The Effectiveness of the Indonesia Stock Exchange's Marketing

Communication Program: Yuk Nabung Saham

Rheza Andhika Pamungkas and Martani Huseini

Department of Communication Science, Universitas Indonesia, Depok, Indonesia

Keywords: Effectiveness, Integrated Marketing Communication, Brand Equity, Indonesia Stock Exchange, Capital

Market.

Abstract: To improve the Indonesian capital market literacy and increase the number of Indonesian capital market

investors, on 12th November 2015 The Indonesia Stock Exchange (IDX) launched a campaign program called

"Yuk Nabung Saham". This research aims to determine the effectiveness of the IDX’s Yuk Nabung Saham

Program.

1 INTRODUCTION

To improve the Indonesian capital market literacy and

increase the number of Indonesian capital market

investors, on 12th November 2015 The Indonesia

Stock Exchange (IDX) launched a campaign program

called "Yuk Nabung Saham". The purpose of this

program is to change the paradigm of the Indonesian

society from saving society to investment society and

encourage people from various groups to invest their

funds regularly as deposits in the form of shares. The

IDX marketing strategy through the Yuk Nabung

Saham campaign, as quoted from the 2015 IDX

Annual Report, is one of the four main pillars in the

strategic plan and the long-term tactical steps set by

the IDX Board of Directors, namely an increase in the

number of active investors.

Effectiveness is needed by the organization to

determine the level of success of the organization in

an effort to achieve its goals and objectives.

Effectiveness is a concept that has a broad

understanding because the achievement of goals or

objectives for an organization certainly involves all

aspects of the organization, both internal and external,

and not only limited to parts of the organization

related to the process of transforming inputs into

output only (Hari Lubis and Huseini, 2009). In order

for the marketing strategy - in this case The Yuk

Nabung Saham campaign strategy - can run

effectively, it requires the development and

implementation of various forms of persuasive

communication programs to a sustainable audience

called Integrated Marketing Communication (Shimp,

2003). The IDX's integrated marketing

communication strategy was introduced to the public

using The Yuk Nabung Saham brand. This program

invites the public to open a securities account at a

securities company and become a capital market

investor on the IDX with only an initial capital of

Rp100.000 used to buy shares of the Listed Company.

The IDX claimed that this program was effective to

increase the number of Indonesian capital market

investors. However, with some of the achievements

of the IDX in developing the capital market in terms

of the number of investors, currently the number of

capital market investors is still small compared to the

number of the middle class or consumer classes that

are considered capable and targeted by prospective

investors.

2 OBJECTIVE OF THIS STUDY

This study aims to: (1) Find out the IDX’s Yuk

Nabung Saham program has been running effectively,

(2) knowing the effectiveness of the IDX’s marketing

communication strategy in shaping brand equity from

the Yuk Nabung Saham campaign, especially on the

target population, and (3) knowing the relationship

and connectivity between marketing communication

strategies and brand equity from Yuk Nabung Saham

IDX.

208

Pamungkas, R. and Huseini, M.

The Effectiveness of the Indonesia Stock Exchange’s Marketing Communication Program: Yuk Nabung Saham.

DOI: 10.5220/0008429402080217

In Proceedings of the 2nd International Conference on Inclusive Business in the Changing World (ICIB 2019), pages 208-217

ISBN: 978-989-758-408-4

3 RELEVANT CONCEPT AND

THEORIES

This study uses two main theories to examine the

effectiveness of marketing communication from the

IDX's Yuk Nabung Saham program. The first theory

is the Mix of Integrated Marketing Communication

Promotion from Belch and Belch (2003), and the

second theory is Brand Equity introduced by Aaker

(2017).

