Keywords

WFH, Mental Emotional, Psychological Well-Being, Performance, Satisfaction, Expectation

Introduction

The Covid-19 pandemic has made governments in many countries decide to lock down and implement Work From Home (WFH) for employees in the government and private sectors, including Indonesia. WFH aims to limit community activities, implement social and physical distancing, and prevent crowds of people, because the threat of the Covid-19 outbreak cannot be underestimated and ignored. This epidemic has been running for 1.5 years, and until early September 2021 as many as 220 million people were exposed to Covid-19 and more than 4.5 million people died. In Indonesia alone, around 4.2 million people have been exposed to this Corona virus and more than 135 thousand people have died (Kompas.com, 2020; Okezone, 2021). It is estimated that the number of people affected by this virus will continue to increase in the future, even though the nations of the world are trying to fight it. In 2021, the governments of various countries are aggressively implementing mass vaccinations to establish herd immunity, where most of the population is immune to certain infectious diseases so that it is expected to provide indirect protection.

The impact of the pandemic appears in aspects of health, education, economy, social relations, cultural activities, recreation, and others. In the health aspect, many people are exposed to COVID-19 or stressed because they are worried and afraid of contracting the corona virus (Nisa, 2021). In the aspect of education, the government is forced to carry out Learning From Home (LFH) for students from primary to tertiary education, carrying out online learning with all the consequences, including the alleged decline in the quality of student learning (Zakso & Agung, 2021). In terms of employment, this pandemic has caused many government and private organizations to stop their activities and oblige their employees to work from home, even many companies have terminated employment with some or all of their employees because they no longer show activity and production. In the life of the state, budget spending is more focused on overcoming the Covid-19 pandemic, low investor sentiment towards the state spending deficit, and others. In people's lives, it causes people's purchasing power to decline, difficulties in meeting the daily needs of families, disruption of social and religious activities, and others (Nasution, Erlina & Muda, 2020; Sayuti & Hidayati, 2020; Varona & Gonzales, 2021).

WFH does raise various problems, ranging from an inadequate work environment at home, support for digital technology and internet networks, the inability to interact and communicate with leaders in the office, discomfort in the workspace at home, stress, reduced social interaction between co-workers, reduced activities, and so on (Pinasti, 2020; Nisa, 2021); From the institutional side, the workplace often creates communication limitations outside working hours, limited information dissemination, unclear employee performance measurements, unpreparedness to use technology, work productivity and effectiveness, and others (Burhan, 2020).

This paper will focus on the impact of WFH on the lives of employees in the government sector or the State Civil Apparatus (SCA). These types of workers are spread across various agencies, ranging from those who work in the central government, local governments, universities, and other government institutions who are relatively more fortunate, because every month they still survive and receive salaries, and are not faced with the fear of being dismissed from their place of work. On the other hand, in the private sector, many manufacturing and service industry companies could no longer maintain their business activities, went bankrupt, and were forced to lay off their employees.

This paper wants to explain the impact of the WFH policy on aspects of mental emotional condition, Psychological Well-Being (PWB), Job Performance (JPr), and Job Satisfaction (JSa), which in turn affects Job Expectations (JEx) of State Civil Servants (SCA). The study will also analyze the contribution of indicators for each variable, with the aim of seeing the contribution of the strongest and weakest indicators. Understanding the contribution of the strongest and weakest indicators is important, especially in emphasizing overcoming the existing problems.

Literature Review

The Covid-19 pandemic that has been going on since 2020 has hit countries in the world with hundreds of millions of people exposed, and claimed many lives. Governments in various countries have taken lockdown measures with the aim of preventing the spread of this virus, one of which is issuing a policy of Working From Home (WFH), where employees temporarily do not go to the office every day (Mungkasa, 2020). WFH is held until the Covid-19 pandemic is considered to have subsided, so that offices can be opened and back to normal. Through WFH, work is done online with the help of digital technology and internet network services.

