LAMPIRAN A Kuesioner - core.ac.uk · 27 Saya menguasai mata kuliah Akuntansi Manajemen (Akmen) 1 2...

LAMPIRAN A

Kuesioner

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KUESIONER

Data Responden :

Nama :

NIM :

Angkatan :

Jenis kelamin : ( ) laki-laki ( ) perempuan

Jalur konsentrasi : ( ) akuntansi keuangan

( ) akuntansi manajemen

( ) sistem informasi

Berikut ini adalah beberapa pertanyaan terkait dengan faktor-faktor apa

yang menjadi pertimbangan anda dalam memilih jalur konsentrasi. Hasil

kuesioner ini diharapkan dapat memberikan masukan bagi jurusan akuntansi

Universitas Katolik Soegijapranata dalam upaya pengembangan jalur konsentrasi

sesuai dengan faktor-faktor yang mempengaruhi mahasiswa dalam pemilihan jalur

konsentrasi tersebut.



Petunjuk pengisian :

Berikan tanda ( √ ) pada jawaban yang anda anggap sesuai dengan penilaian anda

untuk pertanyaan atribut berikut.

1 : sangat tidak setuju

2 : tidak setuju

3 : ragu-ragu

4 : setuju

5 : sangat setuju

Berikut ini adalah faktor-faktor yang menjadi pertimbangan anda dalam memilih jalur konsentrasi sesuai dengan pengalaman anda : No Pertimbangan saya 1 2 3 4 5

Motivasi diri sendiri jalur AK

1

Ingin mendapat pengetahuan tentang dimensi-dimensi internasional akuntansi, pola pengembangan akuntansi internasional , perbandingan sistem dan praktek akuntansi di berbagai negara, termasuk issue teknikal akuntansi internasional dan usaha-usaha yang telah dilakukan untuk mengurangi diversitas prinsip dan praktek akuntansi di negara-negara dunia.

1 2 3 4 5

2

Dapat membahas, mendiskusikan dan menelaah artikel-artikel aktual akuntansi sebagai penerapan kerangka teoritis dari teori akuntansi.

1 2 3 4 5

3

Ingin mendapat pengetahuan tentang pasar modal, mekanisme dan lembaga-lembaga yang ada didalamnya, mekanisme perdagangan bursa efek, settlement dan jenis-jenis sekuritas yang dipedagangkan serta teori portofolionya.

1 2 3 4 5

4 Ingin mendapat pengetahuan tentang prosedur, metode dan tehnik analisis laporan keuangan dan interpretasi terhadap hasil analisis tersebut.

1 2 3 4 5



5 Adanya keahlian yang ingin dikembangkan melalui jalur konsentrasi ini

1 2 3 4 5

Motivasi diri sendiri jalur AM

6

Ingin membahas, mendiskusikan dan menelaah artikel-artikel dan issue-issue aktual akuntansi dan perkembangan akuntansi manajemen sebagai penerapan kerangka teoritis dari Akuntansi Manajemen.

1 2 3 4 5

7

Ingin membahas pemeriksaan terhadap semua fungsi manajemen, yaitu perencanaan, pengorganisasian, pengarahan dan pengawasan untuk menilai efektivitas, efisiensi dan ekonomisasi dari setiap fungsi manajemen tersebut sebagai dasar perbaikan di masa mendatang.

1 2 3 4 5

8

Ingin mendapat pengetahuan tentang internal auditing, proses pemeriksaan yang dilakukan internal auditor dan berbagai peraturan yang berkaitan dengan pemeriksaan internal, dan kedudukan serta peran internal audito tentang temuan-temuan audit, pelaporannya serta tanggapan atas laporan audit.

1 2 3 4 5

9

Ingin mendapat pemahaman tentang penyusunan perencanaan dan pengendalian laba komprehensif, baik laba taktis jangka pendek maupun laba strategis jangka panjang.

1 2 3 4 5


1 2 3 4 5

Motivasi diri sendiri jalur SIA

11

Ingin mempelajari berbagai aplikasi TI dalam bisnis yang ada dewasa ini dan perubahan manajemen sistem informasi dalam organisasi. Mata kuliah ini juga akan membahas lebih lanjut tentang tantangan manajemen dalam era informasi.

1 2 3 4 5

12

Ingin mendapat pemahaman konsep dan aplikasi sistem manajemen basis data yang memungkinkan mahasiswa memahami dan mampu mendesain serta membangun struktur basis data yang efektif dan efisien.

1 2 3 4 5



13

Ingin mendapat pengetahuan mahasiswa konsep dan aplikasi pengembangan sistem informasi berbasis komputer. Pembahasan mencakup antara lain konsep, tools, teknik dan aplikasi-aplikasinya. Secara umum, mata kuliah ini memberikan tekanan pada tahap analisis dan perancangan. Meskipun demikian untuk melengkapi siklus pengembangan system, mata kuiah ini juga akan memberikan bahasan secara ringkas tentang tahap-tahap konstruksi dan implementasi, serta operasi dan dukungan system.

1 2 3 4

5

14

Ingin mendapat pengetahuan dan ketrampilan teknis pemrograman aplikasi berbasis data yang merupakan tipe dari aplikasi-aplikasi sistem informasi akuntansi dan manajemen. Ketrampilan ini akan memperkuat kemampuan untuk mempersiapkan mahasiswa menjasi analis sistem dan auditor sistem informasi.

1 2 3 4 5


1 2 3 4 5

Motivasi Orang lain

16 Saran dari teman / yang sudah memilih jalur konsentrasi tersebut

1 2 3 4 5

17 Saran dari orang tua 1 2 3 4 5

18 Banyak peminat/ banyak teman pada bidang konsentrasi tersebut

1 2 3 4 5

Content kuliah

19 Dosen yang mengajar menarik 1 2 3 4 5

20 Dosen yang mengajar menguasai materi kuliah yang disampaikan

1 2 3 4 5

21 Materi kuliah disajikan secara menarik 1 2 3 4 5

22 Distribusi penilaian yang diberikan 1 2 3 4 5

Keterkaitan mata kuliah jalur AK

23 Saya menguasai mata kuliah Teori Akuntansi (TA)

1 2 3 4 5

24 Saya menguasai mata kuliah Manajemen Keuangan (MK)

1 2 3 4 5

25 Saya menguasai mata kuliah AKM II 1 2 3 4 5

26 Saya menguasai mata kuliah Statistik 1 2 3 4 5



27 Saya menguasai mata kuliah Akuntansi Manajemen (Akmen)

1 2 3 4 5

Keterkaitan mata kuliah jalur AM

28 Saya menguasai mata kuliah Manajemen Keuangan (MK)

1 2 3 4 5

29 Saya menguasai mata kuliah Akuntansi Manajemen (Akmen)

1 2 3 4 5

30 Saya menguasai mata kuliah Pemeriksaan Akuntansi

1 2 3 4 5

Keterkaitan mata kuliah jalur SIA

31 Saya menguasai mata kuliah pengantar Aplikom lanjutan

1 2 3 4 5

32 Saya menguasai mata kuliah Sistem Informasi Akuntansi (SIA)

1 2 3 4 5

Faktor eksternal

33 Rencana studi yang akan saya ambil setelah lulus jenjang s1 mempengaruhi bidang konsentrasi

1 2 3 4 5

34 Lapangan kerja setelah lulus 1 2 3 4 5

Relevansi pengkonsentrasian di jurusan akuntansi

35 Pengkonsentrasian di jurusan akuntansi sebaiknya tetap dilakukan

1 2 3 4 5

Nilai terakhir mata kuliah berikut : A AB B BC C CD D E

Teori Akuntansi (TA)

