14 chapter iii research methodology 3.1 research...

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14 CHAPTER III

RESEARCH METHODOLOGY

3.1 Research Method

According to Sugiyono (2009, p. 9), there are three kinds of research methods based

on natural settings object level, they are: experimental research, survey, and

naturalistic. The experimental research method is very unnatural because it is done in

a laboratory where the condition is controlled so that it is free from external influences.

Survey research methods are conducted in public places, which is naturalistic (not

artificial), but researchers conduct treatment when collecting data such as surveys and

interviews. While naturalistic research method is done in a natural place and without

any treatment from researchers for collecting data.

Sugiyono (2009, p. 11) further argued that the naturalistic method is qualitative

while experimental and survey methods are quantitative. Quantitative research is

research used to examine a population or a particular sample with data collection is

generally done randomly, using research instruments for data collection, as well as

statistical data analysis for testing the research’s hypothesis (Sugiyono, 2009, p. 12).

The object of this research is the consumers Bank Syariah Mandiri in Bandung. This

research is conducted in a public place and use the questionnaire as the tool to collect

data. The data then processed using Structural Equation Modeling, a multivariate

statistical analysis. Therefore the method in this research is surveys and it is

quantitative.

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However, this study also uses the qualitative method, namely literature study for

collecting data. According to Sugiyono (2009, p. 422), a result of a research will be

more credible if the results are supported by data from documents that have high

credibility.

To achieve convincing results, this study collects data from documents that are still

related to research variables by using literature study techniques. These documents

include company reports, reports from survey agencies, and reports from state

institutions, books, and international journals.

3.2 Operational Variable

According to Sugiyono (2009, pp. 59–61), there are five kinds of variables in a

study, namely independent, dependent, moderator, control, and intervening.

Sugiyono (2009, p. 59) stated that the independent variable is a variable that

influences or causes change on the dependent variable. In SEM independent variable

is referred to as an exogenous variable. There are two independent variables in this

research which are Religiosity (X1) and Corporate Reputation (X2).

Sugiyono (2009, p. 59) added, the dependent variable is a variable that is influenced,

or it is a result of the existence of an independent variable. In SEM dependent variable

is referred to as endogenous variable. In this research Consumer Loyalty (Y) is the

dependent variable.

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The following is the independent variables and a dependent variable of this research

along with its indicators:

1. Religiosity as the independent variable (X1), with an indicator as follow:

Intrapersonal Religiosity (X1.1)

2. Corporate reputation as the independent variable (X2), with indicators as

follow:

Emotional Appeal (X2.1)

Products and Services (X2.2)

Social Responsibility (X2.3)

3. Consumer loyalty as the dependent variable (Y), with indicators as follows:

Cognitive Loyalty (Y.1)

Affective Loyalty (Y.2)

Conative Loyalty (Y.3)

Action Loyalty (Y.4)

Based on the theoretical framework of this study, the operationalization variable

of this study can be made as follow:

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Table 3.17

Operational Variable

Dimension Concept Indicator Measurement Questionnaire item Questionnaire

Code

Religiosity (X1)

The extent to which an individual is committed to the religion he or she professes and its teaching, such that the individual’s attitude and behaviors reflect this commitment (Johnson et al. (2001) in Mokhlis & Sparks (2007, p. 90)

Intrapersonal

Religiosity (X1.1) intrapersonal religiosity centers on an individual's religious beliefs and individual religious experiences (Mokhlis, 2009, p. 92)

The intensity of reading

books about religion

The frequency of reading

books about Islam

Saya sering membaca buku

mengenai agama Islam X1.1.1

Passion for

understanding the

teaching of religion

Level of passion for understanding Islam

Saya bersemangat untuk

memahami ajaran- ajaran Islam X1.1.2

The belief of the importance of religion as

the answer to the

question of the meaning of life

Level of belief in the

importance of Islam as

the answer for life

Saya yakin Islam bisa memberikan jawaban mengenai

makna kehidupan X1.1.3

The belief that religion

must be lies behind all

approach in life

Level of putting Islam

behind all approaches in

life

Saya menjadikan Islam

melatarbelakangi seluruh pendekatan saya dalam hidup

terutama di bidang ekonomi

X1.1.4

The belief that religion affects all affairs in life

Level of the belief that

Islam affects the whole affairs of life

Saya menjadikan Islam

mempegaruhi seluruh urusan kehidupan saya terutama dalam

urusan keuangan

X1.1.5

Spare some time to

reflect and think deeply

about religion

The frequency for taking

the time to think deeply

about Islam

Saya sering meluangkan waktu

untuk merenung secara mendalam

mengenai agama Islam

X1.1.6

Corporate Reputation (X2)

A collective assessment of a company's ability to provide valued outcomes to a representative group of stakeholders. (Fombrun et al., 2000, p. 243)

Emotional Appeal

(X2.1)

stakeholder assessment of the company that based on feelings (Fombrun et al., 2000, p. 253)

