The model of Supervisor Support, Work-Life Balance, Job Satisfaction, and Organizational Commitment on IT Employee Performance moderated by Demographic factors

This study aims to explore the effect of Supervisor Support (SS), Work-Life Balance (WLB), Job Satisfaction, and Organizational Commitment on Employee Performance moderated by age, gender, education, and marital status on IT employees. Refer to the theory and empirical evidence from previous research, we collect the data by distributing online questionnaires from November to December 2020 at some IT sector companies in the cities of Tangerang and Jakarta. The respondents are IT employees who were selected by purposive sampling method with the category non-managerial level. This study uses the PLS-SEM method. The results prove that SS, WLB, job satisfaction, and organizational commitment all have positive effects on IT employee performance. While the moderation results in this study as a whole there are no significant differences between groups of age, gender, education, and marital status with the effect of job satisfaction and organizational commitment on IT employee performance. The important managerial implications for the companies to improve the performance of IT employees are by changing the company's internal culture to be more open, creating or strengthening the warm and ‘kinship’ work environment, and organize a routine togetherness program. This will encourage positive changes for employees and be a benefit for the company.


I. INTRODUCTION
The business world is starting to realize the importance of Work-Life Balance (WLB) as an effort to improve employee performance (Peng, 2020). Various studies have described a strong relationship between WLB and employee performance (Kim, 2014;Smith et al., 2016). WLB is a determining factor for the level of job satisfaction of employees, this varies from profession to profession and from industry to industry (Pandu and Sankar, 2018). Delina and Raya (2013) state that IT (Information Technology) employees face high levels of pressure and low WLB among employees who work in several company sectors, such as IT, health, and education. IT companies are reported as one of the main sectors where employees under high pressure due to an imbalance between work and life (Dash et al., 2012). By providing work flexibility can increase WLB of employees (Hayman, 2010). Companies that do not provide work flexibility tend to have a negative impact on the performance of their employees, whereas increasing WLB of employees can be a benefit for the company (Kelly et al., 2014).
Supervisor Support (SS) in the workplace can increase the WLB of employees by providing flexible work schedules to employees, thus enabling them to complete responsibilities between work and non-work (Russo et al., 2015). In addition to having an impact on WLB of employees, SS also has a great influence on the implementation and success of work and life of employees (Fiksenbaum, 2014). When employees believe that their supervisor cares about their family's needs, they can respond with a more positive perception of their work environment, increased job satisfaction, and a greater willingness to stay with the company (Talukder et al., 2018).
Globalization and increasing competition put employees under pressure that more increasing to speed up response times and meet deadlines (Salanova et al., 2002). The increasing workload also has an impact on employees' personal lives and other aspects of life (Kaushal, 2019). Hayman (2010) found a positive correlation between flexible work schedules and WLB, namely reducing stress and overwork, then increasing job satisfaction. WLB can affect the level of employee job satisfaction (Greenhaus and Powell, 2006). When WLB is high, employee job satisfaction also increases (Singh and Dubey, 2016). WLB is also influential in strengthening employee organizational commitment (Kim, 2014). Increasing job satisfaction and strengthening organizational commitment will encourage employee performance improvement (Abdirahman et al., 2020).
Many previous researchers have explored about WLB of IT employees, such as Mohan et al. (2010), Dash et al. (2012), Syrek et al. (2013), Warrier (2013), Walia (2015), Semlali and Hassi (2016), Pandita and Singhal (2017), Manasa and Showry (2018), Pandu and Sankar (2018), Sathyanarayana et al. (2018), Kaushal (2019), and Pandu (2019aPandu ( , 2019b. Some previous studies have explained that Supervisor Support as a form of supervisor concern that can affect WLB of employees Fiksenbaum, 2014;Russo et al., 2015;Talukder et al., 2018). Other researchers also have explored the strength of WLB that affects the level of job satisfaction and employee organizational commitment (Crede et al., 2007;Muse et al., 2008;Casper et al., 2011;Talukder et al., 2018). Another study found that job satisfaction and organizational commitment have an influence that can drive employee performance (Shore and Martin, 1989;Sutanto, 1999;Talukder et al., 2018;Zain and Setiawati, 2019;Abdirahman et al., 2020). However, it is still rare to find research that examines WLB of IT employees which are associated with the effect of Supervisor Support and WLB on Job Satisfaction and Organizational Commitment to determine the effect on Employee Performance moderated by age, gender, education, and marital status.
This study aims to explore the effect of Supervisor Support, Work-Life Balance, Job Satisfaction, and Organizational Commitment on Employee Performance moderated by age, gender, education, and marital status of IT employees. This research is expected to contribute to the development of organizational management science and provide positive managerial implications for many parties.

