Zona Manajemen: Program Studi Magister Sains Manajemen Universitas Batam

DETERMINATION OF SELF EFFICACY, WORKING ETHOS, WORKING DISCIPLINE WITH ORGANIZATIONAL CITIZENSHIP BEHAVIOR AS INTERVENING VARIABLES ON WORK ACHIEVEMENT WITH USING SEM-PLS (RESEARCH STUDY PERSONNEL DITPOLAIRUD POLDA KEPRI)

2021-09-09T16:06:41+00:00

In this study, researchers used respondent data, such as gender, age and length of work of respondents in order to provide information about relationships. Where from the questionnaires distributed as many as 75. The discussion in this chapter is the result of field studies to obtain questionnaire answer data which measures the five main variables in this study, namely self-efficacy, work ethic, work discipline, organizational citizen behavior and work performance. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument tests, normality tests, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Path. This study uses path analysis (path analysis) to examine relationship patterns that reveal the effect of a variable or a set of other variables, both direct and indirect. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To have a direct and indirect effect between variables, the calculation results of the path coefficient and to see the significance.

The influence of the X3 variable on X4 has a P-Values value of 0.043 <0.05, so it can be stated that the effect of X3 on X4 is significant. The influence of the X3 variable on Y has a P-Values value of 0.033 <0.05, so it can be stated that the effect of X3 on Y is significant. The effect of the variable X4 on Y has a P-Values value of 0.013 <0.05, so it can be stated that the effect of X4 on Y is significant. The effect of variable X1 on X4 has a P-Values value of 0.003 <0.05, so it can be stated that the effect of X1 on X4 is significant. The effect of the variable X1 on Y has a P-Values value of 0.010 <0.05, so it can be stated that the effect of X1 on Y is significant. The effect of variable X2 on X4 has a P-Values value of 0.003 <0.05, so it can be stated that the effect of X2 on X4 is significant.The effect of variable X2 on Y has a P-Values value of 0.033 <0.05, so it can be stated that the between X2 and Y is significant.

DETERMINATION OF WORK CHARATERISTICS, LOCUS OF CONTROL, REWARD WITH WORK ACHIEVEMENT AS INTERVENING VARIABLES ON PERFORMANCE WITHUSING SEM-PLS (STUDY EMPLOYEE RESEARCH IN BINTAN DISTRICT HEALTH OFFICE

2021-09-09T16:06:41+00:00

Â Â Â Â Â Â In this study, researchers used respondent data, such as gender, age and length of work of respondents in order to provide information about the characteristics of respondents. Where from the questionnaires distributed as many as 41. The discussion in this chapter is the result of field studies to obtain questionnaire answer data that measures five main variables in this study, namely job characteristics, locus of control, reward, work performance and performance. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument testing, normality test, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Path. 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 direct and indirect. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To determine the direct and indirect effect between variables, it is seen from the calculation of the path coefficient and to determine the significance.

Â Â Â Â Â Â Â Â Â Â Â The effect of the variable X3 on X4 has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X3 on X4 is significant. The influence of the X3 variable on Y has a P-Values value of 0.012 <0.05, so it can be stated that the effect of X3 on Y is significant. The effect of variable X4 on Y has a P-Values value of 0.033 <0.05, so it can be stated that the effect between X4 and Y is significant. The effect of variable X1 on X4 has a P-Values value of 0.043 <0.05, so it can be stated that the effect of X1 on X4 is significant. The effect of variable X1 on Y has a P-Values value of 0.014 <0.05, so it can be stated that the effect of X1 on Y is significant. The effect of the variable X2 on X4 has a P-Values value of 0.021 <0.05, so it can be stated that the effect of X2 on X4 is significant. The influence of the X2 variable on Y has a P-Values value of 0.021 <0.05, so it can be stated that the effect of X2 on Y is significant

DETERMINATION OF ORGANIZATIONAL TRUST, ORGANIZATIONAL CULTURE, ORGANIZATIONAL CLIMATE WITH JOB SATISFACTION ASINTERVENING VARIABLES ON COMMITMENTS ORGANIZATION USING SEM-PLS (EMPLOYEE RESEARCH STUDY IN ORGANICS PERSERO STATE SAVING BANK)

2021-09-09T16:06:41+00:00

In this study, researchers used respondent data, such as gender, age and length of work of respondents in order to provide information about relationships. Where from the questionnaires distributed as many as 107. The discussion in this chapter is the result of field studies to obtain questionnaire answer data that measures the five main variables in this study, namely organizational trust, organizational culture, organizational climate, job satisfaction and organizational commitment. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument tests, normality tests, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Path. This study uses path analysis (path analysis) to examine relationship patterns that reveal the effect of a variable or a set of other variables, both direct and indirect. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To have a direct and indirect effect between variables, the calculation results of the path coefficient and to see the significance.

