Effect of Work Orientation, Training, and Career Development on Performance of Education Staff at
Narotama University
Hary Adi Laksono, Elok Damayanti, Joko Suyono
Departement of Law, Economics and Education, Management Program Study Narotama University
haryadilaksono@gmail.com, elok.damayanti@narotama.ac.id, joko.suyono@narotama.ac.id
Abstract
The COVID-19 pandemic has become a crisis in all sectors, one of which is the education sector in terms of Human Resources. This study aims to determine the effect of work orientation, training, and career development on the performance of Education Staff at Narotama University. This study uses a quantitative approach. The population in this study are 80 Narotama University Education Staff. The sampling technique used census sampling. Data collection is done using Google Forms. The data analysis technique used is the R square test, F test and t test at a significant level of alpha 0.05. The results of this study are work orientation, training, and career development simultaneously have a significant effect on the performance of Narotama University Education staff.
While the results of partial hypothesis testing indicate that work orientation has a significant effect on the performance of education staff. Training has a significant effect on the performance of Education Staff. Career development has a significant effect on the performance of Education Staff.
Keywords
Career Development, Employee Performance, Training, Work Orientation.
1. Introduction
Currently, the COVID-19 pandemic has become a global health crisis. These conditions make countries choose to close universities, schools, and companies or other agencies to inhibit, break the chain, and stop the spread of the corona virus. In this case, the Government of the Republic of Indonesia, the Directorate General of Higher Education continues to be committed to providing access to education services. Several policy adjustments were made by the government, related agencies, and universities in dealing with the COVID-19 pandemic with the aim that students and teaching units get their rights in carrying out education properly and effectively.
Narotama University is a private university located on Arief Rachman Hakim St. Number 51, Surabaya.
The current phenomenon of performance at Narotama University, Educational Staff are still unable to implement policies during the COVID-19 pandemic to the fullest. Narotama University is 40 years old and has 5 Faculties and 12 Study Programs consisting of 4 Masters Study Programs and 8 Undergraduate Study Programs. Narotama University has 1,931 active students, 115 Lecturers, and 80 Education Staff (data per year 2021). The phenomenon that occurs is in the form of complaints from students regarding the policy of the learning system, and there are still several job desks for Education Staff that are deemed not optimal. For example, student complaints regarding the information and process of the Study Plan Card for courses that are not on time, the online lecture system that is carried out is not optimal, the student attendance system is not socialized and transparent, and some students are still confused about the regulations that explain the obligation to attend on campus but they need to go to campus for confirmation and clarification of each of their problems to the relevant unit.
The method of changing learning / lectures, which was originally face to face, is now online or online is something that must be done during the pandemic. On the other hand, the importance of the University in monitoring and evaluating the implementation of online lectures in order to be able to achieve quality lectures based on student satisfaction is always maintained. There are various factors that appear in the online lecture method, the main indications of which are technological, economic and responsibility factors.
Based on the above background, researchers are interested in conducting research with the title "Effect of Work Orientation, Training, and Career Development on the Performance of Education Staff at Narotama University".
1.1. Research Framework
Figure 1 Research Framework 1.2. Hypothesis
According to Kerlinger (1973) the hypothesis is a statement of the alleged relationship between two or more variables. The following is a description of the literature review which then mapped the following hypotheses:
H1 : Work orientation has a partial significant effect on performance of Narotama University Education Staff.
H2 : Training has a partial significant effect on the performance of Narotama University Education Staff.
H3 : Career development has a partial significant effect on performance if Narotama University Education Staff.
H4 : Work orientation, training, and career development have a significant effect simultaneously on performance of Narotama University Education Staff.
1.3. Literature Review
Orientation is an effort to help workers identify themselves well and be able to adapt to the circumstances or environment of the organization/company Nawawi (2008). Work orientation according to (Ingham, 1970) is a concept that forms the basis for a harmonious view of industrial relations in small companies, because work orientation is said to lead to independent selection (individuals) in the corporate sector to improve its performance.
According to Sedarmayanti (2012) orientation has the following objectives:
1. Introducing new employees to their scope of work and activities.
2. Provide information about the current policy.
3. To avoid the possibility of new employees facing chaos, exceeding the tasks or tasks assigned.
4. Provide opportunities for new employees to ask questions related to their work.
According to Rivai and Ella Sagala (2013) Training is a systematic process to change employee behavior to achieve organizational goals. Training will be related to the ability and expertise of employees in doing their current job in order to be successful in doing their job. Simamora in Priansa (2017) states that training has the following benefits:
1. Improve the quality and quantity of productivity.
2. Reducing the learning time required by employees to achieve accepted performance standards.
3. Creating a better attitude, loyalty, and cooperation, both between the organization and its employees, leaders and employees, as well as between employees of the organization.
