Proposing machine learning of Tafsir al-Quran: In search of objectivity with semantic analysis and Natural Language Processing

Putra, D I A; Yusuf, Muhammad

doi:10.1088/1757-899x/1098/2/022101

Cited by 2 publications

(3 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar thinking to the previous one is to be found in the scientific developments of D.I.A. Putra (2021). The author proposes to explain the Holy Quran with the help of artificial intelligence.…”

Section: Discussionsupporting

confidence: 55%

See 1 more Smart Citation

The importance of a semantic approach in understanding the texts of the Holy Quran and Sunnah

Chukhanov,

Kairbekov

2024

pharosjot

View full text Add to dashboard Cite

The relevance of the study is determined by contemporary ideas of modernisation and radicalisation of Islam, the formation of which is directly linked to the problem of interpreting the sacred texts of the Muslim world. Therefore, the aim of the research work is to determine the veracity of applying linguistic and semantic approaches to the interpretation of the Holy Quran in order to find new ways of regulating the socio-cultural space. The research was conducted on the basis of the semantic, cultural, semiotic and formal-logical approaches, using such methods of scientific knowledge as induction, deduction, linguistic analysis, systematisation, comparison, synthesis and generalisation. In the course of the research work, key narratives of contemporary Islam were analysed in terms of their specific understanding of the Holy Quran. The current state of research into the interpretation of the sacred texts of Islam is reviewed. The specifics of understanding the Holy Quran in the context of its metaphorical constructions are explored. The relationship between the linguistic structure of the Arabic language and the interpretations of the texts of the holy injunctions has been established, on the basis of which two ways of investigating the understanding of the Quran have been proposed. A comparative analysis of the research findings with other research findings in the category of modern interpretation of the Quran and Sunnah has been conducted. The trend towards digitalisation of the sacred texts of Islam, as well as the use of artificial intelligence technologies to interpret the ayahs, has been noted. The practical significance of the research work lies in proposing new methodologies for interpreting sacred texts, which can then be qualitatively applied in practice.

show abstract

Section: Discussionsupporting

confidence: 55%

“…A new perspective on the semantic approach to understanding the texts of the Holy Quran and Sunnah is inherent in S. Muhyidin (2022) and D.I.A. Putra (2021).…”

Section: Discussionmentioning

confidence: 99%

The importance of a semantic approach in understanding the texts of the Holy Quran and Sunnah

Chukhanov,

Kairbekov

2024

pharosjot

View full text Add to dashboard Cite

show abstract

“…The development of advances in technology today makes the classification of Al-Qur'an translation texts can be implemented utilizing an algorithm of machine learning. Machine learning is an AI implementation that applies mathematical approaches to build automatic models from a set of data, with the objective of allowing the computer to "learn" [9]. In the context of Qur'anic translation text classification, supervised learning algorithms can learn specific linguistic patterns and language structures in PREDATECS -Vol.…”

Section: Introductionmentioning

confidence: 99%

Text Classification of Translated Qur'anic Verses Using Supervised Learning Algorithm

Ananda,

Nurhidayarnis,

Afifah

et al. 2024

PREDATECS

View full text Add to dashboard Cite

The Quran, comprising Allah's absolute divine messages, serves as guidance. Although reading the Quran with tafsir proves beneficial, it may not offer a comprehensive understanding of the entire message conveyed by the Al-Quran. This is due to the Quran addressing diverse topics within each surah, necessitating readers to reference interconnected verses throughout the entire chapter for a holistic interpretation. However, given the extensive and varied verses, obtaining accurate translations for each verse can be a complex and time-consuming endeavor. Therefore, it becomes imperative to categorize the translated text of Quranic verses into distinct classes based on their primary content, utilizing Fuzzy C-Means, Random Forest, and Support Vector Machine. The analysis, considering the obtained Davies-Bouldin Index (DBI) value, reveals that cluster 9 emerges as the optimal cluster for classifying QS An-Nisa data, exhibiting the lowest DBI value of 4.30. Notably, the Random Forest algorithm demonstrates higher accuracy compared to the SVM algorithm, achieving an accuracy rate of 66.37%, while the SVM algorithm attains an accuracy of 50.56%.

show abstract

Proposing machine learning of Tafsir al-Quran: In search of objectivity with semantic analysis and Natural Language Processing

Cited by 2 publications

References 2 publications

The importance of a semantic approach in understanding the texts of the Holy Quran and Sunnah

The importance of a semantic approach in understanding the texts of the Holy Quran and Sunnah

Text Classification of Translated Qur'anic Verses Using Supervised Learning Algorithm

Contact Info

Product

Resources

About