uji validitas
1
Correlations 1 -.408 1.000** -.408 .408 .500 .500 .500 1.000** 1.000** .829** 1.000** 1.000** .829** .829** .829** .829** .829** 1.000** .829** .931** . .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 -.408 1 -.408 1.000** -1.000** -.816** -.816** -.816** -.408 -.408 -.185 -.408 -.408 -.185 -.185 -.185 -.185 -.185 -.408 -.185 -.658* .242 . .242 . . .004 .004 .004 .242 .242 .610 .242 .242 .610 .610 .610 .610 .610 .242 .610 .039 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 1.000** -.408 1 -.408 .408 .500 .500 .500 1.000** 1.000** .829** 1.000** 1.000** .829** .829** .829** .829** .829** 1.000** .829** .931** . .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 -.408 1.000** -.408 1 -1.000** -.816** -.816** -.816** -.408 -.408 -.185 -.408 -.408 -.185 -.185 -.185 -.185 -.185 -.408 -.185 -.658* .242 . .242 . . .004 .004 .004 .242 .242 .610 .242 .242 .610 .610 .610 .610 .610 .242 .610 .039 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 .408 -1.000** .408 -1.000** 1 .816** .816** .816** .408 .408 .185 .408 .408 .185 .185 .185 .185 .185 .408 .185 .658* .242 . .242 . . .004 .004 .004 .242 .242 .610 .242 .242 .610 .610 .610 .610 .610 .242 .610 .039 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 .500 -.816** .500 -.816** .816** 1 1.000** 1.000** .500 .500 .302 .500 .500 .302 .302 .302 .302 .302 .500 .302 .704* .141 .004 .141 .004 .004 . . . .141 .141 .397 .141 .141 .397 .397 .397 .397 .397 .141 .397 .023 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 .500 -.816** .500 -.816** .816** 1.000** 1 1.000** .500 .500 .302 .500 .500 .302 .302 .302 .302 .302 .500 .302 .704* .141 .004 .141 .004 .004 . . . .141 .141 .397 .141 .141 .397 .397 .397 .397 .397 .141 .397 .023 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 .500 -.816** .500 -.816** .816** 1.000** 1.000** 1 .500 .500 .302 .500 .500 .302 .302 .302 .302 .302 .500 .302 .704* .141 .004 .141 .004 .004 . . . .141 .141 .397 .141 .141 .397 .397 .397 .397 .397 .141 .397 .023 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 1.000** -.408 1.000** -.408 .408 .500 .500 .500 1 1.000** .829** 1.000** 1.000** .829** .829** .829** .829** .829** 1.000** .829** .931** . .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 1.000** -.408 1.000** -.408 .408 .500 .500 .500 1.000** 1 .829** 1.000** 1.000** .829** .829** .829** .829** .829** 1.000** .829** .931** . .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 .829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1 .829** .829** 1.000** 1.000** 1.000** 1.000** 1.000** .829** 1.000** .780** .003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 1.000** -.408 1.000** -.408 .408 .500 .500 .500 1.000** 1.000** .829** 1 1.000** .829** .829** .829** .829** .829** 1.000** .829** .931** . .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 1.000** -.408 1.000** -.408 .408 .500 .500 .500 1.000** 1.000** .829** 1.000** 1 .829** .829** .829** .829** .829** 1.000** .829** .931** . .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 .829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1.000** .829** .829** 1 1.000** 1.000** 1.000** 1.000** .829** 1.000** .780** .003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 .829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1.000** .829** .829** 1.000** 1 1.000** 1.000** 1.000** .829** 1.000** .780** .003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 .829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1.000** .829** .829** 1.000** 1.000** 1 1.000** 1.000** .829** 1.000** .780** .003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 .829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1.000** .829** .829** 1.000** 1.000** 1.000** 1 1.000** .829** 1.000** .780** .003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 .829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1.000** .829** .829** 1.000** 1.000** 1.000** 1.000** 1 .829** 1.000** .780** .003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 1.000** -.408 1.000** -.408 .408 .500 .500 .500 1.000** 1.000** .829** 1.000** 1.000** .829** .829** .829** .829** .829** 1 .829** .931** . .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 .829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1.000** .829** .829** 1.000** 1.000** 1.000** 1.000** 1.000** .829** 1 .780** .003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 .931** -.658* .931** -.658* .658* .704* .704* .704* .931** .931** .780** .931** .931** .780** .780** .780** .780** .780** .931** .780** 1 .000 .039 .000 .039 .039 .023 .023 .023 .000 .000 .008 .000 .000 .008 .008 .008 .008 .008 .000 .008 . 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 p11 p12 p13 p14 p15 p16 p17 p18 p19 p20 ptot p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 p11 p12 p13 p14 p15 p16 p17 p18 p19 p20 ptot Correlation is significant at the 0.01 level (2-tailed). **. Correlation is significant at the 0.05 level (2-tailed). *.
