SKRIPSI
Submitted as Partial Fulfillment of Requirements for the Degree of Sarjana Ekonomi (SE) at the Sebelas Maret University Surakarta
By
Delariza Rika Fasita F 0307036
FACULTY OF ECONOMICS SEBELAS MARET UNIVERSITY
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MOTTO
Sungguh bersama kesulitan itu ada kumudahan, karenanya jika kamu telah
selesai (dari suatu urusan) kerjakanlah sungguh-sungguh (urusan yang lain).
Dan kepada Tuhanmulah kamu berharap
(Q.S. Alam Nasyrah: 6-8).
You live you learn, you love you learn, you cry you learn, you lose you learn (Alanis Morisette).
In the middle of difficulty lies opportunity (Albert Einstein).
Only those who dare to fail greatly, can ever achieve greatly
(Robert F. Kennedy).
Hidup itu tak selamanya indah, tapi biarkan yang indah itu tetap
hidup dalam kenangan
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DEDICATION
This
skripsi
and whatsoever success
that I could achieve is dedicated to
My -greatest - beloved
Papa
and
Mama
If only there is a good enough word to
say my sincerely thanks for you two.
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2. Drs. Jaka Winarna M.Si., Ak., as the Head of Accounting Department, Sebelas
Maret University, Surakarta.
3. Mr. Santoso Tri Hananto, M.Si,Ak., as my skripsi advisor. Thanks for your advices and support so this skripsi can be done.
4. Mr. Agus Budiatmanto SE., M.Si, Ak., as my academic advisor, thanks for all
your support and advices.
5. My Papa and Mama, thank you for being my greatest parents in the worlds. Thank you for all support and endless love, even we were separated, I know
you always there for me. This English skripsi is dedicated only for you two and also my sister, Rensi.
6. My “dudulz” Dedie Saifullah, thank you for all love, care, understanding, and
all you’ve gave for me for whole time. I always could count on you.
ACKNOWLEDGMENT
Researcher will be grateful to Allah SWT for all the mercy and bless so that
she was able to finish this research well. This Skripsi is proposed to complete all the requirements of achieves the degree of Sarjana Ekonomi of Accounting Department, Sebelas Maret University, Surakarta.
Researcher realizes that she could not have finished this skripsi without the supports and involvement of many parties both directly and indirectly. I owe a very great debt
to:
1. Prof.Dr. Bambang Sutopo, M.Com., Ak., as the Dean of Economics
perpustakaan.uns.ac.id digilib.uns.ac.id
7. Dhinar Adi Nugroho, my best brother, thank you for the story, your support
and care for me.
8. My best friends “LOTIZ”, Dewi Listiani thank you for being my first friend at UNS until now, your trust for always share to me. Noor Anis Meikawati,
thanks for our story together, I will never forget it. Murdiani Agustiati, thank
you for coloring our day with your odd behavior. When we feel down,
remember our heart fight to through all this. Novi Eka Rahmawati, thank you
for your serenity that always make me so calm.
9. My best friends in Bekasi, Febri Alfalina Saputri, Reynaldi Oey, Allert
Benedicto Ieua Noya, Dian Anggraini Kumalasari thanks for our beautiful
relationship.
10. All of my best friends, Ebray, aunt Weny, Fata’s mom for being my great
English editor. Joe, Hadi, Gandi “Tria” for the never ending support.
11. Thanks to pakde Dr. Nur Julianto and Bude Mochdiyati whom I lived with at Solo. My big family, Eyang Imam Soeyitno family and Embah Mochammad Family, thanks for your love, care, and support.
12. My “Agent 007” friends: Ayus, Peka, Irla, Fatania, Dewo, Mba Sri, Oppie,
Nani, Rudi, Rija’, Awang, etc. HMJ Akuntansi friends, Mas Okky, Mba Desta, Mas Dancrut, Mba Ulli, Mas Fijri, Mba tryas, Mba Hanni, Mba Finik, Reza, Abhe, Anes, etc. and all of economic faculty friends for all support in the last
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13. And for all parties that Researcher could not mention one by one, but you have
already mentioned in my heart.
Researcher realizes that this research is far from being perfect. This research
has a lot of constraint, thus any suggestions and critics are expected for the sake of
improving this research.
As I close this acknowledgment, I expect that this small print writing will be useful
to all parties.
Surakarta, April, 2011
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TABLE OF CONTENTS
Page
TITLE ... i
ABSTRACT ... ii
ABSTRAK ... iii
PAGE OF ADVISOR’S APPROVAL ... iv
PAGE OF APPROVAL ... v
PAGE OF MOTTO ... vi
PAGE OF DEDICATION ... vii
ACKNOWLEDGEMENT ... viii
TABLE OF CONTENT ... xi
LIST OF TABLES ... ... xiv
LIST OF FIGURE... ... xv
LIST OF APPENDIXES... ... xvi
CHAPTER I. INTRODUCTION A. Background... ... 1
B. Problem Statements ... . 7
C. Research Objectives ... . 7
D. Research Advantages ... 7
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1. Technology Concepts ... 9
2. Conceptual of Mobile Banking ... 11
3. Technology Accpeted Model (TAM) ... 14
B. Conceptualization and Hypotheses Development ... 23
C. Conceptual Framework ... 26
III. RESEARCH METHODS A. Research Design ... 27
B. Population and Sample ... 27
C. Data Source and Data Collecting Technique ... 28
D. Measurement Items ... 28
E. Data Analyze Technique and Hypotheses Test ... 31
1. Data Test Technique ... 31
2. Model Assumption Test ... 33
IV. DATA ANALYSIS A. Data Collection Analysis ... 39
1. Total Data Collection ... 40
2. Respondents Demography ... 40
B. Data Test Analysis ... 43
1. Normality Test ... 43
2. Outlier Evaluation ... 44
3. Validity Test ... 45
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C. Model Assumption Test ... 48
1. Godness of Fit Analysis ... 48
2. Model Modification ... 49
D. Hypotheses Analysis ... 51
V. CONCLUSION A. Conclusions ... 57
B. Research Constraints ... 58
C. Research Suggestion ... 59
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LIST OF TABLES
PAGE
Table III.1 Research Variables 29
Table III.2 Godness of Fit Indices 37
Table IV.1 Data Research Collection 40
Table IV.2 Respondents Age 41
Table IV.3 Respondents Educational Background 42
Table IV. 4 Normality Test 44
Table IV.5 Outliers Data 45
Table IV.6 Validity Test 46
Table IV.7 Reliability Test 47
Table IV.8 Goodness of Fit Model Before Modified 48
Table IV.9 Goodness of Fit Model After Modified 50
Table IV.10 Goodness of Fit Model Summary 51
Table IV.11 Significant Level 51
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LIST OF FIGURE
PAGE
Figure II.1 Technology Accepted Model by Davis et al. (1989) 17
Figure II.2 Conceptual Framework 26
Figure III.1 TAM with Perceived Mobility Value (PMV) and Perceived
Enjoyment (PE) 38
Figure IV.1 Respondents Gender 41
Figure IV.2 Bank Where The Respondents Save Their Money in 42
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LIST OF APPENDIXES
Appendix 1 Questionnaire Form
Appendix 2 Respondents Recapitulation
Appendix 3 Research Path Diagram before Modified
Appendix 4 Research Output Path Diagram before Modified
Appendix 5 Normality Test
Appendix 6 Outlier Test
Appendix 7 Validity Test
Appendix 8 Reliability Test
Appendix 9 Goodness of Fit Model before Modified
Appendix 10 Modification Indices before Modified
Appendix 11 Research Path Diagram after Modified
Appendix 12 Goodness of Fit Model after Modified
Appendix 13 Modification Indices after Modified
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A PERSPECTIVE OF THE EXTENDED TECHNOLOGY ACCEPTED MODEL (TAM) USING PERCEIVED MOBILITY VALUE AND
PERCEIVED ENJOYMENT VARIABLES
DELARIZA RIKA FASITA NIM F0307036
The objective of this research is to examine and verify that the TAM can be employed to explain and predict the acceptance of mobile banking. This study identifies two factors that account for individual differences, i.e. Perceived Mobile Value (PMV) and Perceived Enjoyment (PE) which is adapted from Huang et al. (2006). Population in this research is bank customers who use mobile banking services in Indonesia. A sample of 131 respondents was selected using a purposive sampling method whereby the respondents have to be mobile banking users to be included in the survey. The constructs’ in the model were measured using existing items adapted from some prior TAM research.
