73
BAB V
KESIMPULAN DAN SARAN
Berdasarkan hasil penelitian dan pengolahan data yang diperoleh dari
penyebaran kuesioner kepada responden sebanyak 100 kuesioner tentang pengaruh
harga, kualitas produk, citra merek, dan promosi terhadap keputusan pembelian
menunjukkan hasil yang baik. Berikut ini adalah hasil kesimpulan penelitian
berdasarkan analisis yang telah dilakukan:
5.1.
Kesimpulan
Simpulan yang dapat diambil dari penelitian pengaruh harga, kualitas produk,
citra merek, dan promosi terhadap Keputusan Pembelian yang difokuskan pada
pelanggan Plangtown di kota Semarang adalah sebagai berikut:
1.
Variabel pertama yang paling dominan berpengaruh terhadap Keputusan
Pembelian produk Plangtown berupa pakaian jadi adalah variabel harga.
Harga menurut (
Asih Purwanti, 2010
) “merupakan satu-satunya unsur
bauran pemasaran yang dapat menghasilkan profit bagi perusahaan”,
maka dari itu harga merupakan faktor yang penting dalam menentukan
keputusan pembelian. Pernyataan tersebut dapat dilihat pada table
coefficient
dengan nilai koefisien sebesar 0,291 dan nilai signifikan
sebesar 0,000 yang lebih kecil dibandingkan taraf signifikan 0,05 berarti
bahwa jika variabel harga baik maka Keputusan Pembelian juga akan
meningkat. Demikian juga sebaliknya, apabila harga yang ditawarkan
buruk maka Keputusan Pembelianpun akan menurun.
74
2.
Variabel kedua yang paling dominan berpengaruh terhadap Keputusan
Pembelian produk Plangtown berupa pakaian jadi adalah variabel
promosi. Hal ini dapat dilihat pada table
coefficient
dengan nilai koefisien
sebesar 0,285 dan nilai signifikan sebesar 0,000 yang lebih kecil
dibandingkan taraf signifikan 0,05. Hipotesis yang menyatakan bahwa
faktor promosi berpengaruh signifikan terhadap keputusan pembelian
produk Plangtown berupa pakaian jadi di Plangtown Store diterima.
Berarti bahwa jika variabel promosi meningkat maka Keputusan
Pembelian juga akan meningkat. Demikian juga sebaliknya, apabila
promosi menurun maka Keputusan Pembelianpun akan menurun.
3.
Variabel ketiga yaitu variabel kualitas produk dengan nilai table
coefficient
sebesar 0,226 dan nilai signifikan sebesar 0,004 yang lebih
kecil dibandingkan taraf signifikan 0,05. Hal ini berarti bahwa jika
variabel citra merek dan kualitas produk baik maka Keputusan Pembelian
juga akan meningkat. Demikian juga sebaliknya, apabila citra merek dan
kualitas produk buruk maka Keputusan Pembelianpun akan menurun.
4.
Variabel yang terakhir yaitu variabel citra merek dengan nilai table
coefficient
sebesar 0,213 dan nilai signifikan sebesar 0,005 yang lebih
kecil dibandingkan taraf signifikan 0,05. Hal ini berarti bahwa jika
variabel citra merek meningkat maka Keputusan Pembelian juga akan
meningkat. Demikian juga sebaliknya, apabila citra merek menurun maka
Keputusan Pembelianpun akan menurun.
75
5.2.
Saran
Saran untuk hasil penelitian mengenai pengaruh pengaruh harga, kualitas
produk, citra merek, dan promosi terhadap Keputusan Pembelian produk Plangtown
berupa pakaian jadi di Semarang maka dapat diambil kesimpulan sebagai berikut :
1.
Pada variabel harga yaitu menambah variasi harga produk agar
menambah opsional pelanggan untuk melakukan Keputusan Pembelian
dengan kata lain . Hal ini perlu disikapi supaya pelanggan produk
Plangtown berupa pakaian jadi menambah keyakinan untuk melakukan
Keputusan Pembelian.
2.
