ANGKET/KUESIONER
“PENERAPAN ANALISIS KOMPONEN UTAMA DALAM PENENTUAN FAKTOR DOMINAN YANG MEMPENGARUHI PRESTASI BELAJAR SISWA”
(Studi Kasus : SMA Negeri 1 Medan)
Nama :
Jenis Kelamin : [ ]Laki-laki [ ]Perempuan
Kelas :
Nilai Raport :
No Variabel Pernyataan Skala
1. X1 = Bakat Bakat merupakan komponen dasar siswa dalam menggali potensi yang dimilikinya sehingga dapat menciptakan prestasi sesuai dengan prestasi yang dimilikinya.
1 2 3 4 5
2. X2 = Minat Jika bahan pelajaran yang dipelajari tidak sesuai dengan minat siswa, siswa tidak akan belajar dengan sebaik-baiknya karena tidak ada daya tarik baginya.
1 2 3 4 5
3. X3 = Motivasi siswa
Motivasi adalah keinginan atau dorongan untuk belajar, tanpa motivasi siswa tidak akan mengerti apa yang akan dipelajari dan tidak memahami mengapa hal itu perlu dipelajari, kegiatan belajar-mengajar sulit untuk berhasil.
1 2 3 4 5
4. X4 = Motivasi orang tua
Dalam meningkatkan prestasi siswa, dorongan/motivasi orang tua sangat berperan penting
1 2 3 4 5
5. X5 = Fasilitas belajar di rumah
Intensitas saya belajar di rumah dipengaruhi oleh fasilitas belajar yang ada di rumah.
1 2 3 4 5
6. X6 = Kualitas pengajaran guru
Interaksi tanya-jawab antara guru dengan siswa sering dilakukan untuk mengetahui sejauh mana tingkat penguasaan siswa dalam menerima materi yang diajarkan.
1 2 3 4 5
7. X7 = Fasilitas sekolah
Sarana dan prasarana yang ada di sekolah sudah cukup memadai dalam mendukung kegiatan belajar-mengajar.
1 2 3 4 5
8. X8 =
Ekstrakulikuler
Dengan mengikuti kegiatan ekstrakulikuler yang terdapat di sekolah merupakan salah satu cara meningkatkan kreativitas siswa.
9. X9 = Les tambahan
Saya mengikuti bimbingan di luar sekolah untuk menambah ilmu pengetahuan dan memperdalam materi pelajaran.
1 2 3 4 5
10. X10 = Pergaulan siswa
Siswa menyadari bahwa pergaulan dengan teman di lingkungan masyarakat sangat berpengaruh terhadap prestasi di sekolah.
DATA HASIL KUESIONER
NomorResponden X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
1. 5 5 3 4 3 3 4 4 4 5
2. 3 4 4 4 3 4 3 4 3 2
3. 5 5 5 5 3 5 5 4 4 5
4. 5 4 5 4 4 4 5 5 5 5
5. 4 4 2 3 4 3 2 4 2 3
6. 3 4 5 4 5 5 5 5 5 4
7. 3 5 2 4 5 4 2 4 2 3
8. 4 5 5 3 4 5 5 4 5 5
9. 3 2 3 3 4 2 2 4 4 4
10. 5 4 5 4 5 5 5 5 4 4
11. 4 1 4 5 3 3 2 4 2 4
12. 4 2 5 5 2 4 3 4 3 1
13. 3 3 5 2 3 4 1 4 3 5
14. 3 4 3 4 4 3 4 4 3 3
15. 5 2 2 4 4 4 4 4 4 4
16. 4 5 2 3 2 4 4 5 4 4
17. 4 5 2 5 2 4 4 5 4 4
18. 5 5 5 4 5 5 4 5 5 5
19. 5 5 5 4 5 5 4 5 5 5
20. 4 2 1 4 4 4 5 4 4 4
21. 4 3 2 4 4 4 3 4 4 2
22. 2 4 3 4 5 5 4 4 4 4
23. 4 4 2 2 4 2 4 4 2 4
24. 4 5 2 4 5 4 3 4 4 4
25. 4 4 2 2 4 2 4 5 4 2
26. 4 4 2 2 4 2 3 5 4 2
27. 4 4 4 2 4 2 2 5 5 2
28. 4 4 4 4 4 4 2 4 4 4
29. 4 4 5 4 4 4 4 4 5 4
30. 2 5 2 5 5 5 3 5 4 4
31. 4 4 3 4 5 4 4 5 4 4
32. 2 2 2 4 4 4 5 5 4 3
33. 4 5 5 5 5 4 4 5 5 4
34. 4 4 2 2 3 4 3 4 4 3
35. 2 2 3 3 3 5 3 5 4 3
36. 1 4 2 4 2 2 4 2 2 4
37. 4 5 2 3 5 3 3 5 4 2
38. 3 5 3 3 4 3 2 5 5 4
39. 4 4 2 4 5 4 4 4 3 3
