tugas sub 2 wiwik anggraini

TUGAS STATISTIK

MAGISTER AKUNTANSI

Disusun Oleh :Wiwik Anggraini NIM. 1410245143

FAKULTAS EKONOMI UNIVERSITAS RIAU

PEKANBARU

2014ANALYSIS JURNAL PATH

1. Faktor penyebab kebangkrutan di Perusahaan Property and Real Estate menggunakan data keuangan tahun 2012.

Adapun variabel dependen dan independennya :

X1 = working capital/total asset

X2 = retained earning/total asset

X3 = EBIT/total asset

X4 = market value equity/book value of total liabilities

X5 = sales/total asset

X6 = current ratio

X7 = quick ratio

X8 = return on asset

X9 = return on equity

X10 = zcore

Y = Berpotensi bangkrut/tidak

Gambar

X10X1X1+X10X2X2+X10X3X3+X10X4X4+X10X5X5+X10X6X6+X10X7X7+X10X8X8+X10X9X9+X10X10X10+X10y+X1X1+yX2X2+yX3X3+yX4X4+yX5X5+yX6X6+yX7X7+yX8X8+yX9X9+yX10X10+yy+Kemudian Data diinput ke excel :NoPerusahaanX1X2X3X4X5X6X7X8X9X10

1PT Adhi Karya (Persero) Tbk0.130.070.020.111.30.090.020.151.31.71

2PT Agung Podomoro Group,Tbk-0.33-3.27-0.19-0.920.14-3.75-0.1-0.930.16-6.01

3PT Bhuawanatala Indah Permai Tbk0.420.070.073.020.090.120.056.940.092.73

4PT Bakrieland Development Tbk. 0.380.090.070.540.980.120.260.820.692.12

5PT Ciputra Development Tbk. 0.270.10.120.591.710.160.090.491.382.94

6PT Ciputra Property Tbk0.21-0.05-0.05-3.70.020.090.084.860.03-2.19

7PT Ciputra Surya Tbk.-0.010.000.01-0.40.130.110.10.580.31-0.09

8PT Citraland, Tbk -0.12-0.060.01-0.080.780.000.080.060.710.52

9PT Duta Pertiwi Tbk. 0.240.080.040.221.420.120.080.521.342.08

10PT Gowa Makassar Tourism Development Tbk.0.280.040.040.31.140.10.080.30.961.86

11PT Indonesia Prima Property Tbk.0.10.140.070.41.150.120.050.470.971.82

12PT Intiland Development Tbk. 0.320.120.051.410.090.120.031.90.071.65

13PT Jababeka Tbk. 0.260.120.060.820.690.140.040.020.481.17

14PT Jakarta International Hotel & Development Tbk. 0.210.160.090.391.380.180.050.560.911.91

15PT Jakarta Setiabudi Internasional Tbk.0.170.090.081.470.030.120.035.670.037.37

