Appreciating Hadith Chain Assessment of Classical Scholarship with the Aid of Learning Kit and Network Security Analogy

Appreciating Hadith Chain Assessment of Classical Scholarship with the Aid of Learning Kit and Network Security Analogy

Nuzulha Khilwani Ibrahim¹*, Suhaila Samsuri², Muhamad Sadry Abu Seman², Mira Kartiwi², Ahmed ElMogtaba Banga Ali³, Norzihani Yusof¹

¹Fakulti Technology Maklumat dan Komunikasi, University Technical Malaysia Melaka (UTeM), Malaysia

^2,3Kuliyyah of Information and Communication Technology, International Islamic University Malaysia (IIUM)

DOI: https://dx.doi.org/10.47772/IJRISS.2025.909000540

Received: 10 September 2025; Accepted: 16 September 2025; Published: 17 October 2025

ABSTRACT 

Appreciating the extensive contributions of classical scholars in Hadith chain assessment is crucial in the present context. Their rigorous and systematic efforts, often requiring a lifetime of dedication, established the methodological foundations upon which contemporary Hadith chain studies continue to rely. Valuing these contributions not only preserves the continuity of scholarly tradition but also safeguards the integrity and authenticity of Islamic knowledge in modern times. Therefore, this study is introducing a learning kit designed to serve as an educational tool for understanding classical Hadith chain assessment in a more systematic and accessible manner, with the aid of network security analogy. Specifically, the framework adapts layered security and verification mechanisms commonly applied in Internet banking to the assessment of Hadith narrators (Isnad or Chain). The methodology involves extracting narrator data from Al-Adab Al-Mufrad and related classical sources, followed by the development of an authentication process structured in three layers: (i) confirming narrator identity sequences, (ii) verifying detailed attributes including biographical and reliability information, and (iii) consolidating all criteria for authentication outcomes. Preliminary results demonstrate that the proposed framework provides a structured, layered, and systematic approach to Hadith chain assessment, offering improved interpretability compared to previous models. This study contributes a new computational perspective to Hadith sciences and provides a foundation for developing interactive e-learning tools that enhance both academic and practical engagement with Hadith studies. Future work could be to extend the model by incorporating advanced computational techniques, including machine learning and natural language processing, for large-scale learning Hadith chain assessment.

Keywords: Hadith chain assessment, Isnad authentication, learning kit, network security, Islamic studies.

INTRODUCTION

Hadith, defined as the sayings, actions, tacit approvals, and descriptions of Prophet Muhammad (Peace Be Upon Him), serves as a major source of Islamic law and ethics alongside the Qur’an. Understanding the assessment of Hadith is therefore very important, particularly to the new students in Hadith study.

Recognizing the contributions of classical scholars in Hadith chain assessment is important for sustaining the continuity of scholarly tradition and ensuring methodological consistency in contemporary Hadith studies.

Therefore, this endeavor is carried forward by introducing a learning kit designed to serve as an educational tool for understanding classical Hadith chain assessment in a more systematic and accessible manner. The kit is structured to guide students and researchers through the principles and methodologies outlined by classical scholars, while facilitating comprehension through approaches relevant to the contemporary context. In this way, the learning kit not only streamlines the learning process but also reinforces appreciation for the scholarly heritage of Hadith meticulously developed by earlier generations.

In parallel, digital transformation and the widespread adoption of e-learning platforms have created opportunities for integrating technology into Islamic studies. This aligns with the United Nations’ Sustainable Development Goal (SDG 4) on ensuring inclusive and quality education, by expanding access to religious learning and improving tools for authentic knowledge transmission, refer Fig. 1.

Fig.1: The 17 goals for the SDGs program (SDGs, 2017)

Therefore, we believe that e-learning style of study can contribute greatly to achieving the goal particularly. Therefore, we would say that e-learning products in some critical subjects and topics such as in healthcare and religious studies are now becoming greatly relevant. Briefly, e-learning is any education product, application or tools which is provided usually through website-based and / or web portal digital platforms, with the definition in (Malik, Imran, & Mir Suhail Hamid, 2016):

“An umbrella term which encompasses various synonym terms like online learning, web-based learning, digital learning, internet-based learning, web-enhanced learning, computer-based learning.”