41. 4 4 3 3 5 4 4 5 4 2
42. 5 4 5 4 5 4 5 4 4 5
43. 5 3 5 5 5 5 5 5 4 4
44. 5 5 4 5 4 4 5 5 5 5
45. 5 5 5 4 4 5 4 5 4 5
46. 4 4 2 4 4 4 2 4 3 2
47. 4 5 5 5 4 5 5 5 4 5
48. 4 3 5 2 5 4 2 5 5 1
49. 3 3 4 3 4 2 2 4 4 1
50. 5 4 5 5 5 5 5 4 5 5
51. 5 5 4 4 4 4 4 4 4 5
52. 3 4 4 3 4 4 4 5 4 3
53. 3 4 2 4 3 3 3 5 4 4
54. 5 4 4 4 4 5 4 5 5 5
55. 3 4 2 3 4 2 3 4 5 4
56. 3 4 4 2 4 3 3 4 5 3
57. 5 4 5 4 5 5 4 5 5 5
58. 5 4 5 5 4 5 5 4 5 5
59. 4 5 4 4 4 4 4 5 2 4
60. 3 4 3 2 2 2 3 4 4 1
61. 3 3 3 2 3 2 2 5 4 3
62. 3 3 3 2 3 2 2 4 4 4
63. 4 4 4 4 4 4 4 5 4 4
64. 3 4 5 2 3 3 3 5 5 4
65. 4 2 5 5 4 4 2 5 4 2
66. 2 2 3 4 5 3 5 5 5 2
67. 3 4 2 4 5 4 4 4 2 1
68. 3 4 2 4 5 4 4 4 2 1
69. 2 4 2 4 4 2 2 5 5 4
70. 5 4 5 5 4 5 5 5 5 4
71. 5 4 5 4 4 5 5 5 5 5
72. 5 4 5 4 5 5 4 5 5 5
73. 4 4 3 3 4 4 2 4 4 4
74. 5 5 5 4 4 5 5 4 4 5
75. 4 4 2 4 4 2 4 5 5 4
76. 4 4 5 4 4 5 5 4 5 5
77. 2 2 4 5 4 4 2 5 2 2
78. 4 4 4 2 4 3 2 5 3 4
79. 5 4 4 2 4 2 2 4 5 3
80. 5 4 4 4 4 4 4 4 5 4
81. 4 4 4 4 5 2 2 4 4 2
82. 4 4 2 3 4 3 2 5 4 2
84. 4 5 5 4 4 1 2 5 5 2
85. 4 4 4 3 4 2 3 4 5 4
86. 4 4 2 4 4 2 4 5 4 4
87. 4 5 5 5 4 5 5 4 4 4
88. 4 4 2 4 4 4 3 5 5 3
89. 4 4 2 4 4 4 4 4 4 4
DATA HASIL KUESIONER (INTERVAL)
Nomor
Responden X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
57. 4,887 3,568 4,765 2,748 4,172 4,914 3,937 4,427 3,774 4,251 58. 4,887 3,568 4,765 4,035 2,833 4,914 4,999 2,873 3,774 4,251 59. 3,674 4,941 3,857 2,748 2,833 3,761 3,937 4,427 1,000 3,101 60. 2,725 3,568 3,418 1,000 1,000 2,302 3,255 2,873 2,495 1,000 61. 2,725 2,588 3,418 1,000 1,785 2,302 2,458 4,427 2,495 2,379 62. 2,725 2,588 3,418 1,000 1,785 2,302 2,458 2,873 2,495 3,101 63. 3,674 3,568 3,857 2,748 2,833 3,761 3,937 4,427 2,495 3,101 64. 2,725 3,568 4,765 1,000 1,785 3,018 3,255 4,427 3,774 3,101 65. 3,674 2,028 4,765 4,035 2,833 3,761 2,458 4,427 2,495 1,856 66. 1,936 2,028 3,418 2,748 4,172 3,018 4,999 4,427 3,774 1,856 67. 2,725 3,568 2,612 2,748 4,172 3,761 3,937 2,873 1,000 1,000 68. 2,725 3,568 2,612 2,748 4,172 3,761 3,937 2,873 1,000 1,000 69. 1,936 3,568 2,612 2,748 2,833 2,302 2,458 4,427 3,774 3,101 70. 4,887 3,568 4,765 4,035 2,833 4,914 4,999 4,427 3,774 3,101 71. 4,887 3,568 4,765 2,748 2,833 4,914 4,999 4,427 3,774 4,251 72. 4,887 3,568 4,765 2,748 4,172 4,914 3,937 4,427 3,774 4,251 73. 3,674 3,568 3,418 1,817 2,833 3,761 2,458 2,873 2,495 3,101 74. 4,887 4,941 4,765 2,748 2,833 4,914 4,999 2,873 2,495 4,251 75. 3,674 3,568 2,612 2,748 2,833 2,302 3,937 4,427 3,774 3,101 76. 3,674 3,568 4,765 2,748 2,833 4,914 4,999 2,873 3,774 4,251 77. 1,936 2,028 3,857 4,035 2,833 3,761 2,458 4,427 1,000 1,856 78. 3,674 3,568 3,857 1,000 2,833 3,018 2,458 4,427 1,663 3,101 79. 4,887 3,568 3,857 1,000 2,833 2,302 2,458 2,873 3,774 2,379 80. 4,887 3,568 3,857 2,748 2,833 3,761 3,937 2,873 3,774 3,101 81. 3,674 3,568 3,857 2,748 4,172 2,302 2,458 2,873 2,495 1,856 82. 3,674 3,568 2,612 1,817 2,833 3,018 2,458 4,427 2,495 1,856 83. 