16PT Jaya Konstruksi Manggala Pratama Tbk0.010.110.10.920.310.160.090.610.211.21

17PT Jaya Real Property Tbk. 0.010.030.080.190.710.160.141.60.552.5

18PT Lamicitra Nusantara Tbk. 0.290.130.080.880.970.130.092.260.662.82

19PT Lippo Cikarang Tbk. 0.240.10.080.930.960.090.051.10.581.59

20PT Lippo Karawaci Tbk. 1.97-0.4-0.920.14-3.75-0.1-0.930.160.056.94

21PT Mas Murni Indonesia Tbk. 0.14-0.083.020.090.120.056.940.090.260.82

22PT Metro Supermarket Realty Tbk. 4.960.220.540.980.120.260.820.690.090.49

23PT MNC Land Tbk1.850.30.591.710.160.090.491.380.084.86

24PT Modernland Realty Tbk. 3.01-0.05-3.70.020.090.084.860.030.10.58

25PT Nusa Konstruksi Enjiniring Tbk3.410-0.40.130.110.10.580.310.080.06

26PT Pakuwon Jati Tbk. 0.8-0.06-0.080.780.80.080.060.710.910.52

27PT Pembangunan Jaya Ancol Tbk.0.82-0.050.221.420.120.070.521.340.250.3

28PT Pudjiadi & Sons Tbk. 2.450.010.31.140.10.240.30.960.050.47

29PT Ristia Bintang Mahkotasejati Tbk.1.950.010.41.150.180.050.470.970.031.9

30PT Sentul City Tbk. -0.33-3.27-0.19-0.920.120.031.90.070.116.94

31PT Summarecon Agung Tbk. 0.420.070.073.020.140.040.020.480.260.82

32PT Suryainti Permata Tbk. 0.380.090.070.540.180.050.560.910.090.49

33PT Suryamas Dutamakmur Tbk.0.270.10.120.590.120.0311.670.030.084.86

34PT Surya Semesta Internusa Tbk0.21-0.12-0.08-3.70.260.820.690.080.520.58

35PT Total Bangun Persada Tbk-0.010.03-0.12-0.40.090.491.380.080.30.06

36PT Wijaya Karya (Persero) Tbk0.270.10.120.591.710.160.090.491.382.94

Data diatas diinput ke spss sehingga menghasilkan variabel view sebagai berikut :

2. UJI NORMALITASREGRESSION

/MISSING LISTWISE

/STATISTICS COEFF OUTS R ANOVA COLLIN TOL

/CRITERIA=PIN(.05) POUT(.10)

/NOORIGIN

/DEPENDENT X10

/METHOD=ENTER X1 X2 X3 X4 X5 X6 X7 X8 X9

/RESIDUALS DURBIN.Correlations

[DataSet3] E:\PATH1.sav

Variables Entered/Removeda

ModelVariables EnteredVariables RemovedMethod

1ROE, EBIT/TA, CR, QR, ROA, WC/TA, S/TA, RE/TA, MVE/BVTDb.Enter

a. Dependent Variable: ZSCORE

b. All requested variables entered.

Model Summaryb

ModelRR SquareAdjusted R SquareStd. Error of the EstimateDurbin-Watson

1.767a.588.4451.523281.976

a. Predictors: (Constant), ROE, EBIT/TA, CR, QR, ROA, WC/TA, S/TA, RE/TA, MVE/BVTD

b. Dependent Variable: ZSCORE

ANOVAa

ModelSum of SquaresdfMean SquareFSig.

1Regression85.98299.5544.117.002b

Residual60.330262.320

Total146.31235


b. Predictors: (Constant), ROE, EBIT/TA, CR, QR, ROA, WC/TA, S/TA, RE/TA, MVE/BVTD

Coefficientsa

ModelUnstandardized CoefficientsStandardized CoefficientstSig.Collinearity Statistics

