Pengaruh Partisipasi Anggaran Terhadap Kinerja Manajerial dengan Keadilan Prosedural, Motivasi, dan Job Relevant Information (JRI) Sebagai Variabel Intervening (Studi Empiris Pada Perusahaan Jasa di Kota Semarang) - Unika Repository

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DAFTAR PUSTAKA

Anoraga, Pandji, 2005, Psikologi Kerja, Jakarta : PT. Rineka Cipta

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dan Kepuasan Kerja Terhadap Kinerja Manajer Pada Perusahaann

Manufaktur di

Semarang”. Skripsi

(tidak dipublikasikan)

Program

Sarjana Universitas Katolik Soegijapranata Semarang.

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Selection:

The Role of

Control in Mediating Justice Judgments”,

Journal of Personality and Social Psycology, 56 (6):

1148-1160.

Garisson, Ray H dan Eric W. Norren, 2000, Akuntansi Manajemen, terjemahan A.

Totok Budi Santoso, Jakarta : Salemba Empat

Ghozali, Prof.Dr .H.Imam,M.Com, Akt, 2006,

Aplikasi Analisis Multivariate

dengan Program SPSS, Semarang: Badan Penerbit Universitas

Diponegoro

Govindarajan, V., (1986), “Impact of Participation in The Budgetary Process on

Managerial

Attitudes

and

Performance:

Universilistic

and

Contingency Perspectives”,

Decision Sciences, 17: 496- 516.

Greenberg, and R.H. Willis: 27-55, New York, NY: Plenum Press.

Hasibuan, H Malayu S.P, 2001,

Organisasi dan Motivasi : Dasar Peningkatan

Produktivitas, Jakarta: Bumi Aksara

I.G.K. Ulupui. 2005.

“Pengaruh Partisipasi Anggaran, Persepsi Keadilan

Distributif, Keadilan Prosedural, dan Goal Commitment Terhadap

Kinerja

”

. Alumnus Magister Sains UGM. Volume 9, no. 2, pp.98-112.

I Made Sarjana, Luh Mei Wahyuni, dan I Made Sura Ambarajaya. 2012.

“Pengaruh

Anggaran Partisipatif Terhadap Kinerja Manajerial Pada

PT

(PERSERO) ANGKASA

PURA I BANDAR UDARA NGURAH

RAI-BALI”. Jurnal Bisnis dan

Kewirausahaan. Vol. 8 No.1s

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pengolahan kayu skala menengah di Jawa Timur”

. Jurusan Ekonomi

Manajemen, fakultas Ekonomi, Universitas Kristen Petra.

Kren, L., (1992),

“Budgetary Participation and Managerial Performance: The

Impact of

Information and Environmental Volatility”

,

The

Accounting Review, July: 511-526.

Lind, E.A. and T. Tyler, (1988),

The Social Psychology of Procedural Justice,

New York,

NY: Plenum Press.

Munandar, M,, 1986,

Budgeting :

Perencanaan Kerja,

Pengkoordinasian,

Pengawasan, Yogyakarta : BPFE

Mulyadi dan Jhony Setiawan, 2001,

Sistem Perencanaan dan Pengendalian

Masyarakat, Edisi Kedua, Cetakan Pertama, Jakarta : Salemba Empat.

Nafarin, 2000,

Penganggaran Perusahaan, Edisi Pertama, Jakarta : Salemba

Empat

P. Agustinus Aryo. (2007). “Pengaruh Partisipas

i Dalam Penganggaran terhadap

Kinerja

Manajer dengan Motivasi Kerja Sebagai Variabel

Moderating. Skripsi (tidak dipublikasikan) Program Sarjana Universitas

Katolik Soegijapranata Semarang.

P, Agatha Dyah Rukmi. (2006). “ Peran Partisipasi Anggaran D

alam Hubungan

Antara Keadilan Prosedural dengan Kinerja Manajerial. Skripsi (tidak

dipublikasikan) Program Sarjana Universitas Katolik Soegijapranata

Semarang.

