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Menghitung Sumbangan Efektif
Model Summaryb
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate
1 .445a .198 .169 9.30155
a. Preditors! "#o$sta$t%& Stress'(erja&
(eerdasa$'Emosio$al
). *e+e$de$t ,aria)le! (i$erja
ANOVAb
Model Sum of Squares df Mea$ Square - Si.
1 Reressio$ 1193.9/6 / 596.963 6.900 .00/a
Residual 4845.05 56 86.519
otal 6038.983 58
a. Preditors! "#o$sta$t%& Stress'(erja&
(eerdasa$'Emosio$al
). *e+e$de$t ,aria)le! (i$erja
Coefficientsa
Model
2$sta$dardied
#oeffiie$ts
Sta$dardied
#oeffiie$ts
t Si. Std. Error eta
1 "#o$sta$t% 31.44 11.498 /.61 .008
(eerdasa$'Emosio$al ./// .084 .318 /.651 .010
Stress'(erja .59 ./50 ./8 /.391 .0/0
a. *e+e$de$t ,aria)le! (i$erja
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Correlations
(eerdasa$'Em
osio$al Stress'(erja (i$erja
(eerdasa$'Emosio$al Pearso$ #orrelatio$ 1 .0 .340
Si. "/tailed% .563 .008
Sum of Squares a$d #ross
+roduts1/36.983 319.085 /.94/E3
#o7aria$e /13.396 5.501 50./4
59 59 59
Stress'(erja Pearso$ #orrelatio$ .0 1 .311
Si. "/tailed% .563 .016
Sum of Squares a$d #ross
+roduts319.085 1394.56 903.915
#o7aria$e 5.501 /4.044 15.585
59 59 59
(i$erja Pearso$ #orrelatio$ .340 .311 1
Si. "/tailed% .008 .016
Sum of Squares a$d #ross
+roduts/94/.01 903.915 6.039E3
#o7aria$e 50./4 15.585 104.1/0
59 59 59
. #orrelatio$ is si$ifia$t at the 0.01 le7el "/tailed%.
. #orrelatio$ is si$ifia$t at the 0.05 le7el "/tailed%.
(om+o$e$ ) #ross Produt Reresi Sum). Efetif
otal
(eerdasa$
Emosio$al
0./// /94/ 1193.9/6 19.8:
Stress (erja 0.59 903
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SE=|bx 1CrossProductR2
Regression |x100
);1 < (oefisie$ ) om+o$e$ ;
#ross Produt < ross +rodut om+o$e$ ;
Reressio$ < $ilai reresi
R/< Sum)a$a$ Efetif otal
SE Kecerdasan Emosional=
|0.222x 2942x 0.198
1193.926
|x100=10.83
SE Stress Kerja=|0.597x 903x 0.1981193.926 |x 100=8.95
(edua Sum)a$a$ Efetif di atas telah dida+ata$ se)aai )eriut
!
(om+o$e$ Sia+ Sum)a$a$ Efetif (om+o$e$
(eerdasa$ Emosio$a= 10.83:
Stress (erja 8.95:otal 19.8:
