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Edward Adi, Sfenrianto (2024) Analysis of Factors that Influence the Use of Online Investment
Applications (Ajaib), (06) 08,
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2684-883X
ANALYSIS OF FACTORS THAT INFLUENCE THE USE OF ONLINE
INVESTMENT APPLICATIONS (AJAIB)
Edward Adi, Sfenrianto
Bina Nusantara University, Indonesia
Email: [email protected], [email protected]
Abstract
The purpose of this study is to analyze the factors that influence people who use the Ajaib
mutual fund application. The proposed model considers factors from Technology Adoption
Theory (TAM), which are implemented in this study to analyze how technology adoption
impacts investments in online mutual funds, with Millennials being the focus of the primary
research. This research is quantitative in nature and uses the survey method through the
distribution of online questionnaires. Sampling using purposive sampling method. This study
Used 5 internal variables and 3 external variables which are User Interface, Perceived
Security and Perceived Risk. After collecting data from 400 respondents, it was found that
there are several factors that positively influence the actual use of the online mutual fund
application adoption system, User Interface, Perceived Security, Perceived Risk, Perceived
Usefulness, Perceived Ease of Use, Attitude Towards Use, and Behavioral Intention off Use
on the Ajaib application actual use of the system. This insight will be helpful for online
mutual fund application developers to convert the traditional mutual fund into an online
platform format.
Keywords: Online Mutual Fund Investment Application, Technology Acceptance Model
(TAM), User Interface, Perceived Security, Perceived Risk, Millennial generation
INTRODUCTION
As time progresses, the number of financial services sectors in Indonesia that apply
information technology has increased significantly due to the significant benefits provided by
FinTech, namely increasing the efficiency of the financial ecosystem. The introduction of
FinTech in the financial services sector is carried out through online investment platforms.
Online investment is currently being widely discussed among the general public and
investors. The most popular online investment currently is online mutual fund investment.
One of the most important contributions to the investment sector in Indonesia comes from
investment in mutual funds. Central Securities Depository PT Indonesia (KSEI) found that the
number of unique investor identifiers (SIDs) for mutual fund investors increased by 62.68%
in July 2021 from 3,175,428 SIDs in 2020. In 2021 it will be 5,165,798 SIDs. The age
demographic of investors is dominated by people aged under 30 (58.58%) and 31 – 40
(21.63%) Indonesia, (2021) as seen in figures 1 and 2 under:
JOURNAL SYNTAX IDEA
p–ISSN: 2723-4339 e-ISSN: 2548-1398
Vol. 6, No. 08, Agustus 2024
Analysis of Factors that Influence the Use of Online Investment Applications (Ajaib)
Syntax Idea, Vol. 6, No. 08, Agustus 2024 3487
Figure 1. SID Data from Indonesian Central Securities Custodian (ICSC)
Figure 2. SID Demographics from the Central Securities Custodian (ICSC)
The data above shows that the number of mutual fund investors has increased since the
advancement and existence of online mutual fund investment platforms. With the growth of
innovation, improvements in the capital markets industry, and the presence of FinTech, it is
becoming easier for potential investors to open securities accounts (Rahadi et al., 2021).
One of the successful implementations of online mutual fund investment in Indonesia is
the Ajaib Application, which is an investment application that makes it easy for users to
invest in mutual funds and shares in the form of an online platform. Ajaib offers the best
selection of mutual funds and a real-time stock trading platform. Apart from that, Ajaib also
offers a variety of investment lessons for beginners to advanced investors. So everyone not
only has access to safe investment products, but also the knowledge to support them. Ajaib
Reksa Dana or PT Takjub Teknologi Indonesia is registered with the OJK with license
number KEP-17/PM.21/2018 and was founded in 2019 in Indonesia. Having a vision to open
the door to access to safe and reliable investments, Ajaib provides online mutual fund
services. Investors can invest in shares, bonds and money markets through mutual funds that
suit each individual's risk profile." PT Takjub Teknologi Indonesia or Ajaib Reksa Dana was
founded in 2019 and is registered with the Financial Services Authority with license number
KEP-17/PM.21/2018. Ajaib provides online mutual fund services with the vision of opening
the door to safe and reliable investment. Investors can invest in stocks, bonds and money
markets through mutual funds that suit their respective risk profiles. Ajaib is one of the
mutual fund applications in Indonesia with the fastest acceptance rate among Indonesian
society. Even though this application was only launched to the public in 2019, the number of
users who have joined the Ajaib Application and Use to transact mutual funds has beaten
other competitors who have been involved in this for a long time. in the mutual fund sector
such as Pluang, Stockbit and so on (Marqués et al., 2021). Therefore, the author decided to
use Ajaib as the subject of this research.
The Central Statistics Agency (BPS) projects that the Millennial generation and the
younger generation will become the majority generation in the demographic structure in
Indonesia (Nour Aldeen, Ratih, & Sari Pertiwi, 2022). Therefore, the high number of
millennials and younger generations can be a strong basis for using technology-based
Edward Adi, Sfenrianto
3488 Syntax Idea, Vol. 6, No. 08, Agustus 2024
financial applications, therefore it is important to focus the development of mutual fund
platforms according to the right potential users.
