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All Journal Jurnal Optimasi Sistem Industri Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Jurnal Optimalisasi Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat (ABDIRA) Lux Mensana: Journal of Scientific Health Srawung: Journal of Social Sciences and Humanities Journal of Health Sciences and Medical Development Qomaruna
Sutarto, Auditya Purwandini
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CORRELATION BETWEEN LIFE SATISFACTION AND HEART RATE VARIABILITY COHERENCE AMONG BLUE-COLLAR WORKERS – CASE STUDY IN A MALAYSIAN ELECTRONIC MANUFACTURING COMPANY Sutarto, Auditya Purwandini; Khairai, Kamarulzaman bin Mahmad; Wahab, Muhammad Nubli Abdul; Sukadarin, Ezrin Hani
Lux Mensana: Journal of Scientific Health Vol. 2 Issue 2 (2023)
Publisher : jfpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56943/jsh.v2i2.297

Abstract

  Introduction. In addition to having a higher risk of more physical and psychological health problems, blue-collar workers form the largest proportion of the workforce in industries. Thus, it is important to ensure their well-being which can have broader benefits for economic growth and society. This study aims at investigating the relationship between subjective well-being, namely life satisfaction and heart rate variability (HRV) coherence as an objective indicator. The second aim is to evaluate whether any differences in HRV coherence across three levels of life satisfaction groups (dissatisfied, neutral, and satisfied) after a brief session of resonant breathing training. Methods. A total of 313 female blue-collar workers from an electronic manufacturing company participated in this study. All participants completed a satisfaction with life scale (SWLS). Their HRV coherences were then recorded at baseline or rest and after attending a brief session of resonant breathing. Results and Analysis. We found a significant correlation between life satisfaction and HRV coherence after the intervention but not at rest, implying a current state of cardiac activity did not reflect workers’ attitudes toward their life. Moreover, less satisfied workers showed greater cardiac coherence improvement than those who perceived more satisfaction in life. Discussion. This finding suggests that brief resonant breathing training can help workers achieve greater HRV coherence which offers its potential as a strategy to combat workplace stressors.
DEMOGRAPHIC FACTORS AND LIFE SATISFACTION: A STUDY AMONG INDUSTRIAL FEMALE OPERATORS Khairani, Kamarulzaman bin Mahmad; Wahab, Muhammad Nubli Abdul; Sukadarin, Ezrin Hani; Sutarto, Auditya Purwandini
Srawung: Journal of Social Sciences and Humanities Vol. 2 Issue 1 (2023)
Publisher : jfpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56943/jssh.v2i1.306

Abstract

Employee well-being is crucial thing to performance and organizational success which has been studied extensively in the field of industrial and organizational psychology. Those employees with higher levels of well-being are less probable to quit and are typically more productive at the workplace. Therefore, the objective of this research is to examine the effect of several demographic factors on well-being such as life satisfaction among industrial female operators. There were 313 employees of an electronic component manufacturing company who participated in this research. A Life Satisfaction Scale consisting of five questions regarding the global cognitive evaluation of one's life was administered. The collected demographic factors were age, tenure, department or division, and dependents. The results indicated that tenure and marital status were related to life satisfaction. Those who are married and work longer in the company have a higher level of satisfaction than their peers. Meanwhile, the age, department, and dependents were not significant determinants of life satisfaction. Our research indicates the importance of implementing various strategies to improve life satisfaction, especially among newly recruited employees.
Mental Workload Assessment: The Relationship Between Physiological Heart Rate Variability and Subjective NASA-TLX Measures Sutarto, Auditya Purwandini; Izzah, Nailul; Kusumawardani, Rahma Indah
Journal of Health Sciences and Medical Development Vol. 3 No. 03 (2024): Journal of Health Sciences and Medical Development
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/hesmed.v3i03.686

