Influence Of Emotional Intelligence, Self-efficiency, Working Spirit, Work Satisfaction On Employee Work Achievement In Batam University

This study, researchers used respondent data, such as gender, age and duration of work of respondents to be able to provide information about the characteristics of respondents. The study population was employees at Batam University, which consisted of dosons and employees. The sample is determined by the number of sample members (sample size) of 60 people by proportional random sampling technique. 20 lecturers and 40 Batam university employees. This research is the result of a field study to obtain questionnaire answer data that measures five main variables in this study, namely Emotional Intelligence, Self-Efficiency, Working Spirit, Work Satisfaction to work achievement of Batam University employees. The instrument was developed based on theoretical studies, then defined in conceptual definitions, operational definitions, and developed through lattice instruments and technical techniques. Knitted data analysis uses descriptive statistics and statistical analysis to test the significance of path coefficients, descriptive statistics to present data in the form of frequency distribution tables, histograms, and the number of statistics such as media, modes, averages, variants, and foreign standards. exchange. Statistical tests are used to test the significance of path coefficients using Partial Least Square (PLS) which is a Multivariate Analysis in the second generation using structural equation modeling (SEM). PLS can be used for a small number of samples, and of course with a large number of samples will be better able to improve the accuracy of estimates. PLS does not require the assumption that data distribution must be normal or not. The construct form can use a reflective or formative model in which from the results of statistical analysis, the relationship between variables formulated in the formulation of a problem as many as 7 pieces obtained significant results. Keywords​: Emotional Intelligence, Self-Efficiency, Working Spirit, Work Satisfaction, Work Achievement Copyright © 2021 IAIC All rights reserved.


Introduction
Each organization in carrying out its duties and functions is largely determined by the quality of its human resources and supporting infrastructure. Human resources and equipment are elements in moving the wheels of the organization, as well as internal factors that influence the progress of the organization. To achieve organizational goals there are many factors that support, one of which is emotional intelligence. Emotional intelligence is a person's ability to manage emotions, understand the emotions of self and others, withstand all forms of pressure, have an attitude of optimism, and the ability or ability to relate to others. Emotional intelligence is the result of learning that is based on emotional intelligence and therefore produces prominent performance at work [1].
Employees are very important to have emotional intelligence in order to produce maximum performance. self-efficacy is self-perception of how well the self can function in certain situations. Self-efficacy relates to self-confidence has the ability to take the expected action. Self efficacy is a person's belief in his ability to control events in his life. Self efficacy is not just a rigid estimation of someone's actions in the future. A person's beliefs about his abilities act as a set of determinants and how someone behaves, how they think and how they react emotionally to deal with a particular problem. So self-efficacy arises from cognitive judgments about abilities possessed by someone. A person's decision to determine his life activities and the choice to enter a certain social environment, partly determined by the consideration of his personal efficacy [2]. People tend to avoid tasks and situations that they believe are beyond the reach of their abilities and they should do it if they believe they are capable of doing it. So self-efficacy affects the choice of activities in certain environments. Work spirit is the ability to encourage, guide, direct, and move employees to work, participate in achieving the goals set. Work spirit is the ability or technique to make a group of subordinates in a formal organization or followers or sympathizers in informal organizations follow or obey everything they want, make subordinates enthusiastic and follow leaders and willing to sacrifice for them. Job satisfaction is a pleasant or unpleasant emotional state in which employees view their work. Job satisfaction reflects one's feelings about their work [3]. This is evident in the attitude of employees towards work and everything that is encountered in their morale. Job satisfaction can be interpreted as an employee attitude that arises based on an assessment of the situation in which they work. Job satisfaction is basically something that is individual, each individual has different levels of satisfaction in accordance with the value system that applies to him. The higher the assessment of activities felt according to individual desires. With job satisfaction possessed by employees, it can encourage in improving employee performance, work performance is a result of work achieved by a person in carrying out tasks assigned to him based on skill, experience, and sincerity and timeliness. Work performance is influenced by three factors namely the ability and interest of a worker, the ability and acceptance of the delegation's explanation of duties and roles, and the motivation level of a worker [4].
Formulation of the problem 1. Does Emotional Intelligence directly determine Job Satisfaction? 2. Does Self Efficacy directly determine Job Satisfaction? 3. Does Working Spirit directly determine Job Satisfaction? 4. Does Emotional Intelligence directly determine Work Achievement? 5. Does Self Efficacy directly determine Work Achievement? 6. Does Working Spirit directly determine Work Achievement? 7. Does Job Satisfaction directly determine Work Achievement?
he theoretical framework of this study was developed from the synthesis of theories based on facts, observations and literature reviews, therefore this theoretical framework contains the relationship or influence between the variables involved in research based on supporting theories, and clearly explains the interrelationships between the intertwined variables, other than that it can be used as a basis for answering problems and logic flow relationships between interrelated variables so that it will be very relevant to the problem studied as follows. According to Daniel Goleman (2009:152) revealed that emotional intelligence refers to the ability to recognize our feelings and the feelings of others, the ability to motivate ourselves, and the ability to manage emotions well in ourselves and in relationships with others [5].
According to Schunk (2009:3) says that self efficacy is one's belief in his ability to control events in his life. According to Mulyasa (2009:107) stated that work spirit is an activity to influence people who are directed in achieving organizational goals. According to Yuli (2010:196) defines that job satisfaction is an employee's attitude that arises based on an assessment of the situation in which they work. According to Hasibuan (2011:105), work performance is a result of work achieved by a person in carrying out tasks assigned to him based on skill, experience, and sincerity and timeliness [6].

