5 Sangat Tidak Setuju Sangat Setuju

  LAMPIRAN: 1 Medan, 30 Mei 2013 Perihal : Permohonan Pengisian Kuisioner Penelitian Tesis Kepada Yth, Responden penelitian Tesis Bapak/Ibu _____________________________________ Di tempat Bismillahirrahmanirrahim. Assalamu’alaikum warahmatullahi wabarakatuh Dengan hormat, Sehubungan dengan akan disusunnya penulisan tesis di Magister Ilmu Manajemen

USU dengan judul Analisis Resource-Based View dalam strategi menentukan keunggulan

posisi, bermaksud melakukan survey melalui kuisioner kepada Bapak dan Ibu struktural

sebagai pengelola universitas, Bapak dan Ibu dosen sebagai pelaksana proses belajar mengajar,

dan Bapak dan Ibu alumni sebagai hasil dari pengelolaan dan pelaksanaan proses belajar

mengajar di Program Studi Magister Ilmu Hukum, Universitas Pembangunan Panca Budi

Medan.

  Untuk keakuratan dan validitas data dimohon kepada responden dapat mengisi sesuai

dengan realitas yang terjadi dilapangan, karena hasil penelitian ini akan ‘dikirim’ kepada

manajemen Universitas supaya dijadikan sebagai salah satu dasar penentuan kebijakan posisi

dalam hal pengelolaan dan pengembangan Universitas, khususnya program studi magister ilmu

hukum ke depan.

  Demikian permohonan ini disampaikan, atas perhatian dan bantuannya diucapkan terimakasih.

  Wassalamu’alaikum warrahmatullahi wabarakatuh Hormat Peneliti, Rizal Ahmad NIM. 117019020

  X DAFTAR PERNYATAAN PENELITIAN

STRATEGI MENENTUKAN KEUNGGULAN POSISI PROGRAM STUDI

MAGISTER ILMU HUKUM

UNIVERSITAS PEMBANGUNAN PANCA BUDI MEDAN

PERNYATAAN – PERNYATAAN VARIABLE PENELITIAN

  Petunjuk Pengisian 1.

  Berilah tanda (X) tepat pada angka yang ada di dalam kotak, sesuai dengan pernyataan yang dipilih.

  : 2.

  Kuisioner ini berisi beberapa pernyataan yang dimohonkan untuk dijawab secara pribadi.

  Jawaban yang diberikan tidak terkait dengan kedinasan, namun sepenuhnya untuk kepentingan penelitian dalam rangka penyusunan tesis.

3. Ketentuan bobot nilai jawaban responden sebagai berikut: 1.

  Sangat Tidak Setuju.

2. Tidak Setuju 3.

  Netral 4. Setuju 5. Sangat Setuju Contoh:

  

Jawaban kuisioner berdasarkan skala 1 - 5 dengan angka 1 (satu) menunjukan bahwa

responden memberikan tanggapan yang sangat tidak setuju terhadap pernyataan-pernyataan

yang diajukan, sedangkan angka 5 (lima) menunjukan sangat setuju terhadap pernyataan-

pernyataan yang diajukan.

  1

  2

  

3

  4

  5 Sangat Tidak Setuju Sangat Setuju

  1. Nama responden : ...................................................................................................

  2. Umur : ............................................................... Tahun

  3. Jenis kelamin : Laki-laki / Perempuan )*

  4. Status Responden : Struktural / Dosen Tetap / Dosen Tidak Tetap / Alumni )*

  5. Jabatan : ...................................................................................................

  (Jabatan / Bagian yang sedang diemban dalam pekerjaan sekarang)

  6. Mulai Kerja : Tahun ............... s/d ……………

  7. Pendidikan Terakhir : ...................................................................................................

  8. Telp. / HP : ...................................................................................................

  )* Coret yang tidak sesuai

  IDENTITAS RESPONDEN

1. Kapabilitas (Capabilities) N0 PERNYATAAN

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  1 Rencana Pengembangan Program Studi: Program Studi Magister Ilmu Hukum UNPAB memiliki kemampuan dalam pengelolaan Program Studinya.

  2 Program Studi Magister Ilmu Hukum UNPAB memiliki pengetahuan dalam pengelolaan Program Studinya.

  3 Manajemen Sumberdaya: Program Studi Magister Ilmu Hukum UNPAB memiliki kemampuan dalam pengelolaan sumber daya keuangan .

  4 Program Studi Magister Ilmu Hukum UNPAB memiliki kemampuan dalam pengelolaan sumber daya organisasi .

  5 Program Studi Magister Ilmu Hukum UNPAB memiliki kemampuan dalam pengelolaan sumber daya fisik .

  6 Program Studi Magister Ilmu Hukum UNPAB memiliki kemampuan dalam pengelolaan sumber daya teknologi .

  7 Program Studi Magister Ilmu Hukum UNPAB memiliki pengetahuan dalam pengembangan sumber daya manusia.

  8 Program Studi Magister Ilmu Hukum UNPAB memiliki pengetahuan dalam menciptakan inovasi sumber daya organisasi.

  9 Program Studi Magister Ilmu Hukum UNPAB memiliki pengetahuan dalam mencapai reputasi yang baik.

  10 Program Studi Magister Ilmu Hukum UNPAB memiliki pengetahuan dalam pengembangan budaya organisasi.

  11 Manajemen Mutu Akademis: Program Studi Magister Ilmu Hukum UNPAB memiliki kurikulum yang di review secara periodik dengan melibatkan Stakeholders.

  12 Program Studi Magister Ilmu Hukum UNPAB malaksanakan evaluasi mutu akademik dengan melibatkan mahasiswa.

  13 Program Studi Magister Ilmu Hukum UNPAB memiliki kesesuaian kurikulum dengan visi, misi dan tujuan program studi.

  14 Program Studi Magister Ilmu Hukum UNPAB memiliki mata kuliah yang mendukung kompetensi lulusan.

  15 Dukungan Kerjasama: Program Studi Magister Ilmu Hukum UNPAB memiliki dukungan kerjasama dengan universitas dalam bidang pendidikan dan pengabdian.

  16 Pengembangan Program Studi Magister Ilmu Hukum UNPAB memiliki dukungan kerjasama dengan pemerintah dalam bidang pendidikan dan pengabdian.

2. Sumber Daya Berwujud (Tangible) N0 PERNYATAAN

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  1 Sumber Daya Keuangan: Selain dari uang kuliah, Program Studi Magister Ilmu Hukum UNPAB memiliki unit-unit usaha sebagai unit income generating.

  2 Sumber Daya Organisasi: Program Studi Magister Ilmu Hukum UNPAB memiliki program perencanaan terhadap sumberdaya keuangan, sumberdaya fisik, sumberdaya manusia, dan sumberdaya teknologi.