BStd. ErrorBetaToleranceVIF

1(Constant)1.324.8941.480.151

WC/TA-.448.267-.255-1.678.105.6851.460

RE/TA1.288.433.4992.973.006.5631.777

EBIT/TA.021.325.009.065.949.8921.121

MVE/BVTD-.149.354-.071-.422.676.5621.780

S/TA1.626.440.6013.693.001.5991.670

CR.055.530.017.104.918.6201.612

QR.063.215.042.290.774.7461.341

ROA.522.211.4012.475.020.6031.658

ROE-1.610.878-.345-1.833.078.4472.236


Collinearity Diagnosticsa

ModelDimensionEigenvalueCondition IndexVariance Proportions

(Constant)WC/TARE/TAEBIT/TAMVE/BVTDS/TACRQRROAROE

113.8371.000.01.01.01.00.01.01.01.01.01.01

21.4231.642.00.01.11.01.00.04.09.01.00.03

31.2201.773.00.01.01.00.06.03.00.07.13.01

41.1351.839.00.10.03.13.00.01.09.12.00.01

51.0171.942.00.00.00.59.00.01.01.12.00.01

6.5152.730.00.39.01.16.00.02.03.39.01.02

7.3303.410.00.07.60.01.04.03.52.00.13.01

8.2753.734.01.01.11.00.25.19.25.04.43.06

9.1914.482.01.09.00.08.35.62.00.04.17.30

10.0588.167.98.31.13.01.29.03.00.21.12.54


Correlations

WC/TARE/TAEBIT/TAMVE/BVTDS/TACRQRROAROEZSCORE

WC/TAPearson Correlation1.104-.213-.120-.135-.041.226-.158-.396*-.196

Sig. (2-tailed).546.212.487.432.814.185.358.017.253

N36363636363636363636

RE/TAPearson Correlation.1041.007-.073-.166.591**.046-.131-.256.425**

Sig. (2-tailed).546.968.673.333.000.791.447.132.010

N36363636363636363636

EBIT/TAPearson Correlation-.213.0071.045.113.015.076.010-.014.143

Sig. (2-tailed).212.968.792.512.931.660.954.937.405

N36363636363636363636

MVE/BVTDPearson Correlation-.120-.073.0451-.379*.065-.229.554**-.327.023

Sig. (2-tailed).487.673.792.023.708.179.000.052.896

N36363636363636363636

S/TAPearson Correlation-.135-.166.113-.379*1-.120-.186-.255.556**.276

Sig. (2-tailed).432.333.512.023.487.277.133.000.103

N36363636363636363636

CRPearson Correlation-.041.591**.015.065-.1201-.079-.044-.092.256

Sig. (2-tailed).814.000.931.708.487.645.799.595.131

N36363636363636363636

QRPearson Correlation.226.046.076-.229-.186-.0791-.233-.252-.095

Sig. (2-tailed).185.791.660.179.277.645.172.138.581

N36363636363636363636

ROAPearson Correlation-.158-.131.010.554**-.255-.044-.2331-.291.274

Sig. (2-tailed).358.447.954.000.133.799.172.085.106

N36363636363636363636

ROEPearson Correlation-.396*-.256-.014-.327.556**-.092-.252-.2911-.144

Sig. (2-tailed).017.132.937.052.000.595.138.085.403

N36363636363636363636

ZSCOREPearson Correlation-.196.425**.143.023.276.256-.095.274-.1441

Sig. (2-tailed).253.010.405.896.103.131.581.106.403

N36363636363636363636

*. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

Residuals Statisticsa

MinimumMaximumMeanStd. DeviationN

Predicted Value-.27357.12012.16441.5673736

Residual-2.538903.48811.000001.3129036

Std. Predicted Value-1.5553.162.0001.00036

Std. Residual-1.6672.290.000.86236


Dari hasil output SPSS diatas dapat disusun matriks korelasi antar variabel sebagai berikut :


X11.104-.213-.120-.135-.041.226-.158-.396*-.196

X2.1041.007-.073-.166.591**.046-.131-.256.425**

X3-.213.0071.045.113.015.076.010-.014.143

X4-.120-.073.0451-.379*.065-.229.554**-.327.023

X5-.135-.166.113-.379*1-.120-.186-.255.556**.276

X6-.041.591**.015.065-.1201-.079-.044-.092.256

X7.226.046.076-.229-.186-.0791-.233-.252-.095

X8-.158-.131.010.554**-.255-.044-.2331-.291.274

X9-.396*-.256-.014-.327.556**-.092-.252-.2911-.144

X10-.196.425**.143.023.276.256-.095.274-.1441

3. UJI HIPOTESANYA REGRESSION

/MISSING LISTWISE

/STATISTICS COEFF OUTS R ANOVA

/CRITERIA=PIN(.05) POUT(.10)

/NOORIGIN

/DEPENDENT X10

/METHOD=ENTER X1 X2 X3 X4 X5 X6 X7 X8 X9

/RESIDUALS HISTOGRAM(ZRESID) NORMPROB(ZRESID).

[DataSet3] E:\PATH1.savVariables Entered/Removeda


1ROE, EBIT/TA, CR, QR, ROA, WC/TA, S/TA, RE/TA, MVE/BVTDb.Enter



Model Summaryb

ModelRR SquareAdjusted R SquareStd. Error of the Estimate

1.767a.588.4451.52328

a. Predictors: (Constant), ROE, EBIT/TA, CR, QR, ROA, WC/TA, S/TA, RE/TA, MVE/BVTD


Regression

ANOVAa


1Regression85.98299.5544.117.002b

Residual60.330262.320

Total146.31235


b. Predictors: (Constant), ROE, EBIT/TA, CR, QR, ROA, WC/TA, S/TA, RE/TA, MVE/BVTD

Dari hasil spss table ANOVA diatas menunjukkan bahwa dari semua data yang ada membuktikan data tersebut normal atau bersignifikan karena < 0.05. Hipotesa :H0 diterima

H0 : Secara keseluruhan semua variabel secara simultan dan signifikan terhadap potensi kebangkrutan perusahaan artinya rasio tersebut berpengaruh terhadap prediksi potensi kebangkrutan perusahaan.Coefficientsa

ModelUnstandardized CoefficientsStandardized CoefficientstSig.