Manajemen Keuangan (MK)

AKM II

Statistik

Akuntansi Manajemen (Akmen)

Pemeriksaan Akuntansi

Pengantar aplikom lanjutan

Sistem Informasi Akuntansi (SIA)



LAMPIRAN B

Statistic descriptive



1. Statistic descriptive jalur akuntansi keuangan Mahasiswa perempuan angkatan 2002 Descriptive Statistics N Minimum Maximum Mean Std. Deviation Motivasi Diri AK 3 16.00 18.00 16.6667 1.15470 Motivasi Org Lain 3 9.00 12.00 11.0000 1.73205 Conten Kuliah 3 13.00 15.00 14.3333 1.15470 keterkaitan MK AK 3 18.00 22.00 20.0000 2.00000 Faktor Eksternal 3 6.00 9.00 7.3333 1.52753 Valid N (listwise) 3

Mahasiswa laki-laki angkatan 2002 Descriptive Statistics N Minimum Maximum Mean Std. Deviation Motivasi Diri AK 4 13.00 20.00 16.2500 2.98608 Motivasi Org Lain 4 5.00 11.00 7.5000 2.64575 Conten Kuliah 4 7.00 18.00 12.0000 4.54606 keterkaitan MK AK 4 14.00 24.00 18.5000 4.12311 Faktor Eksternal 4 8.00 8.00 8.0000 .00000 Valid N (listwise) 4

Mahasiswa perempuan angkatan 2003 Descriptive Statistics N Minimum Maximum Mean Std. Deviation Motivasi Diri AK 43 8.00 20.00 15.6512 2.25604 Motivasi Org Lain 43 3.00 15.00 8.9070 3.09234 Conten Kuliah 43 6.00 19.00 13.4186 3.00185 keterkaitan MK AK 43 10.00 25.00 17.0930 2.52430 Faktor Eksternal 43 4.00 10.00 7.6977 1.38933 Valid N (listwise) 43



Mahasiswa laki-laki angkatan 2003 Descriptive Statistics N Minimum Maximum Mean Std. Deviation Motivasi Diri AK 11 5.00 16.00 12.4545 3.88236 Motivasi Org Lain 11 6.00 13.00 8.8182 2.40076 Conten Kuliah 11 8.00 17.00 12.9091 2.46798 keterkaitan MK AK 11 10.00 20.00 16.0909 2.77325 Faktor Eksternal 11 6.00 10.00 7.8182 .98165 Valid N (listwise) 11

2. Statistic descriptive jalur akuntansi manajemen Mahasiswa laki-laki angkatan 2002 Descriptive Statistics N Minimum Maximum Mean Std. Deviation Motivasi Diri AM 10 11.00 19.00 16.1000 2.18327 Motivasi Org Lain 10 6.00 13.00 8.9000 3.14289 Conten Kuliah 10 9.00 20.00 14.6000 3.06232 keterkaitan MK AM 10 8.00 15.00 10.5000 2.22361 Faktor Eksternal 10 4.00 10.00 7.2000 1.93218 Valid N (listwise) 10

Mahasiswa perempuan angkatan 2003 Descriptive Statistics N Minimum Maximum Mean Std. Deviation Motivasi Diri AM 42 12.00 19.00 16.0476 1.49719 Motivasi Org Lain 42 3.00 14.00 9.3810 2.83663 Conten Kuliah 42 9.00 20.00 14.4286 2.81237 keterkaitan MK AM 42 7.00 12.00 9.9048 1.46187 Faktor Eksternal 42 2.00 10.00 7.2143 1.93221 Valid N (listwise) 42



Mahasiswa laki-laki angkatan 2003 Descriptive Statistics N Minimum Maximum Mean Std. Deviation Motivasi Diri AM 16 14.00 19.00 15.6875 1.35247 Motivasi Org Lain 16 6.00 12.00 9.2500 1.91485 Conten Kuliah 16 5.00 20.00 14.2500 3.54965 keterkaitan MK AM 16 6.00 12.00 9.7500 1.43759 Faktor Eksternal 16 5.00 10.00 7.3750 1.31022 Valid N (listwise) 16

3. Statistic descriptive jalur sistem informasi

Mahasiswa perempuan angkatan 2002 Descriptive Statistics N Minimum Maximum Mean Std. Deviation Motivasi diri sia 3 16.00 20.00 18.6667 2.30940 Motivasi Org Lain 3 5.00 11.00 7.3333 3.21455 Conten Kuliah 3 14.00 17.00 15.6667 1.52753 Keterkaitan MK SIA 3 6.00 8.00 7.0000 1.00000 Faktor Eksternal 3 6.00 7.00 6.6667 .57735 Valid N (listwise) 3

Mahasiswa laki-laki angkatan 2002 Descriptive Statistics N Minimum Maximum Mean Std. Deviation Motivasi diri sia 4 18.00 20.00 19.5000 1.00000 Motivasi Org Lain 4 3.00 13.00 7.5000 4.43471 Conten Kuliah 4 18.00 20.00 19.2500 .95743 Keterkaitan MK SIA 4 8.00 10.00 9.0000 1.15470 Faktor Eksternal 4 6.00 10.00 9.0000 2.00000 Valid N (listwise) 4



Mahasiswa perempuan angkatan 2003 Descriptive Statistics N Minimum Maximum Mean Std. Deviation Motivasi diri sia 7 15.00 19.00 16.7143 1.88982 Motivasi Org Lain 7 5.00 12.00 8.8571 2.54484 Conten Kuliah 7 10.00 17.00 14.5714 2.50713 Keterkaitan MK SIA 7 6.00 9.00 7.2857 1.11270 Faktor Eksternal 7 6.00 9.00 7.2857 1.38013 Valid N (listwise) 7

Mahasiswa laki-laki angkatan 2003 Descriptive Statistics N Minimum Maximum Mean Std. Deviation Motivasi diri sia 23 12.00 20.00 17.3043 2.18330 Motivasi Org Lain 23 6.00 14.00 9.1304 2.56381 Conten Kuliah 23 5.00 20.00 16.2609 3.23640 Keterkaitan MK SIA 23 6.00 10.00 8.1304 1.09977 Faktor Eksternal 23 4.00 10.00 7.5652 1.70096 Valid N (listwise) 23

Tabel motivasi diri mahasiswa AK berdasarkan jenis kelamin Jenis Kelamin MDS1 MDS2 MDS3 MDS4

Mean 3.87 3.74 4.06 4.02 N 47 47 47 47

Perempuan

Std. Deviation .612 .706 .791 .571 Mean 3.31 3.38 3.38 3.69 N 16 16 16 16

Laki-laki

Std. Deviation 1.078 1.088 1.408 1.401 Mean 3.73 3.65 3.89 3.94 N 63 63 63 63

Total

Std. Deviation .787 .826 1.018 .859



Tabel motivasi diri mahasiswa AM berdasarkan jenis kelamin Jenis Kelamin MDS6 MDS7 MDS8 MDS9

Mean 3.93 4.16 4.07 3.84 N 44 44 44 44

Perempuan


Laki-laki


Total

Std. Deviation .504 .487 .583 .703 Tabel motivasi diri mahasiswa SIA berdasarkan jenis kelamin Jenis Kelamin MDS11 MDS12 MDS13 MDS14