Belch and Belch (2007) in the journal of Shafi &

Madhavaiah (2013) define integrated marketing

communication as a strategic business procedure that

was used to carry out, evaluate, develop and

coordinate programs with stakeholders over a period

of time. Belch and Belch (2003) state that

traditionally the promotion mix includes four

elements: advertising, sales promotion, publicity/

public relations, and personal selling. However, direct

marketing and interactive marketing are seen as the

main promotional mix elements that modern

marketers use to communicate with their target

audience. Each element of the promotion mix is seen

as an integrated marketing communication tool that

plays a special role in the Integrated Marketing

Communication program. Each can consist of various

forms and certain advantages.

Related to the second theory that used in this study

- Brand Equity, Aaker (2017) defines brand equity as

a set of brand assets and liabilities relating to a brand,

its name and symbol, which increases or decreases the

value provided by an item or service company or

company customers. Brand equity was grouped into

five categories namely brand loyalty, brand

awareness, brand's perceived quality, brand

associations, and other brand assets: patents, stamp,

relationship channels and others.

The focus of this study is on the using of the

integrated marketing communication as a brand

strategy in increasing brand equity, which refers to

the research of Mongkol (2014) and Brunello (2013)

that are adapted to the situation and condition of the

object of this research, The IDX's Yuk Nabung

Saham program. The reason for referring to the two

studies is based on the finding that Integrated

Marketing Communication has far more significant

value than just attracting consumers to buy products

or services from certain companies, but also

contributes to the development of corporate brand

equity, as well as proof of the correlation between

communication integrated marketing and brand

equity in a beverages company in Thailand. This

study would like to see what if we examine the

correlation between integrated marketing

communication strategies carried out by the company

(in this case: The IDX) and its effectiveness towards

the formation of brand equity from service products

in an industry that is in the capital market industry in

Indonesia.

4 RESEARCH FRAMEWORK

AND THEORETICAL

HYPOTHESES

Figure 1: Framework.

Based on the research framework as figure 1, the

theoretical hypotheses of this study are:

H1: Advertising significantly influence Brand

Equity.

H2: Direct Marketing significantly influence

Brand Equity.

H3: Interactive Marketing/ Internet Marketing

significantly influence Brand Equity.

H4: Sales Promotion significantly influence

Brand Equity.

H5: Publicity/ Public Relations significantly

influence Brand Equity.

H6: Personal Selling significantly influence

Brand Equity.

5 METHODOLOGY

5.1 Population and Samples

The population of this study was the Capital Market

School participants in Jabodetabek during the period

of October 2018. IDX holds regular Capital Market

Schools in the Jabodetabek area 3 times each week.

Assuming the average number of participants of the

Capital Market School is 40 people per event, the

population of this study is 480 people. This study uses

The Effectiveness of the Indonesia Stock Exchange’s Marketing Communication Program: Yuk Nabung Saham

209

a probability sampling technique with a simple

random sampling technique. There are various

techniques for determining sample size.

According to Sugiyono (2015) there is a table for

determining the number of samples from a particular

population developed by Isaac and Michael to

calculate errors of 1 percent, 5 percent, and 10

percent. Referring to the tables of Isaac and Michael

(Sugiyono, 2015) the determination of the number of

samples of this study was applied by for a population

of 480 people with a 5 percent margin of error, the

samples were 202 respondents.

5.2 Measurement Scale of Respondents

The measurement scale of this study uses a Likert

scale. To reduce the tendency of respondents to

choose neutral answers, the researcher collects and

processes the data obtained from the questionnaire by

making the answers even and giving the weight

values for each question based on the scale as follows:

1) Strongly Agree (SA): Scale 4.

2) Agree (A): Scale 3.

3) Disagree (D): Scale 2.

4) Strongly Disagree (SD): Scale 1.

5.3 Validity and Reliability Test

This study uses a validity test using Pearson Product

Moment correlation. The reason for using this

analysis technique is because according to Gogtay

and Thatte (2017), the Pearson correlation coefficient

establishes the relationship between two variables

based on three assumptions:

1. Relationships are linear

2. Variables do not depend on each other.

3. Variables are normally distributed.

Pearson Product Moment correlation analysis uses a

method of correlating each item score with a total

score. The total score is the sum of all items. The

question items that correlate significantly with the

total score indicate that these items are able to provide

support in revealing that the significance level (α) of

this study is valid. If the r count is greater than (≥) r

table, the instrument or question items correlate

significantly to the total score so that the item is

declared valid. Whereas if r count is less than (≤) r or

r count is equal to (=) r table, then the item under

study is said to be invalid.