However, the Central Statistics Agency (BPS) also reported in the 2020 population
census report (SP2020), Indonesia was recorded as having more than 270 million residents, of
which 25.87% consisted of the millennial generation and 27.94% were generation Z (Statistik,
2020) making it a third of all Indonesian population. This means that the number of mutual
fund investors is still relatively small compared to Indonesia's millennial population.
The investment sector has an important role in a country's economy, especially in
developing countries like Indonesia. Without good investment prospects, it is difficult to
improve the economy on a high scale that will bring prosperity to developing countries. The
purpose is used to accelerate the pace of improvement and the economy is through the capital
market with activities such as public offerings and securities trading, where public companies
will handle activities related to securities issues, both institutions and professions related to
securities.
In order to increase the number of Indonesian SIDs and attract the attention of potential
investors through online mutual funds, this research will provide information regarding the
factors that influence the use of the Ajaib mutual fund investment application in the millennial
generation so that the results of this research can be used for future online mutual fund
application developers. to attract potential Millennial investors.
RESEARCH METHOD
The type of data used in this research is quantitative data. The data source used in this
research is primary data obtained by distributing questionnaires in electronic form using
Google forms to Ajaib Application users in carrying out investment activities. In preparing
this questionnaire, a Likert scale was used. Next, the respondent will provide an assessment of
the statement that has been prepared. Because exact user data from the Ajaib Application is
not yet available, the researchers took the total population from the number of mutual fund
users taken from KSEI data (2021) as of July 2021 with ages 31 – 40 years and <= 30 years
domiciled in Indonesia. In this study, the sampling technique used was purposive sampling,
namely a sampling technique based on certain criteria (Chandrarin, 2017). A particular
consideration in this study is that respondents who were asked to fill out the questionnaire had
criteria as users of the Ajaib Application. Sampling was obtained with the following criteria:
1. People born in 1982 – 2000 (Millennial Generation).
2. People who live on the island of Java, Indonesia (70.07% of Indonesian investors
according to KSEI data, 2021)
3. People who use the Ajaib application to carry out investment activities
4. The sample size used in this research is a total of approximately 4,2 million Ajaib
application users in Indonesia
The technique used to determine the sample size is to use the calculation method from
(Belot, Ginglinger, Slovin, & Sushka, 2014), using the Slovin method to calculate a
representative sample that is suitable for the model, while using the hair model to calculate
the minimum sample requirements for the model.
Population is a generalized area consisting of objects or subjects that have a certain
number and set of characteristics chosen by a researcher to study and become the basis for a
conclusion. The target group for this research consists of Ajaib application users or 4.2
million people.
Analysis of Factors that Influence the Use of Online Investment Applications (Ajaib)
Syntax Idea, Vol. 6, No. 08, Agustus 2024 3489
The formula used to determine the number of samples is the Slovin method. According
to Ridwan's 2007 research study, the Slovin formula can be used as follows to determine the
minimum number of samples that must be obtained for research:
Based on the explanation above, the following is the sample size calculation using the
Slovin formula:
With explanation:
n = Number of Samples
N = Total Population
E = error tolerance limit (5% / 0.05)
Thus, the minimum sample size for this study is 399.9 or rounded up to 400 respondents
using the Slovin method.
Analytical Approach
Data will be analyzed using PLS-SEM. Then SEM-PLS (Structural Equation Modeling-
Partial Least Square) analyzes the data using the smartPLS 3 application. Analyze the data
using SEM-PLS, taking a useful model path so that the diagram can display the hypothesis
and relationship of the variables to be tested. To evaluate the measurement model, a series of
tests will be carried out using SmartPLS, namely an outer model test which contains a
convergent validity test using outer loading and Average Variance Extracted (AVE) values, a
discriminant validity test using variable cross loading values and a reliability test using
Cronbach's alpha (α) and Composite reliability (CR) value. Meanwhile, measurements for
hypothesis testing are tested on the inner model by looking at the T-Statistic and P values in
the Path coefficient analysis. At this stage, the coefficient of determination (R2) and effect
size (f2) are also tested to determine the significance of each variable.
Research Model
After conducting a literature study, this research will adopt the Technology Acceptance
Model (TAM) by Davis (Davis, 1989) and use all dependent and independent variables,
namely Perceived ease of use (PEOU), Perceived usefulness (PU), Behavioral Intention to
Use (BIU), Attitude Toward Using (ATU), and Actual System Usage (AU) with additional
external factors added by the author as contributions and research novelties such as User
Interface (UI), Perceived Security (PS) and Perceived Risk (PR) as shown in the image model
3 below:
Figure 3. Research Model
Research Hypothesis
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3490 Syntax Idea, Vol. 6, No. 08, Agustus 2024
In the model depicted in figure 3, hypotheses are formulated based on the direct
relationships between two variables. Each hypothesis assesses the substantial positive impact
of a variable, with the arrow indicating the direction from one variable to the affected
variable. As a result, 10 hypotheses were developed as follows:
1. H1: User Interface (UI) has a positive and significant effect on Perceived Usefulness (PU)
of online investment applications (Ajaib)
2. H2: User Interface (UI) has a positive and significant effect on Perceived Easy of Use
(PEOU) of online investment applications (Ajaib)
3. H3: Perceived Security (PS) has a positive and significant effect on Perceived Usefulness
(PU) of online investment applications (Ajaib)
4. H4: Perceived Security (PS) has a positive and significant effect on Perceived Easy of Use
(PEOU) online investment applications (Ajaib)
5. H5: Perceived Risk (PR) has a positive and significant effect on Perceived Usefulness (PU)
of online investment applications (Ajaib)
6. H6: Perceived Risk (PR) has a positive and significant effect on Perceived Easy of Use
(PEOU) of online investment applications (Ajaib)
7. H7: Perceived Usefulness (PU) has a positive and significant effect on Attitude Toward
Using (ATU) online investment applications (Ajaib)
8. H8: Perceived Easy of Use (PEOU) has a positive and significant effect on Attitude
Toward Using (ATU) online investment applications (Ajaib)
9. H9: Attitude Toward Using (ATU) has a positive and significant effect on Behavioral
Intention to Use (BIU) online investment applications (Ajaib)
10. H10: Behavioral Intention to Use (BIU) has a positive and significant effect on Actual
System Usage (AU) of online investment applications (Ajaib)
This research uses a total of 28 questions developed from several previous studies on
TAM as shown in table 1.
