This study aims to determine the effect of age level, education level, work environment and compensation on work productivity at the Persahabatan General Hospital (RSUP). The data source of this study used primary data in the form of a questionnaire, the data of this study was given to 339 respondents at Persahabatan Hospital. In taking the sample for this research using random sampling method. The data analysis technique used is multiple linear regression and hypothesis testing using t-statistics that have been processed in SPSS 23 to test the regression coefficients. Based on the results of the study showed that Age Level (X1) had a negative and insignificant effect, Education Level (X2) had a positive but not significant effect, Work Environment (X3) had a positive and significant effect on Work Productivity, Compensation (X4) had a positive and significant effect on Productivity.

Keywords: Age Level, Education Level, Work Environment, Compensation, Productivity

INTRODUCTION

In the current era of globalization, trade is very free, especially in human resources in Indonesia which must be able to compete and improve the quality of resources from other countries. So human resource development becomes very important. The demands of life and economic demands are very pressing so that everyone is obliged to continue working hard in order to survive, especially humans who are the main figures in development or the workforce. Quality human resource skills are really needed in any organization, be it government or private organizations. Human resources in an organization are called workforce or employees. Labor is the most unique and specific compared to other production factors, basically humans have behavior, feelings, reason and goals. a very important requirement for every company. One of the benchmarks for quality human resources for a company that can be used to assess quality work productivity is human resources.

However, during the Covid-19 pandemic, a decline in productivity occurred in many countries, resulting in a decline in people's purchasing power, economic chains and the cessation of export and import trade due to restrictions on people's movement and mobility, as well as a decrease in working hours and the quality of human resources and increased unemployment. The pandemic has caused a drastic decline in productivity and will be an obstacle for every country in increasing short-term and long-term income. Productivity is seen from the large number of outputs produced in a period. Economists measure a country's level of productivity from the amount of Gross Domestic Product (GDP) per worker. For the case of Indonesia, a decade before the COVID pandemic (2010-2019), the productivity growth of the Indonesian economy as measured by output (GDP) per worker has a downward trend from 6.95% in 2011 to 3% in 2019. (theconversation.com)

During the Covid-19 pandemic, the Indonesian government also implemented the Persahabatan Central General Hospital (RSUP) to become one of the referral hospitals (RS) for Covid-19 patients. This policy meant that the Persahabatan Hospital only served Covid patients, not general patients, which resulted in limited patient arrivals. . During this pandemic, hospital employees are required to use Personal Protective Equipment (PPE) to avoid being exposed to Covid. Hospital employees who use PPE are not allowed to open it during the specified time so that hospital employees will lack concentration when providing services. This is a challenge in itself for hospital employees who are required to remain productive because completing their work even when using PPE can cause a decrease in hospital employee productivity.

Hospital employees are greatly utilized because they are at the forefront of dealing with the Covid-19 pandemic. It is hoped that the existing potential can create high-quality resources when dealing with the pandemic. The opportunities and opportunities given to hospital employees are aimed at developing their skills and abilities without reducing service productivity. For a hospital, hospital employees are a very valuable asset because they can determine aspects of success in terms of obtaining company profits as well as in terms of company continuity and continuous business development in the future. For this reason, the hospital must have a high work ethic in its human resources and also have very high expertise, skills, enthusiasm and professionalism as well. So it can be said that human resources as labor play a very important role in the process of increasing work productivity.

According to data from (Ministry of Communication and Informatics of the Republic of Indonesia, 2020) Persahabatan Central General Hospital (RSUP) is a government agency under the Ministry of Health which is currently designated as a National Respiratory Referral Hospital based on Republic of Indonesia Minister of Health Decree No. HK.02.02/MENKES/566/2016. Employees at the Persabatan Central General Hospital (RSUP) consist of ASN, Honorary Staff and other supporting staff. One proof that the Persahabatan Central General Hospital (RSUP) is successful in carrying out its duties and functions is by looking at the results of the productivity level of its employees.

Shifting work methods has an impact on hospital employees in terms of productivity levels to carry out their duties and responsibilities. Human resource management needs to be carried out in this phenomenon, such as the factors that influence worker productivity. To increase productivity, there needs to be an understanding such as age level, education level, compensation level, work environment and other working conditions. Of the factors that can influence worker productivity, one of them is the age level of workers.