WFH concern in this article is the workers in the public Sector Or Civil State Apparatus (SCA) working in various ministries, universities, and other government agencies. Since March 2020 SCA is required to carry out work from home activities to prevent the spread of Covid-19. The notion of WFH is not a new thing, as implemented, for example by freelancers, translators, SEO specialists, youtubers, resellers, and others (Crosbie & Moore, 2004; Dewayani, 2020; Juliawanti, 2021). But that meant WFH here is the original work activities routinely conducted five (5) days each week by SCA in the office, and then be required to work from home.

Of course implementing WFH means changing work habits. Employees who are accustomed to working with the support of adequate facilities, such as: a clean, fresh, and comfortable workspace equipped with air conditioning, the availability of digital technology, the use of a free and strong internet network, the availability of the necessary data and information, and good social interaction and mutual support with co-workers, etc., moving to a house with a different work environment, ownership of digital technology, own expenses for providing internet network, irregular working hours, and so on. On that basis, it is suspected that WFH has an impact on SCA self and work behavior, especially in terms of emotional mental conditions, psychological well-being, job performance, and job satisfaction, which in turn affect employee job expectations (Ahmad & Ahmad, 2021).

WFH is thought to have an impact on the mental emotional state of employees, especially emotional symptoms, behavioral problems, hyperactivity/inattention, peer relationship problems, and prosocial behavior (Ryff, 1989; Ryff & Keyes, 2007). Emotional symptoms refer to conditions where employees' emotions are different from the patterns and habits that are routinely carried out so far. Emotional symptoms can include depression or anxiety, irritability, frustration, and also physical symptoms, such as stomach pain, headache, or nausea (Ryff, 1989; Ryff & Keyes, 2007; Handayani, 2020). Behavioral problems are related to work actions that may be inappropriate, unacceptable, considered bad, disturbing, and wrong (https://www.honest docs.id/problems-behavior). Hyperactivity/ inattention is a response disorder that becomes inhibited and causes a lack of self-regulation, weak ability to achieve work goals, and difficulty adapting to a new work environment that must be carried out (Chervin et al., 2002; Wood et al., 2009). Problems with co-worker relationships are emotional, cognitive, and interpersonal behavioral disorders of a person with other individuals. Association with coworkers is quite important, not only related to work, but also status, making friends, sharing feelings, and others (Santrock, 2006). Prosocial behavior can be defined as the disruption of voluntary actions to help, support and benefit coworkers (Eisenberg & Mussen, 1989). This prosocial behavior refers to disturbances resulting from the non-fulfillment of various aspects of work, such as: sharing, entertaining, discussing, helping, and others.

WFH is also thought to have an impact on the psychological well-being of employees. Psychological well-being is a condition in which people have a positive attitude toward self and others, organize and manage the environment in accordance with their needs, developing positive relationships with others, have a purpose in life that is more meaningful, trying to explore and develop her potential, and accept the situation themselves, make decisions, and regulate their own behavior (Ryff, 1989). Psychological well-being refers to indicators: autonomy, environmental mastery, personal growth, positive relationships, life goals, and self-acceptance (Ryff, 1989; Ryff & Kayes, 2007; Kállay & Rus, 2014; Prabowo, 2016).

The autonomy indicator means an understanding of the ability of the state civil apparatus to direct behavior independently, confidently, and responsibly. An indicator of environmental mastery is the ability to manage the environment effectively by modifying it to meet the needs and demands of the job. An indicator of personal growth is the ability to develop self-actualization potential. Indicators of positive relationships are the ability to build relationships with other people based on trust, concern, empathy, and understanding of the principles of mutual acceptance and giving, or vice versa tends to be closed, less caring, less sensitive, and less controlling the environment. The life purpose indicator is an assessment where the workplace can provide a better life in the future and make it a meaningful view of life. Indicators of self-acceptance are awareness of the strengths and weaknesses of employees and need to be considered, so that working from home does not bring disappointment, dissatisfaction, and hinders personality qualities, because they are unable to make the desired self-changes (Ryff, 1989; Ryff & Keyes, 2007; Prabowo, 2016; Rahayu & Haq, 2021).

