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profile of respondent

Demographic variables Categories frequency Percentage

Gender Male 68 34

Female 132 66

Age 18-24 194 97.0

25-31 5 2.5

32-38 - -

39 and above 1 0.5

Ethnic Malay 50 25

Indian 22 11

Chinese 43 21.5

Sabah/Sarawak 85 42.5

Material status Single 198 99

Marriage 1 0.5

Widowed 1 0.5

Divorce/Separated - -

Educational level STPM 80 40

Matriculation 29 14.5

Diploma 6 3

Degree 84 42

Master 1 0.5

PHD - -

Program HE19 53 26.5

HE20 22 11

HE21 18 9

HE22 33 16.5

HE23 32 16

HC12 28 14

HC13 14 7

200 100%



Chapter 4: Data Analysis and Findings

4.1 Profile of respondent

4.2 Dependent and independent variables:

independent variables

Trust

Involvement

Influence

Dependent variables Satisfaction

Note: T= Trust, I= involvement, U= Influence, S= Satisfaction

4.3 Factor Analysis

Factor analysis is to summarize patterns of correlations among observed

variables, to reduce a large number of observed variables to a smaller

numbers of factors, and to provide an operational definition for an

underlying process. In order to ensure the appropriateness of factor

analysis, six assumptions need to be met:

1) Kaiser-Meyer-Olkin measure of sampling adequacy (KMO) values

must exceed .50.

2) The result of the Bartlett’s test of sphericity should be at least

significant at .05.

3) Anti-image correlation matrix of items should be at least above .

50.



4) Communalities of the variables must be greater than .50.

5) The factor loadings of .30 or above for each item are considered

practical and statistically significant for sample sizes of 350 or

greater.6) Factors with eigenvalues greater than 1 are considered

significant

From the data that has been analysis, the KMO in dependent and

independent variables is more than 0.5. The Bartlett’s test of sphericity

also show the positive result because all of it is more than 0.05. The anti

image for the independent variables show that all the highlight data is

above 0.50. The independent and dependent variables shows that

communalities is greater than .50, but that is after there are variables that

been deleted after the test been run. Next is the eigenvalues. Both

dependent and independent variables are significant because all is more

than 1.

4.2.1 independent variables (INVOLVEMENT, TRUST, INFLUENCE)

First run



Rotated Component Matrixa

Component

1 2 3

T2 .884

T1 .831

T5 .806

T4 .761

T3 .709

U2 .453 .446

I1 .813

I4 .774

I2 .755

I3 .742

U1 .823

U3 .788

Extraction Method: Principal Component

Analysis.

Rotation Method: Varimax with Kaiser

Normalization.

a. Rotation converged in 4 iterations.

Second run (Removed U2)




Component

1 2 3

T2 .884

T1 .835

T5 .812

T4 .770

T3 .730

I1 .816

I4 .776

I2 .757

I3 .740

U1 .852

U3 .797


Analysis.


Normalization.