Robbins, Stephen P . 1996. Perilaku Organisasi. Jakarta : PT. Gramedia.

Sari, Ima Wulan. (2

007). “Pengaruh Keadilan, Job Relevant Information, dan

Motivasi Sebagai Variabel Intervening dalam Penganggaran Partisipatif

dan Kinerja

Manajerial”. Skripsi (tidak dipublikasikan) Program Sarjana

Universitas Katolik Soegijapranata Semarang.

Shields,

J.F., dan M.D. Shields, (1998), “Antecedent of Participative Budgeting”,

Accounting, Organization and Society, 23 (1): 49-76.

Simamora, Henry, 1999, Akuntansi Manajemen, Jakarta : Salemba Empat

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Kerja (Studi Empiris pada Perusahaan Jasa Perhotelan). Skripsi (tidak

dipublikasikan) Program Sarjana Universitas Katolik Soegijapranata

Semarang.

Sumadiyah, SE, AK & Sri Susanta, SE, Msi, AK.2004. Job Relevant Information

dan

Ketidakpastian Lingkungan dalam Hubungan antara Penyusunan

Partisipasi Anggaran dan Kinerja Manajerial. SNA VII. Denpasar Bali,

23 Desember.

W. Veronika Imelda. (2005). “Peran Partisipasi Pen

ganggaran dalam Hubungan

Antara Keadilan Prosedural dan Keadilan Distributif dengan Kinerja

Manajerial dan Kepuasan Kerja (Studi Empiris Pada Perusahaan

Manufaktur di Semarang). Skripsi (tidak

dipublikasikan)

Program

Sarjana Universitas Katolik Soegijapranata Semarang.

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Hipotesis awal (PA ke KM)

Regression

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 paa . Enter

a. All requested variables entered.

b. Dependent Variable: km

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .515a .266 .255 6.45851

a. Predictors: (Constant), pa

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 1010.516 1 1010.516 24.226 .000a

Residual 2794.730 67 41.712

Total 3805.246 68

Coefficientsa

Model

Unstandardized Coefficients

Standardized

(5)

Residuals Statisticsa

Minimum Maximum Mean Std. Deviation N

Predicted Value 21.7040 37.1649 28.1594 3.85494 69

Residual -1.58577E1 12.25246 .00000 6.41085 69

Std. Predicted Value -1.675 2.336 .000 1.000 69

Std. Residual -2.455 1.897 .000 .993 69

(6)

Hipotesis awal

Normalitas

NPar Tests

One-Sample Kolmogorov-Smirnov Test

Unstandardized

Residual

N 69

Normal Parametersa Mean .0000000

Std. Deviation 6.41084785

Most Extreme Differences Absolute .078

Positive .051

Negative -.078

Kolmogorov-Smirnov Z .649

Asymp. Sig. (2-tailed) .794

(7)

Uji Heterokedastisitas

Regression

Model

Variables

Entered

Variables

Removed Method

1 paa . Enter

b. Dependent Variable: abs

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .000a .000 -.015 3.61737

ANOVAb

1 Regression .000 1 .000 .000 .997a

Residual 876.720 67 13.085

Total 876.721 68

b. Dependent Variable: abs

Coefficientsa

Model

Standardized

(8)

Uji Hipotesis 1

MODEL 1 (PA ke KP)

Regression

Model

Variables

Entered

Variables

Removed Method

1 paa . Enter

b. Dependent Variable: kp

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .327a .107 .093 4.83312

ANOVAb

1 Regression 186.858 1 186.858 7.999 .006a

Residual 1565.056 67 23.359

Total 1751.913 68

Coefficientsa

Model

Standardized

Coefficients

t Sig.