According to research (Nugraha, 2017) and research by Imran (2017), the age level variable has a significant effect on the productivity of female workers. This condition can be interpreted as meaning that age level is a factor that can significantly increase the company's work productivity. Age is a measure of how long we have lived a life. The productive age of the workforce will influence work efficiency which will influence the company's production increase process. Age is also thought to influence a worker's productivity at work. Because if the workforce is old enough, it will determine success in carrying out a job, both physically and mentally. In general, hospital employees provide services 24 hours a day. So the productivity of hospital employees who are of sufficient age are physically and mentally more prepared, whereas older hospital employees not only have the physical abilities but are not necessarily ready mentally. Because on the basis of sufficient age, it is supported by previous experience. But that doesn't mean that being old enough means good productivity. There is also the most important main factor in productivity, namely the level of education

In research (Hermawan, 2017) and research (Fitriani et al., 2019) the education level variable has a significant effect on labor productivity. This condition explains that the level of education is a factor that can increase the company's work productivity. On basically, hospital employees are required to have higher education and have broader insight because they learn the importance of productivity at work, especially when it comes to one's life. High awareness of the importance of productivity can encourage hospital employees to take more productive actions. Higher education functions to develop abilities and shape character so that the potential of hospital employees can develop. This level of education will also determine the size of the compensation the company provides to its workers.

According to research (Novrizal, 2017) and research (Aryatik, 2021), the compensation variable has a significant effect on labor productivity, meaning that compensation is a factor that can increase the company's work productivity. The compensation provided by the company will greatly influence the level of work productivity of hospital employees. When workers feel sufficient with the compensation they receive, productivity is expected to increase as they work. Sufficient compensation in this case can be interpreted as meeting the welfare and needs of a decent life to meet human needs. Compensation contains salary, incentives, allowances and other bonuses. So that when the level of compensation is sufficient, it will lead to work concentration which can direct workers' abilities to increase productivity. Compensation is also one of the company's efforts that can be made to increase productivity internally. Because age and education level are external factors that can be avoided by a company.

Furthermore, according to research (Fitriani et al., 2019) and research (Bayu Setiawan, 2021), work environment variables have a significant effect on labor productivity. It can be said that the work environment is a factor that can increase the company's work productivity internally. By paying attention to the environmental conditions of the workplace, starting from the workplace, lighting, air ventilation, comfort, safety and cleanliness, productivity can be increased. The work environment can be divided into two types, namely the social work environment and the physical work environment. The social work environment includes the work relationships that are fostered within the company. We don't work alone in a company, and in carrying out activities, we also need the help of other people. Thus, we are obliged to foster good relationships between colleagues, subordinates and superiors because we need each other. (Artana, nd 2012) The work environment greatly influences the psychological state of hospital employees. Excellent communication can be key in building working relationships. Meanwhile, poor communication can cause misunderstandings because the information conveyed fails to resonate with one another's thoughts and feelings. Good communication is used as a tool to motivate hospital employees to build a solid work team. The physical work environment is the workplace where hospital employees carry out their activities. The physical work environment affects the morale and emotions of hospital employees. These physical factors include the size of the work space, lighting, noise, air temperature in the workplace, room color, cleanliness and music in the workplace. Paying attention to the working environment conditions of hospital employees means trying to create working environmental conditions that suit the needs of hospital employees as work implementers where they work. Productive work not only requires work skills, new discoveries to improve work methods but also a comfortable work environment that can support the smooth completion of work.

Based on the description above, the objectives that will be discussed in writing this thesis are:

1) To find out and analyze the effect of age level on work productivity at Persahabatan Hospital.

2) To find out and analyze the effect of education level on work productivity at Persahabatan Hospital.

3) To find out and analyze the influence of the work environment on work productivity at Persahabatan Hospital.

4) To find out and analyze the effect of compensation on work productivity at Persahabatan Hospital.