  3 Program Studi Magister Ilmu Hukum UNPAB memiliki program pengawasan terhadap sumberdaya keuangan, sumberdaya fisik, sumberdaya manusia, dan sumberdaya teknologi

  4 Program Studi Magister Ilmu Hukum UNPAB memiliki sistem koordinasi terhadap sumberdaya keuangan, sumberdaya fisik, sumberdaya manusia, dan sumberdaya teknologi

  5 Sumber Daya Fisik: Program Studi Magister Ilmu Hukum UNPAB memiliki gedung dan tanah sebagai prasarana utama untuk kegiatan akademik.

  6 Program Studi Magister Ilmu Hukum UNPAB memiliki tempat olah raga dan ibadah sebagai prasarana penunjang kegiatan akademik.

  7 Program Studi Magister Ilmu Hukum UNPAB memiliki ruang himpunan mahasiswa sebagai prasarana penunjang perkuliahan

  8 Sumber Daya Teknologi: Program Studi Magister Ilmu Hukum UNPAB memiliki fasilitas penunjang akademik seperti Information Technology (IT) dalam pelaksanaan proses pembelajaran.

  9 Program Studi Magister Ilmu Hukum UNPAB memiliki fasilitas penunjang akademik seperti sistem informasi akademik

3. Sumber Daya Tidak Berwujud (Intangible) N0 PERNYATAAN

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  1 Sumber Daya Manusia: Program Studi Magister Ilmu Hukum UNPAB memiliki dosen dengan kualifikasi Guru besar/profesor dan Strata Tiga (S.3)

  2 Program Studi Magister Ilmu Hukum UNPAB memiliki dosen dengan latar belakang pendidikan yang sesuai dengan program studi.

  3 Program Studi Magister Ilmu Hukum UNPAB memiliki dosen yang aktif dalam organisasi keilmuan/profesi.

  4 Program Studi Magister Ilmu Hukum UNPAB memiliki perbandingan jumlah mahasiswa dengan jumlah dosen yang baik (19 : 1).

  5 Program Studi Magister Ilmu Hukum UNPAB memiliki program penelitian dosen yang melibatkan mahasiswa.

  6 Program Studi Magister Ilmu Hukum UNPAB memiliki program pengabdian dosen yang melibatkan mahasiswa.

  7 Program Studi Magister Ilmu Hukum UNPAB memiliki tenaga kependidikan dengan kualifikasi Pustakawan, Laboran/Teknisi/Operator, dan adnimistrasi.

  8 Inovasi: Program Studi Magister Ilmu Hukum UNPAB memiliki tingkat inovasi (ide dan gagasan) yang tinggi dalam program pendidikan.

  9 Program Studi Magister Ilmu Hukum UNPAB memiliki tingkat inovasi (ide dan gagasan) yang tinggi dalam program penelitian

  10 Program Studi Magister Ilmu Hukum UNPAB memiliki tingkat inovasi (ide dan gagasan) yang tinggi dalam program pengabdian.

  11 Reputasi: Program Studi Magister Ilmu Hukum UNPAB memiliki reputasi dalam bidang kerja sama pendidikan dan jejaring sosial (pakar hukum) dalam mendukung tri dharma Perguruan Tinggi.

  12 Budaya Organisasi: Budaya organisasi Program Studi Magister Ilmu Hukum UNPAB yang tercermin dalam 7 (tujuh) nilai dasar yayasan (Sholat & zikir, Bersyukur, Rendah hati, Berfikir positif, Optimis, Memberikan solusi, dan Patuh pada pimpinan), merupakan sumber penting dalam memberikan pelayanan akademik kepada dosen, mahasiswa dan alumni.

4. Posisi Bersaing (Competitive Positioning). N0 PERNYATAAN

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  1 Posisi menurut manfaat: Program pendidikan yang ada pada program studi magister ilmu hukum UNPAB bermanfaat dalam peningkatan pendapatan, karir/jabatan, jejaring sosial, dan relasi bisnis

  2 Program penelitian yang ada pada program studi magister ilmu hukum UNPAB bermanfaat dalam peningkatan pendapatan, karir/jabatan, jejaring sosial, dan relasi bisnis

  3 Program pengabdian kepada masyarakat yang ada pada program studi magister ilmu hukum UNPAB bermanfaat dalam peningkatan pendapatan, karir/jabatan, jejaring sosial, dan relasi bisnis

  4 Posisi menurut penggunaan atau penerapan: Program pendidikan yang ada pada program studi magister ilmu hukum UNPAB dapat digunakan atau diterapkan dalam melaksanakan pekerjaan/tugas dan dalam kehidupan bermasyarakat

  5 Program penelitian yang ada pada program studi magister ilmu hukum UNPAB dapat digunakan atau diterapkan dalam melaksanakan pekerjaan/tugas dan dalam kehidupan bermasyarakat

  6 Program pengabdian kepada masyarakat yang ada pada program studi magister ilmu hukum UNPAB dapat digunakan atau diterapkan dalam melaksanakan pekerjaan/tugas dan dalam kehidupan bermasyarakat

  7 Posisi menurut pemakai: Program pendidikan yang ada pada program studi magister ilmu hukum UNPAB yang terbaik untuk pemakai sebagai individu, komunitas tertentu dan sebagai anggota masyarakat

  8 Program penelitian yang ada pada program studi magister ilmu hukum UNPAB yang terbaik untuk pemakai sebagai individu, komunitas tertentu dan sebagai anggota masyarakat

  9 Program pengabdian kepada masyarakat yang ada pada program studi magister ilmu hukum UNPAB yang terbaik untuk pemakai sebagai individu, komunitas tertentu dan sebagai anggota masyarakat

  10 Posisi menurut harga atau kualitas: Program Studi Magister Ilmu Hukum UNPAB memiliki program pendidikan yang berkualitas tinggi dengan perbandingan harga (uang kuliah) yang layak.

  11 Program Studi Magister Ilmu Hukum UNPAB memiliki program penelitian yang berkualitas tinggi dengan perbandingan harga (biaya penelitian) yang layak.

  12 Program Studi Magister Ilmu Hukum UNPAB memiliki program pengabdian kepada masyarakat yang berkualitas tinggi dengan perbandingan harga (biaya pengabdian) yang layak.

5. Keunggulan Posisi (Positioning Adventage) N0 PERNYATAAN

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  1 Kepentingan (Importance) : Program Studi Magister Ilmu Hukum UNPAB memiliki program pendidikan yang dapat menciptakan nilai manfaat/kepentingan (Importance) yang tinggi untuk mahasiswa dan pengguna lulusan.

  2 Program Studi Magister Ilmu Hukum UNPAB memiliki program penelitian yang dapat menciptakan nilai manfaat/kepentingan (Importance) yang tinggi untuk mahasiswa dan pengguna lulusan.

  3 Program Studi Magister Ilmu Hukum UNPAB memiliki program pengabdian kepada masyarakat yang dapat menciptakan nilai manfaat/kepentingan (Importance) yang tinggi untuk mahasiswa dan pengguna lulusan.

  4 Keistimewaan /ciri khas (Distintive): Program studi magister ilmu hukum UNPAB memiliki program pendidikan dengan keistimewaan/ciri khas (Distintive) dengan 40% dosen praktisi (Pejabat Negara)

  5 Program studi magister ilmu hukum UNPAB memiliki program penelitian dengan keistimewaan/ciri khas (Distintive) dalam bidang Hukum Perdata.