3,674 3,568 2,612 1,817 4,172 3,018 2,458 4,427 3,774 3,101 84. 3,674 4,941 4,765 2,748 2,833 1,000 2,458 4,427 3,774 1,856 85. 3,674 3,568 3,857 1,817 2,833 2,302 3,255 2,873 3,774 3,101 86. 3,674 3,568 2,612 2,748 2,833 2,302 3,937 4,427 2,495 3,101 87. 3,674 4,941 4,765 4,035 2,833 4,914 4,999 2,873 2,495 3,101 88. 3,674 3,568 2,612 2,748 2,833 3,761 3,255 4,427 3,774 2,379 89. 3,674 3,568 2,612 2,748 2,833 3,761 3,937 2,873 2,495 3,101 90. 4,887 3,568 2,612 2,748 2,833 3,761 2,458 2,873 1,000 4,251
Perhitungan Korelasi
Product Momentuntuk
X1dan
YNo.
Responden
X
Y
X
2Y
2XY
1. 4,887 29,466 23,88277 868,2452 144,0003
2. 2,725 25,366 7,425625 643,434 69,12235
3. 4,887 35,058 23,88277 1229,063 171,3284
4. 4,887 35,126 23,88277 1233,836 171,6608
5. 3,674 22,558 13,49828 508,8634 82,87809
6. 2,725 36,468 7,425625 1329,915 99,3753
7. 2,725 26,944 7,425625 725,9791 73,4224
8. 3,674 35,167 13,49828 1236,718 129,2036
9. 2,725 23,325 7,425625 544,0556 63,56063
10. 4,887 35,189 23,88277 1238,266 171,9686
11. 3,674 23,127 13,49828 534,8581 84,9686
12. 3,674 24,38 13,49828 594,3844 89,57212
13. 2,725 23,686 7,425625 561,0266 64,54435
14. 2,725 26,437 7,425625 698,915 72,04083
15. 4,887 26,388 23,88277 696,3265 128,9582
16. 3,674 28,091 13,49828 789,1043 103,2063
17. 3,674 30,309 13,49828 918,6355 111,3553
18. 4,887 37,929 23,88277 1438,609 185,359
19. 4,887 37,929 23,88277 1438,609 185,359
20. 3,674 25,838 13,49828 667,6022 94,92881
21. 3,674 25,021 13,49828 626,0504 91,92715
22. 1,936 31,226 3,748096 975,0631 60,45354
23. 3,674 23,226 13,49828 539,4471 85,33232
24. 3,674 29,958 13,49828 897,4818 110,0657
25. 3,674 25,03 13,49828 626,5009 91,96022
26. 3,674 24,348 13,49828 592,8251 89,45455
27. 3,674 26,075 13,49828 679,9056 95,79955
28. 3,674 27,694 13,49828 766,9576 101,7478
30. 1,936 33,952 3,748096 1152,738 65,73107
31. 3,674 31,627 13,49828 1000,267 116,1976
32. 1,936 28,282 3,748096 799,8715 54,75395
33. 3,674 36,913 13,49828 1362,57 135,6184
34. 3,674 23,728 13,49828 563,018 87,17667
35. 1,936 26,518 3,748096 703,2043 51,33885
36. 1,000 21,268 1 452,3278 21,268
37. 3,674 28,593 13,49828 817,5596 105,0507
38. 2,725 29,787 7,425625 887,2654 81,16958
39. 3,674 27,713 13,49828 768,0104 101,8176
40. 3,674 26,095 13,49828 680,949 95,87303
41. 3,674 29,451 13,49828 867,3614 108,203
42. 4,887 33,632 23,88277 1131,111 164,3596
43. 4,887 35,496 23,88277 1259,966 173,469
44. 4,887 36,878 23,88277 1359,987 180,2228
45. 4,887 35,311 23,88277 1246,867 172,5649
46. 3,674 24,372 13,49828 593,9944 89,54273
47. 3,674 37,66 13,49828 1418,276 138,3628
48. 3,674 27,945 13,49828 780,923 102,6699
49. 2,725 22,223 7,425625 493,8617 60,55768
50. 4,887 37,351 23,88277 1395,097 182,5343
51. 4,887 31,696 23,88277 1004,636 154,8984
52. 2,725 29,074 7,425625 845,2975 79,22665
53. 2,725 27,009 7,425625 729,4861 73,59953
54. 4,887 34,309 23,88277 1177,107 167,6681
55. 2,725 26,135 7,425625 683,0382 71,21788