Final run



KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of

Sampling Adequacy..823

Bartlett's Test of

Sphericity

Approx. Chi-Square 909.53

9

df 55

Sig. .000



Anti-image Matrices

I1 I2 I3 I4 T1 T2 T3 T4 T5 U1 U3

Anti-image

Covariance

I1 .496 -.214 -.122 -.126 -.081 .048 .018 -.043 -.011 .043 .005

I2 -.214 .559 -.036 -.123 .025 -.042 -.074 -.049 .061 .063 -.039

I3 -.122 -.036 .627 -.191 -.091 .080 -.002 .027 -.056 -.006 .038

I4 -.126 -.123 -.191 .582 .071 -.032 .003 .029 -.014 -.088 -.086

T1 -.081 .025 -.091 .071 .344 -.174 -.063 -.011 -.065 -.059 -.017

T2 .048 -.042 .080 -.032 -.174 .331 -.082 -.105 -.061 .074 -.004

T3 .018 -.074 -.002 .003 -.063 -.082 .555 -.003 -.100 -.033 -.061

T4 -.043 -.049 .027 .029 -.011 -.105 -.003 .463 -.154 -.078 -.051

T5 -.011 .061 -.056 -.014 -.065 -.061 -.100 -.154 .436 -.035 .023

U1 .043 .063 -.006 -.088 -.059 .074 -.033 -.078 -.035 .707 -.273

U3 .005 -.039 .038 -.086 -.017 -.004 -.061 -.051 .023 -.273 .706

Anti-image

Correlation

I1 .790a -.406 -.219 -.235 -.195 .119 .034 -.090 -.024 .073 .008

I2 -.406 .791a -.062 -.216 .056 -.098 -.133 -.096 .124 .100 -.062

I3 -.219 -.062 .780a -.316 -.197 .176 -.004 .050 -.107 -.009 .057

I4 -.235 -.216 -.316 .775a .158 -.073 .005 .056 -.027 -.137 -.134

T1 -.195 .056 -.197 .158 .823a -.514 -.144 -.028 -.168 -.119 -.034

T2 .119 -.098 .176 -.073 -.514 .797a -.192 -.267 -.161 .153 -.008

T3 .034 -.133 -.004 .005 -.144 -.192 .922a -.005 -.204 -.052 -.098

T4 -.090 -.096 .050 .056 -.028 -.267 -.005 .879a -.344 -.136 -.089

T5 -.024 .124 -.107 -.027 -.168 -.161 -.204 -.344 .879a -.063 .042

U1 .073 .100 -.009 -.137 -.119 .153 -.052 -.136 -.063 .704a -.386

U3 .008 -.062 .057 -.134 -.034 -.008 -.098 -.089 .042 -.386 .790a



Communalities

Initial Extraction

I1 1.000 .713

I2 1.000 .617

I3 1.000 .559

I4 1.000 .675

T1 1.000 .740

T2 1.000 .785

T3 1.000 .580

T4 1.000 .651

T5 1.000 .691

U1 1.000 .754

U3 1.000 .695


Analysis.



Total Variance Explained

Com

pon

ent

Initial Eigenvalues

Extraction Sums of

Squared Loadings

Rotation Sums of Squared

Loadings

Total

% of

Variance

Cumulati

ve % Total

% of

Variance

Cumulati

ve % Total

% of

Variance

Cumulati

ve %

1 4.294 39.035 39.035 4.294 39.035 39.035 3.426 31.146 31.146

2 1.928 17.532 56.567 1.928 17.532 56.567 2.499 22.716 53.862

3 1.238 11.254 67.820 1.238 11.254 67.820 1.535 13.958 67.820

4 .716 6.505 74.325

5 .549 4.992 79.317

6 .489 4.442 83.759

7 .481 4.372 88.131

8 .420 3.814 91.945

9 .374 3.396 95.341

10 .310 2.817 98.158

11 .203 1.842 100.000

Extraction Method: Principal

Component Analysis.




Component

1 2 3

T2 .884

T1 .835

T5 .812

T4 .770

T3 .730

I1 .816

I4 .776

I2 .757

I3 .740

U1 .852

U3 .797


Analysis.


Normalization.


Measurement: Acceptance of Online Banking



ITEM F1 F2 F3

Trust

T2 Using online banking is financially secure .884

T1I trust in the ability on online banking to protect

my privacy.835

T5Information concerning my online banking

transaction cannot be access by others..812

T3I am confident of using online banking even if

there is no one around to show me how to use it.730

T4I am confident online banking in Malaysia

secure1

.770

Involvement

I1 Online banking is very reliable .816

I4 Online banking transaction are economical .776

I2 Online banking is of outstanding quality .757

I3Online banking provide easy access to

information.740

Factors that influence customer in using

online banking

U

1

My decision to use online banking is influence

by my friend.852

U

3

My decision to use online banking is influence

by colleagues.797

Eigen value 4.294 1.928 1.238

% of variance31.14

6

22.71

6

13.95

8


67.820

Measure Of Sampling Adequacy .

823

Bartlett’s Test of Sphericity

909.539



Significant

0.00

4. 2.2 Dependent variable (SATISFACTION)

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of

Sampling Adequacy..868

Bartlett's Test of

Sphericity

Approx. Chi-Square 493.87

9

df 15

Sig. .000



Communalities

Initial Extraction

S1 1.000 .679

S2 1.000 .534

S3 1.000 .586

S5 1.000 .635

S6 1.000 .610

S7 1.000 .524


Analysis.


Com

pone

nt

Initial Eigenvalues

Extraction Sums of Squared

Loadings

Total

% of

Variance

Cumulativ

e % Total

% of

Variance

Cumulativ

e %

1 3.569 59.479 59.479 3.569 59.479 59.479

2 .728 12.133 71.613

3 .514 8.575 80.187

4 .475 7.914 88.101

5 .376 6.262 94.364

6 .338 5.636 100.000




Com

pone

nt

Initial Eigenvalues

Extraction Sums of Squared

Loadings

Total

% of

Variance

Cumulativ

e % Total

% of

Variance

Cumulativ

e %

1 3.569 59.479 59.479 3.569 59.479 59.479

2 .728 12.133 71.613

3 .514 8.575 80.187

4 .475 7.914 88.101

5 .376 6.262 94.364

Extraction Method: Principal

Component Analysis.



Component Matrixa

Component

1

S1 .824

S5 .797

S6 .781

S3 .766

S2 .731

S7 .724

Extraction Method: Principal Component Analysis.

SatisfactionFactor

Loading

S1Online banking allowed me to manage my finance more

efficiently.824

S2 Online banking gives me greater control over my finance. .731

S3 Online banking is compatible with my lifestyle .766

S5 Online banking is a convenient way to manage my finance. .797

S6Online banking is useful for managing my financial

resource..781

S7

Online banking makes it easier for me to conduct my

banking transaction. .724

Eigen value 3.569

Total Variance Explain 59.479

Measure of Sampling Adequacy .868

Bartlett’s test of Sphericity 493.879

Significant .000



4.4 Reliability test

4.3.1 Independent variables

Trust:

Case Processing Summary

N %

Cases Valid 200 100.0

Exclude

da0 .0

Total 200 100.0

a. Listwise deletion based on all

variables in the procedure.

Reliability

Statistics

Cronbach's

Alpha

N of

Items

.883 5

Item Statistics

Mean

Std.

Deviation N

T1 3.0900 1.00346 200

T2 3.0650 .89711 200

T3 3.1500 .93910 200

T4 3.0050 .93237 200

T5 3.1800 1.02118 200



Item-Total Statistics

Scale Mean

if ItemDeleted

Scale

Variance if

ItemDeleted

Corrected

Item-TotalCorrelation

Cronbach's

Alpha if

ItemDeleted

T1 12.4000 9.920 .757 .850

T2 12.4250 10.376 .783 .845

T3 12.3400 10.859 .641 .876

T4 12.4850 10.643 .690 .865

T5 12.3100 9.934 .735 .855

Involvement:


N %


Exclude

da0 .0

Total 200 100.0



Reliability Statistics

Cronbach's

Alpha

N of

Items

.795 4

Item Statistics

Mean

Std.

Deviation N




N %


Exclude

da0 .0

Total 200 100.0

I1 3.5700 .79262 200

I2 3.3900 .76867 200

I3 3.8700 .77206 200

I4 3.7250 .77614 200


Scale Mean

if ItemDeleted

Scale

Variance if

ItemDeleted

Corrected

Item-TotalCorrelation

Cronbach's

Alpha if

ItemDeleted

I1 10.9850 3.392 .674 .709

I2 11.1650 3.656 .592 .751

I3 10.6850 3.744 .551 .770

I4 10.8300 3.599 .606 .743



Influence:


N %


Exclude

da0 .0

Total 200 100.0




Cronbach's

Alpha

N of

Items

.639 2

Item Statistics

Mean

Std.

Deviation N

U1 3.2800 1.02805 200

U3 3.2250 1.03427 200




Scale Mean

if Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if

Item

Deleted

U1 3.2250 1.070 .470 .a

U3 3.2800 1.057 .470 .a

a. The value is negative due to a negative average

covariance among items. This violates reliability

model assumptions. You may want to check item

codings.

4.3.2 Dependent variables

Satisfaction:


N %


Exclude

da0 .0

Total 200 100.0

a. Listwise deletion based on allvariables in the procedure.


Cronbach's

Alpha

N of

Items

.863 6



Item Statistics

Mean

Std.

Deviation N

S1 3.4700 .82004 200

S2 3.3650 .84578 200

S3 3.5000 .76349 200

S5 3.4550 .80074 200

S6 3.4050 .77717 200

S7 3.8500 .78778 200


Scale Mean

if Item

Deleted

Scale

Variance if

Item

Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if

Item

Deleted

S1 17.5750 9.351 .723 .827

S2 17.6800 9.726 .608 .849

S3 17.5450 9.928 .653 .840

S5 17.5900 9.610 .685 .834

S6 17.6400 9.789 .670 .837

S7 17.1950 10.037 .600 .850

From the table: summary of reliability analysis

Reliability analysis on variables in the study



Variables No of item Cronbach’s alpha

Involvement 4 .795

Trust 5 .883

Influence 2 .639

satisfaction 6 .863

Reliability analysis is to establish by testing for both consistency and

stability of the set of item that positively correlated to one another.

Cronbach’s alpha was calculated. Generally, an alpha value close to 1.0

indicates high internal consistency reliability, an alpha value less than 0.6

is considered to be poor, values of 0.7 are considered acceptable and

values above 0.8 are deemed to be good (Sekaran & Bougie, 2009). From

the table above, after the data been analyse and reduce, all the

Cronbach’s alpha is more than 0.6 and it shows that the variables have a

high internal consistency reliability. Even though the variables of influence

is only 0.639, it still consider acceptable.

4.5 Descriptive analysis



Descriptive Statistics

NMinimu

m

Maximu

mMean

Std.

Deviati

on

Skewness Kurtosis

Statisti

c

Statisti

c

Statisti

c

Statisti

c

Statisti

c

Statisti

c

Std.

Error

Statisti

c

Std.

Error

involvem

ent200 2.00 5.00 3.6388 .61170 .163 .172 .007 .342

trust 200 1.00 5.00 3.0980 .79268 -.061 .172 -.167 .342

influence 200 1.00 5.00 3.2525 .88397 -.383 .172 .013 .342

satisfacti

on200 1.83 5.00 3.5075 .61579 .033 .172 .195 .342

Valid N

(listwise)200

From the Table: summary of Descriptive analysis

Mean and Standard Deviation for variables in the study

Variables Mean Standard Deviation

Involvement3.6388 .61170

Trust3.0980 .79268

Influence3.2525 .88397

Satisfaction 3.5075 .61579

Descriptive Analysis measure the value of the mean and the standard

Deviation of the variables. Based on the scale 1 to 5, the mean score less

than 2 is rated as low, 2 to 4 as average and mean score more than 4,



rated as high. From the summary of the variables, all the mean show

more than 3.0 and this can be rated as average.

4.6 Correlation analysis

involvemen

t trust influence

satisfactio

n

involvemen

t

Pearson

Correlation1 .321** .225** .641**

Sig. (2-tailed) .000 .001 .000

N 200 200 200

trust Pearson

Correlation1 .358** .493**

Sig. (2-tailed) .000 .000

N 200 200

influence Pearson

Correlation1 .315**

Sig. (2-tailed) .000

N 200

satisfaction Pearson

Correlation1

Sig. (2-tailed)

N

**. Correlation is significant at the 0.01 level (2-

tailed).

The Pearson correlation coefficient values can vary from -1.00 to

+1.00.the number of +1.00 represent perfect positive correlation, while

-1.00 represent perfect negative correlation. This means, the highest the

number to the positive, the better or the stronger the correlation between

variables. From the table above, we can see that the relation betweeninvolvement and satisfaction is the highest and the lowest is relation



between influence and involvement. From this data, we can see that

maybe involvement or influence have the impact of the correlation

between variables. This question can be answer when we look at the next

data analysis that is regression analysis.