  6 Program studi magister ilmu hukum UNPAB memiliki program pengabdian kepada masyarakat dengan keistimewaan/ciri khas (Distintive) dalam bidang Hukum Perdata.

  Terjangkau (Affordable):

  7 Program studi magister ilmu hukum UNPAB dalam menentukan biaya pendidikan berdasarkan kualitas pendidikan dan terjangkau (Affordable)

  8 Menguntungkan (Profitable): Program studi magister ilmu hukum UNPAB dalam menentukan biaya pendidikan tetap memperhitungkan keuntungan (Profitable) yang akan digunakan untuk pengembangan

TERIMA KASIH ATAS PARTISIPASINYA DALAM KUISIONER INI

  LAMPIRAN: 2 Reliability Scale: ALL VARIABLES Case Processing Summary

  N % Cases Valid 122 100.0

  Excluded a .0

  Total 122 100.0 a. Listwise deletion based on all variables in the procedure.

  Reliability Statistics

  Cronbach's Alpha N of Items .964

  16 Item-Total Statistics Scale Mean if Item

  Deleted Scale Variance if

  Item Deleted Corrected Item-

  Total Correlation Cronbach's Alpha if Item Deleted

  X1.1.1 54.5082 250.880 .639 .964 X1.1.2 54.4836 250.549 .646 .964 X1.2.1 54.0410 249.577 .841 .961 X1.2.2 54.0164 251.636 .809 .962 X1.2.3 54.0984 247.544 .824 .961 X1.2.4 54.0984 246.833 .859 .961 X1.2.5 54.0820 247.530 .818 .961 X1.2.6 54.0574 244.732 .864 .960 X1.2.7 54.0574 246.137 .822 .961 X1.2.8 54.0492 245.039 .867 .960 X1.3.1 54.3279 247.792 .780 .962 X1.3.2 54.4016 246.771 .777 .962 X1.3.3 54.3934 245.927 .787 .962 X1.3.4 54.4180 249.171 .774 .962 X1.4.1 54.4754 247.425 .717 .963 X1.4.2 54.5246 248.913 .693 .963

  Scale Statistics

  Mean Variance Std. Deviation N of Items 57.8689 281.388 16.77461

  16 Reliability

  Scale: ALL VARIABLES Case Processing Summary

  N % Cases Valid 122 100.0

  Excluded a .0 Total 122 100.0 a. Listwise deletion based on all variables in the procedure.

  Reliability Statistics

  Cronbach's Alpha N of Items .945

  9 Item-Total Statistics Scale Mean if Item

  Deleted Scale Variance if

  Item Deleted Corrected Item-

  Total Correlation Cronbach's Alpha if Item Deleted

  X2.1.1 26.6066 81.579 .739 .942 X2.2.1 26.5164 81.756 .789 .939 X2.2.2 26.5082 79.624 .815 .937 X2.2.3 26.5246 80.929 .811 .937 X2.3.1 26.4672 81.309 .815 .937 X2.3.2 26.5492 81.655 .825 .937 X2.3.3 26.3934 84.819 .758 .941 X2.4.1 26.6311 81.293 .782 .939 X2.4.2 26.5574 81.240 .755 .941

  Scale Statistics

  Mean Variance Std. Deviation N of Items 29.8443 102.546 10.12649

  9

  Reliability Scale: ALL VARIABLES Case Processing Summary

  N % Cases Valid 122 100.0

  Excluded a .0 Total 122 100.0 a. Listwise deletion based on all variables in the procedure.

  Reliability Statistics

  Cronbach's Alpha N of Items .954

  12 Item-Total Statistics Scale Mean if Item

  Deleted Scale Variance if

  Item Deleted Corrected Item-

  Total Correlation Cronbach's Alpha if Item Deleted

  X3.1.1 38.4672 137.358 .822 .949 X3.1.2 38.3770 138.303 .809 .949 X3.1.3 38.1639 137.841 .826 .949 X3.1.4 38.4180 135.204 .870 .947 X3.1.5 38.4508 134.531 .886 .947 X3.1.6 38.5574 133.836 .860 .948 X3.1.7 38.4016 138.870 .824 .949 X3.2.1 38.2951 142.160 .675 .953 X3.2.2 38.3852 137.297 .740 .952 X3.2.3 38.4344 141.603 .707 .952 X3.3.1 38.3689 139.871 .653 .954 X3.4.1 38.4180 139.849 .681 .953

  Scale Statistics

  Mean Variance Std. Deviation N of Items 41.8852 163.623 12.79152

  12

  Reliability Scale: ALL VARIABLES Case Processing Summary

  N % Cases Valid 122 100.0

  Excluded a .0 Total 122 100.0 a. Listwise deletion based on all variables in the procedure.

  Reliability Statistics

  Cronbach's Alpha N of Items .931

  12 Item-Total Statistics Scale Mean if Item

  Deleted Scale Variance if

  Item Deleted Corrected Item-

  Total Correlation Cronbach's Alpha if Item Deleted

  Y1.1.1 39.8279 100.408 .675 .926 Y1.1.2 40.0492 94.295 .707 .925 Y1.1.3 39.9180 94.754 .723 .924 Y1.2.1 39.7787 98.058 .706 .925 Y1.2.2 39.9426 95.311 .728 .924 Y1.2.3 39.9098 96.050 .729 .924 Y1.3.1 39.7377 98.410 .684 .926 Y1.3.2 39.8607 94.815 .737 .924 Y1.3.3 39.8934 95.997 .728 .924 Y1.4.1 39.7541 100.220 .602 .929 Y1.4.2 40.0328 95.784 .696 .925 Y1.4.3 39.9754 96.173 .702 .925

  Scale Statistics

  Mean Variance Std. Deviation N of Items 43.5164 114.351 10.69350

  12

  Reliability Scale: ALL VARIABLES Case Processing Summary

  N % Cases Valid 122 100.0

  Excluded a .0

  Total 122 100.0 a. Listwise deletion based on all variables in the procedure.

  Reliability Statistics

  Cronbach's Alpha N of Items .935

  8 Item-Total Statistics Scale Mean if Item

  Deleted Scale Variance if

  Item Deleted Corrected Item-

  Total Correlation Cronbach's Alpha if Item Deleted

  Y2.1.1 25.7459 52.125 .807 .924 Y2.1.2 25.9918 50.967 .825 .922 Y2.1.3 26.0574 52.864 .803 .924 Y2.2.1 25.8525 54.540 .742 .929 Y2.2.2 26.1230 51.547 .790 .925 Y2.2.3 26.1639 53.527 .780 .926 Y2.3.1 26.0164 51.157 .710 .932 Y2.4.1 26.0984 51.015 .755 .928

  Scale Statistics

  Mean Variance Std. Deviation N of Items 29.7213 67.575 8.22038

  8

  LAMPIRAN: 3 Notes for Group (Group number 1) The model is recursive.