Good feeling about the company

Level of like on company Saya memiliki rasa suka terhadap Bank Syariah Mandiri

X2.1.1

Admired the company Level of admiring on

company

Saya memiliki rasa kagum

terhadap Bank Syariah Mandiri X2.1.2

Trust the company Level of trust on company

Saya memiliki rasa percayakepada Bank Syariah Mandiri

X2.1.3

Product and

services (X2.2)

stakeholder assessment of products and services provided by the company (Fombrun et al., 2000, p. 253)

Stand behind product or

service

Level of company’s

responsibility on its

products

Menurut saya pelayanan yang diberikan Bank Syariah Mandiri

untuk produk tabungan BSM

sesuai dengan apa yang Bank Syariah Mandiri dijanjikan

X2.2.1

Offers high quality

product and services

Level of product’s

quality

Menurut saya pelayanan produk

tabungan BSM yang diberikan

Bank Syariah Mandiri berkualitas tinggi

X2.2.2

Offers product or

services that are good

value for money

Level of profit sharing

Menurut saya tabungan BSM

Bank Syariah Mandiri memberikan keuntungan berupa

bagi hasil yang tinggi

X2.2.3

Develops innovative

product or service

Level of innovation on

product

Menurut saya Bank Syariah Mandiri selalu melakukan inovasi

dalam memperbaiki pelayan

produk tabungan BSM

X2.2.4

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Social

responsibility (X2.3)

the manifestation of company's attitudes as a good citizen by supporting positive things that exist around the company's

environment (Sasmita, 2012, p. 9)

Support good causes

Level of concerns on

positive things in community

Bank Syariah Mandiri mendukung

hal positif di masyarakat dengan

mendukung pertumbuhan Usaha Mikro Kecil dan Menengah

(UMKM)

X2.3.1

Environmentally responsible

Level of concerns on environment

Bank Syariah Mandiri menunjukan kepedulian terhadap

lingkunan dengan melakukan

penghijauan lingkungan melalui

program CSR

X2.3.2

Threats people well Level of concerns on

ummah

Bank Syariah Mandiri

memperlakukan umat dengan baik

melalui penyaluran bantuan CSR kepada masjid-masjid di

Indonesia

X2.3.3

Consumer Loyalty (Y)

loyalty is a sequence of effects, with behavioural (action) loyalty as the outcome from a set of loyalty phases which constitute of cognitive loyalty, affective loyalty, and intention (conative) loyalty (Oliver, 1999, pp. 34–35)

Cognitive Loyalty

(Y1.1)

a belief that the product or brand consumed is better than a competitor's based on the consumer's evaluation of product or brand

attributes (Murdalis, 2005, p. 112)

The quality of Services

given by the company compared to competitor

The quality of service

given by company compare to other banks

Menurut saya tingkat pelayanan tabungan BSM Bank Syariah

Mandiri lebih baik dibandingkan

bank lain

Y1.1.1

Benefits obtained in

using product compared

to competitor

Level of profit sharing

given compare to other

banks

Menurut saya tingkat bagi hasil

yang saya terima dari tabungan

BSM Bank Syariah Mandiri lebih

besar dibandingkan tabungan

bank lain

Y1.1.2

The product used is better

compared to other banks

Ability to compete with other bank’s saving

Menurut saya tabungan BSM

Bank Syariah Mandiri lebih baik dibandingkan tabungan milik

bank lain

Y1.1.3

Affective Loyalty (Y1.2)

a liking or attitude toward the brand or product that has developed from cumulatively satisfying usage occasions (Oliver, 1999, p. 35)

The sense of like that

consumer has for

products that arise after being satisfied

consuming the product

Level of like on product

Saya memiliki rasa ketertarikan

terhadap tabungan BSM Bank

Syariah Mandiri karena saya merasa puas setelah menggunakan

produk tersebut

Y1.2.1

The sense of happiness that consumers have for

the product after being

satisfied consuming the product

Level of happiness in using product

Saya merasa senang menggunakan tabungan BSM

Bank Syariah Mandiri karena

merasa saya puas menggunakan produk tersebut

Y1.2.2

The sense of emotional

attachment that

consumers have for the product after being

satisfied consuming the product

Level of attached towards product

Saya merasa terikat secara

emosional kepada tabungan BSM

Bank Syariah Mandiri karena saya merasa puas menggunakan produk

tersebut

Y1.2.3

Conative Loyalty

(Y1.3) the commitment of consumer to be loyal to the product or brand (Oliver, 1999, p. 35)

Intention to keep using the product for the future

times

The level of intention to

keep using the product in

the future

Saya berniat untuk tetap menggunakan tabungan BSM

bank Syariah Mandiri di masa

yang akan datang

Y1.3.1

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Intention to buy other

product lines offered by

the company

Level of intention to buy other product lines

Saya berniat menggunakan

produk-produk lain yang disediakan oleh Bank Syariah

Mandiri

Y1.3.2

Intentions to recommend

products to others

Level of intentions to

recommend products to others

Saya berniat merekomendasikan

tabungan Bank Syariah Mandiri kepada orang lain

Y1.3.3

Action Loyalty (Y1.4)

real actions were taken by the consumer to be loyal in the form of consumer readiness to overcome obstacles that can prevent

consumers to be loyal (Oliver, 1999, p. 35)

