领导力、纪律性和积极性对师范教育学院讲师绩效的影响。

Bangun Munthe
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引用次数: 0

摘要

本研究旨在确定领导力、纪律和动机对 FKIP HKBP Nommensen Pematangsiantar 大学讲师绩效的影响。样本为 53 名长期基础讲师。使用的工具是调查问卷。所有经过测试的问卷均有效可靠。本研究属于描述性解释研究,即旨在解释所研究变量的位置和变量之间关系的研究。领导力系数的值为 0.316,这意味着在其他变量保持不变的情况下,如果领导力得到改善,讲师的绩效将会提高。纪律系数的值为 0.343,这意味着在其他变量保持不变的情况下,如果纪律性提高,讲师的绩效也会提高。动机系数的数值为 0.222,这意味着在其他变量保持不变的情况下,如果动机越强,讲师的绩效就会越高。研究结果表明,三个自变量(领导力、纪律性和积极性)对因变量(讲师绩效)同时产生了积极而重要的影响。回归分析用于检验关于自变量对因变量的部分影响的假设。根据 SPSS 程序的多元回归估计,结果为 Y = 0.316 X1 + 0.343 X2 + 0.222 X3。从回归计算的结果可以看出,得到的决定系数(调整后 R2)为 0.57,即 57%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PENGARUH KEPEMIMPINAN, DISIPLIN DAN MOTIVASI TERHADAP KINERJA DOSEN FAKULTAS KEGURUAN DAN ILMU PENDIDIKAN
This research was conducted with the aim of determining the influence of leadership, discipline and motivation on lecturer performance at FKIP HKBP Nommensen Pematangsiantar University. With a sample of 53 Permanent Foundation Lecturers. The tool used is a questionnaire. All questionnaires tested are valid and reliable. This research is descriptive explanatory, namely research that aims to explain the position of the variables studied and the relationships between the variables. The leadership coefficient gives a value of 0.316, which means that if leadership gets better assuming other variables remain constant, lecturer performance will increase. The discipline coefficient gives a value of 0.343, which means that if discipline is higher, assuming other variables remain constant, lecturer performance will increase. The Motivation coefficient gives a value of 0.222, which means that if motivation becomes stronger assuming other variables remain constant, lecturer performance will increase. The results of the research show that the three independent variables (Leadership, Discipline and Motivation) have a positive and significant influence, both partially and simultaneously on the dependent variable (Lecturer Performance). Regression analysis is used to test the hypothesis regarding the partial influence of the independent variables on the dependent variable . Based on multiple regression estimates with the SPSS program, the results obtained are Y = 0.316 X1 + 0.343 X2 + 0.222 X3. From the results of the regression calculations, it can be seen that the coefficient of determination (adjusted R2) obtained is 0.57 or 57%.
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