  Sample size = 122

  Variable Summary (Group number 1) Your model contains the following variables (Group number 1)

  Observed, endogenous variables

  X2.2 X2.1

  X2.3 X2.4

  X1.2 X1.1

  X1.3 X1.4

  X3.2 X3.1

  X3.3 X3.4 Y2.3 Y2.4 Y2.2 Y2.1 Y1.2 Y1.1 Y1.3 Y1.4 Unobserved, endogenous variables Y2 Y1 Unobserved, exogenous variables SDB e22 e21 e23 e24 Kapabilitas e12 e11 e13 e14 SDTB e32 e31 e33 e34 e53 e54 e52 e51 e42 e41 e43 e44 z2 z1

  Variable counts (Group number 1)

  Number of variables in your model:

  47 Number of observed variables:

  20 Number of unobserved variables:

  27 Number of exogenous variables:

  25 Number of endogenous variables:

  22 Parameter Summary (Group number 1) Weights Covariances Variances Means Intercepts Total

  Fixed

  27

  27 Labeled Unlabeled

  21

  3

  25

  49 Total

  48

  3

  25

  76 Assessment of normality (Group number 1) Variable min max skew c.r. kurtosis c.r.

  Y1.4 1.000 5.000 -.438 -1.976 -.844 -1.903 Y1.3 1.000 5.000 -.560 -2.526 -.814 -1.834 Y1.1 1.000 5.000 -.421 -1.898 -.987 -2.224 Y1.2 1.000 5.000 -.411 -1.852 -1.010 -2.277 Y2.1 1.000 5.000 -.703 -3.168 -.739 -1.667 Y2.2 1.000 5.000 -.525 -2.366 -.866 -1.953 Y2.4 1.000 5.000 -.575 -2.594 -.942 -2.123 Y2.3 1.000 5.000 -.638 -2.878 -.975 -2.199 X3.4 1.000 5.000 -.256 -1.155 -1.195 -2.693 X3.3 1.000 5.000 -.380 -1.714 -1.302 -2.936 X3.1 1.000 5.000 -.374 -1.687 -1.127 -2.541 X3.2 1.000 5.000 -.410 -1.851 -1.197 -2.699 X1.4 1.000 5.000 -.290 -1.308 -1.362 -3.070 X1.3 1.000 5.000 -.300 -1.352 -1.212 -2.732 X1.1 1.000 5.000 -.200 -.901 -1.262 -2.846 X1.2 1.000 5.000 -.453 -2.043 -1.087 -2.451 X2.4 1.000 5.000 -.260 -1.171 -1.138 -2.565 X2.3 1.000 5.000 -.195 -.879 -1.174 -2.646 X2.1 1.000 5.000 -.182 -.819 -1.257 -2.833 X2.2 1.000 5.000 -.087 -.393 -1.402 -3.162 Multivariate 12.600 2.346

  Observations farthest from the centroid (Mahalanobis distance) (Group number 1)

  Observation number Mahalanobis d-squared p1 p2 82 33.384 .031 .977 66 33.278 .031 .899 121 31.674 .047 .929 86 31.639 .047 .834 73 31.598 .048 .698 52 30.729 .059 .730 80 30.657 .060 .600 54 29.873 .072 .657 92 29.812 .073 .536 58 29.626 .076 .452 98 29.131 .085 .469 76 28.932 .089 .405 120 28.826 .091 .321

  Observation number Mahalanobis d-squared p1 p2 10 28.766 .092 .237 51 28.764 .093 .157 85 28.732 .093 .103 77 28.726 .093 .062 114 28.476 .099 .054

  122 27.821 .114 .097 102 27.294 .127 .140 8 27.088 .133 .127 116 26.958 .136 .103

  50 26.844 .140 .081 107 26.628 .146 .077 19 26.454 .151 .068 1 26.394 .153 .048 49 26.015 .165 .065 20 25.913 .169 .051 74 25.814 .172 .040 118 25.513 .183 .049 24 25.431 .185 .037 6 25.176 .195 .042

  4 25.163 .195 .027 9 25.149 .196 .017 91 25.128 .197 .011 113 24.587 .218 .028 93 24.486 .222 .023 69 24.343 .228 .021 56 23.994 .243 .033 111 23.864 .248 .030

  103 23.723 .255 .028 84 23.671 .257 .020 100 23.444 .268 .024 62 23.150 .281 .035

  2 22.433 .317 .132 109 21.931 .344 .251 35 21.924 .345 .197 72 21.921 .345 .150 43 21.689 .358 .178 83 21.478 .369 .203

  104 21.415 .373 .175 67 21.154 .388 .220 105 21.153 .388 .170 71 20.966 .399 .187 117 20.897 .403 .164 39 20.789 .410 .155

  28 20.572 .423 .183 5 20.354 .436 .215 99 20.124 .450 .257 17 20.079 .453 .220 59 19.972 .460 .211 68 19.655 .480 .295 41 19.388 .497 .366 108 19.366 .498 .311 Observation number Mahalanobis d-squared p1 p2 23 19.347 .499 .259 89 19.338 .500 .208 96 19.212 .508 .207 88 19.059 .518 .218 65 18.894 .529 .235 47 18.794 .535 .223 90 18.778 .536 .179 60 18.771 .537 .137 27 18.135 .579 .364 36 17.875 .596 .441 106 17.764 .603 .433 97 17.611 .613 .450 81 17.383 .628 .512 87 17.313 .633 .479 57 17.276 .635 .426 94 17.253 .636 .367 16 17.124 .645 .368 42 17.090 .647 .317 61 16.766 .668 .429 34 16.404 .691 .570 3 16.322 .696 .542 30 16.207 .704 .533 63 16.127 .709 .503

  7 16.049 .714 .470 53 15.987 .717 .428 79 15.862 .725 .423 119 15.145 .768 .757 21 15.041 .774 .741 40 15.001 .776 .690

  110 14.621 .798 .807 112 14.477 .806 .808 75 14.429 .808 .765 95 14.353 .812 .730 22 13.671 .847 .924 15 13.242 .867 .968 14 13.238 .867 .948

  Sample Moments (Group number 1) Sample Covariances (Group number 1)

