LAMPIRANdigilib.unila.ac.id/1880/12/LAMPIRAN-LAMPIRAN.pdf · 2014. 6. 2. · I. Pertanyaan Pembuka...

LAMPIRAN

Tampilan rumah akun twitter Merpati Nusantara

Contoh kicauan-kicauan akun twitter Merpati Nusantara

KUESIONER PENELITIAN

Nama(*)

:

Nama Akun Twitter(*)

:

Usia :

Jenis Kelamin :

Pekerjaan :

(*)boleh dilewati

I. Pertanyaan Pembuka

Anda menggunakan twitter untuk kepentingan?

a. Komunikasi

b. Media Informasi

c. Media Promosi

d. Sarana Hiburan

e. Lain-lain….

Anda mengakses twitter dengan menggunakan?

a. PC/Komputer

b. Smartphone

c. Lain-lain…

Apakah anda mengikuti (memfollow) akun twitter @MERPATI_info ?

a. Ya

b. Tidak ( berhenti, terimakasih sudah berpartisipasi dalam survey ini)

II. Penggunaan Twitter (Frekuensi dan Durasi Menggunakan Twitter)

1) Sudah berapa lama anda menggunakan / memiliki akun twitter?

a. > 46tahun

b. 5-6 tahun

c. 4-5 tahun

d. 3-4 tahun

e. < 3 tahun

2) Berapa kali anda mengakses twitter dalam sehari ?

a. > 7x sehari

b. 5x-6x sehari

c. 4x-5x sehari

d. 3x-4x sehari

e. < 3x sehari

3) Berapa lama waktu yang biasa anda gunakan setiap kali mengakses twitter?

a. > 15 menit

b. 10-15 menit

c. 5-10 menit

d. 3-5 menit

e. < 3 menit

4) Berapa kali anda membuka timeline akun twitter @MERPATI_info dalam seminggu?

a. >7x dalam seminggu

b. 5x-7x dalam seminggu

c. 3x-5x dalam seminggu

d. 1x-3x dalam seminggu

e. <1x dalam seminggu

III. Pembentukkan Citra Perusahaan

a. Orientasi Terhadap Manfaat

1) Anda merasa mendapatkan manfaat dari kicauan-kicauan (tweets) yang diposting oleh akun

@MERPATI_info?

a. Sangat setuju

b. Setuju

c. Netral (tidak berpendapat)

d. Tidak setuju

e. Sangat tidak setuju

2) Perusahaan Merpati Nusantara memberikan kesempatan kepada followers nya untuk meminta informasi yang

diinginkan/dibutuhkan?

a. Sangat setuju

b. Setuju


d. Tidak setuju


3) Kicauan (tweet) yang diposting oleh @MERPATI_info mampu memenuhi kebutuhan informasi anda?

a. Sangat setuju

b. Setuju


d. Tidak setuju


4) Anda mendapatkan informasi terbaru seputar produk, promo dan layanan dari akun @MERPATI_info?

a. Sangat setuju

b. Setuju


d. Tidak setuju


5) Anda merasa lebih mudah berkomunikasi dengan pihak perusahaan Merpati dengan adanya akun twitter

@MERPATI_info?

a. Sangat setuju

b. Setuju


d. Tidak setuju


b. Citra Yang Realitas

1) Anda mendapatkan informasi yang benar (fakta) dari akun @MERPATI_info?

a. Sangat setuju

b. Setuju


d. Tidak setuju


2) Anda mendapatkan informasi yang dapat dipercaya dari akun @MERPATI_info?

a. Sangat setuju

b. Setuju


d. Tidak setuju


3) Akun @MERPATI_info memberikan tanggapan / penjelasan terhadap keluhan-keluhan yang disampaikan

followersnya?

a. Sangat setuju

b. Setuju


d. Tidak setuju


c. Citra Yang Ditonjolkan

1) Anda merasa cocok dengan harga tiket yang ditawarkan oleh maskapai Merpati Nusantara?