The reliability test of this study uses Cronbach

Alpha (α) calculations. According to Tavakol and

Dennick (2011), the number of test items, the

relevance of items and dimensions affects alpha

values. From a variety of research and research,

acceptable alpha values range from 0.70 to 0.90. Low

alpha values can be caused by a number of low

questions, weak interrelationships between items, or

heterogeneous constructs. While the maximum

recommended alpha value is 0.90 so that reliability is

considered perfect and suggest all items are reliable

and all tests consistently have strong reliability.

6 DATA ANALYSIS

The method of data analysis in this study uses

descriptive statistics. According to Neuman (2013),

descriptive statistics are a general type of simple

statistics to explain the basic patterns in data. This

study also uses factor analysis to create a single score

that represents the diversity of indicators or item

questions in linear regression analysis. To obtain an

acceptable factor score it is necessary to examine

factor analysis such as a loading factor above 0.50,

KMO above 0.50, and a significance test for Bartlett's

test.

Other tests used for data analysis in this study are

several classic assumption tests such as

multicorrelation test, Homocystaticity/

Heterocedasticity test, normality test with Chi Square

test and Kolmogorov-Smirnov test, multiple linear

regression analysis, T test or partial test, and F test or

Simultaneous Test.

7 RESEARCH HYPOTHESIS AND

STATISTICAL HYPOTHESIS

The research hypothesis is as follows:

1. hypothesis of the relationship between advertising

variables and brand equity. The higher the

credibility of advertising variables, the effect on

brand equity will also be higher, and vice versa if

the credibility of the advertising variable is low,

the brand equity formed will also be low.

2. hypothesis of the relationship between direct

marketing variables and brand equity. The higher

the credibility of the direct marketing variable, the

higher the effect on brand equity, and vice versa

if the credibility of the direct marketing variable

is low, the brand equity formed will also be low.

3. The hypothesis of the relationship between

interactive marketing (internet / marketing) and

brand equity. The higher the credibility of

interactive marketing variables, the higher the

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effect on brand equity, and vice versa if the

credibility of the interactive marketing variable is

low, the brand equity formed will also be low.

4. Hypothesis of the variable sales promotion (sales

promotion) with brand equity. The higher the

credibility of the sales promotion variable, the

higher the effect on brand equity, and vice versa

if the credibility of the sales promotion variable is

low, the brand equity formed will also be low.

5. Hypothesis of the relationship between public

relations / public relations with brand equity. The

higher the credibility of public relations variables,

the higher the effect on brand equity, and vice

versa if the credibility of the variable public

relations is low, the brand equity formed will also

be low.

6. Hypothesis of personal selling relationships

(personal selling) with brand equity. The higher

the credibility of the personal sales variable, the

higher the effect on brand equity, and vice versa

if the credibility of the personal sales variable is

low, the brand equity formed will also be low.

The statistical hypothesis of this study uses the

calculation of the F statistical test and the T statistical

test to formulate the null hypothesis (H0) and the

alternative hypothesis (Ha), test the hypothesis, and

draw conclusions.

7.1 Statistic F Test

The F statistic test is used to show whether all the

independent variables entered into the model have a

joint influence on the dependent variable. The null

hypothesis (H0) that is to be tested in this study is

whether all the parameters in the model are zero, or:

H0: b1 = b2 = 0 (1)

The meaning is that whether all independent variables

are not a significant explanation of the dependent

variable. The alternative hypothesis (Ha) is not all

parameters simultaneously equal to zero, or:

Ha: b1 ≠

2 ≠ 0 (2)

The testing criteria are:

a. If F Count ≤ F Table, then H0 is accepted as

meaning not significant.

b. If F Count> F Table, then H0 is rejected and Ha is

accepted, meaning significant.