  Y1.4 Y1.3 Y1.1 Y1.2 Y2.1 Y2.2 Y2.4 Y2.3

  X3.4 X3.3

  X3.1 X3.2

  X1.4 X1.3

  X1.1 X1.2

  X2.4 X2.3

  X2.1 X2.2 Y1.4 1.524 Y1.3 .801 1.636 Y1.1 .809 .867 1.740 Y1.2 .808 .971 .903 1.673 Y2.1 .626 .713 .661 .624 1.706 Y2.2 .609 .567 .592 .533 .998 1.654 Y2.4 .648 .714 .688 .669 1.214 1.121 1.841 Y2.3 .847 .874 .774 .755 1.209 1.052 1.217 1.995 X3.4 .391 .595 .469 .428 .775 .738 .734 .867 1.839 X3.3 .569 .579 .426 .450 .639 .534 .555 .808 1.160 1.971 X3.1 .532 .619 .533 .469 .725 .581 .632 .788 1.201 1.125 1.911 X3.2 .572 .653 .608 .494 .767 .697 .775 .933 1.200 1.210 1.218 2.003 X1.4 .699 .650 .629 .769 .339 .309 .378 .570 .302 .329 .360 .507 2.068 X1.3 .646 .562 .615 .576 .315 .376 .386 .542 .333 .395 .304 .488 1.221 1.911 X1.1 .593 .507 .668 .547 .464 .486 .463 .553 .419 .211 .252 .443 1.168 1.080 1.896 X1.2 .581 .450 .490 .463 .300 .307 .348 .533 .472 .514 .380 .513 1.075 1.183 .915 1.739 X2.4 .519 .465 .528 .473 .758 .624 .763 .802 .437 .445 .445 .421 .227 .322 .336 .266 1.876 X2.3 .522 .602 .586 .524 .808 .719 .865 .776 .403 .462 .392 .395 .397 .482 .472 .377 1.256 1.765 X2.1 .497 .508 .527 .490 .802 .707 .786 .726 .422 .500 .415 .438 .399 .349 .347 .250 1.307 1.282 2.001 X2.2 .590 .535 .637 .601 .706 .759 .781 .696 .377 .414 .403 .352 .379 .444 .434 .179 1.346 1.296 1.319 2.153 Condition number = 30.814 Eigenvalues 13.962 4.404 3.966 2.236 1.766 1.104 .956 .869 .840 .790 .779 .721 .694 .645 .639 .580 .527 .502 .468 .453 Determinant of sample covariance matrix = 3.063

  Universitas Sumatera Utara

  Sample Correlations (Group number 1)

  Y1.4 Y1.3 Y1.1 Y1.2 Y2.1 Y2.2 Y2.4 Y2.3

  X3.4 X3.3

  X3.1 X3.2

  X1.4 X1.3

  X1.1 X1.2

  X2.4 X2.3

  X2.1 X2.2 Y1.4 1.000 Y1.3 .507 1.000 Y1.1 .497 .514 1.000 Y1.2 .506 .587 .529 1.000 Y2.1 .388 .427 .384 .370 1.000 Y2.2 .384 .345 .349 .320 .594 1.000 Y2.4 .387 .412 .384 .381 .685 .642 1.000 Y2.3 .486 .484 .416 .413 .655 .579 .635 1.000 X3.4 .234 .343 .262 .244 .438 .423 .399 .453 1.000 X3.3 .328 .323 .230 .248 .349 .296 .292 .408 .609 1.000 X3.1 .311 .350 .292 .262 .401 .327 .337 .404 .641 .580 1.000 X3.2 .327 .361 .326 .270 .415 .383 .403 .467 .625 .609 .622 1.000 X1.4 .394 .353 .331 .413 .180 .167 .194 .281 .155 .163 .181 .249 1.000 X1.3 .379 .318 .337 .322 .174 .212 .206 .278 .177 .204 .159 .250 .614 1.000 X1.1 .349 .288 .368 .307 .258 .274 .248 .284 .224 .109 .132 .228 .590 .567 1.000 X1.2 .357 .267 .282 .272 .174 .181 .194 .286 .264 .278 .208 .275 .567 .649 .504 1.000 X2.4 .307 .266 .292 .267 .424 .354 .410 .414 .235 .232 .235 .217 .115 .170 .178 .147 1.000 X2.3 .318 .354 .334 .305 .466 .421 .480 .413 .224 .248 .213 .210 .208 .263 .258 .215 .690 1.000 X2.1 .284 .281 .283 .268 .434 .388 .410 .363 .220 .252 .212 .219 .196 .179 .178 .134 .675 .682 1.000 X2.2 .326 .285 .329 .317 .368 .402 .392 .336 .189 .201 .199 .170 .180 .219 .215 .092 .670 .665 .635 1.000 Condition number = 31.248 Eigenvalues 7.611 2.322 2.053 1.239 1.005 .604 .546 .491 .460 .427 .407 .403 .372 .349 .340 .309 .290 .274 .253 .244

  Universitas Sumatera Utara

  Notes for Model (Default model) Computation of degrees of freedom (Default model)

  Number of distinct sample moments : 210 Number of distinct parameters to be estimated:

  49 Degrees of freedom (210 - 49) : 161

  Result (Default model)

  Minimum was achieved Chi-square = 79.893 Degrees of freedom = 161 Probability level = 1.000

  Estimates (Group number 1 - Default model) Scalar Estimates (Group number 1 - Default model) Maximum Likelihood Estimates Regression Weights: (Group number 1 - Default model)

  Estimate S.E. C.R. P Label Y1 <--- Kapabilitas .397 .103 3.849 *** par_13 Y1 <--- SDB .238 .079 3.015 .003 par_15 Y1 <--- SDTB .239 .083 2.880 .004 par_16 Y2 <--- Y1 .390 .131 2.973 .003 par_14 Y2 <--- SDTB .336 .095 3.533 *** par_17 Y2 <--- SDB .334 .090 3.725 *** par_18 X2.2 <--- SDB 1.000 X2.1 <--- SDB .982 .104 9.478 *** par_1 X2.3 <--- SDB .965 .097 9.976 *** par_2 X2.4 <--- SDB .975 .099 9.843 *** par_3 X1.2 <--- Kapabilitas 1.000 X1.1 <--- Kapabilitas .998 .137 7.284 *** par_4 X1.3 <--- Kapabilitas 1.137 .132 8.594 *** par_5 X1.4 <--- Kapabilitas 1.136 .144 7.911 *** par_6 X3.2 <--- SDTB 1.000 X3.1 <--- SDTB .953 .108 8.862 *** par_7 X3.3 <--- SDTB .927 .109 8.490 *** par_8 X3.4 <--- SDTB .967 .107 9.065 *** par_9 Y2.3 <--- Y2 1.000 Y2.4 <--- Y2 .984 .103 9.579 *** par_10 Y2.2 <--- Y2 .847 .099 8.572 *** par_11 Y2.1 <--- Y2 .948 .098 9.710 *** par_12 Y1.3 <--- Y1 1.005 .131 7.654 *** par_19 Y1.2 <--- Y1 1.000 Y1.1 <--- Y1 .977 .137 7.145 *** par_20 Y1.4 <--- Y1 .921 .130 7.090 *** par_21

  Standardized Regression Weights: (Group number 1 - Default model)

  Estimate Y1 <--- Kapabilitas .411 Y1 <--- SDB .290 Y1 <--- SDTB .284 Y2 <--- Y1 .329 Y2 <--- SDTB .337 Y2 <--- SDB .344 X2.2 <--- SDB .793

