Record Details

PENGUJIAN MODEL REGRESI UNTUK PENGUKURAN PRODUKTIVITAS TENAGA KERJA: KASUS INDUSTRI KECIL DI JAWA TENGAH

Journal of Management and Entrepreneurship

View Archive Info
 
 
Field Value
 
Title PENGUJIAN MODEL REGRESI UNTUK PENGUKURAN PRODUKTIVITAS TENAGA KERJA: KASUS INDUSTRI KECIL DI JAWA TENGAH
 
Creator Indrawati, Indrawati; Faculty of Economics, Petra Christian University
Llewelyn, Richard Von; Faculty of Economics, Petra Christian University
 
Subject productivity, small industry regression model evaluation.
 
Description Managers of small industries need accurate information regarding the type of workers which are most productive. This information can be obtained through regression analysis only if the regression model which is used is correct. This analysis has the objective of determining the proper regression model among four possibilities, including the linear model, quadratic model, square root model and logarithmic model. In addition, another objective is to determine the impact of several influential variables on labor productivity.
Although the linear model is often used in productivity research, this analysis shows that for the data used in this study, the quadratic model is the best regression model to be used. It can be concluded that for managers of small businesses: 1) work experience does not make a difference but that age has a negative and significant relationship with productivity; 2) the level of education is significant, though the effect is unclear; 3) educational level may not be ignored but is less important than worker age; 4) it seems that younger workers have higher productivity according to this analysis, perhaps due to greater enthusiasm or an ability to work harder.


Abstract in Bahasa Indonesia :

Para manajer usaha kecil memerlukan informasi yang tepat mengenai jenis pekerja yang paling produktif. Informasi yang tepat itu dapat diperoleh dari analisis regresi jika dan hanya jika model regresi yang digunakan menjadi tepat. Analisis ini bertujuan untuk menentukan model regresi yang paling tepat dari empat kemungkinan yaitu, model linear, model kuadrat, model akar serta model logarithmic. Selain itu, ada tujuan menentukan pengaruh dari beberapa faktor yang berpengaruh terhadap produktivitas tenaga kerja di industri kecil.
Walaupun model linear sering digunakan dalam penelitian produktivitas, analisis ini membuktikan bahwa untuk data yang digunakan dalam analisis ini, model kuadrat menjadi model regresi yang paling tepat untuk digunakan. Kesimpulan untuk para manajer industri kecil adalah bahwa 1) pengalaman kerja tidak berpengaruh tetapi umur mempunyai hubungan yang negatif dan signifikan dengan produktivitas; 2) pendidikan mempunyai pengaruh yang signifikan walaupun hubungannya kurang jelas; 3) tingkat pendidikan tidak dapat diabaikan tetapi menjadi kurang penting dibandingkan dengan umur; 4) orang yang lebih muda menjadi lebih produktif dalam analisis ini, mungkin karena mereka lebih semangat atau dapat bekerja lebih keras.

Kata kunci : produktivitas, industri kecil, pengujian model regresi
 
Publisher Institute of Research and Community Outreach - Petra Christian University
 
Date 2004-06-02
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier http://jurnalmanajemen.petra.ac.id/index.php/man/article/view/15588
10.9744/jmk.1.1.pp. 1-11
 
Source Jurnal Manajemen dan Kewirausahaan; Vol 1, No 1 (1999): MARCH 1999; pp. 1-11
 
Language eng
 
Relation http://jurnalmanajemen.petra.ac.id/index.php/man/article/view/15588/18015
 
Rights Authors who publish with this journal agree to the following terms:Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.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 acknowledgement of its initial publication in this journal.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 (See The Effect of Open Access).