Lampiran 1 : Contoh Kuisioner · Penelitian ini dilakukan dalam rangka penyelesaian tugas akhir....

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Lampiran 1 : Contoh Kuisioner Nama kami, Devi Auberta & Stefanus W, Mahasiswa Program Sarjana Ekonomi Universitas Kristen Petra, saat ini sedang mengadakan penelitian tentang Apakah Ketidakpuasan Konsumen dan Kebutuhan Mencari Variasi Berpengaruh Terhadap Keputusan Perpindahan Merek Konsumen Pengguna Kecap di Surabaya. Penelitian ini dilakukan dalam rangka penyelesaian tugas akhir. Demi tercapainya hasil penelitian yang diinginkan, mohon ketersediaan Anda untuk berpartisipasi dengan menjawab kuisioner ini secara lengkap dan benar. Semua informasi yang diperoleh sebagai hasil dari kuisioner ini bersifat rahasia dan dipergunakan hanya untuk kepentingan akademis. Tidak ada jawaban yang salah dalam pengisian kuisioner ini. Atas kerjasama dan partisipasinya, kami ucapkan terima kasih. Nama Responden : …………………. Alamat : …………………. Petunjuk : Beri tanda silang (X) pada kotak yang tersedia dengan jawaban yang Anda pilih. Pilih salah satu jawaban saja untuk pertanyaan berikut, kecuali ada petunjuk khusus.

SCREENING S1. Apakah pada saat ini Anda mengkonsumsi kecap manis merek ABC,

Bango, atau Indofood? 1. Tidak ( Stop, terima kasih atas partisipasi Anda ) 2. Ya ( Lanjut ke pertanyaan berikut )

S2. Status pernikahan Anda : 1. Menikah ( Lanjut ke pertanyaan berikut ) 2. Janda ( Lanjut ke pertanyaan berikut ) 3. Lainnya ( Stop, terima kasih atas partisipasi Anda )

BRAND AWARENESS

Beri jawaban pada tabel di halaman berikutnya

A1.Berbicara masalah kecap, merek Kecap apa yang Anda ingat? A2.Dalam 1-2 bulan terakhir kecap apa saja yang pernah Anda konsumsi?

A3.Kecap merek apa saja yang paling sering Anda konsumsi?

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http://digilib.petra.ac.id/index.html

http://digilib.petra.ac.id/help.html

http://www.petra.ac.id

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Lampiran 1 : Contoh Kuisioner (sambungan)

A.1 A.2 A.3 ABC Bango Indofood Piring Lombok Cap Sate Cap Jeruk Lainnya

USAGE

U1.Dari mana saja Anda mengetahui merek kecap yang paling sering Anda gunakan?

1. TV komersial 2. Koran/ majalah/ tabloid 3. Promosi di mini/super/hypermarket 4. Saudara, tetangga, teman 5. Lainnya, sebutkan…………….

U2.Dimana Anda biasa membeli kecap yang paling sering Anda gunakan?

1. Minimarket 2. Supermarket 3. Hypermarket 4. Grosir 5. lainnya, sebutkan…………..

U4. Berapa ukuran kemasan yang biasa Anda beli?

1. 125 – 135 ml 2. 275 – 300 ml 3. 600 – 625 ml 4. reffil 200 – 225 ml 5. reffil 600 – 620 ml

U5. Apakah anda rutin menggunakan kecap tersebut setiap kali masak? 1. Ya 2. Tidak

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KETIDAKPUASAN

Tingkat Kepuasan Terhadap Kecap yang saya konsumsi Menurut pendapat saya setelah mengkonsumsi kecap yang saya pakai dalam periode 1-2 bulan terakhir, maka pengalaman saya berkaitan dengan kepuasan terhadap kecap tersebut adalah?

1. Sangat Tidak Puas 2. Kurang puas 3. Cukup puas 4. Puas 5. Sangat puas

Atribut Sangat

tdk puas Kurang

puas Cukup puas

Puas Sangat puas

Desain Kemasan Informasi pada label

Komposisi Aroma kecap manis Rasa kecap

Produk

Kekentalan

Harga lebih terjangkau Harga

Harga bersaing Distribusi Mudah di dapat

Iklan TV menarik Diskon Demo masak

Adanya Hot line Service

Promosi cara penanganan

keluhan

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KEBUTUHAN MENCARI VARIASI Beri tanda (X) pada tabel sesuai dengan pilihan Anda.

5 = Sangat Setuju 4 = Setuju 3 = Antara Setuju & Tidak 2 = Tidak Setuju 1 = Sangat Tidak Setuju

EXPLORATORY ACQUISITION OF PRODUCT

( EAP)

Sangat Tdk

setuju

Tidak setuju

Antara setuju

& tidak

Setuju Sangat setuju

Saya lebih suka merek yang belum pernah saya coba

Saya merasa tertantang jika memesan menu yang belum familiar

Meskipun saya menyukai merek tertentu, saya sering mencoba merek yang baru bagi saya

Saya tidak khawatir dalam mencoba produk baru / berbeda

Jika produk makanan tersedia dalam sejumlah variasi rasa, saya pasti mencobanya

Saya menikmati peluang membeli merek yang tidak familiar demi mendapatkan variasi dalam suatu pembelian

KEPUTUSAN PERPINDAHAN MEREK Beri tanda (X) pada tabel sesuai dengan pilihan Anda. Setelah membeli dan mengkonsumsi produk kecap yang saya konsumsi selama 1-2 bulan ini, maka selanjutnya, saya akan berpindah ke merek kecap lain, selain merek kecap yang saya konsumsi saat ini? Ya Tidak

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DEMOGRAFI

D1. Berapa usia Anda saat ini : 1. 20 – 25 tahun 4. 36 – 40 tahun 2. 26 – 30 tahun 5. 41 – 45 tahun 3. 31 – 35 tahun

D1 Status pendidikan terakhir yang Anda tamatkan : 1. SD 2. SMP 3. SMU 4. Diploma 5. Sarjana

D2 Apakah pekerjaan Anda saat ini : 1. Tidak Bekerja 2. Pegawai Negeri 3. Pegawai Swasta 4. Wiraswasta 5. Lainnya, sebutkan…………….

D3 Rata-rata pengeluaran Anda sebulan

1. < Rp. 1.000.000 2. Rp. 1.000.001 – Rp. 2.000.000 3. Rp. 2.000.001 – Rp. 3.000.000 4. Rp. 3.000.001 – Rp. 4.000.000 5. Rp. 4.000.001 – Rp. 5.000.000 6. > Rp. 5.000.001

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Lampiran 2

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Lampiran 3 : Pengujian Validitas dan Reliabilitas Reliability variabel tingkat kepuasan untuk produksi ***** Method 1 (space saver) 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. P1 2.8900 1.1538 100.0 2. P2 3.4100 1.3640 100.0 3. P3 2.9300 1.1304 100.0 4. P4 2.7700 1.4132 100.0 5. P5 3.4600 1.2982 100.0 6. P6 2.6400 1.1679 100.0 N of Statistics for Mean Variance Std Dev Variables SCALE 18.1000 29.9697 5.4745 6 Item-total Statistics Scale Scale Corrected Mean Variance Item- Alpha if Item if Item Total if Item Deleted Deleted Correlation Deleted P1 15.2100 22.9151 .5181 .8035 P2 14.6900 19.1049 .7551 .7491 P3 15.1700 23.1930 .5050 .8060 P4 15.3300 22.1223 .4401 .8252 P5 14.6400 19.3640 .7808 .7445 P6 15.4600 22.6954 .5311 .8010 Reliability Coefficients N of Cases = 100.0 N of Items = 6 Alpha = .8190 Reliability variabel tingkat kepuasan untuk harga ***** Method 1 (space saver) 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. H1 3.7400 .8601 100.0 2. H2 3.7600 .9962 100.0 N of Statistics for Mean Variance Std Dev Variables SCALE 7.5000 2.5556 1.5986 2 Item-total Statistics Scale Scale Corrected Mean Variance Item- Alpha if Item if Item Total if Item Deleted Deleted Correlation Deleted H1 3.7600 .9923 .4805 . H2 3.7400 .7398 .4805 .

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Lampiran 3 : Pengujian Validitas dan Reliabilitas (sambungan) Reliability Coefficients N of Cases = 100.0 N of Items = 2 Alpha = .6444 Reliability variabel tingkat kepuasan untuk Promosi ***** Method 1 (space saver) 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. PM1 3.4600 1.2982 100.0 2. PM2 3.4600 1.2982 100.0 3. PM3 3.4200 1.2648 100.0 4. PM4 2.8700 1.2281 100.0 5. PM5 3.4800 1.2751 100.0 N of Statistics for Mean Variance Std Dev Variables SCALE 16.6900 33.5898 5.7957 5 Item-total Statistics Scale Scale Corrected Mean Variance Item- Alpha if Item if Item Total if Item Deleted Deleted Correlation Deleted PM1 13.2300 20.6637 .9524 .9192 PM2 13.2300 20.6637 .9524 .9192 PM3 13.2700 22.3001 .8112 .9444 PM4 13.8200 24.2501 .6475 .9707 PM5 13.2100 20.9959 .9386 .9219 Reliability Coefficients N of Cases = 100.0 N of Items = 5 Alpha = .9484 Reliability variabel kebutuhan mencari variasi ***** Method 1 (space saver) 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. E1 4.0800 .6917 100.0 2. E2 3.9100 .7261 100.0 3. E3 3.9600 .7375 100.0 4. E4 4.0600 .7361 100.0 5. E5 3.9500 .8919 100.0 6. E6 3.9600 .7510 100.0

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Lampiran 3 : Pengujian Validitas dan Reliabilitas (sambungan) N of Statistics for Mean Variance Std Dev Variables SCALE 23.9200 6.9632 2.6388 6 Item-total Statistics Scale Scale Corrected Mean Variance Item- Alpha if Item if Item Total if Item Deleted Deleted Correlation Deleted E1 19.8400 5.5903 .2735 .5854 E2 20.0100 5.8080 .1795 .6208 E3 19.9600 5.0287 .4205 .5274 E4 19.8600 4.7277 .5291 .4809 E5 19.9700 4.6961 .3807 .5432 E6 19.9600 5.4529 .2698 .5883 Reliability Coefficients N of Cases = 100.0 N of Items = 6 Alpha = .6053

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Lampiran 4 : Demografi Responden

Status Pernikahan

86 86.0 86.0 86.014 14.0 14.0 100.0

100 100.0 100.0

MenikahJandaTotal

ValidFrequency Percent

ValidPercent

Cumulative Percent

Usia

11 11.0 11.0 11.013 13.0 13.0 24.029 29.0 29.0 53.014 14.0 14.0 67.033 33.0 33.0 100.0

100 100.0 100.0

20 - 25 tahun26 - 30 tahun31 - 35 tahun36 - 40 tahun41 - 45 tahunTotal


ValidPercent

Cumulative Percent

Pendidikan terakhir

1 1.0 1.0 1.042 42.0 42.0 43.036 36.0 36.0 79.021 21.0 21.0 100.0

100 100.0 100.0

SMPSMUDiplomaSarjanaTotal


ValidPercent

Cumulative Percent

Pekerjaan

20 20.0 20.0 20.018 18.0 18.0 38.021 21.0 21.0 59.0

40 40.0 40.0 99.01 1.0 1.0 100.0

100 100.0 100.0

Tidak bekerjaPegawai Negeri

Pegawai SwastaWiraswastaLainnyaTotal


ValidPercent

Cumulative Percent

Pengeluaran

19 19.0 19.0 19.0

31 31.0 31.0 50.0

41 41.0 41.0 91.0

7 7.0 7.0 98.0

2 2.0 2.0 100.0

100 100.0 100.0

< Rp. 1.000.000Rp. 1.000.001 -Rp. 2.000.000Rp. 2.000.001 -Rp. 3.000.000Rp. 3.000.001 -Rp. 4.000.000Rp. 4.000.001 -Rp. 5.000.000Total


ValidPercent

Cumulative Percent

81

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Lampiran 5 : Frekuensi Jawaban Responden Brand Awareness

Merek kecap yang diingat

62 62.0 62.0 62.012 12.0 12.0 74.0

10 10.0 10.0 84.09 9.0 9.0 93.07 7.0 7.0 100.0

100 100.0 100.0

ABCBango

IndofoodPiring LombokCap SateTotal


ValidPercent

Cumulative Percent

Konsumsi kecap 1 bulan terakhir

65 65.0 65.0 65.0

22 22.0 22.0 87.013 13.0 13.0 100.0

100 100.0 100.0

ABC

BangoIndofoodTotal


ValidPercent

Cumulative Percent

Merek kecap paling sering dikonsumsi

51 51.0 51.0 51.023 23.0 23.0 74.0

26 26.0 26.0 100.0100 100.0 100.0

ABC

BangoIndofoodTotal


ValidPercent

Cumulative Percent

Usage

Penggunaan kecap

34 34.0 34.0 34.028 28.0 28.0 62.0

35 35.0 35.0 97.03 3.0 3.0 100.0

100 100.0 100.0

1 - 2 minggu3 - 4 minggu

1 - 2 bulan> 2 bulanTotal


ValidPercent

Cumulative Percent

82

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Lampiran 5 : Frekuensi Jawaban Responden (sambungan)

Sumber informasi merek kecap

54 54.0 54.0 54.012 12.0 12.0 66.0

24 24.0 24.0 90.0

10 10.0 10.0 100.0100 100.0 100.0

TV KomersialKoran / Majalah / TabloidPromosi dimini/super/hypermarketSaudara, tetangga, temanTotal


ValidPercent

Cumulative Percent

Pembelian kecap

41 41.0 41.0 41.023 23.0 23.0 64.0

25 25.0 25.0 89.011 11.0 11.0 100.0

100 100.0 100.0

MinimarketSupermarket

HypermarketGrosirTotal


ValidPercent

Cumulative Percent

Ukuran Kemasan

26 26.0 26.0 26.022 22.0 22.0 48.018 18.0 18.0 66.0

19 19.0 19.0 85.015 15.0 15.0 100.0

100 100.0 100.0

125 - 135 ml275 - 300 ml

600 - 625 mlreffil 200 - 225 mlreffil 600 - 620 mlTotal


ValidPercent

Cumulative Percent

Rutin menggunakan kecap

70 70.0 70.0 70.030 30.0 30.0 100.0

100 100.0 100.0

YaTidakTotal


ValidPercent

Cumulative Percent

84

Lampiran 5 : Frekuensi Jawaban Responden (sambungan) Tingkat Kepuasan untuk Produk

Statistics

100 100 100 100 100 1000 0 0 0 0 0

2.8900 3.4100 2.9300 2.7700 3.4600 2.6400

ValidMissing

N

Mean

DesainKemasan

Informasipada label Komposisi

Aromakecapmanis

Rasakecap

Kekentalan

Desain Kemasan

7 7.0 7.0 7.042 42.0 42.0 49.015 15.0 15.0 64.0

27 27.0 27.0 91.09 9.0 9.0 100.0

100 100.0 100.0

Sangat tidak puasKurang puas

Cukup puasPuasSangat puasTotal


ValidPercent

Cumulative Percent

Informasi pada label

9 9.0 9.0 9.028 28.0 28.0 37.0

1 1.0 1.0 38.0

37 37.0 37.0 75.025 25.0 25.0 100.0

100 100.0 100.0




ValidPercent

Cumulative Percent

Komposisi

5 5.0 5.0 5.043 43.0 43.0 48.015 15.0 15.0 63.0

28 28.0 28.0 91.09 9.0 9.0 100.0

100 100.0 100.0




ValidPercent

Cumulative Percent

85

Lampiran 5 : Frekuensi Jawaban Responden (sambungan) Aroma kecap manis

19 19.0 19.0 19.040 40.0 40.0 59.0

2 2.0 2.0 61.023 23.0 23.0 84.016 16.0 16.0 100.0

100 100.0 100.0




ValidPercent

Cumulative Percent

Rasa kecap

9 9.0 9.0 9.019 19.0 19.0 28.014 14.0 14.0 42.0

33 33.0 33.0 75.025 25.0 25.0 100.0

100 100.0 100.0




ValidPercent

Cumulative Percent

Kekentalan

15 15.0 15.0 15.045 45.0 45.0 60.0

3 3.0 3.0 63.0

35 35.0 35.0 98.02 2.0 2.0 100.0

100 100.0 100.0




ValidPercent

Cumulative Percent

Tingkat Kepuasan untuk Harga

Statistics

100 1000 0

3.7400 3.7600

ValidMissing

N

Mean

Hargalebih

terjangkauHarga

bersaing

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Lampiran 5 : Frekuensi Jawaban Responden (sambungan) Harga lebih terjangkau

10 10.0 10.0 10.023 23.0 23.0 33.0

50 50.0 50.0 83.017 17.0 17.0 100.0

100 100.0 100.0

Kurang puasCukup puas

PuasSangat puasTotal


ValidPercent

Cumulative Percent

Harga bersaing

15 15.0 15.0 15.019 19.0 19.0 34.0

41 41.0 41.0 75.025 25.0 25.0 100.0

100 100.0 100.0

Kurang puasCukup puas

PuasSangat puasTotal


ValidPercent

Cumulative Percent

Tingkat Kepuasan untuk Distribusi

Statistics

Kemudahan mendapatkan produk100

03.4000

ValidMissing

N

Mean

Kemudahan mendapatkan produk

9 9.0 9.0 9.020 20.0 20.0 29.014 14.0 14.0 43.0

36 36.0 36.0 79.021 21.0 21.0 100.0

100 100.0 100.0




ValidPercent

Cumulative Percent

87

Lampiran 5 : Frekuensi Jawaban Responden (sambungan) Tingkat Kepuasan untuk Promosi