56. 2,725 26,557 7,425625 705,2742 72,36783
57. 4,887 36,556 23,88277 1336,341 178,6492
58. 4,887 36,012 23,88277 1296,864 175,9906
59. 3,674 30,605 13,49828 936,666 112,4428
60. 2,725 20,911 7,425625 437,2699 56,98248
61. 2,725 22,852 7,425625 522,2139 62,2717
62. 2,725 22,02 7,425625 484,8804 60,0045
64. 2,725 28,693 7,425625 823,2882 78,18843
65. 3,674 28,658 13,49828 821,281 105,2895
66. 1,936 30,44 3,748096 926,5936 58,93184
67. 2,725 25,671 7,425625 659,0002 69,95348
68. 2,725 25,671 7,425625 659,0002 69,95348
69. 1,936 27,823 3,748096 774,1193 53,86533
70. 4,887 36,416 23,88277 1326,125 177,965
71. 4,887 36,279 23,88277 1316,166 177,2955
72. 4,887 36,556 23,88277 1336,341 178,6492
73. 3,674 26,324 13,49828 692,953 96,71438
74. 4,887 34,819 23,88277 1212,363 170,1605
75. 3,674 29,302 13,49828 858,6072 107,6555
76. 3,674 34,725 13,49828 1205,826 127,5797
77. 1,936 26,255 3,748096 689,325 50,82968
78. 3,674 25,925 13,49828 672,1056 95,24845
79. 4,887 25,044 23,88277 627,2019 122,39
80. 4,887 30,452 23,88277 927,3243 148,8189
81. 3,674 26,329 13,49828 693,2162 96,73275
82. 3,674 25,084 13,49828 629,2071 92,15862
83. 3,674 28,947 13,49828 837,9288 106,3513
84. 3,674 28,802 13,49828 829,5552 105,8185
85. 3,674 27,38 13,49828 749,6644 100,5941
86. 3,674 28,023 13,49828 785,2885 102,9565
87. 3,674 34,956 13,49828 1221,922 128,4283
88. 3,674 29,357 13,49828 861,8334 107,8576
89. 3,674 27,928 13,49828 779,9732 102,6075
90. 4,887 26,104 23,88525 681,4188 127,5769
Hasil outout SPSS for Windows 20.0
Case Processing Summary
N
%
Cases
Valid
90
100,0
Excluded
a0
,0
Total
90
100,0
a. Listwise deletion based on all
variables in the procedure.
Item-Total Statistics
Scale Mean if
Item Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Cronbach's
Alpha if Item
Deleted
VAR00001
29,2660
21,745
,531
,734
VAR00002
29,2657
23,540
,328
,761
VAR00003
29,2660
22,182
,488
,740
VAR00004
30,3599
23,015
,381
,755
VAR00005
29,9555
23,994
,273
,768
VAR00006
29,2660
21,091
,613
,722
VAR00007
29,2659
21,557
,550
,731
VAR00008
29,2661
24,846
,211
,774
VAR00009
30,1906
23,088
,382
,754
VAR00010
29,9560
21,522
,552
,731
Reliability Statistics
Cronbach's
Alpha
N of
Items
Correlation Matrix
aVAR0000
1
VAR0000
2
VAR0000
3
VAR0000
4
VAR0000
5
VAR0000
6
VAR0000
7
VAR0000
8
VAR0000
9
VAR0001
0
Correlatio
n
VAR0000
1
1,000
,282
,390
,231
,174
,368
,346
,082
,288
,513
VAR0000
2
,282
1,000
,122
,114
,133
,194
,231
,105
,163
,370
VAR0000
3
,390
,122
1,000
,244
,130
,435
,256
,157
,387
,364
VAR0000
4
,231
,114
,244
1,000
,139
,508
,454
,028
-,038
,277
VAR0000
5
,174
,133
,130
,139
1,000
,273
,176
,226
,192
,018
VAR0000
6
,368
,194
,435
,508
,273
1,000
,555
,107
,112
,483
VAR0000
7
,346
,231
,256
,454
,176
,555
1,000
,068
,247
,420
VAR0000
8
,082
,105
,157
,028
,226
,107
,068
1,000
,363
,009
VAR0000
9
,288
,163
,387
-,038
,192
,112
,247
,363
1,000
,301
VAR0001
0
,513
,370
,364
,277
,018
,483
,420
,009
,301
1,000
Sig.