Pada variabel promosi, yang perlu ditingkatkan yaitu pengadaan
promo penjualan dengan harga yang menarik dari produk Plangtown
berupa pakaian jadi. Hal ini perlu disikapi agar promosi pada produk
Plangtown berupa pakaian jadi semakin baik, dapat dilakukan dengan
cara menambah sosialisai tentang adanya promo yang akan dilakukan
oleh pihak Plangtown sehingga pelanggan akan mengetahui akan
diadakan promo penjualan dengan harga yang menarik.
3.
Dalam variabel kualitas produk, sebaiknya untuk menjaga kualitas
produk pakaian yang diproduksi Plangtown harus lebih menekankan
pada kontrol kualitas.
76
DAFTAR PUSTAKA
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Perilaku Konsumen Pendekatan Praktis.
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ANDI.
Kotler, P., & Keller, K. L. (2012).
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Model - Model Persamaan Stuktural.
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Lovelock, C., Wirtz, J., & Mussry, j. (2012).
Pemasaran Manusia, Teknologi, Strategi
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AMOS 22 untuk Structural Equation Modeling Konsep Dasar dan
Aplikasi.
Elex Media Komputindo.
Sugiyono. (2010).
Metode Penelitian Bisnis.
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Sujarweni,
V.
W.
(2014).
Metodologi
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PUSTAKABARUPRESS.
Tjiptono, F. (2014).
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Tjiptono, F., & G., C. (2012).
Pemasaran Strategik Edisis 2.
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http://dripsndrops.com/
http://garduhouse.com/
http://www.wadezig.com
Kamal, F. G. (2012). Analisis Pengaruh Harga, Kualitas Produk, dan Lokasi Terhadap
Keputusan Pembelian (Studi pada Pembeli Bandeng Juwana Erlina Semarang
).
DIPONEGORO JOURNAL OF MANAGEMENT
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, 1-10.
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Lamidi, H. A. (2015). Pengaruh Harga, Kualitas Pelayanan dan Lokasi terhadap
Keputusan Pembelian Konsumen.
Jurnal Ekonomi dan Kewirausahaan
.
Martoatmodjo, D. H. (2012). Pengaruh produk, harga, promosi dan distribusi terhadap
Keputusan Pembelian konsumen pada produk projector microvision.
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Ilmu dan Riset Manajemen
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Md Reaz Uddin, N. Z. (2014). Factors Affecting Customer Buying Decision Of
Mobile Phone : A Study On Khulna City Bangladesh.
Nur Achidah, M. M. (2016). Pengaruh Promosi, Harga dan Desain terhadap
Keputusan Pembelian Sepeda Motor Mio GT (Studi Empiris pada produk
Yamaha Mio GT di Weleri-Kendal).
Journal of Management
.
Reimond Yohanes Monintja, S. M. (2015). Analisis merek, promosi, dan harga
pengaruhnya terhadap Keputusan Pembelian di galael swalayan Manado.
Jurnal EMBA
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, 279-289.
Sunyoto, D. (2013).
perilaku konsumen.
Yogyakarta.
Suprihhadi, E. L. (2015). Pengaruh Kualitas Layanan dan Word of Mouth Terhadap
Keputusan Pembelian Karoseli.
jurnal Ilmu dan Riset Manajemen
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.
Ujang Setiawan, P. D. (2015). Pengaruh Citra Merek, Harga, Kualitas
Produk dan Gaya Hidup terhadap Keputusan Pembelian Handphone
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Pandanaran Semarang).
jurnal Manajemen pemasaran
.
78
Kuisioner Penelitian
“Analisis Pengaruh Harga, Kuarlitas Produk, Citra Merek, dan Promosi
terhadap Keputusan Pembelian Pakaian Jadi Merek Plangtown ( Studi Kasus
pada Plangtown
Store
)
”
I.
Identitas Responden
Nama
:
Umur
:
Jenis Kelamin :
Laki-laki Perempuan
Pekerjaan
:
Pelajar
Mahasiswa
Lainnya
Wiraswasta Pegawai
II.
Petunjuk Pengisisan
Berikut ini terdapat beberapa pertanyaan yang berkaitan dengan Keputusan
Pembelian pelanggan yang meliputi
Harga, Kualitas Produk, Citra Merek,
Promosi. Maka kami memohon kepada responden untuk :
a.
Saudara / Saudari dapat menjawab pertanyaan yang telah disediakan
dengan sejujur-jujurnya. Perlu diketahui bahwa pertanyaan yang telah
disediakan tidak berhubungan antara benar atau salah.
b.
