Mesopotamian Journal of Quran Studies

Mechanisms of advocacy work in the workpla

Yacoub Youssef Ahmed Salman — 2024-02-20

Praise be to God, Lord of the worlds, and the end is for the righteous, and there is no aggression except against the wrongdoers. “And God Almighty created the jinn and mankind to be worshiped alone with no partner, and to magnify His commands and prohibitions. So my brother learned from this that among the wisdom in creating creation is to know God Almighty by His names and attributes. "And that He has power over all things. His companions after him bore the trust," and they walked on the path, calling to God Almighty, and spreading throughout the globe as preachers of the truth. Thus, it becomes clear to every seeker of knowledge that calling to God is one of the most important tasks, and that the nation is in Every time and place is in dire need of it.” Indeed, it is in dire need of it.

Quranic Studies Evolution: A Bibliometric Analysis from 1880 to 2023

Akhmed K Kaleel — 2024-01-10

This analysis focuses on the study of the Quran, from 1880 to 2023 using data obtained from Scopus. Made accessible through a BibTeX file on GitHub. The examination covers aspects of research trends including the number of citations per year the influence of sources notable authors and their affiliations the countries of corresponding authors the production trends in different countries over time and a network illustrating how key concepts are interconnected. By conducting an analysis several significant findings were discovered. The data demonstrated an increase in citations per year indicating a growing importance and scholarly interest in Quranic Studies. Noteworthy authors such as Rippin A and Reynolds GS as prominent affiliations like the University of Malaya and International Islamic University Malaysia made substantial contributions to this field. The distribution of corresponding authors countries highlighted Malaysias, Indonesias and Irans roles. Furthermore when examining production trends over time for countries it became evident that contributions from the United Kingdom, USA,Malaysia,Iran and Indonesia had seen growth. Additionally the interconnectedness between concepts such as natural language processing systems, computational linguistics,semantics and information retrieval were emphasized in the cooccurrence network, within Quranic Studies. This, in depth analysis provides insights into the development significant contributors and intersections of themes in the study of the Quran. It establishes a foundation for research endeavors, in this area.

An AI model for Parsing the Text of Holy Quran Sentences

haval ameen — 2024-07-10

The Holy Quran is of immense importance to many societies due to the position that this book holds for Muslims around the world and the religious teachings it contains. The Holy Quran employs a high-standard Arabic language, which requires analysis and simplification of expressions to enhance comprehension and application of its teachings. The digitization and combining of the Holy Quran with computing operations have made it easier to discover the vast amounts of information contained within its verses. Using these applications, academics and erudite researchers have successfully developed norms that govern the study of Qur'anic knowledge, thus expanding the illustration of the Quran. NLP is a well-known branch of study that has been the subject of research for many years. The intrinsic intricacy of this field has resulted in slower progress when compared to other areas of inquiry. Furthermore, despite having the most sophisticated syntax, structure, and verb conjugation of all-natural languages, Arabic has received comparatively little attention. As a result, there is an urgent need for study in this area to aid in the discovery of inclusive lexical knowledge. This research is concerned with the parsing of holy Quranic sentences. A neural network was used Consisting of two layers to training the token word attribute depending on the neural network input words characteristics. This research is based on a knowledge base that consists of 160 features was used, and 26 features related to the grammatical case were selected. The first group comprised an entered dataset with 128,221 rows, whereas the second group had 99.540 rows. We ran seven different experiments within each group and achieved a 96% accuracy rate. This accuracy was reached by using a training set size of 90,000 rows and a testing set size of 9,000 rows. Furthermore, we achieved 94% accuracy within the broader dataset of 128,221 rows by employing a training set size of 90,000 rows and a testing set size of 38,000 rows.