Analisis Beban Mental Pekerja untuk Perbaikan Sistem Kerja pada Konveksi XYZ dengan Metode NASA-TLX

Yudhistira, Gisya Amanda; Febrianti, Melinska Ayu; Fathurrohman, Mohammad Arsyad

doi:10.20961/performa.19.2.46426

Cited by 5 publications

(5 citation statements)

References 4 publications

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“…On the other hand, the element with the lowest Average SOFI Score average product value is the physical demand element, which is 128.80. This research result is consistent with the study conducted by Yudhistira et al [6], which found that the physical demand indicator of 505 is the lowest among other indicators.…”

Section: Discussionsupporting

confidence: 92%

Analysis of Mental Workload and Fatigue Level in Online Learning during the Pandemic among Industrial Engineering Students (A Case Study at Buana Perjuangan University of Karawang)

Auliani,

Rahdiana,

Suhara

et al. 2024

SHS Web Conf.

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Adjustments in online learning systems during the COVID-19 pandemic have led to an increase in mental workload and fatigue levels among students. This study aims to determine the influence of independent factors and the relationship between mental workload and fatigue levels among Industrial Engineering students during online learning. The research methods used were NASA-TLX and SOFI. The results show a significant influence of marital status on the level of mental workload with a p-value of 0.016, while there is no significant influence of student status and gender with p-values of 0.435 and 0.210. However, there is a significant influence of student status and gender on fatigue level with p-values of 0.008 and 0.000, while marital status has a significant influence with a p-value of 0.326. The correlation test results show that in the NASA-TLX method, 6 pairs of elements have a significant relationship with a p-value of 0.000, while the remaining 8 pairs of elements do not have a significant relationship with p > 0.05. Furthermore, the SOFI method shows all elements have a significant relationship with a p-value of 0.000. The findings of this study can serve as evaluation for institutions to create effective and successful online learning.

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Section: Discussionsupporting

confidence: 92%

Analysis of Mental Workload and Fatigue Level in Online Learning during the Pandemic among Industrial Engineering Students (A Case Study at Buana Perjuangan University of Karawang)

Auliani,

Rahdiana,

Suhara

et al. 2024

SHS Web Conf.

View full text Add to dashboard Cite

show abstract

“…The submission time has a range of 2-4 days which gives students the opportunity to do the assignment properly and correctly and it uses e-learning. The reason for the importance of the e-learning learning model is learning in an era where there is a lot of information to always be up-to-date and accessible (Yudhistira, 2021). The workload received by students will always have its own effects, whether light or heavy.…”

Section: Q1: Are Learning Objectives Clear?mentioning

confidence: 99%

English Online Class: Evaluation and Students’ Learning Boredom

Zulfa,

Galuhwardani,

Tazali

2024

E-Jou

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English online class has been conducted as a variety of language learning. It is also as an implementation of the advance of technology and educational system in post pandemic era. This study aimed at investigating English online class as an evaluation and describing students’ learning boredom appeared during class. It employed students majoring Information System and Accounting Information System to ask for their ideas, perception and complains by spreading questionnaires and open-ended interview. The data gathered were analyzed by describing and interpreting them qualitatively. It resulted that English online class could be implemented as a new way of learning and there was learning boredom had by students with some factors, internally and externally.

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“…As students, they bear the responsibility of executing tasks and engaging in the learning process, which can exert internal and external pressure [19]. Industrial engineering students, notably, face numerous assignments from courses and practicum tasks, often dominating their daily routines.…”

Section: Industrial Engineering Advance Research and Applicationmentioning

confidence: 99%

Mental workload analysis of Industrial Engineering students using Subjective Workload Assessment Technique (SWAT)

Leonardo,

Sarvia

2023

JISS UNTIRTA

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Mental stress can stem from uncontrolled physical demands, environmental factors, and social situations. In academic environments, this stress often impacts student performance, notably during lecture activities. This study aims to analyze the mental workload experienced by the 2020 class of Industrial Engineering students at a private university. Its goal is to identify factors contributing to students' mental workload and propose suggestions to address these challenges. The Subjective Workload Assessment Technique (SWAT) was utilized to assess mental workload through respondent evaluations. Additionally, a Fishbone Diagram was employed to pinpoint factors leading to increased mental workload in students. Questionnaires were distributed to all students enrolled in at least 18 credits during the odd semester of 2022-2023. The findings indicate that students of the 2020 class experience mental burden during both class and practicum activities. Specifically, class activities accounted for 46.78% in the time dimension and 25.77% in the effort dimension, while practicum activities accounted for 55.34% in the time dimension and 20.39% in the effort dimension. Stress levels were recorded at 27.45% for class activities and 24.27% for practicum activities. The analysis identifies various stress-inducing factors in teaching and learning activities, including challenges in studying quiz and practicum materials, active participation in practicum activities, completion of practicum reports, and effective communication with practicum partners. To address these challenges, several recommendations are proposed, such as restructuring lecture schedules, equitable distribution of assignments and quizzes throughout the semester, fostering effective time management, aligning credit loads with individual capacities, among other strategies.

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Analisis Beban Mental Pekerja untuk Perbaikan Sistem Kerja pada Konveksi XYZ dengan Metode NASA-TLX

Cited by 5 publications

References 4 publications

Analysis of Mental Workload and Fatigue Level in Online Learning during the Pandemic among Industrial Engineering Students (A Case Study at Buana Perjuangan University of Karawang)

Analysis of Mental Workload and Fatigue Level in Online Learning during the Pandemic among Industrial Engineering Students (A Case Study at Buana Perjuangan University of Karawang)

English Online Class: Evaluation and Students’ Learning Boredom

Mental workload analysis of Industrial Engineering students using Subjective Workload Assessment Technique (SWAT)

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