7.2 Statistic T Test

The T Statistic test is used to test whether the

correlation coefficient (r) has been determined

significant/ meaningful or not before determining /

concluding the results of the research. The

significance level used in this study is two-way at

degrees 0.05 or α = 0.05. The null hypothesis (H0) to

be tested is whether a parameter (bi) equals zero, or:

H0: bi = 0 (3)

The meaning is whether an independent variable is

not a significant explanation for the dependent

variable. The alternative hypothesis (Ha) is that the

parameter of a variable is not equal to zero, or:

H0: b1 ≠ 0 (4)

The means that the variable is a significant

explanation of the dependent variable. The statistical

test used per variable is the t test which is calculated

by the test criteria formula as follows:

a. H0 is accepted if t count <t table.

b. H0 is rejected if t count> t table.

8 RESULTS

8.1 Demographic Information

Table 1: Respondents Gender Information.

Gender Number of Respondents Percentage

Male 120 59

Female 82 41

Total 202 100

Table 2: Respondents Age Information.

Age Number of Respondents Percentage

18-25 Years 20 10”

26-30 Years 40 20

31-40 Years” 128” 63”

Over 41 Years” 14 7

Total” 202 100 ”

Table 3: Respondents Education Information.

Education Number of Respondents Percentage

Senior High School or

Equals

12 6

Diploma Degree 6 3

Bachelor’s Degree” 158 78

Master’s Degree 26 13

Total” 202 100

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Table 4: Respondents Income Information for Savings and

Investments.

Income for savings and

investments (Rupiah Per Month)

Number of

Respondents

Percentage

Under Rp1.000.000 56 28

Rp1.000.000 – Rp2.500.000 73 36

Rp2.600.000 – Rp4.900.000 36 18

Rp5.000.000 – Rp7.000.000 14 7

Over Rp7.000.000 23 11

Total” 202 100

According to the Table 1 – Table 4, the findings

revealed that the majority of respondents were male

(59 percent), aged between 31 – 40 years old (63

percent), holding bachelor’s degree (78 percent), and

spent Rp1.000.000 – Rp2.500.00 for savings and

investments.

8.2 Validity and Reliability Test

Results

Validity analysis was conducted to measure the

validity and feasibility of the questionnaire, to ensure

the validity of the questionnaire. Validity test using

Pearson Product Moment method by comparing r

count and r table. If r count or correlation value is

greater than r table, then the research question is

valid. For the implementation of a validity test of 30

people, then r table is 0.349. The results of the validity

test of this research are:

- The range of the advertising variable r value is

0.606 to 0.724 so it can be concluded that the 8

questions of the questionnaire for the Advertising

variable are valid.

- The range of the direct marketing variable r value

is 0.577 to 0.679 so it can be concluded that the 7

questions of the questionnaire for the Direct

Marketing variable are valid.

- The range of r value for Interactive / Internet

Marketing variables is 0.607 to 0.702 so it can be

concluded that the 9 questions of the

questionnaire for the Interactive / Internet

Marketing variables are valid.

- The range of r value for calculating the Sales

Promotion variable is 0.587 to 0.719 so it can be

concluded that the 4 questions of the

questionnaire for the Sales Promotion variable are

valid.

- The range of the calculated r value in the Publicity

/ Public Relations variable is 0.604 to 0.690 so it

can be concluded that the 4 questions of the

questionnaire for the Publicity / Public Relations

variable are valid.

- The range of the calculated r value on the Personal

Selling variable is 0.678 to 0.725 so it can be

concluded that the 5 questions of the

questionnaire for the Personal Selling variable

questions are valid.

- The range of the calculated r value in the Brand

Equity variable is 0.548 to 0.759 so it can be

concluded that the 21 questions of the

questionnaire for the Brand Equity variable are

valid.

The SPSS software with the Cronbach Alpha method

is used to test the reliability of this research

instrument.