a. Sangat setuju

b. Setuju


d. Tidak setuju


2) Merpati Nusantara seringkali mengadakan promo tiket pesawat?

a. Sangat setuju

b. Setuju


d. Tidak setuju


3) Anda merasa bangga menggunakan jasa penerbangan Merpati Nusantara?

a. Sangat setuju

b. Setuju


d. Tidak setuju


d. Mudah Dimengerti Sasaran

1) Anda mampu memahami setiap maksud tweet yang disampaikan @MERPATI_info?

a. Sangat setuju

b. Setuju


d. Tidak setuju


2) Akun @MERPATI_info memberikan informasi yang jelas dalam setiap tweetnya?

a. Sangat setuju

b. Setuju


d. Tidak setuju


3) Anda mengerti setiap tweet yang diposting @MERPATI_info yang tidak lebih dari 140 karakter?

a. Sangat setuju

b. Setuju


d. Tidak setuju


e. Citra Adalah Sarana, Bukan Tujuan

1) Anda mendapat respond / balasan langsung jika bertanya menggunakan fasilitas mention kepada

@MERPATI_info?

a. Sangat setuju

b. Setuju


d. Tidak setuju


2) Informasi yang diberikan oleh akun @MERPATI_info bergam (info liburan, tips berpergian, dll) ?

a. Sangat setuju

b. Setuju


d. Tidak setuju


f.

3) Perusahaan Merpati Nusantara memiliki pelayanan jasa yang unggul?

a. Sangat setuju

b. Setuju


d. Tidak setuju


VALIDITAS VARIABEL X DENGAN SPSS

CORRELATIONS

/VARIABLES=VAR00001 VAR00002 VAR00003 VAR00004 VAR00005

/PRINT=TWOTAIL NOSIG

/MISSING=PAIRWISE.

Correlations

Notes

Output Created 16-Oct-2013 22:36:36

Comments

Input Active Dataset DataSet0

Filter <none>

Weight <none>

Split File <none>

N of Rows in Working

Data File

9

Missing Value

Handling

Definition of Missing User-defined missing values are

treated as missing.

Cases Used Statistics for each pair of

variables are based on all the

cases with valid data for that pair.

Syntax CORRELATIONS

/VARIABLES=VAR00001

VAR00002 VAR00003

VAR00004 VAR00005


/MISSING=PAIRWISE.

Resources Processor Time 00 00:00:00.141

Elapsed Time 00 00:00:00.260

Correlations

VAR0000

1

VAR0000

2

VAR0000

3

VAR0000

4

VAR0000

5

VAR0000

1

Pearson Correlation 1 .407 .205 .593 .703*

Sig. (2-tailed) .277 .597 .092 .035

N 9 9 9 9 9

VAR0000

2

Pearson Correlation .407 1 .447 .589 .855**

Sig. (2-tailed) .277 .227 .095 .003

N 9 9 9 9 9

VAR0000

3

Pearson Correlation .205 .447 1 .316 .668*

Sig. (2-tailed) .597 .227 .407 .049

N 9 9 9 9 9

VAR0000

4

Pearson Correlation .593 .589 .316 1 .775*

Sig. (2-tailed) .092 .095 .407 .014

N 9 9 9 9 9

VAR0000

5

Pearson Correlation .703* .855

** .668

* .775

* 1

Sig. (2-tailed) .035 .003 .049 .014

N 9 9 9 9 9

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

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

VALIDITAS VARIABEL Y DENGAN SPSS

Validitas Variabel Y Dengan SPSS 19

Correlations

Notes


Comments


Filter <none>

Weight <none>

Split File <none>

N of Rows in Working Data

File

9

Missing Value Handling Definition of Missing User-defined missing values are

treated as missing.

Cases Used Statistics for each pair of variables are

based on all the cases with valid data

for that pair.