B Std. Error Beta

(9)

pa .317 .112 .327 2.828 .006

a. Dependent Variable: kp

Predicted Value 18.0502 24.6986 20.8261 1.65768 69

Residual -1.07990E1 8.00005 .00000 4.79745 69

Std. Residual -2.234 1.655 .000 .993 69

(10)

Uji Normalitas

NPar Tests

Unstandardized

Residual

N 69

Positive .091

Negative -.090

(11)

Uji Heterokedastisitas

Regression

Model

Variables

Entered

Variables

Removed Method

1 paa . Enter

b. Dependent Variable: abs_pakp

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .108a .012 -.003 2.43902

ANOVAb

1 Regression 4.664 1 4.664 .784 .379a

Residual 398.571 67 5.949

Total 403.235 68

b. Dependent Variable: abs_pakp

Coefficientsa

Model

Standardized

Coefficients

t Sig.

(12)

1 (Constant) 4.992 1.046 4.774 .000

pa -.050 .056 -.108 -.885 .379

a. Dependent Variable: abs_pakp

UJI HIPOTESIS 1

MODEL 2 (PA,KP,KM)

Regression

Model

Variables

Entered

Variables

Removed Method

1 KP, PAa . Enter

b. Dependent Variable: KM

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .656a .431 .414 5.72803

a. Predictors: (Constant), KP, PA

ANOVAb

1 Regression 1639.766 2 819.883 24.989 .000a

Residual 2165.481 66 32.810

Total 3805.246 68

(13)

Model

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) 5.439 3.298 1.649 .104

PA .535 .140 .375 3.815 .000

KP .634 .145 .430 4.379 .000

a. Dependent Variable: KM

Predicted Value 18.5018 39.2583 28.1594 4.91062 69

Residual -1.34823E1 11.25764 .00000 5.64316 69

Std. Residual -2.354 1.965 .000 .985 69

(14)

Unstandardized

Residual

N 69

Positive .072

Negative -.114

a. Test distribution is Normal.

(15)

Regression

Model

Variables

Entered

Variables

Removed Method

1 KP, PAa . Enter

b. Dependent Variable: abs_pakpkm

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .127a .016 -.014 3.65745

ANOVAb

1 Regression 14.472 2 7.236 .541 .585a

Residual 882.879 66 13.377

Total 897.351 68

b. Dependent Variable: abs_pakpkm

Coefficientsa

Model

Standardized

a. Dependent Variable: abs_pakpkm

(16)

Regression

Model

Variables

Entered

Variables

Removed Method

1 KP, PAa . Enter

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .656a .431 .414 5.72803

ANOVAb

1 Regression 1639.766 2 819.883 24.989 .000a

Residual 2165.481 66 32.810

Total 3805.246 68

Coefficientsa

Model

Standardized

Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF

1 (Constant) 5.439 3.298 1.649 .104

PA .535 .140 .375 3.815 .000 .893 1.119

KP .634 .145 .430 4.379 .000 .893 1.119

(17)

Model

Dimensi

on Eigenvalue Condition Index

Variance Proportions

(Constant) PA KP

1 1 2.924 1.000 .01 .01 .01

2 .048 7.780 .08 .95 .26

3 .028 10.299 .92 .04 .73

Hipotesis 2

MODEL 1 (PA ke M)

Regression

Model

Variables

Entered

Variables

Removed Method

1 PAa . Enter

b. Dependent Variable: M

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .521a .271 .260 5.25087

a. Predictors: (Constant), PA

b. Dependent Variable: M

ANOVAb

1 Regression 687.863 1 687.863 24.948 .000a

Residual 1847.297 67 27.572

Total 2535.159 68

(18)

Coefficientsa

Model

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) 13.671 2.251 6.072 .000

PA .607 .122 .521 4.995 .000

a. Dependent Variable: M

Predicted Value 19.1378 31.8937 24.4638 3.18051 69

Residual -1.64640E1 9.61023 .00000 5.21211 69

Std. Residual -3.135 1.830 .000 .993 69

(19)

Uji Normalitas

NPar Tests

Unstandardized

Residual

N 69

Positive .070

Negative -.106

(20)

Uji Heterokedastisitas

Regression

Model

Variables

Entered

Variables

Removed Method

1 PAa . Enter

b. Dependent Variable: abs_pam

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .004a .000 -.015 3.05152

ANOVAb

1 Regression .009 1 .009 .001 .975a

Residual 623.890 67 9.312

Total 623.899 68

b. Dependent Variable: abs_pam

(21)