RESEARCH METHOD

This research uses a quantitative approach with descriptive analysis methods and multiple linear regression. The data source used is primary data obtained through a questionnaire given to employees of the Persahabatan Central General Hospital (RSUP). The population studied was 2125 employees, with a sample of 337 employees taken using random sampling techniques. The type of data used is descriptive quantitative, which is measured through a questionnaire with structured questions. The data collection techniques used were questionnaires and literature studies from internal company data.

The analytical methods used in this research include descriptive analysis, inferential analysis, and multiple linear regression analysis. Descriptive analysis is used to describe the collected data, while inferential analysis is used to analyze sample data and the results are used for the population. In addition, multiple linear regression analysis is used to determine the effect of the independent variable on the dependent variable. To test the hypothesis, the researcher used a partial t test for each independent variable against the dependent variable, by establishing a null hypothesis (Ho) and an alternative hypothesis (Ha) for each independent variable. The results of this t test are used to determine whether the independent variable has a significant effect on the dependent variable.

RESULTS AND DISCUSSION

A. Instrument Test

1. Validity test

Validity Test is a test of the accuracy of a measuring instrument that is valid or not in a questionnaire that has been expressed in each statement. The validity test is calculated by looking at the Correlated Item Total Correlation or rcount and then comparing it to the rtable. If the rcount is greater than the rtable at a significant rate of 0.05, it is declared that a statement in the questionnaire is valid. The questionnaire contains several statements totaling 26 items. The work environment variable has 7 statement items, the Compensation variable has

9 statement items, and the work productivity variable has 10 statement items. The thing that was determined for the validity test was to use a rcount of 5% where n = 339, then an rtable of 0.119 was obtained and the overall statement used in this research was that the rcount must be greater than the rtable.

Table 1. Validity Test Results

Variable	Item Number	R Count	R Table	Information
	1	0.534	0.119	Valid
	2	0.634	0.119	Valid
	3	0.590	0.119	Valid
Environment	4	0.622	0.119	Valid
Work (X3)	5 6	0.651 0.641	0.119 0.119	�Valid �Valid
	7	0.471	0.119	Valid
	1	0.548	0.119	Valid
	2	0.574	0.119	Valid
Compensation	3	0.580	0.119	Valid
(X4)	4 5	0.523 0.549	0.119 0.119	�Valid �Valid
	6	0.602	0.119	Valid
	7	0.610	0.119	Valid
	8	0.600	0.119	Valid
	9	0.627	0.119	Valid
	1	0.506	0.119	Valid
	2	0.523	0.119	Valid
	3	0.525	0.119	Valid
Productivity	4	0.551	0.119	Valid
Employees (Y)	5	0.372	0.119	Valid

Source: SPSS 23 Data Processing Results

Based on calculations using SPSS 23, which has tested data on 339 respondents, it has been concluded that all questions 1-26 for the Work Environment, Compensation and Work Productivity variables are declared valid. It can be seen from each calculation result in table 1 that the calculated r is greater than the r table (0.119).

2. Reliability Test

Reliability testing is carried out as a measuring tool that will be used to see a consistent and precise measurement if the measurement is tested again. The Cronbach Alpha method used in the research is a reliability test. This test is a continuation of the validity test, where each statement item included as a test is only a statement item that is declared valid. The reliability test limit is 0.6, this limit is used to determine whether the statement item instrument is considered reliable or not. The test results produce the following data:

Table 2. Reliability Test Results

Variable	Cronbach Alpha	Limitation	Decision
Work Environment (X3)	0.689	0.6	Reliable
Compensation (X4)	0.749	0.6	Reliable
Employee Performance (Y)	0.655	0.6	Reliable

Source: SPSS 23 Data Processing Results

Based on the results of table 2 above, it can be seen that the Cronbach Alpha value for all variables used is above the limit value of 0.6. Based on the data obtained, it can be concluded that the value of the measuring instrument is declared reliable or meets the reliability requirements.