Table 1 Research Statement
No
Questionnaire statement
Source
1
By using the Ajaib Application, I can complete mutual
fund transactions faster (PU1)
(Davis, 1989) (Raman &
Viswanathan, 2011)
2
Using the Ajaib Application makes mutual fund
transactions easier (PU2)
3
Mutual fund transactions are more effective using the
Ajaib Application (PU3)
4
Overall, the Ajaib Application is very useful for carrying
out mutual fund transactions (PU4)
5
Learning Ajaib Application is easy (PEOU1)
(Davis, 1989) (Raman &
Viswanathan, 2011)
6
Easy to understand steps to use Ajaib Application
(PEOU2)
7
No additional effort required in using the Ajaib
Application for mutual fund transactions (PEOU3)
8
Overall, the Ajaib Application is easy to use (PEOU4)
9
The display design in the Ajaib Application is easy to
see and read (UI1)
(Nikou & Economides, 2017)
10
Ajaib Application provides good page layout (UI2)
11
Ajaib Application provides well-designed menu
Analysis of Factors that Influence the Use of Online Investment Applications (Ajaib)
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navigation and icons as well as a clear information
structure. (UI3)
12
I am worried about the quality of the products sold at
Ajaib (PR1)
(Suresh & Shashikala, 2011)
13
Based on considerations regarding costs, it would be
very risky to buy products from Ajaib (PR2)
14
I feel there is a risk if I provide personal information to
Ajaib (PR3)
15
I feel there is a risk of becoming a victim of fraud if I
buy products at Ajaib (PR4)
16
I would feel disadvantaged if I gave personal
information to Ajaib (PR5)
17
I feel Ajaib in providing information that creates many
unexpected problems (PR6)
15
I feel safe when making transactions on the Ajaib
Application (PS1)
(Chawla & Joshi, 2019)
16
I believe that personal information contained in the
Ajaib Application will not be spread to other people
(PS2)
17
I feel the information security on the Ajaib Application
is reliable (PS3)
18
I believe that customer service from the Ajaib
Application will help me if there are problems with
transactions in the Ajaib Application (PS4)
19
I love using the Ajaib Application (ATU1)
(Chawla & Joshi, 2019)
20
In my opinion, it is highly recommended to use Ajaib
when conducting mutual fund transactions (ATU2)
21
Overall, using the Ajaib Application was a pleasure
(ATU3)
22
I want to use the Ajaib Application to carry out mutual
fund transactions (BIU1)
(Chawla & Joshi, 2019;
Venkatesh, Morris, Davis, &
Davis, 2003)
23
I will often invest in Ajaib Application mutual funds
(BIU2)
24
I will use Ajaib Application in the future (BIU3)
25
I recommend Ajaib Application to others (BIU4)
26
I used the Ajaib Application a lot over the past week
(AU1)
(Raman & Viswanathan, 2011;
Wibowo, 2008)
27
I have used the Ajaib Application a lot over the past
month (AU2)
28
Overall, I am satisfied with the performance of Ajaib
Application (AU3)
RESULT AND DISCUSSION
Respondent Profile
The results below show the demographic profile of 400 respondents which corresponds
to the researcher's sample criteria where respondents must be aged 23 – 40 years. The
questionnaire collection period lasted three weeks from 15 January to 4 February 2024 which
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3492 Syntax Idea, Vol. 6, No. 08, Agustus 2024
was distributed using Google form. Table 2 below contains details of respondent data that are
suitable for further analysis.
Table 2 Respondent Profile
Category
Choice
#
%
Gender
Male
284
71
Female
116
29
Age
<23 years
old
0
0
23 – 30
years old
207
52
31 – 35
years old
105
26
36 – 40
years old
88
22
Level of
education
Bachelor
266
66,5
Master
108
27
Doctor
13
3,3
Diploma
10
2,5
High
school or
below
3
0,8
Occupation
Employee
205
51,3
Self-
employed
81
20,3
Student
34
8,5
Others
80
20
Ajaib
Application
Users
Yes
400
100
No
0
0
The results obtained from distributing the questionnaire were that 71% of respondents
were male and the rest were female, slightly more than quarter of the respondents.
Respondents with aged between 23-30 years with total 56%, aged 31-35 with total 26%,
aged 36-40 years with total 22% shows that the majority of respondents are millennials
generation.
More than half of the respondents have a bachelor's degree, as much as 27% have a
master's degree, as much as 3,3% have a doctor's degree, as much as 2,5% have a diploma's
degree, as much as 0,8% have a high school or below degree.
Almost half of the respondents were Employee which implies Ajaib application
provides an opportunity for millennial customers to be part of mutual fund transactions, as
much as 20,3% were Self-employed, as much as 20% were have others occupation and 8,5%
were Student.
Convergent Validity Test
In evaluating the measurement model, discriminant and convergent validity tests are
carried out, where to measure convergent validity, the Outer loading value must be greater
than 0.7 for each indicator, and the Average Variance Extracted (AVE) must be greater than
0.5. The value must be met to be accepted. If the condition value is not met, then the indicator
must be removed from the analysis process (Ghozali, 2008).
Analysis of Factors that Influence the Use of Online Investment Applications (Ajaib)
Syntax Idea, Vol. 6, No. 08, Agustus 2024 3493
Table 3 Outer Loading Value
Indicator
Outer
Loading
Value
Results
UI1
0.924
Valid
UI2
0.810
Valid
UI3
0.921
Valid
PS1
0.887
Valid
PS2
0.855
Valid
PS3
0.888
Valid
PS4
0.850
Valid
PR1
0.876
Valid
PR2
0.883
Valid
PR3
0.887
Valid
PR4
0.884
Valid
PR5
0.881
Valid
PR6
0.872
Valid
PU1
0.900
Valid
PU2
0.879
Valid
PU3
0.886
Valid
PU4
0.885
Valid
PEOU1
0.905
Valid
PEOU2
0.879
Valid
PEOU3
0.881
Valid
PEOU4
0.883
Valid
ATU1
0.916
Valid
ATU2
0.836
Valid
ATU3
0.928
Valid
BIU1
0.908
Valid
BIU2
0.890
Valid
BIU3
0.904
Valid
BIU4
0.876
Valid
AU1
0.935
Valid
AU2
0.822
Valid
AU3
0.938
Valid
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3494 Syntax Idea, Vol. 6, No. 08, Agustus 2024
Table 4 Average Variance Extracted (AVE) Value
Indicator
Average
Variance
Extracted
(AVE)
Value
Results
User
Interface
(UI)
0.786
Valid
Perceived
Security
(PS)
0.758
Valid
Perceived
Risk (PR)
0.776
Valid
Perceived
Usefulness
(PU)
0.788
Valid
Perceived
Ease of
Use
(PEOU)
0.787
Valid
Attitude
Toward
Using
(ATU)
0.799
Valid
Behavioral
Intention
to Use
(BIU)
0.800
Valid
Actual
System
Usage
(AU)
0.810
Valid
Table 3 and 4 shows the outer loading and AVE values from the questionnaire results. It
can be seen that all indicators meet the values required for outer loading validity, namely
more than 0.7 for each item in the study. Likewise, with the AVE value, no indicator must be
removed because the valid value of AVE for each item is greater than 0.5.
Reliability Test
Reliability testing is also carried out on questions used to determine quality. A variable
is said to be reliable if the Cronbach's alpha (α) value is above 0.6, whereas if it is 0.6-0.7 it is
considered acceptable and 0.7-0.9 satisfaction is followed by a Composite Reliability (CR)
value greater than 0.7 (Leguina, 2015).
Table 5 Conbach's alpha and Composite Reliability Value
Variable
Cronbach’s
Alpha (α)
Composite
Reliability
(CR)
Results
Analysis of Factors that Influence the Use of Online Investment Applications (Ajaib)
Syntax Idea, Vol. 6, No. 08, Agustus 2024 3495
Variable
Cronbach’s
Alpha (α)
Composite
Reliability
(CR)
Results
User
Interface
(UI)
0.862
0.916
Reliability
Perceived
Security
(PS)
0.893
0.926
Reliability
Perceived
Risk (PR)
0.942
0.954
Reliability
Perceived
Usefulnes
s (PU)
0.910
0.937
Reliability
Perceived
Ease of
Use
(PEOU)
0.910
0.936
Reliability
Attitude
Toward
Using
(ATU)
0.873
0.923
Reliability
Behavior
al
Intention
to Use
(BIU)
0.917
0.941
Reliability
Actual
System
Usage
(AU)
0.880
0.927
Reliability
The table above shows the Cronbach's Alpha (α) and composite reliability values for
each research indicator. The results show that all indicators meet the criteria and are reliable
for further use in research.
The table above shows the Cronbach's Alpha (α) and composite reliability values for
each research indicator. The results show that all indicators meet the criteria and are reliable
for further use in research.
Outer Structural Framework
Figure 4. Outer Structural Framework
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3496 Syntax Idea, Vol. 6, No. 08, Agustus 2024
Figure 4 displays the final structural framework for the outer research model along with
the p-values, Outer Loadings and Average Variance Extracted (AVE) of each indicator.