II. LITERATURE REVIEW
A. Supervisor Support Eisenberger et al. (2002) stated the definition of supervisor support as employees' views on whether their supervisors' value their contributions and care about their well-being. Actions such as listening to disputes, informing employees about decisions, implementing employee-focused practices (Domínguez-Falcón et al., 2016), and communicating company information can be seen by employees as forms of supervisor support (Karatepe and Kaviti, 2016). Employees can provide support to their supervisors by providing better 316 performance to return the favor (Zhou et al., 2016). Gilbreath and Benson (2004) found that supervisor behavior is directly related to employee welfare, affecting physical and mental health. A supervisor who provides a positive welfare atmosphere can improve team performance in the workplace (Han et al., 2016).

B. Work-Life Balance
Work-Life Balance (WLB) is a term that refers to the absence of conflict between work roles and family roles (Frone, 2003). According to Soomro et al. (2018), WLB is a division of employee's time for work and for their families. Kaushal (2019) states that WLB is a balanced condition in which an individual manages the demands of job roles and personal roles well. Each role has a different set of demands and when the demands of the two roles do not match, many problems can arise which leads to pressure among employees (Kaushal, 2019).

C. Job Satisfaction
Job satisfaction is meaningful as an emotional response in the work environment (Armstrong, 2006in Cic et al., 2018. Ezeja et al. (2010); Jayasuriya et al. (2012) define job satisfaction as a pleasant and positive emotional reaction to an individual's perception of his or her job, and it is important especially in internal perceptions of individual values and their relationship to perceptions of their current working conditions. Employees with high job satisfaction are less likely to be absent, less likely to leave the company, more productive, more likely to show organizational commitment, and more likely to be satisfied with their lives (Lease, 1998).

D. Organizational Commitment
Luthans (2006) in Setyaningrum (2017) states that organizational commitment is the attitude of employees that reflects their loyalty to the organization. Organizational commitment is an attachment to the organization, characterized by shared values, a desire to stay in the organization, and a desire to exert efforts on his or her behalf (Mowday et al., 1979). Allen and Meyer (1990) state that organizational commitment is divided into three dimensions, namely: (1) affective commitment, as an emotional bond where employees identify themselves as part of the organization and enjoy their membership in the organization; (2) continuance commitment, which is related to the costs incurred when leaving the organization, and (3) normative commitment, namely a feeling of responsibility to stay in the organization. This study focuses on affective commitment. Allen and Meyer (1996); Glazer and Kruse (2008); Luturlean et al. (2018) explain that affective commitment is the emotional bond of employees to the organization and their willingness to stay in the organization by believing in the goals and values of the organization. Affective commitment is the main force that encourages individuals to contribute to improving organizational performance (Meyer et al., 1989).

E. Employee Performance
Employee performance is the effectiveness of employees' contributions to organizational goals (Zahrah et al., 2017). Mehrzi and Singh (2016) state that employee performance is about doing the job and the extent of the results are achieved from that job. Employee performance is the result, score, and work achievement (Jankingthong and Rurkkhum, 2012) which is achieved by employees in quality and quantity in carrying out their assigned duties and responsibilities (Shmailan, 2016). Employee performance refers to behaviors, actions, and results that involve or bring in all employees who contribute and are related to the goals of the organization (Viswesvaran and Ones, 2000).

F. Age
Age is usually defined as the number of years of life or distance from birth (Jarvik, 1975). Older employees are perceived to be more positive than younger employees in terms of emotional stability (Rosen and Jerdee, 1976) and job satisfaction (Hassell and Perrewe, 1995). On the other hand, younger employees are seen as more motivated at work, ambitious, and able to learn quickly than older employees (Bertolino et al., 2013). However, younger employees are seen as less loyal and less emotionally stable (Rosen and Jerdee, 1976;Gibson et al., 1993).