Mean 4.40 4.50 4.10 4.30 N 10 10 10 10

Perempuan


Laki-laki


Total

Std. Deviation .604 .557 .789 .683 Tabel motivasi orang lain mahasiswa AK berdasarkan jenis kelamin Jenis Kelamin MOL1 MOL2 MOL3

Mean 2.85 3.11 3.02 N 47 47 47

Perempuan

Std. Deviation 1.285 1.068 1.170 Mean 3.00 2.69 2.81 N 16 16 16

Laki-laki

Std. Deviation 1.265 .946 1.109 Mean 2.89 3.00 2.97 N 63 63 63

Total

Std. Deviation 1.271 1.047 1.150



Tabel motivasi orang lain mahasiswa AM berdasarkan jenis kelamin Jenis Kelamin MOL1 MOL2 MOL3

Mean 3.27 3.07 3.05 N 44 44 44

Perempuan


Laki-laki

Std. Deviation 1.068 .974 1.121 Mean 3.28 2.87 3.07 N 71 71 71

Total

Std. Deviation 1.098 1.120 1.138 Tabel motivasi orang lain mahasiswa SIA berdasarkan jenis kelamin Jenis Kelamin MOL1 MOL2 MOL3

Mean 2.90 2.20 3.30 N 10 10 10

Perempuan


Laki-laki


Total

Std. Deviation 1.125 1.258 1.273



LAMPIRAN C

Validitas



1. faktor analisis jalur akuntansi keuangan Factor Analysis KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .827

Approx. Chi-Square 1227.496 df 171

Bartlett's Test of Sphericity

Sig. .000 Communalities Initial Extraction MDS1 1.000 .686 MDS2 1.000 .676 MDS3 1.000 .718 MDS4 1.000 .747 MDS5 1.000 .398 MOL1 1.000 .689 MOL2 1.000 .625 MOL3 1.000 .630 CK1 1.000 .621 CK2 1.000 .696 CK3 1.000 .727 CK4 1.000 .670 KMK1 1.000 .603 KMK2 1.000 .664 KMK3 1.000 .673 KMK4 1.000 .612 KMK5 1.000 .566 FE1 1.000 .713 FE2 1.000 .683

Extraction Method: Principal Component Analysis.



Total Variance Explained

Component Initial Eigenvalues

Extraction Sums of Squared Loadings

Rotation Sums of Squared Loadings

Total % of

Variance Cumulative

% Total % of

Variance Cumulative

% Total % of

Variance Cumulative

% 1 5.072 26.692 26.692 5.072 26.692 26.692 2.994 15.758 15.758 2 2.731 14.376 41.068 2.731 14.376 41.068 2.945 15.500 31.258 3 2.034 10.707 51.775 2.034 10.707 51.775 2.868 15.092 46.350 4 1.350 7.108 58.883 1.350 7.108 58.883 2.020 10.631 56.982 5 1.209 6.363 65.246 1.209 6.363 65.246 1.570 8.264 65.246 6 .798 4.202 69.448 7 .676 3.556 73.004 8 .642 3.378 76.382 9 .621 3.270 79.652 10 .537 2.827 82.479 11 .501 2.635 85.114 12 .470 2.474 87.589 13 .423 2.224 89.813 14 .386 2.032 91.844 15 .365 1.919 93.764 16 .343 1.806 95.570 17 .310 1.634 97.204 18 .282 1.487 98.690 19 .249 1.310 100.000

Extraction Method: Principal Component Analysis. Component Matrix(a)

Component 1 2 3 4 5 MDS1 .544 -.406 MDS2 .561 -.490 MDS3 .537 -.484 MDS4 .552 -.468 .415 MDS5 .438 MOL1 .464 .441 MOL2 -.410 MOL3 .546 CK1 .405 .656 CK2 .585 .507 CK3 .502 .594 CK4 .515 .591 KMK1 .525 -.432 KMK2 .572 -.557 KMK3 .571 KMK4 .594 -.413 KMK5 .616 FE1 .410 .528 .506 FE2 .613

Extraction Method: Principal Component Analysis. a 5 components extracted.



Rotated Component Matrix(a)

Component 1 2 3 4 5 MDS1 .810 MDS2 .774 MDS3 .830 MDS4 .844 MDS5 .550 MOL1 .785 MOL2 .775 MOL3 .722 CK1 .704 CK2 .781 CK3 .839 CK4 .787 KMK1 .742 KMK2 .778 KMK3 .788 KMK4 .725 KMK5 .666 FE1 .816 FE2 .787

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 6 iterations. Component Transformation Matrix Component 1 2 3 4 5 1 .572 .487 .489 .356 .263 2 -.270 .731 -.570 .255 -.051 3 -.689 -.011 .534 .476 -.118 4 -.353 .217 .157 -.496 .747 5 .030 -.426 -.354 .579 .597

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.



2. faktor analisis jalur akuntansi manajemen Factor Analysis KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .797



Sig. .000 Communalities Initial Extraction MDS6 1.000 .630 MDS7 1.000 .704 MDS8 1.000 .675 MDS9 1.000 .614 MDS10 1.000 .438 MOL1 1.000 .706 MOL2 1.000 .645 MOL3 1.000 .637 CK1 1.000 .599 CK2 1.000 .688 CK3 1.000 .730 CK4 1.000 .679 KMK2 1.000 .678 KMK5 1.000 .655 KMK6 1.000 .652 FE1 1.000 .700 FE2 1.000 .709




Total Variance Explained

Component Initial Eigenvalues



Total % of

Variance Cumulative

% Total % of

Variance Cumulative

% Total % of

Variance Cumulativ

e % 1 4.756 27.979 27.979 4.756 27.979 27.979 2.941 17.299 17.299 2 2.129 12.522 40.501 2.129 12.522 40.501 2.634 15.496 32.794 3 1.821 10.715 51.215 1.821 10.715 51.215 2.032 11.955 44.750 4 1.334 7.848 59.063 1.334 7.848 59.063 1.983 11.667 56.417 5 1.100 6.471 65.535 1.100 6.471 65.535 1.550 9.118 65.535 6 .837 4.925 70.460 7 .697 4.099 74.559 8 .625 3.674 78.233 9 .604 3.553 81.786 10 .528 3.105 84.892 11 .489 2.874 87.765 12 .457 2.688 90.453 13 .365 2.148 92.602 14 .355 2.086 94.688 15 .337 1.984 96.672 16 .302 1.778 98.450 17 .264 1.550 100.000


Component 1 2 3 4 5 MDS6 .439 .610 MDS7 .548 .571 MDS8 .545 .593 MDS9 .475 .591 MDS10 .476 MOL1 .545 -.411 .462 MOL2 .531 MOL3 .600 CK1 .612 CK2 .656 -.410 CK3 .671 CK4 .655 KMK2 .410 .531 KMK5 .539 .509 KMK6 .571 .406 FE1 .454 FE2 .510 .507





Component 1 2 3 4 5 MDS6 .784 MDS7 .804 MDS8 .781 MDS9 .746 MDS10 .521 MOL1 .773 MOL2 .798 MOL3 .716 CK1 .706 CK2 .767 CK3 .822 CK4 .795 KMK2 .804 KMK5 .737 KMK6 .736 FE1 .793 FE2 .812

