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All Journal Zona Manajemen: Program Studi Magister Sains Manajemen Universitas Batam
Muhammad Tammy Ikbal Rumengan
University Of Batam, Batam
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Social Sciences Other

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DETERMINATION OF WORK DISCIPLINE, WORKING ENVIRONMENT, WORKING FACILITIES WITH JOB SATISFACTION AS A VARIABLE OF MEDIATOR ON ORGANIZATIONAL COMMITMENTS OFFICE CLERK OF CAMAT TEMBELAN Rama Agustian; Muhammad Tammy Ikbal Rumengan
Zona Manajemen: Program Studi Magister Sains Manajemen Universitas Vol 10 No 3 (2020): Volume 10, Nomor 03, Desember 2020
Publisher : Universitas Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37776/jzm.v10i3.579

Abstract

In this study, researchers used data respondents, such as gender, age and long working respondents to provide information on the characteristics of respondents. The questionnaire was spread over 40. The discussion in this chapter is the result of field studies to obtain data on the questionnaire responses that measure five key variables in the study, namely the discipline, work environment, work facilities, job satisfaction and the commitment of the employee's organization. Analysis of data with parametric and non parametrics statistics using SEM-PLS (structural Equation Modelling-Partial Least Square) on the research variables, instrument test, normality test, hypothesis test, as well as discussion of the hypothesis test results and path analysis Path. This research uses path analysis to test relationship patterns that reveal the influence of variables or a set of variables against other variables, both direct influences and indirect influences. Calculation of line coefficient in this study assisted with Smart PLS Ver 3.0. To find out the direct and indirect influences between variables then be seen from the calculation result of the line coefficient and to know the significance. The effect of the X3 variable against X4 has a P-Values value of 0.005 < 0.05, so it can be stated that the effect between X3 against X4 is significant. The effect of the variable X3 against Y has a P-Values value of 0.008 < 0.05, so it can be stated that the influence between X3 to Y is significant. The effect of X4 to Y variables has a P-Values value of 0.010 < 0.05, so it can be stated that the effect between X4 to Y is significant. The effect of the X1 variable against X4 has a P-Values value of 0.006 < 0.05, so it can be stated that the effect between X1 against X4 is significant. The effect of a X1 variable against Y has a P-Values value of 0.034 < 0.05, so it can be stated that the effect between X1 to Y is significant. The effect of a variable X2 against X4 has a P-Values value of 0.001 < 0.05, so it can be stated that the effect of X2 against X4 is significant. The effect of a variable X2 against Y has a P-Values value of 0.008 < 0.05, so it can be stated that the effect of the X2 against 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) Aprialdi Ariska; Jemmy Rumengan; Yunazar Manjang; Tammy Ikbal Rumengan
Zona Manajemen: Program Studi Magister Sains Manajemen Universitas Vol 11 No 1 (2021): Volume 11, Nomor 01, April 2021
Publisher : Universitas Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37776/jzm.v11i1.778

Abstract

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 significance                 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) Artati Artati; Jemmy Rumengan; Yunazar Manjang; Tammy Ikbal Rumengan
Zona Manajemen: Program Studi Magister Sains Manajemen Universitas Vol 11 No 1 (2021): Volume 11, Nomor 01, April 2021
Publisher : Universitas Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37776/jzm.v11i1.779

Abstract

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.            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) Desi Veronika; Jemmy Rumengan; Khadafi Khadafi; Tammy Ikbal Rumengan
Zona Manajemen: Program Studi Magister Sains Manajemen Universitas Vol 11 No 1 (2021): Volume 11, Nomor 01, April 2021
Publisher : Universitas Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37776/jzm.v11i1.780

Abstract

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.            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) Dwi Sri Agustini; Jemmy Rumengan; Angelina Eleonora Rumengan; Tammy Arby Rumengan
Zona Manajemen: Program Studi Magister Sains Manajemen Universitas Vol 11 No 1 (2021): Volume 11, Nomor 01, April 2021
Publisher : Universitas Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37776/jzm.v11i1.781

Abstract

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.            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.
Co-Authors Aprialdi Ariska Artati Artati Desi Veronika Dwi Sri Agustini Elly Rumengan Jemmy Rumengan Khadafi Khadafi Rama Agustian Yunazar Manjang