WFH is also suspected to have an impact on the job performance of civil servants (SCA), namely as a show of ability, job opportunities, taking advantage of time, opportunities, and motivation in carrying out work (Robbins, 2007). Employee performance includes several aspects, including: work knowledge, creativity, dependence, work quality, cooperation, integrity (Robbins & Judges, 2017; Gomes, 2014). Work knowledge is a skill in carrying out work that requires creativity in completing work. Cooperation is the ability to build relationships with other people regarding the completion of a job based on trust and interdependence. Integrity is motivation, dedication, and responsibility that is manifested in completing tasks/jobs (Robbins & Judges, 2017; Gomes, 2014).

WFH is thought to have an impact on the job satisfaction of civil servants as a positive or negative response to their work, especially work done online. Job satisfaction is a person's thoughts, feelings, and attitudes towards his work (Vechio, 2014; Greenberg & Baron, 2014; Wibowo, 2007; Kirkpatrick & Levis, 2015). There are several aspects that determine employee job satisfaction, namely: the attitude towards work, compensation and rewards, supervision, management style, and relationships with colleagues (Pettinger, 2013; Kreitner & Kinicki, 2014; Davis & Newstrom, 2014; Kirkpatrick & Levis, 2015).

The response to work is positive if the employee feels happy and satisfied with the job and the implementation of working at home, on the contrary if it is negative the employee does not feel happy and satisfied. Likewise, the compensation and rewards received, employees will feel happy and satisfied if they are considered adequate, and vice versa. In the context of WFH, basically limiting the activities of employees, because there may be a previously planned budget that has been removed for the purpose of dealing with the Covid-19 pandemic. Whereas the implementation of activities has a direct meaning as an additional reward for state civil servants, because they consider the compensation received every month to be relatively low and insufficient to meet their daily needs. Strictly speaking, compensation and rewards are one of the elements that influence employee job satisfaction attitudes towards work to meet their needs (Kreitner & Kinicki, 2014).

Supervision relates to the supervisory function of employees in carrying out their work from home. Employees will be positive, happy, and satisfied if the supervision received is given a fair and favorable award, otherwise if it is judged to be unfair and not as expected. Likewise, the leadership management style will be responded with pleasure and satisfaction if it manifests a fair attitude in the division of labor, transparency, democracy, respect for achievement, and others (Dahl, 2003; Cooper, 2011; Colquitt & Lephine, 2003; Wesson, 2015; Anderson, 2016; Claudia, 2020). Finally, a happy and satisfied attitude will also appear if employees get support from co-workers, reciprocal, mutually beneficial, such as: motivating each other, providing advice, providing needed data and information, and others (Wiyono & Haryadi, 2014; Riyadi, 2014; Sarsono, 2019; Lusianingrum, 2014; Afifatusholihah & Fadhilah, 2020).

Mental emotional conditions, psychological well-being, job performance, and job satisfaction are variables that affect the job expectations of State Civil Servants (SCA) who are working from home. It is not yet known how long WFH will be in effect, because the Covid-19 pandemic is considered not to have subsided. Although recently it has shown a downward trend, it is still feared that it will increase again.

Although the State Civil Apparatus (SCA) carries out work from home, it does not mean that it does not support expectations for its work. Job expectations are the desire to get something from work. Various studies show that there is an effect of expectations on behavior and performance (Greenhaus, Saidel & Marinis, 1983; Asnawi & Bachroni, 1999; Ratnasari, 2015). The existence of work expectations will bring employees to work better and harder (Lee, 2007; Chiang & Jang, 2008; Robbins & Judge, 2017; Murphy, 2020; Tracy, 2020). Better effort will result in performance, and performance is related to the expectation of getting a reward as an attraction for fulfilling the personal needs of employees. Job expectations are an understanding of the achievement of employee goals and the relationship between effort and performance, between performance and rewards (Robbins & Judge, 2017).

