Analysis of Factors Which are Able to Influence the Admittance of

BPJS Ketenagakerjaan Participants towards BPJSTK Mobile by

using Technology Acceptance Model 3 (TAM 3)

Suryaningsih

Magister of Management, Faculty of Economic and Business, Universitas Airlangga, Surabaya -Indonesia

Keywords: BPJSTK Mobile, Perceived Usefulness, Perceived Ease of Use, Intention to Use.

Abstract: Information and Technology are rapidly evolving along with the evolution or the development of an era.

BPJSTK Mobile is a service application intended for the participants as a form of expansion in BPJS

Ketenagakerjaan Program information services, a medium for complaints if any discrepancy status appears,

information regarding the total amount of salary and employee that can be accessed through smartphones.

However, the performance of BPJSTK Mobile service is considered poor, given that it is only providing

information of the employees at the Surabaya Darmo branch which amount are relatively lower than the

total amount of participants who have actually registered. This research aims to analyze factors which are

able to influence the admittance of BPJS Ketenagakerjaan participants at Surabaya Darmo Branch towards

BPJSTK Mobile by using Technology Acceptance Model 3 (TAM 3). Variables that are used in this study

are subjective norm, image, computer self-efficacy, computer/system anxiety, perceived usefulness,

perceived ease of use, and intention of use (IU). Respondents chosen for the research are laborers who have

not used the BPJSTK Mobile Application registered at BPJS Ketenagakerjaan of Surabaya Darmo branch.

The data are gathered directly by conducting the deployment of questionnaires to 150 respondents. The

sampling technique used in this research is incidental sampling. The result of the hypothesis test showed

that SN or subjective norm does not have any positive effect towards intention to use (IU) and image (IMG)

does not have any positive impact towards perceived usefulness (PU).

1 INTRODUCTION

The development and growth of Information and

Technology made many informational search

activities, which hold an important part in human’s

life, no longer be held conventionally. Humans only

need to make use of technologies like the internet to

be able to access various needed information from

various sources that are not limited by time and

distance, unlike when conventional technology was

still around and commonly found (Hong et al., 2002;

Ayele and Sreenivasarao, 2013). One of the forms

of information technology is the appearance of the

mobile service application that can be accessed via

mobile phones or smartphones. The application is

able to answer demands from customers who want

fast service, safety, comfort, cheapness, available at

any time (24/7), and able to be accessed from

everywhere through smartphones (Rahayu, 2015).

There are now many banks and insurance

agencies, commercial and social ones, that offer

mobile access to financial information, one of them

is BPJS Ketenagakerjaan that is BPJSTK Mobile.

BPJSTK Mobile is a service application intended for

the participants as a form of expansion to the

information service media of BPJS Ketenagakerjaan

program, medium to the complaint service regarding

status discrepancy of customers, and the total

amount of salary and employees that can be

accessed anywhere and anytime via smartphones.

BPJSTK Mobile service has many advantages

and is very beneficial for participants since its

launch in 2014, the socialization carried out has been

maximized and awareness is high. But when viewed

from the statistics of its usage at the Surabaya

Darmo Branch Office, where this research will be

conducted, that BPJSTK mobile service

performance for the number of participants utilizing

the mobile BPJSTK is relatively smaller or very low

than the total number of registered participants. The

798

Suryaningsih, .

Analysis of Factors Which are Able to Inﬂuence the Admittance of BPJS Ketenagakerjaan Participants towards BPJSTK Mobile by using Technology Acceptance Model 3 (TAM 3).

DOI: 10.5220/0009506707980804

In Proceedings of the 1st Unimed International Conference on Economics Education and Social Science (UNICEES 2018), pages 798-804

ISBN: 978-989-758-432-9

number of participants registered at the Surabaya

Darmo Branch of BPJS Ketenagakerjaan until June

2017 was 108,101 workers with 2,438 companies.

Of the total 108,101 participants, only 20,587 or

19.04% of participants used or used BPJSTK

Mobile.

The problem of how participants can receive and

utilize the BPJSTK Mobile service can be explained

optimally using the TAM (Theory Acceptance

Model) framework. TAM is a model built to analyze

and understand the factors that influence the

acceptance of technology use (Davis, 1989). In

2008, Venkatesh and Bala conducted theoretical

development and testing of Technology Acceptance

Model 2 (TAM2) by identifying the determinants of

perceived ease of use (PEOU) developed by

Venkatesh in 2000 to become Technology

Acceptance Model 3 (TAM3) (Venkatesh and Bala,

2008). TAM3 examines more deeply the

determinants of user perceptions of perceived

usefulness and the user's perception of perceived

ease of use (Davis, 1989).

User Trust in the ease of use and usefulness of

new technologies is influenced by computer self-

efficacy. Users with high levels of computer self-

efficacy will find it easier to use a new information

technology (Hong et al., 2002).

Subjective norm is one of the variables of social

influence in the form of social pressure received to

do or not do something. It is very important to

determine how social influence influences the

commitment of users in utilizing information

systems to understand, explain, and predict

acceptance behavior and use of information systems

(Malhotra and Galletta, 1999).

Image is interpreted as someone's perception that

the use of innovation will improve their social status.

(Venkatesh and Davis, 2000) describe the large

impact of social influences (subjective norms, and

images) on technology acceptance. (Venkatesh et

al., 2003) assert that social influence is a direct

determinant of intention to use technology.

The use of technology usually has side effects, such

as negative emotions that increase not only during

interaction with technology but even before.

Frustration, confusion, anger, anxiety, and similar

emotions can affect the process of interaction with

technology (George Saadé and Kira, 2009).

Based on the description above, the formulation

of the problem will be compiled which will be

answered with this research, namely:

1. Does subjective norm (SN) have positive

effect(s) towards intention to use (IU).

2. Does subjective norm (SN) have positive

effect(s) towards perceived usefulness (PU).

3. Does image (IMG) have positive effect(s)

towards perceived usefulness (PU).

4. Does computer self-efficacy (CSE) have positive

effect(s) towards perceived ease of use (PEOU).

5. Does system anxiety (CANX) have positive

effect(s) towards perceived ease of use (PEOU).

6. Does perceived ease of use (PEOU) have

positive effect(s) towards perceived usefulness

(PU).

7. Does perceived ease of use (PEOU) have

positive effect(s) towards intention to use (IU).

8. Does perceived usefulness (PU) have positive

effect(s) towards intention to use (IU).

2 THEORICAL FRAMEWORK

The TAM 3 study was previously conducted by

Venkatesh and Bala in 2008 entitled Technology

Acceptance Model 3 and a Research Agenda on

Interventions. The results to be achieved in this

study are to present a research agenda that identifies

a set of interventions for researchers and

practitioners to investigate further about employee

acceptance and adoption of information technology

to be effective in a company. The results of this

study indicate that perceived ease of use has a

positive effect on perceived usefulness, perceived

ease of use has a positive effect on behavioral

intention, perceived usefulness has a positive effect

on behavioral intention and behavioral intention has

a positive effect on use behavior.

The similarity is also found in this study where

this study decided to use the Technology Acceptance

Model 3 (TAM 3) model to identify external factors

and perceived ease of use or perceived usefulness

that are most influential in using a technology. The

difference is that some variables are not used

because the variable is a research object that varies

and is adapted to the existing environment.

Furthermore, this study took the field of labor

regarding social security.

The following is the BPJSTK Mobile TAM 3

research model at the Surabaya BPJS

Ketenagakerjaan of Darmo Branch which will be

used by the researcher:

Analysis of Factors Which are Able to Inﬂuence the Admittance of BPJS Ketenagakerjaan Participants towards BPJSTK Mobile by using

Technology Acceptance Model 3 (TAM 3)

799

Figure 1: Research Model.

3 RESEARCH METHOD

The research method is classified as a type of

confirmatory research that aims to test or confirm

the hypothesized model (Sholihin, Mustafid and

Safitri, 2014). The type of data used in this study is

quantitative data. The source of data used in this

study is primary data which is the result of answers

from the questionnaire distributed to respondents.

Respondents in this study are workers who have

not used the BPJSTK Mobile application registered

at the BPJS Ketenagakerjaan of Surabaya Darmo

Branch. The determination of the number of

respondents for the analysis of Structural Equation

Modeling (SEM) is by using the formula of the

number of indicators from times 5 to 10 (Ferdinand,

2005). Because the number of indicators used in this

study is 22, then the minimum respondents for this

study are 110. Furthermore, Hair, in (Ferdinand,

2005) found that the size of respondents suitable for

SEM is between 100-200 samples. By referring to

the formula for determining the number of

respondents and opinions of Hair, the number of

respondents used in the study was 150 respondents.

The statistical analysis tool used to test

hypotheses is Structural Equation Modeling (SEM),

that is the reason as to why the structure or pattern of

relationships between a set of latent variables or

theoretical variables can be explained through one or

several indicator variables (Rizal, 2014). Data

processing is done using a software called AMOS

(Analysis of Moment Structure) version 24.

4 ANALYSIS

Based on the data of respondents' characteristics, it

was shown that male respondents were more than

female respondents, namely by the percentage of

males by 58.67%. When viewed from the age group,

the majority of respondents aged 26-35 years is

48.67%. Based on the respondents' education, it was

shown that the majority of respondents had an S1

degree (Strata One), which was 49.33%.

