tugas agus
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Transcript of tugas agus
SAVE OUTFILE='C:\Users\dc2\Documents\TUGAS.sav' /COMPRESSED. REGRESSION /DESCRIPTIVES MEAN STDDEV CORR SIG N /MISSING LISTWISE /STATISTICS COEFF OUTS CI(95) R ANOVA CHANGE /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Jumlahpengeluaranpertahun /METHOD=ENTER pangan liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan /SCATTERPLOT=(Jumlahpengeluaranpertahun ,*ZPRED) /RESIDUALS HISTOGRAM(ZRESID) NORMPROB(ZRESID).
Regression
Notes Output Created Comments Input Data Active Dataset Filter Weight Split File N of Rows in Working Data File Missing Value Handling Definition of Missing Cases Used User-defined missing values are treated as missing. Statistics are based on cases with no missing values for any variable used. C:\Users\dc2\Documents\TUGAS.sav DataSet0 5 15-Apr-2012 18:04:01
Syntax
REGRESSION /DESCRIPTIVES MEAN STDDEV CORR SIG N /MISSING LISTWISE /STATISTICS COEFF OUTS CI(95) R ANOVA CHANGE /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT Jumlahpengeluaranpertahun /METHOD=ENTER pangan liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan /SCATTERPLOT=(Jumlahpengeluara npertahun ,*ZPRED) /RESIDUALS HISTOGRAM(ZRESID) NORMPROB(ZRESID).
Resources
Processor Time Elapsed Time Memory Required Additional Memory Required for Residual Plots
00:00:01.295 00:00:04.901 5084 bytes 840 bytes
[DataSet0] C:\Users\dc2\Documents\TUGAS.sav
Warnings For the final model with dependent variable Jumlahpengeluaranpertahun, influence statistics cannot be computed because the fit is perfect.
Descriptive Statistics Mean Jumlahpengeluaranpertahun 76892858.40 Std. Deviation 6776051.172 N 5
pangan liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan
26360000.00 4440000.00 14580000.00 3460000.00 4337740.00 6268676.00 3553356.00 2755531.00 4488666.60 6648888.80
2710719.462 403732.585 3410571.800 320936.131 542491.049 456707.746 131675.790 162897.851 160131.914 316676.450
5 5 5 5 5 5 5 5 5 5
Correlations Jumlahpengelua ranpertahun Pearson Correlation Jumlahpengeluaranpertahun pangan liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan Sig. (1-tailed) Jumlahpengeluaranpertahun pangan liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan N Jumlahpengeluaranpertahun 1.000 .968 -.597 .985 .976 .926 .622 .584 .400 .145 -.728 . .003 .144 .001 .002 .012 .131 .150 .252 .408 .082 5 pangan .968 1.000 -.775 .910 .980 .962 .631 .486 .223 .294 -.680 .003 . .062 .016 .002 .004 .127 .203 .360 .316 .103 5 liburan -.597 -.775 1.000 -.451 -.698 -.781 -.429 -.050 .211 -.544 .287 .144 .062 . .223 .095 .059 .235 .468 .366 .172 .320 5 sandang .985 .910 -.451 1.000 .933 .862 .584 .644 .509 .051 -.731 .001 .016 .223 . .010 .030 .150 .120 .190 .467 .080 5
pangan liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan Correlations
5 5 5 5 5 5 5 5 5 5
5 5 5 5 5 5 5 5 5 5
5 5 5 5 5 5 5 5 5 5
5 5 5 5 5 5 5 5 5 5
bahanbakarkend kesehatan Pearson Correlation Jumlahpengeluaranpertahun pangan liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan Sig. (1-tailed) Jumlahpengeluaranpertahun pangan liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan N Jumlahpengeluaranpertahun pangan .976 .980 -.698 .933 1.000 .982 .745 .406 .212 .101 -.779 .002 .002 .095 .010 . .001 .074 .249 .366 .436 .060 5 5 listrik .926 .962 -.781 .862 .982 1.000 .760 .256 .118 .095 -.724 .012 .004 .059 .030 .001 . .068 .339 .425 .439 .083 5 5 araan .622 .631 -.429 .584 .745 .760 1.000 -.134 -.296 -.395 -.926 .131 .127 .235 .150 .074 .068 . .415 .314 .255 .012 5 5
liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan Correlations
5 5 5 5 5 5 5 5 5
5 5 5 5 5 5 5 5 5
5 5 5 5 5 5 5 5 5
bahanbakardap ur Pearson Correlation Jumlahpengeluaranpertahun pangan liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan Sig. (1-tailed) Jumlahpengeluaranpertahun pangan liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan N Jumlahpengeluaranpertahun pangan liburan .584 .486 -.050 .644 .406 .256 -.134 1.000 .705 .455 -.202 .150 .203 .468 .120 .249 .339 .415 . .092 .221 .372 5 5 5
perawatanruma h .400 .223 .211 .509 .212 .118 -.296 .705 1.000 .030 .080 .252 .360 .366 .190 .366 .425 .314 .092 . .481 .449 5 5 5
sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan Correlations
5 5 5 5 5 5 5 5
5 5 5 5 5 5 5 5
perawatankenda raan Pearson Correlation Jumlahpengeluaranpertahun pangan liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan Sig. (1-tailed) Jumlahpengeluaranpertahun pangan liburan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan N Jumlahpengeluaranpertahun pangan liburan sandang .145 .294 -.544 .051 .101 .095 -.395 .455 .030 1.000 .325 .408 .316 .172 .467 .436 .439 .255 .221 .481 . .297 5 5 5 5 biayapendidikan -.728 -.680 .287 -.731 -.779 -.724 -.926 -.202 .080 .325 1.000 .082 .103 .320 .080 .060 .083 .012 .372 .449 .297 . 5 5 5 5
kesehatan listrik bahanbakarkendaraan bahanbakardapur perawatanrumah perawatankendaraan biayapendidikan
5 5 5 5 5 5 5
5 5 5 5 5 5 5
Variables Entered/Removedb Model Variables Entered Variables Removed Method . Enter
d 1 i m e n s i o n 0
biayapendidikan , perawatanruma h, perawatankenda raan, liburana
a. Tolerance = .000 limits reached. b. Dependent Variable: Jumlahpengeluaranpertahun
Model Summaryb Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1
d 1 i m e n s i o n 0
1.000a
1.000
.
.
1.000
.
4
a. Predictors: (Constant), biayapendidikan, perawatanrumah, perawatankendaraan, liburan b. Dependent Variable: Jumlahpengeluaranpertahun Model Summaryb Model Change Statistics df2 Sig. F Change 0 .
d 1 i m e n s i o n 0
b. Dependent Variable: Jumlahpengeluaranpertahun
ANOVAb Model 1 Regression Residual Total Sum of Squares 1.837E14 .000 1.837E14 df 4 0 4 Mean Square 4.591E13 . F . Sig. .a
a. Predictors: (Constant), biayapendidikan, perawatanrumah, perawatankendaraan, liburan b. Dependent Variable: Jumlahpengeluaranpertahun
Coefficientsa Model Unstandardized Coefficients B 1 (Constant) liburan perawatanrumah perawatankendaraan biayapendidikan 1.276E8 -8.033 22.941 3.528 -14.157 Std. Error .000 .000 .000 .000 .000 -.479 .552 .083 -.662 Standardized Coefficients Beta . . . . . . . . . . t Sig.
a. Dependent Variable: Jumlahpengeluaranpertahun Coefficientsa Model 95.0% Confidence Interval for B Lower Bound 1 (Constant) liburan perawatanrumah perawatankendaraan biayapendidikan 1.276E8 -8.033 22.941 3.528 -14.157 Upper Bound 1.276E8 -8.033 22.941 3.528 -14.157
a. Dependent Variable: Jumlahpengeluaranpertahun
Excluded Variablesb Model Beta In t Sig. Partial Correlation Collinearity Statistics Tolerance 1 pangan sandang kesehatan listrik bahanbakarkendaraan bahanbakardapur .a .a . .a a
. . . . . .