Statistics

100 100 100 100 1000 0 0 0 0

3.4600 3.4600 3.4200 2.8700 3.4800

ValidMissing

N

Mean

Iklan TVmenarik Diskon

Demomasak

Adanyahot lineservice

Carapenanganan keluhan

Iklan TV menarik

9 9.0 9.0 9.019 19.0 19.0 28.0

14 14.0 14.0 42.033 33.0 33.0 75.025 25.0 25.0 100.0

100 100.0 100.0




ValidPercent

Cumulative Percent

Diskon

9 9.0 9.0 9.019 19.0 19.0 28.014 14.0 14.0 42.0

33 33.0 33.0 75.025 25.0 25.0 100.0

100 100.0 100.0




ValidPercent

Cumulative Percent

Demo masak

9 9.0 9.0 9.019 19.0 19.0 28.014 14.0 14.0 42.0

37 37.0 37.0 79.021 21.0 21.0 100.0

100 100.0 100.0




ValidPercent

Cumulative Percent

88

Lampiran 5 : Frekuensi Jawaban Responden (sambungan) Adanya hot line service

6 6.0 6.0 6.050 50.0 50.0 56.0

9 9.0 9.0 65.0

21 21.0 21.0 86.014 14.0 14.0 100.0

100 100.0 100.0




ValidPercent

Cumulative Percent

Cara penanganan keluhan

8 8.0 8.0 8.020 20.0 20.0 28.012 12.0 12.0 40.0

36 36.0 36.0 76.024 24.0 24.0 100.0

100 100.0 100.0




ValidPercent

Cumulative Percent

Kebutuhan Mencari Variasi

Statistics

100 100 100 100 100 1000 0 0 0 0 0

4.0800 3.9100 3.9600 4.0600 3.9500 3.9600

ValidMissing

N

Mean

E1 E2 E3 E4 E5 E6

89

Lampiran 5 : Frekuensi Jawaban Responden (sambungan) E1

6 6.0 6.0 6.02 2.0 2.0 8.0

70 70.0 70.0 78.022 22.0 22.0 100.0

100 100.0 100.0

Tidak setujuAntara setuju dan tidak

SetujuSangat setujuTotal


ValidPercent

Cumulative Percent

E2

10 10.0 10.0 10.01 1.0 1.0 11.0

77 77.0 77.0 88.012 12.0 12.0 100.0

100 100.0 100.0

Tidak setujuantara setuju dan tidak



ValidPercent

Cumulative Percent

E3

9 9.0 9.0 9.02 2.0 2.0 11.0

73 73.0 73.0 84.016 16.0 16.0 100.0

100 100.0 100.0

Tidak setujuAntara setuju dan tidak



ValidPercent

Cumulative Percent

E4

8 8.0 8.0 8.0

70 70.0 70.0 78.022 22.0 22.0 100.0

100 100.0 100.0

Tidak setuju



ValidPercent

Cumulative Percent

E5

1 1.0 1.0 1.012 12.0 12.0 13.0

65 65.0 65.0 78.022 22.0 22.0 100.0

100 100.0 100.0

Sangat tidak setujuTidak setuju



ValidPercent

Cumulative Percent

90

Lampiran 5 : Frekuensi Jawaban Responden (sambungan)

E6

10 10.0 10.0 10.0

74 74.0 74.0 84.016 16.0 16.0 100.0

100 100.0 100.0

Tidak setuju

SetujuSangat tidak setujuTotal


ValidPercent

Cumulative Percent

Keputusan Perpindahan Merek

Keputusan perpindahan merek

37 37.0 37.0 37.063 63.0 63.0 100.0

100 100.0 100.0

TidakYaTotal


ValidPercent

Cumulative Percent

91

Lampiran 6 : Analisa Regresi Logistik Logistic Regression 1 Total number of cases: 100 (Unweighted) Number of selected cases: 100 Number of unselected cases: 0 Number of selected cases: 100 Number rejected because of missing data: 0 Number of cases included in the analysis: 100 Dependent Variable Encoding: Original Internal Value Value .00 0 1.00 1 Dependent Variable.. PINDAH Keputusan perpindahan merek Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 131.79114 * Constant is included in the model. Beginning Block Number 1. Method: Enter Variable(s) Entered on Step Number 1.. KEPUASAN VARIASI Estimation terminated at iteration number 3 because Log Likelihood decreased by less than .01 percent. -2 Log Likelihood 114.086 Goodness of Fit 103.118 Cox & Snell - R^2 .162 Nagelkerke - R^2 .222 Chi-Square df Significance Model 17.705 2 .0001 Block 17.705 2 .0001 Step 17.705 2 .0001 ---------- Hosmer and Lemeshow Goodness-of-Fit Test----------- PINDAH = Tidak PINDAH = Ya Group Observed Expected Observed Expected Total 1 7.000 7.731 3.000 2.269 10.000 2 8.000 5.922 2.000 4.078 10.000 3 6.000 4.963 4.000 5.037 10.000 4 5.000 4.568 6.000 6.432 11.000 5 3.000 3.842 8.000 7.158 11.000 6 1.000 2.981 9.000 7.019 10.000 7 1.000 2.527 9.000 7.473 10.000

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Lampiran 6 : Analisa Regresi Logistik (sambungan) 8 1.000 2.119 9.000 7.881 10.000 9 4.000 1.525 6.000 8.475 10.000 10 1.000 .823 7.000 7.177 8.000 Chi-Square df Significance Goodness-of-fit test 11.5176 8 .1741 -------------------------------------------------------------- Classification Table for PINDAH The Cut Value is .50 Predicted Tidak Ya Percent Correct T ? Y Observed ????????????????? Tidak T ? 17 ? 20 ? 45.95% ????????????????? Ya Y ? 8 ? 55 ? 87.30% ????????????????? Overall 72.00% ----------------- Variables in the Equation ------------------ Variable B S.E. Wald df Sig R Exp(B) KEPUASAN .3587 .2868 1.5645 1 .2110 .0000 1.4315 VARIASI 2.2364 .6324 12.5041 1 .0004 .2823 9.3592 Constant -9.5232 2.7761 11.7676 1 .0006

Logistic Regression 2 Total number of cases: 100 (Unweighted) Number of selected cases: 100 Number of unselected cases: 0 Number of selected cases: 100 Number rejected because of missing data: 0 Number of cases included in the analysis: 100 Dependent Variable Encoding: Original Internal Value Value .00 0 1.00 1 Dependent Variable.. PINDAH Keputusan perpindahan merek Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 131.79114 * Constant is included in the model. Beginning Block Number 1. Method: Enter Lampiran 6 : Analisa Regresi Logistik (sambungan)

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Variable(s) Entered on Step Number 1.. VARIASI Estimation terminated at iteration number 3 because Log Likelihood decreased by less than .01 percent. -2 Log Likelihood 115.669 Goodness of Fit 103.579 Cox & Snell - R^2 .149 Nagelkerke - R^2 .203 Chi-Square df Significance Model 16.122 1 .0001 Block 16.122 1 .0001 Step 16.122 1 .0001 ---------- Hosmer and Lemeshow Goodness-of-Fit Test----------- PINDAH = Tidak PINDAH = Ya Group Observed Expected Observed Expected Total 1 8.000 8.294 3.000 2.706 11.000 2 11.000 8.054 4.000 6.946 15.000 3 7.000 6.566 8.000 8.434 15.000 4 1.000 3.842 10.000 7.158 11.000 5 3.000 6.214 20.000 16.786 23.000 6 3.000 1.862 6.000 7.138 9.000 7 3.000 1.677 8.000 9.323 11.000 8 1.000 .492 4.000 4.508 5.000 Chi-Square df Significance Goodness-of-fit test 10.6186 6 .1009 -------------------------------------------------------------- Classification Table for PINDAH The Cut Value is .50 Predicted Tidak Ya Percent Correct T ? Y Observed ????????????????? Tidak T ? 19 ? 18 ? 51.35% ????????????????? Ya Y ? 7 ? 56 ? 88.89% ????????????????? Overall 75.00% ----------------- Variables in the Equation ------------------ Variable B S.E. Wald df Sig R Exp(B) VARIASI 2.1863 .6258 12.2049 1 .0005 .2783 8.9023 Constant -8.1231 2.4791 10.7366 1 .0011 Lampiran 6 : Analisa Regresi Logistik (sambungan)

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Logistic Regression untuk perpindahan merek terhadap kepuasan untuk atribut produk Total number of cases: 100 (Unweighted) Number of selected cases: 100 Number of unselected cases: 0 Number of selected cases: 100 Number rejected because of missing data: 0 Number of cases included in the analysis: 100 Dependent Variable Encoding: Original Internal Value Value .00 0 1.00 1 Dependent Variable.. PINDAH Keputusan perpindahan merek Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 131.79114 * Constant is included in the model. Beginning Block Number 1. Method: Enter Variable(s) Entered on Step Number 1.. P1 Desain Kemasan P2 Informasi pada label P3 Komposisi P4 Aroma kecap manis P5 Rasa kecap P6 Kekentalan Estimation terminated at iteration number 8 because Log Likelihood decreased by less than .01 percent. -2 Log Likelihood 115.008 Goodness of Fit 89.051 Cox & Snell - R^2 .154 Nagelkerke - R^2 .211 Chi-Square df Significance Model 16.783 6 .0101 Block 16.783 6 .0101 Step 16.783 6 .0101 Classification Table for PINDAH The Cut Value is .50 Lampiran 6 : Analisa Regresi Logistik (sambungan)

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Predicted Tidak Ya Percent Correct T ? Y Observed ????????????????? Tidak T ? 5 ? 32 ? 13.51% ????????????????? Ya Y ? 2 ? 61 ? 96.83% ????????????????? Overall 66.00% ------------------ Variables in the Equation -------------------- Variable B S.E. Wald df Sig R Exp(B) P1 -7.3360 21.9306 .1119 1 .7380 .0000 .0007 P2 .0053 .6611 .0001 1 .9937 .0000 1.0053 P3 7.2634 21.9290 .1097 1 .7405 .0000 1427.1508 P4 -.1445 .2141 .4552 1 .4999 .0000 .8655 P5 .5048 .6682 .5707 1 .4500 .0000 1.6566 P6 -.3959 .2788 2.0163 1 .1556 -.0111 .6731 Constant .4675 .7702 .3684 1 .5439

Logistic Regression untuk perpindahan merek terhadap kepuasan untuk atribut harga Total number of cases: 100 (Unweighted) Number of selected cases: 100 Number of unselected cases: 0 Number of selected cases: 100 Number rejected because of missing data: 0 Number of cases included in the analysis: 100 Dependent Variable Encoding: Original Internal Value Value .00 0 1.00 1 Dependent Variable.. PINDAH Keputusan perpindahan merek Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 131.79114 * Constant is included in the model. Beginning Block Number 1. Method: Enter Lampiran 6 : Analisa Regresi Logistik (sambungan) Variable(s) Entered on Step Number

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1.. H1 Harga lebih terjangkau H2 Harga bersaing Estimation terminated at iteration number 3 because Log Likelihood decreased by less than .01 percent. -2 Log Likelihood 121.599 Goodness of Fit 101.165 Cox & Snell - R^2 .097 Nagelkerke - R^2 .132 Chi-Square df Significance Model 10.192 2 .0061 Block 10.192 2 .0061 Step 10.192 2 .0061 ---------- Hosmer and Lemeshow Goodness-of-Fit Test----------- PINDAH = Tidak PINDAH = Ya Group Observed Expected Observed Expected Total 1 10.000 9.852 5.000 5.148 15.000 2 5.000 4.954 5.000 5.046 10.000 3 6.000 4.943 5.000 6.057 11.000 4 10.000 9.898 21.000 21.102 31.000 5 .000 2.425 8.000 5.575 8.000 6 1.000 1.312 5.000 4.688 6.000 7 1.000 1.959 9.000 8.041 10.000 8 4.000 1.658 5.000 7.342 9.000 Chi-Square df Significance Goodness-of-fit test 8.6317 6 .1954 -------------------------------------------------------------- Classification Table for PINDAH The Cut Value is .50 Predicted Tidak Ya Percent Correct T ? Y Observed ????????????????? Tidak T ? 10 ? 27 ? 27.03% ????????????????? Ya Y ? 6 ? 57 ? 90.48% ????????????????? Overall 67.00% Lampiran 6 : Analisa Regresi Logistik (sambungan) -------------------- Variables in the Equation -------------------

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Variable B S.E. Wald df Sig R Exp(B) H1 .0756 .3043 .0618 1 .8037 .0000 1.0786 H2 .6553 .2623 6.2409 1 .0125 .1794 1.9256 Constant -2.1665 1.0687 4.1096 1 .0426 Logistic Regression untuk perpindahan merek terhadap kepuasan untuk atribut distribusi Total number of cases: 100 (Unweighted) Number of selected cases: 100 Number of unselected cases: 0 Number of selected cases: 100 Number rejected because of missing data: 0 Number of cases included in the analysis: 100 Dependent Variable Encoding: Original Internal Value Value .00 0 1.00 1 Dependent Variable.. PINDAH Keputusan perpindahan merek Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 131.79114 * Constant is included in the model. Beginning Block Number 1. Method: Enter Variable(s) Entered on Step Number 1.. D Kemudahan mendapatkan produk Estimation terminated at iteration number 2 because Log Likelihood decreased by less than .01 percent. -2 Log Likelihood 131.752 Goodness of Fit 99.986 Cox & Snell - R^2 .000 Nagelkerke - R^2 .001 Chi-Square df Significance Model .039 1 .8441 Block .039 1 .8441 Step .039 1 .8441 Lampiran 6 : Analisa Regresi Logistik (sambungan) ---------- Hosmer and Lemeshow Goodness-of-Fit Test-----------

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PINDAH = Tidak PINDAH = Ya Group Observed Expected Observed Expected Total 1 4.000 8.023 17.000 12.977 21.000 2 17.000 13.481 19.000 22.519 36.000 3 7.000 5.137 7.000 8.863 14.000 4 9.000 7.190 11.000 12.810 20.000 5 .000 3.169 9.000 5.831 9.000 Chi-Square df Significance Goodness-of-fit test 11.4026 3 .0097 -------------------------------------------------------------- Classification Table for PINDAH The Cut Value is .50 Predicted Tidak Ya Percent Correct T ? Y Observed ????????????????? Tidak T ? 0 ? 37 ? .00% ????????????????? Ya Y ? 0 ? 63 ? 100.00% ????????????????? Overall 63.00% ------------------ Variables in the Equation ------------------- Variable B S.E. Wald df Sig R Exp(B) D -.0322 .1642 .0386 1 .8443 .0000 .9683 Constant .6421 .5975 1.1546 1 .2826 Logistic Regression untuk perpindahan merek terhadap kepuasan untuk atribut promosi Total number of cases: 100 (Unweighted) Number of selected cases: 100 Number of unselected cases: 0 Number of selected cases: 100 Number rejected because of missing data: 0 Number of cases included in the analysis: 100 Dependent Variable Encoding: Original Internal Value Value .00 0 1.00 1 Lampiran 6 : Analisa Regresi Logistik (sambungan) Dependent Variable.. PINDAH Keputusan perpindahan merek Beginning Block Number 0. Initial Log Likelihood Function

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-2 Log Likelihood 131.79114 * Constant is included in the model. Beginning Block Number 1. Method: Enter Redundancies in Design Matrix: PM2 = PM1 Variable(s) Entered on Step Number 1.. PM1 Iklan TV menarik PM3 Demo masak PM4 Adanya hot line service PM5 Cara penanganan keluhan Estimation terminated at iteration number 3 because Log Likelihood decreased by less than .01 percent. -2 Log Likelihood 120.753 Goodness of Fit 96.788 Cox & Snell - R^2 .105 Nagelkerke - R^2 .143 Chi-Square df Significance Model 11.039 4 .0261 Block 11.039 4 .0261 Step 11.039 4 .0261 ---------- Hosmer and Lemeshow Goodness-of-Fit Test----------- PINDAH = Tidak PINDAH = Ya Group Observed Expected Observed Expected Total 1 4.000 6.276 6.000 3.724 10.000 2 8.000 6.575 4.000 5.425 12.000 3 5.000 5.070 5.000 4.930 10.000 4 2.000 3.117 5.000 3.883 7.000 5 9.000 5.985 7.000 10.015 16.000 6 3.000 3.171 7.000 6.829 10.000 7 4.000 3.474 11.000 11.526 15.000 8 2.000 2.524 12.000 11.476 14.000 9 .000 .808 6.000 5.192 6.000 Chi-Square df Significance Goodness-of-fit test 7.2340 7 .4049 Lampiran 6 : Analisa Regresi Logistik (sambungan) -------------------------------------------------------------- Classification Table for PINDAH The Cut Value is .50 Predicted

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Tidak Ya Percent Correct T ? Y Observed ????????????????? Tidak T ? 15 ? 22 ? 40.54% ????????????????? Ya Y ? 13 ? 50 ? 79.37% ????????????????? Overall 65.00% ------------------- Variables in the Equation ------------------- Variable B S.E. Wald df Sig R Exp(B) PM1 .7550 .7337 1.0589 1 .3035 .0000 2.1276 PM3 -.1902 .3050 .3891 1 .5328 .0000 .8268 PM4 .6985 .2442 8.1832 1 .0042 .2166 2.0107 PM5 -.9145 .7379 1.5358 1 .2152 .0000 .4007 Constant -.1828 .6748 .0734 1 .7865

Logistic Regression untuk perpindahan merek terhadap kebutuhan mencari variasi Total number of cases: 100 (Unweighted) Number of selected cases: 100 Number of unselected cases: 0 Number of selected cases: 100 Number rejected because of missing data: 0 Number of cases included in the analysis: 100 Dependent Variable Encoding: Original Internal Value Value .00 0 1.00 1 Dependent Variable.. PINDAH Keputusan perpindahan merek Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 131.79114 * Constant is included in the model. Beginning Block Number 1. Method: Enter Lampiran 6 : Analisa Regresi Logistik (sambungan) Variable(s) Entered on Step Number 1.. E1 E2 E3 E4 E5 E6

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Estimation terminated at iteration number 3 because Log Likelihood decreased by less than .01 percent. -2 Log Likelihood 114.109 Goodness of Fit 103.125 Cox & Snell - R^2 .162 Nagelkerke - R^2 .221 Chi-Square df Significance Model 17.682 6 .0071 Block 17.682 6 .0071 Step 17.682 6 .0071 ---------- Hosmer and Lemeshow Goodness-of-Fit Test----------- PINDAH = Tidak PINDAH = Ya Group Observed Expected Observed Expected Total 1 8.000 7.877 2.000 2.123 10.000 2 7.000 5.977 3.000 4.023 10.000 3 4.000 4.859 6.000 5.141 10.000 4 7.000 3.947 3.000 6.053 10.000 5 1.000 3.824 10.000 7.176 11.000 6 1.000 3.302 10.000 7.698 11.000 7 1.000 2.543 9.000 7.457 10.000 8 4.000 2.328 7.000 8.672 11.000 9 3.000 1.624 7.000 8.376 10.000 10 1.000 .718 6.000 6.282 7.000 Chi-Square df Significance Goodness-of-fit test 14.4223 8 .0714 -------------------------------------------------------------- Classification Table for PINDAH The Cut Value is .50 Predicted Tidak Ya Percent Correct T ? Y Observed ????????????????? Tidak T ? 16 ? 21 ? 43.24% ????????????????? Ya Y ? 7 ? 56 ? 88.89% ????????????????? Overall 72.00% Lampiran 6 : Analisa Regresi Logistik (sambungan) ------------------- Variables in the Equation -------------------- Variable B S.E. Wald df Sig R Exp(B) E1 .2779 .3524 .6216 1 .4305 .0000 1.3203 E2 .2974 .3208 .8594 1 .3539 .0000 1.3463 E3 .1470 .3357 .1918 1 .6614 .0000 1.1584

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E4 .3724 .3776 .9730 1 .3239 .0000 1.4513 E5 .5230 .2863 3.3370 1 .0677 .1007 1.6871 E6 .5713 .3400 2.8237 1 .0929 .0791 1.7705 Constant -8.1265 2.5957 9.8014 1 .0017 Logistic Regression untuk perpindahan merek terhadap Ketidakpuasan Total number of cases: 100 (Unweighted) Number of selected cases: 100 Number of unselected cases: 0 Number of selected cases: 100 Number rejected because of missing data: 0 Number of cases included in the analysis: 100 Dependent Variable Encoding: Original Internal Value Value .00 0 1.00 1 Parameter Value Freq Coding (1) (2) (3) (4) PM5 Sangat tidak puas 1.00 8 1.000 .000 .000 .000 Kurang puas 2.00 20 .000 1.000 .000 .000 Cukup puas 3.00 12 .000 .000 1.000 .000 Puas 4.00 36 .000 .000 .000 1.000 Sangat puas 5.00 24 .000 .000 .000 .000 P2 Sangat tidak puas 1.00 9 1.000 .000 .000 .000 Kurang puas 2.00 28 .000 1.000 .000 .000 Cukup puas 3.00 1 .000 .000 1.000 .000 Puas 4.00 37 .000 .000 .000 1.000 Sangat puas 5.00 25 .000 .000 .000 .000 P3 Sangat tidak puas 1.00 5 1.000 .000 .000 .000 Kurang puas 2.00 43 .000 1.000 .000 .000 Cukup puas 3.00 15 .000 .000 1.000 .000 Puas 4.00 28 .000 .000 .000 1.000 Sangat puas 5.00 9 .000 .000 .000 .000 P4 Sangat tidak puas 1.00 19 1.000 .000 .000 .000 Kurang puas 2.00 40 .000 1.000 .000 .000 Lampiran 6 : Analisa Regresi Logistik (sambungan) Cukup puas 3.00 2 .000 .000 1.000 .000 Puas 4.00 23 .000 .000 .000 1.000 Sangat puas 5.00 16 .000 .000 .000 .000 P5 Sangat tidak puas 1.00 9 1.000 .000 .000 .000 Kurang puas 2.00 19 .000 1.000 .000 .000 Cukup puas 3.00 14 .000 .000 1.000 .000

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Puas 4.00 33 .000 .000 .000 1.000 Sangat puas 5.00 25 .000 .000 .000 .000 P6 Sangat tidak puas 1.00 15 1.000 .000 .000 .000 Kurang puas 2.00 45 .000 1.000 .000 .000 Cukup puas 3.00 3 .000 .000 1.000 .000 Puas 4.00 35 .000 .000 .000 1.000 Sangat puas 5.00 2 .000 .000 .000 .000 P1 Sangat tidak puas 1.00 7 1.000 .000 .000 .000 Kurang puas 2.00 42 .000 1.000 .000 .000 Cukup puas 3.00 15 .000 .000 1.000 .000 Puas 4.00 27 .000 .000 .000 1.000 Sangat puas 5.00 9 .000 .000 .000 .000 PM2 Sangat tidak puas 1.00 9 1.000 .000 .000 .000 Kurang puas 2.00 19 .000 1.000 .000 .000 Cukup puas 3.00 14 .000 .000 1.000 .000 Puas 4.00 33 .000 .000 .000 1.000 Sangat puas 5.00 25 .000 .000 .000 .000 Parameter Value Freq Coding (1) (2) (3) (4) D Sangat tidak puas 1.00 9 1.000 .000 .000 .000 Kurang puas 2.00 20 .000 1.000 .000 .000 Cukup puas 3.00 14 .000 .000 1.000 .000 Puas 4.00 36 .000 .000 .000 1.000 Sangat puas 5.00 21 .000 .000 .000 .000 PM1 Sangat tidak puas 1.00 9 1.000 .000 .000 .000 Kurang puas 2.00 19 .000 1.000 .000 .000 Cukup puas 3.00 14 .000 .000 1.000 .000 Puas 4.00 33 .000 .000 .000 1.000 Sangat puas 5.00 25 .000 .000 .000 .000 PM4 Sangat tidak puas 1.00 6 1.000 .000 .000 .000 Kurang puas 2.00 50 .000 1.000 .000 .000 Cukup puas 3.00 9 .000 .000 1.000 .000 Puas 4.00 21 .000 .000 .000 1.000 Sangat puas 5.00 14 .000 .000 .000 .000 PM3 Sangat tidak puas 1.00 9 1.000 .000 .000 .000 Kurang puas 2.00 19 .000 1.000 .000 .000 Cukup puas 3.00 14 .000 .000 1.000 .000 Puas 4.00 37 .000 .000 .000 1.000 Sangat puas 5.00 21 .000 .000 .000 .000 Lampiran 6 : Analisa Regresi Logistik (sambungan) H2 Kurang puas 2.00 15 1.000 .000 .000 Cukup puas 3.00 19 .000 1.000 .000 Puas 4.00 41 .000 .000 1.000 Sangat puas 5.00 25 .000 .000 .000 H1 Kurang puas 2.00 10 1.000 .000 .000

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Cukup puas 3.00 23 .000 1.000 .000 Puas 4.00 50 .000 .000 1.000 Sangat puas 5.00 17 .000 .000 .000 Dependent Variable.. PINDAH Keputusan perpindahan merek Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 131.79114 * Constant is included in the model. Beginning Block Number 1. Method: Enter Redundancies in Design Matrix: P3(3) = P1(3) The variable P3 will have its degrees of freedom reduced from 4 to 3 P3(4) = P1(1) + P1(2) + P1(4) - P3(1) - P3(2) The variable P3 will have its degrees of freedom reduced from 3 to 2 P5(1) = P2(1) The variable P5 will have its degrees of freedom reduced from 4 to 3 P5(4) = P2(2) + P2(3) + P2(4) - P5(2) - P5(3) The variable P5 will have its degrees of freedom reduced from 3 to 2 PM1(1) = P2(1) The variable PM1 will have its degrees of freedom reduced from 4 to 3 PM1(2) = P5(2) The variable PM1 will have its degrees of freedom reduced from 3 to 2 PM1(3) = P5(3) The variable PM1 will have its degrees of freedom reduced from 2 to 1 PM1(4) = P2(2) + P2(3) + P2(4) - P5(2) - P5(3) The variable PM1 will have its degrees of freedom reduced from 1 to 0 Lampiran 6 : Analisa Regresi Logistik (sambungan) PM2(1) = P2(1) The variable PM2 will have its degrees of freedom reduced from 4 to 3 PM2(2) = P5(2) The variable PM2 will have its degrees of freedom reduced from 3 to 2

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PM2(3) = P5(3) The variable PM2 will have its degrees of freedom reduced from 2 to 1 PM2(4) = P2(2) + P2(3) + P2(4) - P5(2) - P5(3) The variable PM2 will have its degrees of freedom reduced from 1 to 0 PM3(1) = D(1) The variable PM3 will have its degrees of freedom reduced from 4 to 3 PM3(3) = D(3) The variable PM3 will have its degrees of freedom reduced from 3 to 2 PM3(4) = D(2) + D(4) - PM3(2) The variable PM3 will have its degrees of freedom reduced from 2 to 1 Variable(s) Entered on Step Number 1.. P1 Desain Kemasan P2 Informasi pada label P3 Komposisi P4 Aroma kecap manis P5 Rasa kecap P6 Kekentalan H1 Harga lebih terjangkau H2 Harga bersaing D Kemudahan mendapatkan produk PM3 Demo masak PM4 Adanya hot line service PM5 Cara penanganan keluhan Estimation terminated at iteration number 13 because Log Likelihood decreased by less than .01 percent. Iteration History: Iteration Log Likelihood Constant P1(1) P1(2) P1(3) 1 -36.549997 1.517090 1.768175 .690226 -2.242070 2 -28.211850 2.332213 3.066299 1.743217 -4.337517 3 -24.170398 3.434709 4.556913 2.959963 -6.607273 4 -21.628809 4.614185 6.786004 4.618341 -9.891175 5 -19.965204 5.427767 9.094037 6.481317 -14.652302 6 -19.137066 6.124656 10.500251 7.894270 -20.680189 7 -18.807412 6.974042 12.330881 9.746885 -26.988135 8 -18.686080 7.934672 14.384682 11.804656 -33.108099 9 -18.641507 8.929581 16.434847 13.856024 -39.118204 Lampiran 6 : Analisa Regresi Logistik (sambungan) 10 -18.625084 9.929228 18.460155 15.881764 -45.114139 11 -18.619037 10.929274 20.470722 17.892489 -51.111587 12 -18.616812 11.929315 22.474807 19.896633 -57.110500 13 -18.615993 12.929333 24.476339 21.898186 -63.110078 P1(4) P2(1) P2(2) P2(3) P2(4) P3(1)

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-2.103533 -3.78145 -1.639001 .4682782 -2.760778 -3.007849 -3.607382 -6.83558 -3.984690 .7893315 -6.269415 -5.269690 -5.681789 -10.82489 -5.065141 2.2516528 -9.192624 -7.603778 -8.961855 -17.01896 -6.480453 2.5110857 -12.534586 -10.611082 -13.520657 -26.56788 -9.248607 1.9529401 -17.095657 -13.818109 -19.426730 -38.11017 -12.359591 1.6727176 -21.990875 -17.615349 -25.729049 -49.94297 -15.459247 1.4485540 -26.946197 -22.393299 -31.845953 -61.56338 -18.512317 1.3531692 -31.972540 -27.379437 -37.855603 -73.05929 -21.510158 1.3520704 -36.962077 -32.358246 -43.851463 -84.54565 -24.504306 1.3589297 -41.952617 -37.344899 -49.848898 -96.03889 -27.501450 1.3624056 -46.948277 -42.339143 -55.847809 -107.53615 -30.500298 1.3638179 -51.946552 -47.336902 -61.847387 -119.03510 -33.499860 1.3643563 -56.945899 -52.336059 P3(2) P3(3) P3(4) P4(1) P4(2) P4(3) P4(4) -1.505437 . . 1.677762 .433273 1.4790265 .721858 -4.023937 . . 3.666581 1.486197 1.9198103 1.989847 -6.923517 . . 5.821155 2.280695 2.1514147 3.261782 -10.877144 . . 9.827810 4.193629 2.8427510 5.735022 -15.264168 . . 17.453856 8.264086 3.3065854 10.677282 -19.637472 . . 27.055189 12.715806 3.3084811 16.421349 -24.651121 . . 36.526917 16.812260 3.2671609 21.719928 -29.769378 . . 45.676197 20.837427 3.2362333 26.805647 -34.828472 . . 54.684008 24.835096 3.2286862 31.807420 -39.853794 . . 63.675959 28.831331 3.2267217 36.801338 -44.863957 . . 72.671450 32.829492 3.2261575 41.798150 -49.867840 . . 81.669569 36.828747 3.2259777 46.796841 -54.869290 . . 90.668845 40.828463 3.2259157 51.796340 P5(1) P5(2) P5(3) P5(4) P6(1) P6(2) P6(3) . -.6337416 -2.498354 . 1.030172 1.075429 -.935581 . -.8740334 -4.785461 . 2.309017 2.740675 -.403186 . -1.4056006 -7.906747 . 4.251108 4.552524 .105977 . -2.0382719 -13.136544 . 7.355470 7.461553 2.827597 . -1.5988563 -20.717553 . 12.651565 12.744589 8.425754 . -.2294862 -28.882931 . 19.190233 19.201953 14.276745 . 1.1305396 -36.937970 . 25.683891 25.597736 19.670188 . 2.2458072 -44.982779 . 31.865505 31.757291 24.837384 . 3.2454660 -52.987009 . 37.886275 37.774986 29.856193 . 4.2360962 -60.984661 . 43.884063 43.772479 34.853803 . 5.2314193 -68.983176 . 49.881952 49.770337 39.851656 . 6.2295267 -76.982538 . 55.880996 55.769376 44.850686 . 7.2288062 -84.982289 . 61.880618 61.768999 49.850303 Lampiran 6 : Analisa Regresi Logistik (sambungan) P6(4) H1(1) H1(2) H1(3) H2(1) H2(2) 1.322251 .5088048 -.2351920 -.4592099 -1.537288 -.4140579 2.919953 .7455152 -.0840782 -.8450442 -2.973006 -.4772725 5.027052 .6346470 .3143314 -1.1205271 -5.209662 -.8648596 8.162970 .3303416 1.0040853 -1.1593528 -8.436475 -1.4467910 13.059989 .2450032 1.7131805 -1.0369952 -12.707551 -2.1782913 19.013878 .7210848 2.3638830 -1.0503864 -18.114325 -2.9861535

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25.260453 1.4722432 3.2044651 -1.1732755 -24.170169 -3.9065598 31.397565 2.3414716 4.1668246 -1.2242236 -30.234207 -4.8827571 37.412651 3.2626848 5.1559972 -1.2324285 -36.230493 -5.8735549 43.409937 4.2247268 6.1519129 -1.2334361 -42.221744 -6.8695575 49.407777 5.2090661 7.1503327 -1.2335724 -48.217442 -7.8679786 55.406814 6.2030337 8.1497364 -1.2335912 -54.215702 -8.8673820 61.406436 7.2007750 9.1495148 -1.2335938 -60.215039 -9.8671603 H2(3) D(1) D(2) D(3) D(4) PM3(1) .35088680 1.315370 2.308036 -.1065115 .52566606 . .56941732 2.693355 3.432056 -.1536320 .66727579 . .56293969 4.076165 4.381530 -.1949784 .78934922 . .50355874 4.825013 4.809791 -.8081198 .39595271 . .47417670 5.557322 5.261324 -1.5111799 -.34677648 . .63576008 7.692534 6.588492 -1.4039424 -.57165401 . .80897554 10.349030 7.879721 -1.2058457 -.53431786 . .86800610 12.903388 8.944964 -1.1635647 -.53342845 . .87720376 15.405123 9.955013 -1.1572545 -.53355793 . .87833361 17.901604 10.956393 -1.1564483 -.53365079 . .87848657 20.399738 11.956661 -1.1563383 -.53367078 . .87850772 22.898970 12.956732 -1.1563231 -.53367387 . .87851062 25.398677 13.956754 -1.1563210 -.53367431 . PM3(2) PM3(3) PM3(4) PM4(1) PM4(2) PM4(3) -2.652538 . . .5288439 -.708086 -.181035 -3.543063 . . .4492554 -1.744068 -.668038 -4.945570 . . .5971635 -2.855194 -1.104297 -6.991713 . . -.1229324 -5.219060 -2.031471 -10.858289 . . -1.6221895 -9.358046 -3.536739 -15.711912 . . -1.2867643 -13.569540 -4.863335 -20.165419 . . -.0507846 -17.611069 -5.919109 -24.285613 . . 1.0135409 -21.666277 -6.943074 -28.290714 . . 2.0193531 -25.670816 -7.948777 -32.284266 . . 3.0177765 -29.668422 -8.950337 -36.280808 . . 4.0167715 -33.666903 -9.950838 -40.279387 . . 5.0163495 -37.666246 -10.951011 -44.278844 . . 6.0161872 -41.665991 -11.951073 PM4(4) PM5(1) PM5(2) PM5(3) PM5(4) .888725 1.592499 1.145613 3.180622 1.050699 1.127330 2.926188 2.516495 6.660644 2.772163 1.366122 4.525593 3.762902 9.962231 3.857966 .314914 7.626817 6.060176 15.289250 5.890722 -2.111293 10.649855 8.242225 22.197780 8.213141 -3.756682 11.490400 9.006419 29.127153 9.367602 -4.742425 11.996328 9.716133 36.173976 10.235393 -5.747807 12.871917 10.661554 43.251634 11.232428 Lampiran 6 : Analisa Regresi Logistik (sambungan) -6.761382 13.852879 11.654012 50.257018 12.233664 -7.769112 14.850329 12.653168 57.252769 13.234186 -8.772293 15.849896 13.653070 64.250299 14.234360 -9.773507 16.849802 14.653060 71.249258 15.234419 -10.773960 17.849776 15.653060 78.248856 16.234440 -2 Log Likelihood 37.232

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Goodness of Fit 28.661 Cox & Snell - R^2 .612 Nagelkerke - R^2 .835 Chi-Square df Significance Model 94.559 39 .0000 Block 94.559 39 .0000 Step 94.559 39 .0000 ---------- Hosmer and Lemeshow Goodness-of-Fit Test----------- PINDAH = Tidak PINDAH = Ya Group Observed Expected Observed Expected Total 1 10.000 10.000 .000 .000 10.000 2 10.000 10.000 .000 .000 10.000 3 7.000 7.504 3.000 2.496 10.000 4 7.000 6.154 4.000 4.846 11.000 5 3.000 3.342 7.000 6.658 10.000 6 .000 .000 10.000 10.000 10.000 7 .000 .000 10.000 10.000 10.000 8 .000 .000 9.000 9.000 9.000 9 .000 .000 20.000 20.000 20.000 Chi-Square df Significance Goodness-of-fit test .4524 7 .9996 -------------------------------------------------------------- Classification Table for PINDAH The Cut Value is .50 Predicted Tidak Ya Percent Correct T ? Y Observed ????????????????? Tidak T ? 34 ? 3 ? 91.89% ????????????????? Ya Y ? 7 ? 56 ? 88.89% ????????????????? Overall 90.00% Lampiran 6 : Analisa Regresi Logistik (sambungan) ----------------- Variables in the Equation ------------------ Variable B S.E. Wald df Sig R P1 .8333 4 .9339 .0000 P1(1) 24.4763 1406.4728 .0003 1 .9861 .0000 P1(2) 21.8982 563.0278 .0015 1 .9690 .0000 P1(3) -63.1101 435.4963 .0210 1 .8848 .0000