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B. Classic assumption test

1. Normality test

The normality test in statistical tests is carried out so that the independent and dependent variable regression models have normally distributed results. the independent and dependent variable regression model which has normally distributed results means that there is no significant difference between the data obtained. The data normality test was carried out using the Kolmogorov-Smirnov test. On Application when performing the Kolmogorov-Smirnov test. The Kolmogorov-Smirnov test is seen from the Asymp value. Sig. (2-tailed) above 0.05 then the data is declared normal or has no significant differences. Meanwhile, the Asymp value. Sig. (2-tailed) below 0.05 then the data is declared abnormal or there is a significant difference. This can be seen in the table below as follows:

Table 3. Normality Test Results

	Unstandardized Residual
N	339
Normal�� Mean Parameters, b�� Std.	.0000000
Deviation	2.69321120
Most Extreme�� Absolute Differences�� PositiveNegative	,048 ,048 -.024
Statistical Tests	,048
Asymp. Sig. (2-tailed)	.061c

a. Test distribution is Normal.

b. Calculated from data.

c. Lilliefors Significance Correction.

Source: SPSS 23 Data Processing Results

Looking at the results of table 3, it can be seen that the value of Asymp. Sig (2 tailed) is 0.061. Which means in formulating the hypothesis in this research: if Sig < 0.05 then Ho is rejected, if Sig > 0.05 then HO is accepted. then it can be said that the normality test results are Asymp. Sig (2 tailed) = 0.061 > 0.05 then Ho is accepted, which concludes that the population distribution or productivity results come from age, education level, work environment and Compensation for employee productivity is normally distributed at a significance level of 5% or 0.05.

2. Multicollinearity Test

The Multicollinearity test can be seen in the VIF or Variance Inflation Factors value and the Tolerance value. If the VIF value is more than 10 and Tolerance is less than 0.1, it is stated that multicollinearity has occurred. If otherwise, it is stated that there is no multicollinearity. Regression in which correlation occurs is an imperfect model, a good regression should be close to perfect or perfect between the independent variables. This test can be seen in the table below as follows:

Table 4. Coefficients^a Multicollinearity Test Results

Model		Collinearity Statistics
Model		Tolerance	VIF
1	(Constant)
	Age	,982	1,019
	Education	,971	1,030
	Environment	,829	1,206
	Compensation	,824	1,214

a. Dependent Variable: Productivity

Source: SPSS 23 Data Processing Results

Based on the results of the multicollinearity test in table 4 above. The VIF value for the variable Age Level (X1) was 1.019, Education Level (X2) was 1.030, Work Environment (X3) was 1.206 and Compensation (X4) was 1.214. The four VIF values produce a number less than 10 and the Tolerance value for each variable is more than 0.1. This means that there is no multicollinearity in the regression model.

3. Autocorrelation Test

The autocorrelation test was carried out using the Durbin Watson test method. The test is carried out to detect the presence or absence of data autocorrelation, knowing the relationship between data is needed for each independent or dependent variable. The regression model should not contain autocorrelation. With this method, if the DW value is between DU and 4-DU, then autocorrelation does not occur. So the results of the autocorrelation test can be seen in table 5 below:

Table 5. Durbin Watson Autocorrelation Test Model Summary^b

Model	Durbin-Watson
1	2,052

a. Predictors: (Constant), Compensation, Age, Education, Environment

b. Dependent Variable: Productivity

Source: SPSS 23 Data Processing Results

Based on the results of the autocorrelation test in table 4.9 above, the DW value is 2.052 which is compared to the DW table value with a significance of 5% and the number of respondents is 339 (n = 339) followed by 4 independent variables (k = 4). So in the DW table we get the value DL = 1.8043 and DU = 1.8399. The DW value is 2.052 which is greater than the limit (DU) 1.8399 and less than 2.1601 (4 - 1.8399 = 2.1601). This is in accordance with the criteria, namely DU < DW < 4-DU (1.8399 < 2.052 < 2.1601), so DW is located between DU and 4-DU, so it can be concluded that there is no autocorrelation in the data.

4. Heteroscedasticity Test

The heteroscedasticity test in this research was carried out by looking at the absence of certain patterns on the scatter plot graph. The heteroscedasticity test decision by looking at the scatter plot graph is:

If there is a certain pattern, such as the dots forming a regular pattern (wavy, widening then narrowing), then heteroscedasticity has occurred.

