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All Journal South East Asia Nursing Research ADI Journal on Recent Innovation (AJRI)
Uddin, Saiful
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Religion Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Health Professions Industrial & Manufacturing Engineering Nursing Public Health

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Factors Related The Job Satisfaction Among Migrant Nurses In Qatar Uddin, Saiful
South East Asia Nursing Research Vol 1, No 1 (2019)
Publisher : University of Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/seanr.1.1.2019.1-6

Abstract

Indonesian nurses migrated out of the country with various motifs, for instance, to earn a better income, enhancing the experience, personal development, and improvement of nursing ability. The phenomenon where nurses turn over from their job can also be caused by job dissatisfaction. Nurses job’s satisfaction needs serious attention since the nurses are spearheading the implementation of services. The objective of this study to get an idea of the level of job satisfaction and to identify factors affecting job satisfaction in Indonesian migrants nurse in Qatar. The research method is a descriptive analytic using cross-sectional approach. The research’s sample represents a total sample of 39 Indonesian nurses who work in an outpatient clinic in Qatar in February 2012. The results showed that Indonesian migrant nurses working in Qatar are satisfied with the work of 51.3%. The results of the analysis showed no correlation between length of service and working time arrangements with job satisfaction, whereas there was no correlation between age, education degree and family status with job satisfaction. The recommendations can be given to health care management in Qatar are to further improve the promotion system and nurses self-development and to increase incentives for nurses who do shift duty. Nurses are advised to increase the level of education and improve the performance of work.
Factors Influencing MCI Preparedness of Paramedic in XYZ Industrial City Sulistyadi, Kohar; Ramli, Soehatman; Uddin, Saiful
ADI Journal on Recent Innovation Vol. 2 No. 2 (2021): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v2i2.24

Abstract

Abstract Mass casualty incident (MCI) in industrial area is a definite threat that can result in environmental damage and loss of property and life. The causes of MCI can range from traffic accidents, industrial accidents, fires, toxic gases and terrorism. Paramedics, along with others emergency response team is among the first to reach at the incident scene to provide aid. Preparation is vital in ensuring that the response is fast, effective and efficient. The objective of the study is to analyze the relationship between knowledge, skills, attitudes and training on MCI Preparedness of paramedic in the XYZ Industrial city. Methodology of this paper is quantitative descriptive with cross sectional approach, while data analysis used the partial least square-structural equation model (PLS-SEM). 108 paramedics in XYZ industrial city involved and completed the survey. The research consist 5 latent variable models with 31 indicator variables. Data retrieval use a direct-share questionnaire. The result from data analysis revealed there is a positive and significant relationship between knowledge, skills, attitudes and training on MCI preparedness at t-value<1.96. Meanwhile, Skill has the most influence on MCI preparedness. Paramedics in the XYZ industrial city have the knowledge, skills, attitudes, training and preparedness that are in the "high category". Exogenous variables; knowledge, skills, attitudes and training explain 65.8% of the preparedness (endogenous variables). Continual commitment from paramedics and management is needed to maintain and enhance preparedness, knowledge, skills, attitudes and training in order to provide better medical emergency services. Keywords: PLS-SEM, MCI, preparedness, paramedics, industrial city.
Co-Authors Kohar Sulistyadi Ramli, Soehatman