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P1(4) -61.8474 435.4978 .0202 1 .8871 .0000 P2 .0023 4 1.0000 .0000 P2(1) -119.035 47453087 .0000 1 1.0000 .0000 P2(2) -33.4999 2066.8969 .0003 1 .9871 .0000 P2(3) 1.3644 2777.3718 .0000 1 1.0000 .0000 P2(4) -56.9459 1948.0512 .0009 1 .9767 .0000 P3 .0130 2 .9935 .0000 P3(1) -52.3361 1442.0403 .0013 1 .9710 .0000 P3(2) -54.8693 482.8355 .0129 1 .9095 .0000 P4 .0399 4 .9998 .0000 P4(1) 90.6688 497.9797 .0332 1 .8555 .0000 P4(2) 40.8285 326.7758 .0156 1 .9006 .0000 P4(3) 3.2259 1231.8582 .0000 1 .9979 .0000 P4(4) 51.7963 353.4924 .0215 1 .8835 .0000 P5 .0106 2 .9947 .0000 P5(2) 7.2288 2215.0001 .0000 1 .9974 .0000 P5(3) -84.9823 852.2737 .0099 1 .9206 .0000 P6 .0199 4 1.0000 .0000 P6(1) 61.8806 970.1987 .0041 1 .9491 .0000 P6(2) 61.7690 970.1940 .0041 1 .9492 .0000 P6(3) 49.8503 1197.7312 .0017 1 .9668 .0000 P6(4) 61.4064 970.1935 .0040 1 .9495 .0000 H1 .5739 3 .9024 .0000 H1(1) 7.2008 328.2067 .0005 1 .9825 .0000 H1(2) 9.1495 77.8083 .0138 1 .9064 .0000 H1(3) -1.2336 1.6494 .5594 1 .4545 .0000 H2 .3579 3 .9488 .0000 H2(1) -60.2150 314.1695 .0367 1 .8480 .0000 H2(2) -9.8672 77.8120 .0161 1 .8991 .0000 H2(3) .8785 1.5466 .3227 1 .5700 .0000 D .2002 4 .9953 .0000 D(1) 25.3987 47453086 .0000 1 1.0000 .0000 D(2) 13.9568 878.7533 .0003 1 .9873 .0000 D(3) -1.1563 2.8279 .1672 1 .6826 .0000 D(4) -.5337 2.6076 .0419 1 .8378 .0000 PM3 .0007 1 .9794 .0000 PM3(2) -44.2788 1718.0186 .0007 1 .9794 .0000 PM4 .0371 4 .9998 .0000 PM4(1) 6.0162 1115.7377 .0000 1 .9957 .0000 PM4(2) -41.6660 272.6152 .0234 1 .8785 .0000 PM4(3) -11.9511 210.5814 .0032 1 .9547 .0000 PM4(4) -10.7740 253.3953 .0018 1 .9661 .0000 PM5 .0205 4 .9999 .0000 PM5(1) 17.8498 2379.9909 .0001 1 .9940 .0000 PM5(2) 15.6531 1213.7304 .0002 1 .9897 .0000 PM5(3) 78.2489 1993.2466 .0015 1 .9687 .0000 PM5(4) 16.2344 1928.3334 .0001 1 .9933 .0000 Constant 12.9293 878.7486 .0002 1 .9883 Lampiran 6 : Analisa Regresi Logistik (sambungan) 95% CI for Exp(B) Variable Exp(B) Lower Upper P1(1) 4.265E+10 .0000 . P1(2) 3.238E+09 .0000 . P1(3) .0000 .0000 . P1(4) .0000 .0000 . P2(1) .0000 .0000 .

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P2(2) .0000 .0000 . P2(3) 3.9132 .0000 . P2(4) .0000 .0000 . P3(1) .0000 .0000 . P3(2) .0000 .0000 . P4(1) 2.382E+39 .0000 . P4(2) 5.390E+17 .0000 7.650+295 P4(3) 25.1766 .0000 . P4(4) 3.125E+22 .0000 . P5(2) 1378.5758 .0000 . P5(3) .0000 .0000 . P6(1) 7.489E+26 .0000 . P6(2) 6.698E+26 .0000 . P6(3) 4.464E+21 .0000 . P6(4) 4.661E+26 .0000 . H1(1) 1340.4692 .0000 3.143+282 H1(2) 9409.8732 .0000 1.600E+70 H1(3) .2912 .0115 7.3828 H2(1) .0000 .0000 1.864+241 H2(2) .0001 .0000 8.881E+61 H2(3) 2.4073 .1162 49.8880 D(1) 1.073E+11 .0000 . D(2) 1151705.2 .0000 . D(3) .3146 .0012 80.3464 D(4) .5864 .0035 97.2275 PM3(2) .0000 .0000 . PM4(1) 410.0123 .0000 . PM4(2) .0000 .0000 9.020+213 PM4(3) .0000 .0000 1.140+174 PM4(4) .0000 .0000 1.027+211 PM5(1) 56501421 .0000 . PM5(2) 6281126.9 .0000 . PM5(3) 9.617E+33 .0000 . PM5(4) 11233827 .0000 . Correlation Matrix: Constant P1(1) P1(2) P1(3) P1(4) P2(1) P2(2) Constant 1.00000 -.02260 -.05646 -.08481 -.08482 .00000 .13077 P1(1) -.02260 1.00000 .40031 .17904 .17904 -.00002 .00828 P1(2) -.05646 .40031 1.00000 .44726 .44726 .00000 .02069 P1(3) -.08481 .17904 .44726 1.00000 .99999 .00001 .06359 P1(4) -.08482 .17904 .44726 .99999 1.00000 .00001 .06359 P2(1) .00000 -.00002 .00000 .00001 .00001 1.00000 .00002 P2(2) .13077 .00828 .02069 .06359 .06359 .00002 1.00000 P2(3) .09021 .00560 .01399 .04521 .04521 .00001 .73383 P2(4) .13875 .00657 .01642 .08173 .08173 .00002 .93949 P3(1) -.00357 -.87610 -.14256 .10536 .10536 .00003 .01112 Lampiran 6 : Analisa Regresi Logistik (sambungan) P3(2) -.01067 -.29638 -.74038 .20913 .20913 .00000 .01704 P3(3) . . . . . . . P3(4) . . . . . . . P4(1) -.02931 .02364 .05905 -.49083 -.49082 -.00001 -.09982 P4(2) -.06041 .00840 .02099 -.27105 -.27104 -.00001 -.11198 P4(3) .00000 .00000 .00000 .00000 -.00001 .00000 .00000 P4(4) -.05586 .01995 .04983 -.32926 -.32925 -.00001 -.11181 P5(1) . . . . . . .

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P5(2) -.11312 .52814 -.01269 -.06925 -.06925 -.00002 -.59970 P5(3) -.04334 .09148 .22852 .54812 .54812 .00000 -.24869 P5(4) . . . . . . . P6(1) -.86767 -.05990 -.14963 -.37206 -.37206 .00000 -.14699 P6(2) -.86767 -.05990 -.14962 -.37205 -.37205 .00000 -.14699 P6(3) -.70284 -.04852 -.12120 -.30137 -.30137 .00000 -.11907 P6(4) -.86767 -.05989 -.14962 -.37204 -.37203 .00000 -.14699 H1(1) -.00001 -.18528 -.46284 -.15527 -.15527 .00000 -.02381 H1(2) -.00001 .05539 .13836 -.35720 -.35719 -.00001 -.03763 H1(3) .00034 -.00030 -.00074 .00360 .00362 .00000 .00075 H2(1) -.01639 -.04245 -.10604 .58451 .58451 .00001 .05106 H2(2) .00000 -.05537 -.13831 .35728 .35729 .00001 .03763 H2(3) -.00120 -.00008 -.00019 -.00623 -.00616 .00000 -.00108 D(1) .00000 .00000 .00000 .00000 .00000 -1.00000 .00000 D(2) -.28512 -.02260 -.05646 -.08484 -.08484 .00000 -.41560 D(3) -.00050 -.00069 -.00173 -.00273 -.00324 .00000 .00057 D(4) -.00044 .00010 .00024 -.00015 -.00098 .00000 .00101 PM3(1) . . . . . . . PM3(2) .14584 -.68092 .01635 .10773 .10773 .00002 .21884 PM3(3) . . . . . . . PM3(4) . . . . . . . PM4(1) .00462 -.07047 .01055 -.06556 -.06557 .00000 -.00474 PM4(2) .00001 -.01582 -.03951 .30334 .30331 .00001 .02870 PM4(3) .00000 .00001 .00001 .00004 .00002 .00000 .00001 PM4(4) -.00001 .01700 .04246 .01530 .01527 .00000 -.01154 PM5(1) .00000 .49626 .00000 .00001 .00001 -.00004 -.29946 PM5(2) .00000 .00000 .00001 .00001 .00002 -.00003 -.58722 PM5(3) -.10717 -.04908 -.12260 -.25587 -.25586 -.00002 -.91226 PM5(4) -.12993 -.01030 -.02572 -.03865 -.03865 -.00002 -.92861 P2(3) P2(4) P3(1) P3(2) P3(3) P3(4) P4(1) Constant .09021 .13875 -.00357 -.01067 . . -.02931 P1(1) .00560 .00657 -.87610 -.29638 . . .02364 P1(2) .01399 .01642 -.14256 -.74038 . . .05905 P1(3) .04521 .08173 .10536 .20913 . . -.49083 P1(4) .04521 .08173 .10536 .20913 . . -.49082 P2(1) .00001 .00002 .00003 .00000 . . -.00001 P2(2) .73383 .93949 .01112 .01704 . . -.09982 P2(3) 1.00000 .68817 .00819 .01241 . . -.01849 P2(4) .68817 1.00000 .01826 .03095 . . -.12462 P3(1) .00819 .01826 1.00000 .22067 . . -.13279 P3(2) .01241 .03095 .22067 1.00000 . . -.23714 P3(3) . . . . . . . P3(4) . . . . . . . P4(1) -.01849 -.12462 -.13279 -.23714 . . 1.00000 P4(2) .00129 -.12832 -.06072 -.07904 . . .87974 P4(3) -.44353 .00000 .00000 -.00001 . . .00001 P4(4) -.00498 -.13621 -.09177 -.14405 . . .91648 Lampiran 6 : Analisa Regresi Logistik (sambungan) P5(1) . . . . . . . P5(2) -.44911 -.52430 -.53602 -.02689 . . .03966 P5(3) -.18615 .04177 .05383 .10685 . . -.31581 P5(4) . . . . . . . P6(1) -.08555 -.16236 -.04406 -.08421 . . .24687 P6(2) -.08555 -.16236 -.04406 -.08420 . . .24686 P6(3) -.21758 -.13152 -.03568 -.06821 . . .19997 P6(4) -.08555 -.16236 -.04406 -.08420 . . .24683