. . . . . .
. . . . . .
.000 .000 .000 .000 .000 .000
.a .a
a. Predictors in the Model: (Constant), biayapendidikan, perawatanrumah, perawatankendaraan, liburan b. Dependent Variable: Jumlahpengeluaranpertahun
Residuals Statisticsa
Minimum Predicted Value Residual Std. Predicted Value Std. Residual 66900000.00 .000 -1.475 .
Maximum 83744288.00 .000 1.011 .
Mean 76892858.40 .000 .000 .
Std. Deviation 6776051.172 .000 1.000 .
N 5 5 5 0
a. Dependent Variable: Jumlahpengeluaranpertahun
Charts
GET FILE='I:\TES.sav'. DATASET NAME DataSet1 WINDOW=FRONT.
REGRESSION /DESCRIPTIVES MEAN STDDEV CORR SIG N /MISSING LISTWISE /STATISTICS COEFF OUTS CI(95) R ANOVA CHANGE /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT JUMLAH_YANG_TIDAK_LULUS /METHOD=ENTER SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 SMAN_9 SMAN_10 /SCATTERPLOT=(JUMLAH_YANG_TIDAK_LULUS ,*ZPRED) /RESIDUALS HISTOGRAM(ZRESID) NORMPROB(ZRESID).
Regression
Notes Output Created Comments Input Data Active Dataset Filter Weight Split File N of Rows in Working Data File Missing Value Handling Definition of Missing Cases Used User-defined missing values are treated as missing. Statistics are based on cases with no missing values for any variable used. I:\TES.sav DataSet1 11 15-Apr-2012 18:12:37
Syntax
REGRESSION /DESCRIPTIVES MEAN STDDEV CORR SIG N /MISSING LISTWISE /STATISTICS COEFF OUTS CI(95) R ANOVA CHANGE /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT JUMLAH_YANG_TIDAK_LULUS /METHOD=ENTER SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 SMAN_9 SMAN_10 /SCATTERPLOT=(JUMLAH_YANG_T IDAK_LULUS ,*ZPRED) /RESIDUALS HISTOGRAM(ZRESID) NORMPROB(ZRESID).
Resources
Processor Time Elapsed Time Memory Required Additional Memory Required for Residual Plots
00:00:00.312 00:00:00.460 5084 bytes 840 bytes
[DataSet1] I:\TES.sav
Warnings For the final model with dependent variable JUMLAH_YANG_TIDAK_LULUS, influence statistics cannot be computed because the fit is perfect.
Descriptive Statistics Mean JUMLAH_YANG_TIDAK_LU LUS 16.2727 Std. Deviation 5.23624 N 11
SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 SMAN_9 SMAN_10
2.8182 2.0909 .4545 2.2727 .7273 1.7273 1.6364 1.2727 2.0909 1.1818
2.04050 1.04447 .68755 1.79393 .90453 1.34840 1.62928 1.19087 1.75810 1.16775
11 11 11 11 11 11 11 11 11 11
Correlations JUMLAH_YANG _TIDAK_LULUS Pearson Correlation JUMLAH_YANG_TIDAK_LU LUS SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 SMAN_9 SMAN_10 Sig. (1-tailed) JUMLAH_YANG_TIDAK_LU LUS SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 SMAN_9 .054 .081 .488 .252 .407 .009 .221 .130 .004 . .331 .492 .274 .286 .026 .154 .179 .175 .331 . .263 .201 .411 .360 .040 .185 .213 .492 .263 . .026 .124 .454 .481 .195 .448 .511 .452 -.010 .225 .081 .691 .259 .372 .747 .122 . 1.000 .149 -.006 -.204 -.192 .598 .339 -.307 .312 -.446 .054 .149 1.000 .215 -.281 -.077 -.123 .550 .300 .267 -.097 .081 -.006 .215 1.000 -.597 .380 .039 -.016 -.289 .045 .011 .488 1.000 SMAN_1 .511 SMAN_2 .452 SMAN_3 -.010