4. Meet the requirements of existing HR planning requirements.
According to A.A. Anwar Prabu Mangkunegara (2017) career development is defined as employment activities that support employees in planning their future careers with the company so that the company and related employees can develop optimally.
According to Siagian (2015) there are factors that influence career development, including:
1. Fair treatment in career: Fair treatment can only be realized if the promotion criteria are based on objective and fair considerations and are widely known among employees.
2. Concern for immediate superiors: Employees generally want their manager's direct involvement in career planning. One concern is providing feedback to employees about their individual responsibilities so that they know what they are worthy of
3. Information about promotional opportunities: Employees generally expect to have access to information about promotional opportunities. This access is very important, especially if the available vacancies are filled
Work Orientation (X1) Training
(X2) Career Development
(X3)
Performance of Education Staff H1
H2 H3
H4
4. Interest to be promoted: The right approach in terms of increasing employee interest in career development is a flexible and proactive approach. In other words, career development interests are highly individualistic.
5. Level of satisfaction: In general, it can be said that everyone wants to progress, including in his career, but the actual measure of success used is different. This difference is a result of the level of satisfaction, and although in the latter context it does not necessarily mean success in achieving a high position in the organization.
According to Hasibuan (2002) performance is the result of work achieved by an individual in doing work for the skills, efforts, and opportunities given to him.
According to Wibowo (2016) the actual performance measurement can be done in several ways, namely:
1. Ensure that the requirements desired by the customer are met.
2. Strive for performance standards to generate comparisons 3. Keep a distance for everyone to monitor their performance level.
4. Determine the importance of quality issues and what needs to be prioritized.
5. Avoid the consequences of poor quality.
6. Consider the use of resources.
7. Optimize feedback to drive improvement efforts.
National Education Department Law No. 20 of 2003 explains that Education Staff are members of the community who are dedicated and assigned to support the implementation of education. Educational staff are tasked with carrying out administrative, security, and also implementing Standard Operating Procedure (SOP) properly.
2. Methodology
This type of research is quantitative. Researchers took a sample of all 80 Narotama University Education Staff, thus the sample used was a saturated sample. Data collection techniques in this study used interviews, observations, and questionnaires. The data in this study were processed using the Statistical Package for Social Science (SPSS) 20.0 for Windows program. Data analysis in this research is using multiple linear regression analysis.
The researcher used partial test (t test) and simultaneous test (F test) to test the hypothesis in this study.
The formulation of the hypothesis for the partial test (t statistical test) in this study is as follows:
1) Ho = independent variable (X) partially has no significant effect on the dependent variable (Y).
2) Ha = the independent variable (X) partially has a significant effect on the dependent variable (Y).
The formulation of the hypothesis for the simultaneous test (F statistic test) in this study is as follows:
1) Ho = independent variable (X) simultaneously has no significant effect on the dependent variable (Y).
2) Ha = independent variable (X) simultaneously has a significant effect on the dependent variable (Y).
The basis for decision making with a significance level of 0.05 is as follows:
1) If the value of sig. > 0.05 then the decision Ho is accepted and Ha is rejected, mean that the independent variable (X) simultaneously has no significant effect on the variable (Y).
2) If the value of sig. < 0.05 then the decision Ho is rejected and Ha is accepted, mean that the independent variable (X) simultaneously has a significant effect on the dependent variable (Y).
3. Result and Discussion
3.1. ResultBased on the results of respondents' answers to the questionnaire distributed, respondent data can be described based on gender, majority of respondents are male as many as 54 people or 67.5%. While the rest of the female respondents were 26 people or 32.5%. Based on age, majority of respondents are aged 31-40 years, a total of 36 people or 45%. While the rest aged 21-30 years were 24 people or 30%, ages 41-50 years were 19 people or 24%, and aged 51-60 years were 1 person or 1%. Based on last education, majority of respondents' last education was Bachelor's with 45 people or 56%, then the rest were 29 people or 36% of the last high school education, and for the last education Master's was 6 people or 8%.