Therefore, we agree with the idea not to forget the role of teachers in the classrooms for certain subjects, especially the lists of critical and religious studies with all the critical topics and contents to be understood. While, at the same time they still have chance to use online tools to prepare for certain topics of the subjects to make it easier and faster for preparation and revision of the subject. In supporting the program, our study is developing a new prototype of an electronic learning for Hadith chain assessment on the computer and accesible via the Internet.

Despite progress in computational approaches to Hadith studies, most existing systems focus on text-matching techniques that compare narrations against established databases. Such methods, while useful, often lack a structured framework that systematically verifies the attributes of narrators (Isnad), including biographical details, reliability, and generational connections. This gap limits the accuracy and interpretability of existing computational Hadith authentication systems.

The previous studies (Aldhaln, 2013; Harrag, 2014; Siddiqui et al., 2014) have attempted to apply data mining and text analysis to Hadith classification. However, these approaches generally:

• Do not incorporate a layered, criteria-based framework for Isnad
• Provide limited integration between authentication theory in Hadith sciences and applied computational methods.
• Lack direct inspiration from proven models of authentication in other domains, such as network security, where multi-layered verification processes are standard practice.

This study aims to design a Hadith chain assessment framework for e-learning applications by adopting analogies or parallel concepts from network security authentication. Specifically, it seeks to:

• Develop a layered authentication model for Isnad assessment, based on narrators’ attributes (e.g., biographical details, generational alignment, reliability, and preservation).
• Translate this model into a prototype of a Hadith learning tool that systematically guides learners through the authentication process.

This paper includes introduction to Hadith chain assessment and the analogies or parallel concepts with the network authentication in the Literature Review section. The material and methods section present the details of the data, source and extraction. This paper also includes a novel framework for steps and variables of the Hadith chain assessment proposed for this study. A result of a manual Hadith chain assessment also has been demonstrated at the end of this paper with a comprehensive and all-inclusive conclusion to the reader.

Related Work

Hadith Chain Assessment

Hadith (plural is Ahadith) is what was transmitted on the authority of The Prophet, Peace Be Upon Him (PBUH): his deeds, sayings, tacit approvals, or description of his physical features and moral behaviors.

The importance of Hadith preservation is mainly to protect the genuine Hadith from the fabricated ones, as well as to meet the needs for continuation of studies and preservation among scholars (Abdullah & Abdul Manas, 2006; As-Siba’ee, 2013; Zakaria Stapa, Noranizah Yusuf, 2012).

Among the challenges to protect Hadith is to distinguish the authentic Hadith. Currently there are a number of computer-based studies to validate the Hadith where most of them are based on the matching of test data of Hadith with the authentic Hadith in the database (Bilal & Fit, 2015; Kamsin et al., 2014, 2015; Siddiqui, Saleh, & Bagais, 2014).

Hadith consists of three main things which are: Isnad, Matn and hukm. Isnad is the chain of transmitters who reported the text. Matn is the body of the Hadith, where it reached by the chain. Hukm is the status or grade of the Hadith, whether it is sahih, hasan, da’eef, or mawdhoo’.

Hadith science is the knowledge or rules and maxims through which we know the conditions of the text and the transmission. Science of Hadith is divided into two divisions: Ilm al-riwayah (science of transmission-our study falls into this category) and Ilm al-Dirayah (science of understanding).

In this study, we are focusing on the assessment of Hadith based on the principles theoretically, which the specific criteria will be proposed based on previous studies and science of Hadith. The experiments of Hadith chain assessment involve the dataset extracted from the traditional book of Hadith narrated by Al-Imam Al-Bukhari namely, Al-Adab Al-Mufrad.

There will be a lot of narrators involved in the assessment which will include multiple numbers of students and teachers of the narrators as well. The assessment will be using a common principles agreed by the majority of scholars (’Itar, 1988). The output from assessment experiments will be compared with the manual assessment from the book.

