The Influence of Work Environment, Work Motivation, and Compensation on Job Satisfaction and Its Impact on Employee Turnover PNM Mekaar in West Java

has an original sample value of 0.383 on job satisfaction, with a p-value 0.000. These results indicate that there is a significant influence between compensation and job satisfaction. Thus, these results support the fifth hypothesis

The desire to switch jobs (Turnover intention) in employees can be affected by few factors including the work environment, work motivation and compensation received by employees. The research aim to determine the effect of work environment, motivation and compensation on PNM employee turnover in West Java province. quantitative analysis. work motivation and compensation affect job satisfaction while work environment not affecting job satisfaction while work motivation has an impact on surgical turnover with work environment, compensation and job satisfaction have no impact on turnover

INTRODOCTION
PT PNM (Permodalan Nasional Madani) was formed by the government with the aim of solving strategic problems to raise the economic level of the Indonesian population by providing capital and programs to improve the capabilities of UMKMK actors. It is hoped that this program can bring up UMKMK individuals who have independence, are resilient and can create new jobs. PNM issued a product that can be referred to as Mekaar (Membina Ekonomi Keluarga Sejahtera) where this program has aspirations to provide services specifically for underprivileged women as UMi (ultra micro) business activists, who are just starting a business and expanding their business.
From year to year there is an increase in employees in PNM companies, especially in PNM Mekaar, from the graph below it can be seen the increase in PNM Mekaar employees from 2018 to 2022. From a total of 58,341 employees in 2022 the distribution of employees is most in West Java, followed by East Java then Central Java in third position, for details of the number of the top ten provinces in the highest number of employees is illustrated in the graph below. An organization can never be separated from the conditions of employee turnover in running its business. Labour Turn Over can also be said to be the movement of the workforce to leave the organization. Another thing turnover is a picture of an organization that shows how many employees leave the company in a certain period. Hasibuan (2017) states that Labor Turn Over is the entry and exit of employees in a company. Hasibuan (2017) states that the cessation of an employee based on his own wishes can occur to have less job satisfaction in the company or at the workplace concerned, for example, getting a better job, not a good working environment, low compensation, no promotion opportunities, unfair treatment and so on. The tendency to have a desire to change workplaces can be influenced by one of them from the work environment where a positive and supportive work environment tends to reduce employee turnover rates, while an unpleasant or unsupportive work environment can make employees' desire to leave the company increase.

LITERATURE REVIEW
According to Cashmere (2016), the work environment refers to the conditions or atmosphere that exist around the workplace. This work environment includes various aspects, such as work space, floor plan or room layout, media and tools in the workplace, as well as working relationships with other people and colleagues in the organization. According to Cristensen, cited in Supomo (2018), the work environment is a patern of external situation and affecting that impacted the life and development of the company. This means that the work environment includes all external aspects that can have an impact on the company, including external factors such as government policies, economic situations, industrial competition, and social conditions that affect the company's operations and development. Hasibuan (2017) sais that work motivation is a situation that encourage employees to be aligned in achieving company goals. The attitude of a pro and positive mentality in work situations can strengthen employee motivation to achieve the best performance. Pamela and Oloko (2015) said work motivation is the key to

Total Employees
Ariffadillah, Safaria 2050 organizational success in order to sustainably maintain the continuity of work in the organization and help it to survive. Compensation is a cost and burden for the company, but the company hopes that investment in compensation will provide higher returns in the form of improved employee performance. Thus, the value of employee achievement or work must be greater than the compensation offered by the company. According to Hasibuan (2017), compensation forms are divided into two groups, namely direct compensation and indirect compensation. Indirect compensation received by employees in a form other than direct wages or salaries.
Afandi (2018) defines job satisfaction as a level of effectiveness or emotional response to various aspects of work. It includes a set of feelings felt by employees regarding the level of pleasure or discomfort in carrying out their job duties. Ksama (2016) Turnover intention is a problem that often arises in an organization, which refers to the desire or intention of employees to leave the company or find a new job. These factors are interconnected and can highly affecting the level of turnover intention in an organization. It is important for management to understand and manage these variables well in order to reduce turnover rates and retain high potential employees.

Research Hypothesis
1. Work environment affecting job satisfaction. 2. Work environment affecting employee turnover. 3. Work motivation affecting job satisfaction 4. Work motivation affecting employee turnover 5. Compensation affecting job satisfaction 6. Compensation affecting employee turnover 7. Job satisfaction affecting employee turnover Emzir (2014) state that quantitative approach is a research approach based on the post-positivist paradigm in developing knowledge. This approach involves reasoning about effect and cause, reduction to variables, and theory testing. Using the Slovin Formula, we can estimate the appropriate sample size from a population of 100 respondents.

RESULT AND DISCUSSION
The results of testing the reliability and validity of the based on the results of the outer model test which includes convergent validity, Cronbach's Alpha, composite reliability, and discriminant validity.

