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All Journal Prosiding Seminar Nasional MIPA JURNAL PROFESI KEGURUAN Jurnal Matematika Sains dan Teknologi Jurnal Pendidikan Terbuka Dan Jarak Jauh JURNAL PENDIDIKAN TAMBUSAI EKONOMIKA45 Journal of Comprehensive Science (JCS) Riwayat: Educational Journal of History and Humanities
Isfarudi
Universitas Terbuka
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Journal : Jurnal Matematika Sains dan Teknologi

 1 
BEBERAPA KONSEKUENSI SITUASI MEDIASI SEMPURNA PADA STRUKTUR KORELASI, KONTRIBUSI MEDIATOR, DAN UKURAN SAMPEL Suhardi, Deddy A; Isfarudi, Isfarudi
Jurnal Matematika Sains dan Teknologi Vol 11 No 1 (2010)
Publisher : LPPM Universitas Terbuka

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Abstract

A very popular article by Baron and Kenny (1986), later extended by Kenny, Kashy, and Bolger (1998), recommended to social psychologists a test of mediation based on a set of steps involving correlations and regression weights. The serial published tests of mediation has come to be known as the Baron-Kenny approach. By the Baron-Kenny approach, a simple complete mediation is to be indicated which is a test of the direct path between an independent variable (X) and a dependent variable (Y) with a mediator variable (M) controlled is not significant. A simple mediation model has three correlations of their variables each. According to sequential regression analysis on a simple mediation model, a mediator M come after an independent variable X exist in the model, has a contribution of the mediator. Otherwise, sample size is a critical component to test as well as statistically significances. We argue the importance of investigating condition and interrelation of the three correlations, sequential contribution of the mediator, and sample size in the simple complete mediation cases by using hypotetical data generated by Microsoft Excel. We indicate some general consequences of simple complete mediation cases that are: (i) average of correlation XY is lower than average of correlation XM that lower than average of correlation MY; (ii) average contribution of mediator, indicated by R2 change, at interval of 23% up to 27%; (iii) distribution of effects X on Y when M controlled is influenced by sample size, the higher sample size, the lower distribution is; and (iv) average of mediation effects is at interval: 0.4 and above for levels of small sampel size (10 up to 40), between 0.2 and 0.4 for levels of medium sample size (50 up to 300), and under 0.2 for levels of large sample size (500 or above).  
BEBERAPA KONSEKUENSI SITUASI MEDIASI SEMPURNA PADA STRUKTUR KORELASI, KONTRIBUSI MEDIATOR, DAN UKURAN SAMPEL Deddy A Suhardi; Isfarudi Isfarudi
Jurnal Matematika Sains dan Teknologi Vol. 11 No. 1 (2010)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

A very popular article by Baron and Kenny (1986), later extended by Kenny, Kashy, and Bolger (1998), recommended to social psychologists a test of mediation based on a set of steps involving correlations and regression weights. The serial published tests of mediation has come to be known as the Baron-Kenny approach. By the Baron-Kenny approach, a simple complete mediation is to be indicated which is a test of the direct path between an independent variable (X) and a dependent variable (Y) with a mediator variable (M) controlled is not significant. A simple mediation model has three correlations of their variables each. According to sequential regression analysis on a simple mediation model, a mediator M come after an independent variable X exist in the model, has a contribution of the mediator. Otherwise, sample size is a critical component to test as well as statistically significances. We argue the importance of investigating condition and interrelation of the three correlations, sequential contribution of the mediator, and sample size in the simple complete mediation cases by using hypotetical data generated by Microsoft Excel. We indicate some general consequences of simple complete mediation cases that are: (i) average of correlation XY is lower than average of correlation XM that lower than average of correlation MY; (ii) average contribution of mediator, indicated by R2 change, at interval of 23% up to 27%; (iii) distribution of effects X on Y when M controlled is influenced by sample size, the higher sample size, the lower distribution is; and (iv) average of mediation effects is at interval: 0.4 and above for levels of small sampel size (10 up to 40), between 0.2 and 0.4 for levels of medium sample size (50 up to 300), and under 0.2 for levels of large sample size (500 or above).
EFEKTIVITAS VARIABEL MEDIATOR BERDASARKAN KONTRIBUSINYA DALAM MODEL MEDIASI SEDERHANA Deddy A Suhardi; Settings Isfarudi Isfarudi
Jurnal Matematika Sains dan Teknologi Vol. 10 No. 1 (2009)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (565.38 KB) | DOI: 10.33830/jmst.v10i1.566.2009

Abstract

Structurally relationship of variables is important in deeply analysis of path models, but the process of effect distribution must be concerned. In this situation, one or more variable would be a mediator variable which assessing effect of an independent to a dependent variable. We studied the simple mediation model that is one of path analytical models which contain of one independent variable, dependent variable and mediator variable. A necessary component of mediation is effectiveness that is a statistically significant indirect effect, formal significance tests of indirect effects are early conducted by Sobel (1982). According to sequential regression analysis on a simple mediation model, a mediator variable come after an independent variable exist in the model, the contribution of upcoming variable to the model could be obtained. We argue the importance of investigating empirical relationship between the significance of indirect effects and sequential contribution of mediator variable with a normal theory approach using Microsoft Excel simulation tools developed by Myerson (2000). We find that the higher contribution of mediator variable to the model, the more effectiveness is. This result comes up with three level correlation of independent and dependent variable which each 1000 times iteration that gives relatively immediate information about the recent empirical relationship between the significance of indirect effects and sequential contribution of mediator in the simple mediation models.
Co-Authors Anak Agung Gede Sugianthara Cicik Marantina Cicik Marantina* Deddy Ahmad Suhardi Dewi Juliah Ratnaningsih Ila - Fadila Ma’rifah, Ma’rifah Marsono Marsono Mulyanto Mulyanto Nuraini Soleiman Nurul Hidayat Rozi Djoko Arfiono Soleiman, Nuraini Suprayitno Suprayitno Usup Riassy Christa Yohanes Leonardus Sukestiyarno