T-Statistic Test
To test the Inner structural model, the author uses the bootstrapping feature in smartPLS
and uses 5000 (five thousand) subsamples to calculate the t-statistic and p value with a
significance level of 5% where the t-statistic value must be greater than 1.96 and the p value
less than 0 .05 for variables that are acceptable and considered to have a positive impact.
Table 6 T-Statistic Value
Variable Path
T-Statistics
Information
ATU →BIU
78.801
Significant
BIU →AU
79.060
Significant
PEOU →ATU
3.375
Significant
PR →PEOU
3.698
Significant
PR →PU
4.055
Significant
PS →PEOU
5.328
Significant
PS →PU
3.790
Significant
PU →ATU
2.937
Significant
UI →PEOU
1.741
Not
significant
UI →PU
2.368
Significant
The hypothesis proposed in this research is the positive influence of Perceived Security
(PS), User Interface (UI), Perceived Risk (PR), Perceived Ease of Use (PEOU), Perceived
Usefulness (PU), Attitude Toward Using (ATU), Behavioral Intention to Use (BIU) against
Actual System Use (AU) in the Ajaib Application. Table 6 shows that 1 of the 10 hypotheses
was rejected because the t-statistic value was not greater than 1.96 followed by the p value
being more than the research significance level, namely 0.05.
Coefficient of Determination Test (R2)
At this stage the researcher also uses the coefficient of determination (R2) value to
represent the suitability of the research data to the model and to show the significant
percentage between the independent variables used inside and outside the research on the
dependent variable (Hair, Sarstedt, Hopkins, & Kuppelwieser, 2014). The R2 value can be
used to measure the influence of a particular independent variable on the dependent variable
by removing the independent variables from the model individually and checking whether
there is a difference in the R2 value. Prediction accuracy for endogenous latent variables is
considered high for R2 values higher or equal to 0.75, considered moderate for values
between 0.75 and 0.5, and considered Weak for values between 0.25 and 0.5 (Joe F Hair et
al., 2011). The results of the determinant coefficients are presented in the table below:
Table 7 Coefficient of Determination Value
Variable
Determination
Coefficient
Value (R2)
Information
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Syntax Idea, Vol. 6, No. 08, Agustus 2024 3497
Actual
System
Usage
0.912
High
Attitude
Toward
Using
0.923
High
Behavioral
Intention to
Use
0.910
High
Perceived
Ease of
Use
0.846
High
Perceived
Usefulness
0.843
High
The table above shows that the R2 value for Actual System Usage (AU) is 0.912 which
shows that Perceived Security (PS), User Interface (UI), Perceived Risk (PR), Perceived Ease
of Use (PEOU), Perceived Usefulness (PU) influence 91.2% results of Actual System Usage
of Ajaib Applications while the remaining 8.8% comes from variables outside this research.
The same thing applies to Attitude Toward Using (ATU) has the highest R2 value, where
92.3% of the final results are influenced by variables in this research, for the Behavioral
Intention to Use variable 91% of the results come from variables in this research. The
Perceived Effectiveness (PU) variable 84.3% of the results come from variables in this
research, while the Perceived Ease of Use (PEOU) results are only influenced by the variables
in this research at 84.6%.
Effect Size Test (f2)
The last test done by the author in the inner model is Effect size (f2) test to see how big
the size of influence of each independent variables towards dependent variables. The values
greater than 0.02 represent the magnitude of weak influences of dependent variables, values
greater than 0.15 represent the magnitude of medium influences of dependent variables, and
values greater than 0.35 represent the magnitude of large influences of dependent variables
whereas the value less than 0,02 is considered too weak to be mentioned or descripted in the
table (Hair et al., 2014).
Table 8 Effect Size (f2) value
Variable
Path
f
2
Information
ATU →BIU
10.162
Great
BIU →AU
10.359
Great
PEOU
→ATU
0.341
Moderate
PS →PEOU
0.220
Moderate
PS →PU
0.133
Weak
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3498 Syntax Idea, Vol. 6, No. 08, Agustus 2024
PR →PEOU
0.163
Moderate
PR →PU
0.198
Moderate
PU →ATU
0.255
Moderate
UI →PEOU
0.021
Weak
UI →PU
0.051
Weak
From the table above we can conclude several things as follows:
1. There is a great influence from the Attitude Toward Using (ATU) value variable on the
Behavioral Intention to Use (BIU) outcome variable
2. There is a great influence between the Behavioral Intention to Use (BIU) value variable on
the Actual System Use (AU) outcome variable
3. There is a moderate influence between the value of the Perceived Ease of Use (PEOU)
variable on the Attitude Toward Using (ATU) outcome variable.
4. There is a moderate influence between the Perceived Ease of Use (PEOU) value variable
on the Perceived Usefulness (PU) outcome variable
5. There is a moderate influence between the value of the Perceived Security (PS) variable on
the Perceived Ease of Use (PEOU) outcome variable.
6. There is a weak influence between the value of the Perceived Security (PS) variable on the
Perceived Usefulness (PU) outcome variable
7. There is a moderate influence between the value of the Perceived Risk (PR) variable on the
Perceived Ease of Use (PEOU) outcome variable.
8. There is a moderate influence between the value of the Perceived Risk (PR) variable on the
Perceived Usefulness (PU) outcome variable.