  Estimate X2.1 <--- SDB .807 X2.3 <--- SDB .845 X2.4 <--- SDB .828 X1.2 <--- Kapabilitas .748 X1.1 <--- Kapabilitas .715 X1.3 <--- Kapabilitas .811 X1.4 <--- Kapabilitas .779 X3.2 <--- SDTB .800 X3.1 <--- SDTB .780 X3.3 <--- SDTB .747 X3.4 <--- SDTB .807 Y2.3 <--- Y2 .799 Y2.4 <--- Y2 .818 Y2.2 <--- Y2 .744 Y2.1 <--- Y2 .820 Y1.3 <--- Y1 .748 Y1.2 <--- Y1 .736 Y1.1 <--- Y1 .705 Y1.4 <--- Y1 .711

  Covariances: (Group number 1 - Default model)

  Estimate S.E. C.R. P Label SDB <--> Kapabilitas .336 .128 2.621 .009 par_22 Kapabilitas <--> SDTB .372 .131 2.851 .004 par_23 SDB <--> SDTB .444 .148 3.005 .003 par_24

  Correlations: (Group number 1 - Default model)

  Estimate SDB <--> Kapabilitas .293 Kapabilitas <--> SDTB .333 SDB <--> SDTB .337

  Variances: (Group number 1 - Default model)

  Estimate S.E. C.R. P Label SDB 1.353 .268 5.043 *** par_25 Kapabilitas .974 .216 4.517 *** par_26 SDTB 1.281 .255 5.017 *** par_27 z1 .420 .114 3.687 *** par_28 z2 .448 .106 4.242 *** par_29 e22 .800 .128 6.226 *** par_30 e21 .697 .115 6.067 *** par_31 e23 .506 .093 5.445 *** par_32 e24 .591 .103 5.756 *** par_33 e12 .765 .126 6.077 *** par_34 e11 .927 .145 6.380 *** par_35 e13 .653 .126 5.176 *** par_36 e14 .812 .144 5.641 *** par_37 e32 .722 .127 5.686 *** par_38 e31 .747 .125 6.000 *** par_39 e33 .871 .137 6.341 *** par_40 e34 .642 .115 5.591 *** par_41

  Estimate S.E. C.R. P Label e53 .720 .119 6.062 *** par_42 e54 .608 .104 5.827 *** par_43 e52 .740 .112 6.613 *** par_44 e51 .560 .096 5.861 *** par_45 e42 .766 .126 6.083 *** par_46 e41 .875 .137 6.392 *** par_47 e43 .719 .121 5.955 *** par_48 e44 .754 .119 6.315 *** par_49

  Squared Multiple Correlations: (Group number 1 - Default model)

  Estimate Y1 .537 Y2 .649 Y1.4 .505 Y1.3 .560 Y1.1 .497 Y1.2 .542 Y2.1 .672 Y2.2 .553 Y2.4 .670 Y2.3 .639 X3.4 .651 X3.3 .558 X3.1 .609 X3.2 .640 X1.4 .608 X1.3 .658 X1.1 .511 X1.2 .560 X2.4 .685 X2.3 .713 X2.1 .652 X2.2 .628

  Matrices (Group number 1 - Default model) Implied Correlations (Group number 1 - Default model)

  Y1.4 Y1.3 Y1.1 Y1.2 Y2.1 Y2.2 Y2.4 Y2.3

  X3.4 X3.3

  X3.1 X3.2

  X1.4 X1.3

  X1.1 X1.2

  X2.4 X2.3

  X2.1 X2.2 Y1.4 1.000 Y1.3 .532 1.000 Y1.1 .501 .528 1.000 Y1.2 .523 .551 .519 1.000 Y2.1 .395 .416 .392 .409 1.000 Y2.2 .358 .377 .356 .371 .609 1.000 Y2.4 .395 .415 .391 .409 .671 .609 1.000 Y2.3 .385 .406 .382 .399 .655 .594 .654 1.000 X3.4 .298 .313 .295 .308 .413 .374 .412 .402 1.000 X3.3 .276 .290 .273 .285 .382 .347 .382 .373 .603 1.000 X3.1 .288 .303 .285 .298 .399 .362 .399 .389 .630 .583 1.000 X3.2 .295 .311 .293 .306 .409 .371 .408 .399 .645 .598 .624 1.000 X1.4 .327 .345 .325 .339 .260 .236 .260 .254 .210 .194 .203 .208 1.000 X1.3 .341 .359 .338 .353 .271 .246 .271 .264 .218 .202 .211 .216 .632 1.000 X1.1 .300 .316 .298 .311 .239 .217 .238 .233 .192 .178 .186 .191 .557 .580 1.000 X1.2 .314 .331 .312 .325 .250 .227 .250 .244 .201 .186 .195 .200 .583 .607 .535 1.000 X2.4 .298 .314 .295 .308 .424 .384 .423 .413 .225 .209 .218 .223 .189 .197 .173 .181 1.000 X2.3 .304 .320 .301 .315 .432 .392 .432 .422 .230 .213 .222 .228 .193 .201 .177 .185 .699 1.000 X2.1 .290 .306 .288 .301 .413 .375 .413 .403 .220 .203 .212 .218 .184 .192 .169 .177 .668 .682 1.000 X2.2 .285 .300 .283 .295 .406 .368 .405 .396 .216 .200 .209 .214 .181 .188 .166 .174 .656 .669 .640 1.000

  Universitas Sumatera Utara

  Residual Covariances (Group number 1 - Default model)

  Y1.4 Y1.3 Y1.1 Y1.2 Y2.1 Y2.2 Y2.4 Y2.3

  X3.4 X3.3

  X3.1 X3.2

  X1.4 X1.3

  X1.1 X1.2

  X2.4 X2.3

  X2.1 X2.2 Y1.4 .000 Y1.3 -.039 .000 Y1.1 -.008 -.024 .000 Y1.2 -.028 .059 .018 .000 Y2.1 -.011 .018 -.014 -.067 .000 Y2.2 .040 -.054 -.011 -.085 -.026 .000 Y2.4 -.013 -.006 -.013 -.048 .025 .059 .000 Y2.3 .175 .141 .062 .025 .000 -.028 -.037 .000 X3.4 -.107 .052 -.060 -.113 .044 .085 -.025 .096 .000 X3.3 .091 .059 -.081 -.068 -.061 -.092 -.172 .069 .013 .000 X3.1 .041 .083 .013 -.064 .004 -.063 -.116 .028 .021 -.007 .000 X3.2 .056 .091 .062 -.066 .011 .022 -.010 .135 -.039 .022 -.003 .000 X1.4 .118 .016 .013 .138 -.150 -.128 -.129 .054 -.107 -.063 -.043 .084 .000 X1.3 .065 -.072 -.001 -.055 -.174 -.061 -.122 .026 -.077 .003 -.099 .065 -.036 .000 X1.1 .082 -.050 .127 -.007 .035 .102 .017 .100 .060 -.134 -.102 .072 .064 -.025 .000 X1.2 .070 -.108 -.052 -.092 -.131 -.077 -.099 .079 .112 .169 .025 .140 -.031 .076 -.056 .000 X2.4 .016 -.084 -.006 -.073 .000 -.054 -.023 .002 .019 .044 .032 -.012 -.145 -.050 .009 -.062 .000 X2.3 .023 .058 .058 -.017 .058 .048 .087 -.016 -.011 .065 -.016 -.033 .029 .114 .148 .053 -.016 .000 X2.1 -.011 -.045 -.010 -.060 .039 .025 -.006 -.079 .000 .096 -.001 .002 .025 -.026 .018 -.080 .013 .001 .000 X2.2 .074 -.028 .090 .040 -.072 .064 -.026 -.125 -.052 .002 -.020 -.092 -.003 .062 .099 -.157 .027 -.009 -.009 .000