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Transcript of uji validitas
Correlations
1 -.408 1.000** -.408 .408 .500 .500 .500 1.000** 1.000** .829** 1.000** 1.000** .829** .829** .829** .829** .829** 1.000** .829** .931**
. .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
-.408 1 -.408 1.000** -1.000** -.816** -.816** -.816** -.408 -.408 -.185 -.408 -.408 -.185 -.185 -.185 -.185 -.185 -.408 -.185 -.658*
.242 . .242 . . .004 .004 .004 .242 .242 .610 .242 .242 .610 .610 .610 .610 .610 .242 .610 .039
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
1.000** -.408 1 -.408 .408 .500 .500 .500 1.000** 1.000** .829** 1.000** 1.000** .829** .829** .829** .829** .829** 1.000** .829** .931**
. .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
-.408 1.000** -.408 1 -1.000** -.816** -.816** -.816** -.408 -.408 -.185 -.408 -.408 -.185 -.185 -.185 -.185 -.185 -.408 -.185 -.658*
.242 . .242 . . .004 .004 .004 .242 .242 .610 .242 .242 .610 .610 .610 .610 .610 .242 .610 .039
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
.408 -1.000** .408 -1.000** 1 .816** .816** .816** .408 .408 .185 .408 .408 .185 .185 .185 .185 .185 .408 .185 .658*
.242 . .242 . . .004 .004 .004 .242 .242 .610 .242 .242 .610 .610 .610 .610 .610 .242 .610 .039
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
.500 -.816** .500 -.816** .816** 1 1.000** 1.000** .500 .500 .302 .500 .500 .302 .302 .302 .302 .302 .500 .302 .704*
.141 .004 .141 .004 .004 . . . .141 .141 .397 .141 .141 .397 .397 .397 .397 .397 .141 .397 .023
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
.500 -.816** .500 -.816** .816** 1.000** 1 1.000** .500 .500 .302 .500 .500 .302 .302 .302 .302 .302 .500 .302 .704*
.141 .004 .141 .004 .004 . . . .141 .141 .397 .141 .141 .397 .397 .397 .397 .397 .141 .397 .023
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
.500 -.816** .500 -.816** .816** 1.000** 1.000** 1 .500 .500 .302 .500 .500 .302 .302 .302 .302 .302 .500 .302 .704*
.141 .004 .141 .004 .004 . . . .141 .141 .397 .141 .141 .397 .397 .397 .397 .397 .141 .397 .023
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
1.000** -.408 1.000** -.408 .408 .500 .500 .500 1 1.000** .829** 1.000** 1.000** .829** .829** .829** .829** .829** 1.000** .829** .931**
. .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
1.000** -.408 1.000** -.408 .408 .500 .500 .500 1.000** 1 .829** 1.000** 1.000** .829** .829** .829** .829** .829** 1.000** .829** .931**
. .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
.829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1 .829** .829** 1.000** 1.000** 1.000** 1.000** 1.000** .829** 1.000** .780**
.003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
1.000** -.408 1.000** -.408 .408 .500 .500 .500 1.000** 1.000** .829** 1 1.000** .829** .829** .829** .829** .829** 1.000** .829** .931**
. .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
1.000** -.408 1.000** -.408 .408 .500 .500 .500 1.000** 1.000** .829** 1.000** 1 .829** .829** .829** .829** .829** 1.000** .829** .931**
. .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
.829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1.000** .829** .829** 1 1.000** 1.000** 1.000** 1.000** .829** 1.000** .780**
.003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
.829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1.000** .829** .829** 1.000** 1 1.000** 1.000** 1.000** .829** 1.000** .780**
.003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
.829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1.000** .829** .829** 1.000** 1.000** 1 1.000** 1.000** .829** 1.000** .780**
.003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
.829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1.000** .829** .829** 1.000** 1.000** 1.000** 1 1.000** .829** 1.000** .780**
.003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
.829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1.000** .829** .829** 1.000** 1.000** 1.000** 1.000** 1 .829** 1.000** .780**
.003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
1.000** -.408 1.000** -.408 .408 .500 .500 .500 1.000** 1.000** .829** 1.000** 1.000** .829** .829** .829** .829** .829** 1 .829** .931**
. .242 . .242 .242 .141 .141 .141 . . .003 . . .003 .003 .003 .003 .003 . .003 .000
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
.829** -.185 .829** -.185 .185 .302 .302 .302 .829** .829** 1.000** .829** .829** 1.000** 1.000** 1.000** 1.000** 1.000** .829** 1 .780**
.003 .610 .003 .610 .610 .397 .397 .397 .003 .003 . .003 .003 . . . . . .003 . .008
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
.931** -.658* .931** -.658* .658* .704* .704* .704* .931** .931** .780** .931** .931** .780** .780** .780** .780** .780** .931** .780** 1
.000 .039 .000 .039 .039 .023 .023 .023 .000 .000 .008 .000 .000 .008 .008 .008 .008 .008 .000 .008 .
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
p1
p2
p3
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p11
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p20
ptot
p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 p11 p12 p13 p14 p15 p16 p17 p18 p19 p20 ptot
Correlation is significant at the 0.01 level (2-tailed).**.
Correlation is significant at the 0.05 level (2-tailed).*.