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 6 iterations. Component Transformation Matrix Component 1 2 3 4 5 1 .631 .471 .402 .400 .244 2 -.493 .825 -.210 .105 -.144 3 -.360 .092 .641 -.475 .475 4 -.434 -.272 -.001 .728 .455 5 .205 .121 -.619 -.270 .698




3. faktor analisis jalur system informasi Factor Analysis KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .820



Sig. .000 Communalities Initial Extraction MDS11 1.000 .769 MDS12 1.000 .801 MDS13 1.000 .794 MDS14 1.000 .807 MDS15 1.000 .392 MOL1 1.000 .662 MOL2 1.000 .633 MOL3 1.000 .640 CK1 1.000 .588 CK2 1.000 .694 CK3 1.000 .736 CK4 1.000 .675 KMK7 1.000 .724 KMK8 1.000 .851 FE1 1.000 .667 FE2 1.000 .747




Total Variance Explained Component Initial Eigenvalues



Total % of

Variance Cumulative

% Total % of

Variance Cumulative

% Total % of

Variance Cumulative

% 1 4.827 30.168 30.168 4.827 30.168 30.168 3.219 20.116 20.116 2 2.398 14.988 45.156 2.398 14.988 45.156 2.930 18.311 38.427 3 1.721 10.757 55.913 1.721 10.757 55.913 2.050 12.813 51.240 4 1.346 8.410 64.323 1.346 8.410 64.323 1.582 9.889 61.130 5 .890 5.560 69.883 .890 5.560 69.883 1.401 8.753 69.883 6 .803 5.019 74.902 7 .622 3.890 78.793 8 .587 3.666 82.458 9 .533 3.330 85.789 10 .465 2.908 88.697 11 .397 2.483 91.180 12 .370 2.315 93.495 13 .311 1.945 95.440 14 .288 1.797 97.237 15 .233 1.457 98.695 16 .209 1.305 100.000


Component 1 2 3 4 5 MDS11 .624 -.569 MDS12 .704 -.524 MDS13 .655 -.589 MDS14 .622 -.593 MDS15 .511 MOL1 .452 .406 MOL2 .505 -.402 MOL3 .465 .434 CK1 .594 CK2 .617 .409 CK3 .684 CK4 .719 KMK7 .467 .631 KMK8 .490 .688 FE1 .416 .554 FE2 .585 .438





Component 1 2 3 4 5 MDS11 .858 MDS12 .865 MDS13 .861 MDS14 .892 MDS15 .517 MOL1 .778 MOL2 .786 MOL3 .751 CK1 .685 CK2 .805 CK3 .822 CK4 .748 KMK7 .704 KMK8 .882 FE1 .773 FE2 .854

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 6 iterations. Component Transformation Matrix Component 1 2 3 4 5 1 .604 .637 .309 .235 .280 2 -.740 .429 .513 .072 -.008 3 -.277 .090 -.553 .607 .491 4 .094 -.585 .541 .595 .034 5 -.051 -.243 .207 -.465 .824




LAMPIRAN D

Reliabilitas



Reliability ****** Method 2 (covariance matrix) will be used for this analysis ****** _ R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A) Mean Std Dev Cases 1. MDS1 3.5988 .9091 172.0 2. MDS2 3.6395 .8841 172.0 3. MDS3 3.6512 1.0233 172.0 4. MDS4 3.7674 .8809 172.0 Correlation Matrix MDS1 MDS2 MDS3 MDS4 MDS1 1.0000 MDS2 .5976 1.0000 MDS3 .5905 .5583 1.0000 MDS4 .5839 .6426 .6685 1.0000 N of Cases = 172.0 N of Statistics for Mean Variance Std Dev Variables Scale 14.6570 9.6419 3.1051 4 Item-total Statistics Scale Scale Corrected Mean Variance Item- Squared Alpha if Item if Item Total Multiple if Item Deleted Deleted Correlation Correlation Deleted MDS1 11.0581 5.8212 .6826 .4688 .8288 MDS2 11.0174 5.8886 .6926 .4956 .8251 MDS3 11.0058 5.2807 .7046 .5150 .8228 MDS4 10.8895 5.7246 .7452 .5653 .8043 Reliability Coefficients 4 items Alpha = .8588 Standardized item alpha = .8606



Reliability ****** Method 2 (covariance matrix) will be used for this analysis ****** _ R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A) Mean Std Dev Cases 1. MDS6 3.5291 .8613 172.0 2. MDS7 3.6919 .9134 172.0 3. MDS8 3.7849 .8687 172.0 4. MDS9 3.7093 .8358 172.0 Correlation Matrix MDS6 MDS7 MDS8 MDS9 MDS6 1.0000 MDS7 .5801 1.0000 MDS8 .4891 .5424 1.0000 MDS9 .4098 .4948 .5819 1.0000 N of Cases = 172.0 N of Statistics for Mean Variance Std Dev Variables Scale 14.7151 7.7254 2.7795 4 Item-total Statistics Scale Scale Corrected Mean Variance Item- Squared Alpha if Item if Item Total Multiple if Item Deleted Deleted Correlation Correlation Deleted MDS6 11.1860 4.7488 .5953 .3830 .7774 MDS7 11.0233 4.3620 .6628 .4498 .7452 MDS8 10.9302 4.5331 .6590 .4480 .7473 MDS9 11.0058 4.8362 .5959 .3874 .7771 Reliability Coefficients 4 items Alpha = .8105 Standardized item alpha = .8103



Reliability ****** Method 2 (covariance matrix) will be used for this analysis ****** _ R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A) Mean Std Dev Cases 1. MDS11 3.7849 .9764 172.0 2. MDS12 3.7384 .9279 172.0 3. MDS13 3.6221 .8867 172.0 4. MDS14 3.7674 .9199 172.0 Correlation Matrix MDS11 MDS12 MDS13 MDS14 MDS11 1.0000 MDS12 .6991 1.0000 MDS13 .6621 .7534 1.0000 MDS14 .7318 .7094 .7233 1.0000 N of Cases = 172.0 N of Statistics for Mean Variance Std Dev Variables Scale 14.9128 10.8052 3.2871 4 Item-total Statistics Scale Scale Corrected Mean Variance Item- Squared Alpha if Item if Item Total Multiple if Item Deleted Deleted Correlation Correlation Deleted MDS11 11.1279 6.1239 .7714 .6065 .8893 MDS12 11.1744 6.2267 .8028 .6543 .8771 MDS13 11.2907 6.4530 .7916 .6447 .8815 MDS14 11.1453 6.2536 .8054 .6523 .8762 Reliability Coefficients 4 items Alpha = .9080 Standardized item alpha = .9086



Reliability ****** Method 2 (covariance matrix) will be used for this analysis ****** _ R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A) Mean Std Dev Cases 1. MOL1 3.1279 1.1777 172.0 2. MOL2 2.8721 1.1270 172.0 3. MOL3 3.0174 1.1672 172.0 Correlation Matrix MOL1 MOL2 MOL3 MOL1 1.0000 MOL2 .4750 1.0000 MOL3 .5216 .4107 1.0000 N of Cases = 172.0 N of Statistics for Mean Variance Std Dev Variables Scale 9.0174 7.7950 2.7920 3 Item-total Statistics Scale Scale Corrected Mean Variance Item- Squared Alpha if Item if Item Total Multiple if Item Deleted Deleted Correlation Correlation Deleted MOL1 5.8895 3.7129 .5938 .3539 .5820 MOL2 6.1453 4.1834 .5079 .2621 .6856 MOL3 6.0000 3.9181 .5442 .3064 .6437 Reliability Coefficients 3 items Alpha = .7265 Standardized item alpha = .7261