  Universitas Sumatera Utara

  Standardized Residual Covariances (Group number 1 - Default model)

  Y1.4 Y1.3 Y1.1 Y1.2 Y2.1 Y2.2 Y2.4 Y2.3

  X3.4 X3.3

  X3.1 X3.2

  X1.4 X1.3

  X1.1 X1.2

  X2.4 X2.3

  X2.1 X2.2 Y1.4 .000 Y1.3 -.238 .000 Y1.1 -.045 -.137 .000 Y1.2 -.171 .344 .100 .000 Y2.1 -.069 .112 -.083 -.404 .000 Y2.2 .260 -.336 -.068 -.529 -.143 .000 Y2.4 -.081 -.038 -.075 -.280 .128 .317 .000 Y2.3 1.032 .796 .343 .142 .001 -.146 -.179 .000 X3.4 -.672 .314 -.351 -.674 .253 .504 -.137 .514 .000 X3.3 .557 .345 -.462 -.398 -.345 -.527 -.926 .359 .063 .000 X3.1 .251 .497 .073 -.376 .024 -.364 -.630 .149 .106 -.032 .000 X3.2 .341 .526 .349 -.377 .059 .124 -.053 .693 -.187 .106 -.014 .000 X1.4 .697 .091 .071 .774 -.852 -.738 -.705 .285 -.590 -.339 -.231 .444 .000 X1.3 .396 -.424 -.007 -.320 -1.026 -.365 -.688 .143 -.439 .017 -.558 .358 -.170 .000 X1.1 .509 -.295 .737 -.043 .207 .619 .099 .551 .346 -.749 -.581 .399 .313 -.124 .000 X1.2 .448 -.670 -.314 -.563 -.811 -.489 -.590 .453 .674 .988 .147 .812 -.154 .392 -.301 .000 X2.4 .099 -.503 -.036 -.436 .002 -.312 -.128 .012 .107 .249 .184 -.068 -.797 -.287 .051 -.369 .000 X2.3 .149 .357 .348 -.103 .335 .290 .487 -.085 -.066 .377 -.094 -.191 .165 .669 .878 .326 -.081 .000 X2.1 -.064 -.263 -.059 -.345 .215 .139 -.031 -.405 .002 .522 -.004 .012 .130 -.142 .101 -.465 .061 .005 .000 X2.2 .431 -.157 .491 .222 -.381 .349 -.131 -.615 -.283 .013 -.106 -.475 -.013 .333 .531 -.880 .124 -.041 -.042 .000

  Factor Score Weights (Group number 1 - Default model)

  Y1.4 Y1.3 Y1.1 Y1.2 Y2.1 Y2.2 Y2.4 Y2.3

  X3.4 X3.3

  X3.1 X3.2

  X1.4 X1.3

  X1.1 X1.2

  X2.4 X2.3

  X2.1 X2.2 SDTB .010 .011 .009 .010 .027 .018 .026 .022 .240 .169 .203 .220 .003 .004 .002 .003 -.002 -.002 -.002 -.002 Kapabilitas .021 .024 .019 .022 .004 .002 .003 .003 .003 .002 .003 .003 .189 .235 .145 .176 .001 .001 .001 .001 SDB .008 .009 .007 .009 .023 .016 .022 .019 -.002 -.001 -.002 -.002 .001 .001 .001 .001 .228 .263 .194 .173 Y1 .165 .189 .151 .177 .028 .019 .027 .023 .012 .008 .010 .011 .024 .030 .018 .022 .011 .012 .009 .008 Y2 .020 .023 .018 .022 .225 .152 .215 .185 .024 .017 .021 .022 .003 .004 .002 .003 .023 .026 .020 .017

  Universitas Sumatera Utara

  Total Effects (Group number 1 - Default model)

  SDTB Kapabilitas SDB Y1 Y2 Y1 .239 .397 .238 .000 .000 Y2 .430 .155 .427 .390 .000 Y1.4 .220 .366 .219 .921 .000 Y1.3 .240 .399 .239 1.005 .000 Y1.1 .233 .388 .232 .977 .000 Y1.2 .239 .397 .238 1.000 .000 Y2.1 .407 .147 .405 .370 .948 Y2.2 .364 .131 .362 .330 .847 Y2.4 .423 .152 .420 .384 .984 Y2.3 .430 .155 .427 .390 1.000 X3.4 .967 .000 .000 .000 .000 X3.3 .927 .000 .000 .000 .000 X3.1 .953 .000 .000 .000 .000 X3.2 1.000 .000 .000 .000 .000 X1.4 .000 1.136 .000 .000 .000 X1.3 .000 1.137 .000 .000 .000 X1.1 .000 .998 .000 .000 .000 X1.2 .000 1.000 .000 .000 .000 X2.4 .000 .000 .975 .000 .000 X2.3 .000 .000 .965 .000 .000 X2.1 .000 .000 .982 .000 .000 X2.2 .000 .000 1.000 .000 .000

  Standardized Total Effects (Group number 1 - Default model)

  SDTB Kapabilitas SDB Y1 Y2 Y1 .284 .411 .290 .000 .000 Y2 .431 .135 .440 .329 .000 Y1.4 .202 .292 .206 .711 .000 Y1.3 .212 .308 .217 .748 .000 Y1.1 .200 .290 .205 .705 .000 Y1.2 .209 .303 .214 .736 .000 Y2.1 .353 .111 .360 .270 .820 Y2.2 .320 .101 .327 .245 .744 Y2.4 .352 .111 .360 .269 .818 Y2.3 .344 .108 .352 .263 .799 X3.4 .807 .000 .000 .000 .000 X3.3 .747 .000 .000 .000 .000 X3.1 .780 .000 .000 .000 .000 X3.2 .800 .000 .000 .000 .000 X1.4 .000 .779 .000 .000 .000 X1.3 .000 .811 .000 .000 .000 X1.1 .000 .715 .000 .000 .000 X1.2 .000 .748 .000 .000 .000 X2.4 .000 .000 .828 .000 .000 X2.3 .000 .000 .845 .000 .000 X2.1 .000 .000 .807 .000 .000 X2.2 .000 .000 .793 .000 .000

  Direct Effects (Group number 1 - Default model)