Model

Standardized

a. Dependent Variable: abs_pam

HIPOTESIS 2

MODEL 2 (PA, M , KM)

Regression

Model

Variables

Entered

Variables

Removed Method

1 M, PAa . Enter

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .564a .318 .297 6.27220

a. Predictors: (Constant), M, PA

ANOVAb

1 Regression 1208.771 2 604.386 15.363 .000a

Residual 2596.475 66 39.341

Total 3805.246 68

(22)

ANOVAb

1 Regression 1208.771 2 604.386 15.363 .000a

Residual 2596.475 66 39.341

Total 3805.246 68

Coefficientsa

Model

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) 10.599 3.348 3.165 .002

PA .537 .170 .376 3.157 .002

M .328 .146 .267 2.245 .028

Predicted Value 19.6933 37.6453 28.1594 4.21617 69

Residual -1.41011E1 10.97909 .00000 6.17928 69

Std. Residual -2.248 1.750 .000 .985 69

(23)

Uji Normalitas

NPar Tests

Unstandardized

Residual

N 69

Positive .051

Negative -.080

(24)

Unstandardized

Residual

N 69

Positive .051

Negative -.080

(25)

Uji Heterokedastisitas

Regression

Model

Variables

Entered

Variables

Removed Method

1 M, PAa . Enter

b. Dependent Variable: abs_pamkm

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .080a .006 -.024 3.34244

Coefficientsa

Model

Standardized

(26)

Uji Multikolinearitas

Regression

Model

Variables

Entered

Variables

Removed Method

1 M, PAa . Enter

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .564a .318 .297 6.27220

Coefficientsa

Model

Standardized

Coefficients

t Sig.

1 (Constant) 10.599 3.348 3.165 .002

PA .537 .170 .376 3.157 .002 .729 1.372

M .328 .146 .267 2.245 .028 .729 1.372

Collinearity Diagnosticsa

Model

Dimensi

(Constant) PA M

1 1 2.931 1.000 .01 .01 .00

2 .041 8.494 .49 .84 .02

3 .028 10.251 .51 .16 .97

(27)

Hipotesis 3

MODEL 1 (PA ke JRI)

Regression

Model

Variables

Entered

Variables

Removed Method

1 PAa . Enter

b. Dependent Variable: JRI

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .363a .132 .119 3.52720

ANOVAb

1 Regression 126.212 1 126.212 10.145 .002a

Residual 833.556 67 12.441

Total 959.768 68

Coefficientsa

Model

Standardized

Coefficients

t Sig.

(28)

1 (Constant) 11.319 1.512 7.484 .000

PA .260 .082 .363 3.185 .002

a. Dependent Variable: JRI

Predicted Value 13.6606 19.1247 15.9420 1.36237 69

Residual -6.56351 7.07917 .00000 3.50117 69

Std. Residual -1.861 2.007 .000 .993 69

Uji Normalitas

(29)

Unstandardized

Residual

N 69

Positive .078

Negative -.094

Uji Heterokedastisitas

(30)

Model

Variables

Entered

Variables

Removed Method

1 PAa . Enter

b. Dependent Variable: abs_pajri

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .188a .035 .021 1.81195

ANOVAb

1 Regression 8.057 1 8.057 2.454 .122a

Residual 219.972 67 3.283

Total 228.028 68

Coefficientsa

Model

Standardized

(31)

Hipotesis 3

MODEL 1 (PA ke JRI)

Regression

Model

Variables

Entered

Variables

Removed Method

1 PAa . Enter

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .363a .132 .119 3.52720

ANOVAb

1 Regression 126.212 1 126.212 10.145 .002a

Residual 833.556 67 12.441

Total 959.768 68

Coefficientsa

Model

(32)

Coefficientsa

Model

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) 11.319 1.512 7.484 .000

PA .260 .082 .363 3.185 .002

Predicted Value 13.6606 19.1247 15.9420 1.36237 69

Residual -6.56351 7.07917 .00000 3.50117 69

Std. Residual -1.861 2.007 .000 .993 69

(33)