Willingness to pay more

for the product

Level of willingness to

pay more for the product

Saya tetap menggunakan

tabungan BSM Bank Syariah

Mandiri walaupun biaya

administrasi tabungan mengalami

kenaikan

Y1.4.1

Tells positive things

about the product to

others

The desire to tells

positive things about the

product to others

Saya memberitahukan hal positif

mengenai keunggulan tabungan

BSM Bank Syariah Mandiri kepada orang lain meskipun

beredar isu negative mengenai

Bank Syariah Mandiri

Y1.4.2

Make product as the main choice

Level of willingness to

make product as the main

choice

Saya menjadikan tabungan BSM Bank Syariah Mandiri sebagai

pilihan utama meskipun adanya

tawaran-tawaran menarik dari bank lain

Y1.4.3

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3.3 Data Source, Determination, and Obtaining

3.3.1 Data Source

According to Sugiyono (2009, p. 137), based on its source, there are two

types of data, namely primary and secondary data. Primary data is data obtained

by collecting data directly from the data source. On the contrary, secondary data

is data obtained indirectly from data sources, but through other media such as

reports.

This study uses both primary and secondary data. The primary data in this

research obtained through questionnaires from consumers of Bank Syariah

Mandiri Bandung. While the secondary data in this study comes from literature

such as scientific journals and books, as well as reports on Islamic banking

published by government agencies, survey agencies, companies, and

consultants.

3.3.2 Data Determination

Population is a generalisation area that includes objects/subjects that have

a particular characteristic set by to be studied and then taken the conclusion.

Population includes not only the number of the population but also includes the

characteristics of the object/subject being studied (Sugiyono, 2009, p. 15). The

population of this research is the consumers of Bank Syariah Mandiri in

Bandung.

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There are eleven Bank Syariah Mandiri outlet networks in Bandung. The

eleven outlet networks consist of two branches, seven sub-branches, and two

cash offices.

Table 3.28

Bank Syariah Mandiri Outlet Network in Bandung No Bank Syariah Mandiri Outlet in Bandung

1 Bandung Antapani Sub-branch

2 Bandung Ujung Berung Sub-branch

3 Metro Margahayu Sub-branch

4 Rumah Sakit Al Islam Cash Office

5 Bandung Pajajaran Sub-branch

6 Bandung Setia Budi Sub-branch

7 Japati Cash Office

8 Bandung Dago Branch

9 Bandung Moh Toha Sub-branch

10 Bandung Ahmad Yani Branch

11 Bandung Buah Batu Sub-branch

Source: syariahmandiri.co.id (2017)

The huge number of Bank Syariah Mandiri consumers in Bandung makes

it impossible to study all that is in the population. With limited time, funds, and

energy, this research took samples from the population. According to Sugiyono

(2009, p. 115), the sample is part of the number and characteristics in a

population. What is studied from the sample, the conclusions can be applied to

the population.

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Hair et al., (2010, p. 47) stated that the number of samples needs to be taken

from research that uses multivariate analysis is at least five times the number of

parameters/indicators used in research. Based on this calculation, the minimal

number of respondents need to be taken for this study are:

n = numbers of indicators x 5

n = 28 x 5

n = 140

So a minimal number of sample needed in this study are as many as 140

respondents.

This study uses a proportional purposive sampling technique; this sampling

technique determines based on specific considerations (Sugiyono, 2009, p.

122). The considerations used in determining the sample of this research are:

1. Respondent is a Muslim

2. Respondent is domiciled in Bandung

3. Respondent uses BSM saving

The consideration of making BSM savings consumers as respondent is

because saving BSM is the product most in demand by consumers (Syariah

Mandiri 2016, p. 69). Therefore, it is expected that the data collection process

will be easier because there are many users of BSM savings. In addition, BSM

savings is the featured product of Bank Syariah Mandiri.

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Bank Syariah Mandiri Bandung don’t provide data about the number of

consumers that they have because it is a company’s secret. Therefore, the

observations were made to each branch office (KC), sub-branch office (KCP),

and cash office (KK) to obtain the average number of consumers who perform

transactions per day by interviewing bank tellers and security officers. Here are

the average number of consumers per day which made transactions in each

outlet of Bank Syariah Mandiri in Bandung.