The proposed experiment will be focusing on one part of the Hadith, the chain of narrators (Isnad) individually, based on the physical structure of the Isnad. However, based on common agreed principles by majority of Hadith scholars, there are five (5) main principles need to be verified and validated to authenticate a Hadith for a complete evaluation of both its chain and text, as the following:

• (Isnad) Ittisol sanad. Connected chain of all narrators.
• (Isnad) ‘Adaalah Ar-ruwah. Reliability level of all narrators.
• (Isnad) ‘Dhobt Ar-ruwah. Preservation level of all narrators.
• (Matn) ‘Adamu Shaz. No irregularity in text.
• (Matn) ‘Adamu ‘illah. No defect in text.

While traditional Hadith criticism relies heavily on scholars’ expertise, the complexity of verifying narrator reliability and biographical details makes manual authentication time-consuming and challenging for large-scale datasets. This motivates the need for computational approaches to support Hadith studies

Authentication System

The word ‘authenticate’ which is originally from Greek word gives three meanings (Dictionary.com, 2016), briefly presented as (1) To establish something as genuine, (2) To establish the origin by the technique of scholarship, (3) To make authoritative or valid.

A general definition of ‘authentication’ from an open-accessed encyclopedia briefly is ‘the act of confirming the truth of a single of a data claimed true by an entity’ (Wikipedia contributors, 2016). Authentication is different with authorization, where authentication concerns on confirming the identity of the thing, while authorization concerns on confirming the permission to do something (Almohri, Yao, & Kafura, 2014).

Authentication is also not the same with identification, where identification concerns on the act of stating an identity of something while authentication is the act of confirming the identity (Wikipedia contributors, 2016).

In this study, the assessment of Hadith is to confirm the authenticity of the Isnad Al-Hadith from the attributes of all criteria based on the principles in Hadith science. In contrast, authorization in this case is to make the Isnad permitted to be authentic, while identification in this case is to state the Isnad is authentic.

Process Authentication for Network Security

While we have a wide range of application for authentication process, the studies on network authentication is seen more dominant, where we also have guidelines on secure e-authentication (Burr et al., 2013) and public key certificate (Kuhn, Hu, & Polk, 2001) which are produced by National Institute of Standards and Technology (NIST), a department under United States Department of Commerce.

A generic model of secure e-authentication has been proposed by National Institute of Standard and Technology (NIST), a United States Commerce Department in (Burr et al., 2013) with three main processes which are enrollment, authentication and maintenance. The guidelines of electronic authentication assurance by NIST provide the following scenarios:

• Enrollment – registration of user from the credential service provider (CSP) before using the system.
• Authentication – process of getting permission to perform transaction.
• Maintenance – a lifetime process to maintain the user’s credential by CSP.

Our study is focusing on the second process of e-authentication which are the authentication process itself where the authentication of chain of narrator (Isnad) in a Hadith chain assessment is somewhat equivalent to the authentication of user to getting permission before performing transactions.

Guidelines by NIST also state the 5-steps process to meet the authentication assurance requirements. We could relatively relate the process of authentication of e-authentication in a secure network to the authentication of Isnad as such.

Compared to the guidelines by the NIST, the authentication of Isnad will be commencing from the drawback mentioned in the previous study (K. A. Aldhaln, 2013) where this study is proposing to come out with a new model which will be focusing on Isnad only. The findings from this comparison can be found in the next sections.

Parallel Concept of Layered Security in Banking Authentication

A supplement of 2005 Guideline from FFIEC (FFIEC, 2011) has outlined a layered security programs which comprising different controls at different points of a transaction process. The layered security program by an institution is expected to include in their customers’ banking authentication process, at minimum, the following two elements: (Layer 1) Detecting and responding to suspicious activity and (Layer2) Controlling of administrative functions.

The detail process of the positive verification in banking authentication process has been mapped interrelatedly with the criteria check in Isnad authentication, where the elements of positive verification in banking authentication analogically mapped to the elements of criteria check in Isnad authentication.