Reliability ****** Method 2 (covariance matrix) will be used for this analysis ****** _ R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A) Mean Std Dev Cases 1. CK1 3.2733 1.1347 172.0 2. CK2 3.8663 .8981 172.0 3. CK3 3.7733 .9495 172.0 4. CK4 3.4477 .9868 172.0 Correlation Matrix CK1 CK2 CK3 CK4 CK1 1.0000 CK2 .5181 1.0000 CK3 .5192 .5815 1.0000 CK4 .5012 .5958 .6270 1.0000 N of Cases = 172.0 N of Statistics for Mean Variance Std Dev Variables Scale 14.3605 10.4892 3.2387 4 Item-total Statistics Scale Scale Corrected Mean Variance Item- Squared Alpha if Item if Item Total Multiple if Item Deleted Deleted Correlation Correlation Deleted CK1 11.0872 5.9046 .5979 .3593 .8187 CK2 10.4942 6.5789 .6737 .4590 .7789 CK3 10.5872 6.3023 .6892 .4869 .7698 CK4 10.9128 6.1619 .6845 .4891 .7708 Reliability Coefficients 4 items Alpha = .8288 Standardized item alpha = .8342



Reliability ****** Method 2 (covariance matrix) will be used for this analysis ****** R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A) Mean Std Dev Cases 1. KMK1 3.0116 .7872 172.0 2. KMK2 3.1453 .8494 172.0 3. KMK3 3.1395 .8117 172.0 4. KMK4 3.0698 .8348 172.0 5. KMK5 3.4419 .8251 172.0 Covariance Matrix KMK1 KMK2 KMK3 KMK4 KMK5 KMK1 .6197 KMK2 .3550 .7214 KMK3 .3317 .3656 .6588 KMK4 .2740 .3407 .3469 .6969 KMK5 .2638 .3389 .2947 .3725 .6808 Correlation Matrix KMK1 KMK2 KMK3 KMK4 KMK5 KMK1 1.0000 KMK2 .5309 1.0000 KMK3 .5191 .5303 1.0000 KMK4 .4170 .4805 .5120 1.0000 KMK5 .4062 .4836 .4401 .5408 1.0000 N of Cases = 172.0 Item-total Statistics Scale Scale Corrected Mean Variance Item- Squared Alpha if Item if Item Total Multiple if Item Deleted Deleted Correlation Correlation Deleted KMK1 12.7965 6.8765 .5932 .3751 .7986 KMK2 12.6628 6.4236 .6504 .4296 .7820 KMK3 12.6686 6.6088 .6417 .4217 .7848 KMK4 12.7384 6.5803 .6230 .4084 .7901 KMK5 12.3663 6.7247 .5935 .3737 .7986 R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A) Reliability Coefficients 5 items Alpha = .8255 Standardized item alpha = .8254



Reliability ****** Method 2 (covariance matrix) will be used for this analysis ****** R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A) Mean Std Dev Cases 1. KMK2 3.1453 .8494 172.0 2. KMK5 3.4419 .8251 172.0 3. KMK6 3.3547 .7546 172.0 Correlation Matrix KMK2 KMK5 KMK6 KMK2 1.0000 KMK5 .4836 1.0000 KMK6 .4392 .4982 1.0000 N of Cases = 172.0 N of Statistics for Mean Variance Std Dev Variables Scale 9.9419 3.8329 1.9578 3 Item-total Statistics Scale Scale Corrected Mean Variance Item- Squared Alpha if Item if Item Total Multiple if Item Deleted Deleted Correlation Correlation Deleted KMK2 6.7965 1.8706 .5340 .2861 .6633 KMK5 6.5000 1.8538 .5778 .3351 .6074 KMK6 6.5872 2.0801 .5437 .2995 .6517 Reliability Coefficients 3 items Alpha = .7284 Standardized item alpha = .7297



Reliability ****** Method 2 (covariance matrix) will be used for this analysis ****** _ R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A) Mean Std Dev Cases 1. KMK7 3.8895 .7129 172.0 2. KMK8 3.5814 .7249 172.0 Correlation Matrix KMK7 KMK8 KMK7 1.0000 KMK8 .4758 1.0000 N of Cases = 172.0 N of Statistics for Mean Variance Std Dev Variables Scale 7.4709 1.5255 1.2351 2 Item-total Statistics Scale Scale Corrected Mean Variance Item- Squared Alpha if Item if Item Total Multiple if Item Deleted Deleted Correlation Correlation Deleted KMK7 3.5814 .5255 .4758 .2264 . KMK8 3.8895 .5082 .4758 .2264 . Reliability Coefficients 2 items Alpha = .6448 Standardized item alpha = .6448



Reliability ****** Method 2 (covariance matrix) will be used for this analysis ****** R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A) Mean Std Dev Cases 1. FE1 3.5698 .9182 172.0 2. FE2 3.9419 .9222 172.0 Correlation Matrix FE1 FE2 FE1 1.0000 FE2 .4537 1.0000 N of Cases = 172.0 N of Statistics for Mean Variance Std Dev Variables Scale 7.5116 2.4619 1.5690 2 Item-total Statistics Scale Scale Corrected Mean Variance Item- Squared Alpha if Item if Item Total Multiple if Item Deleted Deleted Correlation Correlation Deleted FE1 3.9419 .8504 .4537 .2059 . FE2 3.5698 .8431 .4537 .2059 . Reliability Coefficients 2 items Alpha = .6242 Standardized item alpha = .6242



LAMPIRAN E

Regresi Logistik



1. Regresi logistik konsentrasi akuntansi keuangan Logistic Regression Case Processing Summary Unweighted Cases(a) N Percent

Included in Analysis 172 100.0 Missing Cases 0 .0

Selected Cases

Total 172 100.0 Unselected Cases 0 .0 Total 172 100.0

a If weight is in effect, see classification table for the total number of cases. Dependent Variable Encoding Original Value Internal Value non ak 0 ak 1

Block 0: Beginning Block Iteration History(a,b,c)

Coefficients

Iteration -2 Log

likelihood Constant 1 225.996 -.535 2 225.989 -.548

Step 0

3 225.989 -.548 a Constant is included in the model. b Initial -2 Log Likelihood: 225.989 c Estimation terminated at iteration number 3 because parameter estimates changed by less than .001. Classification Table(a,b)

Observed Predicted

akt keu

non ak ak Percentage

Correct akt keu non ak 109 0 100.0 ak 63 0 .0

Step 0

Overall Percentage 63.4 a Constant is included in the model. b The cut value is .500 Variables in the Equation B S.E. Wald df Sig. Exp(B) Step 0 Constant -.548 .158 11.999 1 .001 .578



Variables not in the Equation Score df Sig.