(1-tailed)
VAR0000
VAR0000
2
,004
,125
,143
,105
,033
,014
,163
,063
,000
VAR0000
3
,000
,125
,010
,111
,000
,008
,070
,000
,000
VAR0000
4
,014
,143
,010
,096
,000
,000
,398
,359
,004
VAR0000
5
,051
,105
,111
,096
,005
,048
,016
,035
,432
VAR0000
6
,000
,033
,000
,000
,005
,000
,158
,147
,000
VAR0000
7
,000
,014
,008
,000
,048
,000
,261
,010
,000
VAR0000
8
,222
,163
,070
,398
,016
,158
,261
,000
,465
VAR0000
9
,003
,063
,000
,359
,035
,147
,010
,000
,002
VAR0001
0
,000
,000
,000
,004
,432
,000
,000
,465
,002
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy.
,738
Bartlett's Test of
Sphericity
Approx. Chi-Square
215,393
df
45
Sig.
,000
Communalities
Initial
Extraction
VAR00001
1,000
,551
VAR00002
1,000
,319
VAR00003
1,000
,433
VAR00004
1,000
,685
VAR00005
1,000
,567
VAR00006
1,000
,729
VAR00007
1,000
,577
VAR00008
1,000
,633
VAR00009
1,000
,694
VAR00010
1,000
,727
Anti-image Matrices
VAR0000
1
VAR0000
2
VAR0000
3
VAR0000
4
VAR0000
5
VAR0000
6
VAR0000
7
VAR0000
8
VAR0000
9
VAR0001
0
Anti-image
Covarianc
e
VAR0000
1
,653
-,070
-,121
-,017
-,084
-,005
-,049
,011
-,039
-,182
VAR0000
2
-,070
,827
,036
,012
-,084
,026
-,051
-,068
,007
-,174
VAR0000
3
-,121
,036
,651
-,061
,040
-,163
,074
-,005
-,206
-,023
VAR0000
4
-,017
,012
-,061
,668
-,020
-,136
-,169
-,025
,131
-,017
VAR0000
5
-,084
-,084
,040
-,020
,826
-,147
,001
-,099
-,104
,145
VAR0000
6
-,005
,026
-,163
-,136
-,147
,459
-,174
-,057
,118
-,142
VAR0000
7
-,049
-,051
,074
-,169
,001
-,174
,579
,045
-,139
-,042
VAR0000
8
,011
-,068
-,005
-,025
-,099
-,057
,045
,817
-,241
,090
VAR0000
VAR0001
0
-,182
-,174
-,023
-,017
,145
-,142
-,042
,090
-,122
,525
Anti-image
Correlatio
n
VAR0000
1
,849
a
-,095
-,186
-,026
-,115
-,008
-,079
,015
-,061
-,310
VAR0000
2
-,095
,787
a
,049
,016
-,102
,042
-,073
-,083
,010
-,264
VAR0000
3
-,186
,049
,757
a
-,092
,055
-,298
,121
-,006
-,323
-,039
VAR0000
4
-,026
,016
-,092
,786
a
-,027
-,246
-,271
-,035
,203
-,028
VAR0000
5
-,115
-,102
,055
-,027
,623
a
-,238
,001
-,121
-,145
,221
VAR0000
6
-,008
,042
-,298
-,246
-,238
,731
a
-,338
-,093
,220
-,289
VAR0000
7
-,079
-,073
,121
-,271
,001
-,338
,787
a
,065
-,231
-,077
VAR0000
8
,015
-,083
-,006
-,035
-,121
-,093
,065
,588
a
-,338
,138
VAR0000
9
-,061
,010
-,323
,203
-,145
,220
-,231
-,338
,579
a
-,212
VAR0001
0
-,310
-,264
-,039
-,028
,221
-,289
-,077
,138
-,212
,750
a
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
3,372
33,721
33,721
3,372
33,721
33,721
2,304
23,041
23,041
2
1,418
14,176
47,897
1,418
14,176
47,897
2,104
21,045
44,086
3
1,125
11,248
59,144
1,125
11,248
59,144
1,506
15,059
59,144
4
,935
9,349
68,494
5
,755
7,553
76,047
6
,640
6,399
82,446
7
,568
5,675
88,121
8
,486
4,864
92,985
9
,424
4,237
97,222
10
,278
2,778
100,000
Component Matrix
aComponent
1
2
3
VAR00001
,679
,032
-,297
VAR00002
,447
,075
-,337
VAR00003
,631
,166
-,087
VAR00004
,551
-,482
,387
VAR00005
,350
,305
,593
VAR00006
,762
-,284
,260
VAR00007
,705
-,243
,146
VAR00008
,255
,680
,326
VAR00009
,475
,661
-,178
VAR00010
,721
-,139
-,433
Extraction Method: Principal Component
Analysis.
a. 3 components extracted.