Various kinds of employee job expectations, both material and non-material. In this study, job expectations are limited to 3 (three) indicators, namely: compensation and rewards, work career, and co-workers (Findlay, Kalleberg & Warhust, 2013). Even in the Covid-19 pandemic situation, working from home must be able to provide challenging work, be able to arouse a sense of interest, creativity, independence, achievement-oriented, and achieve good performance of the State Civil Apparatus (SCA) Good performance is expected to work careers (Jalagat, 2016; Diamantidis & Chatzoglou, 2018). Another work expectation is to increase trust from the leadership and support from colleagues to achieve optimal goals and work results (Xu et al., 2017; Jungart et al., 2018).

Based on the description above, the following theoretical framework of the study was developed (figure 1).

Methodology

This paper is part of the results of research on the impact of WFH on the work patterns of civil servants. This paper is a study of employees who work in various government agencies in the capital city of DKI Jakarta (ministry, ministry-level government agencies, universities, and schools) with various job statuses (administrative staff, lecturers, teachers, researchers, and others). This study is not aimed at civil servants working at the provincial and regional levels.

Data was collected by distributing questionnaires to civil servants from ministries, government agencies, universities, and schools. The questionnaire was developed based on the variables and indicators used in the study. The sample of respondents was obtained randomly, namely the state civil apparatus who are carrying out Work From Home (WFH). The distribution of the questionnaire was also assisted by co-authors from various government institutions at the central level with the status of administrative staff, researchers, lecturers, and teachers. Before the questionnaire was applied, a number of civil servants were tested to determine the level of validity and reliability of the questions asked. Measurement of validity and reliability was carried out using the Pearson and Cronbach Alpha product moment criteria (Mulyani et al., 2021; Sugiyono, 2017).

Data analysis was carried out using Structural Equation Modeling (SEM) with the help of the LISREL 8.70 program. The results presented consist of validity and reliability indicators, godness fit model as a condition for analyzing the impact between variables and the contribution of indicators to each variable used (Joreskog & Sorborn, 1993; Ferdinand, 2002; Hair et al., 2010; Haryono & Wardoyo, 2017; Sarjono & Yulainita, 2019; Yohana, Dania & Prihandono, 2021; Zakso et al., 2021; Sariwulan et al., 2021).

Results and Discussion

Characteristics of Respondents

From the questionnaires, 184 civil servants gave answers, consisting of: 63 administrative staff from 4 (four) ministries, 35 researchers, 27 state university lecturers, 25 elementary school teachers, and 28 junior high and high school teachers. A total of 102 respondents were male and 82 female. The lowest sample age was 25 years and the highest was 65 years, with the largest being at the age of 31-55 years as many as 133 people.

As many as 13.6% of the total respondents have an educational background of SMA/SMK graduates, 45.1% of people with undergraduate education from various study programs, 29.3% master's education, and 12.0% are doctoral. Most of the respondents have worked more than 10 years, and those aged >56 years have worked more than 30 years. State civil servants earn income from basic salaries, performance allowances, and functional allowances for employees who have certain functional positions, such as: lecturers, researchers, engineers, and others. In this study, the lowest level of fixed income per month is around Rp. 6 million were obtained by employees with high school education, administrative staff status, and no functional position status. Those with bachelor's, master's, and doctoral education, and occupy certain functional positions, earn a fixed income of more than Rp. 10 million, with the highest around Rp. 27 million sourced from basic salary, functional position allowance, and performance allowance. In addition, there are also non-fixed sources of income that come from incentives for activities inside and outside the office, official trips to the field, and others.

Validity-Reability Indicators

Test the validity and reliability of the study indicators using Confirmatory Factor Analysis (CFA) with the aim of measuring that the indicators and variables really form the latent variable by comparing the loading factor of at least 0.5. If it is greater than 0.5 then the indicator is valid (Joreskog & Sorborn, 1993; Ferdinand, 2002; Hair et al., 2010; Haryono & Wardoyo, 2017; Sarjono & Yulianita, 2019; Yohana, Dania & Prihandono, 2021; Zakso & Agung, 2021; Sariwulan et al., 2021). Reliability test to find out how well the measuring instrument can produce relatively the same results if repeated measurements are made on the same object. The reliability value was measured by Construct Reliability (CR) and Variance Extract (VE). It is said to be reliable if CR>0.70 and VE>0.50. Below is shown the results of the validity and reliability of the indicators of each of the variables studied (table 1).