If there is no clear pattern, and the points are spread above and below zero on the Y axis, then heteroscedasticity does not occur.

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The following are the results of the heteroscedacity test:

Figure 1. Heteroscedasticity scatter plot test

Based on Figure 1, it can be seen that there is no clear pattern, the points are spread above and below zero on the Y axis, so it can be concluded that heteroscedasticity does not occur.

C. Results of Multiple Linear Regression Analysis

The form of analysis using the mathematical model of this research usually uses Multiple Linear Regression Analysis. This model will discuss the extent of influence of each independent variable on the dependent variable. The independent variables used in this research are age level (X1), education level (X2), work environment (X3), compensation (X4) and the dependent variable is work productivity (Y). The table below shows the results of multiple linear regression analysis as follows:

Based on the results of multiple linear regression analysis which refers to the table

it can be seen that the multiple linear regression equation is as follows:

Y = - 0.062 X1 + 0.066 X2 + 0.423 X3 + 0.124 X4

Information:

Y�� = Productivity Variable

X1� = Age Level

X2� = Education Level

X3� = Work Environment

X4� = Compensation

The regression equation above shows the results and explains that:

The age level variable has a regression value of -0.062, meaning that if age increases by 1, productivity will decrease by -0.062 or -6.2% with a standard error of 0.05 if the variables of education level, work environment and compensation are constant.

The education level variable has a regression value of 0.066, meaning that if the education level increases by 1 then productivity will increase by 0.066 or 6.6% with a standard error of 0.05 if the age level, work environment and compensation variables are constant.

The work environment variable has a regression value of 0.423, meaning that if the work environment increases by a value of 1, productivity will increase by 0.423 or 42.3% with a standard error of 0.05 if the variables age level, education level and compensation are constant.

The compensation variable has a regression value of 0.124, meaning that if compensation increases by 1, productivity will increase by 0.124 or 12.4% with a standard error of 0.05 if the variables age level, education level and work environment are constant.

The results show that the four independent variables, namely age level, education level, work environment and compensation have a positive influence on the dependent variable of employee productivity. Thus, if the level of education, work environment and compensation increases, employee productivity variables will also increase. Meanwhile, the age level variable has a negative influence on the employee productivity variable. So if age increases, employee productivity variables will decrease.

D. Hypothesis testing t test

The t test is a statistical test measuring tool to test partially and to determine whether or not an independent variable has a significant effect on each variable on the dependent variable. The t test uses a significance level of 5% or 0.05 and looks at 2 sides. Test the hypothesis between Age Level (X1), Education Level (X2), Work Environment (X4) and Compensation (X4) on Work Productivity (Y). This partial t test shows how far the influence of each independent variable partially or individually is in explaining variations in the dependent variable. The decision making criteria in the t test are carried out in the following way:

If the significance value (t) <0.05 then Ha is accepted and Ho is rejected, which means the independent variable has an effect on the dependent variable.

If the significance value (t) > 0.05 then Ha is rejected, and Ho is accepted, which means the independent variable has no effect on the dependent variable.

The hypothesis used in the partial t test is as follows:

Ha1: Age level affects work productivity

Ha2: Education level affects work productivity

Ha3: Work environment affects work productivity

Ha4: Compensation affects work productivity

For greater clarity, the author explains the results of the t test in table 6 as follows:

Table 6. t test results

Model	Q	Sig.
(Constant)	15,476	,000
Age	-1,289	,198
Education	1,356	,176
Environment	8,076	,000
Compensation	2,353	.019

a. Dependent Variable: Productivity

Source: SPSS 23 Data Processing Results

Based on the t test results in table 6 above, the following results were obtained:

Age level influences productivity.

Age level based on partial test results in table 6 gets a significant value of 0.198. This significant value is valuable

0.05. From these results it was concluded that H1 was rejected and H01 was accepted

Age has no effect on productivity.

1. Education level influences productivity

Education level based on partial test results in table 6 gets a significant value of 0.176. This significant value is valuable 0.05. From these results it was concluded that H1 was rejected and H01 was accepted. Education level had no effect on productivity.

