Data-Driven Profiling of Arabic Language Proficiency: Integrating Fuzzy Clustering and Neural Network Analysis

Atikah Marwa; Danial Hilmi; Syaiful Mustofa; Ayu Desrani; Apri Wardana Ritonga

doi:10.32332/an-nabighoh.v28i1.211-232

Authors

Atikah Marwa Universitas Islam Negeri Maulana Malik Ibrahim , State University of Jakarta
Danial Hilmi Universitas Islam Negeri Maulana Malik Ibrahim
Syaiful Mustofa Universitas Islam Negeri Maulana Malik Ibrahim
Ayu Desrani Yogyakarta State University
Apri Wardana Ritonga Institut As-Syifa

DOI:

https://doi.org/10.32332/an-nabighoh.v28i1.211-232

Keywords:

Arabic Language Assessment, Competency Profiling, Fuzzy C-Means Clustering, Neural Network, Educational Data Mining

Abstract

Introduction: Evaluating multidimensional language competencies in tertiary-level Arabic education poses persistent methodological difficulties, as conventional scoring systems frequently reduce complex proficiency dimensions to single aggregated values that conceal underlying skill structures and diminish the instructional utility of assessment feedback. Research Objectives: The present study constructs an empirically grounded competency profiling framework by combining clustering algorithms with predictive modeling techniques to uncover latent proficiency patterns among Arabic language learners. Methodology: A cross-sectional quantitative design was adopted using data from 128 students in the Arabic Language Education program at Universitas Negeri Jakarta, whose scores across listening, speaking, reading, and writing skills were analyzed through Fuzzy C-Means (FCM) clustering to identify latent proficiency groupings, followed by the use of a feedforward neural network to model predictive relationships between individual skill domains and overall academic performance. Results: Three learner profiles emerged: low, moderate, and high proficiency each showing statistically significant inter-group differences across all skills (p < 0.001), with effect size estimates (η² = 0.20–0.25) confirming moderate to substantial cluster-level variance, while the neural network attained 93.33% accuracy with a minimal mean squared error (MSE = 2e⁻⁰⁶). Unique Contribution: This study offers an empirically validated hybrid framework synthesizing exploratory clustering with predictive analytics to advance language competency assessment methodology. Conclusion: Arabic language proficiency appears to be organized along a clearly delineated continuum that is statistically distinguishable and reliably predictable. Recommendations: Future research should incorporate broader learner-level variables and apply this framework across diverse educational settings to strengthen generalizability and instructional relevance.

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Author Biographies

Atikah Marwa, Universitas Islam Negeri Maulana Malik Ibrahim, State University of Jakarta

Atikah Marwa is a doctoral student in Arabic Language Education at UIN Maulana Malik Ibrahim Malang, Indonesia. She also serves as a Lecturer (Assistant Professor) in Arabic Language Education at Universitas Negeri Jakarta. Her academic interests focus on Arabic language pedagogy, particularly digital scaffolding, the integration of artificial intelligence in language learning, and knowledge construction within constructivist and social constructivist frameworks. Her research explores technology-enhanced instructional strategies to strengthen learner engagement, cognitive development, and competency formation in Arabic education. In addition to her research activities, she is actively involved in curriculum development, academic instruction, and professional training in higher education contexts. She can be contacted at [email protected].
Danial Hilmi, Universitas Islam Negeri Maulana Malik Ibrahim

Danial Hilmi is a Professor of Arabic Language Education at UIN Maulana Malik Ibrahim Malang, Indonesia. His research focuses on technology-enhanced language learning, curriculum development, and neurolinguistic perspectives in Arabic education, with particular emphasis on digital media integration and innovative instructional design. He has published extensively in national and international journals on blended learning, audiolingual approaches, digital applications, and curriculum evaluation, with his scholarly work indexed in Scopus and SINTA. In addition to his research, he is actively involved in academic leadership, graduate supervision, and professional development activities in Arabic language education. He can be contacted at [email protected].
Syaiful Mustofa, Universitas Islam Negeri Maulana Malik Ibrahim

Syaiful Mustofa is a Senior Lecturer in Arabic Language Education at the Faculty of Tarbiyah and Teacher Training, UIN Maulana Malik Ibrahim Malang, Indonesia. He holds a Doctorate in Arabic Language Education from UIN Maulana Malik Ibrahim Malang and has also completed postgraduate training in Teaching Arabic for Non-Arabic Speakers at King Saud University, Saudi Arabia, as well as a postdoctoral fellowship at Mohammed V University and al-Qarawiyyin University, Morocco. His academic interests focus on Arabic language pedagogy, innovative instructional strategies, teacher training, and higher education collaboration. In addition to his teaching and research, he has held several academic leadership positions and has authored numerous scholarly works contributing to the advancement of Arabic language education in Indonesia. Email: [email protected].
Ayu Desrani, Yogyakarta State University

Ayu Desrani is a doctoral student in Educational Research and Evaluation at Yogyakarta State University, Indonesia. She also serves as a lecturer in the Bandung area, where she is actively involved in teaching and academic development in higher education. Her expertise lies in measurement, assessment, and learning evaluation, with a particular focus on Arabic language education. Her research interests include competency-based assessment, educational data analysis, and the application of quantitative methods and machine learning approaches in language proficiency evaluation. In addition to her research activities, she is engaged in developing innovative instructional and evaluation strategies aimed at improving the quality of language learning and assessment practices. She can be contacted at [email protected].
Apri Wardana Ritonga, Institut As-Syifa

Apri Wardana Ritonga is a lecturer at Institut As-Syifa, Subang, Indonesia. He earned his bachelor's, master's, and doctoral degrees in Arabic Language Education and continues to advance his expertise in this field through teaching, research, and academic engagement. His research interests include Arabic language education, language policy, and language planning. He has published numerous scholarly articles in reputable national and international journals, including several papers indexed in Scopus. Actively engaged in academic research and professional discourse, he is committed to promoting the development of Arabic language education and contributing to educational scholarship. He can be reached at [email protected].

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