Uji Normalitas

NPar Tests

Unstandardized

Residual

N 69

Positive .078

Negative -.094

(34)

Uji Heterokedastisitas

Regression

Model

Variables

Entered

Variables

Removed Method

1 PAa . Enter

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .188a .035 .021 1.81195

ANOVAb

1 Regression 8.057 1 8.057 2.454 .122a

Residual 219.972 67 3.283

Total 228.028 68

Coefficientsa

Model

Standardized

(35)

Hipotesis 3

MODEL 1 (PA ke JRI)

Regression

Model

Variables

Entered

Variables

Removed Method

1 PAa . Enter

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .363a .132 .119 3.52720

ANOVAb

1 Regression 126.212 1 126.212 10.145 .002a

Residual 833.556 67 12.441

Total 959.768 68

(36)

Model

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) 11.319 1.512 7.484 .000

PA .260 .082 .363 3.185 .002

Predicted Value 13.6606 19.1247 15.9420 1.36237 69

Residual -6.56351 7.07917 .00000 3.50117 69

Std. Residual -1.861 2.007 .000 .993 69

(37)

NPar Tests

Unstandardized

Residual

N 69

Positive .078

Negative -.094

(38)

Regression

Model

Variables

Entered

Variables

Removed Method

1 PAa . Enter

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .188a .035 .021 1.81195

ANOVAb

1 Regression 8.057 1 8.057 2.454 .122a

Residual 219.972 67 3.283

Total 228.028 68

Coefficientsa

Model

Standardized

(39)

Hipotesis 3

MODEL 2 (PA, JRI, KM)

Regression

Model

Variables

Entered

Variables

Removed Method

1 JRI, PAa . Enter

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .700a .490 .475 5.42039

a. Predictors: (Constant), JRI, PA

ANOVAb

1 Regression 1866.127 2 933.064 31.758 .000a

Residual 1939.119 66 29.381

Total 3805.246 68

(40)

Coefficientsa

Model

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) 3.610 3.149 1.146 .256

PA .473 .135 .331 3.509 .001

JRI 1.013 .188 .509 5.396 .000

Predicted Value 17.9953 38.5923 28.1594 5.23861 69

Residual -1.31613E1 11.57370 .00000 5.34008 69

Std. Residual -2.428 2.135 .000 .985 69

(41)

Uji Normalitas

NPar Tests

Unstandardized

Residual

N 69

Positive .086

Negative -.103

(42)

Uji Heterokedastisitas

Regression

Model

Variables

Entered

Variables

Removed Method

1 JRI, PAa . Enter

b. Dependent Variable: abs_pajrikm

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .142a .020 -.010 3.52809

ANOVAb

1 Regression 16.870 2 8.435 .678 .511a

Residual 821.529 66 12.447

Total 838.399 68

b. Dependent Variable: abs_pajrikm

Coefficientsa

Model Unstandardized Coefficients

Standardized

(43)

B Std. Error Beta

1 (Constant) 4.032 2.050 1.967 .053

PA .092 .088 .137 1.046 .299

JRI -.105 .122 -.112 -.856 .395

a. Dependent Variable: abs_pajrikm

Uji Multikolinearitas

Regression

Model

Variables

Entered

Variables

Removed Method

1 JRI, PAa . Enter

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .700a .490 .475 5.42039

ANOVAb

1 Regression 1866.127 2 933.064 31.758 .000a

Residual 1939.119 66 29.381

Total 3805.246 68

(44)

Model

Standardized

Coefficients

t Sig.

1 (Constant) 3.610 3.149 1.146 .256

PA .473 .135 .331 3.509 .001 .868 1.151

JRI 1.013 .188 .509 5.396 .000 .868 1.151

Collinearity Diagnosticsa

Model

Dimensi

(Constant) PA JRI

1 1 2.927 1.000 .00 .01 .01

2 .046 7.953 .12 .99 .20

3 .026 10.566 .87 .01 .80