4.7 Regression analysis

Variables Entered/Removedb

Mode

l

Variables

Entered

Variables

Removed Method

1 influence,

involveme

nt, trusta

. Enter

a. All requested variables

entered.

b. Dependent Variable:

satisfaction

Model Summary

Mode

l R

R

Square

Adjusted R

Square

Std. Error

of the

Estimate

1 .714a .510 .502 .43436

a. Predictors: (Constant), influence,

involvement, trust



ANOVAb

Model

Sum of

Squares df

Mean

Square F Sig.

1 Regressio

n38.482 3 12.827 67.990 .000a

Residual 36.979 196 .189

Total 75.461 199

a. Predictors: (Constant), influence,

involvement, trust

b. Dependent Variable: satisfaction



Coefficientsa

Model

UnstandardizedCoefficients

Standardiz

ed

Coefficients

t Sig.B Std. Error Beta

1 (Constant) .669 .205 3.267 .001

involvemen

t.530 .054 .527 9.904 .000

trust .226 .043 .291 5.236 .000

influence .064 .038 .092 1.707 .089

a. Dependent Variable: satisfaction

From the table: Summary of Regression Analysis

Regression analysis of all independent variables with satisfaction

Dependent Variables independent Variables std. Coefficient

Satisfaction Involvement 0.527**

Trust 0.291**

Influence 0.092

R2 0.510

Adjust R2 0.502

Sig. F 67.990

Note: significant Levels: ** p < 0.01, * p < 0.05



From the regression analysis, we can make a conclusion that the

independent variables (influence), is not significant compare to the other

variables. That why in the correlation analysis, the relation between

influence and involvement is very low because influence variable is notsignificant.

Chapter 5: Discussion and conclusion

5.1 Introduction

The purposes of this chapter are to summarize and discuss the relevantfindings of this study. First, this chapter present brief view purpose and

then result of this study. Then, continue with discussion. Next, is

theoretical and methodological, contribution as well as managerial

implications. Finally, the limitation and recommendation part of this study

for future research.

5.2 Discussion of Findings



Factor analysis is to summarize patterns of correlations among observed

variables, to reduce a large number of observed variables to a smaller

numbers of factors, and to provide an operational definition for an

underlying process. The dependent variable in this study is satisfactionwhile independent variable is trust, involvement and influence. Both

dependent and independent variables are significant because all is more

than 1 (refer to discussion, chapter 4). Reliability analysis is to establish

by testing for both consistency and stability of the set of item that

positively correlated to one another. Cronbach’s alpha was calculated. In

this study, the Cronbach’s alpha value is more than 0.6 and it shows that

the variables have high internal consistency reliability. Descriptive

Analysis measure the value of the mean and the standard Deviation of the

variables. The mean in this study was 3.00 and it consider as average. The

Pearson correlation coefficient values can vary from -1.00 to +1.00.the

number of +1.00 represent perfect positive correlation, while -1.00

represent perfect negative correlation. Relation between involvement and

satisfaction is the highest and the lowest is relation between influence and

involvement (refer to discussion, chapter 4). Finally, in regression

analysis, in this study can conclude that the independent variables

(influence), is not significant compare to the other variables (refer to

discussion, chapter 4).

5.3 Contribution of research

This study offers theoretical ramification. This study also contributes of

student involvement, satisfaction, trust and factor that influence customer

in using online banking. In today’s business environment, students are

aware of the importance of online banking especially among

undergraduate students. Through this study, it provides the main factor

which attracted students to use online banking in daily transaction. The

findings which derived from this research may be useful to students



insofar as alerting them to the factor of attracted in using online banking.

Finally, this also study provide some useful guidelines for academician or

policy makers, to increase the usage of online banking among students.