Syntax CORRELATIONS

/VARIABLES=VAR00001

VAR00002 VAR00003 VAR00004

VAR00005 VAR00006 VAR00007

VAR00008 VAR00009 VAR00010

VAR00011 VAR00012 VAR00013

VAR00014 VAR00015 VAR00016

VAR00017 VAR00018


/MISSING=PAIRWISE.


Elapsed Time 00 00:00:00.190

Correlations

VAR0000

1

VAR0000

2

VAR0000

3

VAR0000

4

VAR0000

5

VAR0000

6

VAR0000

7

VAR0000

8

VAR0000

9

VAR0001

0

VAR0001

1

VAR0001

2

VAR0001

3

VAR0001

4

VAR0001

5

VAR0001

6

VAR0001

7

VAR0001

8

VAR0000

1

Pearson

Correlation

1 .949**

.943**

.891**

.857**

.686* .622 .472 .485 .759

* .759

* .857

** .454 .809

** .857

** .879

** .705

* .946

**

Sig. (2-tailed) .000 .000 .001 .003 .041 .074 .200 .186 .018 .018 .003 .220 .008 .003 .002 .034 .000

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0000

2

Pearson

Correlation

.949**

1 .909**

.959**

.822**

.672* .590 .395 .391 .575 .575 .870

** .478 .767

* .680

* .850

** .775

* .898

**

Sig. (2-tailed) .000 .001 .000 .007 .047 .095 .292 .298 .105 .105 .002 .193 .016 .044 .004 .014 .001

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0000

3

Pearson

Correlation

.943**

.909**

1 .866**

.950**

.438 .426 .500 .354 .632 .632 .750* .378 .763

* .800

** .813

** .791

* .880

**

Sig. (2-tailed) .000 .001 .003 .000 .239 .252 .170 .351 .068 .068 .020 .316 .017 .010 .008 .011 .002

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0000

4

Pearson

Correlation

.891**

.959**

.866**

1 .866**

.650 .554 .433 .408 .548 .548 .866**

.655 .721* .693

* .866

** .822

** .897

**

Sig. (2-tailed) .001 .000 .003 .003 .058 .122 .244 .275 .127 .127 .003 .056 .029 .039 .003 .007 .001

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0000

5

Pearson

Correlation

.857**

.822**

.950**

.866**

1 .350 .341 .550 .354 .601 .601 .700* .529 .693

* .820

** .800

** .822

** .852

**

Sig. (2-tailed) .003 .007 .000 .003 .356 .369 .125 .351 .087 .087 .036 .143 .038 .007 .010 .007 .004

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0000

6

Pearson

Correlation

.686* .672

* .438 .650 .350 1 .906

** .406 .707

* .751

* .751

* .875

** .661 .555 .575 .719

* .316 .769

*

Sig. (2-tailed) .041 .047 .239 .058 .356 .001 .278 .033 .020 .020 .002 .052 .121 .105 .029 .407 .015

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0000

7

Pearson

Correlation

.622 .590 .426 .554 .341 .906**

1 .533 .754* .775

* .775

* .853

** .645 .503 .533 .666 .438 .754

*

Sig. (2-tailed) .074 .095 .252 .122 .369 .001 .140 .019 .014 .014 .003 .061 .168 .140 .050 .238 .019

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0000

8

Pearson

Correlation

.472 .395 .500 .433 .550 .406 .533 1 .884**

.672* .672

* .625 .614 .693

* .550 .406 .395 .674

*

Sig. (2-tailed) .200 .292 .170 .244 .125 .278 .140 .002 .047 .047 .072 .078 .038 .125 .278 .292 .046

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0000 Pearson .485 .391 .354 .408 .354 .707* .754

* .884

** 1 .783

* .783

* .707

* .668

* .686

* .566 .442 .224 .692

*

9 Correlation

Sig. (2-tailed) .186 .298 .351 .275 .351 .033 .019 .002 .013 .013 .033 .049 .041 .112 .234 .563 .039