Positive verification in banking authentication matches the applicant’s specific and detail answer against information in a trusted database. Whereas in Isnad authentication, the program will compare the attribute values of each specific and detail criteria against information in an Isnad authentication database.

In the banking authentication, if the specific and detail questions correctly answered are increased, then the confidence level of the authentication will also be increased. It is mapped to the Isnad authentication, where the confidence level of Isnad authentication will be increased if and only if all the specific and detail criteria match correctly one by one.

Table I shows the justification of interrelating between the positive verification techniques in banking authentication compared to the authentication of Hadith.

The assessment of Hadith also will be processed layer by layer, where we have multiple criteria to check consecutively.

Furthermore, the level of layered program in the customer’s banking authentication is relatively equivalent to the level of layered program in criteria check of Hadith chain authentication. Isnad authentication has a list of specific and detail criteria to be checked as the following:

• Layer 1: Confirming the sequence of narrators’ identity in an Isnad
• Layer 2: Comparing the attribute of the following specific and detail criteria against the information in the database:
  • Date of birth and date of death of narrator
  • Generation or Tabaqat of narrator
  • Reliability and preservation of the narrator
  • Defect of the narrator
  • The preceding narrator is included in the list of his teacher
  • The succeeding narrator is included in the list of his students
• Layer 3: Confirming all of attributes of the specific and detail criteria to be correct so that an Isnad authentication will be passed.

Table I. Parallel Concepts of Authentication for Banking and Hadith

The details of the Isnad authentication will be further discussed in the next sections.

MATERIALS AND METHOD

Dataset

There two main sources of dataset, which are Al-Adab Al-Mufrad, and Al-Adab Al-Mufrad Taaleeqaat.

The information extracted from the book (from Al-Adab Al-Mufrad, and Al-Adab Al-Mufrad Taaleeqaat):

Al-Adab Al-Mufrad is the primary book, to get the following data:

1. A complete Isnad of the Hadith.
2. ID of Hadith in the book, which then will be used as a primary key.

Al-Adab Al-Mufrad Taaleeqaat is a secondary book, to get the following data:

1. Topic of Hadith.
2. ID of topic.

ID of Hadith in the book (the primary key of the dataset).

1. A complete Matn of Hadith with Tashkeel.
2. Status/ hukm of Isnad from established scholar’s assessment.
3. Source/ name of book where hukm for Isnad is retrieved.

The total number of Hadith in the book is 1,322 while the Hadith with the status of Isnad availability is only to 85. Therefore, we are planning to test the 85 Hadith with the related information of every Hadith.

In this study, the name of the narrators in the following table is extracted from a Shamela program, in a menu Tarjamah -book namely Ruwaatu Tahzeebeen (“Ruwaatu Tahzeebeen, Shamela Program Ver 3.15,” 2017) while the other related information also extracted from the a variety platform and sources of Al-Maktabah Al-Shamelah available on the web-based source.

Based on preliminary assessment, we produced a variables framework as it presented in Fig. 2.

Fig. 2: Variables Framework of Learning Classical Hadith Chain Assessment

Pre-processing

To prepare the dataset for computational analysis, the following preprocessing steps were conducted to ensure consistency and accuracy for subsequent authentication assessment:

1. Normalization – Standardizing narrator names across multiple sources to resolve spelling variations.
2. Entity Mapping – Linking narrators to their corresponding tabaqat and biographical attributes.
3. Attribute Extraction – Structuring reliability ratings and relational data (teachers and students) into tabular form.
4. Primary Key Assignment – Assigning a unique ID to each Hadith and narrator for database integration.

Framework Design

The proposed framework adopts layered authentication principles from network security and applies them to Hadith Isnad assessment. The process is structured into three layers:

• Layer 1: Identity Verification
  Confirming the sequence of narrators in the Isnad chain to ensure completeness.
• Layer 2: Attribute Validation
  Assessing six criteria for each narrator:
  1. Date of birth and death
  2. Generational classification (tabaqat)
  3. Reliability rating (‘adalah)
  4. Preservation level (dhobt)
  5. Teacher–student linkage (preceding narrator)
  6. Teacher–student linkage (succeeding narrator)
• Layer 3: Consolidation –

Integrating the results from Layer 1 and Layer 2 to determine whether the Isnad passes authentication. Only when all criteria are satisfied is the Hadith considered authentic at the chain level.