5.4 Managerial Implication

The findings of this study provide several managerial implications for

manager and practitioner, especially those who are involve with online

banking. This study provide strong evidence that it could help managers

to gain better knowledge on the usage of online banking among students ,

based on the result that we can conclude that in chapter 4 we achieved

our objective which is (1) to investigate the involvement of students in

using online banking, (2) to determine the satisfaction of existing student

that offer by online banking, (3) to determine the trustable level of the

students towards online banking and (4) to identify the factor that

influence student in using online banking.

In term of the involvement, online banking become students choice

because online banking is very reliable. It provide easy access information

to student, and the transaction are economical as well as it outstanding

quality. Nowadays, involvement of customers especially students are

more like to use online banking for every single transaction even to do

reload transaction.

To determine the satisfaction of existing student that offer by online

banking can help students to manager and control their finance

efficiently, easier to conduct banking transaction. Online banking is

convenient for students because it does not require a lot of mental effort.

Students will feel satisfied with online banking because online banking is

compatible with their lifestyle.

Based on the result, student feel more trusted when using online banking.

It because they find out their privacy risk protected by bank. Students feel

confident when using online banking because the information concerning

by them in online banking transaction cannot be access by other throughtransaction access code (TAC).



Lastly, the objective which stated in this study that already achieved is

factor that influence student in using online banking. Influence from friend

one of factor as well influence from family member. Due to online banking

service is available for 24 hours for seven day nonstop it is veryconvenient for student to manage their account effectively.

5.5 Limitations of the study

This study is constrained by limitation as well. Specific limitation of the

methodology and methods are discussed on Chapter 4 in regards to

limitation of data collection and data analysis along the stages of the

development cycle. The limitations of the research are first addressed by

discussion the objective of the research, discussion the limitation of the

data, data analysis and the validity of analysis.

• Objective of research

The main objective of this research is to determine the usage of

online banking in Malaysia among student especially in UMSKAL.

The limitation which this study found are restricted by the limited

number of questionnaire may affect the accuracy of research. Totalcandidate for this research are 200 students out of 2550 students.

Therefore, it will be problematic to generalize the findings to other

part as well. Besides that, the accuracy of the research is full

depended on the respondent. It based on their cooperation and how

they fill the questionnaire. Some of the person which fill up this

questionnaire just fill and not answering according to question. The

“trustworthiness” of research depend on “what counts as

knowledge?” (Lincoln & Guba,1985). The limitations of this study are

the respondent may not fully understand about the certain meaning

in the questionnaire that will lead to different meaning. This

research also only focus student in UMSKAL, and this questionnaire

also not distributed to the lectures as well.

• Limitation of data

Data management involves the procedure used for a systematic,

process of data collection, storage and retrieval for the high quality,



accessible data, the documentation of analysis and retention of data

( Huberman & Miles,1998 ). Data source for this questionnaire are

based on questionnaire which is the limitation. The targets for this

study are student who are among 18-24 years. However the datawhich used for this research are fully completed.

• Data analysis

All the data collected will be analyzed through Statistical Program

for Social Science (SPSS). This software will help to identify the

association and relationship between variables. Cronbach’s alpha is

used to measure the reliability of data collected. Coefficient alpha

between 70% to 80% are acceptable and more than 80% are good

(Sekaran & Bougie,2009) .The limitation which gain through this

data are some of the variables are fall below 70% which have to

reject the variable.

However, within the limitations of the study the study provide some

interesting result and spend avenues for further result.

5.6 Recommendation for Future Research

Due to the limitation of the study on online banking, this has shown that

the future study on similar research should be refined and making

improvement in order to create more conciseness and more sufficient

data to make easier to understand on the related study. Therefore,

through the limitation of the study, objective of the research, limitation of

the data as well as the data analysis, this study has stated clearly thatsome recommendation are needed to improve on future research.

