Analisis Jaringan Sanad Hadis melalui Centrality dan Common Link untuk Validitas Riwayat

Authors

  • Sadam Adam Universitas Islam Negeri Maulana Malik Ibrahim Malang, Indonesia, Indonesia
  • Nasrulloh Universitas Islam Negeri Maulana Malik Ibrahim Malang, Indonesia, Indonesia

Keywords:

Analisis jaringan sanad, Centrality Measures, standard link theory, validasi hadis, Social Network Analysis

Abstract

Penelitian ini mengkaji ulang dinamika transmisi hadis dengan memanfaatkan pendekatan Social Network analysis (SNA) untuk membaca struktur sanad secara lebih luas daripada model linear tradisional. Dengan memetakan perawi sebagai simpul dalam jaringan dan hubungan guru–murid sebagai keterhubungan langsung, penelitian ini menelusuri pola interaksi yang membentuk sebaran riwayat dalam Sahih al-Bukhari dan Sahih Muslim. Sebanyak 150 sanad dipilih melalui teknik purposive untuk melihat bagaimana ukuran-ukuran centrality—degree, Betweenness, closeness, dan eigenvector—mampu mengungkap posisi perawi yang berperan penting dalam proses transmisi. Analisis ini kemudian dikaitkan dengan konsep common link guna mengidentifikasi titik konvergensi jalur periwayatan. Hasil penelitian menunjukkan bahwa jaringan sanad memiliki karakteristik small-world, di mana beberapa perawi memainkan peran sentral sebagai penghubung antara berbagai komunitas ilmiah. Perawi dengan nilai Betweenness yang tinggi umumnya merupakan figur yang secara historis dikenal memiliki otoritas kuat dalam periwayatan, sehingga memperkuat korelasi antara posisi struktural dalam jaringan dan kredibilitas menurut ulama jarh wa ta‘dil. Temuan ini menegaskan bahwa integrasi pendekatan kuantitatif dan kritik sanad klasik dapat memberikan gambaran yang lebih komprehensif mengenai validitas riwayat, sekaligus membuka peluang pengembangan metode verifikasi hadis yang lebih adaptif terhadap kebutuhan akademik dan teknologi digital masa kini.

References

Al-'Asqalani, A. ibn H. (2002). Tahdhib al-Tahdhib (Vol. 1). Dar al-Fikr.

Al-Bukhari, M. ibn I. (1422 H). Kitab Bada' al-Wahy, Hadith No. 1. Dar Tawq al-Najah.

Al-Bukhari, M. ibn I. (1422 H). Sahih al-Bukhari. Dar Tawq al-Najah.

Al-Mizzî, Y. ibn 'A. (2002). Tahdhib al-Kamal fi Asma' al-Rijal. Mu'assasat al-Risalah.

Ali, M., Azmi, A. M., & Zainol, Z. (2023). Digital tools for hadith authentication: A systematic review. Journal of King Saud University - Computer and Information Sciences, 35(2), 189–204. https://doi.org/10.1016/j.jksuci.2023.01.015

Anugerah, A. R., Sensuse, D. I., Sucahyo, Y. G., & Gandhi, A. (2022). A systematic literature review of Social Network Analysis for construction project management. Buildings, 12(11), Article 1869. https://doi.org/10.3390/buildings12111869

Azami, M. M. (2023). Studies in Hadith Methodology and Literature. Islamic Book Trust.

Barabási, A.-L. (2022). Network Science. Cambridge University Press.

Barabási, A.-L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512. https://doi.org/10.1126/science.286.5439.509

Bloch, F., Jackson, M. O., & Tebaldi, P. (2023). Centrality Measures in networks. Social Choice and Welfare, 61, 413–453. https://doi.org/10.1007/s00355-023-01456-4

Bonacich, P. (2007). Some unique properties of Eigenvector Centrality. Social Networks, 29(4), 555–564. https://doi.org/10.1016/j.socnet.2007.04.002

Borgatti, S. P., Everett, M. G., & Johnson, J. C. (2018). Analyzing Social Networks (2nd ed.). SAGE Publications.

Brandes, U. (2001). A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25(2), 163–177. https://doi.org/10.1080/0022250X.2001.9990249

Brown, J. A. C. (2009). Hadith: Muhammad's Legacy in the Medieval and Modern World. Oneworld Publications.