Table 3.39

Average Number of Consumers Performing Transactions per Day in each

Outlet of Bank Syariah Mandiri Bandung Name of Outlet Average Number of Consumers Performing

Transactions per Day

Bandung Antapani Sub-branch 100

Bandung Ujung Berung Sub-branch 90

Metro Margahayu Sub-branch 130

Rumah Sakit Al Islam Cash Office 50

Bandung Pajajaran Sub-branch 80

Bandung Setia Budi Sub-branch 120

Japati Cash Office 50

Bandung Dago Branch 150

Bandung Moh Toha Sub-branch 100

Bandung Ahmad Yani Branch 100

Bandung Buah Batu Sub-branch 130

Total 1100

Source: Interview with teller and security in every Bank Syariah Mandiri

Bandung

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After knowing the population and the minimum number of samples need

to be taken, then it was necessary to determine the number of samples

proportionally for each outlet using purposive sampling formula (Sugiyono,

2009, p. 128).

𝑛𝑖 =𝑁𝑖

n𝑁

Explanation:

ni = the number of samples that need to be taken for a particular

outlet

Ni = the population in a particular outlet

n = Total population of every outlet

N = the number of samples that needed for the research

By using purposive sampling formula, here are the number of samples

needed for each outlet of Bank Syariah Mandiri in Bandung:

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Table 3.410

The Number of Samples Need to Be Taken for Each Bank Syariah

Mandiri Outlet in Bandung Name of Outlet Average Number of Consumers

Performing Transactions per Day

Number of Samples

Need to Be Taken

Bandung Antapani Sub-branch 100 13

Bandung Ujung Berung Sub-branch 90 11

Metro Margahayu Sub-branch 130 17

Rumah Sakit Al Islam Cash Office 50 6

Bandung Pajajaran Sub-branch 80 10

Bandung Setia Budi Sub-branch 120 15

Japati Cash Office 50 6

Bandung Dago Branch 150 19

Bandung Moh Toha Sub-branch 100 13

Bandung Ahmad Yani Branch 100 13

Bandung Buah Batu Sub-branch 130 17

Total 1100 140

3.3.3 Data Collecting

This research use questionnaire techniques to collect data as explained

earlier. According to Sugiyono (2009, p. 199), questionnaires is a technique of

data collection by providing a set of questions or statements for respondents to

answer. The questionnaire is an efficient data collection technique, suitable for

large numbers of respondents that are spread over a large area. Questionnaires

can be given to respondents directly, by mail, or via the internet (online). Uma

Sekaran (1992) in Sugiyono (2009, p. 200) stated, there are two types of

questions or statements in a questionnaire, namely open question and closed

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question. Open questions are questions that expect respondents to provide

answers in the form of a description. Meanwhile, closed questions are questions

that expect respondents to give a short answer or choose one alternative answer

to the question that available. The answer to a closed question can take the form

of ordinal data, nominal data, and interval data.

This research has the large sample size, which is 140 respondents, spread

to eleven outlet in Bandung. Therefore, the questionnaire is the suitable data

collection technique for this research. The questionnaire of this study was

distributed directly to the respondents in eleven Bank Syariah Mandiri outlets

in Bandung.

This research’s questionnaire is divided into two parts. The first part is the

questions about the respondent's personal information, such as sex, age,

occupation, and income. The second part is a set of questions to investigate the

influence of Religiosity and Corporate Reputation on Consumer Loyalty. The

answer to the statement on this part was measured using a Likert scale.

According to Sugiyono (2009, p. 132), the Likert scale is used for opinions,

attitudes, and perceptions of respondents about social phenomena. In this study

social phenomena has been explicitly defined by researchers in the form of

questionnaires based on research variables. The statements contained in the

second part of the research questionnaire are closed statement. Respondents

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were only required to respond to the statement on the scale available based on

respondents' opinions, attitudes, and perceptions.

Sugiyono (2009, p. 202) stated, empirically it is suggested the ideal amount

of item of question or statement for a questionnaire are 20 to 30. This research

questionnaire has 28 statement, and hence it can be said this questionnaire is

ideal.

3.4 Validity and Reliability Test

3.4.1 Validity Test

Based on Sarjono & Julianita (2015, p. 35), the validity test is used to gauge

the ability of indicator (manifest) to measure the research dimension (latent). If

a measurement has a high degree of validity, it means the measurement can

measure what it should be measured, and vice versa (Sugiyono, 2009, p. 172).

High validity also means respondents can understand the questions or

statements in the questionnaire.

According to Malhotra (2010) in Rinaldi (2013), there are three types of

validity test :

1. Content Validity

Content validity is the extent measurement represents the dimension of

variables. It shows whether the items in the questionaires represents the

construct appropriately.

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2. Cirterion Validity

It examines whether the measurement scale appears as expected in

relation to other variables, that chosen as research criteria.

3. Construct Validity

Construct validity examines the characteristic of the construct. It

measures based on the pattern of interrelationship between question

items in the construct. The items that measure the same construct should

have strong inter-correlations

This reseach uses content and construct validity. The content validity test

is done in this chapter, while contruct validity will be done in Chapter 4. This

study does not use criterion validity, because there are no specific measurement

criteria. According to Kane (2001) in Rinaldi (2013), the criteria validity is used

in a study if there was an appropriate criterion size.