The result shows that the data fit the extended TAM well. Furthermore, the result show that perceived enjoyment and perceived mobility can affect individual intention to use mobile banking. Overall, the result support that perceived mobility value and perceived enjoyment may appropriate to use in predicting user acceptance of mobile banking.
PERSPEKTIF DARI PERLUASAN MODEL PENERIMAAN TEKNOLOGI MENGGUNAKAN VARIABEL PERSEPSI NILAI MOBILITAS DAN PERSEPI
KENIKMATAN
DELARIZA RIKA FASITA NIM F0307036
Tujuan penelitian ini adalah untuk menguji dan memverifikasi apakah TAM dapat digunakan untuk menjelaskan dan memprediksi penerimaan pengguna mobile banking. Penelitian ini menggunakan dua faktor yang menjelaskan perbedaan-perbedaan individual, yaitu persepsi nilai mobilitas dan persepsi kenikmatan, yang diadaptasi dari Huang et al. (2006). Populasi pada penelitian ini adalah nasabah bank pengguna jasa mobile banking. Sampel dari 131 responden didapat dengan menggunakan metode purposive sampling di mana kriteria responden adalah pengguna mobile banking. Konstruk yang digunakan dalam model diukur dengan menggunakan item pengukuran yang diadaptasi dari penelitian TAM yang pernah ada.
Hasil menunjukkan bahwa data cocok dengan perluasan model TAM ini dan persepsi nilai mobilitas dan persepsi kenikmatan dapat mempengaruhi niat seseorang untuk menggunakan mobile banking. Secara keseluruhan, persepsi nilai mobilitas dan persepsi kenikmatan dimungkinkan untuk digunakan dalam memprediksi penerimaan pengguna mobile banking.
perpustakaan.uns.ac.id CHAPTER I digilib.uns.ac.id
INTRODUCTORY
A. BACKGROUND
Nowadays technology, provide dynamic collaborative environments that
widely recognized today, becomes an important factor in the future development
(Baten, 2010). Information technology is weakening geographical constraints
and changing the way people communicating to each others (Mazhar, 2006). The
usage of new information technology will also change the individual behaviour
(Hamzah, 2009).
The internet, one of the information technologies, has created an
incredible market space. Same with it, another technology stream has emerged to
play an increasingly important role in business and society: mobile
communications (Feng et al. in Barati and Mohammadi, 2009). Mobile phones
have become an integral part of the 21st century landscape with an expected
penetration of 4.5 billion by 2011. As the number of mobile phone users is
growing, purchasing products and services using mobile phones and other
mobile devices are also increasing (Manochehri and Alhinai in Barati and
Mohammadi, 2009).
The major change has come in the delivery of the content, application,
and services to the mobile communication devices (Sadi et al., 2010). Since the
mid-1990s, there has been a fundamental change in banking delivery channels
perpustakaan.uns.ac.id et al., 2004). Banks began to look at electronic banking (e-banking) as a means digilib.uns.ac.id
to replace some of their traditional branch functions for two reasons. Firstly,
branches were very expensive to set up and maintain due to the large overheads
associated with them. Secondly, e-banking products or services like Automatic
Teller Machine (ATM) and electronic fund transfer were a source of
differentiation for banks that utilised them. Banks can find significant savings by
serving customers in the mobile channel ($0.08) rather than through the contact
centre ($3.75), IVR banking ($1.25), ATM ($0.85) or even online banking
($0.17) (Eads, 2009: 1). Being a tight competitive industry, the ability of banks
to differentiate themselves based on price is limited (Singh et al. in Goi, 2006).
Mobile banking, the lowest cost banking service, is defined as a way for
the customer to perform banking actions on his or her cell phone or other mobile
device (Miller, 2011). Mobile banking is a financial service access from using
Short Message Services (SMS) technology platform for simple transaction as a
customer’s asks (Hristu in Amin et al. 2006) to using Wireless Application
Protocol (WAP) technology for more complex financial information. With
mobile banking services, customers should not go to ATM. In the past, people
were doing their transactions using ATM. This machine gives an enough
solution to customers for paying without stand in a long line, but it still needs the
attendant from the customers to do their transaction.
Although information technology condition in Indonesia leave behind
from other countries (Harmadi and Hermana, 2005), but compared with other
perpustakaan.uns.ac.id rush growth is because mobile banking services, use for different kinds of digilib.uns.ac.id
banking services ranging from bill payment to making investment, can answer
the needs of modern citizens who have a high mobility. Customers are not the
only beneficiary of this new service, commercial banks may greatly increase the
market coverage and better track customer as well (Shao, 2007).
Now on, almost all banks in Indonesia apply this kind of services. The
government hope with this popular channel from banking services will decrease
the used of cash money. A survey research from the International Financial
Institute reveals that 35% from all over the world online housing work chores
will shift to mobile banking services. It predicted that the value of mobile
banking services will increase two times per years and will increase four times
per years after 2011. According to a study conducted by the telecommunications
analyst firm the number of mobile phone banking users will exceed 150 million
globally by 2011.
Based on Indonesia Bank, internet banking user reached about 2,5
million by 2009. It larger than in 2008 where the internet banking user only
reached about 1,5 million (Ismartunun, 2010). The amount of BCA mobile
banking transaction has increased 57%, from Rp. 27,9 billion at the first quarter
by 2009 to Rp. 43,9 billion at the first quarter by 2010 (Ismartunun, 2010).
TELKOMSEL, one of Indonesia’s cellular network provider, has 2,5 million
mobile banking users, with the highest traffic from BCA and Mandiri Bank, and
perpustakaan.uns.ac.id 2007 (Noor in Niagara, 2008: 3). It can conclude that mobile banking users in digilib.uns.ac.id
Indonesia are quite enough perspective.
The success of mobile banking usage depends on how users would
achieve the systems (Wijayanti and Akhirson, 2009). Thus, the metaphorical tide
is likely to raise all boats by increasing overall customer comfort with mobile
banking and mobile commerce in general, which will decrease costs and
increasing profits through the new customers and more profitable transactions
(Eads, 2009).
Choosing mobile banking as the object of this study analysis is due to
two particular reasons. First, the need of media for people who has a high
mobility is increasing overtime. Second, mobile banking helps to reduce the
transaction cost and give more value-added for the customers.
Human beings, being creatures of habit, will probably view anything that
is new with caution and suspicion. The same applies to multimedia banking.
However, with the threat of globalization and possible squeezes in margins,
banks are attempting to 'push' clients towards multimedia banking (Vijayan et
al., 2005).
Many research were explained by Harmadi and Hermana (2005) in
Indonesia, Lee et al. (2007) in South Korea, Kripanont (2007) in Thailand,
Wessels and Drennan (2009) in Australia, Sadi et al. (2010) in Sultanate Oman
about determinant adoption of internet banking is no longer generally consistent.
It means that those researches not yet found the exact factors affecting the
perpustakaan.uns.ac.id approach, developed by Davis et al. (1989) based on Theory of Reasoned Action digilib.uns.ac.id
(TRA), used by those researches, which can explain customer acceptance of
information technologies.
TAM consists of six primaries constructs, namely external variables (e.g.
prior experience, voluntariness, compatibility, complexity, etc.), perceived
usefulness, perceived ease of use, attitude, behavioural intention, and actual
usage. It shows that user behaviour is determined by perceptions of usefulness
and the ease of use of the technology (Adams et al., 1992; Davis et al., 1989;
Mathieson, 1991; in Huang et al., 2006). Davis (1989) observed that external
variables enhance the ability of TAM to predict acceptance for future
technology. In other words, the constructs of TAM need to be extended by using
additional factors (Huang et al., 2006).
Many research extended their TAM with external variables in order to
explain further and become the antecedent from perceived usefulness or
perceived ease of use (Jogiyanto, 2008: 124). Choosing additional factors
depends on the target technology, main users, and context (Moon and Kim in
Huang et al., 2006). Wang et al. in Huang et al. (2006) noted that variables relating to individual differences play a vital role in the implementation of
technology. The more accepting of a new information system the users are, the
more willing they are to make changes in their practices and use their time and
effort to actually start using the new information system (Succi and Walter in
Pikkarainen et al., 2004). Usage of a system can be an indicator of information
perpustakaan.uns.ac.id regarded as good or bad depends on how the user feels about the system digilib.uns.ac.id
(Pikkarainen et al., 2004).
Mobile banking services are still in infancy. It has a great deal of room
for improvement. Thus, there is a need to study and understand user’s
acceptance of mobile banking services in order to identify the significant
motivational factors affecting their intention to use mobile banking.
From a marketing perspective the greatest advantage of mobile
communication and mobile commerce is that it offers suppliers a channel of
direct communication with consumers via a mobile device at any time and at any
place (Lubbe and Louw, 2009). How to anticipate customer needs and develop
mobile content services is not easy in a rapidly developing mobile market
(Pihlstrom, 2008: 2). Mobile devices create an opportunity to deliver new
services to existing customers and to attract new ones (Lubbe and Louw, 2009)
and when consumers enjoy positive experience in using mobile banking, they
will increase the amount of transaction (Suki and Suki, 2007). From that
explanation, this study will identify two constructs, which are adopted from
Huang et al. (2006), namely “perceived mobility value”, and “perceived
enjoyment” in order to identify the factors that influencing user acceptance of
perpustakaan.uns.ac.id B. PROBLEM STATEMENTS digilib.uns.ac.id
Previous research, conducted by Huang et al. (2007), explains that user
acceptance of mobile learning can be explained by TAM with two external
variables, i.e. perceived mobility value and perceived enjoyment. Based on the
problem background, the researcher formulates the problems of this research,
using the same model with Huang et al. (2007) but with different object, in
question forms “Are perceived mobility value and perceived enjoyment
variables affecting user acceptance of mobile banking with Technology
Acceptance Model (TAM)?”
C. RESEARCH OBJECTIVES
The objective of this research is to examine and verify that the TAM can be
employed to explain and predict the user acceptance of mobile banking using
two factors that account for individual differences, i.e. Perceived Mobile Value
(PMV) and Perceived Enjoyment (PE).
D. RESEARCH ADVANTAGES
1. Advantages for banking provider
The researcher expects with this research, banking provider would know what
factors affecting their customers using or adopting mobile banking to do their
transaction so that can use for their future strategic plan, substance policy
improving their productivity, and enhance their market section in this
perpustakaan.uns.ac.id 2. Advantages for bank customer digilib.uns.ac.id
This research hopefully can give advantages to the customers, so they can
maximize using mobile banking services. Afterwards, for the customers who
not yet known and not yet use it before will know and use it in their daily life.
3. Advantages for next research
Hopefully, this research can contribute a reference for literature development
and knowledge for next research about mobile banking technology.
perpustakaan.uns.ac.id CHAPTER II digilib.uns.ac.id
THEORETICAL FRAMEWORK
A. Agency Theory
1. Technology Concepts
Nowadays, technology has been being an unearthed part of human life.
There are so many definitions of technology. In Random House Dictionary
quotes from Kumala (2008: 12) technology is defined tightly relating to life,
citizens, and environment. It means that technology will not be a free valuable.
A technology usually started from individual or group imagination using
nature phenomenon and practical needs. From those imaginations, individual
or group developed it to be an invention. According to Galbraith in Niagara
(2008) technology is defined as a systematic application and obtained from
formulation science knowledge concept or knowledge collection that have
certain function in practical human daily live and technology as the activity
that involving organizational activity and system value.
Technology is defined by Goetch in Kumala (2008: 12) as “people
tools, resources, to solve problems or to extend their capabilities”. Pacey in
Kumala (2008: 12) defines technology as “the application or scientific and
other knowledge to the practical task by ordered systems that involve people
and organization, living things and machines”. From those definitions, there
are obtaining some essence: (1) technology related to eternal idea or human
perpustakaan.uns.ac.id technology is the human creation, so it does not come naturally, and it was digilib.uns.ac.id
artificial; (3) technology is set of means, so it can be bordered or it universals,
depends on the analysis side sight; (4) technology is purposing to facilitate
human endeavour, so technology must be able increasing human ability
performance (Kumala, 2008: 12).
Fichman in Stylanou and Jackson (2007) introduced a related argument
by distinguishing between two types of technologies in terms of the main
knowledge that each type determines the user. Type 1 technologies (e.g.
personal computers, word processing packages, graphics software) are
generally independent use technologies that are intended to facilitate
self-contained tasks performed by individual users. These technologies impose a
relatively small main knowledge and typically require only a few hours of
training before users achieve basic proficiency. In contrast, Type 2
technologies (e.g. software development process technologies) involve
significant knowledge barriers to adoption, including a lengthier training
process and a situation where the user ability, not just the willingness to use, is
a determining factor. As such, experience, attitudes, training, and supervisory
desires become valid predictor variables (Lee et al. in Stylanou and Jackson,
2007).
Facts in technology adoption based on the dynamic process, based on
empirical literature in naturally affecting static network (Ryan and Tucker in
Niagara, 2008: 12). The benefits of technology adoption is a beginning to
perpustakaan.uns.ac.id the economic agent of the corporation in the same industry. Decision of digilib.uns.ac.id
adopting technology can also relate to how a corporation developing
information technology innovation. Thus, manager in a corporation must be
prepared for what strategy will be used to adopt information technology that
took by the end user as technology acceptance (Zhu and Weyant, 2000).
Innovation in technology information done by vendor can be speed, quality
and flexibility increasing for the end user operating (Steinmueller. 2001;
Callantone, et al. 2006; in Niagara, 2008: 13).
Orlikowski and Iacono in Stylanou and Jackson (2007) point to the fact
that not enough attention is paid to the technology itself as well as to the
tendency to threat technologies as an independent and stable constant despite
the empirical evidence that highlights the impact of system design on
perceptions and use. Adopting the perspective that technology use is a
function of how the technology merges with the social environment, they point
to the silence of cultural, normative, and regulatory influences on the usage
decision (Stylanou and Jackson, 2007).
2. Conceptual of Mobile Banking
Mobile phone is no longer known as it traditional functions, i.e. voice
conversation and Short Message Services (SMS). Nowadays, the mobile
phones even facilitate for a real time teleconference through 3G (Third
Generations). Nonetheless, from the banking perspective, mobile phones
perpustakaan.uns.ac.id demand are keeping on increasing hence entrenched its feasibility as a new digilib.uns.ac.id
media of banking transaction (Amin et al., 2006).
In Barati and Mohammadi (2009), mobile banking is defined as the
“type of execution of financial services which the customer uses mobile
communication techniques in conjunction with mobile devices” (Pousttchi and
Schurig, 2004). It is defined as “a channel whereby the customer interacts with
a bank via a mobile device, such as a mobile phone or personal digital
assistant” (Barness and Corbit, Scornavacca and Barnes, in Barati and
Mohammadi, 2009). According to Amin et al. (2006), mobile banking defines
as the newest channel in electronic banking to provide a convenience way of
performing banking transaction, which is known as "pocket-banking". The
terms m-banking, m-payments, m-transfers, m-payments, and m-finance refer
collectively to a set of applications that enable people to use their mobile
telephones to manipulate their bank store value in an account linked to their
handsets, transfer funds, or even access credit or insurance products (Donner
and Tellez, 2008).
In Amin et al. (2006), Kohli (2004) claimed that the mobile banking service gives customers the convenience of account access information and
real-time transaction capabilities. Hamzah (2005) in Amin et al. (2006) said that "mobile banking" brings the convenience and enhanced value. Riivari
(2005) in Amin et al. (2006) claimed that the opportunity for mobile services is three times as many mobile phone users as those who use online PCs, and they
perpustakaan.uns.ac.id According to Donner (2006) mobile banking services enable consumers, for digilib.uns.ac.id
example, to request their account balance and the latest transactions in their
accounts, to transfer funds between accounts, to make, buy and sell orders, for
the stock exchange and to receive portfolio and price information.
There are a variety of mobile media channels, including, SMS (Short
Message Service), mobile web, mobile client application, phone banking, etc.
Each mobile media channel has its strengths and weaknesses, and it is
important to identify the delivery mode that is most appropriate for each
banking service. According to Rahardjo in Widyastuti (2008: 32), there are
some conditions for mobile banking services: (1) easy use application, (2) the
services can be reached from everywhere and every time, (3) cheap, (4) secure,
and (5) reliable. Mobile banking services generally classified into three type
characteristics (Kumala, 2008: 15), mention as follow.
1) Informational
This type is the simplest of mobile banking. It consists of products and services information from bank provider. The risk is quite low, because this system does not connect to banks’ main server and network, but connects to web hosting server.
2) Communicative
This type is enabling communication between customers and banks systems. It can be account balance information, transaction report, customer data changed, and also member services form. The risk is higher than the first above, because there is an interaction between the customers and some banking network server, which is susceptible with programs that can harm the system such as viruses.
3) Transactional
perpustakaan.uns.ac.id According to Alsindi et al. (2004) in Kumala (2008: 16), mobile digilib.uns.ac.id
banking services have some strengths and weaknesses. The strengths are
mentioned as follow.
1) WAP provides more alternatives to connect with bank customers and to increase the number of customers.
2) Bank customer can reach their banking services anytime and anywhere. 3) It can consider as one of the markets competitive advantage.
4) The used of this technology will decrease the number of customers to visit bank or ATM and also opening new branch.
The weaknesses are mentioned as follow.
1) The number of mobile banking users is very minim.
2) Mobile banking, perhaps, considered by some customers is a complex used of technology.
3) Developing mobile banking services needs a lot of cost because it needs more effort and infrastructure assure the security to do.
4) Limitation of cell phone screen width considered as one of the weaknesses because the information than shown is limited.
Mobile banking is still in development phase which needs more
concerned due to enhance the mobile banking system content to fulfill the
customer needs. When it probably completing the customer needs, the
acceptance of consumer will increase and bank can rise up their profitability.
With driving customer loyalty, engaging new segment, and empowering it own
capability, it also probably gives some opportunities to bank provider.
3. Technology Acceptance Model (TAM)
One of the most utilized models in studying information system
acceptance is the Technology Acceptance Model (TAM) (Davis et al., 1989;
Mathieson, 1991; Davis and Venkatesh, 1996; Gefen and Straub, 2000; Al-
Gahtani, 2001) in which system use (actual behaviour) is determined by
Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) relating to the
perpustakaan.uns.ac.id (Pikkarainen et al., 2004). TAM has become so popular that it has been cited digilib.uns.ac.id
in most of the research that deals with user acceptance of technology (Lee et
al., 2003).
TAM is based on the Theory of Reasoned Action (TRA), which is
concerned with the determinants of consciously intended behaviours (Fishbein
and Ajzen in Pikkarainen et al., 2004). Behavioural intention will determine
individual behavioural. Expression from behavioural intention should be
relating with high accurate prediction of related volitional action (Jogiyanto,
2007: 26). From the information systems' perspective one relevant element of
TRA is its assertion that any other factor that influences behaviour, for
example, systems design variables user, characteristics, task characteristics,
political influences and organizational structure do so only indirectly by
influencing an attitude toward behaviour, subjective norm or their relative
weights (Davis et al. in Pikkarainen et al., 2004).
Since 1967 TRA has been developed, tested and used extensively and
its extension, the Theory of Planned Behaviour (TPB) utilized widely since
1988 by Ajzen. Ajzen included a construct which was not use yet in TRA.
This construct namely perceived behavioural control which is used to control
individual behaviour that is limited by their weaknesses and their boundaries
from lack of sources used to realize their behaviour (Jogiyanto, 2007: 61).
Although the TAM and the TRA share many issues they have some
considerable differences. The first difference is that according to TRA beliefs
perpustakaan.uns.ac.id TAM states that PEOU and PU are issues that affect acceptance of all digilib.uns.ac.id
information systems. The other significant difference is that in TRA all beliefs
are summed together, but in the TAM both beliefs are seen as distinct
constructs. Modelling each belief separately allows researchers to better trace
influences of all the affecting factors on information system acceptance (Davis
et al. in Pikkarainen et al., 2004).
TAM has been tested in many studies (e.g. Davis, 1989; Davis et al.,
1989; Mathieson, 1991; Adams et al., 1992; Davis, 1993; Segars and Grover,
1993; Taylor and Todd, 1995), and it has been found that TAM’s ability to
explain the attitude toward using an information system is better than other
model’s (TRA and TPB) (Mathieson in Taylor and Todd, 1995). In other
words, the use of an information system acts as an indicator for information
system’s acceptance. There are five main constructs used in TAM:
1) perceived usefulness,
2) perceived ease of use,
3) attitude towards behaviour or attitude towards using technology,
4) behavioural intention or behavioural intention to use,
perpustakaan.uns.ac.id Figure II.1 digilib.uns.ac.id
Technology Accepted Model by Davis et al. (1989)
3.1 Perceived Usefulness
Several studies on TAM perceived usefulness as an important
antecedent of computer utilization (Davis et al. and Igbaria et al. in Selamat et al., 2009). Davis (1989) defined PU as the degree to which an
individual believes that using the system will enhance his job
performance (Alrafi, _____). From that definition, it is known that
perceived usefulness as a belief about decision making process
(Jogiyanto, 2007: 114). Many research found strong relationships
between perceived usefulness and technology usage. In the study of
mobile banking acceptance Luarn and Lin (2005) in Selamat et al. (2009)
found that perceived usefulness has a positive impact on the willingness
to use mobile banking. Therefore, it is highly predictable that people use
information technology because they find it useful. Its construct is made
by six items, i.e. work more quickly, job performance, increase
productivity, effectiveness, make job easier, and useful. External
perpustakaan.uns.ac.id 3.2 Perceived Ease of Use (PEOU) digilib.uns.ac.id
Quote from Selamat et al. (2009), PEOU is a major factor that
affects acceptance of an information system (Davis et al., 1989). PEOU
is defined as the degree to which an individual believes that using
computer or computerized system will be free from physical and mental
efforts (Davis in Alrafi, ______). From the definition, it is known that
PEOU also a belief about decision making process (Jogiyanto, 2007:
115).
According to Teo (2001) if a system is easy to use, it requires less
effort on the part of users, thereby increasing the likelihood of adoption
and usage. Conversely, if systems that are complex or difficult to use are
less likely to be adopted, since it requires significant effort and interest
on the user. Franco and Roldan (2005) in Selamat et al. (2009) found the
relationship between PEOU, and PU was significant and positively
related. This means a difficult system is less useful. The construct of
PEOU is formed by many items (Jogiyanto, 2007: 115), i.e. easy of learn,
controllable, clear and understandable, flexible, easy to become skilful,
and easy to use.
3.3 Attitude Towards Using
Attitude toward using the system is defined as the degree of
evaluative affect that an individual associates with using the target
system in his or her job (Davis et al. in Jogiyanto, 2007: 116). It refers to
perpustakaan.uns.ac.id new technology. TAM conceptualizes individual perceptions of digilib.uns.ac.id
usefulness based on instrumentality as being strongly related to attitude
toward technology use. It is also defined by Mathieson (1991) as the
user’s evaluation of the desirability of his or her using the system
(Jogiyanto, 2007: 116). Prior research showed that attitude has positive
influence to the behavioural intention, and some showed negative results.
Thus, some researches do not include this construct (Jogiyanto, 2007:
116).
3.4 Behavioural Intention
The behavioural intent constructs as a proxy to predict the actual
usage had been successful thus far (Ramayah and Ignatius, 2003).
Warshaw and Davis (1985) define behavioural intention as “the degree to
which a person has formulated conscious plans to perform or not perform
some specified future behaviour” (Ramayah and Ignatius, 2003). This is
in line with the Theory of Reasoned Action (Fishbein & Ajzen, 1975)
and its successor Theory of Planned behaviour (Ajzen, 1985), which
contend that behavioural intention is a strong predictor of actual
behaviour. In the application of information systems, the TAM has been
successfull used by many researchers to predict behavioural intent
towards the use of information technology (Ramayah and Jantan, 2003;
Ramayah, Sarkawi and Lam, 2003; Legris, Ingham, and Collerette, 2002;
perpustakaan.uns.ac.id digilib.uns.ac.id
3.5 Behaviour (Actual Usage)
The behavior construct represents a user’s subjective estimate of
the amount of time or frequency that he/she actually spends using the
technology (Stylianou and Jackson, 2007). Igbaria et al. (1995) defined perceived usage as the amount of time interacting with a technology and
the frequency of use (Gardner and Amoroso, 2004). They found strong
relationships with behavioural intent to use the technology. Igbaria et al.
in Gardner and Amoroso (2004) found that individuals are likely to use a
system if they believe it is easy to use and will increase their performance
productivity.
Actual usage, as originally conceptualized in the Davis (1989)
study, was measured by the frequency of use and the length of time of
use (Szajna, 1996). Objective measures of actual use are difficult to
obtain for Internet-based technologies and therefore, many of the TAM
studies either left out usage as a dependent variable, focusing solely on
behavioural intention or else moved to perceived usage. The construct
captures both work and entertainment related use. The mobile banking
conceptualization examines use as a function of the time spent
transaction on the mobile banking. Szajna (1996) recommended the
examination of self-reported usage. Sun (2003) in Gardner and Amoroso
(2004), reports that most TAM studies used a perceptual self-report
perpustakaan.uns.ac.id usage did not fit to the model to their research for mobile banking digilib.uns.ac.id
acceptance.
3.6 External Variables
Although TAM is a model applicable to a variety of technologies
(Adams et al., 1992; Chin and Todd, 1995; Doll et al., 1998), it has been
criticized for not providing adequate information on individuals’
opinions of novel systems (Mathieson, 1991; Moon and Kim, 2001;
Perea y Monsuwe et al., 2004; in Huang et al., 2006). Davis (1989)
observed that external variables enhance the ability of TAM to predict
acceptance of future technology. In other words, the constructs of TAM
need to be extended by incorporating additional factors. Choosing
additional factors depends on the target technology, main users and
context (Moon and Kim in Huang et al., 2006). Wang et al. (2003) in Huang et al. (2006) noted that variables relating to individual differences
play a vital role in the implementation of technology. Additionally,
empirical research based on TAM has discovered strong relationships
between individual differences and information technology acceptance
(Agarwal and Prasad in Venkatesh, 2000).