Research Method
In this study, researchers used respondent data, such as gender, age and length of work of the respondent to provide information about the characteristics of the respondents. Where from the questionnaire questionnaire distributed as many as 60. The discussion in this chapter is the result of field studies to obtain questionnaire answers that measure five main variables in this study, namely Emotional Intelligence, Self-Efficacy, Working Spirit, Work Satisfaction and work achievement. Data analysis uses parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument testing, normality testing, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Path [7] IAIC J. IICS This study uses path analysis to examine patterns of relationships that reveal the effect of a variable or set of variables on other variables, both directly and indirectly. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To determine the direct and indirect effects between variables, this can be seen from the calculation of the path coefficient, while to determine significance. The study population was employees at Batam University, which consisted of lecturers and Batam University employees. The sample is determined by the number of sample members (sample size) of 60 people by proportional random sampling technique. 20 lecturers and 40 employees [8].

Results and Analysis 3.1. Internal Consistency Analysis
Internal consistency analysis is a form of reliability used to assess the consistency of results across items on the same test. Internal consistency testing uses composite reliability values with the criteria of a variable said to be reliable if the composite reliability value> 0.600 [9].

Convergent Validity
Convergent validity is used to see the extent to which a measurement is positively correlated with alternative measurements of the same construct. To see an indicator of a construct variable is valid or not, it is seen from the outer loading value. If the outer loading value is greater than (0.4) then an indicator is valid [11]. Based on the above table, it can be seen that the outer loading value for variables X1, X2, X3, X4, Y where the value of all item items in the 5 variables tested is greater than 0.4, then all items developed for all variables are declared valid, meaning that the measurement is positively correlated with alternative measurements of the same construct thus the indicators of all construct variables are valid [12].

Validity Of Diskriminan
Discriminant validity aims to assess an indicator of a construct variable is valid or not, namely by looking at the Heterotrait -Monotrait Ratio Of Correlation (HTMT) <0.90, then the variable has a good discriminant validity (valid) [13]. Table 3. Validity of Diskriminan. Source Data Processing (2020) Based on the above table, the correlation results obtained variables X1 with X2, X3, X4, Y and X3 with X2, X4 with X2, Y with X2 and X4 with X3, Y with X3 and Y with X4 have a correlation value <0.900, thus the value the correlation of all variables is declared valid. Analysis of structural models or (inner models) aims to test the research hypothesis. The part that needs to be analyzed in the structural model is the coefficient of determination (R Square) by testing the hypothesis. Collinearity testing is to prove the correlation between latent / construct variables is strong or not. If there is a strong correlation it means that the model contains problems if viewed from a methodological point of view, because it has an impact on the estimation of statistical significance. This problem is called colinearity. The value used to analyze it is by looking at the value of Variance Inflation Factor (VIF). (Hair, Hult, Ringle, & Sarstedt, 2014; Garson, 2016). If the VIF value is greater than 5.00 then it means there is a colinearity problem, and in contrast there is no colinearity problem if the VIF value <5.00 [14].

ISSN: 2528-2417
■ 20 Table 4. Collinearity Source Data Processing (2020) From the above data it can be described as follows:The VIF value for the correlation of X1 with Y, X2 with Y, X3 with Y, X4 with Y is <5.00 (there is no colinearity problem). Therefore, from the data above and the development of structural models in this case there is no problem. colinearity. In this test there are two stages, namely testing the direct influence hypothesis and testing the indirect effect hypothesis. The coefficients of the hypothesis testing path are in the figure below:Test the significance of the structural coefficient of the path model (Structural Model Path Coefficient). This test is to determine the path coefficient of the structural model, the aim is to test the significance of all relationships or hypothesis testing [15].