Validity testing should be done on every item in a questionnaire. According

to Aaker et al., (2011) in Rinaldi (2013), content validity is done by using

Pearson product moment. This validity test in this reseach is done using SPSS

version 23. The criterias for an item of questionaire in order to be consider valid

are as follow:

1. If the value of rvalue is positive and rresult > rtable , the item in the questionaire

is considered to be valid

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2. If the value of rvalue is negative and rvalue < rtable , the item in the questionaire

is considered to be not valid

The coeficcient of rtable is come from product moment table with α = 5%

1. Content Validity Test on Religiosity

Table 3.5

Content Validity Test on Religiosity

Variable Item Item Indicator r

value Information

Religiosity

(X1)

X1.1.1 The intensity of reading books about religion 0.870 Valid

X1.1.2 Passion for understanding the teaching of religion 0.775 Valid

X1.1.3 The belief of the importance of religion as the

answer to the question of the meaning of life 0.739 Valid

X1.1.4 The belief that religion must be lies behind all

approach in life 0.830 Valid

X1.1.5 The belief that religion affects all affairs in life 0.864 Valid

X1.1.6 Spare some time to reflect and think deeply about

religion 0.772 Valid

Source: Processed Questionnaire Data

Note : item is valid by r value > 0.138

Based on Table 3.5, all items of Religiosity variable are valid. All the items

have positive rvalue and it is bigger than the value of rtable, which is 0.138.

Item X1.1.1 with indicator of intensity of reading books about religion, has

the highest rvalue, which is 0.870. Meanwhile, item X1.1.4 with indicator belief

of the importance of religion as the answer to the question of the meaning of

life, has the smallest rvalue, which is 0.739. It can be concluded that item X1.1.1

has the the best ability to measure Religiosity.

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2. Content Validity Test on Corporate Reputation

Table 3.6

Content Validity Test on Corporate Reputation

Variable Item Item Indicator r

value Information

Corporate

Reputation

(X2)

X2.1.1 Good feeling about the company 0.895 Valid

X2.1.2 Admired the company 0.912 Valid

X2.1.3 Trust the company 0.886 Valid

X2.2.1 Stand behind product or service 0.881 Valid

X2.2.2 Offers high quality product and services 0.901 Valid

X2.2.3 Offers product or services that are good value for

money 0.841 Valid

X2.2.4 Develops innovative product or service 0.850 Valid

X2.3.1 Support good causes 0.898 Valid

X2.3.2 Environmentally responsible 0.904 Valid

X2.3.3 Threats people well 0.908 Valid



Based on Table 3.6, all items of Corporate Reputation variable are valid. All

the items have positive rvalue and are bigger than the value of rtable, which is

0.138.

Item X2.1.2 with indicator admired the company , has the highest rvalue,

which is 0.912. Meanwhile, item X2.2.3 with indicator offers product or

services that are good value for money, has the samllest value of rvalue which is

0.841. It can be concluded that item X2.1.2 has the the best ability to measure

Corporate Reputation.

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3. Content Validity Test on Consumer Loyalty

Table 3.7

Content Validity Test on Consumer Loyalty

Variablele Item Item Indicator R value Information

Consumer

Loyalty (Y)

Y1.1.1 The quality of Services given by the company

compared to competitor 0.870 Valid

Y1.1.2 Benefits obtained in using product compared to competitor

0.876 Valid

Y1.1.3 The product used is better compared to other banks

0.914 Valid

Y1.2.1 The sense of like that consumer has for products that arise after being satisfied consuming the product

0.918 Valid

Y1.2.2 The sense of happiness that consumers have for the

product after being satisfied consuming the product 0.911 Valid

Y1.2.3 The sense of emotional attachment that consumers have for the product after being satisfied consuming the

product 0.889 Valid

Y1.3.1 Intention to keep using the product for the future times

0.879 Valid

Y1.3.2 Intention to buy other product lines offered by the

company 0.853 Valid

Y1.3.3 Intentions to recommend products to others 0.882 Valid

Y1.4.1 Willingness to pay more for the product 0.818 Valid

Y1.4.2 Tells positive things about the product to others 0.861 Valid

Y1.4.3 Make product as the main choice 0.865 Valid



Based on Table 3.6, all items of Consumer Loyalty variable are valid. All

the items have positive rvalue and are bigger than the value of rtable, which is

0.138.

Item Y1.2.1 with indicator the sense of like that consumer has for products

that arise after being satisfied consuming the product, has the highest rvalue,

which is 0.918. Meanwhile, item X1.4.1 with willingness to pay more for the

product, has the samllest value of rvalue which is 0.818. It can be concluded that

item X1.2.1 has the the best ability to measure Consumer Loyalty.

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3.4.2 Reliability Test

According to Sugiyono (2009, p. 172), the reliability test use to measure the

reliability of a research instrument. Instruments are said to be reliable when it

can generate the same data or result if it is use multiple times to measure the

same object. Meanwhile, according to Sarjono & Julianita (2015, p. 35), a

reliability test is performed to measure the consistency level of the manifest

variable (indicator) in measuring its latent construct (dimension).