2. The work environment influences productivity

Work Environment based on partial test results in table 6 gets a significant value of 0.000. This significant value is valuable < 0.05. From these results, it can be concluded that H1 Acceptance of the Work Environment has an influence on Productivity.

3. Compensation affects productivity

Compensation based on partial test results in table 6 gets a significant value of 0.019. The significant value is <0.05. From these results, it can be concluded that H1 Accepting Work Compensation has an influence on Productivity

E. Model Feasibility Test

1. F test

The Simultaneous F test is carried out to see whether the model being analyzed is in the appropriate category. By looking at the model, high variables can be used to explain the phenomenon being analyzed.

Based on the F test results a significant F value of 0.000. The significant F value is smaller than 0.05, so this research model is worthy of research.

2. Coefficient of Determination

The coefficient of determination is a benchmark as a tool to determine the suitability or accuracy of the analytical model being studied. to measure how far the independent variables Age, Education Level, Work Environment and Compensation are able to explain variable variations dependent.

It can be seen that the coefficient of determination value explained in column R is 0.491 or 49.1%, meaning that the variables Age Level, Education Level, Work Environment and Compensation have an influence on the Work Productivity variable, while the remaining 50.9 % influenced by other variables not analyzed in this study.

Discussion

This research has several independent variables, namely Age Level, Education Level, Work Environment and Compensation for the dependent variable, namely Work Productivity. The total number of respondents in this research was 339 respondents. The results of tests that have been carried out using multiple regression analysis, with a partial t test on the Persahabatan Central General Hospital (RSUP) are summarized as follows:

Table 7. Summary of Hypothesis Testing Results

Hypothesis	Independent Variable (x)	KP (ROA)
Hypothesis	Independent Variable (x)	Β	Sig.		Sig level.	Results
H1	Age Level	-.062	,198	>	0.05	No effect
H2	Level of education	,066	,176	>	0.05	No effect
H3	Environment Work	,423	,000	<	0.05	Influential
H4	Compensation	.124	.019	>	0.05	Influential
R2 value						0.491

Source: Data processed by researchers

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A. The Effect of Age on Work Productivity

From the results of the processed data, it shows that Ha1 is rejected, namely that there is no influence of Age Level on the Work Productivity of Employees at the Persahabatan Central General Hospital (RSUP). Based on the obtained significant level value of 0.198 which is greater than 0.05 and the regression coefficient is negative at -0.062, it can be concluded that the Age Level variable (X1) has a negative and insignificant effect. Basically, aged workers who are still in their productive period should have a higher level of productivity compared to older workers who are physically weak and are limited when working. The negative characteristic explains that as age increases, employees cannot work in 24-hour shifts in the hospital. However, as a hospital employee, age level does not matter because the average respondent is in the productivity age range, namely 20 - 40 years, reaching 65% of the total respondents, and as a hospital employee, you are obliged to provide the best service because it concerns life or health, every service is not Quality may decrease, especially during this pandemic, employees have to serve 24 hours a day. This research also supports previous research. This research is in line with (Baihaqi, 2021) which states that the age level variable has a negative and insignificant effect on employee work productivity.

B. The Effect of Education Level on Work Productivity

The education referred to in this research is based on the level of education and type of education each employee has. From the results of the processed data, the result of Ha1 is rejected, namely that there is no influence of education level on the work productivity of employees at the Persahabatan Central General Hospital (RSUP). Based on the obtained significant level value of 0.176 which is greater than 0.05 and the regression coefficient is positive at 0.066, it can be concluded that the variable Education Level (X2) has a positive but not significant effect. So Ha1 is rejected which means that partially the level of education has no significant effect on employee work productivity. Based on the results of research data that has been processed, it is proven that the level of education does not have a significant effect on the Persahabatan Central General Hospital (RSUP), it can be concluded that when the level of education is high it does not have a significant effect on employee productivity. Judging from the educational level of employees at the Persahabatan Central General Hospital (RSUP), the majority are D3 and S1, amounting to 75% of the total respondents who filled out the questionnaire, it can be said that the education level of those working at Persahabatan Hospital is standardized because it is related to patient health. This research also supports previous research. The results of this research are in line with (Tua, 2021) which states that there is no influence of education level on employee work productivity. This is because employee work productivity is focused on the work environment at RSUP Persahabatan and the compensation given to employees, while the level of employee education is seen in the recruitment process as a method for selecting employees at RSUP Persahabatan.