Pilihlah jawaban dengan memberi tanda
Checlist
( √ ) pada salah satu
jawaban yang menurut anda sesuai. Penelitan jawaban menggunakan
skala berikut ini :
Keterangan
Nilai
Sangat Setuju ( SS )
5
Setuju (S)
4
Netral (N)
3
Tidak Setuju (TS)
2
79
III.
Daftar Pertanyaan
A.
Harga
No. Pertanyaan-pertanyaan
STS
TS
N
S
SS
1.
Harga yang ditawarkan Plangtown
sebanding dengan kualitas produk.
2.
Harga Produk Plangtown
bervariasi.
3.
Harga produk Plangtown berupa
pakaian jadi lebih murah dari pada
tempat yang lain
4.
Harga dari produk Plangtown
berupa pakaian jadi sesuai dengan
kondisi keuangan anak muda di
Semarang
B.
Kualitas Produk
No. Pertanyaan-pertanyaan
STS
TS
N
S
SS
1.
Merek Plangtown memiliki banyak
desain daripada pakaian distro
sejenis di Semarang.
2.
Pakian Produk Plangtown nyaman
dipakai
3.
Pakian Produk Palngtown rapi dan
tahan lama
4.
Produk dari Plangtown selalu
mengikuti jaman
C.
Citra Merek
No. Pertanyaan-pertanyaan
STS
TS
N
S
SS
1.
Merek Plangtown dapat dengan
mudah diingat oleh anda
2.
Memakai produk dari Plangtown
secara tidak langsung membuat
anda percaya diri
3.
Harga produk dari Plangtown
secara tidak langusng menjamin
kualitasnya
80
D.
Promosi
No. Pertanyaan-pertanyaan
STS
TS
N
S
SS
1.
Plangtown sudah memiliki iklan
digital.
2.
Model yang digunakan oleh
Plangtown membuat anda tertarik
membeli produknya.
3.
Pada saat – saat tertentu Plangtown
selalu mengadakan promo harga
yang menarik.
E.
Keputusan pembelian
No. Pertanyaan-pertanyaan
STS
TS
N
S
SS
1.
Harga yang ditawarkan oleh
Plangtown terjangkau
2.
Saya membeli produk dari
Plangtown dikarenakan desain
yang selalu mengikuti jaman.
3.
Saya membeli pakaian di
Plangtown Store berdasarkan
keinginan pribadi.
4.
Saya akan berkunjung kembali ke
Plangtown Store
untuk melakukan
pembelian
81
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15
4
4
4
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00
12
4
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4
3,
67
11
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4
4
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00
16
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4
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25
17
4
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75
15
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4
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12
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00
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75
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11
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00
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50
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75
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00
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00
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75
15
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00
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00
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15
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00
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00
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4
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5
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5
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5,
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4
4
4
4,
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17
4
4
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4,
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5
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4
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4
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4,
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4
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5
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4
4
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5
5
4
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5
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5,
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5
4
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4
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4
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4
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4,
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4
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4
4
4
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4
5
4
4,
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5
5
4
4
4,
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4
4
4
5
4,
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3
4
4
5
4,
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16
4
4
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3,
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5
4
5
4,
67
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5
5
4
4
4,
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4
5
4
4
4,
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4
4
5
4,
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5
4
5
4,
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4
4
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4,
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5
5
4
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5
4
4
5
4,
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18
4
4
3
4
3,
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4
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3
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5
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4,
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5
3
5
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4,
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3
5
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4,
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3
4
5
3
3,
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3
3,
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5
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3
4,
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3
4
5
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4
5
4
4
4,
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5
5
4
3
4,
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17
4
4
5
4,
33
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4
3
4
3,
67
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4
4
5
4
4,
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5
4
4
4
4,
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4
4
4
4
4,
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16
4
4
5
4,
33
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3
4
4
3,
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4
4
5
4
4,
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5
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4
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4,
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4
4
4
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4
4
5
4,
33
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4
5
5
4,
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4
4
5
4
4,
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3
4
3
3
3,
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4
5
4
4,
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4
3
5
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4
5
3
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4
4
5
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4
3
3
3,
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3
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5
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5
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5
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4,
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4
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4
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4,
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4
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5
5
5,
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4
5
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4,
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4
3
3
3
3,
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4
4
3
3,
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3
4
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3,
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4
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3
5
3,
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5
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4
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3
3,
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3,
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3
3
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3
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5
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5
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4,
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3
4
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5
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4
4
4
4
4,
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16
4
4
3
4
3,
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4
5
4
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4
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4
4,
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4
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4
5
4,
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5
4
4
4
4,
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5
4
3
4
4,
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16
4
3
4
3,
67
11
5
5
5
5,
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4
4
4
5
4,
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4
4
3
4
3,
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15
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4
3
5
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16
4
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4
4,
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4
4
4
4,
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4
4
4
5
4,
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4
4
5
4,
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4
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4
4
5
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4,
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4
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4
4
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4
4
5
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4
4
5
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33
13
5
5
5
5,
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5
4
4
5
4,
50
18
4
4
4
3
3,
75
15
3
5
4
5
4,
25
17
4
4
5
4,
33
13
5
4
4
4,
33
13
5
4
4
5
4,
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18
5
5
4
4
4,
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18
4
4
5
5
4,
50
18
4
4
5
4,
33
13
4
5
4
4,
33
13
5
4
4
5
4,
50
18
5
5
4
4
4,
50
18
5
5
5
5
5,
00
20
5
4
5
4,
67
14
5
5
5
5,
00
15
5
4
4
5
4,
50
18
3
5
4
4
4,
00
16
3
4
5
4
4,
00
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3
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00
12
5
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4
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4
5
4
5
4,
50
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4
5
4
4
4,
25
17
4
5
4
5
4,
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18
5
5
4
4,
67
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4
4
4
4,
00
12
4
5
4
5
4,
50
18
4
5
5
5
4,
75
19
4
5
5
5
4,
75
19
4
4
5
4,
33
13
4
4
5
4,
33
13
4
5
4
5
4,
50
18
5
5
5
5
5,
00
20
4
5
4
4
4,
25
17
5
5
4
4,
67
14
4
4
4
4,
00
12
5
5
4
5
4,
75
19
4
5
5
5
4,
75
19
4
4
5
4
4,
25
17
5
4
5
4,
67
14
4
5
4
4,
33
13
5
5
4
5
4,
75
19
4
4
5
5
4,
50
18
5
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5
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4,
75
19
5
5
4
4,
67
14
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5
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5,
00
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5
5
5
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00
20
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4
5
4,
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14
4
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4
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11
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5
4
5
4,
75
19
5
4
4
4
4,
25
17
5
4
3
4
4,
00
16
4
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3
3,
67
11
5
5
5
5,
00
15
5
3
5
5
4,
50
18
4
4
5
5
4,
50
18
3
4
4
5
4,
00
16
4
4
3
3,
67
11
4
5
4
4,
33
13
5
3
5
5
4,
50
18
4
4
5
4
4,
25
17
4
5
5
4
4,
50
18
5
5
5
5,
00
15
4
5
4
4,
33
13
4
4
5
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4,
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18
5
4
4
4
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25
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4
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5
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4,
50
18
4
5
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4,
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13
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5
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4
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50
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5
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5
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5
5
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5
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4,
75
19
4
4
5
5
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50
18
4
4
5
5
4,
50
18
4
4
5
4,
33
13
4
4
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4,
33
13
5
4
5
5
4,
75
19
5
5
4
4
4,
50
18
4
3
3
3
3,
25
13
4
4
5
4,
33
13
4
5
4
4,
33
13
4
5
5
5
4,
75
19
5
5
5
4
4,
75
19
5
5
4
5
4,
75
19
5
5
4
4,
67
14
5
4
5
4,
67
14
4
5
5
5
4,
75
19
5
5
5
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4,
75
19
5
5
4
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4,
75
19
5
5
4
4,
67
14
5
5
5
5,
00
15
4
5
5
5
4,
75
19
5
5
5
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4,
75
19
5
5
4
5
4,
75
19
5
4
5
4,
67
14
4
5
4
4,
33
13
4
5
5
5
4,
75
19
5
5
5
4
4,
75
19
5
5
4
5
4,
75
19
5
4
5
4,
67
14
4
5
4
4,
33
13
4
5
5
5
4,
75
19
5
4
5
5
4,
75
19
5
4
5
4
4,
50
18
5
5
5
5,
00
15
5
5
5
5,
00
15
5
5
5
5
5,
00
20
5
5
5
4
4,
75
19
5
5
4
5
4,
75
19
5
5
5
5,
00
15
5
5
5
5,
00
15
5
5
5
5
5,
00
20
5
5
5
5
5,
00
20
5
5
4
5
4,
75
19
4
5
4
4,
33
13
4
5
5
4,
67
14
5
5
5
5
5,
00
20
4
4
5
5
4,
50
18
5
4
5
5
4,
75
19
5
4
5
4,
67
14
5
5
5
5,
00
15
5
5
5
5
5,
00
20
Reliability
Notes
Output Created 31-JUL-2016 20:53:41
Comments
Input
Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
File 100
Matrix Input
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 for all variables in the procedure.
Syntax RELIABILITY /VARIABLES=X11 X12 X13 X14 /SCALE('ALL VARIABLES') ALL /MODEL=ALPHA /STATISTICS=DESCRIPTIV E SCALE CORR COV /SUMMARY=TOTAL.
Resources
Processor Time 00:00:00,03
Elapsed Time 00:00:00,02
Scale: ALL VARIABLES
Case Processing SummaryN %
Cases
Valid 100 100.0
Excludeda 0 .0
Total 100 100.0
a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .744 .745 4 Item Statistics Mean Std. Deviation N X11 4.03 .717 100 X12 4.13 .677 100 X13 4.00 .711 100 X14 3.96 .737 100
Inter-Item Correlation Matrix
X11 X12 X13 X14
X12 .450 1.000 .462 .395
X13 .337 .462 1.000 .424
X14 .461 .395 .424 1.000
Inter-Item Covariance Matrix
X11 X12 X13 X14 X11 .514 .218 .172 .244 X12 .218 .458 .222 .197 X13 .172 .222 .505 .222 X14 .244 .197 .222 .544 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted X11 12.09 2.790 .529 .301 .690 X12 11.99 2.838 .559 .324 .674 X13 12.12 2.834 .515 .286 .698 X14 12.16 2.701 .547 .307 .680 Scale Statistics
Mean Variance Std. Deviation N of Items
16.12 4.571 2.138 4
Reliability
Notes
Output Created 31-JUL-2016 20:53:53
Comments
Input
Active Dataset DataSet1
Filter <none>
Split File <none> N of Rows in Working Data
File 100
Matrix Input
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 for all variables in the procedure.
Syntax RELIABILITY /VARIABLES=X21 X22 X23 X24 /SCALE('ALL VARIABLES') ALL /MODEL=ALPHA /STATISTICS=DESCRIPTIV E SCALE CORR COV /SUMMARY=TOTAL.
Resources
Processor Time 00:00:00,03
Elapsed Time 00:00:00,01
Scale: ALL VARIABLES
Case Processing SummaryN %
Cases
Valid 100 100.0
Excludeda 0 .0
a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .748 .749 4 Item Statistics Mean Std. Deviation N X21 3.96 .764 100 X22 4.02 .710 100 X23 3.90 .732 100 X24 4.05 .770 100
Inter-Item Correlation Matrix
X21 X22 X23 X24
X21 1.000 .429 .300 .484
X22 .429 1.000 .431 .497
X23 .300 .431 1.000 .421
X24 .484 .497 .421 1.000
Inter-Item Covariance Matrix
X21 X22 X23 X24
X21 .584 .233 .168 .285
X22 .233 .505 .224 .272
X23 .168 .224 .535 .237
Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted X21 11.97 3.100 .509 .284 .710 X22 11.91 3.093 .584 .342 .669 X23 12.03 3.262 .476 .245 .726 X24 11.88 2.874 .608 .372 .652 Scale Statistics
Mean Variance Std. Deviation N of Items
15.93 5.056 2.248 4
Reliability
Notes
Output Created 31-JUL-2016 20:56:07
Comments
Input
Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
File 100
Matrix Input
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 for all variables in the procedure.
Syntax RELIABILITY /VARIABLES=X31 X32 X33 /SCALE('ALL VARIABLES') ALL /MODEL=ALPHA /STATISTICS=DESCRIPTIV E SCALE CORR COV /SUMMARY=TOTAL.
Resources
Processor Time 00:00:00,00
Elapsed Time 00:00:00,00
Scale: ALL VARIABLES
Case Processing SummaryN %
Cases
Valid 100 100.0
Excludeda 0 .0
Total 100 100.0
a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .741 .747 3 Item Statistics Mean Std. Deviation N X31 4.04 .724 100
X32 3.94 .649 100
X33 3.97 .834 100
Inter-Item Correlation Matrix
X31 X32 X33
X31 1.000 .586 .571
X32 .586 1.000 .333
X33 .571 .333 1.000
Inter-Item Covariance Matrix
X31 X32 X33 X31 .524 .275 .345 X32 .275 .421 .180 X33 .345 .180 .696 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted X31 7.91 1.477 .705 .503 .488 X32 8.01 1.909 .508 .344 .722 X33 7.98 1.495 .514 .326 .736 Scale Statistics
Mean Variance Std. Deviation N of Items
11.95 3.240 1.800 3
Reliability
Notes
Output Created 31-JUL-2016 20:56:16
Input
Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
File 100
Matrix Input
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 for all variables in the procedure.
Syntax RELIABILITY /VARIABLES=X41 X42 X43 /SCALE('ALL VARIABLES') ALL /MODEL=ALPHA /STATISTICS=DESCRIPTIV E SCALE CORR COV /SUMMARY=TOTAL.
Resources
Processor Time 00:00:00,02
Elapsed Time 00:00:00,02
Scale: ALL VARIABLES
Case Processing SummaryN %
Cases
Valid 100 100.0
Excludeda 0 .0
a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .724 .726 3 Item Statistics Mean Std. Deviation N X41 4.02 .681 100 X42 4.13 .734 100 X43 4.00 .682 100
Inter-Item Correlation Matrix
X41 X42 X43
X41 1.000 .439 .544
X42 .439 1.000 .424
X43 .544 .424 1.000
Inter-Item Covariance Matrix
X41 X42 X43 X41 .464 .220 .253 X42 .220 .538 .212 X43 .253 .212 .465 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted X41 8.13 1.427 .580 .349 .594 X42 8.02 1.434 .491 .242 .704
X43 8.15 1.442 .568 .338 .609
Scale Statistics
Mean Variance Std. Deviation N of Items
12.15 2.836 1.684 3
Reliability
Notes
Output Created 31-JUL-2016 20:56:27
Comments
Input
Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
File 100
Matrix Input
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 for all variables in the procedure.
Syntax
RELIABILITY
/VARIABLES=Y11 Y12 Y13 Y14 /SCALE('ALL VARIABLES') ALL /MODEL=ALPHA /STATISTICS=DESCRIPTIV E SCALE CORR COV /SUMMARY=TOTAL.
Resources
Processor Time 00:00:00,02
Elapsed Time 00:00:00,06
Scale: ALL VARIABLES
Case Processing SummaryN %
Cases
Valid 100 100.0
Excludeda 0 .0
Total 100 100.0
a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .753 .751 4 Item Statistics Mean Std. Deviation N Y11 4.04 .751 100 Y12 4.01 .718 100 Y13 4.11 .695 100 Y14 4.14 .739 100
Inter-Item Correlation Matrix
Y11 Y12 Y13 Y14
Y11 1.000 .468 .456 .518
Y12 .468 1.000 .342 .455
Y14 .518 .455 .344 1.000
Inter-Item Covariance Matrix
Y11 Y12 Y13 Y14
Y11 .564 .252 .238 .287 Y12 .252 .515 .171 .241 Y13 .238 .171 .483 .176 Y14 .287 .241 .176 .546 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Y11 12.26 2.720 .628 .396 .649 Y12 12.29 2.996 .534 .293 .703 Y13 12.19 3.186 .472 .237 .735 Y14 12.16 2.883 .562 .333 .687 Scale Statistics
Mean Variance Std. Deviation N of Items
16.30 4.838 2.200 4
Regression
Notes
Output Created 31-JUL-2016 20:56:48
Comments
Input
Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
Missing Value Handling
Definition of Missing User-defined missing values are 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 COLLIN TOL /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT KeputusanPembelian /METHOD=ENTER Harga KualitasProduk CitraMerek Promosi /SCATTERPLOT=(*SRESID ,*ZPRED) /RESIDUALS HISTOGRAM(ZRESID) NORMPROB(ZRESID) /SAVE PRED RESID.
