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All Journal JURNAL NASIONAL TEKNIK ELEKTRO Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control International Journal of Engineering, Science and Information Technology Jurnal INFOTEL
Miftahujjannah, Rizka
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Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

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University Students Stress Detection During Final Report Subject by Using NASA TLX Method and Logistic Regression Khairah, Alfita; Melinda; Hasanuddin, Iskandar; Asmadi, Didi; Arifin, Riski; Miftahujjannah, Rizka
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 3 (2025): June 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i3.6401

Abstract

Stress is a psychological response that occurs when someone faces pressure or demands that exceed their ability to adapt. In the context of a final-year student, stress is often a significant problem due to academic pressure, such as completing final assignments, as well as demands to immediately prepare to enter the workforce and demands to immediately prepare to enter the workforce. Research shows that stress that is not managed properly can cause various negative effects, such as sleep disorders and decreased cognitive function. This study aimed to identify and analyze stress levels among final-year students who completed a final report by integrating physiological and psychological data. In this study, 30 students were assessed using a wearable system to obtain physiological data, such as heart rate and body temperature, while subjective assessments were carried out using the NASA-TLX method to measure mental workload. The results showed that 19 out of 30 respondents experienced significant levels of stress and 11 respondents were in normal conditions, with the main causal factors including high academic pressure and distance regarding the future. In addition, the logistic regression analysis applied in this study succeeded in developing a predictive model with an accuracy of 94% in identifying students' stress conditions. This shows that this method is sufficiently accurate for detecting stress symptoms in final-year students.
Co-Authors Acula, Donata D Acula, Donata D. Alfariz, Muhammad Fauzan Amalia Amalia Arifin, Riski Asmadi, Didi Basir, Nurlida D Acula, Donata Farhan Ghimri, Agung Hilm Hasanuddin, Iskandar Khairah, Alfita Khairia, Syaidatul Melinda Melinda Melinda Muhammad Irhamsyah Oktiana, Maulisa Qadri Zakaria, Lailatul Ramadhan, Irsyan Sakarkar, Gopal Siti Rusdiana Yunidar Zainal, Zulfan