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Triple - Relational Latent Lexicology-phonology-semantic “mmrllexicolphonosemc” Analysis Model For Extracting Qura’nic Concept

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dc.contributor.authorAsma Abdul Rahmanen_US
dc.contributor.authorSarah Husna Mat Rasiden_US
dc.date.accessioned2024-05-28T05:47:42Z
dc.date.available2024-05-28T05:47:42Z
dc.date.issued2022
dc.date.submitted2022-4-26
dc.descriptionVolume 2, Issue 1 (pages: 99-114)en_US
dc.description.abstractAl Quran is a divine text which represents the purest and most authentic form of the classical Arabic language. In order to understand the meaning of each verse, a deep knowledge of Arabic linguistic is essential. Therefore, our scholars have made their efforts by engaging themselves in the works of explaining al Quran’s words, interpreting its meanings into Arabic and other languages. Currently, more people are interested in knowing the content of al-Quran, especially for non-Muslim, after 9/11 tragedy. Thus, a flexible model that can represent Qur’anic concept is required for people to understand the content of the Quran. In this research, propose a Multi-Relational Latent Lexicology– phonology -Semantic Analysis Model (MMRLLEXICOLPHONOSEMC) based on a combination of Arabic Phonology Semantic and six multiple relations between words, which are synonym, antonym, hypernym, hyponym, homonym and meronym, to precisely extract Qur’anic concept. The existing literatures focus only on very limited relationships between words which could not extract the in-depth concept of Qur’anic without considering the importance Arabic phonology Semantic. Therefore, the objectives of this research are: (1) to analyses and categorize Quranic words according to Arabic phonology Semantic patterns, (2) to propose a new model for extracting Quranic concept using MMRLLEXICOLPHONOSEMC, (3) to investigate phonology semantic relationships between Qur’anic words, and (4) to validate the proposed model with Arabic linguistic, and Qur’anic experts. This research will be conducted qualitatively through content analysis approach a new innovative technological technique. It is expected that the model will come out with a precise analysis for extracting Qur’anic concept. This will be very significant in enhancing the overall Quran’s understanding among the society in Malaysia and Muslim’s world for sustainable society.en_US
dc.identifier.citationAsma Abdul Rahman & Sarah Husna Mat Rasid. 2022 Triple - Relational Latent Lexicology-Phonology-Semantic “Mmrllexicolphonosemc” Analysis Model for Extracting Qura’nic Concept. International Journal of Advanced Research in Islamic Studies and Education (ARISE), 2(1), 99-114.en_US
dc.identifier.doihttps://doi.org/10.3390/socsci11030113
dc.identifier.epage114
dc.identifier.issn2785-9088
dc.identifier.issue1
dc.identifier.spage99
dc.identifier.urihttps://www.myedujournal.com/index.php/arise/article/view/111
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/6517
dc.identifier.volume2
dc.language.isoen_USen_US
dc.publisherInternational Journal of Advanced Research in Islamic Studies and Education (ARISE)en_US
dc.relation.ispartofInternational Journal of Advanced research in Islamic Studies and Education (ARISE)en_US
dc.subjectMultiple Triple-Relational, Latent, Lexicology-Phonology-Semantic, Model Extracting, Qur’anicen_US
dc.titleTriple - Relational Latent Lexicology-phonology-semantic “mmrllexicolphonosemc” Analysis Model For Extracting Qura’nic Concepten_US
dc.typeArticleen_US
dspace.entity.typePublication

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