  SDTB Kapabilitas SDB Y1 Y2 Y1 .239 .397 .238 .000 .000 Y2 .336 .000 .334 .390 .000 Y1.4 .000 .000 .000 .921 .000 Y1.3 .000 .000 .000 1.005 .000 Y1.1 .000 .000 .000 .977 .000 Y1.2 .000 .000 .000 1.000 .000 Y2.1 .000 .000 .000 .000 .948 Y2.2 .000 .000 .000 .000 .847 Y2.4 .000 .000 .000 .000 .984 Y2.3 .000 .000 .000 .000 1.000 X3.4 .967 .000 .000 .000 .000 X3.3 .927 .000 .000 .000 .000 X3.1 .953 .000 .000 .000 .000 X3.2 1.000 .000 .000 .000 .000 X1.4 .000 1.136 .000 .000 .000 X1.3 .000 1.137 .000 .000 .000 X1.1 .000 .998 .000 .000 .000 X1.2 .000 1.000 .000 .000 .000 X2.4 .000 .000 .975 .000 .000 X2.3 .000 .000 .965 .000 .000 X2.1 .000 .000 .982 .000 .000 X2.2 .000 .000 1.000 .000 .000

  Standardized Direct Effects (Group number 1 - Default model)

  SDTB Kapabilitas SDB Y1 Y2 Y1 .284 .411 .290 .000 .000 Y2 .337 .000 .344 .329 .000 Y1.4 .000 .000 .000 .711 .000 Y1.3 .000 .000 .000 .748 .000 Y1.1 .000 .000 .000 .705 .000 Y1.2 .000 .000 .000 .736 .000 Y2.1 .000 .000 .000 .000 .820 Y2.2 .000 .000 .000 .000 .744 Y2.4 .000 .000 .000 .000 .818 Y2.3 .000 .000 .000 .000 .799 X3.4 .807 .000 .000 .000 .000 X3.3 .747 .000 .000 .000 .000 X3.1 .780 .000 .000 .000 .000 X3.2 .800 .000 .000 .000 .000 X1.4 .000 .779 .000 .000 .000 X1.3 .000 .811 .000 .000 .000 X1.1 .000 .715 .000 .000 .000 X1.2 .000 .748 .000 .000 .000 X2.4 .000 .000 .828 .000 .000 X2.3 .000 .000 .845 .000 .000 X2.1 .000 .000 .807 .000 .000 X2.2 .000 .000 .793 .000 .000

  Indirect Effects (Group number 1 - Default model)

  SDTB Kapabilitas SDB Y1 Y2 Y1 .000 .000 .000 .000 .000 Y2 .093 .155 .093 .000 .000 Y1.4 .220 .366 .219 .000 .000 Y1.3 .240 .399 .239 .000 .000 Y1.1 .233 .388 .232 .000 .000 Y1.2 .239 .397 .238 .000 .000 Y2.1 .407 .147 .405 .370 .000 Y2.2 .364 .131 .362 .330 .000 Y2.4 .423 .152 .420 .384 .000 Y2.3 .430 .155 .427 .390 .000 X3.4 .000 .000 .000 .000 .000 X3.3 .000 .000 .000 .000 .000 X3.1 .000 .000 .000 .000 .000 X3.2 .000 .000 .000 .000 .000 X1.4 .000 .000 .000 .000 .000 X1.3 .000 .000 .000 .000 .000 X1.1 .000 .000 .000 .000 .000 X1.2 .000 .000 .000 .000 .000 X2.4 .000 .000 .000 .000 .000 X2.3 .000 .000 .000 .000 .000 X2.1 .000 .000 .000 .000 .000 X2.2 .000 .000 .000 .000 .000

  Standardized Indirect Effects (Group number 1 - Default model)

  SDTB Kapabilitas SDB Y1 Y2 Y1 .000 .000 .000 .000 .000 Y2 .093 .135 .095 .000 .000 Y1.4 .202 .292 .206 .000 .000 Y1.3 .212 .308 .217 .000 .000 Y1.1 .200 .290 .205 .000 .000 Y1.2 .209 .303 .214 .000 .000 Y2.1 .353 .111 .360 .270 .000 Y2.2 .320 .101 .327 .245 .000 Y2.4 .352 .111 .360 .269 .000 Y2.3 .344 .108 .352 .263 .000 X3.4 .000 .000 .000 .000 .000 X3.3 .000 .000 .000 .000 .000 X3.1 .000 .000 .000 .000 .000 X3.2 .000 .000 .000 .000 .000 X1.4 .000 .000 .000 .000 .000 X1.3 .000 .000 .000 .000 .000 X1.1 .000 .000 .000 .000 .000 X1.2 .000 .000 .000 .000 .000 X2.4 .000 .000 .000 .000 .000 X2.3 .000 .000 .000 .000 .000 X2.1 .000 .000 .000 .000 .000 X2.2 .000 .000 .000 .000 .000

  Minimization History (Default model)

  Negative Condition Smallest Iteration Diameter F NTries Ratio eigenvalues # eigenvalue e 10 -.619 9999.000 1321.812 9999.000 1 e*

  6 -.175 4.312 548.209 20 .285 2 e 3 -.132 1.327 195.539 5 .847 3 e 1068.457 .753 112.959

  5 .826 4 e 33.800 .710 95.025 6 .000 5 e 24.199 .352 83.377 2 .000 6 e 25.366 .254 79.998 1 1.079 7 e 28.610 .054 79.893 1 1.030 8 e 28.372 .003 79.893 1 1.002 9 e 28.376 .000 79.893 1 1.000

  Model Fit Summary CMIN

  Model NPAR CMIN DF P CMIN/DF Default model 49 79.893 161 1.000 .496 Saturated model 210 .000 Independence model 20 1337.797 190 .000 7.041

RMR, GFI

  Model RMR GFI AGFI PGFI Default model .067 .939 .920 .720 Saturated model .000 1.000 Independence model .650 .276 .200 .250

  Baseline Comparisons

  NFI RFI

  IFI TLI Model

  CFI Delta1 rho1 Delta2 rho2

  Default model .940 .930 1.069 1.083 1.000 Saturated model 1.000 1.000 1.000 Independence model .000 .000 .000 .000 .000

  Parsimony-Adjusted Measures

  Model PRATIO PNFI PCFI Default model .847 .797 .847 Saturated model .000 .000 .000 Independence model 1.000 .000 .000

  NCP

  Model NCP LO 90 HI 90 Default model .000 .000 .000 Saturated model .000 .000 .000 Independence model 1147.797 1035.516 1267.538

  FMIN

  Model FMIN F0 LO 90 HI 90 Default model .660 .000 .000 .000 Saturated model .000 .000 .000 .000 Independence model 11.056 9.486 8.558 10.476

  RMSEA

  Model RMSEA LO 90 HI 90 PCLOSE Default model .000 .000 .000 1.000 Independence model .223 .212 .235 .000

  AIC

  Model AIC BCC BIC CAIC Default model 177.893 198.473 315.290 364.290 Saturated model 420.000 508.200 1008.844 1218.844 Independence model 1377.797 1386.197 1433.877 1453.877

  ECVI

  Model ECVI LO 90 HI 90 MECVI Default model 1.470 2.140 2.140 1.640 Saturated model 3.471 3.471 3.471 4.200 Independence model 11.387 10.459 12.376 11.456

  HOELTER

  HOELTER HOELTER Model

  .05 .01 Default model 291 312 Independence model

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