1. Validity Test
According to Ghozali (2011) the validity test aims to determine whether or not the questionnaire used for data collection is valid. Validity test is conducted to see whether the items presented in the questionnaire can reveal what is being researched. Validity test is used as a measure of whether a questionnaire is valid or not. The questionnaire is said to be valid if the questionnaire can reveal something that will be measured by the questionnaire itself. Validity test using Pearson Correlation is a way of calculating the correlation with the value obtained in terms of questions or statements. The statement will be said to be valid if the significance level is below 0.05 (Ghozali, 2012).
Table 1 Validity Test
Based on table 1, the validity test above has a value of r count > r table = 0.2172. Therefore, the indicators in this study are declared "Valid".
2. Reliability Test
The reliability test is actually a questionnaire measuring instrument which is an indicator of a variable. A questionnaire is said to be reliable if a person's response to a statement is consistent from time to time. The questionnaire instrument is said to be feasible or reliable, if the value of Cronbach's alpha is greater than 0.06 and is said to be not feasible or reliable, if the Cronbach's alpha value is less than 0.06 (Ghozali, 2012).
Variable Statement Items
Corrected Item-Total Correlation
rtabel Description
Work Orientation
(X1)
X1.1 0.518 0.2172 Valid
X1.2 0.546 0.2172 Valid
X1.3 0.599 0.2172 Valid
X1.4 0.561 0.2172 Valid
X1.5 0.504 0.2172 Valid
X1.6 0.357 0.2172 Valid
X1.7 0.341 0.2172 Valid
Training (X2)
X2.1 0.687 0.2172 Valid
X2.2 0.687 0.2172 Valid
X2.3 0.710 0.2172 Valid
X2.4 0.763 0.2172 Valid
X2.5 0.785 0.2172 Valid
X2.6 0.455 0.2172 Valid
X2.7 0.536 0.2172 Valid
X2.8 0.314 0.2172 Valid
X2.9 0.410 0.2172 Valid
X2.10 0.352 0.2172 Valid
Career Development
(X3)
X3.1 0.672 0.2172 Valid
X3.2 0.614 0.2172 Valid
X3.3 0.653 0.2172 Valid
X3.4 0.678 0.2172 Valid
Performance of Education
Staff (Y)
Y.1 0.649 0.2172 Valid
Y.2 0.782 0.2172 Valid
Y.3 0.658 0.2172 Valid
Y.4 0.590 0.2172 Valid
Table 2 Reliability Test Item-Total Statistics Scale Mean if
Item Deleted
Scale Variance if Item Deleted
Corrected Item- Total Correlation
Cronbach's Alpha if Item Deleted
X1.1 95.60 130.091 0.520 0.813
X1.2 95.24 139.348 0.404 0.819
X1.3 95.06 133.705 0.574 0.812
X1.4 94.91 141.321 0.311 0.823
X1.5 95.01 140.494 0.350 0.821
X1.6 95.19 147.648 0.024 0.834
X1.7 95.09 144.359 0.164 0.828
X2.1 95.42 134.121 0.491 0.815
X2.2 95.70 134.061 0.464 0.816
X2.3 95.87 130.541 0.508 0.814
X2.4 95.61 130.266 0.518 0.813
X2.5 95.52 130.126 0.573 0.811
X2.6 95.12 139.427 0.367 0.821
X2.7 95.49 136.405 0.430 0.818
X2.8 94.85 146.357 0.131 0.828
X2.9 94.82 146.045 0.142 0.828
X2.10 94.89 145.164 0.209 0.826
X3.1 95.12 141.655 0.307 0.823
X3.2 95.01 144.747 0.177 0.827
X3.3 94.94 139.528 0.350 0.821
X3.4 95.11 139.747 0.279 0.825
Y.1 95.09 139.347 0.293 0.824
Y.2 95.22 139.164 0.408 0.819
Y.3 95.06 133.705 0.574 0.812
Y.4 94.92 141.513 0.304 0.823
Based on table 2 above, the reliability test results have a Cronbach's Alpha value > from 0.6. Thus, the indicators in this study are said to be” Reliable”.
3. Normality Test
According to Ghozali (2012) defines that the normality test has a purpose to test whether in the regression model, the independent variable and the dependent variable both have a normal data distribution or not. A good regression model is said to have a normal data distribution or close to normal. In this study, the normality test uses the Normal Plot of Regression Standardized Residual, that is, if the data spreads around the diagonal line of the graph, then follows the direction of the diagonal line, then the regression model fulfills the assumption of normality, but on the contrary if the data spreads away from the diagonal line, then follow or does not follow the direction of the diagonal line, the regression model can be said to not meet the assumption of normality. The graph is presented in Figure 2 below:
Figure 2 Normality Test Source: SPSS Output Data
Based on the graph above, it shows that all existing data is normally distributed, because all data spreads to form a straight diagonal line, the data meets the normal assumption or follows the normality line.
