In the current era of globalization, the development of the world is so fast and rapid that it demands every company in various industrial fields to develop along with the rapid development. Organizations and companies are required to quickly respond to changing times and quickly adapt to the environment in facing all forms of change to survive in global competition. In this increasingly fierce world competition, every organization or company is competing to strengthen its human resources [1].

To strengthen human resources, of course, there are obstacles experienced by organizations or companies, one of which is a high turnover rate. This problem is a common problem both nationally and globally, where almost all organizations experience this problem. Hirschi and Spurk [2], said "Turnover intention is a classic problem that is always faced by entrepreneurs". The high rate of employee turnover will affect the company's operations, this proves that human resources have an important position and role in the company, besides having an important role, human resources are also the foundation for the company, without human resources the company will find it difficult to achieve the goal [3].

So to achieve company goals, human resources need to be managed as well as possible so that company operations can run well and regularly. Human resource management is a very important concept because the human factor as a resource can generate a comparative advantage for an organization [4].

One of the problems in human resources is the management of high employee turnover. Abdalla et al. [5], said that if employee turnover occurs frequently, the continuity of the company's operations will be disrupted and cause problems for the company. High turnover results in several losses for the company, such as costs that must be borne and time spent on recruiting, selecting and training to get employees who have the same quality as those leaving the company, as well as losses due to the loss of employees with the best quality [6].

The main thing that will become a problem in a company or organization is that the funds issued by the company to carry out the employee recruitment process up to the various pieces of training provided to employees will be in vain [7]. New employees need to adapt quickly so that work left by previous employees can be handled properly, therefore a replacement is needed that is commensurate and adapts quickly to the environment and workload that will be given to reduce the possibility of neglected work or avoid chaos within the company. Problems in HR will determine success in achieving a company's goals, where these goals will not be achieved if employees do not carry out their work properly [8].

Human Resource Management

Mululi et al. state that "Human resource management, abbreviated HRM, is a science or method of how to manage the relationships and roles of resources (labour) owned by individuals efficiently and effectively and can be used optimally so that the common goals of the company, employees and society are achieved. maximum". Furthermore, Nalini and Alexander Pravin Durai, [9], states that human resource management is the process of acquiring, training, appraising and compensating employees and managing labour relations, health and safety and matters related to fairness. Kim and Lee, [10], states that human resource management is the utilization, development, assessment, remuneration and management of individual members of an organization or group of workers.

Based on the opinions of the experts above, it can be concluded that human resource management is the science of managing every role, task and problem of each individual or employee in carrying out responsibilities towards the company so that existing human resources can be used optimally effectively and efficiently to achieve goals desired by the company.

Turnover Intention

Turnover intention (the desire to change jobs) is the tendency or intensity of individuals to leave the organization for various reasons, including the desire to get a better job [11]. Meanwhile, according to Ivanovic et al. [12], the Turnover intention is the result of an employee's evaluation of the possibility of leaving and not realizing its sustainability in the organization. Furthermore Waterwall and Alipour [13], reveals that turnover intention is a feeling that arises from an individual, namely the intention to quit his job voluntarily according to his own choice. From some of the opinions of the researchers above, it can be concluded that turnover intention is an attitude that generally exists within every individual in an organization that arises from self-evaluation of his work which causes the intensity of a worker to leave the organization according to his wishes.

Job Satisfaction

Böckerman et al., [14], said that job satisfaction is a positive feeling about work, which results from an evaluation of its characteristics. Meanwhile, according to Widyanty [15], job satisfaction is a driver of employee and organizational results because job satisfaction is the result of employee perceptions of how well their work provides things that are considered important. Furthermore, job satisfaction is a state of positive emotions or negative emotions that come from an assessment of the work or work experience of employees. Demirović Bajrami et al. [16], state that job satisfaction is a pleasant emotional attitude and loving his job. This attitude is reflected in work morale, discipline and work performance. Each individual has a different level of satisfaction according to the value system that applies to him. The higher the assessment of the activities that are felt by individual wishes, the higher the satisfaction with these activities.

From several expert opinions regarding job satisfaction above, it can be concluded that job satisfaction is a set of feelings of employees or workers that are individual in nature in the form of attitudes towards their work so that employees evaluate and assess positively or negatively their work.