From the first limitation of the study which is the main objective of the

research. UMSKAL has around 2550 local and foreign students, instead of

taking all students; the study enquires only 200 students out of 2550 that

will be almost only 8% students from UMSKAL. Therefore, this limited

number of respondent on our questionnaire may be affecting the accuracy

of the research. Besides that, when doing some research we need a lot of



information from a large group instead of asking question towards a small

amount of people. This study suggests that for the future research, the

number of the respondent on our questionnaire need to be exceeding the

amount than this study. That will be 2000 respondent of questionnaire inorder to avoid inaccuracy of research and provide sufficient data to the

future study. Since in UMSKAL there have around 2550 students, so the

more respondent on our questionnaire, the more accuracy of the study.

In additional, besides the amount of respondent on the questionnaire, this

study also suggests that for the future research, researchers should focus

on the attitude from the respondents. This situation depends on their

cooperative and the way they answering the question from the

questionnaire. Sometimes, when asking respondent to answer the

questionnaire, for the one whom asking for help should be patient and

they need to explain how to answer or what the meaning of the question

is. If we fulfil the requirements, the respondent will help us finish the

tasks. In addition, this study also needs more cooperative from the

respondent. If the respondent more cooperative, the questionnaire will be

easily to solve. But in the other hand, if the respondents don’t want to

cooperative with us, these will interference the result. Therefore, we must

be polite and asking for some time for us to answer our questionnaire at

first. If the respondent really in hurry, we shouldn’t block him instead we

need to thank them because they willing to hear your favour. After the

respondents finished the questionnaire, we should thank them with

sincerely then they will feel more comfortable.

Besides the two limitations above, in sometimes the respondents may not

fully understand about the certain meaning in the questionnaire. In fact,

this will make them misunderstand the question and lead them to a

different meaning and different answer. Therefore, researchers should

lend a hand to each responder. So, the researchers need to be at

respondents’ side to help them understanding the questionnaire. Besides

that, we can also help respondents finished the questionnaire by orally.

This will make easily to the respondents to understand the questionnaire



faster and answering the question smoother. In result, the accuracy for

the research will be more accurate and having sufficient result data.

This study also suggest that to avoid some of the variable reject due to

the cronbach’s alpha fall below 70%, other variable should be over 70%as

well as exceeding 80%. This is because reliabilities less than 60% is

consider as poor, 70% is range, acceptable and over 80% is good. Based

on the table summary of reliabilities analysis although the variable of

influence is 0.639 which is 63.90%, is still consider acceptable, as long as

there are not below 0.50 which is 50%. If the cronbach’s alpha is below

0.50, the variable should be reject.

5.7 Conclusion

As a conclusion, the current study is carried out to a gain better

understanding for the relationship between involvement, satisfaction,

trust and factors that influence students in using online banking. This

study also incorporates both reliable and quality as conduct of

involvement in order to gain more insight into how students perceive the

benefit of online banking as well as satisfaction when using online banking

services.

A review of the satisfaction showed mixed findings concerning the

relationship between involvement, trust and influence in using online

banking services of university students. Nevertheless, the finding of the

study shows that students trust and involvement has a substantial

influence of satisfaction on online banking services with the bank

performance. Security and privacy of the online banking system is one of

the important things for students when using online banking services.

Online banking in fact is indeed a very good use of service offer by the

banks. Nowadays, mostly all the banks in Malaysia are offering online

banking service such as the Maybank had launch their online banking

system – “Maybank2u” which have been launched 11 years until now.

The following successful of online banking system “Maybank2u”, thebanks in Malaysia have launched their own online banking system one by



another. This shown that online banking is not only easy-to-use for access

information, very reliable but also reducing the time of complicated

procedures during bank in.

Therefore, present study suggests that in order to increase users of online

banking, online banking managers should be more concentrate on the

involvement, trust, influences and satisfaction as the part of strategy. By

maintaining and strengthening the satisfaction, it will position the quality

of online banking, security and privacy in mind of consumers. Besides

that, online banking managers can also make decision regarding market

expansion and be more concentrate on the security and privacy of this

online banking service. If the security and privacy are officially recognized

as safety, ordinary people will use more on online banking than travel to

the bank to bank in, pay or take out their money. Therefore, there is a

need to understand the important roles of online banking services.

analysis king 2

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