Convergent Validity
Convergent Validity is a convergent validity test conducted to evaluate the extent to which the indicators used in measuring latent variables actually reflect the desired construct. The results of this test indicate whether the indicators correlate with relevant and significant latent variables. There are measuring items that have an outer loading value smaller than 0.7. Therefore, in order not to affect the average variance expected (AVE) value of the variable, the question items must be dropped / deleted, namely KK11, KK3, MK9, TO10 and TO2. The table will present the final loading value after items smaller than 0.7 are dropped.  Based on the test results, all construct have met the test requirements with a Cronbach's alpha value above 0.7.

Composite Reliability
Composite reliability is The indicators used to measure a construct are seen in the "view latent variable coefficients." In assessing validity and reliability, composite reliability can be evaluated using two measuring tools, namely "internal consistency" and "Cronbach's Alpha." Composite reliability is used to measure the internal consistency of the indicators used in measuring latent variables. These two measurement tools help ensure that the latent variable measurements have validity and are reliable in structural analysis. The composite reliability test is also used to measure the reliability of the same indicators in one latent variable. It is similar to the Cronbach's Alpha test, but can provide an alternative in measuring reliability. A construct has high reliability if the value achieved is > 0.70.

Discriminant Validity
In measurement models with reflective indicators, evaluation of cross loading and discriminant validity is very important. Crossloading occurs when indicators have significant relationships with more than one latent variable, while discriminant validity measures the extent to which constructs distinct one another. If the relationship between the indicator and the measured construct is stronger than the relationship with other constructs, then the measure of that group of constructs is considered better than the other groups. This evaluation is important to make sure measurement quality of latent variables and the validity of the measurement model as a whole. Discriminant validity test is used to ensure that one latent variable is statistically distinct from other latent variables in the model. The results of this test show that the latent variable has a higher correlation with its own indicators than with indicators of other latent variables. there is no significant correlation between the question indicators of the variables Job Satisfaction (KK), Compensation (KS), Work Environment (LK), Work Motivation (MK), and Turnover (TO). The relationship between these indicators does not exceed the relationship between indicators with the same variable.
Another method to count discriminant validity by compare square root of average variance extracted (AVE) values. A good AVE is when the AVE value of each construct is > 0.50. If the AVE value of a factor is <0.5, then the indicator should be removed from the analysis.  Figure 3. Discriminant Validity

Inner Model Analysis
"Inner Model Analysis is an analysis that explain the relationship between hidden variables based on substantive theory. Inner model analysis can be assessed by using the R-square for the dependent construct where the R-Square or coefficient of determination is a simple and frequently used measure to evaluate the quality of a regression equation." (Gujarati, 2004). Stone-Geisser Q-square test for significance of structural path parameter coefficients, t-test and predictive relevance. Inner model evaluated with smartPLS, we start by checking the R-square on the hidden dependent variable. (Ghozali, 2016). "A Q-Square value > 0 means the model has predictive relevance. Meanwhile, if the Q-Square value = 0 (zero), then the model has no predictive relevance." (Chin, 1998). The R-Square Job Satisfaction variable is 67.0%, it means that most of the variation in the dependent variable can be explained by variations in the independent variable. The remaining 33.0% cannot be explained by the independent variables and may be affected by other factors outside the independent variables.
Meanwhile, the R-Squere turnover variable is 10.5%, it means that a small part of the variation of the dependent variable can be explained by the variation of the independent variable. The rest, about 89.5%, cannot be explained by the independent variables and may be affected by other factors outside the independent variables.

Figure 4. Bootstrapping Test Results Source : PLS Algorithm Procedure Test Results
Interpretation is done to see whether the research hypothesis that has been made is rejected or accepted. A hypothesis check can be described by the probability value and tstatistic. Ananda Sabil Husein (2015) explains that in hypothesis testing, we can use statistical values with a significance level of 5% (alpha 0.05). For this test, the t-statistic value used is 1.96. Therefore, the criteria for accepting or rejecting a hypothesis is when the t-statistic value > 1.96, Ha accepted and H0 rejected. In addition, the hypothesis can also be accepted based on probability, namely Ha accepted if the p value <0.05.  The work environment variable has a positive correlation of 0.118 to job satisfaction, but the p-value obtained is 0.122. Therefore, these results dont support the first hypothesis.
The table also shows that the original sample value for the work environment variable has a positive effect of 0.030 on turnover, but the p-value obtained is 0.785. Therefore, these results dont support second hypothesis.
Work motivation variable has an original sample value of 0.435 on job satisfaction, with a p-value of 0.000. This indicates that there is a significant influence between work motivation on job satisfaction. Thus, this result supports the third hypothesis.
Work motivation variable has an original sample value of -0.382 on turnover, with a p-value 0.011. This shows that there is a significant influence between work motivation and employee turnover. Therefore, this result supports the fourth hypothesis.
Compensation variable has an original sample value of 0.383 on job satisfaction, with a p-value 0.000. These results indicate that there is a significant influence between compensation and job satisfaction. Thus, these results support the fifth hypothesis.
Compensation variable has a positive original sample value of 0.383 on turnover, with a p-value 0.000. However, although the original sample value is positive, the very small p-value indicates that the effect is highly statistically significant. Therefore, this result dont support sixth hypothesis.
Based on the results in the original sample value table, the job satisfaction variable has a negative effect of -0.044 on turnover, with a p-value of 0.780. These results indicate that there is no significant influence between job satisfaction on employee turnover. Therefore, this result dont support seventh hypothesis.
Hypothesis testing is an important stage in Structural Equation Modeling (SEM) to evaluate the fit of the structural model to the empirical data collected. This test involves comparing the significance value between the variables in the model with a predetermined significance level to determine whether the hypothesis is accepted or rejected. By evaluating the results of hypothesis testing, researchers can conclude whether the proposed structural model fits the data or needs to be revised to be closer to the actual conditions in the population or sample under study.