BStd. ErrorBeta

1(Constant)1.324.8941.480.151

WC/TA-.448.267-.255-1.678.105

RE/TA1.288.433.4992.973.006

EBIT/TA.021.325.009.065.949

MVE/BVTD-.149.354-.071-.422.676

S/TA1.626.440.6013.693.001

CR.055.530.017.104.918

QR.063.215.042.290.774

ROA.522.211.4012.475.020

ROE-1.610.878-.345-1.833.078


Namun jika dilihat dari table Coefficients bahwa ada 5 variabel yang tidak berpengaruh terhadap X10 (variable dependen) karena > 0.05Ket :

Ho:

1. WC/TA : Ho ditolak (tidak mempengaruhi potensi kebangkrutan karena nilai sig 0.105)

2. RE/TA : Ho diterima (signifikan terhadap variable dependen)

3. EBIT/TA : Ho ditolak (tidak mempengaruhi potensi kebangkrutan karena nilai sig > 0.5 yakni 0.949)4. MVE/BVTD : Ho ditolak (tidak mempengaruhi potensi kebangkrutan karena nilai sig > 0.5yakni 0.676)5. S/TA : Ho diterima (signifikan dan mempengaruhi prediksi potensi kebangkrutan perusahaan)6. CR : Ho ditolak (tidak mempengaruhi variable dependen karena nilai sig 0.774)

7. ROA : Ho diterima (karena signifikan terhadap variable dependen yakni 0.20)

8. ROE : Ho ditolak (karena lebih besar dari alpha yaitu 0.078)Residuals Statisticsa


Predicted Value-.27357.12012.16441.5673736

Residual-2.538903.48811.000001.3129036


Std. Residual-1.6672.290.000.86236


Charts

Dari gambar grafik diatas menunjukkan bahwa data berdistribusi normal karena grafik batang mampu membagi dua atau grafik garis memotong ditengah grafik batang, yakni antara -2 sampai dengan 2.Charts

Dari grafik menggambarkan butir-butir yang mendekati garis normal, itu artinya rata-rata data yang ada berdistribusi normal dan dapat diuji.

Data yang signifikan yaitu X2. X5 dan X8, sedangkan yang tidak signifikan X1,X3,X4,X6,X7 dan X9 harus dikeluarkan TRIMMING JALUR PATH

Dihasilkan output SPSS :Regression


Variables Entered/Removeda


1ROA, RE/TA, S/TAb.Enter



Model Summaryb

ModelRR SquareAdjusted R SquareStd. Error of the EstimateDurbin-Watson

1.712a.508.4611.500461.971

a. Predictors: (Constant), ROA, RE/TA, S/TA


ANOVAa


1Regression74.268324.75610.996.000b

Residual72.044322.251

Total146.31235


b. Predictors: (Constant), ROA, RE/TA, S/TA

Coefficientsa

ModelUnstandardized CoefficientsStandardized CoefficientstSig.Collinearity Statistics

BStd. ErrorBetaToleranceVIF

1(Constant).163.445.365.717

RE/TA1.469.330.5694.449.000.9401.064

S/TA1.331.355.4923.749.001.8941.118

ROA.616.170.4743.630.001.9041.106


Correlations

RE/TAS/TAROAZSCORE

RE/TAPearson Correlation1-.166-.131.425

Sig. (2-tailed).333.447.010

N36363636

S/TAPearson Correlation-.1661-.255.276

Sig. (2-tailed).333.133.103

N36363636

ROAPearson Correlation-.131-.2551.274

Sig. (2-tailed).447.133.106

N36363636

Collinearity Diagnosticsa

ModelDimensionEigenvalueCondition IndexVariance Proportions

(Constant)RE/TAS/TAROA

112.1241.000.06.05.06.06

2.8811.553.00.72.05.08

3.8001.630.00.00.31.41

4.1963.296.94.23.58.46


Residuals Statisticsa


Predicted Value.37445.83862.16441.4566936

Residual-3.378774.37224.000001.4347136


Std. Residual-2.2522.914.000.95636


Charts

Dari table diatas menunjukkan ketiga variable tersebut signifikan

(yx2 = 0.569(yx5 = 0.492(yx8 = 0.474Kemudian menghitung koefisien determinan : R2yx8x5x2 = (yx2 . ryx2 + (yx5 . ryx5 + (yx8 . ryx8