Table 5: Instrument Reliability Test Results.

Variables Cronbach Alpha Value

Advertising 0,886

Direct Marketing 0,860

Interactive/Internet Marketing 0,897

Sales Promotion 0,826

Publicity/Public Relations 0,826

Personal Selling 0,869

Brand Equity 0,841

From a variety of research, an acceptable alpha

values range is from 0.70 to 0.90. While the

maximum recommended alpha value is 0.90, so that

reliability is considered perfect and suggest all items

are reliable and all tests consistently have strong

reliability. From the results of the instrument

reliability test of each variable, the value of Cronbach

Alpha is obtained with a range between 0.826 to

0.897 which indicates that the instrument is very

reliable.

8.3 Factor Analysis Results

The purpose of using factor analysis in this study is to

create a single score that represents the diversity of

indicators or item questions in linear regression

analysis. Each dependent, bound, or free variable

must be represented by a single score, or what is

called in factor analysis as a factor score. The factor

score is a linear combination of the value of the

loading factor which represents the diversity of

question items. The higher the loading factor value,

the higher the level of diversity in creating a factor

score. To obtain an acceptable factor score it is

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necessary to examine factor analysis such as a loading

factor above 0.50, KMO above 0.50, and a

significance test for Bartlett's test less than 0,05.

Table 6: Loading Factor Analysis, KMO, and Significance

Bartlett’s Test Results.

Variable

Number of

Valid Items

Facto

KMO

Significance

Barlett's Test

Advertising 8

0,704 -

0,807

0,885 0,000

Direct

Marketing

0,693 -

0,784

0,890 0,000

Interactive/

Internet

Marketing

0,693 -

0,775

0,926 0,000

Sales

Promotion

0,760 -

0,859

0,802 0,000

Publicity/

Public

Relations

0,774 -

0,838

0,804 0,000

Personal

Selling

0,782 -

0,835

0,858 0,000

Brand Equity –

Brand Loyalty

0,683 -

0,797

0,861 0,000

Brand Equity –

Brand

Awareness

0,715 -

0,824

0,800 0,000

Brand Equity –

Perceived

Quality

0,714 -

0,831

0,842 0,000

Brand Equity -

Brand

Association

0,771 -

0,827

0,863 0,000

The results in Table 6 show that all variables

represent the diversity of indicators or question items

for linear regression analysis based on a range of

factor loading values above 0,50, KMO values above

0,50 and the significance value of Bartlett's test less

than 0,05.

8.4 Classic Assumption Test Results

8.4.1 Multicorrelation Test Results

The first classic assumption test is to test

multicorrelation to find out whether the relationships

between independent variables have multicorrelation

problems (symptoms of multicollinearity) or not. To

find out whether or not multicollinearity can use the

value of VIF (Variance Inflation Factory). Symptoms

of multicollinearity occur when the tolerance value is

less than 0.1 or VIF is more than 10.

Table 7: Multicorrelation Test Results.

Model

Collinearity

Statistics

Tolerance VIF

1 (Constant)

Advertising .330 3.026

Direct Marketing .233 4.288

Interactive/ Internet Marketing .235 4.260

Sales Promotion .323 3.092

Publicity/ Public Relation .314 3.182

Personal Selling .260 3.842

a. Dependent Variable: Y: Brand Equity

The results of the multicorrelation test through the

SPSS system above show that the tolerance values of

all the X variables to variable Y are less than 0.1 and

VIF values are less than 10 so that multicollinearity

does not occur or there is no high correlation between

all of the X variables which are the independent

variables.

8.4.2 Homocystaticity/ Heterocedasticity

Test Results

Homocystaticity / heterocedasticity test is a test that

assesses whether there is an inequality of variants

from residuals for all observations in the linear

regression model. This test is one of the classic

assumption tests that must be done in linear

regression analysis. If heterocedasticity assumptions

are not fulfilled, then the regression model is declared

invalid as a forecasting tool.