To understand user perception of mobile banking, this study use
two individual difference variables, namely “perceived mobility value”
and “perceived enjoyment”, into the proposed TAM model. These two
constructs are described as follow. Perceived Mobility Value (PMV)
perpustakaan.uns.ac.id has three different elements, including convenience, expediency and digilib.uns.ac.id
immediacy (Seppala and Alamaki in Huang et al. 2006). Mobility permits users to gain access to service or information anywhere at
anytime via mobile devices. Previous studies found that mobile users
valued efficiency and availability as the main advantages of mobile
banking, and these advantages are a result of the “mobility” of a mobile
device (Chen et al., 2003; Hill and Roldan, 2005; Ting, 2005; in Huang et
al., 2006). From paper build by exploring customer perceived value in the mobile service field, the majority of respondents show positive
critical incidents when users perceived mobile services to be especially
valuable them, description of reasons why and under which condition
they had used the service, and description of consequences of service use
in their own language (Pihlstrom, 2008: 65). Therefore, mobile banking
is valuable because of its mobility. Consequently, the perceived mobility
value is a critical factor of individual differences affecting users’
behaviors (Huang et al., 2006).
Individuals engage in activities because these activities lead to
enjoyment and pleasure (Teo and Lim, 1997). According to Davis et al.
(1992), Perceived Enjoyment (PE) is defined as “the extent to which the
activity of using the technology is perceived to be enjoyable in its own
right, apart from any performance consequences that may be anticipated”
Jogiyanto, 2007: 131). In this study, perceived enjoyment denotes the
perpustakaan.uns.ac.id intrinsically enjoyable or interesting. Perceived enjoyment is seen as an digilib.uns.ac.id
example of intrinsic motivation, and it has been found to influence user
acceptance significantly. Furthermore, research on the role of enjoyment
suggested the importance of enjoyment on users’ attitudes and behaviors
(Igbaria et al., 1995; Teo and Lim, 1997; Wexler, 2001; Yi and Hwang,
2003; in Huang et al. 2006).
B. Conceptualization And Hypotheses Development
1. Perceived Mobility Value (PMV)
PMV tested by Huang et al. (2006), it relates to users’ personal
awareness of mobility value. Mobility enables users to receive and transmit
information anytime and anywhere (Huang et al., 2006). The mobility
associated with time-related needs will encourage users to adopt mobile
technology since enhanced accessibility is expected to affect dynamic
interaction and high levels of engagement (Anckar and D’Incau, 2002 in
Huang et al., 2006). Earlier research supports the importance of conditional
value, in that people in general lack motivation to use new mobile services
unless these services create value in situations where mobility really matters
and thereby affect people’s lives positively (Jarvenpaa et al. in Pihlstrom,
2008: 183)
Hence, users who perceive the value of mobility also understand the
uniqueness of mobile banking and have a strong perception of its usefulness.
perpustakaan.uns.ac.id perceived usefulness of mobile banking. Therefore, this work treats perceived digilib.uns.ac.id
mobility value as a direct antecedence of perceived usefulness.
H1: Perceived mobility value has a positive effect on perceived usefulness of mobile banking.
2. Perceived Enjoyment
The concept of perceived enjoyment (PE) adapted from Davis et al.
(1992) means that users feel enjoyable from the instrumental value of using
mobile banking. Prior studies on technology acceptance behaviour examined
the effects of perceived enjoyment on perceived ease of use (Igbaria et al.,
1996; Venkatesh, 2000; Venkatesh et al., 2002; Yiand Hwang, 2003; in
Huang et al., 2006). New technologies that are considered enjoyable are less
likely to be difficult to use. By extending these results to the context of the
mobile banking, we can therefore postulate that perceived enjoyment will
have a positive effect on perceived ease of use.
H2: Perceived enjoyment has a positive effect on perceived ease of use of mobile banking.
There is a causal relationship between perceived enjoyment and
attitudes. When users feel that mobile banking is enjoyable, the stimulus of
happiness in turn enhances their perception of mobile banking. Venkatesh
(2000) found that perceived enjoyment indirectly influences users on
adoption. Another research showed that attitudinal outcomes, such as
happiness, pleasure, and satisfaction, result from the enjoyable experience
perpustakaan.uns.ac.id al., 2005; in Huang et al., 2006). These findings indicate that enjoyment digilib.uns.ac.id
highly correlates with the users’ positive attitudes.
H3: Perceived enjoyment has a positive effect on attitude toward using mobile banking.
3. Perceived Ease of Use, Perceived Usefulness, Attitude, and Behavioural
Intention
Perceived ease of use has been found to influence the usefulness,
attitude intention, and actual use (Chau in Gardner and Amoroso, 2004).
Chau study revealed that perceived ease of use significantly affected
perceived usefulness, but did not significantly affect intention to use. In the
context of the mobile banking, we can postulate positive relationships
between perceived ease of use and two constructs, perceived usefulness of
mobile banking and attitude toward using mobile banking.
H4: Perceived ease of use of the mobile banking has a positive effect on perceived usefulness of mobile banking.
H5: Perceived ease of use of the mobile banking has a positive effect on attitude toward using mobile banking.
Perceived usefulness is the degree to which an individual believes that
using a particular system would enhance his or her performance. Usefulness
has been confirmed to be the most important factor affecting user acceptance
with few exceptions (Sun in Gardner and Amoroso, 2004). Hence, perceived
usefulness of mobile banking is likely to be positively related to attitude
toward using mobile banking.
perpustakaan.uns.ac.id In TAM, behavioural intention is influenced by both perceived digilib.uns.ac.id
usefulness and attitude. This relationship has been examined and supported
by many prior studies (Adams et al., 1992; Davis et al., 1989; Hu et al., 1999;
Venkatesh and Davis, 1996, 2000; in Huang et al., 2006). Therefore, this study presents the following hypotheses.
H7: Perceived usefulness of mobile banking has a positive effect on behavioural intention toward using the mobile banking.
H8: Attitude has a positive effect on behavioural intention toward using the mobile banking.
C. Conceptual Framework
According to prior research, the objective of this research is to examine
and verify that the TAM can be employed to explain and predict the acceptance
of mobile banking using two factors that account for individual differences, i.e.
Perceived Mobile Value (PMV) and Perceived Enjoyment (PE). It will adopt
perpustakaan.uns.ac.id CHAPTER III digilib.uns.ac.id
RESEARCH METHODOLOGY
A. Research Design
This research tries to explain an effect of perceived mobile value on
perceived usefulness and perceived enjoyment on attitude towards using mobile
banking and perceived ease of use with TAM model. It uses quantitative research
method with hypothesis test. Sekaran (2000: 108) defines that hypothesis is a
logically conjectured relationship between two or more variables expressed in the
form of a testable statement.
B. Population and Sample
Population in this research is bank customers who use mobile banking
service in Indonesia. The sample is bank customers who use mobile banking
service who stay in Jakarta. Sample size has an important role for SEM
interpretation result. Sample size becomes based on sampling error estimation.
With estimation model using Maximum Likelihood (ML), it requires at least 100
samples. When the sample raises more than 100, the ML sensitivity will increase
to detect differential among data. When sample size become large (400-500
samples), ML will be a very sensitive and will always result in significant
differential so goodness of fit measurement will be poor. Ghozali (2008: 64)
perpustakaan.uns.ac.id C. Data Source and Data Collecting Technique digilib.uns.ac.id
This research will use primary data, which is directly obtained from the
respondents, with purposive convenience sampling technique. Purposive
convenience sampling is collecting information from members of the population
who are conveniently available to provide it. Each respondent will be asked to
give their evaluation about the statements or questions by choosing answers
served with a Likert scale ranging from 1 for totally disagreeing to 4 for totally
agree.