Work Stress

Mariappanadar [3], states that work stress is a tension that results in an imbalance in the psychological state of employees which can affect their way of thinking, emotions and conditions themselves. Whereas Sroka and Vveinhardt [17], interpret work stress as a condition in which employees feel pressure in dealing with work. Work stress can cause a person's emotional state to be unstable, excessive anxiety, tension, nervousness and other disturbances. Furthermore Smith et al. [18], say stress is external demands on a person, for example, objects in the environment or stimulation that is objectively harmful. Stress is also defined as unpleasant pressure, tension or disturbance that comes from outside one's self. Stress is an adaptive response linked by individual psychological characteristics and/or processes, which is a consequence of any external action, situation, or event that places special psychological/physical demands on a person.

Based on some of the opinions above, it can be concluded that work stress is a condition in which a person or individual experiences tension caused by external demands, causing emotional instability.

Relationship Between Job Satisfaction and Turnover Intention

Job satisfaction is a factor for employees to assess their feelings as individuals towards their work. This can lead to positive or negative feelings. A person with a high level of job satisfaction holds positive feelings towards their job, while a dissatisfied person holds negative feelings towards their job. This states that a person with a high level of satisfaction is more likely to generate positive feelings or impressions of his work to enable a worker to remain in the company where he works, whereas someone with a low level of satisfaction can cause negative feelings or impressions of his work. This leads to disappointment and thoughts of leaving.

• H1: Job satisfaction has a negative and significant effect on turnover intention

Relationship between Workload and Turnover Intention

The workload is a feeling or impression that arises from the interaction between demands and tasks that must be done by an employee in a company. if the perceived workload exceeds their capacity or in other words an employee experiences an excessive workload, this can lead to feelings of wanting to leave the company. the higher the perceived workload the higher the desire to leave.

• H2: Workload has a positive and significant effect on turnover intention

Relationship between Job Stress and Turnover Intention

Job stress is the pressure an employee faces on his job. This creates an emotional and physical imbalance. If an employee experiences a high level of work stress, then when his emotional state cannot be controlled, there will be a desire to leave his job. the higher the level of work stress felt by employees, the intention to move or the desire to leave the company will increase.

• H3: Job stress has a positive and significant effect on turnover intention

Figure 1: Research Framework

The design used in this study is to use quantitative research in the form of a causal relationship, namely research based on influence and causation. This causal research is research that aims to test the hypothesis of the relationship between variables, namely job satisfaction, workload, work stress and turnover intention.

The data collection technique used was a questionnaire in the form of a set of statements to be responded to by the respondent with a Likert scale, namely a measurement of the respondent's answers in the form of numbers 1 to 5 which states that the greater the number, the greater the value of the agreement.

The population in this study are employees who live in Jakarta. For sampling, it refers to Hair, 2016, namely 5x the number of indicators, so based on this, the number of samples in this study was 100 people. The sampling technique used is probability random sampling where all members of the population have the same opportunity to be used as research samples.

The data analysis carried out includes grouping data based on variables and types of respondents, tabulating data based on variables from all respondents, presenting data for each variable studied, performing calculations to answer the problem formulation and performing calculations to test the hypotheses that have been proposed. Then the test that will be carried out is as follows:

Validity Test

Is an instrument measure to determine whether the research instrument used is legitimate or valid for use in research? According to Ghozali, the validity test is used to measure the legitimacy or validity of the statement items in the questionnaire. This test aims to find out whether the questions in the questionnaire made can measure what is to be measured.

Reliability Test

According to Ghozali, a reliability test is a tool for measuring a questionnaire which is an indicator of a variable. A questionnaire is said to be reliable if one's answers to statements are consistent or stable from time to time. Reliability indicates that the instrument is trusted enough to be used as a data collection tool because the instrument is good. The test tool used is Cronbach's alpha coefficient with the following conditions: 

• If Cronbach's alpha value is >0.7, the research instrument is reliable

• If the value of Cronbach's alpha <0.7 then the research instrument is not reliable

Part Least Square Analysis

In this study, the Partial Least Square (SmartPLS) version 3.0 program will be used to analyze the data. Ghozali stated that Partial Least Square (PLS) was first developed by Herman Wold as a general method for estimating path models that use latent constructs with multiple indicators. PLS is intended for causal predictive analysis in situations of high complexity and low theoretical support. The steps for testing using PLS are as follows

Evaluation of the Measurement Model (Outer Model)

The outer model often also called (the outer relation or measurement model) defines how each indicator block relates to its latent variables.

