THE EFFECT OF COMPENSATION ON JOB SATISFACTION WITH WORK MOTIVATION AS AN INTERVENING VARIABLE (Case Study at PT. Tiga Mutiara Nusantara Molding Section in Dolok Merawan District

Based on the results of research and discussion regarding the effect of compensation on job satisfaction with work motivation as an intervening variable "at PT. Tiga Mutiara Nusantara Molding Section in Kec. Dolok Merawan, it can be concluded that: Based on the results of the analysis of hypothesis 1, it can be concluded that the first hypothesis is accepted, meaning that the compensation variable (X) influences the work motivation variable (Z). This reflects that the greater the compensation given by PT. Tiga Mutiara Nusantara will be more motivated by employees at work. Based on the results of the analysis of hypothesis 2 it can be concluded that it can be concluded that the second hypothesis is accepted, meaning that the Compensation variable (X) influences the Job Satisfaction variable (Y). This can be interpreted that the higher the compensation given, the more satisfied employees will be. Based on the results of the analysis of hypothesis 3, it can be concluded that the third hypothesis is accepted, meaning that the variable Work Motivation (Z) affects the variable Job Satisfaction (Y). This reflects that if employees are motivated to eat, employees will be more satisfied at work. Based on the results of the analysis of hypothesis 4, it shows the direct influence of the Compensation variable (X) on the Job Satisfaction variable (Y). While the indirect effect is through the variable Work Motivation (Z). the indirect effect through the Work Motivation variable (Z) is smaller than the direct effect on the Job Satisfaction variable (Y).


IMPLEMENTATION METHOD
The type of research that will be carried out in this study is a type of quantitative research. This type of quantitative research quoted from (Sugiyono, 2018) is a research method based on the philosophy of positivism, used to research on certain populations or samples, collecting data using research instruments, analyzing data quantitative or statistical with the aim of testing established hypotheses. The population is a generalization area consisting of: objects/subjects determined by researchers with a selection of certain qualities and characteristics to be understood and to provide conclusions (Sugiyono, 2014). In this study the population is employees of PT. Tiga Mutiara Nusantara Molding Section in Dolok Merawan District, totaling 112 employees.
Given the large number of population, the researchers used the type of sampling Non-Probability Sampling, which is a sampling technique that does not provide an opportunity for every element or member of the population to be selected as a sample. The sampling technique is a sampling technique, which is used in this study is non probability sampling. According to Sugiyono (2018), Accidental sampling is a sampling technique based on chance, that is, anyone who accidentally meets the researcher can be used as a sample, if it is deemed that the person met by chance matches the data source. This technique is used by researchers who happen to meet anyone throughout PT. Tiga Mutiara Nusantara, the molding section of Dolok Merawan District, which is suitable as a data source. Data collection techniques or methods used in this research are interviews and questionnaires. Based on Table 1, shows that all statement points, both the Job Satisfaction variable (Y), the Work Motivation variable (Z) and the Compensation variable (X) have a higher r count value than the r table value, so that it can be concluded if all statements for each variable are stated valid. Based on the reliability test using Cronbach Alpha, all research variables are reliable/reliable because Cronbach Alpha is greater than 0.6, so the results of this study indicate that the measurement tools in this study have fulfilled the reliability test (reliable and can be used as a measuring tool).

Classic assumption test
Source:Primary Data processed, 2022 Data that is normally distributed will form a straight diagonal line and plotting the residual data will be compared with the diagonal line, if the distribution of the residual data is normal then the line that describes the actual data will follow the diagonal line (Ghozali, 2016).The test results using SPSS 25 are as follows: From the output in table 3 it can be seen that the significance value (Monte Carlo Sig.) of all variables is 0.111. If the significance is more than 0.05, then the residual value is normal, so it can be concluded that all variables are normally distributed Source:Primary Data processed, 2022