MDSAK 3.130 1 .077 MOL .330 1 .566 CK 11.339 1 .001 KMKAK 18.774 1 .000

Variables

FE 1.417 1 .234

Step 0

Overall Statistics 39.814 5 .000 Block 1: Method = Enter Iteration History(a,b,c,d)

Coefficients

Iteration -2 Log

likelihood Constant MDSAK MOL CK KMKAK FE 1 182.915 -1.748 .006 .013 -.220 .248 .032 2 177.211 -2.815 .009 .035 -.313 .384 .010 3 176.911 -3.121 .011 .040 -.339 .425 -.005 4 176.909 -3.142 .011 .041 -.341 .428 -.006

Step 1

5 176.909 -3.142 .011 .041 -.341 .428 -.006 a Method: Enter b Constant is included in the model. c Initial -2 Log Likelihood: 225.989 d Estimation terminated at iteration number 5 because parameter estimates changed by less than .001. Omnibus Tests of Model Coefficients Chi-square df Sig.

Step 49.080 5 .000 Block 49.080 5 .000

Step 1

Model 49.080 5 .000 Model Summary

Step -2 Log

likelihood Cox & Snell R Square

Nagelkerke R Square

1 176.909 .248 .339 Hosmer and Lemeshow Test Step Chi-square df Sig. 1 3.695 8 .884



Contingency Table for Hosmer and Lemeshow Test

akt keu = non ak akt keu = ak Observed Expected Observed Expected Total

1 16 16.412 1 .588 17 2 17 15.264 0 1.736 17 3 14 14.338 3 2.662 17 4 12 13.326 5 3.674 17 5 11 12.251 6 4.749 17 6 11 10.665 6 6.335 17 7 9 9.392 8 7.608 17 8 9 8.096 8 8.904 17 9 6 5.669 11 11.331 17

Step 1

10 4 3.588 15 15.412 19

Classification Table(a)

Observed Predicted

akt keu

non ak ak Percentage

Correct akt keu non ak 94 15 86.2 ak 29 34 54.0

Step 1

Overall Percentage 74.4 a The cut value is .500 Variables in the Equation B S.E. Wald df Sig. Exp(B)

MDSAK .011 .072 .025 1 .875 1.011 MOL .041 .078 .271 1 .603 1.042 CK -.341 .076 20.337 1 .000 .711 KMKAK .428 .092 21.439 1 .000 1.534 FE -.006 .136 .002 1 .963 .994

Step 1(a)

Constant -3.142 1.457 4.648 1 .031 .043

a Variable(s) entered on step 1: MDSAK, MOL, CK, KMKAK, FE.



Correlation Matrix Constant MDSAK MOL CK KMKAK FE

Constant 1.000 -.311 -.107 -.104 -.413 -.284

MDSAK -.311 1.000 -.176 .034 -.193 -.225 MOL -.107 -.176 1.000 -.385 .037 -.022 CK -.104 .034 -.385 1.000 -.450 .018 KMKAK -.413 -.193 .037 -.450 1.000 -.249

Step 1

FE -.284 -.225 -.022 .018 -.249 1.000 Step number: 1 _ Observed Groups and Predicted Probabilities 16 F R 12 E Q n U n E 8 n N n a a a C n n a aaa a a Y n n n a ann a a a a 4 n nna n n n ann n aaa a na a a a nnnnnnnnn nnnnn nan nnna naanaaa a a a nnnnnnnnn nnnnn nnan nnnnannannaa ana aaaanaa a a nnnnnnnnnnnnnnnannnnannnnnnnnnnnnannn naannnnaaa aaa a n a Predicted Prob: 0 .25 .5 .75 1 Group: nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa Predicted Probability is of Membership for ak The Cut Value is .50 Symbols: n - non ak a - ak Each Symbol Represents 1 Case.



2. Regresi logistik konsentrasi akuntansi manajemen Logistic Regression Case Processing Summary Unweighted Cases(a) N Percent


Selected Cases


a If weight is in effect, see classification table for the total number of cases. Dependent Variable Encoding Original Value Internal Value non am 0 am 1


Coefficients

Iteration -2 Log

likelihood Constant 1 233.184 -.349 2 233.183 -.352

Step 0

3 233.183 -.352 a Constant is included in the model. b Initial -2 Log Likelihood: 233.183 c Estimation terminated at iteration number 3 because parameter estimates changed by less than .001. Classification Table(a,b)

Observed Predicted

akt mnj

non am am Percentage

Correct akt mnj non am 101 0 100.0 am 71 0 .0

Step 0

Overall Percentage 58.7 a Constant is included in the model. b The cut value is .500 Variables in the Equation B S.E. Wald df Sig. Exp(B) Step 0 Constant -.352 .155 5.179 1 .023 .703




MDSAM 24.309 1 .000 MOL .674 1 .412 CK .030 1 .863 KMKAM .029 1 .866

Variables

FE 2.302 1 .129

Step 0


Coefficients

Iteration -2 Log

likelihood Constant MDSAM MOL CK KMKAM FE 1 198.949 -2.462 .300 -.015 -.044 -.013 -.187 2 193.654 -3.901 .459 .022 -.097 -.034 -.242 3 193.367 -4.476 .508 .031 -.110 -.038 -.249 4 193.365 -4.521 .511 .032 -.111 -.038 -.249

Step 1

5 193.365 -4.521 .511 .032 -.111 -.038 -.249 a Method: Enter b Constant is included in the model. c Initial -2 Log Likelihood: 233.183 d Estimation terminated at iteration number 5 because parameter estimates changed by less than .001. Omnibus Tests of Model Coefficients Chi-square df Sig.

Step 39.818 5 .000 Block 39.818 5 .000

Step 1


Step -2 Log


Nagelkerke R Square

1 193.365 .207 .278 Hosmer and Lemeshow Test Step Chi-square df Sig. 1 3.507 8 .899




akt mnj = non am akt mnj = am Observed Expected Observed Expected Total

1 17 16.257 0 .743 17 2 13 14.271 4 2.729 17 3 13 13.116 4 3.884 17 4 12 11.838 5 5.162 17 5 12 10.440 5 6.560 17 6 10 9.492 7 7.508 17 7 7 8.528 10 8.472 17 8 6 7.345 11 9.655 17 9 6 5.760 11 11.240 17

Step 1

10 5 3.954 14 15.046 19 Classification Table(a)

Observed Predicted

akt mnj

non am am Percentage

Correct akt mnj non am 81 20 80.2 am 30 41 57.7

Step 1


MDSAM .511 .105 23.513 1 .000 1.668 MOL .032 .072 .192 1 .661 1.032 CK -.111 .070 2.548 1 .110 .895 KMKAM -.038 .113 .113 1 .737 .963 FE -.249 .125 3.943 1 .047 .780

Step 1(a)

Constant -4.521 1.684 7.205 1 .007 .011

a Variable(s) entered on step 1: MDSAM, MOL, CK, KMKAM, FE. Correlation Matrix Constant MDSAM MOL CK KMKAM FE

Constant 1.000 -.653 -.119 -.028 -.206 -.281

MDSAM -.653 1.000 .022 -.274 -.162 -.084 MOL -.119 .022 1.000 -.406 -.009 -.088 CK -.028 -.274 -.406 1.000 -.249 .040 KMKAM -.206 -.162 -.009 -.249 1.000 -.282

Step 1

FE -.281 -.084 -.088 .040 -.282 1.000



Step number: 1 Observed Groups and Predicted Probabilities 8 a a a a F a a R 6 a n a aa a a E a n a aa a a Q n a na a n a aan a a a a U n a na a n a aan a a a a E 4 n n nna aan n anan aaa a a aa a a N n n nna aan n anan aaa a a aa a a C nnnn n nannnn nnn aan nnnnanaaaanaa aa aa a Y nnnn n nannnn nnn aan nnnnanaaaanaa aa aa a 2 nnnn n nannnn nnnnnan nnnnnnanaanaa aanaaa aa a a nnnn n nannnn nnnnnan nnnnnnanaanaa aanaaa aa a a nnnn nn nnnnnnnnnnnnannnnnnnnnnnnnannannnnnnnnaanaan nnnn nn nnnnnnnnnnnnannnnnnnnnnnnnannannnnnnnnaanaan Predicted Prob: 0 .25 .5 .75 1 Group: nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa Predicted Probability is of Membership for am The Cut Value is .50 Symbols: n - non am a - am Each Symbol Represents .5 Cases.