Detecting the presence or absence of

heterocedasticity is done by looking at a scatterplot

diagram. If there are certain patterns, such as dots that

form a certain pattern and are regular (wavy, widened

and then narrowed) then heterocedasticity occurs. If

there is no clear pattern, and the spread points occur

homocystaticity or heterocedasticity does not occur.

Figure 1: Homocystaticity / heterocedaticity test results.

Based on the scatterplot diagram as in Figure 1, it

can be seen that the data does not form a particular

pattern (irregularly dispersed) or in other words the

research model is homocedasticity. This means that

the research model is free from heterocedasticity

problems.

The Effectiveness of the Indonesia Stock Exchange’s Marketing Communication Program: Yuk Nabung Saham

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8.4.3 Normality Test Results

The normality test is to see whether the residual value

is normally distributed or not. A good regression

model is to have a residual value that is normally

distributed. The normality test was carried out by

looking at the results of the residual distribution plot

from the research data, and using the Kolmogorov-

Smirnov test. The following Figure 2 are the results

of the residual distribution plot from the research

data:

Figure 2: Normality Test Results.

Next is the normality test that carried out on the

residual value and not on each variable using the

Kolmogorov-Smirnov test. The following figure 3

shows the results of the Kolmogorov-Smirnov test:

Figure 3: Kolmogorov-Smirnov Normality Test Results.

If the probability or significance value is more

than 0.05 then the data is normally distributed, and if

the probability or significance value is less than 0.05

then the data is not normally distributed. From the

Kolmogorov-Smirnov test results obtained a

significance value above 0.05, which is 0.200. This

means that the distribution of residual data is

normally distributed.

8.5 Hypothesis Testing

8.5.1 Multiple Regression Analysis

Multiple linear regression analysis is used to see

whether there is an influence between Integrated

Marketing Communication and Brand Equity.

Testing this hypothesis is done through simultaneous

significance test or simultaneous test (F statistical

test), significance test for individual parameters or

partial test (T statistical test), and test the coefficient

of determination (R square). The multiple regression

equation in this study is formulated with the

following models:

(5)

Information:

Y: Brand Equity (dependent)

a: Constant value

b: Regression Coefficient Value

X1: Advertising

X2: Direct Marketing

X3: Interactive/ Internet Marketing

X4: Sales Promotion

X5: Publicity/ Public Relations

X6: Personal Selling

Table 8: Multiple Regression Analysis Results.

Coefficients

Model

Unstandardized

Coefficients

Standardized

Coefficients

Std.

Erro

Beta

(Constant)

.079 .074

X1: Advertising .230 .041 .227

X2: Direct Marketing .286 .045 .306

X3: Interactive/ Internet

Marketing

.087 .045 .093

X4: Sales Promotion .050 .034 .060

X5: Publicity/ Public

Relations

.148 .038 .164

X6: Personal Selling .182 .041 .204

a. Dependent Variable: Y: Ekuitas Mere

Based on the table 8 the equation is obtained as

follows:



Y=a+b1X1+b2X2+b3X3+b4X4+b5X5+b6X6

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(6)

Explanation of the equation is:

- The value of 0.230 X1 is the variable regression

coefficient of Advertising variable, which means

that every addition of 1 value or number for

Advertising it will increase Brand Equity by

0.230.

- The value of 0.286 X2 is the regression coefficient

value of Direct Marketing variable, which means

that every addition of 1 value or number for Direct

Marketing, it will increase the Brand Equity by

0.286.

- The value of 0.087 X3 is the regression coefficient

value of Interactive/ Internet Marketing variable,

which means that every addition of 1 value or

number for Interactive Marketing will increase the

Brand Equity by 0.087.

- The value of 0.050 X4 is the regression coefficient

value of Sales Promotion variable, which means

that every addition of 1 value or number for Sales

Promotion will increase Brand Equity by 0.050.

- Value of 0.148 X5 is the regression coefficient

value of Publicity/ Public Relations variable,

which means that every time there is an addition

of 1 value or number for Publicity/ Public

Relations, it will increase Brand Equity by 0.148.