Convergent Validity

Convergent validity can be seen from the value of the standardized loading factor. Measurement (indicator) with its construct. a loading factor value above 0.7 can be said to be ideal, meaning that the indicator is said to have good validity. However, in the early stages of research, standardized loading factor values ​​above 0.5 could be considered sufficient and acceptable, while those below 0.5 were excluded from the model.

Discriminant Validity

To test discriminant validity, it can be seen through cross-loading, for each variable it must be >0.70. It can also be measured by comparing the AVE squared root value with the correlation value between the constructs in the model. Discriminant validity is said to be good if the AVE square root for each construct is greater than the correlation between constructs in the model. The recommended AVE value must be greater than 0.50, this shows that 50% or more of the variance of the indicator can be explained.

Composite Reliability

Composite Reliability is done by looking at the view latent variable coefficients. From this output, the criteria are seen from two things, namely composite reliability and Cronbach's alpha, if in all variables the value of composite reliability and Cronbach's alpha ≥0.70 it can be said that the construct is declared to have good reliability or the questionnaire used as a research tool has been consistent.

Evaluation of the Structural Model (Inner Model)

The Inner Model specifies the relationship between latent constructs and other latent constructs. Evaluation of the structural model (inner model) includes the model fit test, path coefficient and R2. This model fit test is used to determine whether a model matches the data. In the model fit test, there are 3 test indices, namely average path coefficient (APC), average R-squared (ARS) and average variance factor (AVIF).

Description of Respondents

The following is a description of the respondent data obtained through a questionnaire distributed to 100 employees (Table 1).

Table 1: Distribution of Respondents by Gender

Respondents in this study were fifty-nine people or 59% male and forty-one people or 41% female respondents.

Respondents in this study were dominated by employees with an age range of 25 to 30 years as many as 44 people or 44%. Respondents aged under 25 years were 8%, with an age range of 31 to 36 years 35% and respondents with an age range above 36 years were 13% (Table 2).

Table 2: Distribution of Respondents by Age

Respondents in this study with a high school education level or equivalent were 23 people or 23%, 17 people or 17% graduated with a diploma, 52 people or 52% with a bachelor's degree and 8 people with a master's degree or 8% (Table 3).

Table 3: Distribution of Respondents by Education

Respondents based on years of service were dominated by employees who worked for 4 to 6 years as many as 48% or 48 people, working years under 1 year as many as 4 people or 4%, working years 1 to 3 years as many as 18 people or 18% and years of service over 6 years as many as 30 people or 30% (Table 4).

Table 4: Distribution of Respondents Based on Years of Service

Instrument Testing

The following is a measurement model test (outer model), namely validity and reliability testing.

From the results of statistical validity data testing, it can be seen that no indicators were rejected or ruled out because they met the validity test requirements with a loading factor value >0.7 and an AVE value >0.50 so that all indicators in the construct were declared valid (Table 5).

The results of reliability testing show value Cronbach's Alpha and Composite Reliability >0.70 so it can be concluded that all variables are declared reliable and have good reliability.

Table 5: Validity and Reliability Testing

Source: Processed data for 2022

Structural Model Test Results (Inner Model)

R Square Test: R-square is also referred to as the coefficient of determination which describes how far the dependent data can be explained by independent data.

The results of the R-square test which explain the Turnover Intention construct variable are explained by the construct variables Job Satisfaction, Workload and Work Stress of 54.8% and 45.2%, meanwhile, are explained by other variables not included in the study (Table 6).

Table 6: R-Square Test Results

F Square Test

F square is a test to find out how much influence the exogenous construct has on the endogenous construct, in this test, there are 3 ranges of values, namely 0.02; 0.15; 0.35 for indicating small, medium and large effects of exogenous constructs on endogenous constructs. F2 effect size is a measure to assess the relative magnitude of the impact of exogenous constructs on endogenous constructs.