Table 1 Validity and Reliability Indicators
Variables	Indicators	SLF	T-Count	CR	VE	Conclusion
WorkFrom Home(WFH)	x1=Work management	0.73	39.31	0.88791	0.55468	Valid&Reliabel
	x2 =Work environment	0.83	44.25
	x3 =Digital technology and internet	0.79	42.56
	x4 =Provision data and Information	0.83	44.25
	x5 =Colleagues relationships	0.73	39.26
MentalEmotionalConditions (MEC)	x6 =Emotional symptoms	0.73	20.16	0.91112	0.58288	Valid&Reliabel
	x7 =Behavioral problems	0.86	22.16
	x8 =Hyperactivity/inattention	0.77	21.08
	x9 =Peer relationship problems	0.84	21.84
	x10=Prosocial behavior	0.85	21.84
PsychologicalWell-Being(PWB)	x11=Autonomy	0.87	32.90	0.93093	0.69338	Valid&Reliabel
	x12=Environmental mastery	0.78	26.53
	x13=Personal growth	0.88	28.17
	x14=Positive relationships	0.87	28.10
	x15=Life goals	0.88	27.84
	x16=Self-acceptance	0.70	25.08
JobPerformance(JPr)	x17=Work knowledge	0.73	40.76	0.94093	0.72855	Valid&Reliabel
	x18=Creativity	0.72	20.55
	x19=Dependence	0.87	22.56
	x20=Work quality	0.90	22.89
	x21=Cooperation	0.93	23.21
	x22=Integrity	0.93	23.27
JobSatisfaction(JSa)	x23=Work attitudes	0.88	25.68	0.90837	0.58548	Valid&Reliabel
	x24=Compensation and rewards	0.91	28.69
	x25=Leadership	0.92	27.66
	x26=Supervision	0.81	27.38
	x27=Coworker relations	0.82	27.58
JobExpectation(JEx)	x28=Increased revenue	0.88	23.25	0.89214	0.73406	Valid&Reliabel
	x29=Work carrier	0.85	23.40
	x30=Working relationship development	0.81	29.54

* Source: The Impact of Work from Home (WFH) in the Covid-19 Pandemic Period on Emotional Mental Conditions, Psychological Well-Being, Job Performance, Job Satisfaction, and Employee Job Expectations: The Case of the State Civil Apparatus

Goodness of Fit Model (GOF Model)

Based on the results of the validity-reliability tests above, the Goodness of Fit Model (GOF Model) test was carried out as a test of the fit between the frequency of expectations and observations. Through the test results, it can be seen whether the indicators in whole or in part indicate that the model is fit or good, and is able to answer the theory built. In modeling the system, the suitability test is very important, because the structural model analysis in SEM starts based on the Goodness-of-Fit (GFI) statistical indicator. In the Goodness of Fit Model test, the required limit values are RMR, RMSEA, GFI, AGFI, CFI, NFI, NNFI, IFI, and RFI. If it meets the boundary value requirements, it can be said that the built model is good or fit (Joreskog & Sorborn, 1993; Ferdinand, 2002; Hair et al., 2010; Haryono & Wardoyo, 2017; Sarjono & Yulianita, 2019; Yohana, Dania & Prihandono, 2021; Zakso & Agung, 2021; Sariwulan et al., 2021).

The LISREL output in this study resulted in an RMR (Root Mean Square Residual) value of 0.0187 0,05 atau 0,1, RMSEA (Root Mean square Error of Approximation) 0.0231 0.08, GFI (Goodness of Fit) 0,98 0.90, AGFI (Adjusted Goodness of Fit Index) 0.97 0.90, CFI (Comparative Fit Index) 0.96 0.90, NFI (Normed Fit Index) 0.96 0.90, NNFI (Non-Normed Fit Index) 0.97 0.90, IFI (Incremental Fit Index) ), and RFI (Relative Fit Index) 0.95 0.90. The test model can be said to be fit or good. The study data is able to answer the theory that is built.