9. There is a moderate influence between the value of the Perceived Usefulness (PU) variable
on the Attitude Toward Using (ATU) outcome variable.
10. There is a weak influence between the User Interface (UI) variable value on the
Perceived Ease of Use (PEOU) outcome variable
11. There is a weak influence between the User Interface (UI) variable value on the
Perceived Usefulness (PU) outcome variable
Indirect Effect Test
T-statistics can be used to determine the significant effect of indirect effects. If the t-
Statistics value is higher than 1.96 as explained in section 4.3.1. t-Statistics Test, the size of
the indirect effect between variables is considered significant. The results showed that there
were 6 indirect effects that were not significant and 17 indirect effects that were significant.
Table 9 Indirect Effect value
No
Variable Path
t-Statistics
Information
1.
Perceived Risk -> Perceived Ease of Use -> Attitude Toward
Using -> Behavioral Intention to Use -> Actual System Usage
2.508
Significant
2.
Perceived Security -> Perceived Ease of Use -> Attitude
Toward Using -> Behavioral Intention to Use -> Actual
System Usage
2.744
Significant
3.
Perceived Ease of Use -> Attitude Toward Using ->
Behavioral Intention to Use -> Actual System Usage
3.226
Significant
4.
Perceived Risk -> Perceived Usefulness -> Attitude Toward
Using -> Behavioral Intention to Use -> Actual System Usage
2.414
Significant
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Syntax Idea, Vol. 6, No. 08, Agustus 2024 3499
5.
Perceived Security -> Perceived Usefulness-> Attitude
Toward Using -> Behavioral Intention to Use -> Actual
System Usage
2.260
Significant
6.
Attitude Toward Using -> Behavioral Intention to Use ->
Actual System Usage
42.678
Significant
7.
Perceived Usefulness-> Attitude Toward Using -> Behavioral
Intention to Use -> Actual System Usage
2.929
Significant
Of the 17 significant results, only 7 results had an indirect effect on the dependent
variable or Actual System of Usage. These results prove that there is significance to the
dependent variable with the mediation of other variables, namely:
1. Perceived Risk -> Perceived Ease of Use -> Attitude Toward Using -> Behavioral
Intention to Use -> Actual System Usage. Perceived Risk has an indirect effect on Actual
System Usage through the variables Perceived Ease of Use, Attitude Toward Using and
Behavioral Intention to Use.
2. Perceived Security -> Perceived Ease of Use -> Attitude Toward Using -> Behavioral
Intention to Use -> Actual System Usage. Perceived Security has an indirect effect on
Actual System Usage through the variables Perceived Ease of Use, Attitude Toward Using
and Behavioral Intention to Use.
3. Perceived Ease of Use -> Attitude Toward Using -> Behavioral Intention to Use -> Actual
System Usage. Perceived Ease of Use has an indirect effect on Actual System Usage
through the variables Attitude Toward Using and Behavioral Intention to Use.
4. Perceived Risk -> Perceived Usefulness -> Attitude Toward Using -> Behavioral Intention
to Use -> Actual System Usage. Perceived Risk has an indirect effect on Actual System
Usage through the variables Perceived Usefulness, Attitude Toward Using and Behavioral
Intention to Use.\
5. Perceived Security -> Perceived Usefulness -> Attitude Toward Using -> Behavioral
Intention to Use -> Actual System Usage. Perceived Security has an indirect effect on
Actual System Usage through the variables Perceived Usefulness, Attitude Toward Using
and Behavioral Intention to Use.
6. Attitude Toward Using -> Behavioral Intention to Use -> Actual System Usage. Attitude
Toward Using has an indirect effect on Actual System Usage through the Behavioral
Intention to Use variable.
7. Perceived Usefulness -> Attitude Toward Using -> Behavioral Intention to Use -> Actual
System Usage. Perceived Usefulness has an indirect effect on Actual System Usage
through the variables Attitude Toward Using and Behavioral Intention to Use.
Hypothesis Test Results
The hypothesis proposed in this research is the positive influence of Perceived Security
(PS), User Interface (UI), Perceived Risk (PR), Perceived Ease of Use (PEOU), Perceived
Usefulness (PU), Attitude Toward Using (ATU) and Behavioral Intention to Use (BIU)
against the Actual System Use (AU) of the Ajaib Application. Table 10 shows that 1 out of 10
hypotheses was rejected because the t-statistic value was not greater than 1.96 followed by the
p-value being greater than the research significance level, namely 0.05.
Table 10 Hypothesis Test Results
H
Variable Path
P-Values
T-Statistics
Path Coefficient
Result
H1
UI → PU
0.009
2.368
0.245
Accepted
H2
UI → PEOU
0.041
1.741
0.154
Rejected
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3500 Syntax Idea, Vol. 6, No. 08, Agustus 2024
H3
PS → PU
0.000
3.790
0.424
Accepted
H4
PS → PEOU
0.000
5.328
0.541
Accepted
H5
PR → PU
0.000
4.055
0.301
Accepted
H6
PR → PEOU
0.000
3.698
0.271
Accepted
H7
PU → ATU
0.002
2.937
0.451
Accepted
H8
PEOU →
ATU
0.000
3.375
0.522
Accepted
H9
ATU → BIU
0.000
78.80
0.954
Accepted
H10
BIU →AU
0.000
79.06
0.955
Accepted
The results of this research show that there is a significant relationship between the User
Interface variable and the Perceived Usefulness variable. This shows that users tend to
consider application design as a factor that supports the usability and benefits that users feel
when using the Ajaib application. Therefore, the Ajaib application can improve the quality of
application design to increase the usability of the application in the eyes of users. UI was also
found to have a significant influence on Perceived Usefulness because the T-Statistic was
above 1.96 which was worth 2,368 and the P-value was below 0.05, which was worth 0.009,
this shows that improving the appearance of the Ajaib application will give a better
impression. good to application users, which makes users want to use the application
repeatedly and encourages real application usage activities. Therefore, the first hypothesis
which states that the User Interface (UI) has a positive and significant effect on the Perceived
Usefulness (PU) of the Ajaib online mutual fund investment application is accepted.