Â Â Â Â Â Â Â Â Â Â Â The influence of the X3 variable on X4 has a P-Values value of 0.024 <0.05, so it can be stated that the effect of X3 on X4 is significant. The influence of the X3 variable on Y has a P-Values value of 0.000> <0.05, so it can be stated that the effect of X3 on Y is significant. The effect of the variable X4 on Y has a P-Values value of 0.005 <0.05, so it can be stated that the effect of X4 on Y is significant.The effect of variable X1 on X4 has a P-Values value of 0.017 <0.05, so it can be stated that between X1 against X4 is significant. The effect of variable X1 on Y has a P-Values value of 0.022 <0.05, so it can be stated that the effect of X1 on Y is significant. The effect of the variable X2 on X4 has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X2 on X4 is significant. The influence of the X2 variable on Y has a P-Values value of 0.031 <0.05, so it can be stated that the effect of X2 on Y is significant.

DETERMINATION OF WORK ETHICS, WORK DISCIPLINE, WORK EXPENSE WITH JOB SATISFACTION AS INTERVENING VARIABLES ON PERFORMANCE USING SEM-PLS (EMPLOYEE RESEARCH STUDY IN THE COMMUNICATION AND INFORMATICS DEPARTMENT RIAU ISLANDS)

2021-09-09T16:06:41+00:00

In this study, researchers used respondent data, such as gender, age and length of work of respondents in order to provide information about the characteristics of respondents. Where from the questionnaires distributed as many as 48. The discussion in this chapter is the result of field studies to obtain questionnaire answer data which measures the five main variables in this study, namely work ethic, work discipline, workload, job satisfaction and performance. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument testing, normality test, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Path. 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 direct and indirect. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To determine the direct and indirect effect between variables, it is seen from the calculation of the path coefficient and to determine the significance.

Â Â Â Â Â Â Â Â Â Â Â The influence of the X3 variable on X4 has a P-Values value of 0.002 <0.05, so it can be stated that the effect of X3 on X4 is significant. The influence of the X3 variable on Y has a P-Values value of 0.008 <0.05, so it can be stated that the effect of X3 on Y is significant. The influence of the variable X4 on Y has a P-Values value of 0.011 <0.05, so it can be stated that the effect of X4 on Y is significant. The effect of variable X1 on X4 has a P-Values value of 0.024 <0.05, so it can be stated that the effect of X1 on X4 is significant. The effect of the variable X1 on Y has a P-Values value of 0.044 <0.05, so it can be stated that the effect of X1 on Y is significant. The effect of the variable X2 on X4 has a P-Values value of 0.011 <0.05, so it can be stated that the effect of X2 on X4 is significant. The influence of the X2 variable on Y has a P-Values value of 0.005 <0.05, so it can be stated that the effect of X2 on Y is significant.

DETERMINATION OF WORK STRESS, WORKING DISCIPLINE, WORK EXPENSE WITH WORK SPIRIT AS INTERVENING VARIABLES ON PERFORMANCE USING SEM-PLS (STUDY EMPLOYEE RESEARCH AT PT BANK TABUNGAN NEGARA PERSERO, TBK OFFICE BATAM BRANCH)

2021-09-09T16:06:41+00:00

In this study, researchers used respondent data, such as gender, age and length of work of respondents in order to provide information about relationships. Where from the questionnaires distributed as many as 107. The discussion in this chapter is the result of field studies to obtain questionnaire answer data that measures five main variables in this study, namely work stress, work discipline, workload, work morale and performance. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument tests, normality tests, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Path. This study uses path analysis (path analysis) to examine relationship patterns that reveal the effect of a variable or a set of other variables, both direct and indirect. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To have a direct and indirect effect between variables, the calculation results of the path coefficient and to see the significanceÂ Â Â Â

Â Â Â Â Â Â Â Â Â Â Â The influence of the X3 variable on X4 has a P-Values value of 0.006 <0.05, so it can be stated that the effect of X3 on X4 is significant. The influence of the variable X3 on Y has a P-Values value of 0.002 <0.05, so it can be stated that the effect of X3 on Y is significant. The effect of the variable X4 on Y has a P-Values value of 0.002 <0.05, so it can be stated that the effect of X4 on Y is significant. The effect of variable X1 on X4 has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X1 on X4 is significant. The effect of variable X1 on Y has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X1 on Y is significant. The effect of the variable X2 on X4 has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X2 on X4 is significant. The influence of the X2 variable on Y has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X2 on Y is significant.