Abstract

The rapid advancement of technology has shifted many jobs to be dominated by mental or cognitive activities. Consequently, it is essential to measure mental workload (MWL) to ensure it does not exceed workers' capacity, which could increase error rates, pose safety risks, reduce productivity, and worsen well-being. This study aims to investigate the relationship between objective and subjective measures of mental workload. Using an experimental approach, HRV physiological signals were recorded from 30 subjects under four different conditions: baseline, MWL test 1 ("d2 attention" test), MWL test 2 ("switcher featuring" test), and recovery. Subjects were also asked to complete the NASA-TLX questionnaire to assess their perceived mental workload levels during the "d2 attention" and "switcher featuring" tests. The results of the repeated measures ANOVA showed significant differences in six HRV parameters across the four conditions. However, post-hoc tests revealed that only heart rate was able to distinguish between the two MWL tests. While NASA-TLX was sensitive enough to differentiate mental workload levels between the two types of tests, no significant correlations were found between each HRV index and NASA-TLX. This suggests a discrepancy between the two types of measures. Further studies are needed to employ different types of tests as well as other physiological measures.
Machine Learning models for the Cognitive Stress Detection Using Heart Rate Variability Signals Izzah, Nailul; Sutarto, Auditya Purwandini; Hariyadi, Mohamad
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 24 No. 2 (2022): Dec 2022
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.24.2.83-94

Abstract

Cognitive domains play a critical role in daily functioning. The prediction of cognitive stress state is important to better monitor work performance. This study aims to explore machine learning models to detect cognitive load or state using heart rate variability (HRV) signals. HRV data were recorded from thirty subjects during rest, two cognitive tasks (d2 Attention and Featuring Switcher task), and recovery. Seven HRV indexes from both time and frequency domains, extracted from raw R-R intervals, were used to identify whether subjects performed cognitive tasks or not. Five classifier models: linear support vector machine (LSVM), kernel SVM radial basis function, k-nearest neighbor (KNN), and random forest (RF), were trained and evaluated using a leave-one-out cross-validation approach. The accuracies and F1-score range from 0.54 to 0.62, with LSVM, showing the best. These acceptable performances indicate the machine learning approach could be used to further distinguish between rest and cognitive state. With the ubiquity of non-invasive and low-cost wearable devices, this finding offers insight to be incorporated into personal work performance monitoring in the digital age.
Pelatihan Peningkatan Pembelajaran Mandiri melalui Literasi Teknologi Large Language Model bagi Siswa Sekolah Menengah Kejuruan Sutarto, Auditya Purwandini; Narto, Narto; Rosyidi, Moh Ririn; Yusuf, Moh Hafidz; Izzah, Nailul; Rufaidah, Anik; Suparno, Suparno; Iksan, Iksan; Hanim, Muhammad Ismail
Jurnal Pengabdian Masyarakat (ABDIRA) Vol 5, No 2 (2025): Abdira, April
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/abdira.v5i2.601

Abstract

To produce high-quality graduates from Vocational High Schools (SMK), Education must develop mastery of hard skills and development of soft skills, including independent learning skills. This Community Service Program (PKM) aims to enhance the technological literacy of students at SMKN 1 Duduksampeyan, particularly in utilizing Large Language Models (LLM) such as ChatGPT and Gemini.. The methods used in this program include lectures and practice sessions. The lecture sessions are designed to provide an understanding of the basic concepts, history, and applications of LLM in various sectors, particularly accounting. The practice sessions involve hands-on training in using LLM, where students are taught effective prompting techniques to complete school assignments and improve their analytical skills. Based on the pre-test questionnaire results, nearly 20% of students had never used LLM, while 5% considered this technology less beneficial. The main challenges faced were limited internet access and a lack of understanding of how to use the technology. This program is expected to equip students with adaptive skills and support the integration of LLM in vocational education.
Evaluasi Pemanfaatan Sistem Informasi Desa (SID) di Kabupaten Gresik (Studi kasus di seluruh Desa pada Kecamatan Ujungpangkah) Syamsi, Nur; Indarto, Tomi; Kholifah, Anik Nur; Hakim, Lutfi; Sutarto, Auditya Purwandini; Suparno, Suparno; Afiyat, Nur
Jurnal Optimalisasi Vol 11, No 1 (2025): April
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/jopt.v11i1.11629

