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All Journal Indonesian Journal of Integrated English Language Teaching Jurnal Manajemen Informatika dan Sistem Informasi
Ibrahim, Akbar
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Religion Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Social Sciences

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Teachers’ Perspectives on Seating Arrangements for English Language Learners Saputra, Muhammad Ari; Ibrahim, Akbar; Lubis, Asmaul Husna; Khairani, Nikmah
Indonesian Journal of Integrated English Language Teaching Vol 11, No 1 (2025): IJIELT: VOLUME 11, Number 1, 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijielt.v11i1.36596

Abstract

Students’ learning quality in the classroom is influenced by the learning environment. The ability of teachers to control the seating arrangement is required. This study sought to understand how English teachers saw setting arrangements and what challenges they encountered while implementing them. A descriptive study using a qualitative methodology was used in this investigation. The study’s findings showed how crucial the English teacher’s opinion of the seating arrangement pattern is. The class arrangement that has been used is a separate table for solitary work and a seating pattern. In an effort to make learning enjoyable and not boring. One of the challenges that teachers frequently encountered was the state of the students, who frequently made noise when the sitting arrangement was altered. They were not only difficult to control, but they also objected to the change; b) The classroom’s tight space also makes it difficult to implement the seating arrangement plan. In order to improve the quality of learning for students, this research study aims to motivate teachers to design the learning environment.
SISTEM PERINGATAN DINI UNTUK DETEKSI AKTIVITAS AI BERBAHAYA BERBASIS MACHINE LEARNING Ibrahim, Akbar; Tue Rebong, Hendrikus; Adiputra, Jason; Satria, Fauzan; Ilyas, Muhammad; Budiarti, Yusnia; Heriyanto; Amsury, Fachri
Jurnal Manajemen Informatika dan Sistem Informasi Vol. 9 No. 1 (2026): MISI Januari 2026
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/misi.v9i1.1869

Abstract

Perkembangan teknologi kecerdasan buatan (AI) telah memberikan banyak manfaat di berbagai sektor, namun juga menimbulkan risiko keamanan akibat potensi penyalahgunaan sistem AI. Penelitian ini mengusulkan sistem peringatan dini berbasis machine learning untuk mendeteksi aktivitas AI berbahaya secara proaktif melalui prompt berbasis teks. Sistem ini menerapkan pendekatan klasifikasi teks menggunakan algoritma Logistic Regression, Linear Support Vector Classifier (SVC), dan Random Forest dengan ekstraksi fitur TF-IDF. Hasil pengujian menunjukkan bahwa seluruh model menghasilkan performa yang kuat dengan tingkat akurasi di atas 95%. Model Random Forest menunjukkan performa tertinggi dengan akurasi sebesar 95,64% dan nilai ROC-AUC 95,64%, sementara Linear SVC dan Logistic Regression memberikan hasil yang stabil dan kompetitif. Temuan ini menunjukkan bahwa sistem yang diusulkan efektif sebagai mekanisme peringatan dini dalam mendeteksi prompt AI berbahaya sebelum terjadi eskalasi ancaman.
Co-Authors Adiputra, Jason Fachri Amsury Heriyanto Khairani, Nikmah Lubis, Asmaul Husna Muhammad Ari Saputra, Muhammad Ari Muhammad Ilyas Satria, Fauzan Tue Rebong, Hendrikus Yusnia Budiarti