Figure 2 Normal P Plot of Equation II
Data that is normally distributed will form a straight diagonal line and plotting the residual data will be compared with the diagonal line, if the distribution of the residual data is normal then the line that describes the actual data will follow the diagonal line (Ghozali, 2016). The test results using SPSS 25 are as follows:  Based on table 5 it can be seen that the tolerance value of the Compensation variable (X) is 0.757 and Work Motivation (Z) is 0.757 which is greater than 0.10 while the VIF value of the Compensation variable (X) is 1.332, which is less than 10 Based on the calculation results above, it can be seen that the tolerance value of all independent variables is greater than 0.10 and the VIF value of all independent variables is also less than 10, so there is no correlation symptom in the independent variables. So it can be concluded that there are no symptoms of multicollinearity between independent variables in the regression model Based on table 6, it is known that the significant value of the Compensation variable (X) is 0.236, the significant value of the Work Motivation variable (Z) is 0.130, where both are greater than 0.05 so it can be concluded that there are no symptoms of heteroscedasticity.    Based on table 10 it can be seen that the value of the adjusted R square is 0.683 or 68.3%. This indicates that the Compensation variable (X) and Work Motivation variable (Z) can explain the Job Satisfaction Variable (Y) of 68.3%, the remaining 31.7% (100% -68.3%) is explained by other variables in outside of this research model, for example, the factors that influence job satisfaction, namely: opportunities for advancement, job security, salary, company and management. Factors that influence work motivation, namely: appropriate salary, company culture, work goals, personal goals.

Hypothesis Test Effect of Compensation variable (X) on Work Motivation variable (Z)
The form of hypothesis testing based on statistics can be described as follows: Table 11 obtains a tcount value of 4.051 With α = 5%, ttable (5% ; nk = 53-1 = 52) obtained a ttable value of 2.007 From this description it can be seen that tcount (4.051) > ttable (2.007), likewise with a significance value of 0.000 <0.05, it can be concluded that the first hypothesis is accepted, meaningCompensation variable (X) effecton the variable Work Motivation (Z).
The results of this study are in accordance with the results of research conducted by(Harahap & Khair, 2019)entitledThe Influence of Leadership and Compensation on Job Satisfaction Through Work MotivationonPT PLN (Persero) North Sumatra Generation Main Unit. The form of hypothesis testing based on statistics can be described as follows: From table 12, the tcount value is obtained8,034With α = 5%, ttable (5% ; nk = 53-2 = 51) obtained a ttable value of 2.008. From this description it can be seen that tcount (8,034) > ttable (2.008), likewise with a significance value of 0.000 <0.05, it can be concluded that the second hypothesis is accepted, meaningCompensation variable (X) effecton the variable Job Satisfaction (Y). The results of this study are in accordance with the results of research conducted by(Nurhayati 2018) with the title Effect of Compensation and Motivation on Employee Job Satisfaction at Pt. Bank Sulselbar Maros Sharia Branch.

Hypothesis Testing Effect of Work Motivation variable (Z) on Job Satisfaction variable (Y)
The form of hypothesis testing based on statistics can be described as follows: From table 12, the tcount value is obtained2,160With α = 5%, ttable (5% ; nk = 53-2 = 51) obtained a ttable value of 2.001. From this description it can be seen that tcount (2.160) > ttable (2.008), and a significance value of 0.036 <0.05, it can be concluded that the third hypothesis is accepted, meaningthe variable Work Motivation (Z) has an effecton the variable Job Satisfaction   Furthermore, the value of standardized coefficients beta will be entered into the path analysis image as follows:

DISCUSSION
Based on the results of hypothesis testing that has been done, the next stage is an explanation of the relationship between the variables in this study which is then linked to consumer behavior, previous studies and management science so that it can support pre-existing statements. The explanation of the results is as follows: 1. Effect of Compensation (X) on Work Motivation (Z) Based on the results of the analysis of hypothesis 1, it can be seen that it can be concluded that the first hypothesis is accepted, meaningCompensation variable (X) effecton the variable Work Motivation (Z). The results of this study are in accordance with the results of research conducted by(Harahap & Khair, 2019)entitledThe Influence of Leadership and Compensation on Job Satisfaction Through Work MotivationonPT PLN (Persero) North Sumatra Generation Main Unit. Which means that Compensation is a major consideration factor for PT. Tiga Mutiara Nusantara so that they are motivated in carrying out their work and are able to provide ideas at work.
2. Effect of Compensation (X) on Job Satisfaction (Y) Based on the results of the analysis of hypothesis 2 it can be seen that it can be concluded that the second hypothesis is accepted, meaningCompensation variable (X) effecton the variable Job Satisfaction (Y). The results of this study are in accordance with the results of research