The results of this research show that there is no significant relationship between the
User Interface variable and the Perceived Ease of Use variable. This shows that even though
users are free from difficulties in using the Ajaib application, it does not mean they think
Ajaib is the easiest mutual fund application to operate, this indicates that users also have the
intention to use other similar applications. Therefore, the Ajaib application does not need to
create a complex User Interface to increase the usability of the application in the eyes of
users. Therefore, the second hypothesis which states that the User Interface (UI) has a positive
and significant effect on the Perceived Ease of Use (PEOU) of the Ajaib online mutual fund
investment application is rejected.
The results of this research show that there is a significant relationship between the
Perceived Security variable and the Perceived Usefulness variable. This shows that users
consider application security to support the usability and benefits that users feel when using
the Ajaib application. Therefore, the Ajaib application can strengthen application security so
that users experience more benefits in using the application. PS was also found to have a
significant indirect effect on Attitude Toward Using (ATU) through PU with a t-statistic of
2.260. Therefore, the Ajaib application can strengthen application security to improve the
quality of the good impression given to application users when using the Ajaib application.
Therefore, the Ajaib application does not need to strengthen application security to increase
the usability of the application in the eyes of users. Therefore, the third hypothesis which
states that Perceived Security (PS) has a positive and significant effect on the Perceived
Usefulness (PU) of the Ajaib online mutual fund investment application is accepted.
The results of this research show that there is a significant relationship between the
Perceived Security variable and the Perceived Ease of Use variable. This shows that users
consider the security of the application to make users feel that using the Ajaib application is
easier. Therefore, the Ajaib application can strengthen application security so that users
experience greater ease in using the application. PS was also found to have a significant
Analysis of Factors that Influence the Use of Online Investment Applications (Ajaib)
Syntax Idea, Vol. 6, No. 08, Agustus 2024 3501
indirect effect on Attitude Toward Using (ATU) via PEOU with a t-statistic of 2.744.
Therefore, the Ajaib application can strengthen application security to improve the quality of
the good impression given to application users when using the Ajaib application. Therefore,
the Ajaib application does not need to strengthen application security to increase the usability
of the application in the eyes of users. Therefore, the fourth hypothesis which states that
Perceived Security (PS) has a positive and significant effect on Perceived Ease of Use
(PEOU) of the Ajaib online mutual fund investment application is accepted.
The results of this research show that there is a significant relationship between the
Perceived Risk variable and the Perceived Usefulness variable. This shows that users perceive
the risks of an application to support the usefulness and benefits that users feel when using the
Ajaib application. Therefore, the Ajaib application can prevent or overcome the risks of the
application so that users experience more benefits from using the application. PR was also
found to have a significant indirect effect on Attitude Toward Using (ATU) through PU with
a t-statistic of 2.414. Therefore, the Ajaib application can minimize and reduce application
risks to increase the quality of the good impression given to application users when using the
Ajaib application. Therefore, the Ajaib application needs to strengthen the quality of
application risk prevention and management to increase the usability of the application in the
eyes of users. Therefore, the fifth hypothesis which states that Perceived Risk (PR) has a
positive and significant effect on Perceived Usefulness (PU) of the Ajaib online mutual fund
investment application is accepted.
The results of this research indicate that there is a significant relationship between the
Perceived Risk variable and the Perceived Ease of Use variable. This shows that users
consider the risk of an application to make users feel that using the Ajaib application is easier.
Therefore, the Ajaib application can prevent or overcome the risks of the application so that
users experience greater ease in using the application. PR was also found to have a significant
indirect effect on Attitude Toward Using (ATU) via PEOU with a t-statistic of 2.508.
Therefore, the Ajaib application can minimize and reduce application risks to increase the
quality of the good impression given to application users when using the Ajaib application.
Therefore, the Ajaib application needs to strengthen the quality of application risk prevention
and management to increase the usability of the application in the eyes of users. Therefore,
the sixth hypothesis which states that Perceived Risk (PR) has a positive and significant effect
on Perceived Ease of Use (PEOU) of the Ajaib online mutual fund investment application is
accepted.