- The value of 0.182 X6 is the regression coefficient

value of Personal Selling variable, which means

that every addition of 1 value or number for

Personal Selling will increase the Brand Equity by

0.182.

8.5.2 Simultaneous Test / F Test Results

Simultaneous test or F statistical test is intended to

test whether the independent variables included in the

model have a significant effect together on the

dependent variable. The null hypothesis (H0) that is

to be tested is whether all parameters in the model are

zero, in the sense that all independent variables are

not significant explanations of the dependent

variable. The alternative hypothesis (Ha) is not all

parameters simultaneously equal to zero.

The testing criteria are, if F Count is less or equal

to (≤) F Table or its significance value is more than

(>) 0.05, then H0 is accepted meaning not significant,

and if F Calculate more than (>) F Table or less

significance value from (<) 0.05, H0 is rejected and

H1 is accepted, meaning significant.

a. Dependent Variable: Y: Brand Equity

b. Predictors: (Constant), X6: Personal Selling, X4: Sales

Promotion, X5: Publicity/ Public Relation, X1: Advertising, X3:

Interactive/ Internet Marketing, X2: Direct Marketing

Figure 4: Annova Test Results.

From the results of the ANOVA test as in figure

4, the F statistic value of 274,286 with the calculated

F value is more than F table or the significance value

is less than 0.05, which is 0,000. This means that H0

is rejected and H1 is accepted, which means that the

independent variables namely Advertising, Direct

Marketing, Interactive / Internet Marketing, Sales

Promotion, Publicity / Public Relations, and Personal

Selling, together have a significant effect on the

dependent variable: Brand Equity.

8.5.3 Partial Test / T Test Results

The significance test of individual parameters or

partial test or T test was intended to test whether the

independent variables partially have a significant

effect on the dependent variable.

The hypotheses to be tested are as follows:

H0: Variable Advertising, Direct Marketing,

Interactive/ Internet Marketing, Sales Promotion,

Publicity/ Public Relations, and Personal Selling,

partially do not have a significant effect on Brand

Equity.

Ha: Variable Advertising, Direct Marketing,

Interactive/ Internet Marketing, Sales Promotion,

Publicity/ Public Relations, and Personal Selling,

partially have a significant effect on Brand Equity.

Table 9: Correlation Between Advertising, Direct

Marketing, Interactive/ Internet Marketing, Sales

Promotion, Publicity/ Public Relations, and Personal

Selling, and Brand Equity of The Firm Based on Partial Test

or T Test Results.

Integrated Marketing

Communication (IMC) Variables

Correlation with The Brand

Equity

Advertising

.000*

Direct Marketing

.000*

Interactive/ Internet Marketing

.054

Sales Promotion

.146

Publicity/ Public Relations

.000*

Personal Selling

.000*

*significant level at .05

Y = a + 0,230 X1 + 0,286 X2 + 0,087 X3 + 0,050 X4 +

0,148 X5 + 0,182 X6”

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The result is shown in table 9 that advertising,

direct marketing, publicity/ public relations, and

personal selling were directly related to brand equity.

In contrast, interactive/ internet marketing and sales

promotion were the tools which was not related to

brand equity.

8.5.4 Determination Coefficient Test (R

Squared) Results

Below was the result of testing of the Determination

Coefficient (R Squared) of all X variables in the

model against the variation of Y variable, to measure

the contribution of all independent variables (X) in

the model to the dependent variable (Y):

Table 10: Determination Coefficient Test (R Squared)

Results.

Model Summary

Model R R Square

Adjusted R

Square

Std. error of

the Estimate

1 .946

.894 .891 .14892

a. Predictors: (Constant), X6: Personal Selling, X4: Sales

Promotion, X5: Publicity/ Public Relations, X1: Advertising, X3:

Interactive/ Internet Marketing, X2: Direct Marketing

. Dependent Variable: Y: Brand Equity

The value of R Squared of 0.894 in the table above

shows that 89.4 percent of the variance Y can be

explained by changes in the variable Advertising -

X1, Direct Marketing - X2, Interactive/ Internet

Marketing - X3, Sales Promotion - X4, Publicity/

Public Relations - X5, and Personal Selling - X6.

