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Hadi, Sutrisno, 1991, Statistika II, BPFE, Yogyakarta.

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Jakarta : PT Gramedia Pustaka Utama.

Kotler, Philip & Armstrong, Gary, 2001, Prinsip-Prinsip Pemasaran, Edisi VIII, Jilid

I, Erlangga, Jakarta.

Kotler, Philip, 1997, Manajemen Pemasaran : Analisis Perencanaan, Implementasi

dan Kontrol, Jilid I, PT. Prenhalindo, Jakarta.

Loundon, D. L. and Della- Bitta, A. J., 1993, Consumer Behavior, Singapore :

McGraw-Hill, Inc.

Ries, A. and Trout, J., 1986, Positioning : The Battle For Your Mind, New York :

McGraw-Hill, Inc.

Santoso, S. and Tjiptono, F., 2001, Riset Pemasaran : Konsep dan Aplikasi dengan

SPSS, Jakarta : PT Elex Media Komputindo.

Simamora, Bilson, 2001, Panduan Riset Pemasaran, PT. Gramedia Pustaka Utama,

Jakarta.

Sugiyono, Dr. Prof, 1999, Metode Penelitian Bisnis, CV Alfabeta, Bandung.

Umar, H., 1997, Metodologi Penelitian : Aplikasi Dalam Pemasaran, Jakarta : PT

Gramedia Pustaka Utama.

www.media-indonesia.com

www.gizi.net

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Lampiran 1.

Profil

 

Responden

 

Minuman

 

Isotonik

 

(3)
(4)
(5)

13 26.0 26.0 26.0

Frequency Percent Valid Percent Percent

(6)
(7)

4 8.0 8.0 8.0

Frequency Percent Valid Percent Percent

(8)
(9)

1 2.0 2.0 2.0

Frequency Percent Valid Percent Percent

(10)
(11)

6 12.0 12.0 12.0

Frequency Percent Valid Percent Percent

(12)
(13)

3 6.0 6.0 6.0

Frequency Percent Valid Percent Percent

Lampiran 3.

ANACOR

TABLE=ALL(12,3) /DIMENSION=2

/NORMALIZATION CANONICAL

/PRINT TABLE SCORES CONTRIBUTIONS PROFILES PERMUTATION /VARIANCE ROWS COLUMS SINGULAR

/PLOT ROWS COLUMS JOINT NDIM(ALL,MAX).

ANACOR

The table to be analyzed:

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(15)

1 .081 -.121 -.287

Contribution of row points to the inertia of each dimension:

Marginal Dim

Contribution of dimensions to the inertia of each row point:

(16)

8 .082 .811 .189 1.000 9 .081 .997 .003 1.000 10 .074 .994 .006 1.000 11 .092 .991 .009 1.000 12 .089 .923 .077 1.000

Column Scores:

Marginal Dim

Column Profile 1 2

1 Pocari_S .335 -.445 .078 2 Mizone .346 .094 -.225 3 Vitazone .320 .365 .162 C

Contribution of column points to the inertia of each dimension:

Marginal Dim

Column Profile 1 2

1 Pocari_S .335 .593 .072 2 Mizone .346 .027 .627 3 Vitazone .320 .380 .301 --- --- 1.000 1.000

Contribution of dimensions to the inertia of each column point:

Marginal Dim Total Column Profile 1 2

1 Pocari_S .335 .993 .007 1.000 2 Mizone .346 .413 .587 1.000 3 Vitazone .320 .953 .047 1.000

Variances and Correlation Matrix of the singular values:

Dim Variances Correlations between dimensions 1 .006 1.000

2 .008 -.006 1.000

Variances and Correlation Matrix of scores of Row 1

Dim Variances Correlations between dimensions 1 .248 1.000

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2 .066 .119 1.000

Variances and Correlation Matrix of scores of Row 3

Dim Variances Correlations between dimensions 1 .136 1.000

2 .191 -.016 1.000

Variances and Correlation Matrix of scores of Row 4

Dim Variances Correlations between dimensions 1 .389 1.000

2 .326 -.116 1.000

Variances and Correlation Matrix of scores of Row 5

Dim Variances Correlations between dimensions 1 .088 1.000

2 .073 -.069 1.000

Variances and Correlation Matrix of scores of Row 6

Dim Variances Correlations between dimensions 1 .142 1.000

2 .118 .031 1.000

Variances and Correlation Matrix of scores of Row 7

Dim Variances Correlations between dimensions 1 .040 1.000

2 .036 .407 1.000

Variances and Correlation Matrix of scores of Row 8

Dim Variances Correlations between dimensions 1 .007 1.000

2 .005 .228 1.000

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Variances and Correlation Matrix of scores of Row 9

Dim Variances Correlations between dimensions 1 .022 1.000

2 .030 .409 1.000

Variances and Correlation Matrix of scores of Row 10

Dim Variances Correlations between dimensions 1 .009 1.000

2 .011 -.533 1.000

Variances and Correlation Matrix of scores of Row 11

Dim Variances Correlations between dimensions 1 .004 1.000

2 .004 .497 1.000

Variances and Correlation Matrix of scores of Row 12

Dim Variances Correlations between dimensions 1 .024 1.000

2 .021 .379 1.000

Variances and Correlation Matrix of scores of Column 1 Pocari_Sweat

Dim Variances Correlations between dimensions 1 .038 1.000

2 .054 .497 1.000

Variances and Correlation Matrix of scores of Column 2 Mizone

Dim Variances Correlations between dimensions 1 .163 1.000

2 .127 .113 1.000

C

Variances and Correlation Matrix of scores of Column 3 Vitazone

Dim Variances Correlations between dimensions 1 .113 1.000

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9 4.16 3.50 2.94 10.60 10 3.52 3.30 2.84 9.66 12 4.16 3.88 3.56 11.60 1 3.66 3.86 3.08 10.60 11 4.24 4.08 3.68 12.00 4 3.56 3.84 2.98 10.38 2 3.90 3.66 3.52 11.08 8 3.66 3.64 3.38 10.68 6 3.84 3.62 3.60 11.06 5 3.74 3.72 3.70 11.16 7 3.20 3.84 3.60 10.64 3 1.98 4.12 4.76 10.86 --- --- --- --- Margin 43.62 45.06 41.64 130.32

The data-matrix permuted according to the scores in dimension: 2

2 1 3

Mizone Pocari_S Vitazone Margin

4 3.84 3.56 2.98 10.38 1 3.86 3.66 3.08 10.60 7 3.84 3.20 3.60 10.64 10 3.30 3.52 2.84 9.66 3 4.12 1.98 4.76 10.86 11 4.08 4.24 3.68 12.00 9 3.50 4.16 2.94 10.60 8 3.64 3.66 3.38 10.68 12 3.88 4.16 3.56 11.60 2 3.66 3.90 3.52 11.08 5 3.72 3.74 3.70 11.16 6 3.62 3.84 3.60 11.06 --- --- --- --- Margin 45.06 43.62 41.64 130.32 C

Abbreviated Extended Name Name

(20)

Dimension 1

1.5 1.0

0.5 0.0

-0.5

Di

mension 2

0.2

0.0

-0.2

-0.4

12

11 10 9 8

7 6

5

4

3 2

1

Row Scores

(21)

Dimension 1

0.4 0.2

0.0 -0.2

-0.4 -0.6

Dimensio

n 2

0.2

0.1

0.0

-0.1

-0.2

-0.3

Vitazone

Mizone Pocari_Sweat

Column Scores

(22)

Dimension 1

1.5 1.0

0.5 0.0

-0.5

Di

mension 2

0.2

0.0

-0.2

-0.4

12 11 10 9

8 7 6

5

4

3 2

1

Vitazone

Mizone Pocari_Sweat

Row and Column Scores

Rows Columns

Variable

Symmetric Normalization

Lampiran 4.

Reliability POCARI SWEAT

(23)

50 100.0

(24)

Reliability MIZONE

(25)

Case Processing Summary

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