SMAN_10 N JUMLAH_YANG_TIDAK_LU LUS SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 SMAN_9 SMAN_10 Correlations SMAN_4 Pearson Correlation JUMLAH_YANG_TIDAK_LU LUS SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 SMAN_9 SMAN_10 Sig. (1-tailed) JUMLAH_YANG_TIDAK_LU LUS SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 .274 .201 .026 . .222 .413 .496 .194 -.204 -.281 -.597 1.000 -.258 .075 .003 .289 .182 -.026 .252 .225
.361 11
.084 11
.388 11
.487 11
11 11 11 11 11 11 11 11 11 11
11 11 11 11 11 11 11 11 11 11
11 11 11 11 11 11 11 11 11 11
11 11 11 11 11 11 11 11 11 11
SMAN_5 .081
SMAN_6 .691
SMAN_7 .259
-.192 -.077 .380 -.258 1.000 .261 -.685 .262 .143 .336 .407
.598 -.123 .039 .075 .261 1.000 -.050 .113 .391 .035 .009
.339 .550 -.016 .003 -.685 -.050 1.000 -.047 -.162 -.435 .221
.286 .411 .124 .222 . .219 .010 .219
.026 .360 .454 .413 .219 . .442 .370
.154 .040 .481 .496 .010 .442 . .446
SMAN_9 SMAN_10 N JUMLAH_YANG_TIDAK_LU LUS SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 SMAN_9 SMAN_10 Correlations
.297 .470 11
.338 .156 11
.117 .460 11
.317 .091 11
11 11 11 11 11 11 11 11 11 11
11 11 11 11 11 11 11 11 11 11
11 11 11 11 11 11 11 11 11 11
11 11 11 11 11 11 11 11 11 11
SMAN_8 Pearson Correlation JUMLAH_YANG_TIDAK_LU LUS SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 SMAN_9 SMAN_10 Sig. (1-tailed) JUMLAH_YANG_TIDAK_LU LUS SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 .179 .185 .195 .194 .219 .370 .446 -.307 .300 -.289 .289 .262 .113 -.047 1.000 .082 .248 .130 .372
SMAN_9 .747
SMAN_10 .122
.312 .267 .045 .182 .143 .391 -.162 .082 1.000 .332 .004
-.446 -.097 .011 -.026 .336 .035 -.435 .248 .332 1.000 .361
.175 .213 .448 .297 .338 .117 .317
.084 .388 .487 .470 .156 .460 .091
SMAN_8 SMAN_9 SMAN_10 N JUMLAH_YANG_TIDAK_LU LUS SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 SMAN_9 SMAN_10
. .405 .231 11
.405 . .159 11
.231 .159 . 11
11 11 11 11 11 11 11 11 11 11
11 11 11 11 11 11 11 11 11 11
11 11 11 11 11 11 11 11 11 11
Variables Entered/Removedb Model Variables Entered Variables Removed Method . Enter
d 1 i m e n s i o n 0
SMAN_10, SMAN_3, SMAN_6, SMAN_2, SMAN_5, SMAN_9, SMAN_4, SMAN_8, SMAN_7, SMAN_1a
a. All requested variables entered. b. Dependent Variable: JUMLAH_YANG_TIDAK_LULUS
Model Summaryb Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics
R Square Change F Change . df1 10
d 1 i m e n s i o n 0
1.000a
1.000
.
.
1.000
a. Predictors: (Constant), SMAN_10, SMAN_3, SMAN_6, SMAN_2, SMAN_5, SMAN_9, SMAN_4, SMAN_8, SMAN_7, SMAN_1 b. Dependent Variable: JUMLAH_YANG_TIDAK_LULUS Model Summaryb Model Change Statistics df2 Sig. F Change 0 .