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0001

0

Pearson

Correlation

.759* .575 .632 .548 .601 .751

* .775

* .672

* .783

* 1 1.000

** .791

* .598 .614 .885

** .751

* .350 .845

**

Sig. (2-tailed) .018 .105 .068 .127 .087 .020 .014 .047 .013 .000 .011 .089 .079 .001 .020 .356 .004

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0001

1

Pearson

Correlation

.759* .575 .632 .548 .601 .751

* .775

* .672

* .783

* 1.000

** 1 .791

* .598 .614 .885

** .751

* .350 .845

**

Sig. (2-tailed) .018 .105 .068 .127 .087 .020 .014 .047 .013 .000 .011 .089 .079 .001 .020 .356 .004

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0001

2

Pearson

Correlation

.857**

.870**

.750* .866

** .700

* .875

** .853

** .625 .707

* .791

* .791

* 1 .756

* .693

* .700

* .875

** .632 .946

**

Sig. (2-tailed) .003 .002 .020 .003 .036 .002 .003 .072 .033 .011 .011 .018 .038 .036 .002 .068 .000

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0001

3

Pearson

Correlation

.454 .478 .378 .655 .529 .661 .645 .614 .668* .598 .598 .756

* 1 .367 .529 .661 .478 .687

*

Sig. (2-tailed) .220 .193 .316 .056 .143 .052 .061 .078 .049 .089 .089 .018 .331 .143 .052 .193 .041

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0001

4

Pearson

Correlation

.809**

.767* .763

* .721

* .693

* .555 .503 .693

* .686

* .614 .614 .693

* .367 1 .693

* .555 .570 .817

**

Sig. (2-tailed) .008 .016 .017 .029 .038 .121 .168 .038 .041 .079 .079 .038 .331 .038 .121 .109 .007

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0001

5

Pearson

Correlation

.857**

.680* .800

** .693

* .820

** .575 .533 .550 .566 .885

** .885

** .700

* .529 .693

* 1 .800

** .538 .867

**

Sig. (2-tailed) .003 .044 .010 .039 .007 .105 .140 .125 .112 .001 .001 .036 .143 .038 .010 .136 .002

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0001

6

Pearson

Correlation

.879**

.850**

.813**

.866**

.800**

.719* .666 .406 .442 .751

* .751

* .875

** .661 .555 .800

** 1 .672

* .898

**

Sig. (2-tailed) .002 .004 .008 .003 .010 .029 .050 .278 .234 .020 .020 .002 .052 .121 .010 .047 .001

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0001

7

Pearson

Correlation

.705* .775

* .791

* .822

** .822

** .316 .438 .395 .224 .350 .350 .632 .478 .570 .538 .672

* 1 .723

*

Sig. (2-tailed) .034 .014 .011 .007 .007 .407 .238 .292 .563 .356 .356 .068 .193 .109 .136 .047 .028

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

VAR0001

8

Pearson

Correlation

.946**

.898**

.880**

.897**

.852**

.769* .754

* .674

* .692

* .845

** .845

** .946

** .687

* .817

** .867

** .898

** .723

* 1

Sig. (2-tailed) .000 .001 .002 .001 .004 .015 .019 .046 .039 .004 .004 .000 .041 .007 .002 .001 .028

N 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9

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

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

NEW FILE.

DATASET NAME DataSet1 WINDOW=FRONT.

FREQUENCIES VARIABLES=VAR00001 VAR00002 VAR00003 VAR00004 VAR00005 VAR00006 VAR00007

VAR00008 VAR00009 VAR00010 VAR00011 VAR00012 VAR00013 VAR00014 VAR00015 VAR00016

Frequencies

Notes

Output Created 14-Jan-2014 11:40:26

Comments


Filter <none>

Weight <none>

Split File <none>

N of Rows in Working Data

File

100

Missing Value Handling Definition of Missing User-defined missing values are

treated as missing.