DETERMINATION OF COMPETENCY , SCHOOL CLIMATE, WORK DISCIPLINE WITH WORK MOTIVATION AS INTERVENING VARIABLES ON TEACHER PERFORMANCE BY USING SEM-PLS (TEACHER RESEARCH STUDY AT VOCATIONAL SCHOOL OF PERTIWI BATAM)

2021-09-09T16:06:42+00:00

In this study, researchers used respondent data, such as gender, age and length of work of respondents in order to provide information about relationships. Where from the questionnaires distributed as many as 30. The discussion in this chapter is the result of field studies to obtain questionnaire answer data that measures five main variables in this study, namely competence, school climate, work discipline, work motivation and performance. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument tests, normality tests, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Path. This study uses path analysis (path analysis) to examine relationship patterns that reveal the effect of a variable or a set of other variables, both direct and indirect. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To have a direct and indirect effect between variables, the calculation results of the path coefficient and to see the significance.

Â Â Â Â Â Â Â Â Â Â Â The influence of the X3 variable on X4 has a P-Values value of 0.029 <0.05, so it can be stated that the effect of X3 on X4 is significant. The influence variable X3 on Y with a P-Values value of 0.002 <0.05, so it can be stated that the influence between X3 on Y is significant. The effect of the variable X4 on Y with a P-Values value of 0.002 <0.05, so it can be stated that the effect of X4 on Y is significant. The effect of variable X1 on X4 with a P-Values value of 0.027 <0.05, so it can be stated that the effect of X1 on X4 is significant. The effect of variable X1 on Y with a P-Values value of 0.012 <0.05, so it can be stated that the effect of X1 on Y is significant. The influence variable X2 on X4 has a P-Values value of 0.009 <0.05, so it can be stated that the effect between X2 and X4 is significant. The effect of the X2 variable on Y with a P-Values value of 0.017 <0.05, so it can be stated that the effect of X2 on Y is significant

DETERMINATION OF LEADERSHIP, COMPETENCY AND WORK DISCIPLINE WITH WORK MOTIVATION AS A MEDIATOR VARIABLES TO ORGANIZATIONAL COMMITMENT USING SEM-PLS (EMPLOYEE RESEARCH STUDY IN DEPARTMENT OF HEALTH BINTAN DISTRICT)

2021-09-09T16:06:42+00:00

In this study, researchers used respondent data, such as gender, age and length of work of respondents in order to provide information about the characteristics of respondents. Where from the questionnaires distributed as many as 75. The discussion in this chapter is the result of field studies to obtain data on the answers to the questionnaire which measures the five main variables in this study, namely leadership, competence, work discipline, work motivation and organizational commitment. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument testing, normality test, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Path. 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 direct and indirect. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To determine the direct and indirect effect between variables, it is seen from the calculation of the path coefficient and to determine the significance.

Â Â Â Â Â Â Â Â Â Â Â The effect of the variable X3 on X4 has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X3 on X4 is significant. The influence of the X3 variable on Y has a P-Values value of 0.003<0.05, so it can be stated that the effect of X3 on Y is significant. The influence of the X4 variable on Y has a P-Values value of 0.014 <0.05, so it can be stated that the effect of X4 on Y is significant. The effect of variable X1 on X4 has a P-Values value of 0.020<0.05, so it can be stated that the effect of X1 on X4 is significant. The effect of variable X1 on Y has a P-Values value of 0.001 <0.05, so it can be stated that The influence between X1 on Y is significant. The effect of the variable X2 on X4 has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X2 on X4 is significant. The influence of the X2 variable on Y has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X2 on Y is significant.

DETERMINATION OF EMOTIONAL INTELLIGENCE, INTELLECTUAL INTELLIGENCE AND WORK SPIRIT WITH DISCIPLINE WORKING AS A MEDIATOR VARIABLES ON PERFORMANCE BY USING SEM-PLS (RESEARCH STUDY EMPLOYEES AT RAJA AHMAD HOSPITAL TABIB TANJUNG PINANG PROVINCE KEPRI)

2021-09-09T16:06:42+00:00

In this study, researchers used respondent data, such as gender, age and length of work of respondents in order to provide information about the characteristics of respondents. Where from the questionnaires distributed as many as 281. The discussion in this chapter is the result of field studies to obtain questionnaire answer data that measures the five main variables in this study, namely emotional intelligence, intellectual intelligence, morale, work discipline, and performance. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument testing, normality test, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Path. 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 direct and indirect. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To determine the direct and indirect effect between variables, it is seen from the calculation of the path coefficient and to determine the significance.