Impact Analysis

Test the validity-reliability of the study indicators and the GOF Model, then become the basis for the analysis of structural relationships between variables. Analysis of structural relationships to determine the magnitude of the impact of WFH on Mental Emotional Conditions (MEC), Psychological Well-Being (PWB), Job Performance (JPr), and Job Satisfaction (JSa), then Job Expectations (JEx) of employees. In addition, through this relationship analysis, we also want to know the contribution of indicators to variables, as shown in figure 2.

Figure 2 shows that the effect of WFH on Mental Emotional Conditions (MEC), Psychological Well-Being (PWB), Job Performance (JPr), and Job Satisfaction (JSa) does not show a significant difference, although its effect on Job Performance (JPr) has the highest coefficient value. It also shows that WFH has the most impact on employee performance, especially when faced with limited work, not as much as working in the office. On the other hand, it can be seen that the MEC and PWB variables have the highest coefficient of influence on employee job expectations (JEx). Table 2 below shows the results of testing the hypotheses between the variables studied.

Table 2 Hypothesis Testing
Hypothesis		SLF	T-count	Conclusion
H1	WFH à MEC	0.98	25.64	Significantly Positive
H2	WFH à PWB	0.96	21.45	Significantly Positive
H3	WFH à JPr	0.99	25.42	Significantly Positive
H4	WFH à JSa	0.95	21.11	Significantly Positive
H5	MEC à JEx	0.87	24.73	Significantly Positive
H6	PWB à JEx	0.85	21.39	Significantly Positive
H7	JPr à JEx	0.72	17.60	Significantly Positive
H8	JSa à JEx	0.68	11.71	Significantly Positive

* Source: The Impact of Work from Home (WFH) in the Covid-19 Pandemic Period on Emotional Mental Conditions, Psychological Well-Being, Job Performance, Job Satisfaction, and Employee Job Expectations: The Case of the State Civil Apparatus

Discussion

In the WFH variable, five indicators are used, namely: work management (x1), work environment (x2), digital and internet technology (x3), provision of data and information (x4), and co-worker relations (x5) (Seva, Tejero & Fedrian-Camacho, 2021; Colletta, 2021; Tuwinanto & Rahadi, 2021; Gibbs, Mengel, & Siemroth, 2021; Weinstein & Ryan, 2010). Figure 2 shows that the indicators of the work environment and the availability of digital and internet technology provide the highest contribution to the WFH variable of 0.83, followed by the indicator of providing data and information of 0.79, and indicators of work management and relationships with coworkers at 0.73 (Mungkasa, 2020; Marifah, 2020; Gibbs, Mengel & Siemroth, 2021).

The results show that the smooth implementation of WFH is largely determined by the feasibility of the work environment at home and the availability of digital technology and a strong internet network, attending online meetings, and others. Many employees say that working from home is faced with an uncomfortable workspace, interference from family members or other parties, and causes stress for employees (Seva, Tejero & Fedrian-Camacho, 2021; Colletta, 2021; Tuwinanto & Rahadi, 2021). Employees are also often hampered in obtaining data and information to complete tasks/jobs, as well as having difficulty communicating and obtaining the necessary information from the leadership. Working relationships with colleagues also do not run smoothly, especially to get data and information support, because it must be done remotely via telephone lines, gadgets, emails, and the like which are not as free as working in the office (Mungkasa, 2020; Marifah, 2020; Gibbs, Mengel & Siemroth, 2021).

