THE IMPROVEMENT OF IN ISLAMIC LEADERSHIP TOWARDS TEACHER PERFORMANCE WITH COMPETENCY-BASED AND QUALITY OF WORK LIFE

Authors

DOI:

https://doi.org/10.30659/ijibe.3.2.458-472

Abstract

The problem in this research is the unimmunity of teacher performance of SD Negeri in Mejobo District Kudus Regency. The purpose of this study is to analyze and to know the influence of Islamic Leadership on Teacher Performance through Teacher Competence and Quality of Work Life of Elementary School Teachers. The population of this research is all elementary school teachers from 3 villages in Mejobo District Kudus Regency as many as 129 people. This study used 100 teachers as a sample with Purposive Random Sampling. Datas were obtained from questionnaires and interviews. Data analysis using SPSS 16.0 and Eviews 9. The result of this research is Islamic Leadership, Teacher Competence, and Quality of Work Life positively influence to Teacher Performance. Based on data analysis only Quality of Work Life on Teacher Performance which has no significant effect. Teacher competence and Quality of Work Life can not be considered as intervening variable in this research.

Keywords: Islamic Leadership, Quality of Work Life, Teacher Competency, and Teacher Performance.

Downloads

Published

2018-09-03

Issue

Vol. 3 No. 2 (2018): September 2018

Section

Articles

License

License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
  • They are authorized by their co-authors to enter into these arrangements.
  • The work described has not been formally published before, except in the form of an abstract or as part of a published lecture, review, thesis, or overlay journal.
  • That it is not under consideration for publication elsewhere,
  • That its publication has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
  • They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
  • They agree to the following license and copyright agreement.
Copyright
Authors who publish with IJIBE agree to the following terms:
  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
Licensing for Data Publication
IJIBE uses a variety of waivers and licenses, that are specifically designed for and appropriate for the treatment of data:
Other data publishing licenses may be allowed as exceptions (subject to approval by the editor on a case-by-case basis) and should be justified with a written statement from the author, which will be published with the article.

Open Data and Software Publishing and Sharing
The journal strives to maximize the replicability of the research published in it. Authors are thus required to share all data, code or protocols underlying the research reported in their articles. Exceptions are permitted but have to be justified in a written public statement accompanying the article.
Datasets and software should be deposited and permanently archived inappropriate, trusted, general, or domain-specific repositories (please consult http://service.re3data.org and/or software repositories such as GitHub, GitLab, Bioinformatics.org, or equivalent). The associated persistent identifiers (e.g. DOI, or others) of the dataset(s) must be included in the data or software resources section of the article. Reference(s) to datasets and software should also be included in the reference list of the article with DOIs (where available). Where no domain-specific data repository exists, authors should deposit their datasets in a general repository such as ZENODO, Dryad, Dataverse, or others.
Small data may also be published as data files or packages supplementary to a research article, however, the authors should prefer in all cases a deposition in data repositories.

This work is licensed under a Creative Commons Attribution 4.0 International License.