Rotated Component Matrix
aComponent
1
2
3
VAR00001
,695
,250
,071
VAR00002
,561
,058
,017
VAR00003
,541
,256
,273
VAR00004
,058
,825
-,032
VAR00005
-,095
,365
,652
VAR00006
,328
,778
,125
VAR00007
,370
,658
,083
VAR00008
,078
-,050
,790
VAR00009
,572
-,170
,581
VAR00010
,789
,300
-,125
Extraction Method: Principal Component
Analysis.
Rotation Method: Varimax with Kaiser
Normalization.
Reproduced Correlations
VAR0000
1
VAR0000
2
VAR0000
3
VAR0000
4
VAR0000
5
VAR0000
6
VAR0000
7
VAR0000
8
VAR0000
9
VAR0001
0
Reproduce
d
Correlatio
n
VAR0000
1
,551
a
,406
,460
,244
,071
,431
,428
,098
,396
,614
VAR0000
2
,406
,319
a
,323
,080
-,021
,231
,247
,055
,321
,458
VAR0000
3
,460
,323
,433
a
,234
,220
,411
,391
,246
,425
,470
VAR0000
4
,244
,080
,234
,685
a
,275
,657
,561
-,062
-,126
,297
VAR0000
5
,071
-,021
,220
,275
,567
a
,334
,259
,489
,262
-,047
VAR0000
6
,431
,231
,411
,657
,334
,729
a
,644
,085
,127
,476
VAR0000
7
,428
,247
,391
,561
,259
,644
,577
a
,062
,148
,479
VAR0000
8
,098
,055
,246
-,062
,489
,085
,062
,633
a
VAR0000
9
,396
,321
,425
-,126
,262
,127
,148
,512
,694
a
,328
VAR0001
0
,614
,458
,470
,297
-,047
,476
,479
-,052
,328
,727
a
Residual
bVAR0000
1
-,124
-,070
-,013
,102
-,063
-,082
-,016
-,108
-,102
VAR0000
2
-,124
-,201
,034
,154
-,037
-,016
,050
-,159
-,088
VAR0000
3
-,070
-,201
,010
-,090
,024
-,136
-,089
-,038
-,106
VAR0000
4
-,013
,034
,010
-,136
-,149
-,107
,089
,087
-,019
VAR0000
5
,102
,154
-,090
-,136
-,061
-,083
-,264
-,070
,065
VAR0000
6
-,063
-,037
,024
-,149
-,061
-,088
,022
-,016
,007
VAR0000
7
-,082
-,016
-,136
-,107
-,083
-,088
,007
,098
-,059
VAR0000
8
-,016
,050
-,089
,089
-,264
,022
,007
-,149
,061
VAR0000
9
-,108
-,159
-,038
,087
-,070
-,016
,098
-,149
-,027
VAR0001
0
-,102
-,088
-,106
-,019
,065
,007
-,059
,061
-,027
Perhitungan Nilai Cronbach Alpha Untuk Variabel X
11.
Mencari nilai varians dari masing-masing variabel dengan menggunakan rumus
varians sebagai berikut :
2.
Mencari nilai total varians (tanpa variabel
X1).
745
menggunakan rumus :
745 , 21
5011 , 7 1 9 10 r
3449
,
0
1
11
,
1
r
6551
,
0
11
,
1
r
7271 , 0 r
Dari hasil perhitungan diperoleh nilai
Cronabch Alphauntuk variabel X
1= 0,7271 hampir
sama dengan output SPSS yaitu 0,734. Hal ini disebabkan karena faktor pembulatan dalam
proses perhitungannya.