Figure 2 shows that WFH has an impact on emotional mental conditioning. There are five indicators used in this emotional mental condition (MEC) variable, namely: emotional symptoms (x6), behavioral problems (x7), hyperactivity/inattention (x8), peer relationship problems (x9), and prosocial behavior (x10). ). The behavioral problem indicator gave the highest contribution to the MEC variable at 0.86, followed by prosocial behavior at 0.85, relationship problems with peers in the office at 0.84, hyperactivity/inattention at 0.77, and emotional symptoms at 0. 73.

The impact of WFH on mental and emotional conditions is prominent in aspects of work behavior that are less productive, less responsible, erratic working hours, not being able to work well together, less quality-oriented, and others, similar to what was stated by Topchik (2000); Griffith (2003). Another indicator that is influenced by WFH is prosocial behavior, namely the disruption of employees' prosocial behavior to benefit others (Caprara & Steca, 2007; Marbun & Setiawan, 2017). Prosocial behavior that is carried out intentionally to give positive consequences for individuals or groups, becomes inhibited. So far, employees feel they have an attachment to other people in the work environment, so they need to build good relationships with co-workers in order to create feelings of satisfaction, usefulness, pride, mutual acceptance and giving, and so on (Weinstein & Ryan, 2010; Megawati & Herdiyanto, 2016). However, through WFH, the relationship with co-workers was disturbed due to limited interaction and communication (Abubakar et al., 2021).

Another indicator is hyperactivity/inattention. Working online makes employees feel less cared for. If given a job that is not in accordance with their abilities, they tend not to follow directions, lack of responsibility, low quality of work, irregular working hours, lazy, lack of confidence, lack of creativity, lack of guidance and assistance from the leadership, and others. This has an impact on emotional symptoms related to the ability to regulate, control, and use emotions as a basis for developing reasoning and self-awareness (Salovey & Mayer, 1990; Mestre et al., 2006). WFH brings about positive or negative changes in the mood and emotions of employees, depending on the nature of the job. WFH will bring a positive and cheerful mood, if it manifests a work fit, motivating and guiding leadership, paying attention to online needs facilities, appreciation for work, and so on. Jobs that are considered inappropriate can lead to negative moods, not getting attention, not meeting online needs, and so on. A bad mood tends to reflect irritability, aggressiveness, sadness, disappointment, low self-esteem, and an inability to take responsibility for work. Therefore, the implementation of WFH needs to develop a good or positive mood towards employees, among others by creating two-way communication and dialogue between leaders and staff, developing self-awareness, generating active attitudes, and others (Mestre et al., 2006; Zhang et al., 2021).

The impact of WFH on psychological well-being is prominent in the indicators of environmental mastery and positive relationship building with a value contribution of 0.88, followed by personal growth 0.87, autonomy 0.78, self-acceptance 0.73, and life goals 0.70. Environmental control indicators relate to employees' ability to regulate, control, and utilize the surrounding environment to support their WFH activities. Employees who have the ability to master the environment will be creative and develop well to support their work, on the contrary will experience difficulties, be disturbed, and are less able to use it properly to support their activities. (Danladi, 2021; Zhang et al., 2021).

Positive relationships relate to employees' ability to build good relationships with other people (leaders, co-workers, and people around the house). Building this relationship is reflected through self-disclosure, a sense of closeness, communicativeness, trust, empathy, concern, and based on mutual give and take. On the other hand, a negative relationship will reflect a closed attitude, isolation, disharmony and compromise (Ryff & Keyes, 2007; Kabir & Helal, 2021). Fostering positive relationships is one aspect that can support personal growth, namely the ability to develop one's potential. An attitude of openness to other people and new experiences, trust from others, attention, and others will encourage self-actualization and sustainable development of self-potential, and vice versa. The development of this potential will also reflect the attitude of autonomy and the ability to plan and regulate behavior, independence, self-evaluation, and making decisions for the good of life. On the other hand, employees who are not independent will depend on others, are easily influenced by others, lack self-confidence, are unable to accept and know their potential, lack self-evaluation, and are less able to plan life goals properly.