H1
There is a significant influence between the work environment on job satisfaction.

H2
There is a significant influence between work environment and employee turnover.

H3
There is no significant influence between work motivation on job satisfaction. T-Statistics = 4.768 P-Values = 0.000 Accepted

H4
There is a significant influence between work motivation on employee turnover T-Statistics = 2.572 P-Values = 0.011 Accepted

H5
There is a significant influence between compensation on job satisfaction. T-Statistics = 4.552 P-Values = 0.000 Accepted

H6
There is a significant influence between compensation on employee turnover T-Statistics = 0.725 P-Values = 0.470 Rejected

H7
There is no significant influence between job satisfaction and employee turnover. T-Statistics = 0.280 P-Values = 0.780 Rejected

Source : Author Research
Relation Between Work Environment and Job Satisfaction P-value is 0.122 greater than the alpha value set at 0.05 (5%). In addition, the original sample value for the correlation between work environment and job satisfaction is 0.118.
Based on these results, the first hypothesis examining the relationship between work environment and job satisfaction is not supported. This means that there is no significant influence between work environment variables on job satisfaction variables in this study.
The reason for not supporting the first hypothesis can be explained with reference to the theory put forward by Gibson (1997). This theory states that job satisfaction is a pleasant feeling developed by employees based on various aspects of work which include promotion opportunities, wages, and interactions with coworkers. However, in this study, no evidence was found that the work environment has a significant influence on job satisfaction.

Relation Between Work Environment and Turnover
P-value is 0.785 greater than the alpha value set at 0.05 (5%). In addition, the original sample value for the correlation between work environment and employee turnover is 0.030.
Based on these results, the second hypothesis examining the relationship between work environment and employee turnover is not supported. This means that there is no significant influence between work environment variables on employee turnover variables in this study.
The reason for not supporting the second hypothesis can be explained by the high P-value (0.785) so no significant correlation between work environment and employee turnover rate. This result indicates that in this study, work environment does not have a significant influence on employee turnover rate.

Relation Between Work Motivation and Job Satisfaction
P-value is 0.000 much smaller than the alpha value set at 0.05 (5%). In addition, the original sample value for the correlation between work motivation and job satisfaction is 0.435.
Based on these results, the third hypothesis examining the relationship between work motivation and job satisfaction is supported. That is, there is a significant influence between work motivation variables on job satisfaction variables in this study.
Increased work motivation in employees will have a positive impact on the level of job satisfaction felt by employees. Management needs to pay attention to work motivation as a Tool to increase employee satisfaction. One of the things that can motivate employees is encouragement from the leadership. With this encouragement, employees are more active and enthusiastic at work so that they are able to complete their work properly, this will be able to increase employee satisfaction with the work performed.
Motivation-Hygiene (Two-Factor Theory) proposed by Frederick Herzberg. According to the Motivation-Hygiene Theory, there are two main factors that influence employee job satisfaction and job dissatisfaction, namely motivational factors (motivators) and hygiene factors (hygiene). Motivational factors relate to the characteristics of the job itself and how the job affects employees' feelings of achievement and personal growth. Meanwhile, hygiene factors relate to external working conditions and how they can cause dissatisfaction if not met, but do not directly contribute to job satisfaction when met.

