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Ishwara, Luki
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A Systematic Literature Review on Intelligent Tutoring Systems for Outcome-Based Education in Higher Education Syaddad, Hasbu Naim; Salim , Andi Agus; Ishwara, Luki; Hasibuan , Zainal Arifin; Kurniawan , Bobi; Supatmi, Sri
Technologia Journal Vol. 3 No. 1 (2026): Technologia Journal-February
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/pd6g0a26

Abstract

Penerapan Outcome-Based Education (OBE) di pendidikan tinggi menuntut pendekatan pembelajaran yang mampu mendukung pencapaian capaian pembelajaran dan kompetensi mahasiswa secara terukur. Intelligent Tutoring Systems (ITS) merupakan sistem pembelajaran berbasis kecerdasan buatan yang bersifat adaptif dan personal, sehingga berpotensi mendukung implementasi OBE. Namun, temuan empiris terkait penerapan dan efektivitas ITS dalam konteks OBE di pendidikan tinggi masih tersebar dan belum tersintesis secara sistematis. Penelitian ini bertujuan untuk mengkaji peran, karakteristik, dan efektivitas ITS dalam mendukung outcome-based education di pendidikan tinggi. Penelitian ini menggunakan metode systematic literature review dengan mengacu pada pedoman PRISMA 2020. Pencarian literatur dilakukan melalui basis data Scopus terhadap artikel jurnal berbahasa Inggris yang dipublikasikan pada periode 2018–2025. Dari proses seleksi yang ketat, sebanyak 56 artikel jurnal memenuhi kriteria inklusi dan dianalisis menggunakan pendekatan sintesis naratif. Hasil kajian menunjukkan bahwa ITS umumnya dibangun atas komponen inti berupa model peserta didik, model domain, model pedagogik, dan antarmuka tutor. Teknik kecerdasan buatan yang banyak digunakan meliputi machine learning, rule-based systems, Bayesian networks, dan natural language processing. Sebagian besar studi melaporkan bahwa ITS berdampak positif terhadap kinerja akademik, penguasaan kompetensi, dan keterlibatan mahasiswa. Meskipun demikian, penelitian lanjutan masih diperlukan untuk mengevaluasi dampak jangka panjang dan integrasi ITS dalam kerangka OBE di tingkat institusi.  
Computer Vision Analysis for Traffic Monitoring and Road Safety in Smart City Concept Ishwara, Luki; Syaddad, Hasbu Naim; Salim, Andi Agus; Kurniawan, Bobi; Bachtiar, Adam Mukharil; Rainarli, Ednawati
Technologia Journal Vol. 3 No. 1 (2026): Technologia Journal-February
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/vk562576

Abstract

Rapid urban growth and rising traffic complexity require Smart City solutions that move beyond passive CCTV toward intelligent, real-time traffic management. This study examines how computer vision–based analytics contribute to road safety when integrated into an Intelligent Transportation System (ITS). A quantitative quasi-experimental design was applied across multiple intersections using a 12-month before–after window. Data were collected from video analytics (vehicle and pedestrian detection, tracking, violations, road conditions), adaptive signal logs, crash and injury records, near-miss indicators, and contextual variables such as weather and traffic volume. Analysis combined perception validation (mAP, tracking accuracy), time-series operational assessment, and Difference-in-Differences modeling to estimate safety impacts. Results show high perception reliability (mAP > 0.85) and significant operational improvements, including a 33% reduction in waiting time and 35% shorter queues. More importantly, red-light violations decreased by 39%, near-miss events by 45%, crash frequency by 42%, and severity index by 37%. The findings indicate a causal pathway from vision-based perception to adaptive control and enforcement, leading to measurable safety gains. The study concludes that computer vision serves as a safety governance instrument within Smart City ITS when detection outputs are tightly coupled with intervention mechanisms.