University Students Stress Detection During Final Report Subject by Using NASA TLX Method and Logistic Regression

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 pr...

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Bibliographic Details
Main Authors: Alfita Khairah, Melinda, Iskandar Hasanuddin, Didi Asmadi, Riski Arifin, Rizka Miftahujjannah
Format: Article
Language:English
Published: Ikatan Ahli Informatika Indonesia 2025-05-01
Series:Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
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Online Access:https://jurnal.iaii.or.id/index.php/RESTI/article/view/6401
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Summary: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.
ISSN:2580-0760