Open AccessThe Influence of Transformational Leadership, Organizational Culture, Work Environment, Organizational Commitment on Job Satisfaction of Batam University employees
Author(s) -
Tommy Arby Rumengan,
Jemmy Rumengan,
Dahlan Gunawan
Publication year - 2021
Publication title -
iaic international conference series
Language(s) - English
Resource type - Journals
eISSN - 2774-5899
pISSN - 2774-5880
DOI - 10.34306/conferenceseries.v3i2.460
Subject(s) - respondent , transformational leadership , descriptive statistics , job satisfaction , statistics , path analysis (statistics) , sample (material) , psychology , mathematics , social psychology , political science , chemistry , chromatography , law
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 dozens and employees. The sample is determined by the number of sample members (sample size) of 60 people by proportional random sampling technique. 25 lecturers and 35 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 Transformational Leadership, Organizational Culture, Work Environment, Organizational Commitment to Job Satisfaction 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.