= 0.569 . 0.425 + 0.492 . 0.276 + 0.474 . 0.274

= 0.24 + 0.14 + 0.13

= 0.51

Jadi, = 7Jika digambarkan grafik panah dari persamaan diatas yakni :

1 = 0.469

ANALYSIS FAKTOR1. Dengan data yang sama didapat hasil uji analisis faktor (output SPSS) sebagai berikut :DATASET ACTIVATE DataSet3.

DATASET CLOSE DataSet0.Factor Analysis

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy..486

Bartlett's Test of SphericityApprox. Chi-Square96.093

df45

Sig..000

Tabel KMO menunjukkan nilai 0.486 artinya dr dan signifikan 0.00 sehingga masih bisa dilakukan model trimming.Anti-image Matrices


Anti-image CovarianceWC/TA.618-.070.178.077-.123.030-.036.024.252.158

RE/TA-.070.420-.002.050.134-.253.047.146.017-.210

EBIT/TA.178-.002.892-.055-.091-.005-.107.030.079-.008

MVE/BVTD.077.050-.055.558.074-.067.155-.186.098.040

S/TA-.123.134-.091.074.393.025.102.118-.192-.236

CR.030-.253-.005-.067.025.620.051.026-.035-.010

QR-.036.047-.107.155.102.051.743.124.108-.031

ROA.024.146.030-.186.118.026.124.488.038-.196

ROE.252.017.079.098-.192-.035.108.038.396.137

ZSCORE.158-.210-.008.040-.236-.010-.031-.196.137.412

Anti-image CorrelationWC/TA.410a-.138.240.131-.250.049-.053.044.510.313

RE/TA-.138.468a-.003.103.329-.496.084.322.042-.504

EBIT/TA.240-.003.412a-.078-.153-.006-.132.045.133-.013

MVE/BVTD.131.103-.078.674a.157-.114.241-.357.208.083

S/TA-.250.329-.153.157.435a.051.189.270-.487-.587

CR.049-.496-.006-.114.051.620a.074.047-.071-.020

QR-.053.084-.132.241.189.074.568a.207.199-.057

ROA.044.322.045-.357.270.047.207.533a.087-.437

ROE.510.042.133.208-.487-.071.199.087.529a.338

ZSCORE.313-.504-.013.083-.587-.020-.057-.437.338.325a

a. Measures of Sampling Adequacy(MSA)

jika dibuat persamaannya :

Kemudian diinput kedalam persamaan :

[DataSet3] E:\PATH1.savCommunalities

InitialExtraction

WC/TA1.000.554

RE/TA1.000.834

EBIT/TA1.000.720

MVE/BVTD1.000.730

S/TA1.000.691

CR1.000.675

QR1.000.706

ROA1.000.736

ROE1.000.797

ZSCORE1.000.662

Extraction Method: Principal Component Analysis.

Total Variance Explained

ComponentInitial EigenvaluesExtraction Sums of Squared Loadings

Total% of VarianceCumulative %Total% of VarianceCumulative %

12.28322.83422.8342.28322.83422.834

21.86218.61641.4501.86218.61641.450

31.83218.31659.7661.83218.31659.766

41.12911.29371.0581.12911.29371.058

5.9389.37680.434

6.6896.88887.322

7.4454.45191.773

8.3753.74995.522

9.2822.81998.341

10.1661.659100.000


Component Matrixa

Component

1234

WC/TA.196-.677.201-.130

RE/TA.434.158.778-.120

EBIT/TA-.022.290.048.796

MVE/BVTD.624.247-.527-.051

S/TA-.711.387.178.068

CR.376.299.606-.276

QR.056-.587.264.537

ROA.554.383-.529.045

ROE-.805.320-.040-.213

ZSCORE.249.633.394.213


a. 4 components extracted.