Cases Used Statistics are based on all cases with

valid data.

Syntax FREQUENCIES

VARIABLES=VAR00001

VAR00002 VAR00003 VAR00004

VAR00005 VAR00006 VAR00007

VAR00008 VAR00009 VAR00010

VAR00011 VAR00012 VAR00013

VAR00014 VAR00015 VAR00016

/ORDER=ANALYSIS.

Resources Processor Time 00 00:00:00,078

Elapsed Time 00 00:00:00,117

Statistics

VAR00001 VAR00002 VAR00003 VAR00004 VAR00005 VAR00006 VAR00007 VAR00008 VAR00009 VAR00010 VAR00011 VAR00012 VAR00013 VAR00014 VAR00015 VAR00016

N Valid 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100

Missing 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Frequency Table

VAR00001

Frequency Percent Valid Percent

Cumulative

Percent

Valid 2,00 6 6,0 6,0 6,0

3,00 24 24,0 24,0 30,0

4,00 48 48,0 48,0 78,0

5,00 22 22,0 22,0 100,0

Total 100 100,0 100,0

VAR00002


Cumulative

Percent

Valid 2,00 10 10,0 10,0 10,0

3,00 16 16,0 16,0 26,0

4,00 45 45,0 45,0 71,0

5,00 29 29,0 29,0 100,0

Total 100 100,0 100,0

VAR00003


Cumulative

Percent

Valid 2,00 7 7,0 7,0 7,0

3,00 28 28,0 28,0 35,0

4,00 47 47,0 47,0 82,0

5,00 18 18,0 18,0 100,0

Total 100 100,0 100,0

VAR00004


Cumulative

Percent

Valid 2,00 2 2,0 2,0 2,0

3,00 25 25,0 25,0 27,0

4,00 46 46,0 46,0 73,0

5,00 27 27,0 27,0 100,0

Total 100 100,0 100,0

VAR00005


Cumulative

Percent

Valid 2,00 4 4,0 4,0 4,0

3,00 29 29,0 29,0 33,0

4,00 39 39,0 39,0 72,0

5,00 28 28,0 28,0 100,0

Total 100 100,0 100,0

VAR00006


Cumulative

Percent

Valid 2,00 4 4,0 4,0 4,0

3,00 29 29,0 29,0 33,0

4,00 51 51,0 51,0 84,0

5,00 16 16,0 16,0 100,0

Total 100 100,0 100,0

VAR00007


Cumulative

Percent

Valid 2,00 3 3,0 3,0 3,0

3,00 29 29,0 29,0 32,0

4,00 50 50,0 50,0 82,0

5,00 18 18,0 18,0 100,0

Total 100 100,0 100,0

VAR00008


Cumulative

Percent

Valid 2,00 8 8,0 8,0 8,0

3,00 45 45,0 45,0 53,0

4,00 41 41,0 41,0 94,0

5,00 6 6,0 6,0 100,0

Total 100 100,0 100,0

VAR00009


Cumulative

Percent

Valid 2,00 12 12,0 12,0 12,0

3,00 40 40,0 40,0 52,0

4,00 43 43,0 43,0 95,0

5,00 5 5,0 5,0 100,0

Total 100 100,0 100,0

VAR00010


Cumulative

Percent

Valid 1,00 3 3,0 3,0 3,0

2,00 2 2,0 2,0 5,0

3,00 39 39,0 39,0 44,0

4,00 49 49,0 49,0 93,0

5,00 7 7,0 7,0 100,0

Total 100 100,0 100,0

VAR00011


Cumulative

Percent

Valid 1,00 1 1,0 1,0 1,0

2,00 6 6,0 6,0 7,0

3,00 45 45,0 45,0 52,0

4,00 39 39,0 39,0 91,0

5,00 9 9,0 9,0 100,0

Total 100 100,0 100,0

VAR00012


Cumulative

Percent

Valid 2,00 2 2,0 2,0 2,0

3,00 24 24,0 24,0 26,0

4,00 69 69,0 69,0 95,0

5,00 5 5,0 5,0 100,0

Total 100 100,0 100,0

VAR00013


Cumulative

Percent

Valid 2,00 1 1,0 1,0 1,0