3. Regresi logistik konsentrasi sistem informasi Logistic Regression Case Processing Summary Unweighted Cases(a) N Percent


Selected Cases


a If weight is in effect, see classification table for the total number of cases. Dependent Variable Encoding Original Value Internal Value non si 0 si 1


Coefficients

Iteration -2 Log

likelihood Constant 1 182.291 -1.116 2 181.661 -1.255 3 181.660 -1.260

Step 0

4 181.660 -1.260 a Constant is included in the model. b Initial -2 Log Likelihood: 181.660 c Estimation terminated at iteration number 4 because parameter estimates changed by less than .001. Classification Table(a,b)

Observed Predicted

sistem

non si si Percentage

Correct sistem non si 134 0 100.0 si 38 0 .0

Step 0

Overall Percentage 77.9 a Constant is included in the model. b The cut value is .500



Variables in the Equation B S.E. Wald df Sig. Exp(B) Step 0 Constant -1.260 .184 47.019 1 .000 .284


MDSSIA 32.916 1 .000 MOL .095 1 .758 CK 16.933 1 .000 KMKSIA 8.129 1 .004

Variables

FE .175 1 .676

Step 0


Coefficients

Iteration -2 Log

likelihood Constant MDSSIA MOL CK KMKSIA FE 1 143.537 -4.989 .187 -.099 .132 .079 -.067 2 130.291 -8.381 .333 -.122 .212 .104 -.121 3 128.075 -10.397 .426 -.125 .258 .094 -.152 4 127.981 -10.902 .450 -.126 .271 .089 -.161 5 127.981 -10.927 .451 -.126 .272 .088 -.162

Step 1

6 127.981 -10.927 .451 -.126 .272 .088 -.162 a Method: Enter b Constant is included in the model. c Initial -2 Log Likelihood: 181.660 d Estimation terminated at iteration number 6 because parameter estimates changed by less than .001. Omnibus Tests of Model Coefficients Chi-square df Sig.

Step 53.680 5 .000 Block 53.680 5 .000

Step 1


Step -2 Log


Nagelkerke R Square

1 127.981 .268 .411



Hosmer and Lemeshow Test Step Chi-square df Sig. 1 3.456 8 .903


sistem = non si sistem = si Observed Expected Observed Expected Total

1 17 16.911 0 .089 17 2 17 16.714 0 .286 17 3 16 16.390 1 .610 17 4 16 15.879 1 1.121 17 5 14 15.121 3 1.879 17 6 13 14.265 4 2.735 17 7 14 13.101 3 3.899 17 8 13 11.514 4 5.486 17 9 10 9.073 7 7.927 17

Step 1

10 4 5.033 15 13.967 19 Classification Table(a)

Observed Predicted

sistem

non si si Percentage

Correct sistem non si 126 8 94.0 si 22 16 42.1

Step 1


MDSSIA .451 .106 18.003 1 .000 1.569 MOL -.126 .086 2.130 1 .144 .882 CK .272 .104 6.773 1 .009 1.312 KMKSIA .088 .216 .168 1 .682 1.093 FE -.162 .153 1.124 1 .289 .851

Step 1(a)

Constant -10.927 2.319 22.198 1 .000 .000

a Variable(s) entered on step 1: MDSSIA, MOL, CK, KMKSIA, FE.



Correlation Matrix Constant MDSSIA MOL CK KMKSIA FE

Constant 1.000 -.577 -.144 -.286 -.307 -.158

MDSSIA -.577 1.000 .067 -.068 -.171 -.084 MOL -.144 .067 1.000 -.337 -.030 .017 CK -.286 -.068 -.337 1.000 -.228 -.172 KMKSIA -.307 -.171 -.030 -.228 1.000 -.221

Step 1

FE -.158 -.084 .017 -.172 -.221 1.000 Step number: 1 Observed Groups and Predicted Probabilities 32 n F n R 24 n E n Q n U n E 16 n N ns C nn n Y nnnn 8 nnnn s s s nnnnnnnss ns n s nnnnnnnnnnnn nn nnn s n s s nnnnnnnnnnnnnnnsnnnnn ns snnsnnsn nns n ssns sssss s Predicted Prob: 0 .25 .5 .75 1 Group: nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnssssssssssssssssssssssssssssss Predicted Probability is of Membership for si The Cut Value is .50 Symbols: n - non si s - si Each Symbol Represents 2 Cases.



LAMPIRAN F

ANOVA



Oneway Descriptives

N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean

Minimum

Maximum

Lower Bound

Upper Bound

Teori Akuntansi AK 63 4.8095 1.82153 .22949 4.3508 5.2683 .00 8.00 AM 71 3.5634 1.97652 .23457 3.0955 4.0312 .00 8.00 SIA 38 3.0789 1.87993 .30497 2.4610 3.6969 .00 8.00 Total 172 3.9128 2.01702 .15380 3.6092 4.2164 .00 8.00 Manajemen Keuangan

AK 63 6.5079 1.61518 .20349 6.1012 6.9147 2.00 8.00

AM 71 4.8592 1.58831 .18850 4.4832 5.2351 .00 8.00 SIA 38 4.7105 1.69112 .27434 4.1547 5.2664 1.00 8.00 Total 172 5.4302 1.80992 .13801 5.1578 5.7026 .00 8.00 Akt Keu 2 AK 63 5.8889 1.41548 .17833 5.5324 6.2454 2.00 8.00 AM 71 4.5352 1.24017 .14718 4.2417 4.8288 1.00 8.00 SIA 38 3.9474 1.62659 .26387 3.4127 4.4820 1.00 8.00 Total 172 4.9012 1.59553 .12166 4.6610 5.1413 1.00 8.00 Statistik AK 63 5.3968 1.90534 .24005 4.9170 5.8767 .00 8.00 AM 71 4.2394 1.58983 .18868 3.8631 4.6157 .00 8.00 SIA 38 3.4211 1.15388 .18718 3.0418 3.8003 2.00 7.00 Total 172 4.4826 1.79497 .13687 4.2124 4.7527 .00 8.00 Akt Manajemen AK 63 6.4444 1.76688 .22261 5.9995 6.8894 .00 8.00 AM 71 5.5493 1.60168 .19008 5.1702 5.9284 .00 8.00 SIA 38 4.6842 1.87595 .30432 4.0676 5.3008 .00 8.00 Total 172 5.6860 1.84017 .14031 5.4091 5.9630 .00 8.00 Auditing AK 63 5.3016 1.91459 .24122 4.8194 5.7838 .00 8.00 AM 71 4.3099 1.76952 .21000 3.8910 4.7287 .00 8.00 SIA 38 3.7895 2.23193 .36207 3.0559 4.5231 .00 8.00 Total 172 4.5581 2.01227 .15343 4.2553 4.8610 .00 8.00 Peng.Aplikom Lanj

