Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Diwan: Jurnal Bahasa dan Sastra Arab Studies in English Language and Education
Ahmad, Maulana Ihsan
Unknown Affiliation
Humanities Education Languange, Linguistic, Communication & Media Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Computational linguistics and natural language processing techniques for semantic field extraction in Arabic online news Ahmad, Maulana Ihsan; Anwari, Moh. Kanif
Studies in English Language and Education Vol 11, No 3 (2024)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/siele.v11i3.38090

Abstract

The research aimed to extract semantic fields from Arabic online news and advance Natural Language Processing (NLP) applications in understanding and managing news information effectively. It provides a comprehensive approach to processing and analyzing large volumes of Arabic news data by integrating semantic field analysis, NLP, and computational linguistics. Using quantitative methods, Arabic news articles were collected and processed with Python, a popular programming language in data analysis, and applied various NLP techniques and machine learning models to accurately extract semantic fields. The primary objective was to evaluate the effectiveness of different classification models in categorizing Arabic news and to identify the most suitable model for semantic field extraction. The research evaluated five classification models: Naive Bayes, Support Vector Machine (SVM), Logistic Regression, Random Forest, and Gradient Boosting. Among these, SVM achieves the highest overall accuracy of 90%. Specifically, SVM demonstrated exceptional performance in categorizing sports-related news, with a 99% probability and an F1-Score of 98%. However, it faced challenges in categorizing health and science news, achieving a lower F1-Score of 79%. Overall, the study demonstrated the effectiveness of computational methods, particularly SVM, in classifying Arabic news and extracting semantic fields, thereby advancing NLP and computational linguistics. The findings highlighted the potential of SVM for accurate news analysis and the need for further enhancement of NLP techniques to address multilingual and domain-specific challenges.
Acehnese interference in students' spoken Arabic: A multi-level cross-linguistic analysis in an Indonesian Islamic boarding school Ahmad, Maulana Ihsan; Zaini, Hisyam; Rambe, Windi Alhafiza
Diwan: Jurnal Bahasa dan Sastra Arab Vol. 18 No. 1 (2026): IN PROGRESS
Publisher : Jurusan Bahasa dan Sastra Arab Fakultas Adab dan Humaniora UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/diwanjurnalbahasadansastraarab.v18i1.2443

Abstract

Although numerous studies have examined Arabic language interference among Indonesian learners, detailed analyses integrating multiple linguistic levels within a single Acehnese-speaking institutional context remain a significant gap in the literature. This study addresses that gap by investigating cross-linguistic influence in students’ spoken Arabic at Dayah Babul Maghfirah, an Islamic boarding school in Aceh that formally enforces Arabic-only communication. Adopting a qualitative descriptive approach, the study analyzes naturally occurring oral interactions collected through non-participant observation over one week. Data were examined using Miles, Huberman, and Saldaña’s interactive model. The findings reveal systematic Acehnese interference across four linguistic levels: 1) phonological substitutions of marked Arabic consonants; 2) morphological projection of Acehnese particles and affixes; 3) syntactic transfer of Acehnese-dominant structural templates; and 4) lexical insertion of discourse markers and interjections. These patterns demonstrate that local linguistic repertoires remain structurally active even within immersion-oriented institutional settings, challenging assumptions that policy-driven environments suppress first-language influence. By providing a systematic multi-level mapping of interference within a single pesantren environment, this study contributes empirically to cross-linguistic influence research and extends Indonesian interference scholarship to an underrepresented regional context. The findings offer evidence-based insight for Arabic pedagogy in multilingual religious education settings where immersion policies coexist with deeply entrenched vernacular linguistic identities.
Co-Authors Hisyam Zaini Moh. Kanif Anwari, Moh. Kanif Rambe, Windi Alhafiza