Figure 2. Hypothesis Testing
Direct influence hypothesis testing aims to prove the hypotheses of the influence of a variable on other variables directly (without intermediaries). If the value of the path coefficient is positive indicates that an increase in the value of a variable is followed by an increase in the value of another variable. If the value of the path coefficient is negative indicates that an increase in a variable is followed by an decrease in the value of other variables.If the probability value (P-Value) <Alpha (0.05) then Ho is rejected (the effect of a variable with other variables is significant). If the value of probability (P-Value)> Alpha (0.05) then Ho is rejected (the effect of a variable with other variables is not significant) [16].

ISSN: 2528-2417
■ 21 Table 5. Hypothesis of Direct Effect. Source Data Processing (2020) 1. The direct effect of variable X1 on variable X4 has a path coefficient of 2.191 (positive), then an increase in the value of variable X1 will be followed by an increase in variable X4. The effect of the variable X1 on X4 has a P-Values value of 0.032<0.05, so it can be stated that the influence between X1 on X4 is significant. 2. The direct effect of variable X1 on variable Y has a path coefficient of 2.781 (positive), then an increase in the value of variable X2 will be followed by an increase in variable Y. The effect of variable X1 on Y has a P-Values value of 0.009<0.05, so it can be stated that the influence between X1 on Y is significant. 3. The direct effect of variable X2 on variable X4 has a path coefficient of 3.289 (positive), then an increase in the value of variable X2 will be followed by an increase in variable X4. The effect of variable X2 on X4 has a P-Values value of 0.002<0.05, so it can be stated that the influence between X2 on X4 is significant. 4. The direct effect of variable X2 on variable Y has a path coefficient of 2.536 (positive), then an increase in the value of variable X2 will be followed by an increase in variable Y. The influence of variable X2 to Y has a P-Values value of 0.014<0.05, so it can be stated that the influence between X2 to Y is significant. 5. The direct effect of variable X3 on variable X4 has a path coefficient of 2.918 (positive), then an increase in the value of variable X3 will be followed by an increase in variable X4. The effect of variable X3 on X4 has a P-Values value of 0.005<0.05, so it can be stated that the influence between X3 to X4 is significant. 6. The direct effect of variable X3 on variable Y has a path coefficient of 2.858 (positive), then an increase in the value of variable X3 will be followed by an increase in variable Y. The effect of variable X3 on Y has a P-Values value of 0.006<0.05, so it can be stated that the influence between X3 on Y is significant. 7. The direct effect of variable X4 on variable Y has a path coefficient of 2.408 (positive), then an increase in the value of variable X4 will be followed by an increase in variable Y. The effect of variable X4 on Y has a P-Values value of 0.019<0.05, so it can be stated that the influence between X4 on Y is significant.
Testing the hypothesis of indirect effects aims to prove the hypotheses of the influence of a variable on other variables indirectly (through intermediaries). If the value of the indirect effect coefficient> direct effect coefficient, then the intervening variable is mediating the relationship between one variable with another variable. Conversely, if the value of the indirect effect korfisien <coefficient of direct effect, then the intervening variable does not mediate the relationship between one variable with another variable [17]. The coefficient of determination (R Square) aims to evaluate the accuracy of the predictions of a variable. In other words, to evaluate how the variation of the value of the dependent variable is influenced by the variation of the value of the independent variable in a path model [18,19].

Conclusion
The findings of data analysis in the discussion and testing of hypotheses, it can be concluded that the direct effect between variables measured in the full research model according to the SEM-PLS has a significant positive path coefficient, where theoretically that the employee performance model will involve emotional intelligence, self efficacy, work enthusiasm in developing the concept of study substance creates job satisfaction to produce optimal employee work performance, in addition there are a number of other variables not examined that can be developed including, work environment, responsibility, competence, Personality, etc., related to the development of the substance of achievement studies employee work then this research study involves emotional intelligence, self-efficacy, work morale, job satisfaction in studies of improving employee performance. Theoretically this is because these three variables will increase job satisfaction and job satisfaction directly affect employee performance and produce recommendations for improvement in an effort to improve the role of the organization so the need for learning outcomes based on emotional intelligence and therefore will produce prominent performance in work and increasing employee confidence in facing or completing work and supported by very high employee morale will create employee job satisfaction which will lead to optimal work performance