112

H1(1) -.01772 -.03471 -.05965 .50157 . . .23459 H1(2) -.02800 -.07986 -.16183 -.32244 . . .46856 H1(3) .00093 .00096 .00137 .00240 . . -.00180 H2(1) .03759 .08384 .18740 .37353 . . -.78600 H2(2) .02800 .07984 .16183 .32244 . . -.46865 H2(3) -.00124 -.00106 -.00181 -.00241 . . .00631 D(1) .00000 .00000 .00000 .00000 . . .00000 D(2) -.31639 -.44095 -.00358 -.01067 . . -.02926 D(3) .00079 .00045 -.00047 .00142 . . .00596 D(4) .00119 .00128 -.00061 -.00110 . . .00093 PM3(1) . . . . . . . PM3(2) .16649 .23580 .69108 .03467 . . -.08340 PM3(3) . . . . . . . PM3(4) . . . . . . . PM4(1) -.01772 -.00781 .04893 -.06021 . . .06990 PM4(2) -.03719 .04186 .07188 .09203 . . -.48601 PM4(3) -.07580 .00001 -.00001 .00000 . . -.00004 PM4(4) -.07159 -.02450 -.04972 -.09905 . . -.07480 PM5(1) -.22286 -.31773 -.48401 .00000 . . -.00001 PM5(2) -.43700 -.62304 .00000 .00000 . . -.00002 PM5(3) -.68157 -.97103 -.02459 -.05040 . . .09432 PM5(4) -.69430 -.98526 -.00163 -.00486 . . -.01335 P4(2) P4(3) P4(4) P5(1) P5(2) P5(3) P5(4) Constant -.06041 .00000 -.05586 . -.11312 -.04334 . P1(1) .00840 .00000 .01995 . .52814 .09148 . P1(2) .02099 .00000 .04983 . -.01269 .22852 . P1(3) -.27105 .00000 -.32926 . -.06925 .54812 . P1(4) -.27104 -.00001 -.32925 . -.06925 .54812 . P2(1) -.00001 .00000 -.00001 . -.00002 .00000 . P2(2) -.11198 .00000 -.11181 . -.59970 -.24869 . P2(3) .00129 -.44353 -.00498 . -.44911 -.18615 . P2(4) -.12832 .00000 -.13621 . -.52430 .04177 . P3(1) -.06072 .00000 -.09177 . -.53602 .05383 . P3(2) -.07904 -.00001 -.14405 . -.02689 .10685 . P3(3) . . . . . . . P3(4) . . . . . . . P4(1) .87974 .00001 .91648 . .03966 -.31581 . P4(2) 1.00000 .00000 .97686 . .00674 -.18806 . P4(3) .00000 1.00000 .00001 . .00000 .00000 . P4(4) .97686 .00001 1.00000 . .02171 -.21404 . P5(1) . . . . . . . P5(2) .00674 .00000 .02171 . 1.00000 .22700 . P5(3) -.18806 .00000 -.21404 . .22700 1.00000 . P5(4) . . . . . . . P6(1) .17639 -.03709 .19839 . .13354 -.20679 . P6(2) .17639 -.03710 .19838 . .13354 -.20679 . P6(3) .14290 -.03005 .16071 . .10817 -.16751 . Lampiran 6 : Analisa Regresi Logistik (sambungan) P6(4) .17637 -.03711 .19835 . .13353 -.20678 . H1(1) .15056 -.00001 .19130 . .03053 -.07933 . H1(2) .2 Logistic Regression untuk perpindahan merek terhadap Kebutuhan Mencari Variasi

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Total number of cases: 100 (Unweighted) Number of selected cases: 100 Number of unselected cases: 0 Number of selected cases: 100 Number rejected because of missing data: 0 Number of cases included in the analysis: 100 Dependent Variable Encoding: Original Internal Value Value .00 0 1.00 1 Parameter Value Freq Coding (1) (2) (3) E3 Tidak setuju 2.00 9 1.000 .000 .000 Antara setuju dan tidak 3.00 2 .000 1.000 .000 Setuju 4.00 73 .000 .000 1.000 Sangat setuju 5.00 16 .000 .000 .000 E2 Tidak setuju 2.00 10 1.000 .000 .000 antara setuju dan tidak 3.00 1 .000 1.000 .000 Setuju 4.00 77 .000 .000 1.000 Sangat setuju 5.00 12 .000 .000 .000 E1 Tidak setuju 2.00 6 1.000 .000 .000 Antara setuju dan tidak 3.00 2 .000 1.000 .000 Setuju 4.00 70 .000 .000 1.000 Sangat setuju 5.00 22 .000 .000 .000 E5 Sangat tidak setuju 1.00 1 1.000 .000 .000 Tidak setuju 2.00 12 .000 1.000 .000 Setuju 4.00 65 .000 .000 1.000 Sangat setuju 5.00 22 .000 .000 .000 E4 Tidak setuju 2.00 8 1.000 .000 Setuju 4.00 70 .000 1.000 Sangat setuju 5.00 22 .000 .000 E6 Tidak setuju 2.00 10 1.000 .000 Setuju 4.00 74 .000 1.000 Sangat tidak setuju 5.00 16 .000 .000 Lampiran 6 : Analisa Regresi Logistik (sambungan) Dependent Variable.. PINDAH Keputusan perpindahan merek Beginning Block Number 0. Initial Log Likelihood Function -2 Log Likelihood 131.79114 * Constant is included in the model.

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Beginning Block Number 1. Method: Enter Variable(s) Entered on Step Number 1.. E1 E2 E3 E4 E5 E6 Estimation terminated at iteration number 6 because Log Likelihood decreased by less than .01 percent. -2 Log Likelihood 99.666 Goodness of Fit 108.051 Cox & Snell - R^2 .275 Nagelkerke - R^2 .375 Chi-Square df Significance Model 32.125 16 .0096 Block 32.125 16 .0096 Step 32.125 16 .0096 ---------- Hosmer and Lemeshow Goodness-of-Fit Test----------- PINDAH = Tidak PINDAH = Ya Group Observed Expected Observed Expected Total 1 8.000 8.897 2.000 1.103 10.000 2 8.000 5.689 .000 2.311 8.000 3 7.000 5.900 3.000 4.100 10.000 4 4.000 4.952 6.000 5.048 10.000 5 2.000 3.274 8.000 6.726 10.000 6 1.000 3.204 13.000 10.796 14.000 7 1.000 1.418 6.000 5.582 7.000 8 3.000 1.600 7.000 8.400 10.000 9 1.000 1.383 10.000 9.617 11.000 10 2.000 .683 8.000 9.317 10.000 Chi-Square df Significance Goodness-of-fit test 12.0981 8 .1469 Lampiran 6 : Analisa Regresi Logistik (sambungan) -------------------------------------------------------------- Classification Table for PINDAH The Cut Value is .50 Predicted Tidak Ya Percent Correct T ? Y Observed ?????????????????

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Tidak T ? 24 ? 13 ? 64.86% ????????????????? Ya Y ? 7 ? 56 ? 88.89% ????????????????? Overall 80.00% ------------------- Variables in the Equation -------------------- Variable B S.E. Wald df Sig R Exp(B) E1 1.2505 3 .7409 .0000 E1(1) -.7253 1.2675 .3274 1 .5672 .0000 .4842 E1(2) -1.6452 1.5689 1.0997 1 .2943 .0000 .1930 E1(3) -.4001 .6714 .3552 1 .5512 .0000 .6702 E2 9.4959 3 .0234 .1629 E2(1) -.7484 1.0891 .4722 1 .4920 .0000 .4731 E2(2) 7.4754 36.6669 .0416 1 .8385 .0000 1764.0634 E2(3) 1.5187 .7683 3.9079 1 .0481 .1203 4.5664 E3 2.0192 3 .5684 .0000 E3(1) -.4364 1.2534 .1212 1 .7277 .0000 .6464 E3(2) -2.1261 1.6762 1.6089 1 .2046 .0000 .1193 E3(3) -.8810 .8462 1.0840 1 .2978 .0000 .4143 E4 2.3685 2 .3060 .0000 E4(1) -1.5281 1.3362 1.3079 1 .2528 .0000 .2169 E4(2) .3284 .6636 .2449 1 .6207 .0000 1.3887 E5 5.0673 3 .1669 .0000 E5(1) -5.8059 36.7039 .0250 1 .8743 .0000 .0030 E5(2) -1.9100 .9694 3.8821 1 .0488 -.1195 .1481 E5(3) -.1047 .6681 .0246 1 .8755 .0000 .9006 E6 2.3494 2 .3089 .0000 E6(1) -1.8377 1.1998 2.3458 1 .1256 -.0512 .1592 E6(2) -.8292 .8426 .9683 1 .3251 .0000 .4364 Constant 1.6130 1.1712 1.8966 1 .1685

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