Fig. 3: Learning Framework of Hadith Chain Assessment

Validation and Comparison

To validate the proposed framework:

• Manual Benchmarking – Results from the framework are compared against scholarly assessments provided in Al-Adab Al-Mufrad Ta’leeqaat.
• Consistency Check – Agreement between computational output and classical evaluations is measured.
• Expert Review – Feedback from Hadith scholars is sought to evaluate interpretability and domain relevance.

This validation ensures that the framework is both faithful to traditional Hadith sciences and practically applicable within an e-learning environment.

Result And Finding

The proposed framework was applied to a subset of 85 Hadith narrations with available chain of narrators (Isnad) from Al-Adab Al-Mufrad. The dataset was processed through the three-layer authentication framework. Table II presents an example result of narrator attributes extracted from the source of data.

The preliminary analysis indicates that the framework is able to systematically validate narrator attributes and detect inconsistencies. For instance, chains with missing or mismatched teacher–student relationships failed authentication at Layer 2, while chains with complete, reliable, and continuous narrators passed all three layers.

Results generated by the framework were compared with scholarly evaluations from Al-Adab Al-Mufrad Ta’leeqaat. The comparison showed a high level of agreement in identifying authentic chains, suggesting that the layered approach is consistent with traditional Hadith sciences.

However, some discrepancies were observed in cases where biographical data were incomplete or conflicting across sources.

Table II. Preliminary Result of Learning Hadith Chain Assessment

DISCUSSION & FUTURE WORK

The results highlight several key insights:

1. Structured Verification Improves Transparency –

Unlike text-matching approaches, the proposed layered framework provides a step-by-step process that makes authentication more interpretable. Learners can see which specific criteria were satisfied or failed, which enhances their educational value.

2. Incorporation of Generational Data (Tabaqat) –
   By adding tabaqat as a verification attribute, the model extends beyond prior studies (Aldhaln, 2013; Harrag, 2014). This allows the detection of chronological inconsistencies between narrators, thereby improving reliability of the authentication process.
3. Parallel with Network Security –
   The analogy with network security strengthens the design rationale. Just as layered authentication increases confidence in verifying user identities, multi-criteria learning assessment of Isnad increases confidence in Hadith authenticity. This cross-disciplinary mapping demonstrates the potential of borrowing concepts from computer science to address challenges in Islamic studies.
4. Limitations and Challenges
   • The framework currently focuses only on Isnad (chain of narrators) and does not assess the Matn (text).
   • Biographical data inconsistencies across classical sources can limit accuracy.
   • The current implementation is rule-based; incorporating statistical or machine learning models could further improve scalability.

The findings suggest that the proposed framework not only offers a computational method for Hadith authentication but also has practical significance in e-learning. By embedding the model into a digital learning tool, students and scholars can engage with Hadith authentication in a structured and transparent manner. This supports the wider educational agenda of enhancing access to authentic Islamic knowledge in the digital age.

CONCLUSION & SIGNIFICANCE

In conclusion, appreciating the contributions of classical scholars in Hadith chain assessment remains highly significant, as it not only sustains the continuity of scholarly tradition but also reinforces the methodological integrity that underpins the authenticity of contemporary Hadith studies.

This study has produced a novel framework for learning classical Hadith chain assessment by adapting layered authentication principles from network security. Preliminary results demonstrate that this model aligns closely with classical scholarly evaluations while offering enhanced transparency and interpretability.

The key contribution of this research lies in the integration of this framework into an e-learning tool which provides practical value, enabling students and scholars to engage interactively with Hadith authentication processes. This supports broader educational objectives, particularly the advancement of digital Islamic studies in line with the United Nations’ Sustainable Development Goal (SDG 4) on quality education.