G. Gender
Gender refers to the roles and social responsibilities that are built from men and women (Chaudhry and Rahman, 2009). According to Lindsey (2016), gender refers to social, cultural, and psychological characteristics 317 associated with men and women through certain social contexts. Gender differences can be seen from infancy because different teachings are given to boys and girls (Gulla and Masrur, 2019).

H. Education
Education is a continuous practice consisting of a structured learning process that is deliberately aimed at the realization of goals that consciously come from a certain conception of 'goodness' (Sarid, 2017). Each level of education obtained can equip individuals with new skills and knowledge needed to carry out job roles (Kahya, 2007;Ng and Feldman, 2009;Asiamah et al., 2016;Asiamah, 2017;Asiamah et al., 2019).

I. Marital Status
Marital status is defined as terms of the presence or absence of a partner that involves more than just a personal relationship, because every condition of marriage is linked to socially agreed rights and obligations relating to children, sexuality, kinship ties, place of residence, household, and economic services (Harris, 1969in Morgan, 1980. Marital status is a condition that is determined socially, generally, and legally, also serves to distinguish between people who are married and single (Morgan, 1980).

A. Supervisor Support and Work-Life Balance
Supervisor support is part of the resources that can help reduce negative psychological impacts, e.g., poor WLB felt by employees (Talukder et al., 2018). Supervisor support in the workplace can be the form of emotional support from the supervisor such as providing assistance or solutions to employees so that their work can be completed faster and have sufficient time for family (Talukder et al., 2018). When supervisors pay attention to the employee's family needs, these employees can be better at managing their work commitments and family demand (Talukder et al., 2018). This will make employees having a more balanced life and less conflict between work and family (Talukder et al., 2018). The results of research by Talukder et al. (2018) show that there is a positive effect between supervisor support on WLB. From the description, we propose the following hypothesis: H1: Supervisor support has a positive effect on WLB of IT employees.

B. Work-Life Balance and Job Satisfaction
Previous research has shown that companies that implement WLB practices (e.g. flexible work arrangements) expect to have more satisfied employees (Talukder et al., 2018), such as the presence of reciprocal behavior (Gouldner, 1960) and feel the presence of support from the organization (Rhoadres and . Talukder et al. (2018) confirmed that individuals who perceive that companies are taking care of their well-being (e.g., through formal or informal support for WLB) can experience positive feelings and increase their job satisfaction. Individuals who experience WLB will be more satisfied with their work because they participate in activities with roles that are prominent to them (Greenhaus and Powell, 2006). Previous research has confirmed that WLB has a positive effect on job satisfaction (Crede et al., 2007;Talukder et al., 2018;Suryanto et al., 2019). Based on the above statements, we propose the following hypothesis: H2a: WLB has a positive effect on job satisfaction of IT employees.

C. Work-Life Balance and Organizational Commitment
Individual WLB is achieved through supervisors who support and implement a 'kinship' atmosphere in the organization (Talukder et al., 2018). Organizations that provide a 'kinship' work environment get benefit significantly in terms of performance through reduced turnover intentions and increased organizational commitment (Grover and Crooker, 1995;Thompson et al., 1999). When employees perceive their supervisors play a role in helping them to achieve WLB (e.g., flexible work arrangements), employees tend to reciprocate with a commitment to the organization (Talukder et al., 2018). Kossek et al. (2001) found that employee commitment increased when the organization help employees in fulfilling responsibilities outside of work for their families. The presence of WLB will foster loyalty and commitment to the organization (Kim, 2014). Emotional attachment to the organization can keep individuals staying with the organization (Allen and Meyer, 1996). Hyman and Summers (2007) admit that there have been many studies that support the relationship between WLB and increased employee performance and commitment. Oyewobi et al. (2019) imply that WLB increases employee loyalty to their organization, which in the end increases commitment (affective). Based on 318 previous research, it can be concluded that WLB has a positive effect on employee organizational commitment (Muse et al., 2008;Casper et al., 2011;Talukder et al., 2018;Wardana et al., 2020). Therefore, we propose the following hypothesis: H2b: WLB has a positive effect on organizational commitment of IT employees.