Abstract

This study aims to evaluate the utilization of the Village Information System (Sistem Informasi Desa or SID) in Gresik Regency, with a case study involving all villages in the Ujungpangkah District. The Village Information System (SID) serves as a crucial tool for enhancing the efficiency of public services at the village level and promoting transparency and accountability in village governance. However, its implementation and utilization still face various challenges. This research employs both qualitative and quantitative approaches to obtain a comprehensive overview of the extent to which SID has been implemented and utilized by the villages in Ujungpangkah District. Data were collected through in-depth interviews, questionnaires, and field observations. The analysis was conducted using descriptive and inferential methods to identify the factors influencing SID utilization, including technical aspects, human resources, and government support. The findings indicate that the utilization of SID in these villages remains suboptimal, with the main obstacles being limited technological infrastructure, lack of training for village officials, and insufficient support from the local government. The recommendations derived from this study are expected to serve as a reference for local governments in improving the utilization of SID to achieve better village governance.
Enhancing Above-Knee Prosthetic Design for Inclusive Workplaces: Ergonomic Considerations in Manual Material Handling Muslim, Khoirul; Shafira, Adinda; Kurnianto, Rifko Rahmat; Mihardi, Sandro; Sutarto, Auditya Purwandini
Jurnal Optimasi Sistem Industri Vol. 24 No. 1 (2025): Published in June 2025
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v24.n1.p102-120.2025

Abstract

Employment is crucial for economic sustainability and social inclusion, yet individuals with disabilities face significant barriers. Globally, only 44% of disabled individuals are employed compared to 75% of those without disabilities. Manual material handling (MMH) relies heavily on stability and control in demanding industries such as manufacturing and logistics. Such demands create challenges for individuals with above-knee prostheses, as most current designs focus on walking and do not adequately support the postural and load-bearing requirements of MMH tasks. This study aims to evaluate the performance of transfemoral prosthesis designs during MMH, analyzing the effects of container type, load mass, and their interaction on gait efficiency, discomfort, and stability. Eight male unilateral above-knee amputees (24–39 y) carried handled and handle-less boxes loaded from 4 to 10 kg in a randomised within-subject trial. Gait deviation, perceived discomfort, and steadiness were captured with self-report measures. Two-way analysis of variance analyses showed a significant container × load interaction: handle-less 10 kg loads produced the greatest lateral trunk lean toward the prosthetic side, whereas lighter handled loads minimised deviation. Increasing load also elevated discomfort in the back, waist, stump and contralateral arm and reduced perceived stability. Observed lateral lean and impact-related knee extension suggest three priority modifications: (1) add socket adduction within an ischial-containment design to improve femoral stabilisation, (2) increase knee-swing friction to soften terminal impact, and (3) fit dual-keel feet to cushion heel strike. Implementing these changes may reduce gait errors and fatigue, raising safe lifting capacity for transfemoral prosthesis users in MMH task. Nonetheless, the male-only sample may not capture gender-specificgait strategies; future trials should include female participants and a larger cohort to verify generalisability. These preliminary findings still offer insights into improving prosthetic designs to enhance safety, functionality, and inclusion in industrial MMH tasks.
Addressing Ergonomics in Paddy Milling: Insights from RULA, Nordic Body Map, and Anthropometry Rosyidi, Maulana; Sutarto, Auditya Purwandini; Izzah, Nailul
Jurnal Studi Multidisiplin Qomaruna Vol 1 No 1 (2023): 2023
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Universitas Qomaruddin, Gresik, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62048/qjms.v1i1.21

Abstract

A majority of the rice milling process in Indonesia has been categorized as small and medium enterprises that rely heavily on human labor during their operations. Such activities put human operators at high ergonomic risks, particularly in relation to the onset of musculoskeletal disorders (MSDs) due to postural stress, repetitive exertions, and sustained or static exertions. Ignorance of these ergonomic risk factors is likely to cause permanent disabilities in the future. As such, this study aims to identify ergonomics risk factors in the milling rice process using both the subjective method by Nordic Body Map Questionnaire and the observation method through Rapid Upper Limb Assessment (RULA). The results show that all milling rice operators reported symptoms in their shoulders and low back pain. The final score of RULA was seven or very high risk, indicating that investigation and changes are required immediately. A redesign of the existing step ladder was proposed, developed by an anthropometry-based design approach. The proposed design is expected could reduce the score to 4 or medium risk level
Physiological Signals as Predictors of Mental Workload: Evaluating Single Classifier and Ensemble Learning Models Izzah, Nailul; Sutarto, Auditya Purwandini; Hendi, Ade; Ainiyah, Maslakhatul; bin Abdul Wahab, Muhammad Nubli
Jurnal Optimasi Sistem Industri Vol. 22 No. 2 (2023): Published in December 2023
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (347.324 KB) | DOI: 10.25077/josi.v22.n2.p81-98.2023

