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All Journal Journal of English Education Forum (JEEF)
Kamaluddin, Mohamad Ihsan
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Education Languange, Linguistic, Communication & Media

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Cultural Diversity and Language Education: Lessons from the European Migrant Crisis Mukti, Muhammad Abdee Praja; Maulana, Muhamad Trian; Kamaluddin, Mohamad Ihsan; Wardoyo, Cipto
Journal of English Education Forum (JEEF) Vol. 4 No. 4 (2024): OCT-DEC 2024
Publisher : Program Studi Pendidikan Bahasa Inggris

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jeef.v4i4.808

Abstract

This study investigates the European migration crisis, focusing on its root causes, cultural conflicts, and social integration challenges. The research highlights how armed conflict, political instability, economic disparities, and climate change drive mass migration and create significant social and economic pressures on host countries. Using a systematic literature review, this paper identifies the main barriers to integration, including language differences, discrimination, and unequal access to resources. The findings emphasize the importance of comprehensive policies that promote social cohesion, inclusive integration programs, and international cooperation to address migration flows and humanitarian concerns effectively. This research contributes to the ongoing discussion on sustainable migration policies by providing insights into both immediate and long-term strategies for managing migration challenges.
Culture and Syntax: A Qualitative Comparative Study on How Cultural Norms Shape Sentence Structure Kamaluddin, Mohamad Ihsan
Journal of English Education Forum (JEEF) Vol. 5 No. 3 (2025): JUL-SEP 2025
Publisher : Program Studi Pendidikan Bahasa Inggris

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jeef.v5i3.874

Abstract

This study investigates how cultural norms shape syntactic structures by comparing sentence construction in Indonesian and English using a qualitative literature review approach. Through a critical analysis of recent linguistic and cross-cultural studies, the research explores how cultural values such as collectivism, individualism, politeness orientation, and communication context influence syntactic features like word order, voice, ellipsis, and pragmatic forms. The findings demonstrate that Indonesian syntax, with its flexibility in structure, frequent use of passive constructions, and reliance on contextual ellipsis, aligns with high-context and collectivist cultural values that emphasize relational harmony and indirectness. In contrast, English syntax, characterized by more rigid word order and subject-centered constructions, reflects low-context and individualistic norms that value clarity and directness. These syntactic tendencies are not merely linguistic choices but manifestations of deeper cultural orientations. The study emphasizes the importance of integrating cultural awareness into language education and linguistic technology, as syntactic forms carry social meanings that affect communication outcomes. It concludes that syntax should be understood not only as a structural aspect of language but also as a culturally embedded system shaped by the social and cognitive frameworks of its speakers.
Accuracy Analysis of DeepL: Breakthroughs in Machine Translation Technology Kamaluddin, Mohamad Ihsan; Rasyid, Moch. Wildan Khoerul; Abqoriyyah, Fourus Huznatul; Saehu, Andang
Journal of English Education Forum (JEEF) Vol. 4 No. 2 (2024): APR-JUN 2024
Publisher : Program Studi Pendidikan Bahasa Inggris

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jeef.v4i2.681

Abstract

This study examines the accuracy and technological innovations of DeepL, a prominent machine translation tool. Through a comprehensive literature review, we analyze DeepL's performance compared to other translation systems, exploring its advanced neural network architecture and training methods. Key findings indicate that DeepL consistently outperforms other tools in BLEU scores and human evaluations, particularly excelling in handling context, idiomatic expressions, and specialized terminology. The research highlights DeepL's use of the Transformer model, diverse training data, and techniques like transfer learning and data augmentation. Practical applications across academic, professional, and educational sectors are discussed, with special emphasis on how DeepL benefits students and teachers by facilitating multilingual learning, enhancing comprehension of foreign texts, and assisting in accurate translation of academic materials. User feedback underscores DeepL's accuracy and user-friendly features. While demonstrating significant advancements in machine translation technology, this study also acknowledges areas for potential improvement, contributing to the ongoing development of AI-driven language solutions.
Co-Authors Abqoriyyah, Fourus Huznatul Andang Saehu, Andang Cipto Wardoyo Maulana, Muhamad Trian Mukti, Muhammad Abdee Praja Rasyid, Moch. Wildan Khoerul