4. Multicollinearity Test
According to Ghozali (2005) multicollinearity is a condition in which the independent variable (independent) is correlated with other independent variables or the independent variable is a linear function of the other independent variables. A good regression model should have no correlation between independent variables.
The results of the multicollinearity test are presented in table 6 below:
Table 3 Multicollinearity Test Variable Collinearity Statistics
Description Tolerance VIF
Work Orientation (X1) 0.610 1.640 Free of multicollinearity Training (X2) 0.702 1.424 Free of multicollinearity Career Development (X3) 0.844 1.184 Free of multicollinearity Source: SPSS output data
Based on table 3, it is known that the regression model does not experience multicollinearity disorders.
This is indicated by the tolerance value for each independent variable is more than 0.1. Then the results of the VIF calculation also prove that the VIF value for each independent variable is less than 10. It is concluded that there is no multicollinearity between the independent variables in the regression model used.
5. Heteroscedasticity Test
According to Ghozali (2005) Heteroscedasticity test aims to test whether in the regression model there is an inequality of variance from one study to another. The way to test heteroscedasticity data is by looking at the presence or absence of certain patterns in the scatterplot graph between SRESID & ZPRED, where the Y axis is Y which has been predicted, & the X axis is residual (Y predicted – Y actually) which has previously been standardized. Then the basis for making heteroscedasticity test decisions is:
a. If in certain patterns such as dots that form certain and regular patterns (melting which then narrows, and wavy), then it means that heteroscedasticity has occurred.
b. If there is no clear pattern, both points that spread above and below the number 0 (zero) on the Y axis, it means that there is no heteroscedasticity.
The graph of Heteroscedasticity testing can be explained in the following figure:
Figure 3: Heteroscedasticity Test Source: SPSS Output Data
Based on the graph above, it can be seen that the data distribution is irregular and does not form a certain pattern, the data distribution is spread above and below the number 0 on the Y axis, thus it can be concluded that in this regression model there is no heteroscedasticity problem.
6. Multiple Linear Regression Equation
Multiple linear regression was used to prove the results of the research hypothesis. This analysis uses input data obtained from the distribution of questionnaires. The summary of data processing using the SPSS application in this study is as follows:
Table 4 Multiple linear regression equation
Description B Tcount ttable Sig.
Constant -0.181
Work Orientation (X1) 0.913 7.308 1.995 0.000
Training (X2) -0.186 -2.067 1.995 0.042
Career Development (X3) 0.322 3.913 1.995 0.000 Source: SPSS Output Data
The regression equation model that can be written from these results in the form of a standard form regression equation is as follows:
Y = -0.181 + 0.913X1 - 0.186X2 + 0.322X3
From the multiple linear regression equation above, the following values are obtained:
1) Constant
The value of Constant Y is -0.181, which means the performance value of Narotama University Education Staff (Y) is 0.181 units. If it is assumed that work orientation, training and career development, the performance of Narotama University Education Staff (Y) is 0, mean that if the value of the independent variable is 0 then the dependent or dependent variable will be 0.181.
2) Work Orientation coefficient value (X1)
The value of the work orientation coefficient (X1) is 0.913, if the performance of Narotama University Education Staff increases work orientation (X1) it will increase the performance of Narotama University Education Staff (Y) by 0.913 units. Assuming the value of the other independent variables is equal to zero.
3) Training coefficient value (X2)
The value of the training coefficient (X2) is -0.186, if the performance of Narotama University Education Staff increases training (X2) it will increase the performance of Narotama University Education Staff (Y) by -0.186 units. Assuming the value of the other independent variables is equal to zero.
4) Career Development coefficient value (X3)
The career development coefficient value (X3) is 0.322, if the performance of Narotama University Education Staff increases career development (X3), it will increase the performance of Narotama University Education Staff (Y) by 0.322 units. Assuming the value of the other independent variables is equal to zero.
7. Determination Test
(Ghozali, 2012) states that the coefficient of determination (R2) is a measure of how far the model is able to explain the variance of the dependent or dependent variable. Then the value of the coefficient of determination occurs between zero or one. A small R2 value means that the ability of the independent variables in explaining the variant of the dependent variable is very limited. The contrary, if the value is close to 1 means that the independent variables provide almost all of the information needed in predicting the dependent variables.
