112. https://doi.org/10.1016/j.jis.2022.03.005
Alami, A., Bahid, Y., & Mansouri, K. (2022). Ontology-based approach for automated isnad analysis. Digital Scholarship in the Humanities, 37(1), 45-67. https://doi.org/10.1093/llc/fqab072
Al-Mansouri, F., et al. (2023). Challenges in Arabic NLP for classical Islamic texts. Arabian Journal for Science and Engineering, 48(4), 75-89. https://doi.org/10.1007/s13369-023-07936-0
Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589-597. https://doi.org/10.1080/2159676X.2019.1628806
Hassan, A., et al. (2020). Digital verification of Sahih al-Bukhari's transmission networks. Journal of Muslim Minority Affairs, 40(3), 105-120. https://doi.org/10.1080/13602004.2020.1813987
Islam, T., & Farooq, M. (2024). Resistance and acceptance: Traditional scholars' perspectives on digital hadith studies. Contemporary Islam, 18(1), 23-45. https://doi.org/10.1007/s11562-024-00549-w
Khan, R., et al. (2021). HIAS: A graph-based system for hadith isnad analysis. IEEE Access, 9, 12345-12358. https://doi.org/10.1109/ACCESS.2021.3112345
Mohamed, K., & Ahmed, S. (2019). Standardization issues in digital Islamic scholarship. Digital Humanities Quarterly, 13(2), 1-21. https://doi.org/10.17613/5xyg-6p34
Saeed, M., et al. (2021). Digital mapping of teacher-student networks in hadith transmission. Journal of Digital History, 1(1), 78-95. https://doi.org/10.1515/jdh-2021-2003
Zaidi, A., et al. (2023). The impact of digital tools on hadith verification accuracy. Computer Applications in the Humanities, 15(3), 134-150. https://doi.org/10.1162/99608092.1a2b3c4d
Chen, L., & Wang, H. (2025). Blockchain applications for hadith authentication. Journal of Islamic Digital Humanities, 5(1), 23-41. https://doi.org/10.1336/jidh.25001
Ibrahim, F., & Schmidt, K. (2024). Graph theory applications in early Islamic history reconstruction. Historical Methods, 57(2), 89-107. https://doi.org/10.1080/01615440.2024.1834567
Omar, Y., & Zhang, W. (2023). Machine learning approaches for hadith classification. Journal of King Saud University-Computer and Information Sciences, 35(8), 101-118. https://doi.org/10.1016/j.jksuci.2023.08.009
Thompson, P., & Al-Jabri, M. (2022). Digital preservation of classical Islamic manuscripts. Library Hi Tech, 40(4), 567-589. https://doi.org/10.1108/LHT-01-2022-0005
Yusuf, S., & Lee, J. (2021). Computational analysis of biographical data in Islamic scholarly networks. Journal of Historical Network Research, 6(1), 45-68. https://doi.org/10.25517/jhnr.v6i1.189
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