C. The Influence of the Work Environment on Work Productivity

Testing the hypothesis in table 7 above, the results of the research analysis showed that the significant value was greater than the predetermined significant level value, namely 5% = (0.000 < 0.05) and the regression coefficient was positive at 0.423, meaning that the Work Environment variable had a positive and significant effect. On the Work Productivity of Employees at the Persahabatan Central General Hospital (RSUP). It can be concluded that if the work environment becomes more comfortable, employee work productivity will also increase. According to (Novita, 2013) the work environment is the condition surrounding the workplace, both physical and non-physical, which can give a pleasant, safe, reassuring and comfortable impression while working. In hospitals that work as public health service agencies, if they want to produce good quality service then they must pay attention to their work environment because if employees are comfortable with their work environment then the employee will work effectively.

Especially during the current pandemic, hospitals must pay attention to their work environment so that employees do not contract the virus by providing national standard Personal Protective Equipment (PPE), placing hand sanitizer in every corner of the room, and carrying out sports activities to increase employee immunity. This research is supported by (Maulana, 2020) who has conducted it previously. which states the influence of the work environment on employee work productivity. This is because a comfortable work environment will influence the level of employee work productivity.

D. The Effect of Compensation on Work Productivity

The results of hypothesis testing in table 7 above obtained research analysis which states that the significant value is greater than the predetermined significant level value, namely 5% = (0.019 > 0.05) and the regression coefficient is positive at 0.124, meaning that the Compensation variable has a positive and significant effect on Work Productivity of Employees at the Persahabatan Central General Hospital (RSUP). According to the Decree of the Minister of Health Number HK.01.07/MENKES/278/2020, "The targets for providing incentives and death compensation are health workers, both State Civil Apparatus (ASN), non-ASN, and volunteers who handle Covid-19 and are determined by the leadership health service facilities or heads of health institutions," said the Minister of Health, Dr. Terawan Agus Putranto, Wednesday (29/4) in Jakarta. One of the agencies that makes references to Covid-19 is Persahabatan Hospital, therefore providing compensation to employees at Persahabatan Hospital can increase the level of employee work productivity.

This research is supported by (Munthe, 2018) who has conducted it previously. which states that there is a positive and significant influence of compensation on employee work productivity. Therefore, in an effort to increase employee productivity, providing compensation must be in accordance with the law or the mandate that has been imposed on employees is the most important thing. Because it will improve enthusiasm, providing compensation will also increase employee productivity, so providing compensation needs to be a company's concern.

CONCLUSION

Based on the findings derived from data analysis and discussions conducted on Employee Productivity at the Central General Hospital (RSUP), several conclusions have been drawn. Firstly, the Age Level (X1) was found to have no significant impact on the Work Productivity (Y) of Persahabatan Central General Hospital employees, as evidenced by a t-test result with a significance value of 0.198, exceeding the threshold of 0.05. The regression coefficient was negative at -0.062, indicating an insignificant and negative effect. Secondly, the Education Level (X2) was observed to lack a significant influence on the work productivity of Persahabatan Hospital employees, with a t-test result of 0.066 and a positive regression coefficient of 0.232. Although positively correlated, the effect was not deemed significant. Thirdly, the Work Environment (X3) demonstrated a substantial and positive impact on the Work Productivity (Y) of Persahabatan Hospital employees, supported by a t-test value below 0.05 (0.000) and a positive regression coefficient of 0.423. Lastly, Compensation (X4) was identified as significantly influencing the Work Productivity (Y) of Persahabatan Hospital employees, with a t-test result of 0.019 and a positive regression coefficient of 0.124. This implies a positive and significant effect of compensation on employee productivity. The research is a collaborative effort between the Faculty of Economics and Business at the National University, Jakarta, and the Faculty of Business, Economics, and Social Development at Universiti Malaysia Terengganu.

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Annisa Feby Yolanda, Herry Krisnandi, Kumba Digdowiseiso (2024)

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