Umar, Zeindri Abu
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Scientific Cosmopolitanism in 9th-Century Baghdad: Muslim, Jewish, and Christian Knowledge Exchange in Sociological Perspective Umar, Zeindri Abu; Hidayat, Marwan; Qomarullah, Ahmad Basuki; Mutmainnah, Rizky
Al-Qarawiyyin: Jurnal Ilmu Ushuluddin Vol. 1 No. 4 (2025): The Golden Age of Islam
Publisher : Yayasan Albahriah Jamiah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64691/aqz5ej83

Abstract

The 9th century was a pivotal phase in Islamic intellectual history, when Baghdad, under the Abbasid dynasty, emerged as a cosmopolitan center of knowledge. However, studies on interfaith interactions in the social construction of knowledge have rarely been discussed sociologically, particularly regarding the mechanisms of collaboration and the driving forces behind them. This study aims to analyze the exchange of knowledge between Muslim, Jewish, and Christian communities through social relations, institutions, and scientific networks, and to examine how these interactions have shaped cosmopolitan structures for the development of knowledge. This study employs a qualitative method with a historical-sociological approach, drawing on both primary and secondary literature. This study examines the role of Bayt al-Ḥikmah, the patronage of the caliphs, and the contributions of translators and scholars across religions through their works, institutions, and intellectual networks. The results show that Christian translators played a strategic role in transmitting Greek works through philological phases and conceptual adaptations. At the same time, Muslim scholars developed a methodological synthesis that connected rationalism and theology in the fields of philosophy, medicine, and mathematics. The Jewish community also made significant contributions to the development of philology and philosophy, which later had a profound influence on the Andalusian intellectual tradition. These findings confirm that Baghdad’s scientific cosmopolitanism was not simply the result of knowledge transfer, but rather a social construct shaped by epistemic tolerance, institutional cooperation, and cultural openness. In conclusion, interfaith interactions during this period gave rise to a knowledge ecosystem model that was not only productive and collaborative but also accelerated methodological integration and the expansion of the intellectual horizons of the Islamic world.
Optimalisasi Teknologi OCR dalam Digitalisasi Manuskrip Hadis: Studi Akurasi dan Tantangan Linguistik Arab Klasik Umar, Zeindri Abu; Yunus, Mahmud
Hamidah: Jurnal Ilmu Hadis Vol. 1 No. 1 (2025): Hadith and Digitalization
Publisher : Yayasan Albahriah Jamiah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64691/6vn20070

Abstract

The digitization of hadith manuscripts is a strategic step in preserving and disseminating Islamic intellectual treasures. Still, this process faces significant challenges related to the accuracy of classical Arabic text recognition using Optical Character Recognition (OCR) technology. The complexity of Arabic orthography, the diversity of calligraphic styles, and the presence of diacritics and ligatures typical of classical manuscripts often lead to errors in character recognition, which impact the reliability of the digitization results. This study aims to analyze the accuracy of various OCR systems in reading hadith manuscripts, identify the main linguistic constraints that cause distortions in letter and word recognition, and develop an optimization model based on linguistic and computational integration to improve system performance. Using a mixed methods approach, this study combines quantitative analysis of text processing results from several popular OCR platforms with qualitative analysis of linguistic error patterns that appear in classical Arabic manuscripts. The results show that the accuracy of OCR for hadith manuscripts varies widely, ranging from 68% to 91%, depending on image quality, calligraphy type, and the system’s ability to recognize morphological forms and punctuation typical of classical Arabic. The most common errors occur in letters with graphemic similarities, such as “س” and “ش,” as well as in words with full vowels or complex Iʻrāb markings. An optimization model developed through a combination of machine learning and Arabic morphological analysis has been shown to improve accuracy by up to 94%, while accelerating the post-correction process for digital texts. In conclusion, the digitization of hadith manuscripts requires an integrative approach between OCR technology and an understanding of classical Arabic linguistics to ensure the validity, efficiency, and sustainability of digital religious manuscript preservation.