Abstract

With a growing emphasis on cognitive processing in occupational tasks and the prevalence of wearable sensing devices, understanding and managing mental workload has broad implications for safety, efficiency, and well-being. This study aims to develop machine learning (ML) models for predicting mental workload using Heart Rate Variability (HRV) as a representation of the Autonomic Nervous System (ANS) physiological signals. A laboratory experiment, involving 34 participants, was conducted to collect datasets. All participants were measured during baseline, two cognitive tests, and recovery, which were further separated into binary classes (rest vs workload). A comprehensive evaluation was conducted on several ML algorithms, including both single (Support Vector Machine/SVM and Naïve Bayes) and ensemble learning (Gradient Boost and AdaBoost) classifiers and incorporating selected features and validation approaches. The findings indicate that most HRV features differ significantly during periods of mental workload compared to rest phases. The SVM classifier with knowledge domain selection and leave-one-out cross-validation technique is the best model (68.385). These findings highlight the potential to predict mental workload through interpretable features and individualized approaches even with a relatively simple model. The study contributes not only to the creation of a new dataset for specific populations (such as Indonesia) but also to the potential implications for maintaining human cognitive capabilities. It represents a further step toward the development of a mental workload recognition system, with the potential to improve decision-making where cognitive readiness is limited and human error is increased.
Do Job Boredom and Distress Influence Self-Report Individual Work Performance? Case Study in an Indonesia Muslim Fashion Industry Sutarto, Auditya Purwandini; Izzah, Nailul
Jurnal Optimasi Sistem Industri Vol. 21 No. 1 (2022): Published in April 2022
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v21.n1.p1-9.2022

Abstract

A creative and innovative workforce is a key determinant of the sustainability of the fashion industry in a highly competitive market. Such characteristics have been linked to employees’ well-being. This study aimed at examining to what extent the employees’ boredom, stress, and work performance levels in a medium-scale Muslim fashion Industry. We employed a cross-sectional study design by administering a set of questionnaires consisting of the Dutch Boredom Scale; Depression, Anxiety, and Stress Scale; and Individual Work Performance in a total sampling of 75 female workers. The association between key variables and demographic factors was analyzed using non-parametric tests while the relationship between boredom, stress, and work performance was analyzed using the regression. Less-educated employees reported more stress and lower work performance while their boredom levels were similar, compared to their counterparts. Job boredom and stress were higher among newly hired employees but no significant difference in self-reported productivity between the two job experience groups was observed. There are also no differences in job boredom, stress, and work performance between sales and non-sales groups. Our regression model shows that job boredom and stress were significant predictors to work performance after controlling age, education, job experience, and type of occupations. These findings support the importance of improving employees’ well-being for better individual performance which may, in turn, lead to any tangible organizational outcomes. Regardless of the case study design, our study may provide insights for other industrial sectors and beyond the context of small and medium enterprises.
Co-Authors Afiyat, Nur Ainiyah, Maslakhatul bin Abdul Wahab, Muhammad Nubli Hanim, Muhammad Ismail Hendi, Ade Iksan, Iksan Indarto, Tomi Khairai, Kamarulzaman bin Mahmad Khairai, Kamarulzaman Mahmad Khairani, Kamarulzaman bin Mahmad Kholifah, Anik Nur Kurnianto, Rifko Rahmat Kusumawardani, Rahma Indah Lutfi Hakim Mihardi, Sandro Mohamad Riyadi Muslim, Khoirul Nailul Izzah Narto Narto, Narto Nur Syamsi Rosyidi, Maulana Rufaidah, Anik Shafira, Adinda Sukadarin, Ezrin Hani Suparno Suparno Wahab, Muhammad Nubli Abdul Yusuf, Moh Hafidz Yusuf, Muhammad Hafidz