3,00 20 20,0 20,0 21,0

4,00 74 74,0 74,0 95,0

5,00 5 5,0 5,0 100,0

Total 100 100,0 100,0

VAR00014


Cumulative

Percent

Valid 2,00 3 3,0 3,0 3,0

3,00 19 19,0 19,0 22,0

4,00 68 68,0 68,0 90,0

5,00 10 10,0 10,0 100,0

Total 100 100,0 100,0

VAR00015


Cumulative

Percent

Valid 2,00 3 3,0 3,0 3,0

3,00 37 37,0 37,0 40,0

4,00 32 32,0 32,0 72,0

5,00 28 28,0 28,0 100,0

Total 100 100,0 100,0

VAR00016


Cumulative

Percent

Valid 2,00 2 2,0 2,0 2,0

3,00 31 31,0 31,0 33,0

4,00 57 57,0 57,0 90,0

5,00 10 10,0 10,0 100,0

Total 100 100,0 100,0

Reliability Variabel X Dengan SPSS 19

Notes


Comments


Filter <none>

Weight <none>

Split File <none>


Data File

9

Matrix Input

Missing Value

Handling


treated as missing.

Cases Used Statistics are based on all cases

with valid data for all variables in

the procedure.

Syntax RELIABILITY

/VARIABLES=VAR00001

VAR00002 VAR00003

VAR00004

/SCALE('ALL VARIABLES')

ALL

/MODEL=ALPHA

/STATISTICS=DESCRIPTIVE

SCALE

/SUMMARY=TOTAL.


Elapsed Time 00 00:00:00.050

[DataSet1]

Scale: ALL VARIABLES

Case Processing Summary

N %

Cases Valid 9 100.0

Excludeda 0 .0

Total 9 100.0

a. Listwise deletion based on all variables

in the procedure.

Reliability Statistics

Cronbach's

Alpha N of Items

.715 4

Item Statistics

Mean

Std.

Deviation N

VAR0000

1

2.2222 1.09291 9

VAR0000

2

3.3333 1.50000 9

VAR0000

3

3.0000 1.11803 9

VAR0000

4

1.6667 .70711 9

Item-Total Statistics

Scale Mean if

Item Deleted

Scale

Variance if

Item Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if Item

Deleted

VAR0000

1

8.0000 7.250 .467 .672

VAR0000

2

6.8889 4.861 .617 .591

VAR0000

3

7.2222 7.444 .410 .705

VAR0000

4

8.5556 8.028 .666 .623

Scale Statistics

Mean Variance

Std.

Deviation N of Items

10.2222 11.194 3.34581 4

Reliability Variabel Y Dengan SPSS 19

Notes


Comments


Filter <none>

Weight <none>

Split File <none>


Data File

9

Matrix Input

Missing Value

Handling


treated as missing.

Cases Used Statistics are based on all cases

with valid data for all variables in

the procedure.

Syntax RELIABILITY

/VARIABLES=VAR00001

VAR00002 VAR00003

VAR00004 VAR00005

VAR00006 VAR00007

VAR00008 VAR00009

VAR00010 VAR00011

VAR00012 VAR00013

VAR00014 VAR00015

VAR00016 VAR00017

/SCALE('ALL VARIABLES')

ALL

/MODEL=ALPHA

/STATISTICS=DESCRIPTIVE

SCALE

/SUMMARY=TOTAL.


Elapsed Time 00 00:00:00.090

[DataSet3]

Scale: ALL VARIABLES

Case Processing Summary

N %

Cases Valid 9 100.0

Excludeda 0 .0

Total 9 100.0

a. Listwise deletion based on all variables

in the procedure.