This study makes three key contributions to the field of Hadith authentication and e-learning design:

Novel Framework –

It introduces a new authentication framework for learning Hadith chain assessment inspired by network security principles; particularly layered authentication processes used in Internet banking. This provides a unique parallel model that has not been explored in previous studies.

Structured Methodology –

By focusing on Isnad (chain of narrators) and extracting biographical, generational, and reliability attributes from classical sources, the study proposes a systematic, step-by-step learning assessment process rather than relying solely on text-matching techniques.

Practical Application –

The framework is embedded into the design of a Hadith chain assessment learning tool for e-learning environments. This tool not only supports Islamic scholarship in preserving authentic Hadith but also enhances digital learning resources aligned with the UN-SDG 4 on quality education.

In addition, it also bridging traditional Hadith sciences with modern computational concepts, thereby introducing an interdisciplinary methodology that strengthens the concept of Isnad authentication accuracy.

Several limitations remain. The framework currently focuses exclusively on the chain of narrators (Isnad) and does not incorporate learning assessment of the Hadith text (Matn). Furthermore, biographical inconsistencies across classical sources present challenges for automated verification.

Future work could be to address these limitations by extending the model to include Matn analysis, incorporating larger datasets, and integrating advanced computational techniques such as natural language processing and machine learning. Such enhancements will improve scalability, precision, and usability, paving the way for a comprehensive digital Hadith authentication platform.

Overall, this research contributes both theoretically and practically: it strengthens computational approaches to Hadith sciences and provides an applied model that can be expanded using advanced technologies such as machine learning and natural language processing in future work of appreciating the work of classical scholars in Hadith chain assessment since it is the key to sustaining scholarly tradition and the authenticity of contemporary Hadith studies.

By appreciating the contributions of classical scholars in Hadith chain assessment, we not only inherit a noble scholarly tradition but also safeguard the continuity of truth for future generations.

ACKNOWLEDGEMENTS

We thank our supervisors, advisors, expert matters, colleagues and friends who provided insight and expertise that greatly assisted the research. This research was supported by Universiti Teknikal Malaysia Melaka (UTeM) and Ministry of Higher Education (MoHE).