D. Measurement Items
Measurement items used in this research particularly for the core
constructs (six key determinants) of the proposed research model have been
adapted from the measurement items originally used in many theories. All
original measurement items used in measurements of the core constructs of the
theories or models including perceived mobility value, perceived enjoyment,
perceived usefulness, perceived ease of use, attitude toward using, behavioral
intention had statistical explanation and prediction under investigation by
Gardner and Amoroso (2004), Huang et al. (2006), and Jogiyanto (2007). The
29
Type Items Source Questionnaire
PE Perceived
PE1 Saya akan senang menggunakan mobile banking.
PE2 Mobile banking akan menjadi hal yang menarik.
PE3 Mobile banking akan membuat saya merasa baik.
PMV Perceived mobility
value
Independent 4 Huang et al (2006) PMV1 Saya tahu bahwa perangkat mobilitas (handphone, laptop,
dsb) adalah media untuk mobile banking.
PMV2 Saya merasa mudah mengakses mobile banking di mana saja
dan kapan saja.
PMV3 Mobile Banking memungkinkan saya melakukan transaksi
pada saat itu juga (real time data/transaction).
PMV4 Mobilitas adalah keuntungan utama dari mobile banking.
PU Perceived
PU1 Penggunaan mobile banking dapat mempercepat penyelesaian transaksi.
PU2 Penggunaan mobile banking dapat meningkatkan kinerja saya.
PU3 Penggunaan mobile banking dapat memudahkan pekerjaan saya.
PU4 Penggunaan mobile banking dapat menghemat waktu saya.
PU5 Penggunaan mobile banking dapat meningkatkan efektivitas saya dalam bertransaksi.
30
Source: Adopted from Gardner and Amoroso (2004), Huang et al. (2006), and Jogiyanto (2007)
Variable Description Constructs
Type Items Source Questionnaire
PEOU Perceived
PEOU1 Menggunakan mobile banking merupakan hal yang
mudah bagi saya.
PEOU2 Penggunaaan mobile banking jelas dan mudah dipahami.
Huang et al. (2006); PEOU3 Penggunaan mobile banking fleksibel.
Jogiyanto (2007) PEOU4 Penggunaan mobile banking tidak membutuhkan terlalu
banyak usaha berpikir.
ATT1 Menurut Saya, mobile banking sangat dibutuhkan.
ATT2 Saya mendapat hasil positif dari mobile banking..
ATT3 Saya ingin menggunakan mobile banking.
BI Behavioral intention
Dependent 5 Gardner and Amoroso
(2004):
BI1 Saya memilih menggunakan mobile banking dalam penyelesaian transaksi saya.
Huang et al. (2006); BI2 Saya berencana untuk menggunakan mobile banking
untuk penyelesaian transaksi di masa yang akan dating
Jogiyanto (2007)
BI3 Di masa depan, saya berniat untuk menggunakan mobile banking secara rutin.
perpustakaan.uns.ac.id E. Data Analyze Technique and Hypotheses Test digilib.uns.ac.id
1. Data Test Technique
a. Validity test
Validity is the extent to which the data collected truly reflect the
phenomenon being studied. For the sake of the clarity, Sekaran (2000)
can group validity test under three broad headings: content validity,
criterion-related validity, and construct validity. This research use
construct validity test because this approach is more objectives, simple
and it use in many research.
Construct validity testifies to how well the results obtained from
the use of the measure fit the theories around which the test is designed
(Sekaran, 2000: 208). Any biases could also be detected if the
respondents had tended to respond similarly to all items or stuck to only
certain points on the scale (Sekaran, 2000: 208). To test whether latent
constructs are unidimensional or indicators measurement constructs are
valid. First, we must see whether indicators are statistically significant or
not. Second, we must see convergent validity value or loading factor
value for each indicator. Some established research use 0,70 for good
validity value. While convergent validity 0,50-0,60 still acceptable for
earlier research (Ghozali, 2008: 132).
b. Reliability Test
The reliability of a measure indicates the extent to which the
perpustakaan.uns.ac.id measurement across time and across the various items in the instrument digilib.uns.ac.id
(Sekaran, 2000: 204). According to Ticehurst and Veal (2000) in
Kripanont (2007: 128), reliability is the extent to which research findings
would be the same if the research were to be repeated at a later date, or
with a different sample of subjects. A construct or variable is said reliable,
if the Cronbach’s alphavalue is >0,70 (Ghozali, 2008: 137). According to
Sekaran (2006) in Bhilawa (2010: 33), reliability less than 0.6 is
considered to be poor, those in the 0.7 is acceptable, and those over 0.8 is
good. The closer the reliability coefficient gets to 1.0 is the better.
c. Normality Data Assumption
SEM requires normal distribution of data. If data distributes
abnormal, maybe it will influence data analysis resulting to high bias
data. In this research, normality test is counted by using computerized
program, AMOS 18. The postulate used in this research to examine data
normality is the critical ratio (cr) value. The data distribution is normal if
cr skewness value or kurtosis cr value is between -2,58 and +2,58
(Wijaya, 2009: 134). Curran et al. in Bhilawa (2010: 34) divides
normality data level into three parts, they are:
• normal, if z statistic value (critical ratio or c.r.) skewness < 2 and
c.r. kurtosis value is < 7,
• moderately non-normal, if c.r skewness is between 2 to 3 and c.r
perpustakaan.uns.ac.id • extremely non-normal, if c.r. skewness is >3 and c.r. kurtosis is> digilib.uns.ac.id
21.
d. Outlier Evaluation
Outlier is the observation that appears with extremely values,
which have a unique different characteristic from other observation, and
it appears on extreme value, whether it on one variable or combination
variables (Hair et al. in Bhilawa, 2010: 33). Outlier can be handled with
erasing one or some data which far from the certain spot center.
Test to multivariate outliers is done using Mahalanobis Distance
criteria at the level p<0,001. Mahalanobis Distance evaluated using χ2 at
free degree as big as variables sum, which is used in research (Ferdinand
in Bhilawa, 2010: 33). This outlier evaluation is done with computer’s
software, AMOS 18.
2. Model Assumption Test
This research uses Structural Equation Modeling (SEM) multivariate
analyzing to examine hypotheses using AMOS 18 software. SEM is a
statistical model that provides approximate calculation of the strength of the
hypothesis on the relationship between variables in a theoretical model, either
directly or through intervening variables (Maruyama in Wijaya, 2009: 1).
SEM refers to the relationship between endogenous variables and exogenous
variables, which is the variable can not be observed or calculated directly
perpustakaan.uns.ac.id AMOS 18 used to examine whether the estimated model has goodness of fit digilib.uns.ac.id
and has causality relation as hypothesized. The test consists of:
a. Goodness of Fit Measurement
Structural model categorized as “good fit” if it fulfills these conditions
below.