d 1 i m e n s i o n 0
b. Dependent Variable: JUMLAH_YANG_TIDAK_LULUS
ANOVAb Model 1 Regression Residual Total Sum of Squares 274.182 .000 274.182 df 10 0 10 Mean Square 27.418 . F . Sig. .a
a. Predictors: (Constant), SMAN_10, SMAN_3, SMAN_6, SMAN_2, SMAN_5, SMAN_9, SMAN_4, SMAN_8, SMAN_7, SMAN_1 b. Dependent Variable: JUMLAH_YANG_TIDAK_LULUS
Coefficientsa Model Unstandardized Coefficients B 1 (Constant) SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 SMAN_9 SMAN_10 -3.307E-15 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 Std. Error .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .390 .199 .131 .343 .173 .258 .311 .227 .336 .223 Standardized Coefficients Beta . . . . . . . . . . . . . . . . . . . . . . t Sig.
a. Dependent Variable: JUMLAH_YANG_TIDAK_LULUS Coefficientsa Model 95.0% Confidence Interval for B Lower Bound 1 (Constant) SMAN_1 SMAN_2 SMAN_3 SMAN_4 SMAN_5 SMAN_6 SMAN_7 SMAN_8 SMAN_9 SMAN_10 .000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 Upper Bound .000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
a. Dependent Variable: JUMLAH_YANG_TIDAK_LULUS
Residuals Statisticsa Minimum Predicted Value Residual Std. Predicted Value Std. Residual 5.0000 .00000 -2.153 . Maximum 23.0000 .00000 1.285 . Mean 16.2727 .00000 .000 . Std. Deviation 5.23624 .00000 1.000 . N 11 11 11 0
a. Dependent Variable: JUMLAH_YANG_TIDAK_LULUS
Charts
* Chart Builder. GGRAPH /GRAPHDATASET NAME="graphdataset" VARIABLES=TAHUN MEAN(SMAN_1) MEAN(SMAN_2) MEAN(SMAN_3) MEAN(SMAN_4) MEAN(SMAN_5) MEAN(SMAN_6) MEAN(SMAN_7) MEAN(SMAN_8) MEAN(SMAN_9) MEAN(SMAN_10) MISSING=LISTWISE REPORTMISSING=NO TRANSFORM=VARSTOCASES(SUMMARY="#SUMMARY" INDEX="#INDEX") /GRAPHSPEC SOURCE=INLINE. BEGIN GPL SOURCE: s=userSource(id("graphdataset")) DATA: TAHUN=col(source(s), name("TAHUN"), unit.category()) DATA: SUMMARY=col(source(s), name("#SUMMARY")) DATA: INDEX=col(source(s), name("#INDEX"), unit.category()) COORD: rect(dim(1,2), cluster(3,0)) GUIDE: axis(dim(3), label("TAHUN")) GUIDE: axis(dim(2), label("Mean")) GUIDE: legend(aesthetic(aesthetic.color.interior), label("")) SCALE: linear(dim(2), include(0)) SCALE: cat(aesthetic(aesthetic.color.interior), include("0", "1", "2", "3", "4", "5", "6", "7", "8", "9")) SCALE: cat(dim(1), include("0", "1", "2", "3", "4", "5", "6", "7", "8", "9")) ELEMENT: interval(position(INDEX*SUMMARY*TAHUN), color.interior(INDEX), shape.interior(shape.square)) END GPL.