Fig. 4: Interface Design for Learning Kit of Hadith Chain Assessment

REFERENCES

1. ’Itar, N. (1988). Manhaj An-Naqad fi Ulum Al-Hadith. Dar Al-Fikr, Damsyiq, Syria.
2. Abdullah, I., & Abdul Manas, S. (2006). Introduction to the Sciences of Hadith. (I. Research Centre, Ed.) (First). Research Centre, International Islamic University Malaysia.
3. Abidin, D. Z. (2013). The Power of Al-Quran – Meneroka Keajaiban Mukjizat Agung,. Selangor, Malaysia: PTS Millenia Sdn Bhd.
4. Aldhaln, K. A. (2013). Data Mining for Hadith Classification. International Islamic University Malaysia.
5. Aldhaln, K. A., & Zeki, A. M. (2011). Employing machine learning algorithms to extract Islamic knowledge.pdf. In Data Management: Issues, Challenges and Opportunities. IIUM Press.
6. Aldhaln, K. A., & Zeki, A. M. (2012). Knowledge Extraction In Hadith Using Data Mining Technique. In 2 nd International Conference on E-Learning & Knowledge Management Technologies ( ICEKMT 2012 ) Venue : Hotel Corus , Malaysia Knowledge Extraction In Hadith Using Data Mining Technique 2 nd International Conference on E-Learning & Knowledge Management T.
7. Aldhaln, K., Zeki, A., Zeki, A., & Alreshidi, H. (2012). Improving Knowledge Extraction Of Hadith Classifier Using Decision Tree Algorithm 1.
8. Aldhlan, K. A., Zeki, A. M., Zeki, A. M., & Alreshidi, H. A. (2013). Novel mechanism to improve Hadith classifier performance. In Proceedings – 2012 International Conference on Advanced Computer Science Applications and Technologies, ACSAT 2012 (pp. 512–517). http://doi.org/10.1109/ACSAT.2012.93
9. Almohri, H. M. J., Yao, D., & Kafura, D. (2014). Process Authentication for High System Assurance. IEEE Transactions on Dependable and Secure Computing, 11(2), 168–180. http://doi.org/10.1109/TDSC.2013.29
10. As-Siba’ee, M. (2013). The Sunnah and its role in Islamic Legislation. Igarss 2014. http://doi.org/10.1007/s13398-014-0173-7.2
11. Bilal, K., & Fit, S. M. (2015). MuHadith : A Cloud Based Distributed Expert System for Classification of AHadith . Knowledge discovery in Al ­ Hadith using text classification algorithm A textbook of Hadith studies : authenticity , compilation , classification and criticism of Hadith Ec, 4–5.
12. Burr, W. E., Dodson, D. F., Newton, E. M., Perlner, R. A., Polk, W. T., Gupta, S., & Nabbus, E. A. (2013). Electronic Authentication Guideline. NIST Special s2
13. Dictionary.com. (2016). Authenticate. Retrieved from http://www.dictionary.com/browse/authentication
14. FFIEC. (2005). Authentication in an Internet Banking Environment. Federal Financial Institutions Examination Council. http://doi.org/10.1109/ICISP.2006.3
15. FFIEC. (2011). Authentication in an Internet Banking Environment. Federal Financial Institutions Examination Council. http://doi.org/10.1109/ICISP.2006.3
16. Harrag, F. (2014). Text Mining Approach for Knowledge Extraction in Sahih Al-Bukhari. Computers in Human Behaviour, 30, 558–566.
17. Harrag, F., Alothaim, A., Abanmy, A., Alomaigan, F., & Alsalehi, S. (2013). Ontology Extraction Approach for Prophetic Narration (Hadith) using Association Rules. International Journal on Islamic Applications in Computer Science And Technology, 1(2), 17–26.
18. Harrag, F., Hamdi-cherif, A., Al-salman, A. M. S., & El-qawasmeh, E. (2009). Experiments in Improvement of Arabic Information Retrieval, 71–81.
19. Harrag, F., Hamdi-Cherif, A., & El-Qawasmeh, E. (2008). Vector space model for Arabic information retrieval—application to “Hadith” indexing. In 1st International Conference on the Applications of Digital Information and Web Technologies ICADIWT 2008 (pp. 107–112). Retrieved from http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4664328
20. Ibrahim, N. K., Noordin, M. F., Samsuri, S., Seman, M. S. A., & Ali, A. E. B. (2016). Isnad Al-Hadith Computational Authentication : An Analysis Hierarchically. In 2016 6th International Conference on Information and Communication Technology for The Muslim World (ICT4M) (pp. 344–349). http://doi.org/10.1109/ICT4M.2016.68
21. Ibrahim, N. K., Samsuri, S., Seman, M. S. A., Ali, A. E. B., & Kartiwi, M. (2016). Frameworks for A Computational Isnad Authentication and Mechanism Development. In 2016 6th International Conference on Information and Communication Technology for The Muslim World (ICT4M) (pp. 154–159). http://doi.org/10.1109/ICT4M.2016.36