D. Job Satisfaction and Employee Performance and also its moderation
If employees perceive their job well (e.g., their salary, supervisor support, working conditions, etc.) and satisfied with it, then they are more likely to perform well (Talukder et al., 2018). According to Coomber and Barriball (2007), employees with high job satisfaction will work in a healthier mood and they are ready to learn more skills that can lead to improved employee performance. Some researchers have found that job satisfaction has a positive and significant effect on employee performance (Shore and Martin, 1989;Zain and Setiawati, 2019;Abdirahman et al., 2020;Kishen et al., 2020;Sidabutar et al., 2020). Nasir et al. (2011) found that age, gender, education, and marital status had a significant effect on employee performance. Valaei and Jiroudi (2016) state that age, gender, and education moderated the effect of job satisfaction on employee performance. Milledzi et al. (2018) states that older employees have higher job satisfaction than younger employees; single employees have higher job satisfaction than married employees. Weaver (1974); Forgionne and Peeters (1982) found that job satisfaction in male gender is higher than female. Meanwhile, the findings of Bartol and Wortman (1975);Clark (1996) stated that female gender has higher job satisfaction than male. The different levels of job satisfaction between male and female employees may be due to differences in the types of their expectations of their jobs (Campbell et al., 1976).
Based on the statement, we propose the following hypothesis: H3a: Job satisfaction has a positive effect on IT employee performance. H3a1: There is a significant difference between age and the effect of job satisfaction on IT employee performance, where older age has a stronger influence. H3a2: There is a significant difference between gender and the effect of job satisfaction on IT employee performance, where male gender has a stronger influence. H3a3: There is a significant difference between education and the effect of job satisfaction on IT employee performance, where Bachelors-Masters education has a stronger influence. H3a4: There is a significant difference between marital status and the effect of job satisfaction on IT employee performance, where single status has a stronger influence.

E. Organizational Commitment and Employee Performance and its moderation
According to Allen (2001), employees can return the favor for organizational support for their family life by forming a stronger attachment to the organization. Steers (1977) states that there are three main reasons why committed employees tend to perform better: (1) employees with a higher level of organizational commitment tend to arrive on time; (2) these employees have a stronger relationship with the goals of the organization, so they have a stronger desire to work towards the achievement of their organizational goals; and (3) committed employees will put more effort into their jobs. Sutanto (1999);Talukder et al., 2018;Abdirahman et al. (2020); Imron et al. (2020); Soelton et al. (2020) stated that there is a strong and significant effect between organizational commitment and employee performance. Hassan and Ogunkoya (2014) found that there is a significant effect between age, gender, education, and marital status as demographic factors that affect employee performance. Salami (2008) obtained that age, education, and marital status have a significant effect on organizational commitment. Rabindarang et al. (2014) emphasized that employees who are older are more committed to an organization than younger employees and new employees. Other researchers found that gender moderated the effect of organizational commitment (Singh et al., 2004) on employee performance (Valaei and Jiroudi, 2016). Education can be a source of new competencies to improve employee performance (Ng and Feldman, 2009;Enein et al., 2012). The higher the educational qualification, the less organizational commitment (Joiner and Bakalis, 2006). The assumption is employees with higher educational qualifications can find work anywhere and have more expectations that the organization might be able to meet, while employees with lower educational qualifications have difficulty changing jobs and finding other suitable jobs (Clarence and George, 2018). Married employees are more committed to the organization and motivated to show higher performance than single employees because they need stable jobs by reason of the responsibility they feel towards their family and concerns about their financial (Choong et al., 2012). Therefore, we propose the following hypothesis: H3b: Organizational commitment has a positive effect on IT employee performance. H3b1: There is a significant difference between age and the effect of organizational commitment on IT employee performance, where older age has a stronger influence. H3b2: There is a significant difference between gender and the effect of organizational commitment on IT employee performance, where male gender has a stronger influence. H3b3: There is a significant difference between education and the effect of organizational commitment on IT employee performance, where Bachelors-Masters education has a stronger influence. H3b4: There is a significant difference between marital status and the effect of organizational commitment on IT employee performance, where married status has a stronger influence.
Based on the proposed hypotheses, the following is the research model in Figure 1:

III. RESEARCH METHODOLOGY
This research is conducted from November to December 2020 at some IT sector companies in the city of Tangerang and Jakarta in Indonesia, such as IT System Integrator, IT Services, and other similar companies. The respondents are IT employees who were selected by the purposive sampling method with the category nonmanagerial level. Data collection begins with conducting a pre-test first by distribute questionnaires to 30 respondents. To obtain primary data, we are distributing online questionnaires via Google Form using the Likert scale with a scale of 1 (strongly disagree) to 5 (strongly agree).
Measurement for variable of Supervisor Support is adopted from Clark (2001) which consists of 3 statements and from Thompson et al. (1999)  For variable of Organizational Commitment, the measurement is adopted from Mowday et al. (1979) which consists of 5 statements. Measurement for variable of employee performance is adopted from Williams and Anderson (1991) which consists of 6 statements and from Lynch et al. (1999) which consists of 4 statements. This measurement has also been used in some studies by previous researchers (Wang and Walumbwa, 2007;Carlson et al., 2009;Greenhaus et al., 2012;Qu and Zhao, 2012;Abbas et al., 2014;Bagger and Li, 2014;Brough et al., 2014;Russo et al., 2015;Talukder et al., 2018).
In the moderating variable for age, the measurement is made into 2 scales consisting of a scale of 1 for ages 18-35 years (younger) and 2 for ages 36-55 years (older). The moderating variable for gender is differentiated between male and female using a scale of 1 for male and 2 for female. The moderating variable for education consists of 4 scales, namely a scale of 1 for Senior High School, 2 for Diploma, 3 for Bachelors, and 4 for Masters. The moderating variable for marital status is differentiated between single and married using a scale of 1 for single and 2 for married.
From the result of pre-test data, we use factor analysis to test the validity and reliability then processed the data using SPSS software. The validity test is measured by looking at the KMO (Kaiser-Meyer-Olkin) and MSA (Measures of Sampling Adequacy) values, the KMO and MSA values are more than 0.50 meaning that the factor analysis is appropriate (Hair et al., 2014). The reliability test uses the Cronbach's Alpha measurement, when the Cronbach's Alpha value closer to 1 it means that it is more reliable (Hair et al., 2014).
Based on the results of the validity and reliability tests on the pre-test data, the variable of Supervisor Support out of 5 statements, only 3 are declared valid. For the variable of Work-Life Balance, out of 5 statements, only 4 are declared valid, while for the variable of Job Satisfaction all of them are declared valid. Then for the variable of Organizational Commitment out of 5 statements, only 4 are declared valid, and the variable of Employee Performance out of 10 statements only 6 are declared valid. Thus, out of the 30 statements which are declared valid and reliable, there are 22 statements that become the questionnaire in this study.
Because this study uses the PLS-SEM (Partial Least Squares -Structural Equation Modeling) method where the determination of the number of research samples is at least 10 times the maximum number of arrows pointing to any latent variable in the PLS path model (Hair et al., 2017), then the number of samples in this study are 184 people.
To analyze the research data result, we use the SmartPLS software. Because this study uses demographic factors as the moderating variable where demographic factors are categorical variables, the analysis of the moderation hypothesis testing is carried out separately from the path model using the Multi-Group Analysis The construct validity and reliability tests are carried out based on the recommendations of Hair et al. (2017). The measurement of construct validity in this study is declared valid and acceptable, because most of the indicators for each variable had a loading factor (outer loading) value more than 0.70. Only one indicator has a loading factor value less than 0.70, which is the first indicator of the Supervisor Support variable (SS1 0.630). The results of the calculation of CR (Composite Reliability) and AVE (Average Variance Extracted) in this study as a whole are declared to meet the construct reliability requirements, because all variables show CR value more than 0.70 and AVE value more than 0.50, namely Supervisor Support (CR 0.913; AVE 0.840), Work-Life Balance (CR 0.908; AVE 0.713), Job Satisfaction (CR 0.890; AVE 0.620), Organizational Commitment (CR 0.895; AVE 0.681), and Employee Performance (CR 0.919; AVE 0.654).
Structural tests are carried out to determine the value of R-Square (R 2 ) in each equation. The value of R 2 shows the extent to which the exogenous variables are able to explain the endogenous variables (Hair et al., 2014). Based on the results of the analysis, the first is that the Work-Life Balance (WLB) variable is influenced by the Supervisor Support (SS) variable with R 2 value of 0.207 which means that 21% the variants of the Work-Life Balance (WLB) can be explained by the Supervisor Support (SS) variable, while the remaining 79% is explained by other variables which is not discussed in this study. The second analysis, namely the Job Satisfaction (JS) variable is influenced by the Work-Life Balance (WLB) variable with R 2 value of 0.118 which means that 12% variant of Job Satisfaction (JS) can be explained by the Work-Life Balance (WLB) variable, while 88% the rest is explained by other variables which is not discussed in this study. Third, the Organizational Commitment (OC) variable is influenced by the Work-Life Balance (WLB) variable with R 2 value of 0.277 which means that 28% of the variants of Organizational Commitment (OC) can be explained by the Work-Life 321 Balance (WLB) variable, while the remaining 72% is explained by other variables which is not discussed in this study. And fourth, the Employee Performance (EP) variable is influenced by the Job Satisfaction (JS) and Organizational Commitment (OC) variables with R 2 value of 0.318 which means that 32% of the variants of Employee Performance (EP) can be explained by the Job Satisfaction (JS) and Organizational Commitment (OC) variable, while 68% the rest is explained by other variables which is not discussed in this study.
The fit model analysis is carried out based on the recommendations of Hair et al. (2017) which is measured based on the SRMR (Standardized Root Mean Square Residual) value. SRMR value less than 0.08 means the model is fit (Hu and Bentler, 1998). The results of the analysis in this study obtained an SRMR value of 0.077, meaning that the overall research model is declared fit.
The results of the research analysis are described in the path model in Figure 2: Based on the path model in Figure 2, the following are the results of the research hypothesis tests shown in Table 1: By looking at the table of hypothesis tests in Table 1, it is known that the data in this study support all of the hypotheses because all path coefficients are positive and have T-Value more than 1.96 and P-Value less than 0.05 (Hair et al., 2017).
Especially for the analysis of hypothesis testing with moderation, it is carried out separately from the path model using Multi-Group Analysis (MGA). The analysis is presented in Table 2: Based on the table of hypothesis tests in Table 2, it is known that the data in this study does not support all of the research hypotheses with moderation because PLS-MGA has no P-Value less than 0.05 or more than 0.95 (Garson, 2016;Cheah et al., 2020).