While the remaining 10.6 percent was explained by

other factors outside the linear regression model of

this study.

9 CONCLUSIONS

After conducting research with survey methods and

data analysis with multiple linear regression tests, the

results of the study were as follows:

1. The IDX’s Yuk Nabung Saham Program so far

can be said to have run effectively along with the

increasing public awareness to invest in the

capital market and the growing number of stock

investors on the IDX significantly, especially

since the Yuk Nabung Saham campaign was

launched on 12 November 2015 with the growth

in the number of investors has grown 91,06

percent from 434,107 single investor

identification (SID) at the end of 2015 to 829,426

SID as of November 19, 2018.

2. The marketing communication strategy carried

out by IDX has effectively built brand equity from

Yuk Nabung Saham, especially to the target

population of Capital Market School participants

in Jabodetabek during the October 2018 period.

This is reflected in the data of the majority of

respondents in this study who have been able to

know and understand well information about

capital market products and Yuk Nabung Saham

campaigns and are interested in trying to save

shares and become investors in the Indonesian

capital market. The interest was because the

respondents had seen the Yuk Nabung Saham

advertisement in electronic media (TV, radio and

videotron), were interested and had participated in

and became IDX Capital Market School

participants which led to the opening of stock

accounts, and BEI trainer explanations in the

Capital Market School about investment capital

market and investment to the capital market.

3. From the results of multiple linear regression it

was concluded that there are a relationship and the

relationship between the integrated marketing

communication strategy carried out by the IDX

with brand equity from The Yuk Nabung Saham.

The results of this study were certainly in line with

the theory used by this study, namely Integrated

Marketing Communication theory from Belch and

Belch (2003) and Brand Equity Theory from

Aaker (2017). The results of this study have also

been in line with the results of previous studies

conducted by Brunello (2013) and Mongkol

(2014) which agreed that organizations could

create brand equity by implementing integrated

marketing communication. However there are

differences in the results of this research with

previous research, namely at the level of the

integrated mix of promotional marketing

communications that most significantly influence

the increase in brand equity of research subjects.

For example, a study conducted by Mongkol

(2014) which saw that all variables other than

advertising variables had a significant effect on

the formation of brand equity. Where as in this

study the integrated marketing communication

promotion mix which has a significant effect on

the formation of brand equity from Yuk Nabung

Saham was Advertising, Direct Marketing,

Publicity/ Public Relations, and Personal Selling.

There are two variables that have no significant

effect on brand equity, namely Interactive/

Internet Marketing, and Sales Promotion. Overall

brand equity in this study can be explained by the

Integrated Marketing Communication variable

through the Determination Coefficient test (R

ICIB 2019 - The 2nd International Conference on Inclusive Business in the Changing World

216

Squared) with a value of 0.891. This indicates that

89 percent of variations that occur in the high and

low brand equity were caused by changes in

Advertising, Direct Marketing, Interactive/

Internet Marketing, Sales Promotion, Publicity/

Public Relations, and Personal Selling. While the

remaining 10.6 percent was explained by other

factors outside of this research variable.

10 RECOMMENDATION

1. Exploration of research can be more focused on

other marketing strategies that might be able to

create more brand equity in the company besides

Integrated Marketing Communication.

2. The results of this study can be applied in different

industries to confirm the results of research

whether integrated marketing communication can

have a significant effect on the brand equity of a

company, industry, or strategy/ company

campaign.

3. Further research can also use qualitative studies in

depth to help a researcher better understand the

creation of brand equity, especially in the capital

market industry.

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Belch, George E., dan Belch, Michael A., 2003.

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Brunello, Adrien., 2013. The Relationship Between

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Gogtay, NJ, Thatte, UM., 2017. Principles of Correlation

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