AK 63 7.0159 1.22464 .15429 6.7075 7.3243 4.00 8.00

AM 71 6.3521 1.52220 .18065 5.9918 6.7124 .00 8.00 SIA 38 6.3158 1.84692 .29961 5.7087 6.9229 2.00 8.00 Total 172 6.5872 1.52885 .11657 6.3571 6.8173 .00 8.00 SIA AK 63 5.8413 1.61851 .20391 5.4337 6.2489 2.00 8.00 AM 71 5.1549 1.46041 .17332 4.8093 5.5006 2.00 8.00 SIA 38 5.1579 1.34619 .21838 4.7154 5.6004 4.00 8.00 Total 172 5.4070 1.52467 .11626 5.1775 5.6365 2.00 8.00



ANOVA

Sum of

Squares df Mean Square F Sig. Between Groups 85.750 2 42.875 11.880 .000 Within Groups 609.942 169 3.609

Teori Akuntansi

Total 695.692 171 Between Groups 116.009 2 58.005 22.071 .000 Within Groups 444.153 169 2.628

Manajemen Keuangan


Akt Keu 2


Statistik


Akt Manajemen


Auditing


Peng.Aplikom Lanj


SIA

Total 397.512 171



Post Hoc Tests Multiple Comparisons Tukey HSD

Dependent Variable

(I) Kosentrasi

(J) Kosentrasi

Mean Difference

(I-J) Std. Error Sig. 95% Confidence Interval

Lower Bound Upper Bound Teori Akuntansi AK AM 1.2461(*) .32882 .001 .4686 2.0236 SIA 1.7306(*) .39021 .000 .8079 2.6532 AM AK -1.2461(*) .32882 .001 -2.0236 -.4686 SIA .4844 .38185 .415 -.4185 1.3873 SIA AK -1.7306(*) .39021 .000 -2.6532 -.8079 AM -.4844 .38185 .415 -1.3873 .4185 Manajemen Keuangan

AK AM 1.6488(*) .28059 .000 .9853 2.3123

SIA 1.7974(*) .33298 .000 1.0101 2.5848 AM AK -1.6488(*) .28059 .000 -2.3123 -.9853 SIA .1486 .32585 .892 -.6219 .9191 SIA AK -1.7974(*) .33298 .000 -2.5848 -1.0101 AM -.1486 .32585 .892 -.9191 .6219 Akt Keu 2 AK AM 1.3537(*) .24178 .000 .7820 1.9254 SIA 1.9415(*) .28692 .000 1.2631 2.6200 AM AK -1.3537(*) .24178 .000 -1.9254 -.7820 SIA .5878 .28078 .094 -.0761 1.2518 SIA AK -1.9415(*) .28692 .000 -2.6200 -1.2631 AM -.5878 .28078 .094 -1.2518 .0761 Statistik AK AM 1.1574(*) .28283 .000 .4886 1.8262 SIA 1.9758(*) .33564 .000 1.1821 2.7694 AM AK -1.1574(*) .28283 .000 -1.8262 -.4886 SIA .8184(*) .32845 .036 .0418 1.5950 SIA AK -1.9758(*) .33564 .000 -2.7694 -1.1821 AM -.8184(*) .32845 .036 -1.5950 -.0418 Akt Manajemen AK AM .8951(*) .29870 .009 .1888 1.6014 SIA 1.7602(*) .35448 .000 .9221 2.5984 AM AK -.8951(*) .29870 .009 -1.6014 -.1888 SIA .8651(*) .34688 .036 .0449 1.6853 SIA AK -1.7602(*) .35448 .000 -2.5984 -.9221 AM -.8651(*) .34688 .036 -1.6853 -.0449 Auditing AK AM .9917(*) .33438 .010 .2011 1.7824 SIA 1.5121(*) .39682 .001 .5738 2.4504 AM AK -.9917(*) .33438 .010 -1.7824 -.2011 SIA .5204 .38831 .375 -.3978 1.4386 SIA AK -1.5121(*) .39682 .001 -2.4504 -.5738 AM -.5204 .38831 .375 -1.4386 .3978 Peng.Aplikom Lanj

AK AM .6638(*) .26001 .031 .0489 1.2786

SIA .7001 .30856 .063 -.0295 1.4297 AM AK -.6638(*) .26001 .031 -1.2786 -.0489 SIA .0363 .30195 .992 -.6777 .7503



SIA AK -.7001 .30856 .063 -1.4297 .0295 AM -.0363 .30195 .992 -.7503 .6777 SIA AK AM .6863(*) .25911 .024 .0737 1.2990 SIA .6834 .30749 .070 -.0437 1.4105 AM AK -.6863(*) .25911 .024 -1.2990 -.0737 SIA -.0030 .30091 1.000 -.7145 .7085 SIA AK -.6834 .30749 .070 -1.4105 .0437 AM .0030 .30091 1.000 -.7085 .7145

* The mean difference is significant at the .05 level. Homogeneous Subsets Teori Akuntansi Tukey HSD

Subset for alpha = .05 Kosentrasi N 1 2 SIA 38 3.0789 AM 71 3.5634 AK 63 4.8095 Sig. .388 1.000

Means for groups in homogeneous subsets are displayed. a Uses Harmonic Mean Sample Size = 53.311. b The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed. Manajemen Keuangan Tukey HSD


Means for groups in homogeneous subsets are displayed. a Uses Harmonic Mean Sample Size = 53.311. b The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed. Akt Keu 2 Tukey HSD




Means for groups in homogeneous subsets are displayed. a Uses Harmonic Mean Sample Size = 53.311. b The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed. Statistik Tukey HSD

Subset for alpha = .05 Kosentrasi N 1 2 3 SIA 38 3.4211 AM 71 4.2394 AK 63 5.3968 Sig. 1.000 1.000 1.000

Means for groups in homogeneous subsets are displayed. a Uses Harmonic Mean Sample Size = 53.311. b The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed. Akt Manajemen Tukey HSD

Subset for alpha = .05 Kosentrasi N 1 2 3 SIA 38 4.6842 AM 71 5.5493 AK 63 6.4444 Sig. 1.000 1.000 1.000

Means for groups in homogeneous subsets are displayed. a Uses Harmonic Mean Sample Size = 53.311. b The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed. Auditing Tukey HSD


Means for groups in homogeneous subsets are displayed. a Uses Harmonic Mean Sample Size = 53.311. b The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed.



Peng.Aplikom Lanj Tukey HSD

Subset for alpha = .05 Kosentrasi N 1 2 SIA 38 6.3158 AM 71 6.3521 6.3521 AK 63 7.0159 Sig. .991 .061

Means for groups in homogeneous subsets are displayed. a Uses Harmonic Mean Sample Size = 53.311. b The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed. SIA Tukey HSD

Subset for alpha = .05 Kosentrasi N 1 2 AM 71 5.1549 SIA 38 5.1579 5.1579 AK 63 5.8413 Sig. 1.000 .051

Means for groups in homogeneous subsets are displayed. a Uses Harmonic Mean Sample Size = 53.311. b The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed.



LAMPIRAN A Kuesioner - core.ac.uk · 27 Saya menguasai mata kuliah Akuntansi Manajemen (Akmen) 1 2...

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Transcript of LAMPIRAN A Kuesioner - core.ac.uk · 27 Saya menguasai mata kuliah Akuntansi Manajemen (Akmen) 1 2...