V. DISCUSSION
The results of this study prove that supervisor support has a positive effect on WLB of IT employees. It means the higher supervisor support to IT employees, the higher their work-life balance will be. Supervisor support in the workplace has an important role as a positive energy generator for employees. Supervisors who are open and willing to listen to stories or complaints from their employees and provide assistance in the form of solutions or suggestions are assessed by employees as a form of support for them. IT companies that apply flexible work arrangements and work schedules such as working from home (work remotely) and the absence of an attendance system which is generally required to be used when entering and leaving work are assessed by IT employees as a form of WLB for them, so that they can manage their time properly between work and life. Supervisors can control the work of their employees through the timesheets that are reported regularly, and do not often interfere with employees' time related to work outside of work time (such as on leave and weekends) as well as support SS perceptions and increase WLB of IT employees. This is in line with the thoughts of some 323 previous researchers and contributes to strengthening previous research Fiksenbaum, 2014;Russo et al., 2015;Talukder et al., 2018).
This research also found that WLB has a positive effect on job satisfaction of IT employees. That means the higher WLB on IT employees, the more their job satisfaction will be. For employees, WLB is very important to be applied in their lives. With the formation of WLB, IT employees can divide their time for work and for their personal and family lives, so that employees feel calmer and more comfortable because they can live their lives in a balanced way. IT employees who own WLB carry out their work wholeheartedly, more productive, and show a positive emotional attitude in their environment. This finding is in line with some opinions and studies that have been done before (Greenhaus and Powell, 2006;Crede et al., 2007;Soomro et al., 2018;Talukder et al., 2018;Kaushal, 2019;Suryanto et al., 2019;Abdirahman et al., 2020).
Besides job satisfaction, WLB has also been shown to have a positive effect on organizational commitment of IT employees. It means the higher WLB of IT employees, the higher their organizational commitment. IT companies that create WLB and 'kinship' work atmosphere make employees feel emotionally attached to the organization. This sense of attachment makes employees feel proud to be a part of the company and eager to make the best contribution as a form of their organizational commitment to the company. This result is in line with some opinions and previous studies (Muse et al., 2008;Casper et al., 2011;Soomro et al., 2018;Talukder et al., 2018;Kaushal, 2019;Abdirahman et al., 2020;Wardana. et al., 2020).
This study also proves that job satisfaction has a positive effect on IT employee performance. High job satisfaction will improve the performance of IT employees. Basically, job satisfaction is individual because each individual has a different level of satisfaction according to the hopes and desires that exist within them. The more aspects of work that are in line with individual expectations and desires, the higher the level of job satisfaction that is felt. IT employees who have high job satisfaction will carry out their duties with enthusiasm and a sense of responsibility. Because of this feeling of satisfaction, they will produce a good performance output. The finding that job satisfaction has a positive effect on employee performance strengthens some similar studies (Shore and Martin, 1989;Zain and Setiawati, 2019;Abdirahman et al., 2020;Kishen et al., 2020;Sidabutar et al., 2020).
Organizational commitment has also been shown to have a positive effect on IT employee performance. This shows that high organizational commitment will improve the performance of IT employees. Organizational commitment encourages employees to be loyal to their work and produce performance in accordance with the targets given by the company. IT employees with high organizational commitment will work with passion and strive for the best contribution and work results for the company. These employees can also be positive influencers to other employees in the work environment to increase the effectiveness and performance of their work. Organizational commitment also has a major impact on employee performance that can be a benefit for the company, such as maintaining the company's good name and promoting the positive side of the company to the people closest to them. This is in line and supports the findings of some previous researchers (Sutanto, 1999;Talukder et al., 2018;Abdirahman et al., 2020;Imron et al., 2020;Soelton et al., 2020).
Age does not have a significant difference in the effect of job satisfaction on IT employee performance. It means that older IT employees do not make their job satisfaction levels higher than younger IT employees. Likewise, the impact on their job performance, it cannot be guaranteed that older people will perform higher than younger ages. This result is different from the opinion of Milledzi et al. (2018), but supports some previous research such as Sarmiento et al. (2007); Anari (2012); Badawy and Magdy (2015) who found similar results with this study.