Table 5 Determination Test Model R R Square Adjusted R
Square
Std. Error of the
Estimate Durbin-Watson
1 0.776a 0.601 0.586 0.46021 1.994
a. Predictors: (Constant), Career Development, Work Orientation, Training b. Dependent Variable: Performance of Education Training
Source: SPSS output data
Based on table 8 above, the coefficient value (R) shows the significant effect of the independent variables work orientation (X1), training (X2), career development (X3) on the dependent variable of Education Staff performance (Y), the magnitude of the coefficient value is 0.776. This proves that the independent variables of work orientation (X1), training (X2), career development (X3) have a strong or close effect on the dependent variable of Education Staff performance (Y).
The value of the coefficient of determination or Adjust R Square (R2) was obtained at 0.586, which proves that the contribution of the independent variables of work orientation (X1), training (X2), career development (X3) affects the dependent variable of Education Staff performance (Y) by 58.6%. While the remaining 41.4% is influenced by variables not examined in this study.
8. T-Test (Partial)
(Ghozali, 2012) defines that the t-test difference test is used to test how far the influence of the independent variables used in individual research in explaining the dependent variable partially. The basis for decision making used in the t-test are if the significant probability value is greater than 0.05 then the hypothesis is rejected. The rejected hypothesis means that the independent variable has no significant effect on the dependent variable. The significant probability value is less than 0.05 then the hypothesis is accepted. The accepted hypothesis means that the independent variable has a significant effect on the dependent variable.
Table 6 Partial Test Model
Unstandardized Coefficients
Standardized
Coefficients t Sig.
B Std. Error Beta
1 (Constant) -0.181 0.444 -0.408 0.684
Work Orientation 0.913 0.125 0.678 7.308 0.000
Training -0.186 0.090 -0.179 -2.067 0.042
Career Development -0.322 0.082 -0.308 3.913 0.000 a. Dependent Variable: Performance of Education Staff
Source: SPSS output data
1) Testing the effect of work orientation on the performance of Education Staff
Based on table 9, the tcount value is 7.308 with a significance value of 0.000 < 0.05, then HO is rejected and Ha is accepted, then work orientation has a significant effect on performance of Narotama University Education Staff.
2) Testing the effect of training on the performance of Education Staff
Based on table 9, the tcount value is -2.067 with a significance value of 0.042 < 0.05 then HO is rejected and Ha is accepted, then training has a significant effect on performance of Narotama University Education Staff.
3) Testing the effect of career development on the performance of Education Staff
Based on table 9, the tcount value is 3.913 with a significance value of 0.000 < 0.05, then HO is rejected and Ha is accepted, so career development has a significant effect on performance of Narotama University Education Staff.
9. F-Test (Simultaneous)
According to (Ghozali, 2012) F-test basically shows whether all independent variables included in the model have a simultaneous effect on the dependent variable. So that this hypothesis uses the F-test with decision making criteria if the probability value is less than 0.05, then the HO is rejected in other words Ha is accepted, which means that all the independent variables together and significantly affect the dependent variable. Provide a comparison between the value of Fcount with Ftable. If the value of Fcount > Ftable, then HO is rejected and Ha is accepted.
Table 7 F-Test (Simultaneous)
Model Sum of
Squares df Mean
Square F Sig.
1 Regression 24.521 3 8.097 38.232 0.000a Residual 16.096 76 0.212
Total 40.387 79
a. Predictors: (Constant), Career Development, Work Orientation, Training b. Dependent Variable: Performance of Education Staff Source: SPSS output data
Based on table 10, the results of the F-test calculations show that the Fcount is 38.232 greater than F table 2.72 with a significant level of 0.000, which is less than (α) 0.05. The probability is less than 0.05, then Ha is accepted, mean that the variables of work orientation, training, and career development simultaneously have a significant effect on performance of Narotama University Education Staff.
3.2. Discussion
1. Effect of Work Orientation on Performance of Education Staff
The results of statistical calculations show that the value of tcount is 7.308 with sig. 0.000 is less than 0.05, then HO is rejected and Ha is accepted, meaning that work orientation has a significant effect on the performance of Narotama University Education Staff.
In reality, work orientation carried out is proven to be able to provide a significant effect in improving the performance of the Education Staff. Each Education Staff has a different work orientation, this is one of the policies adapted by the company or agency where they work. Work orientation is a concept that can improve harmonization in work and be able to improve the individual performance of each Education Staff at Narotama University. The indicators contained in the work orientation are able to help education personnel to shape themselves and become one of the influences in their performance. This is because basically humans need equal treatment and a desire to respect each other regardless of whether the Education Staff has a position as a subordinate.
