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All Journal G-Tech : Jurnal Teknologi Terapan jurnal syntax admiration
Tata Sutabri
Universitas Bina Darma, Indonesia
Aerospace Engineering Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics

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Desain UI/UX Aplikasi Mobile LMS dengan Metode Design Thinking untuk Efektifitas Pembelajaran Mahasiswa di Perguruan Tinggi Bosya Perdana; Tata Sutabri
Jurnal Syntax Admiration Vol. 5 No. 12 (2024): Jurnal Syntax Admiration
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jsa.v5i12.1925

Abstract

This research seeks to develop the UI/UX of the Mobile Learning Management System (LMS) application by utilizing the Design Thinking methodology to improve the effectiveness of student learning in higher education. Design Thinking is used because of its user-centric methodology, guaranteeing that LMS apps align with the preferences and behaviors of students who are increasingly relying on mobile devices in their daily routines. Application development goes through the stages of Empathize, Define, Ideate, Prototype, and Test, with validation carried out using the System Usability Scale (SUS) approach. The assessment involved five students from various academic fields who are proficient in desktop-based Learning Management Systems (LMS). The test results showed a SUS score of 78, categorized as "Good" and close to "Very Good". This score signifies the program's excellent usability, easy navigation, and functions that encourage learning flexibility, including content access, assignment submission, and discussion forums. This study shows that the mobile Learning Management System created using the Design Thinking methodology significantly increases student access to lecture materials and encourages the efficacy of learning in higher education. Suggestions for improvements include conducting assessments with a wider group of participants and implementing design iterations to refine features based on user feedback.
Penggunaan Algoritma Greedy dan Deep Reinforcement Learning untuk Optimasi Jadwal Operasi dalam Adaptive Scheduling Muhammad Andika Fadilla; Tata Sutabri
G-Tech: Jurnal Teknologi Terapan Vol 9 No 2 (2025): G-Tech, Vol. 9 No. 2 April 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/gtech.v9i2.6844

Abstract

Operating room scheduling faces persistent challenges in healthcare facilities worldwide, with inefficiencies leading to resource wastage, extended patient waiting times, and staff burnout. This study addresses these challenges through three methodologies: greedy algorithm, deep reinforcement learning (DRL), and a novel hybrid model. Analysis of 35,000 surgical procedures revealed significant inefficiencies in current practices, including OR overutilization (463.87%), substantial waiting times (170.07 minutes), and frequent delays (58.39% of procedures). The hybrid model demonstrated superior performance, achieving a 34.2% reduction in OR utilization, 55.9% reduction in waiting times, and 87.5% improvement in on-time procedures compared to baseline. These improvements translated into significant clinical benefits, including reduced staff overtime (57.1%) and enhanced emergency case accommodation (17.6%). The hybrid model's resilience to operational disruptions and balanced performance across multiple dimensions provides compelling evidence for implementing adaptive scheduling methodologies in clinical practice, offering a comprehensive solution that balances efficiency, adaptability, and patient-centered care.
Co-Authors Bosya Perdana Muhammad Andika Fadilla