Â Â Â Â Â Â Â Â Â Â Â The effect of the variable X3 on X4 has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X3 on X4 is significant. The influence of the X3 variable on Y has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X3 on Y is significant. The effect of the variable X4 on Y has a P-Values value of 0.001 <0.05, so it can be stated that the effect of X4 on Y is significant. The effect of variable X1 on X4 has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X1 on X4 is significant. The effect of variable X1 on Y has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X1 on Y is significant. The effect of the variable X2 on X4 has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X2 on X4 is significant. The influence of the X2 variable on Y has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X2 on Y is significant.

DETERMINATION OF TRANSFORMATIONAL LEADERSHIP , ORGANIZATIONAL CULTURE, ACHIEVEMENT MOTIVATION WITH ORGANIZATIONAL CITIZENSHIP BEHAVIOR AS INTERVENING VARIABLES ON PERFORMANCE USING ALL-PLS (EMPLOYEE RESEARCH STUDY IN PT. THE COMMUNITY BANK INDONESIA PINANG TANJUNG PINANG KENCANA BRANCH, UNIT)

2021-09-09T16:06:42+00:00

In this study, researchers used respondent data, such as gender, age and length of work of respondents in order to provide information about relationships. Where from the questionnaires distributed as many as 30. The discussion in this chapter is the result of field studies to obtain questionnaire answer data that measures five main variables in this study, namely transformational leadership, organizational culture, achievement motivation, organizational citizen behavior and performance. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument tests, normality tests, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Path. This study uses path analysis (path analysis) to examine relationship patterns that reveal the effect of a variable or a set of other variables, both direct and indirect. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To have a direct and indirect effect between variables, the calculation results of the path coefficient and to see the significance.

Â Â Â Â Â Â Â Â Â Â Â The influence of the X3 variable on X4 has a P-Values value of 0.046 <0.05, so it can be stated that the effect of X3 on X4 is significant. The influence of the X3 variable on Y with a P-Values value of 0.005 <0.05, so it can be stated that the effect of X3 on Y is significant. The effect of the variable X4 on Y with a P-Values value of 0.010 <0.05, so it can be stated that the effect of X4 on Y is significant. The effect of variable X1 on X4 has a P-Values value of 0.045 <0.05, so it can be stated that the effect of X1 on X4 is significant. The effect of the variable X1 on Y with a P-Values value of 0.000 <0.05, so it can be stated that the effect of X1 on Y is significant. The effect of the variable X2 on X4 has a P-Values value of 0.000 <0.05, so it can be stated that the effect of X2 on X4 is significant. The effect of the variable X2 on Y with a P-Values value of 0.022 <0.05, so it can be stated that the effect of X2 on Y is significant

DETERMINATION OF WORK COMMUNICATION, WORK SPIRIT, WORK ETHOS WITH WORK MOTIVATION AS INTERVENING VARIABLES TOWARDS PERFORMANCE USING SEM-PLS IN THE DINAS KESEHATAN KOTA BATAM

2021-09-09T16:06:42+00:00

In this study, researchers used respondent data, such as gender, age and length of work of respondents in order to provide information about relationships. Where from the questionnaires distributed as many as 102. The discussion in this chapter is the result of field studies to obtain questionnaire answer data that measures five main variables in this study, namely work communication, work morale, work ethic, work motivation and performance. Data analysis with parametric and non-parametric statistics using SEM-PLS (Structural Equation Modeling-Partial Least Square) regarding research variables, instrument tests, normality tests, hypothesis testing, and discussion of the results of hypothesis testing and Path Analysis Path. This study uses path analysis (path analysis) to examine relationship patterns that reveal the effect of a variable or a set of other variables, both direct and indirect. The calculation of the path coefficient in this study was assisted by Smart PLS Ver 3.0. To have a direct and indirect effect between variables, the calculation results of the path coefficient and to see the significance.

Â Â Â Â Â Â Â Â Â Â Â The influence of the X3 variable on X4 has a P-Values value of 0.010 <0.05, so it can be stated that the effect of X3 on X4 is significant. The influence variable X3 on Y with a P-Values value of 0.003 <0.05, so it can be stated that the influence between X3 on Y is significant. The effect of the variable X4 on Y with a P-Values value of 0.046 <0.05, so it can be stated that the effect of X4 on Y is significant. The influence variable X1 on X4 has a P-Values value of 0.009 <0.05, so it can be stated that the influence between X1 and X4 is significant. The effect of the variable X1 on Y with a P-Values value of 0.000 <0.05, so it can be stated that the effect of X1 on Y is significant. The effect of the variable X2 on X4 has a P-Values value of 0.040 <0.05, so it can be stated that the effect of X2 on X4 is significant. The variable of the influence of X2 on Y with a P-Values value of 0.009 <0.05, so it can be stated that the effect of X2 on Y is significant.