Perhitungan Korelasi Antara Variabel
X1Dengan
X2Nomor
Responden
X
1X
2X
12X
22X
1X
21. 4,887 4,941 23,88277 24,41348 24,14667
2. 2,725 3,568 7,425625 12,73062 9,7228
3. 4,887 4,941 23,88277 24,41348 24,14667
4. 4,887 3,568 23,88277 12,73062 17,43682
5. 3,674 3,568 13,49828 12,73062 13,10883
6. 2,725 3,568 7,425625 12,73062 9,7228
7. 2,725 4,941 7,425625 24,41348 13,46423
8. 3,674 4,941 13,49828 24,41348 18,15323
9. 2,725 2,028 7,425625 4,112784 5,5263
10. 4,887 3,568 23,88277 12,73062 17,43682
11. 3,674 1,000 13,49828 1 3,674
12. 3,674 2,028 13,49828 4,112784 7,450872
13. 2,725 2,588 7,425625 6,697744 7,0523
14. 2,725 3,568 7,425625 12,73062 9,7228
15. 4,887 2,028 23,88277 4,112784 9,910836
16. 3,674 4,941 13,49828 24,41348 18,15323
17. 3,674 4,941 13,49828 24,41348 18,15323
19. 4,887 4,941 23,88277 24,41348 24,14667
20. 3,674 2,028 13,49828 4,112784 7,450872
21. 3,674 2,588 13,49828 6,697744 9,508312
22. 1,936 3,568 3,748096 12,73062 6,907648
23. 3,674 3,568 13,49828 12,73062 13,10883
24. 3,674 4,941 13,49828 24,41348 18,15323
25. 3,674 3,568 13,49828 12,73062 13,10883
26. 3,674 3,568 13,49828 12,73062 13,10883
27. 3,674 3,568 13,49828 12,73062 13,10883
28. 3,674 3,568 13,49828 12,73062 13,10883
29. 3,674 3,568 13,49828 12,73062 13,10883
30. 1,936 4,941 3,748096 24,41348 9,565776
31. 3,674 3,568 13,49828 12,73062 13,10883
32. 1,936 2,028 3,748096 4,112784 3,926208
33. 3,674 4,941 13,49828 24,41348 18,15323
34. 3,674 3,568 13,49828 12,73062 13,10883
35. 1,936 2,028 3,748096 4,112784 3,926208
36. 1,000 3,568 1 12,73062 3,568
37. 3,674 4,941 13,49828 24,41348 18,15323
38. 2,725 4,941 7,425625 24,41348 13,46423
39. 3,674 3,568 13,49828 12,73062 13,10883
40. 3,674 3,568 13,49828 12,73062 13,10883
41. 3,674 3,568 13,49828 12,73062 13,10883
42. 4,887 3,568 23,88277 12,73062 17,43682
43. 4,887 2,588 23,88277 6,697744 12,64756
44. 4,887 4,941 23,88277 24,41348 24,14667
45. 4,887 4,941 23,88277 24,41348 24,14667
46. 3,674 3,568 13,49828 12,73062 13,10883
47. 3,674 4,941 13,49828 24,41348 18,15323
48. 3,674 2,588 13,49828 6,697744 9,508312
49. 2,725 2,588 7,425625 6,697744 7,0523
50. 4,887 3,568 23,88277 12,73062 17,43682
51. 4,887 4,941 23,88277 24,41348 24,14667
52. 2,725 3,568 7,425625 12,73062 9,7228
54. 4,887 3,568 23,88277 12,73062 17,43682
55. 2,725 3,568 7,425625 12,73062 9,7228
56. 2,725 3,568 7,425625 12,73062 9,7228
57. 4,887 3,568 23,88277 12,73062 17,43682
58. 4,887 3,568 23,88277 12,73062 17,43682
59. 3,674 4,941 13,49828 24,41348 18,15323
60. 2,725 3,568 7,425625 12,73062 9,7228
61. 2,725 2,588 7,425625 6,697744 7,0523
62. 2,725 2,588 7,425625 6,697744 7,0523
63. 3,674 3,568 13,49828 12,73062 13,10883
64. 2,725 3,568 7,425625 12,73062 9,7228
65. 3,674 2,028 13,49828 4,112784 7,450872
66. 1,936 2,028 3,748096 4,112784 3,926208
67. 2,725 3,568 7,425625 12,73062 9,7228
68. 2,725 3,568 7,425625 12,73062 9,7228
69. 1,936 3,568 3,748096 12,73062 6,907648
70. 4,887 3,568 23,88277 12,73062 17,43682
71. 4,887 3,568 23,88277 12,73062 17,43682
72. 4,887 3,568 23,88277 12,73062 17,43682
73. 3,674 3,568 13,49828 12,73062 13,10883
74. 4,887 4,941 23,88277 24,41348 24,14667
75. 3,674 3,568 13,49828 12,73062 13,10883
76. 3,674 3,568 13,49828 12,73062 13,10883
77. 1,936 2,028 3,748096 4,112784 3,926208
78. 3,674 3,568 13,49828 12,73062 13,10883
79. 4,887 3,568 23,88277 12,73062 17,43682
80. 4,887 3,568 23,88277 12,73062 17,43682
81. 3,674 3,568 13,49828 12,73062 13,10883
82. 3,674 3,568 13,49828 12,73062 13,10883
83. 3,674 3,568 13,49828 12,73062 13,10883
84. 3,674 4,941 13,49828 24,41348 18,15323
85. 3,674 3,568 13,49828 12,73062 13,10883
86. 3,674 3,568 13,49828 12,73062 13,10883
87. 3,674 4,941 13,49828 24,41348 18,15323
89. 3,674 3,568 13,49828 12,73062 13,10883
90. 4,887 3,568 23,88277 12,73062 17,43682
Jumlah
326,638
326,638
1263,632
1259,401
1206,88
PERHITUNGANGAN KMO DAN MSA
Untuk menghitung KMO dan MSA maka diperlukan matriks korelasi sederhana dan
matriks korelasi parsial yang semua entrinya telah dikuadratkan. Berikut ini akan disajikan
matriks korelasi sederhana dan matriks korelasi parsial yang semua entrinya telah
dikuadratkan.