The results of this research show that there is a significant relationship between the
Perceived Usefulness variable and the Attitude Toward Using variable. This shows that Ajaib
users believe the application is useful in carrying out mutual fund transactions, they like using
the Ajaib feature and overall, using the Ajaib feature is very enjoyable. Therefore, the Ajaib
application can increase the usability of the application, such as adding features to give a good
impression of use to application users. PU was also found to have a significant indirect
influence on Behavioral Intention to Use (BIU) through ATU with a t-statistic of 2.929, this
shows that the usability of the application gives a good impression to users so that the
intention to use the application appears. Therefore, the seventh hypothesis which states that
Perceived Usefulness (PU) has a positive and significant effect on Attitude Toward Using
(ATU) of the Ajaib online mutual fund investment application is accepted.
The results of this research show that there is a significant relationship between the
Perceived Ease of Use variable and the Attitude Toward Using variable. This shows that when
users find it easy to use the Magic App, it means they find the experience enjoyable. PEOU
was also found to have a significant indirect effect on Behavioral Intention to Use (BIU) via
Edward Adi, Sfenrianto
3502 Syntax Idea, Vol. 6, No. 08, Agustus 2024
ATU with a t-statistic of 3.226. Therefore, the Ajaib application needs to increase the ease of
use of the application to give a good impression of use to application users. Therefore, the
eighth hypothesis which states that Perceived Ease of Use (PEOU) has a positive and
significant effect on Attitude Toward Using (ATU) of the Ajaib online mutual fund
investment application is accepted.
The results of this research indicate that there is a significant relationship between the
Attitude Toward Using variable and the Behavioral Intention to Use variable. This hypothesis
suggests that users who have a pleasant time using an application will have the mind to
frequently use the application's functions and content. They will use Ajaib's functionality and
content in the future. They would recommend Ajaib to others. Therefore, the Ajaib
application can increase the user's impression of the application to generate the user's
intention to use the application. ATU was also found to have a significant indirect influence
on Actual System Usage (AU) through BIU with a t-statistic of 42.678, this shows that if an
application gives a good impression to users, then this will be one of the supporting factors in
actual use of the application the. Therefore, the Ajaib application can increase the user's
impression of the application to generate the user's intention to use the application which will
later help increase the actual use of the Ajaib application. Therefore, the ninth hypothesis
which states that Attitude Toward Using (ATU) has a positive and significant effect on
Behavioral Intention to Use (BIU) of the Ajaib online mutual fund investment application is
accepted.
The results of this research show that there is a significant relationship between the
Behavioral Intention to Use variable and the Actual System Usage variable. Behavioral
Intention to Use was also found to have a significant influence on Actual System Usage
because the T-Statistic was above 1.96 which was worth 79,060 and the P-value was below
0.05, which was worth 0.955. This shows that users who have developed a behavioral
tendency to have the intention to use the Ajaib App will use Ajaib frequently over the past
week and month. Therefore, the Ajaib application can strengthen the user's intention to use
the application to increase the actual use of the Ajaib application. Therefore, the tenth
hypothesis which states that Behavioral Intention to Use (BIU) has a positive and significant
effect on the Actual System Use (AU) of the Ajaib online mutual fund investment application
is accepted.
CONCLUSSION
In conclusion, this research was conducted by applying 5 (five) internal TAM variables
and 3 (three) external variables, namely User Interface (UI), Perceived Security (PS), and
Perceived Risk (PR). This resulted in 10 hypotheses which were then found to be 1 of the 10
hypotheses which were rejected, the 1 which were rejected was: 1. User Interface (UI) against
Perceived Ease of Use.
The results of this research also show that there is a significant indirect effect of the
variables Perceived Security, Perceived Risk, Perceived Ease of Use, Perceived Usefulness
and Attitude Toward Using on Actual System Use. This shows that the level of security of the
Ajaib Application, the level of risk in using the Ajaib Application, the ease of using the Ajaib
Application, the benefits that users feel when using the Application and the user's attitude
towards using the Application have an indirect influence on the use of the Ajaib Online
Mutual Fund Application through mediation from other related variables.
Analysis of Factors that Influence the Use of Online Investment Applications (Ajaib)
Syntax Idea, Vol. 6, No. 08, Agustus 2024 3503
Overall, the variables used in the research are all fit to use, with the overall quality of
the outer model declared valid through convergent and discriminant validity tests. All model
variables are also reliable with all dependent variables having the ability to influence the
dependent variable with at least a weak effect. Overall, the variables used in the research are
all fit to use, with the overall quality of the external model being considered valid even when
testing convergent and discriminant validity. All model variables are also reliable with all
dependent variables having the ability to influence their dependent variables with at least a
weak effect.
This research contributes to studying the acceptance of Ajaib Application from PT
Takjub Teknologi Indonesia in order to fulfill the sources for studying the Indonesian fintech
acceptance model. Furthermore, this research is expected to provide evidence regarding the
influence of User Interface (UI), perceived security (PS), perceived risk (PR), perceived
usefulness, perceived ease of use, attitudes towards use, and Behavioral Intention to Use on
Actual System Usage of Ajaib online investment application. For companies, it is hoped that
the results of this research will be useful as consideration and input for PT Takjub Teknologi
Indonesia in an effort to increase interest in using the Ajaib mutual fund application. For
future researchers, this research can be used as a reference source regarding the factors that
influence investors' interest in using the Ajaib mutual fund application. For investors and the
public, it is hoped that this research can be used as a source of information so that it can
provide insight to investors and the public that the Ajaib mutual fund application can be easily
used to support mutual fund transactions
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