Malhotra (2010, p. 319-320) in Rinaldi (2013) said there are three types of

reliability:

1. Test-restest reliability

Test-retest reliability is a an approach to assess a measurement

reliability by giving respondent the same measurement to respondent

at two different times. This method is used to test the reliability of

instruments over time.

2. Alternative form-reliability

Alternative form-reliability is an extended form of test-retest

reliability. The approach assess a measurement by giving the same

respondent two different types of same measurement at different

times.

3. Internal Consistency

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Internal consistency is the standard and commonly use to measure

item’s reliabilty. This method use cornbach’s alpha and only done in

one time.

Acoording to Streiner (2003, p.10) in Rinaldi (2013), internal consistency

reliablility is the most efficent method to test reability of a measurement. It does

not need two different types of the same measurement and only done once. This

research use internal consistency reliablity because it is more efficienct

compare to test-retest and alternative-form reliability. The internal consisteny

reability test is done by using SPSS version 23. Accroding to Malhotra

(2010:319), cornbach alpha measure based on cornach alpha scale from 0 to 1.

Below are the intepretation of the cornbach alpha value:

Corncah Alpha <0.60 means unreliable

Corncah Alpha 0.60 > α > 0.69 means marginal reliable

Corncah Alpha 0.70 > α > 0.79 means reliable

Corncah Alpha 0.80 > α > 0.89 means very reliable

Corncah Alpha > 0.90 means highly reliable

Table 3.8

Reliability Test on Research Variabe

Variable Reability

Coefficient nformation

Religiosity (X1) 0.861 Very Reliable

Corporate Reputation (X2) 0.939 Highly Reliable

Consumer Loyalty (Y) 0.944 Highly Reliable


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Based on Table 3.8, Religiosity, Corporate Reputation, and Consumer

Loyalty have cronbach alpha value > 0.6. Items of Corporate Reputation and

Consumer Loyalty is more consistent in measuring its variable compared to the

items of Religiosity. Overall, the items of reseach questionaires are very reliable

and this reseach can be conducted on future times.

3.4.3 Variable Measurement

As explained before, the answers to this research questionnaire are measured

with Likert scale. According to Sugiyono (2009, p. 132), the Likert scale is used

for measuring attitudes and perceptions of respondents about social phenomena.

In this research social phenomena have been specified by researchers in the

form of questionnaire statements based on research variables.

Furthermore Sugiyono (2009, p. 133) said that the answer to the question or

statement of the questionnaire using Likert scale has a gradation from very

positive to very negative. Gradation of answer from the Likert scale is as

follows:

a. Strongly agree

b. Agree

c. Neutral

d. Disagree

e. Strongly disagree

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Sugiyono (2009, p. 133) also said, for quantitative research, the answer

from the Likert scale can be scored from 1 to 5. The Analysis of answers done

by summing the scores obtained. For examples:

Table 3.9 Likert Scale

Answers Value

Highly Agree/Always/ Very Positive 5

Agree/Often/Positive 4

Doubt/Sometimes/Neutral 3

Disagree/ Almost Never/Negative 2

Highly Disagree/Never/Very Negative 1

3.5 Data Analysis and Hypothesis Testing

3.5.1 Frequency Analysis

According to Aaker et al., (2011) in Budiarsa (2017, p. 80), frequency

analysis is one of descriptive analysis that can provide description and

explanation about variables studied in a situation.

The purpose of this research is to obtain a description and explanation of

Religiosity, Corporate reputation, and Consumer Loyalty. To obtain the

description and explanation, the frequency analysis is done by counting the

answers of the respondents.

Frequency analysis in this research use steps belong to Riduwan & Kuncoro

(2008, p. 20-22), the steps are:

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1. Calculate answers from each item of questionnaire

2. Calculates the total score on each item questionnaire. This is done by

multiplying the frequency of respondents who answer on particular answer

with the answer value

3. Determine the ideal score for each item of the questionnaire. The number

of respondents in this research is 218 people, then the ideal score for each

item questionnaire is the highest value, which is five. The value is then

multiplied by the number of respondents. Then the ideal score for each item

questionnaire is 1090

4. Calculate Percentage of total score divided by the highest score on each

item questionnaire, with formula below :

Score percentage :Total Score of Each Item

Ideal Score of Each Item𝑥 100%

5. Calculates the percentage of total scores for each variable by using this

formula : 𝑇𝑜𝑡𝑎𝑙 𝑆𝑜𝑐𝑟𝑒 𝑜𝑓 𝑉𝑎𝑟𝑖𝑎𝑏𝑙𝑒

𝑇𝑜𝑡𝑎𝑙 𝑄𝑢𝑒𝑠𝑡𝑖𝑜𝑛𝑎𝑖𝑟𝑒 𝐼𝑡𝑒𝑚 𝑥 1000𝑥100%

6. Make interpretations based on five intervals (due to the five interval in the

instrument). The lowest precentage score tahn can be achieve is 20%, while

the highest is 100% . The range of intervals that can be divided is 80% with

a range per interval of 16% (80% divided by 5). The interpretation of the

total score based on the guidelines is listed in the following table:

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Table 3.10 Interpretation of Total Score Percentage

Total Score Percentage Score Limit Intepertation

20% - 36% 218 - 392 Very Weak

36.1% - 52% 393 – 566 Weak

52.1% - 68% 443 – 578 Medium

68.1% - 84% 742 – 915 Strong

84.1% - 100% 916 – 1090 Very Strong

3.5.2 Structural Equation Modeling

Structural Equational Modeling (SEM) is a multivariate analysis that can

perform three tests simultaneously, which are: testing the relationship between

latent variables and manifest variables, testing the relationship between latent

variables with other latent variables, and can expose measurement error

(Sarjono & Julianita, 2015, p. 1). According to Ghozali & Fuad(2014, p. 5), the

latent variable is a variable that cannot be measured directly and requires an

indicator as a proxy. While the manifest variable is the indicator of the

measured manifest variable.

Bollen (1989) in Ghozali & Fuad (2014, p. 3) added that, unlike multiple

regression and factor analysis, SEM could test two things simultaneously:

1. The relation between constructs (latent variables) independent and

dependent

2. Relationship (factor loading) between indicators (variable manifest) with

constructs (latent variables)

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Ghozali & Fuad (2014, p. 3)then added that the ability of the SEM allows

researchers to:

1. Testing the measurement instrument error which is an integral part of

SEM

2. Conducting hypothesis testing simultaneously by performing factor

analysis

SEM analysis in this research is done with software LISREL (Linear

Structural Relationship) version 8.8 (full version). According to Ghozali &

Fuad (2014, p. 4), LISREL is the only sophisticated SEM software program

that can identify various problems. SEM can even do things not be possible with

other SEM software like AMOS and EQS. Also, LISREL tends to be more

informative in presenting statistical results so that the cause of unfit of a model

and modification model can quickly be known.

According to Budiarsa (2017, p. 82) quoted Hair et al. (2010: 696-712) in

Ghozali and Fuad (2008,9), The process of conducting SEM analysis are the

following steps:

1. Model Conceptualization

According to Ghozali & Fuad (2014, p. 7), the conceptualization

stage relates to the development of hypotheses based on theories as for

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the basis of connecting latent variables to other latent variables, as well

as between latent variables and their indicators.

Model conceptualization in this research has been done with

literature study in chapter two. The chapter explains the relationship

between variables and the relationship of variables between the

indicators

2. Designing Path Diagram

Ghozali & Fuad (2014, p. 8) stated that constructing path diagrams

will allow researchers to visualize hypotheses that have been proposed

in the conceptualization stage of the model, even though LISREL can

still work without the preparation of flowcharts.

Ghozali & Fuad (2014, p. 8) added, designing path diagram can

provide other benefits such as reducing the level of error when building

a model on LISREL and helping to modify the model if the model is not

fit.

According to Hair et al., (2010:697-698) in Budiarsa (2017, p. 83),

in the path diagram, the construct relationship is expressed through two

arrows, the straight arrow indicating the causal relationship between one

construct with another dashed lines with arrows at the end showing the

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correlation between the constructs. The path diagram of this study can

be seen in the following figure

Figure 3.13

Structural Model

Source: Output LISREL 8.8

According to Sarjono & Julianita (2015, p. 9), there are two kinds

of variables in the SEM model: latent variable and manifest variable. A

Latent variable is a variable that cannot be measured or observed

directly, so it requires an indicator to measure it.

In SEM path diagram, the latent variable is given an ellipse symbol.

A latent variable is divided into two, namely endogenous latent

variables and exogenous latent variables. The exogenous latent variable

is a latent variable that is not influenced by any latent variables or also

known as an independent variable. In the flowchart, no arrows lead to

exogenous latent variables. The mathematical notation of an exogenous

latent variable is ξ ("ksi") (Sarjono & Julianita, 2015, p. 10).

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In contrast to an exogenous latent variable, the endogenous latent

variable is a latent variable that influenced by another latent variable.

The endogenous latent variable is also commonly called the dependent

variable. In the flowchart, there are always arrows leading to

endogenous latent variables and the mathematical notation is η ("eta")

(Sarjono & Julianita, 2015, p. 10).

Meanwhile, the manifest variable is a variable that acts as an

indicator for latent variable. Manifest variables are known also known

as observed variables or measurable variables. According to Hair et al.,

(1995) in Sarjono & Julianita (2015, p. 11), the manifest variable is the

observed value for specific points of the questionnaire question. In the

SEM Path Diagram, the manifest variable is symbolized as a square or

rectangle. Here is the SEM model of this research.

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Figure 3.24

Measurement Model


Information :

ξ (ksi) = latent variable X (exogenous)

η (eta) = latent variable Y (endogenous).