MATRIKS KORELASI SEDERHANA = rik
1 2 3 4 5 6 7 8 9 10
1 0,282 0,390 0,231 0,174 0,368 0,346 0,082 0,288 0,513
2 0,282 0,122 0,114 0,133 0,194 0,231 0,105 0,163 0,370
3 0,390 0,122 0,244 0,130 0,435 0,256 0,157 0,387 0,364
4 0,231 0,114 0,244 0,139 0,508 0,454 0,028 0,038 0,277
5 0,174 0,133 0,130 0,139 0,273 0,176 0,226 0,192 0,018
6 0,368 0,194 0,435 0,508 0,273 0,555 0,107 0,112 0,483
7 0,346 0,231 0,256 0,454 0,176 0,555 0,068 0,247 0,420
8 0,082 0,105 0,157 0,028 0,226 0,107 0,068 0,363 0,009
9 0,288 0,163 0,387 0,038 0,192 0,112 0,247 0,363 0,301
1 2 3 4
5 6 7 8 9
10
1
-0,095 -0,186 - 0,026 -0,115 -0,008 -0,079 0,015 -0,061 -0,310
2 -0,095 0,049 0,016 -0,102 0,042 -0,073 -0,083 0,010 -0,264
3 -0,186 0,049 -0,092 0,055 -0,298 0,121 -0,006 -0,323 -0,039
4 -0,026 0,016 -0,092 -0,027 -0,246 -0,271 -0,035 0,203 -0,028
5 -0,115 -0,102 0,055 -0,027 -0,238 0,001 -0,121 -0,145 0,221
6 -0,008 0,042 -0,298 -0,246 -0,238 -0,338 -0,093 0,220 -0,289
7 -0,079 -0,073 0,121 -0,271 0,001 -0,338 0,065 -0,231 -0,077
8 0,015 -0,083 -0,006 -0,035 -0,121 -0,093 0,065 -0,338 0,138
9 -0,061 0,010 -0,323 0,203 -0,145 0,220 -0,231 -0,338 -0,212
KUADRAT MATRIKS KORELASI SEDERHANA =
r2ik1 2 3 4 5 6 7 8 9 10 Jumlah
1 0,079 0,152 0,053 0,030 0,135 0,119 0,006 0,082 0,263 0,923
2 0,079 0,014 0,012 0,017 0,037 0,053 0,011 0,026 0,136 0,390
3 0,152 0,014 0,059 0,016 0,189 0,065 0,024 0,149 0,132 0,805
4 0,053 0,012 0,059 0,019 0,258 0,206 0,000 0,001 0,076 0,688
5 0,030 0,017 0,016 0,019 0,074 0,030 0,051 0,036 0,000 0,277
6 0,135 0,037 0,189 0,258 0,074 0,308 0,011 0,012 0,233 1,260
7 0,119 0,053 0,065 0,206 0,030 0,308 0,004 0,061 0,176 1,025
8 0,006 0,011 0,024 0,000 0,051 0,011 0,004 0,131 0,000 0,242
9 0,082 0,026 0,149 0,001 0,036 0,012 0,061 0,131 0,090 0,593
10 0,263 0,136 0,132 0,076 0,000 0,233 0,176 0,000 0,090 1,109
TOTAL 7,316
KUADRAT MATRIKS KORELASI PARSIAL = a2ik
1 2 3 4 5 6 7 8 9 10 Jumlah
1 0,009 0,034 0,000 0,013 0,000 0,006 0,000 0,003 0,096 0,163
2 0,009 0,002 0,000 0,010 0,001 0,005 0,006 0,000 0,069 0,105
3 0,034 0,002 0,008 0,003 0,088 0,014 0,000 0,104 0,001 0,257
4 0,000 0,000 0,008 0,000 0,060 0,073 0,001 0,041 0,000 0,187
5 0,013 0,010 0,003 0,000 0,056 0,000 0,014 0,021 0,048 0,168
6 0,000 0,001 0,088 0,060 0,056 0,114 0,008 0,048 0,083 0,462
7 0,006 0,005 0,014 0,073 0,000 0,114 0,004 0,053 0,005 0,277
8 0,000 0,006 0,000 0,001 0,014 0,008 0,004 0,114 0,019 0,169
9 0,003 0,000 0,104 0,041 0,021 0,048 0,053 0,114 0,044 0,431
10 0,096 0,069 0,001 0,000 0,048 0,083 0,005 0,019 0,044 0,370