Evans, S., & Chen, B. (2022). Linking the network Centrality Measures closeness and degree. Communications Physics, 5(1), Article 172. https://doi.org/10.1038/s42005-022-00949-5

Farooqi, M. A., Gul, F., Malik, M. S. A., & Khan, H. U. (2024a). Multi-IsnadSet: A large-scale multiplex network dataset of Hadith narrations for the scientific Hadith studies. Data in Brief, 54, 110366. https://doi.org/10.1016/j.dib.2024.110366

Farooqi, M. A., Gul, F., Malik, M. S. A., & Khan, H. U. (2024b). Multi-IsnadSet: A large-scale multiplex network dataset of Hadith narrations for the scientific Hadith studies. Social Network Analysis and Mining, 14(1), Article 50. https://doi.org/10.1007/s13278-024-01186-8

Farooqi, M. A., Khan, H. U., Malik, M. S. A., & Gul, F. (2023). Automated authentication of Hadith: A machine learning approach. IEEE Access, 11, 34567–34580. https://doi.org/10.1109/ACCESS.2023.3265789

Fernández-Peña, R., Molina-Montes, D., Wendy Lee, Y., Lee, H., & Hernández-Trova, S. (2022). Social Network Analysis for social and health support: A systematic scoping review protocol. BMJ Open, 12(9), e062463. https://doi.org/10.1136/bmjopen-2022-062463

Freeman, L. C. (1978). Centrality in social networks: Conceptual clarification. Social Networks, 1(3), 215–239. https://doi.org/10.1016/0378-8733(78)90021-7

Görke, A., & Schoeler, G. (2023). Reconstructing early Islamic history: The case of hadith transmission networks. Islamic Law and Society, 30(1-2), 45–78. https://doi.org/10.1163/15685195-bja10038

Hakak, S., Kamsin, A., Tayan, O., Idris, M. Y. I., Gani, A., & Zainol, A. (2022). Approaches for preserving content integrity of sensitive online Arabic content: A survey and research challenges. Information Processing & Management, 56(2), 367–380. https://doi.org/10.1016/j.ipm.2018.10.011

Khan, A. Z. (2021). Defining the criterion of authentication for hadith text. Al-Milal: Journal of Religion and Thought, 3(1), 1–19.

Mohamed, E., & Sarwar, R. (2022). Linguistic features evaluation for hadith authenticity through automatic machine learning. Digital Scholarship in the Humanities, 37(3), 830–843. https://doi.org/10.1093/llc/fqab096

Motzki, H. (2022). The question of the authenticity of Muslim traditions reconsidered: A structuralist approach. In Method and Theory in the Study of Islamic Origins (pp. 211–257). Brill.

Nasrulloh. (2014). Rekonstruksi Definisi Sunnah sebagai Pijakan Kontekstualitas Pemahaman Hadits. Ulul Albab, 15(1), 23.

Newman, M. E. J. (2023). Networks: An Introduction (3rd ed.). Oxford University Press.

Okamoto, K., Chen, W., & Li, X. Y. (2022). Ranking of closeness centrality for large-scale social networks. In Frontiers in Algorithmics (pp. 186–195). Springer. https://doi.org/10.1007/978-3-540-73814-5_17

Shatnawi, M., Shdefat, A., & Aldulaimi, S. H. (2023). Review of authentication techniques of Arabic Hadith. International Journal of Advanced Computer Science and Applications, 14(5), 734–742. https://doi.org/10.14569/IJACSA.2023.0140580

Valente, T. W., Coronges, K., Lakon, C., & Costenbader, E. (2023). How correlated are network Centrality Measures? Connections, 28(1), 16–26.

Wasserman, S., & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press.

Downloads

Published

2025-12-29

How to Cite

Adam, S., & Nasrulloh. (2025). Analisis Jaringan Sanad Hadis melalui Centrality dan Common Link untuk Validitas Riwayat. Jawahir Al-Ahadis, 1(2), 114–126. Retrieved from https://ejournal.uinbukittinggi.ac.id/index.php/jawahir/article/view/10508

Issue

Vol. 1 No. 2 (2025): December 2025

Section

Articles

Citation Check

License

Copyright (c) 2025 sadam adam, Nasrulloh

Creative Commons License

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