Gender also does not have a significant difference with the effect of job satisfaction on IT employee performance. Thus, gender differences of IT employees in the IT industries are not a measure to differentiate the level of job satisfaction between males and females and its effect on the performance they achieve. These findings strengthen some previous studies which found that gender differences have no effect on job satisfaction and employee performance (Badawy and Magdy, 2015;Ogunleye and Osekita, 2016;Milledzi et al., 2018).
Education does not show a significant difference between the effect of job satisfaction on IT employee performance. This means the different educational levels of IT employees cannot be a benchmark for assessing job satisfaction with their job performance. This result is in line with some previous researchers who found that education has no effect on job satisfaction and employee performance (Sarmiento et al., 2007;Wright et al., 2007;Trivellas et al., 2015).
Marital status also does not show a significant difference in the effect of job satisfaction on IT employee performance. The marital status of IT employees cannot predict the difference in the level of job satisfaction 324 with their performance. This is in contrast to the research of Milledzi et al. (2018), but supports several previous researchers who obtained results that marital status does not moderate the effect of job satisfaction on employee performance (Azim et al., 2013;Valaei and Jiroudi, 2016).
Age does not have a significant difference in the effect of organizational commitment on IT employee performance. It means older IT employees do not necessarily have higher organizational commitment than younger IT employees. Likewise, the effect on their performance cannot be predicted just by looking at their age. This does not support the statement of Rabindarang et al. (2014), but some other researchers found similar results with this study that age does not moderate the effect of organizational commitment on employee performance (Sarmiento et al., 2007;Iqbal, 2010;Anari, 2012).
Gender also does not have a significant difference with the effect of organizational commitment on IT employee performance. That means gender cannot measure the difference in the level of organizational commitment and performance achievement between male and female IT employees, especially in IT companies. This result is different from the research by Singh et al. (2004); Valaei and Jiroudi (2016), but in line with several other researchers who explore the effect of gender differences on organizational commitment and employee performance, the results show that gender does not have a significant difference in the effect of organizational commitment on employee performance (Salami, 2008;Anari, 2012;Khalili and Asmawi, 2012;Çoğaltay, 2015;Ogunleye and Osekita, 2016;Cao et al., 2020).
Education does not have a significant difference between the effect of organizational commitment on IT employee performance. Thus, the education level of IT employees cannot predict the level of organizational commitment to their job performance. This is not in line with previous researchers (Joiner and Bakalis, 2006;Clarence and George, 2018). However, this result is in line with several other research results, such as Aranya and Jacobson (1975); Sarmiento et al. (2007) which confirms that education does not moderate the effect of organizational commitment on employee performance.
Marital status also does not have a significant difference in the effect of organizational commitment on IT employee performance. This means that the marital status of IT employees cannot be used as a reference to determine the level of organizational commitment to their job performance. This finding does not support the opinion of Choong et al. (2012), but supports some previous researchers such as Aranya and Jacobson (1975); Çoğaltay (2015); Cao et al. (2020) who states that marital status has no effect on organizational commitment to employee performance.
Based on the results of the moderation test between groups of age, gender, education, and marital status with the effect of job satisfaction on IT employee performance as a whole there are no significant difference, it means all demographic factors cannot be used to predict the effect of job satisfaction on IT employee performance. This result is not in line with some similar studies whose findings significant effect (Nasir et al., 2011;Valaei and Jiroudi, 2016). Similar to job satisfaction, the results of the moderation test on the effect of organizational commitment on IT employee performance with demographic factors in this study as a whole there are also no significant differences, that means groups of age, gender, education, and marital status cannot be used to predict the effect of organizational commitment on IT employee performance. This finding is not in line with the findings of some previous researchers (Salami, 2008;Hassan and Ogunkoya, 2014). The moderation test in this study also checks using the Analysis of Variance (ANOVA) method using SPSS software to validate the causes of the results of all moderation. After being checked, it turns out that because of age, gender, education, and marital status of IT employees as a whole have the same average in job satisfaction, organizational commitment, and employee performance.