This first hypothesis supports the previous researcher by Putu Anggita Laksmi Pratiwi (2017) which shows that work orientation has a significant effect on employee performance.
2. Effect of Training on Performance of Education Staff
The results of statistical calculations show that the value of tcount is -2,067 with sig. 0.042 is less than 0.05, then HO is rejected and Ha is accepted, meaning that training has a significant effect on the performance of Narotama University Education Staff.
Training has an important role in determining the efficiency and effectiveness of the company in the performance of Education Staff at Narotama University. Universities hold trainings, of course, there are certain reasons so that their education personnel become more skilled, so that they are able to provide advantages for the organization and for the education staff themselves. Meanwhile, training is the creation of an environment in which education personnel acquire and learn attitudes, skills, abilities, knowledge of specific behaviors related to their work.
The second hypothesis support the previous researcher by Arika (2020) which shows that training has a significant effect on employee performance.
3. Effect of Career Development on Performance of Education Staff
The results of statistical calculations show that the value of tcount is 3,913 with sig. 0.000 is less than 0.05, then HO is rejected and Ha is accepted, meaning that career development has a significant effect on the performance of Narotama University Education Staff.
Veitzhal Rivai (2004) defines career development as crucial, where management can increase productivity, improve employee attitudes towards work, and build higher job satisfaction. According to Rwayne Monday (2011) career development is the normal approach that organizations use to ensure that people with the right qualifications and experience are available when needed.
This third hypothesis supports the previous researcher by Jumawan & Mora (2018) which shows that career development has a significant effect on employee performance.
4. Effect of Work Orientation, Training, and Career Development on Performance of Education Staff
Testing the effect of independent variables simultaneously on the dependent variable was carried out using the F-test. The results of statistical calculations showed the Fcount value 38.232 greater than Ftable 2.72 with a significant level of 0.000 less than (α) 0.05, then Ha is accepted. This means that the hypothesis which states that the variables of work orientation, training, and career development simultaneously have a significant effect on the performance of Education Staff at Narotama University.
Based on the results of statistical tests, it can be clearly seen that simultaneously all independent variables affect the dependent variable. In the independent variable test that jointly affects the dependent variable which is carried out using the F-test. This shows that the hypothesis which states that work orientation, training, and career development variables simultaneously have an effect on the performance of Narotama University Education Staff.
4. Conclussion
The conclusion of this study is that each variable of work orientation, training, and career development has a significant effect either partially or simultaneously. The benefits of doing work orientation, training and career development greatly affect the performance of Education Staff at Narotama University. Increasing the implementation of work orientation will improve the performance of Education Staff. This means that the orientation given to employees will be able to improve the performance of Education Staff.
Narotama University needs to manage training activities by mapping and observing the Education Staff needs. Also evaluate Education Staff who have participated in training activities before, whether the training activities increase the knowledge and abilities of the Education Staff. Likewise with the career development provided by Narotama University, Education Staff will improve their performance in order to reach the next career path. Therefore, Narotama University should continue to maintain the career development for the Education Staff so they will continue to improve performance and develop careers in the company.
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Biography/Biographies
Hary Adi Laksono is a student of Narotama University, Faculty of Law, Economics and Education Management Study Program.
Elok Damayanti graduated at Surabaya University (UBAYA) in major of Foreign Business Language and then continued her study at Sekolah Tinggi Ilmu Ekonomi YAPAN, Surabaya. She completed her Master’s Degree of Management, focuses in Human Resource Management at Narotama University. Active as a lecturer in Departement of Management at Narotama University since 2016 with courses of Human Resources Management, International HRM, HRM Practicums, Business Introduction, Business Ethics, International Business, Public Speaking and Business English. Active in national and international organizations of ADRI, IORA, ICOGOIA, and World Conference. Also active in writing scientific articles and writing books in National and International journals. In addition, she is a Director of Professional Certification Body at Narotama University and also as a Head of National Partnership, responsible for the domestic cooperation at the university.
Joko Suyono is a lecturer at Narotama University, Surabaya, Indonesia. He got bachelor degree in business administration and also accounting, he got master degree in industrial management and also in marketing management, and he got doctoral degree in business administration. Prior becoming a lecturer, he is a practitioner as senior manager in some multinational corporation such as Stanley Works Indonesia (USA Company), Ericsson Indonesia (European Company) and Lotus Indah Textile Industries, a multinational company in the textile, spun yarns.
