Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Al Ishlah Jurnal Pendidikan An Nabighoh Jurnal Pendidikan dan Pembelajaran Bahasa Arab
Ayu Desrani
Yogyakarta State University
Education Languange, Linguistic, Communication & Media Mathematics Other

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

Found 2 Documents
Search

 1 
Readiness for Smart Learning in Indonesia’s Islamic Universities Susanto Susanto; Apri Wardana Ritonga; Ayu Desrani; Yohan Rubiyantoro
AL-ISHLAH: Jurnal Pendidikan Vol 17, No 2 (2025): JUNE 2025
Publisher : STAI Hubbulwathan Duri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35445/alishlah.v17i2.6162

Abstract

Technological advancements have driven significant innovations in education, notably through smart learning systems. In Indonesia, Islamic universities are increasingly adopting smart learning to enhance the quality of higher education. This study examines their readiness for smart learning implementation. A mixed-method approach combined quantitative and qualitative data collection. Questionnaires were distributed via Google Forms to 608 students, and additional insights were gathered through interviews. Quantitative data were analyzed using percentage calculations and descriptive analysis, while qualitative findings were thematically organized. The study found that the implementation of smart learning in Islamic universities is moderately effective across four key areas: learning management systems, personalized learning, assessment, and library management systems. Questionnaire scores for all aspects exceeded 6.00, indicating a generally positive perception. Nevertheless, issues such as inadequate infrastructure and insufficient faculty readiness emerged as significant challenges. The findings suggest that Islamic universities in Indonesia are adapting to technological changes but require ongoing development to integrate smart learning practices fully. Addressing infrastructure and faculty training gaps is essential to enhance educational quality, graduate competencies, and institutional competitiveness.
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
An Nabighoh Jurnal Pendidikan Dan Pembelajaran Bahasa Arab Vol 28 No 1 (2026): An Nabighoh
Publisher : Universitas Islam Negeri Jurai Siwo Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32332/an-nabighoh.v28i1.211-232

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.
Co-Authors Apri Wardana Ritonga Apri Wardana Ritonga Atikah Marwa Danial Hilmi Susanto Susanto Syaiful Mustofa Yohan Rubiyantoro