22. Kamsin, A., Gani, A., Suliaman, I., Jaafar, S., Mahmud, R., Sabri, A. Q., … Yusoff, M. Y. Z. M. (2014). Proposing the Pogram for Developing the Novel Quran and Hadith Authentication System. In 2nd International Conference on Islamic Application in Computer Science and Technology (pp. 1–8).
23. Kamsin, A., Gani, A., Suliaman, I., Jaafar, S., Sabri, A. Q. M., Idris, M. Y. I., & Razak, Z. (2015). Program for Developing the Novel Quran and Hadith Authentication System. International Journal on Islamic Applications in Computer Science and Technology, 3(1), 8–17.
24. Kuhn, D. R., Hu, V. C., & Polk, W. T. (2001). Introduction to Public Key Technology and the Federal PKI Infrastructure, (February), 1–54.
25. Mustafa, M., & Najeeb, A. (2016a). Processing Of “ Hadith Isnad ” Based On Hidden Markov Model, 6(1), 50–55.
26. Mustafa, M., & Najeeb, A. (2016b). XML Database for Hadith and Narrators. http://doi.org/10.3844/ajassp.2016.55.63
27. Najeeb, M., Abdelkader, A., Al-Zghoul, M., & Osman, A. (2015). A Lexicon for Hadith Science Based on a Corpus. International Journal of Computer Science and Information Technologies, 6(2), 1336–1340.
28. Najeeb, M. M. (2014). Towards Innovative System for Hadith Isnad Processing ISSN : 2231-2803. International Journal of Computer Trends and Technology (IJCTT), 18(6), 257–259. http://doi.org/10.14445/22312803/IJCTT-V18P154
29. Noordin, M. F., & Othman, R. (2006). An Information Retrieval System for Quranic Texts: A Proposed System Design. 2006 2nd International Conference on Information & Communication Technologies, 1, 1704–1709. http://doi.org/10.1109/ICTTA.2006.1684642
30. Othman, R., & Wahid, F. A. (2014). Quranic texts retrieval in Indri. 2014 the 5th International Conference on Information and Communication Technology for the Muslim World, ICT4M 2014. http://doi.org/10.1109/ICT4M.2014.7020619
31. Philips, A. A. B. (2005). Usool At-Tafseer: The Methodology of Qur’anic Interpretation (English Ed). Riyadh, Saudi Arabia: International Islamic Publishing House.
32. Rahman, N. A., Bakar, Z. A., & Sembok, T. M. T. (2010). Query expansion using thesaurus in improving Malay Hadith retrieval system. In Proceedings 2010 International Symposium on Information Technology – System Development and Application and Knowledge Society, ITSim’10 (Vol. 3, pp. 1404–1409). http://doi.org/10.1109/ITSIM.2010.5561518
33. Rasyidi, I., Romadhony, A., & Wibowo, A. T. (2013). Indonesian Hadith Retrieval System using thesaurus. In Proceeding – 2013 International Conference on Computer, Control, Informatics and Its Applications: “Recent Challenges in Computer, Control and Informatics”, IC3INA 2013 (pp. 285–288). http://doi.org/10.1109/IC3INA.2013.6819189
34. Rebhi S. Baraka; Yehya M. Dalloul. (2014). Building Hadith Ontology to Support the Authenticity of Isnad. International Journal on Islamic Applications in Computer Science And Technology, 2(1), 25–39.
35. Ruwaatu Tahzeebeen, Shamela Program Ver 3.15. (2017).
36. Saad, S., Noah, S. A. M., Salim, N., & Zainal, H. (2015). Rules and Natural Language Pattern in Extracting Quranic Knowledge. In 2013 Taibah University International Conference on Advances in Information Technology for the Holy Quran and Its Sciences, NOORIC 2013 (pp. 381–386). Institute of Electrical and Electronics Engineers Inc.. http://doi.org/10.1109/NOORIC.2013.80
37. Shamela Library. (n.d.). Retrieved August 11, 2017, from Shamela.ws
38. Shamela Library Software Ver 3.15. (n.d.).
39. Shamela Library Software Ver 3.61. (n.d.).
40. Siddiqui, M. A., Saleh, M. E., & Bagais, A. A. (2014). Extraction and Visualization of the Chain of Narrators from Hadiths using Named Entity Recognition and Classification. International Journal of Computational Linguistics Research, 5(1), 14–25.
41. Stepney, S., Smith, R. E., Timmis, J., Tyrrell, A. M., Neal, M. J., & Hone, A. N. W. (2005). Conceptual Frameworks for Artificial Immune Systems. International Journal of Unconventional Computing, 1, 1–24.
42. Wikipedia contributors. (2016). Authentication. http://doi.org/10.1515/9781400821334.toc
43. Zakaria Stapa, Noranizah Yusuf, A. F. S. (2012). Pendidikan Menurut Al-Quran dan Sunnah serta Peranannya dalam Memperkasakan Tamadun Ummah. Jurnal Hadhari Special Edition (2012) 7-22, 7–22.