The F square value of the exogenous construct towards the endogenous construct in this study where the Job Satisfaction variable has the greatest influence on the Turnover Intention variable with an F square value of 0.316 is included in the large value range and the Workload variable has the smallest influence with an F square value of 0.078 included in the range medium value (Table 7).

Table 7: F-square Test Results

Model Fit Test

Evaluation of the fit model in this study was carried out using three test models including Chi-square, Standardized Root Mean Square residual (SRMR) and Normal Fit Index (NFI). According to Bentler and Bonett, the model can be accepted if the Chi-square value is more than 0.9 (Chi-square>0.9). While Hair et al. suggested that the model will be considered to have a good fit if the Standardized Root Mean Square Residual (SRMR) value is below 0.1. Evaluation of the fit model is done by looking at the Normal Fit Index (NFI) value. SRMR, Chi-square and NFI values ​​can be seen in the Table 8.

The value of the calculation using smart PLS shows the value of SRMR, Chi-square and NFI, where from these data it can be concluded that the research model can be said to be fit because it meets all the requirements.

Table 8: Model Fit Test Results

Hypothesis Testing

Path coefficients (path coefficients) are used to see the hypothesized relationship between constructs. According to Helm et al. in Hair et al, path coefficient values ​​are in the range of values ​​-1 to +1, where path coefficient values ​​close to +1 represent a strong positive relationship and path coefficient values ​​close to -1 indicate a negative relationship. strong.

To see the significance of the hypothesis, it can be done by looking at the parameter coefficient values ​​and the T-statistical significance value in the algorithm bootstrapping report, the T-statistical significance value must be more than 1.96. To see whether significant or not significant can be seen from the T-table at alpha 0.05 (5% = 1.96) then the T-table is compared by the T-count.

The Table 9, shows that the variable Job Satisfaction has a negative and significant effect on Turnover Intention because it has an Original Sample (Path Coefficient) value of -0.400 which indicates a negative direction of influence with a t statistics value of 5.573 which is greater than t table = 1.96 and also p values of 0.000 is smaller than 0.05 which shows a significant and F square value of 0.316 which shows a big influence. So Ha is accepted and Ho is rejected.

Table 9: Model Fit Test Results

Table 10: Operational Definitions of Variables

Then the Workload variable has a positive and significant effect on Turnover Intention because it has an Original Sample (Path Coefficient) value of 0.232 which indicates a positive direction of influence with a t statistics value of 2.804 which is greater than t table = 1.96 and also p values ​​of 0.005 or smaller than 0.05 which shows a significant and F square value of 0.078 which shows a moderate or medium effect. So Ha is accepted and Ho is rejected.

Furthermore, the Job Stress variable has a positive and significant effect on Turnover Intention because it has an Original Sample (Path Coefficient) value of 0.391 indicating a positive direction of influence, with a t statistics value of 4.603 which is greater than t table = 1.96 and also a p-value of 0.000 where smaller than 0.05 indicates significant. And the F square value of 0.207 shows a big influence. So Ha is accepted and Ho is rejected.

Based on the research results that have been obtained with the stages of statistical tests that have been carried out, it is known that job satisfaction has a negative and significant effect on turnover intention. These results are following research that has been previously conducted by Seema et al. [6], which states that job satisfaction has a negative and significant effect on turnover intention. Based on the results of the research conducted and supported by the results of previous research, it shows that the relationship between job satisfaction and turnover intention is reverse (not unidirectional), meaning that if job satisfaction increases, the employee's desire to leave their job (turnover intention) will decrease or decrease and conversely, if employee job satisfaction decreases, the employee's desire to leave his job (turnover intention) will increase. Based on the description of the respondents' answers related to the indicator of job satisfaction on turnover intention, which is the respondent's answer with the lowest mean, that is, employees are satisfied with the benefits provided.