VI. CONCLUSION AND RECOMENDATION
This study proves that the higher supervisor support is given to IT employees, the higher their work-life balance will be. When the work-life balance of IT employees increases, job satisfaction and organizational commitment will also increase. High job satisfaction and high organizational commitment will improve IT employee performance.
On the other hand, the moderation results in this study as a whole there are no significant differences between groups of age, gender, education, and marital status with the effect of job satisfaction and organizational commitment on IT employee performance, it means all demographic variables cannot be used to predict the effect of job satisfaction and organizational commitment on IT employee performance. The reason is 325 because of age, gender, education, and marital status of IT employees as a whole have the same average in job satisfaction, organizational commitment, and employee performance.
There are still some limitations that need to be fixed in further research. First, this research is limited to IT sector companies in the city of Tangerang and Jakarta in Indonesia, so it is not necessarily able to describe the condition or represent IT companies in other cities. Therefore, similar future research can explore other company sectors, such as E-Commerce and Banking. Second, the moderating variable used in this study is limited to demographic factors, further researchers are expected to add other moderating variables, such as tenure or factors outside of work. Further researchers are also advised to discuss further about the effect of supervisor support on work-life balance, for example by adding co-workers as an intervening variable.
This research has some points of managerial implications that are important to do in order to improve the performance of IT employees, considering that supervisor support is proven to contribute to improving work-life balance of IT employees which can increase their job satisfaction and organizational commitment. First, changing the company's internal culture to be more open to listening to any feedback from employees, this implementation certainly needs to start from top management so that all company members also familiarize themselves with this culture, especially team leaders who have members under them. For example, by being willing to take the time to listen to and discuss with employees, give appreciation or compliment to employees who have successfully completed a project on time, approach employees who tend to be quiet or passive, encourage and assist employees in finding solutions to a problem at hand. Open company culture will be a benefit for the company, such as reducing employee turnover, reducing work stress, strengthening employer branding, and increasing the company's competitive advantage. Second, creating or strengthening the warm and 'kinship' work environment so that employees feel that their workplace is very comfortable as a 'second home' for them. Thus, employees will be more loyal and attached to the company. Third, organize a routine togetherness program (at least once a year) that includes all of the employees, e.g., the event of employee gathering and outbound. Activities with a relaxed and pleasant atmosphere like this can eliminate employee boredom with work routines and make employees more engaged with the company.