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 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.

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Publication Details

Journal
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Published
2025-05-24
DOI
https://doi.org/10.29207/resti.v9i3.6401
Primary Topic
Smart Systems and Machine Learning
Type
article
Field-Weighted Citation Impact
0.00

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

Didi Asmadi, Riski Arifin, Melinda Melinda, Iskandar Hasanuddin et al.
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Smart Systems and Machine Learning
article

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

Didi Asmadi, Riski Arifin, Melinda Melinda, Iskandar Hasanuddin, Alfita Khairah, Rizka Miftahujjannah
article en

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.

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)Vol. 9(3)
Universitas Syiah Kuala (ID)
Universitas Syiah Kuala
Openalex Percentile: Top 88%
Smart Systems and Machine Learning
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