Furthermore, it is known that workload has a positive and significant influence on turnover intention. The results of this study are following research conducted by Maziero et al. [19], which states that workload has a positive and significant effect on turnover intention. Workload has a positive and significant effect on turnover intention, meaning that it has a unidirectional effect in the sense that if workload increases, the employee's desire to leave his job (turnover intention) will increase and conversely if workload decreases, the employee's desire to leave his job will decrease. From the results of the respondents' answers related to the workload indicator on turnover intention which has the lowest mean value is the feeling that the number of existing jobs is following the number of employees, based on this it can be concluded that employees feel the number of existing jobs is not balanced with the number of the existing workforce,

Based on the results of the research conducted, it is known that work stress has a positive and significant effect on turnover intention. The results of this study are following research that has been conducted by SJ Lee and Lee [20], as well as Giorgi et al. [21], which states that work stress has a positive and significant effect on turnover intention.

Furthermore, work stress has a positive and significant effect on turnover intention which shows that work stress has a unidirectional effect in the sense that if work stress increases, the employee's desire to leave his job will increase and vice versa if work stress decreases, the employee's desire to leave his job will decrease. From the results of the respondents' answers related to the work stress indicator which has the lowest mean value, namely the employee's feelings towards the political situation will not affect his work, from this it can be concluded that the work stress factor that arises comes from environmental factors, this sufficiently influences turnover intention where environmental factors This can cause work stress on employees, It is known that an unstable environmental situation can affect the company's condition. If the company's conditions are not in good condition, employees will tend to feel worried and feel uncomfortable with their work. This can increase work stress on employees and trigger employees' thoughts to look for companies that can survive and continue to operate well in unfavorable environmental conditions and situations. stable.

Suggestion

Based on the results of the research that has been done, suggestions that can be considered to reduce the level of turnover intention are to pay attention to and further improve health insurance for all employees, such as improving health facilities with higher standards, so that employees feel comfortable while working with adequate health benefits and adequate. In this case, benefits have an important role in employee job satisfaction, so the company should provide benefits. With this, it is expected that job satisfaction of employees can increase and reduce the level of turnover intention. Furthermore, to reduce the level of turnover intention, what the company can do is increase its workforce so that the workload imposed on employees is following their capacity so that employees work in good physical and psychological conditions, of course, after analyzing the effective working hours of employees. In addition to increasing the number of employees, what the company can do is improve the effectiveness (simplification) of the existing work system so that it can ease the workload of employees. So it is expected that the workload of employees can be reduced and the level of turnover intention at the company is also reduced. what can be done by the company is to make the effectiveness (simplification) of the applicable work system to ease the workload of employees. So it is expected that the workload of employees can be reduced and the level of turnover intention at the company is also reduced. what can be done by the company is to make the effectiveness (simplification) of the applicable work system to ease the workload of employees. So it is expected that the workload of employees can be reduced and the level of turnover intention at the company is also reduced.

In addition, to reduce the level of turnover intention, what the company can do is create a comfortable work environment for employees so that external factors do not cause work stress to employees and the company can carry out regular consultation sessions to find out the difficulties experienced and the things that arise. trigger work stress so that the company can help reduce the worries that arise in employees and overcome them. So that work stress on employees is reduced and the level of turnover intention is also reduced.

Acknowledgment

We have no conflicts of interest to declare. The author received funding from Mercu Buana University.

1. Vu, T.V. “Perceived socially responsible HRM, employee organizational identification and job performance: The moderating effect of perceived organizational response to a global crisis.” Heliyon, vol. 8, no. 11, 2022, e11563. https://doi.org/10.1016/j.heliyon.2022.e11563.

2. Hirschi, A. and D. Spurk. “Ambitious employees: Why and when ambition relates to performance and organizational commitment.” Journal of Vocational Behavior, vol. 127, March 2021. https://doi.org/10.1016/j.jvb.2021.103576.

3. Mariappanadar, S. “Do HRM systems impose restrictions on employee quality of life? Evidence from a Sustainable HRM Perspective.” Journal of Business Research, vol. 118, June 2020, pp. 38–48. https://doi.org/10.1016/j.jbusres.2020.06.039.

4. Raub, S. et al. “New employee orientation, role-related stressors and conflict at work: Consequences for work attitudes and performance of hospitality employees.” International Journal of Hospitality Management, vol. 94, 2021. https://doi.org/10.1016/j.ijhm.2020.102857.