Reliability Statistics

Cronbach's

Alpha N of Items

.967 17

Item Statistics

Mean

Std.

Deviation N

VAR0000

1

3.7778 .97183 9

VAR0000

2

3.8889 1.05409 9

VAR0000

3

3.6667 1.00000 9

VAR0000

4

4.0000 .86603 9

VAR0000

5

3.7778 .83333 9

VAR0000

6

3.7778 .66667 9

VAR0000

7

3.8889 .78174 9

VAR0000

8

3.2222 .66667 9

VAR0000

9

3.3333 .70711 9

VAR0001

0

3.5556 .52705 9

VAR0001

1

3.5556 .52705 9

VAR0001

2

3.6667 .50000 9

VAR0001

3

3.7778 .44096 9

VAR0001

4

3.8889 .60093 9

VAR0001 3.7778 .83333 9

5

VAR0001

6

3.7778 .66667 9

VAR0001

7

3.4444 .52705 9

Item-Total Statistics

Scale Mean if

Item Deleted

Scale

Variance if

Item Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if Item

Deleted

VAR0000

1

59.0000 85.000 .935 .962

VAR0000

2

58.8889 84.611 .875 .964

VAR0000

3

59.1111 85.861 .854 .964

VAR0000

4

58.7778 87.694 .879 .963

VAR0000

5

59.0000 89.000 .827 .964

VAR0000

6

59.0000 92.750 .740 .965

VAR0000

7

58.8889 91.361 .717 .965

VAR0000

8

59.5556 94.028 .636 .966

VAR0000

9

59.4444 93.278 .653 .966

VAR0001

0

59.2222 93.944 .829 .964

VAR0001

1

59.2222 93.944 .829 .964

VAR0001

2

59.1111 93.361 .940 .964

VAR0001

3

59.0000 96.750 .663 .967

VAR0001

4

58.8889 93.111 .795 .965

VAR0001

5

59.0000 88.750 .844 .964

VAR0001

6

59.0000 91.000 .884 .963

VAR0001

7

59.3333 95.250 .697 .966

Scale Statistics

Mean Variance

Std.

Deviation N of Items

62.7778 102.694 10.13383 17

HASIL OLAH DATA (REGRESI LINIER SEDERHANA)

Regression

Notes


Comments


Filter <none>

Weight <none>

Split File <none>


Data File

100

Missing Value

Handling


treated as missing.

Cases Used Statistics are based on cases with

no missing values for any

variable used.

Syntax REGRESSION

/MISSING LISTWISE

/STATISTICS COEFF OUTS R

ANOVA

/CRITERIA=PIN(.05)

POUT(.10)

/NOORIGIN

/DEPENDENT Y

/METHOD=ENTER X

/RESIDUALS

HISTOGRAM(ZRESID)

NORMPROB(ZRESID).


Elapsed Time 00 00:00:02.681

Memory Required 1356 bytes

Additional Memory

Required for Residual

Plots

656 bytes

[DataSet0]

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 Xa . Enter

a. All requested variables entered.

b. Dependent Variable: Y

ANOVAb

Model

Sum of

Squares df Mean Square F Sig.

1 Regression 1772.267 1 1772.267 26.695 .000a

Residual 6506.173 98 66.390

Total 8278.440 99

a. Predictors: (Constant), X


Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 49.193 2.857 17.220 .000

X 1.353 .262 .463 5.167 .000

a. Dependent Variable: Y

Residuals Statisticsa

Minimum Maximum Mean

Std.

Deviation N

Predicted Value 55.9553 72.1854 63.3400 4.23104 100

Residual -15.66034 21.28215 .00000 8.10672 100

Std. Predicted

Value

-1.745 2.091 .000 1.000 100

Std. Residual -1.922 2.612 .000 .995 100

a. Dependent Variable: Y

Charts

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .463a .214 .206 8.14798

a. Predictors: (Constant), X


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