λ (lamda) = The relationship between exogenous or endogenous latent

variables on its indicators (factor loading)

γ (gamma) = Direct relationship of exogenous variables to endogenous

variables.

ζ (zeta) = Model error opportunities.

ε (epsilon) = Error of manifest variable for the latent

variable Y.

δ (delta) = Error the manifest variable for the latent

variable X.

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Structural Equation

η = γ1 * ξ1 + γ2 * ξ2 + γ121 * ξ1ξ2 + ζ

Measurement Equation Exogeneous Variable (Religiosity X1)

X1.1.1 = λX11*ξ1 + δ1

X1.1.2 = λX12*ξ1 + δ2

X1.1.3 = λX13*ξ1 + δ3

X1.1.4 = λX14*ξ1 + δ4

X1.1.5 = λX15*ξ1 + δ5

X1.1.6 = λX16*ξ1 + δ6

Measurement Equation Exogeneous Variable (Corporate

Reputation X2)

EMA = λX21*ξ2 + δ7

PS = λX22*ξ2 + δ8

SR = λX23*ξ2 + δ9

Measurement Equation Endogeneous Variable (Consumer

Loyalty Y)

CGL = λY1*η + ε1

AFL = λY2*η + ε2

CNL = λY3*η + ε3

ACL = λY4*η + ε4

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3. Evaluation of Goodness of Fit Criteria

Ghozali & Fuad (2014, pp. 29–34) points out; there some criteria

to judge whether a model is fit or not. The criteria are:

Chi-Square

Chi-square is a measurement to determine whether or not a model is

bad. A chi-square value of 0 indicates that the fit model is perfect.

According to Sarjono & Julianita (2015, p. 38), the smaller the chi-

square, the better.

Goodness of Fit Index (GFI)

GFI measures the accuracy of the model in generating the observed

covariance matrix. According to Sarjono & Julianita (2015, p. 38), the

greater the value, the better. If GFI ≥ 0.90 means good fit, while 0.8 ≤

GFI ≥ 0.9 means marginal fit

Root Mean Square Error of Approximation (RMSEA)

RMSEA measures the value of parameter deviations on a model

using the population covariance matrix. RMSEA is the most informative

fit model indicator. According to Sarjono & Julianita (2015, p. 38) said

close fit if ≤ 0.05 and a good fit if 0.05 ≤ RMSEA ≥ 0.08.

Adjusted Goodness of Fit Index (AGFI)

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AGFI Just like GFI in measuring the accuracy of the model but AGFI

has adjusted to the degree of freedom. In AGFI ≥ 0.90 means good fit,

while 0.8 ≤ AGFI ≥ 0.9 means marginal fit.

Normed Fit Index (NFI)

Normed Fit Index (NFI) is an alternative to determine the fit model.

NFI value ranges from 0-1. In order to be considered good fit, a Model

need to have NFI value greater than or equal to 0.9.

Comparative Fit Index (CFI)

CFI is a development of NFI because NFI is considered to have a

tendency to lower fit on small samples. A model is considered to be fit

if it has a CFI value greater than 0.9.

Relative Fit Index (RFI)

A model is considered to be good if it has a RFI value approaching

1, while 0.9 is a model constraint can be said fit.

Parsimony Normed Fit Index (PNFI)

PNFI shows how much degree of freedom is used to achieve model

conformity.

Parsimony Goodness of Fit (PGFI)

PGFI shows how many latent variables are formed in the model. The

value of PGFI is in the range 0-1.

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3.5.3 Hypothesis Testing

3.5.3.1 Hypothesis 1

Religiosity influence consumer loyalty. Hypothesis 1 is illustrated as

follows:

Figure 3.35

Path diagram of Hypothesis 1


To test hypothesis 1, the hypothesis used is as follows:

H0: γ1 = 0 : Religiosity (ξ1) does not influence Consumer Loyalty (η)

H1: γ1 ≠ 0: Religiosity (ξ1) influence Consumer Loyalty (η)

H0 is rejected if t-count > t-table on significance level α = 5%

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Corporate reputation influences consumer loyalty. Hypothesis 2 is

illustrated as follows:

Figure 3.46

Path Diagram of Hypothesis 2



H0: γ2 = 0 : Corporate reputation (ξ2) does not influence Consumer

Loyalty (η)

H1: γ2 ≠ 0: Corporate Reputation (ξ2) influence Consumer Loyalty (η)


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Religiosity and Corporate Reputation influence consumer loyalty.

Hypothesis 3 is illustrated as follows:

Figure 3.57

Path Diagram of Hypothesis 3



H0: γ12 = 0 : Religiosity (ξ1) and corporate reputation (ξ2) does not

influence consumer loyalty (η)

H1: γ12 ≠ 0 : Religiosity (ξ1) and corporate reputation (ξ2) influence

consumer loyalty (η)

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14 chapter iii research methodology 3.1 research...

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