WFH has an impact on employee performance. The indicators of cooperation and integrity have the highest influence on the performance of this work with a recorded value contribution of 0.93, followed by work quality 0.90, dependability 0.87, work knowledge 0.73, and creativity 0.72. This means that the application of working from home can interfere with employees in working with colleagues, responsibilities, and quality of work. In particular, the high and low quality of work obtained by employees in the implementation of WFH is very dependent on the comfort and support of colleagues, especially in obtaining the necessary data and information, work assistance, and realizing integrity, independence, developing work skills, and developing creativity (Nugroho & Suswanta, 2020; Tuwinanto & Rahadi, 2021; Gibbs, 2021).

WFH also has an impact on employee job satisfaction or dissatisfaction. The leadership indicator occupies the highest contribution to the job satisfaction variable (x25) with a coefficient of 0.92, followed by compensation and reward indicators (x24) of 0.91, work attitude (x23) of 0.88, co-worker relations of 0.82, and supervision of 0.8. These results indicate that leadership factors greatly determine employee job satisfaction, especially in treating employees fairly, distributing work evenly, providing appropriate jobs, acting as motivators and facilitators, guiding, appreciating staff performance, and so on (Sutisna, 2020; Ramadhan & Firmansyah, 2021). ). Another thing related to the impact on job satisfaction is the indicators of compensation and rewards given by the leadership, especially on timeliness of work, responsibilities, and work performance. Various studies do support the strong influence between compensation and rewards on employee job satisfaction (Rahayu & Riena, 2017; Mabaso & Dlamini, 2018; Hakim, 2020). On the other hand, work attitudes, work relations, and supervision are indicators that have little effect on employee job satisfaction, although they cannot be ignored.

Furthermore, emotional mental conditions, psychological well-being, job performance, and job satisfaction have a positive effect on employee job expectations. This study found that mental emotional condition had the highest influence coefficient of 0.87, followed by psychological well-being of 0.85 on employee job expectations, job performance of 0.72, and job satisfaction of 0.68. It also shows that WFH which is able to minimize behavioral problems, emotional symptoms, impaired achievement of personal growth, life goals, maintain relationships with coworkers, etc., has a more dominant positive influence on employee job expectations. These two conditions also greatly determine employee performance and job satisfaction, which will directly or indirectly affect their job expectations.

How do emotional mental states, psychological well-being, job performance, and job satisfaction affect employee job expectations? This study also found that the highest influence of the four variables on job expectations was directed at the indicators of increasing income with a coefficient of 0.88, career advancement 0.85, and increasing work relations 0.81. The implication is that the implementation of WHF is expected to be able to minimize the negative impact on the four variables, so that employees can maintain productivity and work quality, but also provide hope in increasing employee income and careers.

Conclusion

The impact of the Covid-19 pandemic has had an impact on various aspects, including emotional mental conditions, psychological well-being, work performance, and job satisfaction, which in turn affects employee work expectations. The implication is that these four aspects must receive attention in the implementation of WFH, so that employees can still maintain routines, responsibilities, work quality and productivity. The implementation of WFH itself needs to be supported by a conducive work environment at home, support for the availability of the necessary data and information, as well as the availability of digital technology and a strong internet network.

In line with that, to avoid the emergence of negative impacts of WFH, it is necessary to pay attention to the indicators that make the strongest contribution of each variable, namely: the emergence of behavioral problems and serious emotional symptoms (MEC), maintaining personal growth and life goals (PWB), fostering cooperation and integrity (JPr), and developing leadership attitudes by applying compensation and rewards (JSa). Emphasis on these indicators will affect the maintenance of employee job expectations, especially in the certainty of increasing income and careers.

Acknowledgement

Author Suyono Thamrin is a major contributor in the preparation of this paper, with another writer as a contributor member.

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Received: 08- Dec -2021, Manuscript No. jmids-21-9115; Editor assigned: 11- Dec -2021, PreQC No. jmids-21-9115 (PQ); Reviewed: 20-Dec-2021, QC No. jmids-21-9115; Revised: 25-Dec-2021, Manuscript No. jmids-21-9115 (R); Published: 12-Jan-2022.