5. Abdalla, M.J. et al. “COVID-19 and unpaid leave: impacts of psychological contract breach on organizational distrust and turnover intention: Mediating role of emotional exhaustion.” Tourism Management Perspectives, vol. 39, December 2020, 100854. https://doi.org/10.1016/j.tmp.2021.100854.

6. Seema, Choudhary, V. and G. Saini. “Effect of job satisfaction on moonlighting intentions: mediating effect of organizational commitment.” European Research on Management and Business Economics, vol. 27, no. 1, 2021, 100137. https://doi.org/10.1016/j.iedeen.2020.100137.

7. Jirawuttinunt, S. and K. Limsuwan. “The effect of green human resource management on performance of certified ISO 14000 businesses in Thailand.” UTCC International Journal of Business and Economics (UTCC IJBE), vol. 11, no. 1, 2019, pp. 168–185.

8. Zhang, X. et al. “The influence of job satisfaction, resilience and work engagement on turnover intention among village doctors in China: A cross-sectional study.” 2020, pp. 1–11.

9. Nalini, B. and F. Alexander Pravin Durai. “Emerging trends of HR practices in green initiatives.” International Journal of Research in Engineering, IT and Social Sciences, 2019. http://inducedu.org.

10. Kim, M.Y. and H.J. Lee. “Does grit matter to employees’ quality of work life and quality of life? The Case of the Korean Public Sector.” Public Personnel Management, vol. 51, no. 1, 2022, pp. 97–124. https://doi.org/10.1177/00910260211012713.

11. Lee, P.C. et al. “Is career adaptability a double-edged sword? The impact of work social support and career adaptability on turnover intentions during the covid-19 pandemic.” International Journal of Hospitality Management, vol. 94, January 2021, 102875. https://doi.org/10.1016/j.ijhm.2021.102875.

12. Ivanovic, T. et al. “The relationship between recruiter burnout, work engagement and turnover intention: Evidence from Serbia.” Management, vol. 31, no. 2, 2020, pp. 197–210.

13. Waterwall, B. and K.K. Alipour. “Non-Family employees’ perceptions of treatment in family businesses: Implications for the organizational drive, job pursuit intentions, work attitudes and turnover intentions.” Journal of Family Business Strategy, 2021, 100387. https://doi.org/10.1016/j.jfbs.2020.100387.

14. Böckerman, P. et al. “Does high involvement management improve worker well-being?” Journal of Economic Behavior and Organization, vol. 84, no. 2, 2012, pp. 660–680. https://doi.org/10.1016/j.jebo.2012.09.005.

15. Widyanty, W. “Toward a model of the linkages between safety culture and employee performance in gold mining companies.” 2019.

16. Demirović Bajrami, D. et al. “Will we have the same employees in hospitality after all? The impact of COVID-19 on employees’ work attitudes and turnover intentions.” International Journal of Hospitality Management, vol. 94, November 2020. https://doi.org/10.1016/j.ijhm.2020.102754.

17. Sroka, W. and J. Vveinhardt. “Is a CSR policy an equally effective vaccine against workplace mobbing and psychosocial stressors?” International Journal of Environmental Research and Public Health, vol. 17, no. 19, 2020, pp. 1–19. https://doi.org/10.3390/ijerph17197292.

18. Smith, T.D. et al. “Stress, burnout and diminished safety behaviours: An argument for total worker health® approaches in the fire service.” Journal of Safety Research, vol. 75, October 2020, pp. 189–195. https://doi.org/10.1016/j.jsr.2020.09.010.

19. Maziero, R. et al. “Analysis of physical records of trabalho and biomecânica na construction of telhados com estruturas de madeira.” Floresta e Ambiente, vol. 25, no. 1, 2018, pp. 1–10. https://doi.org/10.1590/2179-8087.072114.

20. Lee, S.J. and T.W. Lee. “Factors influencing migrant workers’ motivation to participate in physical leisure activities in Korea.” Journal of Public Health (Germany), 2020. https://doi.org/10.1007/s10389-020-01276-1.

21. Giorgi, G. et al. “Stress, well-being and aging in the italian banking sector: Evidence and future perspectives.” Handbook of Research on Stress and Well-Being in the Public Sector, 2020, pp. 167–180. https://doi.org/10.4337/9781788970358.00020.