Relation Between Work Motivation and Turnover
P-value is 0.011 smaller than the alpha value set at 0.05 (5%). In addition, the original sample value for the correlation between work motivation and employee turnover rate is -0.382. the fourth hypothesis examining the relationship between work motivation and employee turnover is supported. That is, there is a significant influence between the work motivation variable and the employee turnover rate variable in this study.
Work motivation has an effect on intention to quit, so work motivation has an impact on revenue growth. To reduce the increase, management should further improve by providing incentives for employees. The company should consistently give praise and motivation to employees fairly according to their achievements. This is important because it provides enthusiasm and happiness for employees in carrying out the work duties that have been entrusted to them. The company also needs to socialize the problems faced by each employee so that employees feel cared for and valued and motivated to continue doing the assigned work. Employees with strong internal and external motivation will be able to suppress revenue growth.

Relation Between Compensation and Job Satisfaction
P-value is 0.000 lower than the alpha value set at 0.05 (5%). In addition, the original sample value for the correlation between compensation and job satisfaction is 0.383.
Based on these results, the fifth hypothesis examining the relationship between compensation and job satisfaction is supported. This means that there is a significant influence between the compensation variable and the variable level of employee job satisfaction in this study.
Mangkunegara (2016) explains that "compensation provided to employees has a significant influence on the level of job satisfaction, work motivation, and work results." Meanwhile, Hasibuan (2013) states that "the objectives of compensation include bonding cooperation, job satisfaction, motivation, and employee discipline." Therefore, compensation is an important part of organizational policy that must be taken seriously, by providing appropriate and proper compensation so as to meet the level of job satisfaction for each employee.

Relation Between Compensation and Turnover
P-value is 0.470 greater than the alpha value set at 0.05 (5%). In addition, the original sample value for the correlation between compensation and employee turnover is 0.077.
Based on these results, that the sixth hypothesis examining the relationship between compensation and employee turnover is not supported. This means that there is no significant influence between the compensation variable and the employee turnover rate variable in this study.
Management needs to manage the compensation system seriously and appropriately, because if not, it can cause employee dissatisfaction with the rewards received, which is referred to as "pay dissatisfaction," and this has the potential to cause turnover. According to Rumangkit (2017), turnover intention is a process in which employees feel like leaving the company for several reasons. Poor management of the compensation system can have a direct or indirect impact on employee performance. If the compensation system is not implemented properly, it can cause demotivation and job dissatisfaction among workers. This condition will result in a decrease in job performance, motivation, and job satisfaction. As a result, the agency itself will experience losses, and this can lead to turnover.

Relation Between Job Satisfaction and Turnover
P-value is 0.780 greater than the alpha value set at 0.05 (5%). In addition, the original sample value for the correlation between job satisfaction and employee turnover is -0.044.
The seventh hypothesis examining the relationship between job satisfaction and employee turnover rate is not supported. This means that there is no significant influence between job satisfaction variables on employee turnover rate variables in this study. This is in line with Dewi Mawadati's research (2020) which states that "job satisfaction variables have no effect on turnover intention."

CONCLUSION AND RECOMMENDATION Conclusion
First hypothesis There is insufficient evidence to state that the work environment affecting level of employee job satisfaction at PNM.
The second hypothesis seeks to identify the effect of work environment on employee turnover rate at PNM. So second hypothesis cannot be accepted The third hypothesis examines the effect of work motivation on employee job satisfaction at PNM. The findings indicate that work motivation has a strong and positive influence on the level of job satisfaction within PNM.
The fourth hypothesis examines the effect of work motivation on employee turnover rate at PNM. The findings indicate that work motivation has a significant and important influence on employee turnover rate.
The fifth hypothesis examines the effect of compensation on the level of employee job satisfaction at PNM. The findings indicate that compensation has a significant and important influence on the level of employee job satisfaction.
The sixth hypothesis examines the effect of compensation on employee turnover rate at PNM. The findings show that there is no significant influence between compensation and turnover.
The seventh hypothesis examines the effect of job satisfaction on employee turnover rate at PNM. The findings indicate that there is no significant influence between job satisfaction and employee turnover rate.

Reccomendations
Some of the proposed recommendations are as follows: Focus on Good Compensation. Companies need to ensure that they provide competitive and fair compensation to employees. Good compensation can motivate employees to work harder and contribute more.
Pay Attention to Job Satisfaction. In addition to providing good compensation, it is important for companies to pay attention to other factors that can affect employee job satisfaction. Efforts to improve the work environment, provide career development opportunities, and recognize employee achievements can increase job satisfaction and reduce turnover.
Link Performance to Compensation. companies can link employee performance and achievements to increases in salary or compensation. This can encourage employees to achieve better results and provide incentives for them to continue to perform.
Further Research on Factors Influencing Turnover. It is recommended to conduct further research to identify what factors affect employee turnover more comprehensively. With a deeper understanding of these factors, companies can take more appropriate steps to overcome turnover problems.
Expansion of the Number of Respondents: To increase the validity of the research results, it is necessary to increase the number of respondents so that the data obtained can better represent broader conditions and views within the company.
By implementing these recommendations, the company is expected to reduce employee turnover rates and create a more productive, motivating, and satisfying work environment for employees.