GGraph
Notes Output Created Comments Input Data Active Dataset Filter Weight Split File N of Rows in Working Data File I:\TES.sav DataSet1 11 15-Apr-2012 18:17:16
Syntax
GGRAPH /GRAPHDATASET NAME="graphdataset" VARIABLES=TAHUN MEAN(SMAN_1) MEAN(SMAN_2) MEAN(SMAN_3) MEAN(SMAN_4) MEAN(SMAN_5) MEAN(SMAN_6) MEAN(SMAN_7) MEAN(SMAN_8) MEAN(SMAN_9) MEAN(SMAN_10) MISSING=LISTWISE REPORTMISSING=NO TRANSFORM=VARSTOCASES(SU MMARY="#SUMMARY" INDEX="#INDEX") /GRAPHSPEC SOURCE=INLINE. BEGIN GPL SOURCE: s=userSource(id("graphdataset")) DATA: TAHUN=col(source(s), name("TAHUN"), unit.category()) DATA: SUMMARY=col(source(s), name("#SUMMARY")) DATA: INDEX=col(source(s), name("#INDEX"), unit.category()) COORD: rect(dim(1,2), cluster(3,0)) GUIDE: axis(dim(3), label("TAHUN")) GUIDE: axis(dim(2), label("Mean")) GUIDE: legend(aesthetic(aesthetic.color.interior ), label("")) SCALE: linear(dim(2), include(0)) SCALE: cat(aesthetic(aesthetic.color.interior), include("0", "1", "2", "3", "4", "5", "6", "7", "8", "9")) SCALE: cat(dim(1), include("0", "1", "2", "3", "4", "5", "6", "7", "8", "9")) ELEMENT: interval(position(INDEX*SUMMARY*TA HUN), color.interior(INDEX), shape.interior(shape.square))
Resources
Processor Time Elapsed Time
00:00:00.640 00:00:01.239
[DataSet1] I:\TES.sav
* Chart Builder. GGRAPH /GRAPHDATASET NAME="graphdataset" VARIABLES=SUM(SMAN_1) SUM(SMAN_2) SUM(SMAN_3) SUM(SMAN_4) SUM(SMAN_5) SUM(SMAN_6) SUM(SMAN_7) SUM(SMAN_8) SUM(SMAN_9) SUM(SMAN_10) MISSING=LISTWISE REPORTMISSING=NO TRANSFORM=VARSTOCASES(SUMMARY="#SUMMARY" INDEX="#INDEX") /GRAPHSPEC SOURCE=INLINE. BEGIN GPL SOURCE: s=userSource(id("graphdataset")) DATA: SUMMARY=col(source(s), name("#SUMMARY"))
DATA: INDEX=col(source(s), name("#INDEX"), unit.category()) COORD: polar.theta(startAngle(0)) GUIDE: axis(dim(1), null()) GUIDE: legend(aesthetic(aesthetic.color.interior), label("TAHUN")) SCALE: linear(dim(1), dataMinimum(), dataMaximum()) SCALE: cat(aesthetic(aesthetic.color.interior), include("0", "1", "2", "3", "4", "5", "6", "7", "8", "9")) ELEMENT: interval.stack(position(summary.percent(SUMMARY))), color.interior(INDEX)) END GPL.
GGraph
Notes Output Created Comments Input Data Active Dataset Filter Weight Split File N of Rows in Working Data File I:\TES.sav DataSet1 11 15-Apr-2012 18:19:47
Syntax
GGRAPH /GRAPHDATASET NAME="graphdataset" VARIABLES=SUM(SMAN_1) SUM(SMAN_2) SUM(SMAN_3) SUM(SMAN_4) SUM(SMAN_5) SUM(SMAN_6) SUM(SMAN_7) SUM(SMAN_8) SUM(SMAN_9) SUM(SMAN_10) MISSING=LISTWISE REPORTMISSING=NO TRANSFORM=VARSTOCASES(SU MMARY="#SUMMARY" INDEX="#INDEX") /GRAPHSPEC SOURCE=INLINE. BEGIN GPL SOURCE: s=userSource(id("graphdataset")) DATA: SUMMARY=col(source(s), name("#SUMMARY")) DATA: INDEX=col(source(s), name("#INDEX"), unit.category()) COORD: polar.theta(startAngle(0)) GUIDE: axis(dim(1), null()) GUIDE: legend(aesthetic(aesthetic.color.interior ), label("TAHUN")) SCALE: linear(dim(1), dataMinimum(), dataMaximum()) SCALE: cat(aesthetic(aesthetic.color.interior), include("0", "1", "2", "3", "4", "5", "6", "7", "8", "9")) ELEMENT: interval.stack(position(summary.percent (SUMMARY))), color.interior(INDEX)) END GPL.
Resources
Processor Time Elapsed Time
00:00:00.265 00:00:00.320
[DataSet1] I:\TES.sav