Resources
Processor Time 00:00:00,80
Elapsed Time 00:00:00,74
Memory Required 2804 bytes
Additional Memory Required
for Residual Plots 888 bytes
Variables Created or Modified
PRE_2 Unstandardized Predicted
Value
Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Promosi, Citra Merek, Kualitas Produk, Hargab . Enter
a. Dependent Variable: Keputusan Pembelian b. All requested variables entered.
Model Summaryb
Model R R Square Adjusted R
Square
Std. Error of the Estimate
1 .913a .833 .826 .917
a. Predictors: (Constant), Promosi, Citra Merek, Kualitas Produk, Harga b. Dependent Variable: Keputusan Pembelian
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 399.125 4 99.781 118.676 .000b
Residual 79.875 95 .841
Total 479.000 99
a. Dependent Variable: Keputusan Pembelian
b. Predictors: (Constant), Promosi, Citra Merek, Kualitas Produk, Harga
Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .308 .746 .413 .680 Harga .299 .080 .291 3.745 .000 Kualitas Produk .221 .076 .226 2.923 .004 Citra Merek .261 .092 .213 2.846 .005 Promosi .373 .087 .285 4.293 .000 Coefficientsa
Model Collinearity Statistics
Tolerance VIF 1 (Constant) Harga .291 3.438 Kualitas Produk .294 3.397 Citra Merek .312 3.206 Promosi .397 2.520
a. Dependent Variable: Keputusan Pembelian
Collinearity Diagnosticsa
Model Dimension Eigenvalue Condition Index Variance Proportions
(Constant) Harga Kualitas Produk
1 1 4.973 1.000 .00 .00 .00 2 .013 19.718 .91 .01 .03 3 .006 27.749 .05 .02 .00 4 .004 33.863 .00 .02 .94 5 .004 35.944 .04 .96 .03
Collinearity Diagnosticsa
Model Dimension Variance Proportions
Citra Merek Promosi
1 1 .00 .00 2 .07 .01 3 .33 .74 4 .24 .21 5 .36 .05
a. Dependent Variable: Keputusan Pembelian
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 9.43 19.70 16.30 2.008 100
Std. Predicted Value -3.423 1.693 .000 1.000 100
Standard Error of Predicted
Value .094 .362 .197 .057 100
Adjusted Predicted Value 9.34 19.68 16.29 2.007 100
Residual -2.217 2.193 .000 .898 100
Std. Residual -2.418 2.392 .000 .980 100
Stud. Residual -2.473 2.584 .003 1.009 100
Deleted Residual -2.375 2.560 .006 .953 100
Stud. Deleted Residual -2.543 2.666 .001 1.019 100
Mahal. Distance .042 14.480 3.960 2.989 100
Cook's Distance .000 .223 .012 .028 100
Centered Leverage Value .000 .146 .040 .030 100
a. Dependent Variable: Keputusan Pembelian
Notes
Output Created 31-JUL-2016 20:57:12
Comments
Input
Active Dataset DataSet1
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 for each test are based on all cases with valid data for the variable(s) used in that test. Syntax NPAR TESTS /K-S(NORMAL)=PRE_1 /MISSING ANALYSIS. Resources Processor Time 00:00:00,00 Elapsed Time 00:00:00,00
Number of Cases Alloweda 196608
a. Based on availability of workspace memory.
Notes
Output Created 31-JUL-2016 20:59:24
Comments
Input
Active Dataset DataSet1
Filter <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 for each test are based on all cases with valid data for the variable(s) used in that test. Syntax NPAR TESTS /K-S(NORMAL)=RES_1 /MISSING ANALYSIS. Resources Processor Time 00:00:00,00 Elapsed Time 00:00:00,00
Number of Cases Alloweda 196608
a. Based on availability of workspace memory.
One-Sample Kolmogorov-Smirnov Test
Unstandardized Residual
N 100
Normal Parametersa,b
Mean 0E-7
Std. Deviation .89823101
Most Extreme Differences
Absolute .056
Positive .047
Negative -.056
Kolmogorov-Smirnov Z .565
Asymp. Sig. (2-tailed) .907
a. Test distribution is Normal. b. Calculated from data.