Component Score Coefficient Matrix

Component

1234

WC/TA.086-.364.110-.116

RE/TA.190.085.425-.106

EBIT/TA-.010.156.026.705

MVE/BVTD.273.132-.288-.045

S/TA-.311.208.097.061

CR.165.161.331-.245

QR.025-.315.144.475

ROA.243.206-.289.040

ROE-.352.172-.022-.189

ZSCORE.109.340.215.188


Component Scores.

Component Score Covariance Matrix

Component1234

11.000.000.000.000

2.0001.000.000.000

3.000.0001.000.000

4.000.000.0001.000


Component Scores.

Dari tabel output Anti-image Matrices diperoleh yang signifikan atau > 0.5 sebanyak 5 variabel yakni Variabel MVE/BVTD, CR, QR, ROA dan ROE, Namun dari kelima variable tersebut dipilih kembali variable-variabel mana yang paling dominan mampu mempengaruhi variable dependennya, menguji variable dominan dengan melakukan uji trimming.

TRIMMING ANALISIS FAKTOR1. Melakukan uji trimming dengan mengeluarkan variabel yang tidak signifikan yakni >0,5. Variabel yang dikeluarkan yakni X1, X2, X3, X5 dan X10. Kemudian akan muncul hasil output spss seperti dibawah ini : FACTOR

/VARIABLES X4 X6 X7 X8 X9

/MISSING LISTWISE

/ANALYSIS X4 X6 X7 X8 X9

/PRINT INITIAL KMO AIC EXTRACTION FSCORE

/CRITERIA MINEIGEN(1) ITERATE(25)

/EXTRACTION PC

/ROTATION NOROTATE

/SAVE REG(ALL)

/METHOD=CORRELATION.

Factor Analysis


KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy..533

Bartlett's Test of SphericityApprox. Chi-Square24.824

df10

Sig..006

Anti-image Matrices

MVE/BVTDCRQRROAROE

Anti-image CovarianceMVE/BVTD.631-.046.143-.286.176

CR-.046.964.108.103.110

QR.143.108.784.147.297

ROA-.286.103.147.642.147

ROE.176.110.297.147.737

Anti-image CorrelationMVE/BVTD.601a-.059.203-.449.258

CR-.059.283a.124.130.130

QR.203.124.412a.207.390

ROA-.449.130.207.593a.214

ROE.258.130.390.214.483a

a. Measures of Sampling Adequacy(MSA)

Dari table output spss anti image matrices diatas dapat kita lihat ada 2 variabel yang >0.5 sehingga diperolehlah 2 variabel yang dominan yakni variable MVE/BVTD dan ROA.Communalities

InitialExtraction

MVE/BVTD1.000.738

CR1.000.977

QR1.000.840

ROA1.000.749

ROE1.000.804


Total Variance Explained

ComponentInitial EigenvaluesExtraction Sums of Squared Loadings

Total% of VarianceCumulative %Total% of VarianceCumulative %

11.83936.77436.7741.83936.77436.774

21.24624.91261.6871.24624.91261.687

31.02420.48082.1671.02420.48082.167

4.4579.13991.305

5.4358.695100.000


Component Matrixa

Component

123

MVE/BVTD.858-.050-.017

CR.111-.011.982

QR-.314.857-.087

ROA.836-.084-.207

ROE-.542-.708-.095


a. 3 components extracted.

Component Score Coefficient Matrix

Component

123

MVE/BVTD.466-.040-.017

CR.061-.009.959

QR-.171.688-.085

ROA.455-.068-.202

ROE-.295-.569-.092


Component Scores.

Component Score Covariance Matrix

Component123

11.000.000.000

2.0001.000.000

3.000.0001.000


Component Scores.

2. Setelah diperoleh 2 variabel yang paling dominan, kemudian kita buat gambar grafik panah seperti dibawah ini : = 7

: Sehingga diperoleh persamaan

= 0.601X1 + 0.593X2 + 7X1

X2

X3

Y

X10

X4

X5

X6

X7

X9

X8

X2

Y

X5

X8

X4

Y

X8

tugas sub 2 wiwik anggraini

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