1)Chi-Square (χ2) Measurement Statistic (CMIN)
This analysis is purposing to develop and examine a model
which appropriate with the data. Chi's square is so sensitive to very
small sample as well as to very large sample. Thus, this examination
needs to complete with another examine the instrument (Ghozali,
2008: 130). CMIN shows the likelihood ratio chi-square statistic for
each fitted model (tested against the saturate model). If the p value for
each model is greater than 0.05, this means that the data do not depart
significantly from the model.
Furthermore, if at each step up the hierarchy from the
unconstrained model to the measurement residuals model, the increase
in chi-square is never much larger than the increase in degrees of
freedom (a non-significant chi-square, p value greater than 0.05), the
model up the hierarchy is preferable otherwise, the model up the
hierarchy is worse (a significant chi-square, p value less than 0.05)
perpustakaan.uns.ac.id 2)Minimum Probability Value Level digilib.uns.ac.id
P value is the probability of getting as large a discrepancy as
occurred with the present sample under appropriate distributional
assumptions and assuming a correctly specified model. So P is a “p value” for testing the hypothesis that the model fits perfectly in the population. Therefore, this is a method to select the model by testing
the hypothesis to eliminate any models that are inconsistent with the
available data (Kripanont, 2007: 192). The minimum probability value
level that needs is 0,1 or 0,2, but for probability level about 0,05 is
still able. (Hair et al. in Bhilawa, 2010: 36). 3)Normed Chi-Square (CMIN/DF)
This index is chi square value divided with degree of freedom.
According to Wheaton et al. (1977), ratio value ≤ 5 is a reasonable
measurement. Other researchers such as Byrne (1988) suggest to this
value ratio < 2 is a fit measurement (Ghozali, 2008: 67). CMIN/DF
(χ2 / df) is the minimum discrepancy divided by its degrees of
freedom; the ratio should be close to 1 for correct models. Although
Arbuckle (2005) claimed that it is not clear how far from 1 we should
let the ratio get before concluding that a model is unsatisfactory. In
contrast, Byrne (2006) suggested that ratio should not exceed 3 before
it cannot be accepted. Since the chi-square statistic (χ2) is sensitive to
sample size it is necessary to look at others that also support goodness
perpustakaan.uns.ac.id 4)Measures Based on the Population Discrepancy digilib.uns.ac.id
The Root Mean Square of Approximation (RMSEA) indicates
expected goodness of fit if the model estimated in population.
Recommended RMSEA acceptant value is ≤ 0,08 (Wijaya, 2009: 7).
According to Ghozali (2008: 67), RMSEA value between 0,05 to 0,08
is acceptable.
5)Goodness of Fit Index (GFI)
GFI is a goodness- of- fit index for ML (Maximum likelihood)
and ULS (Unweighted Least Squares) estimation (Kripanont, 2007:
193). GFI is used to calculate the weighted proportion of the variance
in the sample covariance matrix described by the covariance matrix in
estimated population (Wijaya, 2009: 8). Recommended acceptant
level by GFI is ≥ 0,90 (Ghozali, 2008: 67).
6)Adjusted Goodness of Fit Index (AGFI)
AGFI is GFI development, adjusted with degree of freedom
that is available to test whether the model accepted. Recommended
value is > 0,90 (Ghozali, 2008: 67). Wijaya (2009: 8) also
recommends AGFI value for at least equals or greater than 0,90.
7)Tucker Lewis Index (TLI)
TLI is an incremental fit index alternative that compares a
tested model against a baseline model (Wijaya, 2009: 8). TLI is a
index fit measure that less influenced by sample size. Recommended
perpustakaan.uns.ac.id 8)Comparative Fit Index (CFI) digilib.uns.ac.id
CFI is also known as Bentler Comparative Index. CFI is
incremental fit index which also compares the tested model with null
model (Wijaya, 2009: 8). This index is quite good for measuring the
goodness of fit because it is not influenced by sample size.
Recommended value by CFI is ≥ 0,90 (Wijaya, 2009: 9).
9)Normed Fit Index (NFI)
NFI is a comparison measurement between proposed model
and null model. NFI value is various starting from 0 (no fit at all) to 1
(perfect fit). In parallel with TLI, NFI does not have an absolute
standard value, but generally it recommends for equals or more than
0,90 (Ghozali, 2008: 68).
Table III.2 Goodness of Fit Indices
Fit Indices Cut Off
Value Source
Chi-Square Approaches 0 Wijaya, 2009
Probability level ≥ 0.05 Wijaya, 2009
NFI Approaches 1 Ghozali, 2008
perpustakaan.uns.ac.id Figure III.1 digilib.uns.ac.id
TAM with Perceived Mobility Value (PMV) and Perceived Enjoyment (PE)
3CHAPTER III
perpustakaan.uns.ac.id CHAPTER IV digilib.uns.ac.id
DATA ANALYSIS
This chapter will describe the data analysis and research results about mobile
banking acceptance with external variables using perceived mobility value variable
and perceived enjoyment variable with Technology Accepted Model (TAM). It will
be divided into three parts: (1) describing about data research collection and
respondents demographic descriptions, (2) data test analysis, (3) model assumption
analysis, and (4) hypotheses test.
A. Data Collection Analysis
1. Total Data Collection
Data collected from 80 questionnaires were directly distributed to
respondents and 110 questionnaires were distributed by email. Based on the
sample criteria discussed above, this study has obtained 67 respondents by
direct distribution and 65 respondents by email distribution, so 132 samples
total are obtained. From table IV.1 we can see that level of returned
questionnaires is 69.47% from 190 distributed questionnaires which one of
them can not be processed. So, there are 131 questionnaires that can use for
perpustakaan.uns.ac.id Table IV.1 digilib.uns.ac.id
Data Research Collection
Source: Primary data processing (2011)
2. Respondents Demography
a. Respondents Characteristics
From table IV.2 we can see that majority of respondents’ age range
between 21-25 years old with 62 respondents (47.33%), and the second
majority is between 26-30 years old with 22 respondents (16.79%). It
shows that there are much more productive respondents than
unproductive respondents. The minority respondents’ age is between
51-55 years old and >51-55 years old (2.29%). Researcher has the youngest
respondent with 19 years old and the oldest with 83 years old.
b. Respondent Gender
Based on data collection, respondent gender characteristic describes
as follows. There are 62 men respondents (47%), 62 women respondents
(47%), and seven respondents did not answer it (6%).
DESCRIPTION TOTAL PERCENTAGE
Questionnaire distributed 190 100%
Questionnaires returned 132 69.47%
Questionnaire which can not be processed 1 0.76%
perpustakaan.uns.ac.id Table IV.2 digilib.uns.ac.id
Respondent Age
Source: Primary data processing (2011)
Figure IV.1 Respondent Gender
c. Respondent Educational Background
Based on data collection, respondent educational background
characteristic describes as follows. There are 81 S1 graduates as majority educational background (61.83%). Second, 30 respondents are D3
graduates (22.9%). Then 10 respondents are SLTA or equals graduates Age Range Total Percentage
≤20 9 6.87%
21-25 62 47.33%
26-30 22 16.79%
31-35 7 5.34%
36-40 12 9.16%
41-45 4 3.05%
46-50 5 3.82%
51-55 3 2.29%
>55 3 2.29%
NO ANSWERS 4 3.05%
TOTAL 131 100%