Convergent validity is a measure of construct

validity that shows that items or indicators of a latent

construct must converge or share (share) high

variance proportions. High loading values on a

factor (latent construct) indicate that they converge

at one point. Loading factors of variables SN, IMG,

CSE, CANX, PU, PEOU, and IU are all valued at ≥

0.5 so it can be concluded that all indicators used to

measure subjective norm variables, image, computer

self-efficacy, system anxiety, perceived usefulness,

perceived ease of use, and the intention to use are

declared valid and constitutes a unity of indicators

examined.

Table 1: Convergence Validity Test.

Indicators Variables Loading Factors Value

SN1 <--- SN 0,812

SN2 <--- SN 0,659

SN3 <--- SN 0,892

SN4 <--- SN 0,912

IMG1 <--- IMG 0,906

IMG2 <--- IMG 0,942

IMG3 <--- IMG 0,742

CSE1 <--- CSE 0,9

CSE2 <--- CSE 0,994

CSE3 <--- CSE 0,742

CANX1 <--- CANX 0,947

CANX2 <--- CANX 0,976

CANX3 <--- CANX 0,92

PU1 <--- PU 0,932

PU2 <--- PU 0,942

PU3 <--- PU 0,895

PEOU1 <--- PEOU 0,958

PEOU2 <--- PEOU 0,935

PEOU3 <--- PEOU 0,929

IU1 <--- IU 0,922

IU2 <--- IU 0,949

IU3 <--- IU 0,844

After the convergent validity is achieved, the

second validity test is done, namely discriminant

validity, which aims to test whether a construct is

completely different from other constructs. The

square root value of AVE has a higher value than the

correlation value between constructs. It can be said

that the measurement model has met discriminant

validity.

Table 2: Discriminant Validity Test.

IMG SN CSE CANX PU UI PEOU

IMG

0.825

0.414

0.868

CSE

0.074 0.348

0.885

CANX

0.123 -0.210 -0.207

0.948

0.214 0.652 0.415 -0.325

0.923

0.093 0.567 0.376 -0.446 0.833

0.906

PEOU

0.114 0.510 0.325 -0.369 0.701 0.682

0.941

UNICEES 2018 - Unimed International Conference on Economics Education and Social Science

800

In SEM analysis, the reliability of the model is

examined using construct reliability. A model is said

to be reliable when the construct reliability value of

each variable/construct is more than 0.7 (Solimun,

2002). (Ghozali, 2017) describe the rule of thumb

the value of construct reliability must be > 0.70.

AMOS calculation’s result for testing construct

reliability shows that the variables/constructs of the

study consist of subjective norm, image, computer

self-efficacy, system anxiety, perceived usefulness,

perceived ease of use, and intention to use has a

value of construct reliability > 0.70. Based from the

above, it is concluded that these variables are

reliable in developing the model developed in this

study.

Hypothesis testing is conducted to determine

whether exogenous variables on endogenous

variables and endogenous variables on endogenous

variables are affecting one another. The hypothesis

is stated acceptable if the value of prob (P) < 0.05.

There are 2 rejected hypothesis, H1 and H3, while

H2, H4, H5, H6, H7 and H8 are all accepted.

Table 3: Hypothesis Test.

Hypothesis Causality Relation Estimate S.E. C.R. P Label Information

H1 SN ---> IU .025 .062 .400 .689 par_16 Rejected

H2 SN ---> PU .391 .073 5.351 * ** par_ 18 A dmitted

H3 IMG ---> PU -.028 .077 -.360 .719 par_19 Rejected

H4 CSE ---> PEOU .321 .096 ,3335 *** par_21 Admitted

H5 CANX ---> PEOU -.311 .076 -4.074 *** par_22 Admitted

H6 PEOU ---> PU .550 .074 7.434 * ** par_ 23 A dmitted

H7 PEOU ---> IU .194 .074 2.610 .009 par_20 Admitted

H8 PU ---> IU .623 .086 7.235 *** par_17 Admitted

5 RESULTS

H1: Subjective norm (SN) has positive impact(s)

towards intention to use (IU)

Based on data from the results of data processing, it

is known that the P value (probability) is 0.689.

These results do not meet the requirements of < 0.05

so that it can be concluded that H1 in this study was

not accepted/rejected. This is not in line with Park's

study which states that subjective norms influence

both behavioral intentions and attitudes towards e-

learning (Park, 2009). (Jimantoro and Tjondro,

2014) state that subjective norms (subjective norms)

do not have a significant effect on the intention of

taxpayers in the use of e-filling (intention to use e-

filing). This means that the social environment such

as friends, family, and superiors in the company

have no effect on participants' intention to use the

BPJSTK Mobile application. The intention of the

participants to use the BPJSTK Mobile application is

because of their awareness of the importance of

using BPJSTK Mobile.

H2: Subjective norm (SN) has positive impact(s)

towards perceived usefulness (PU)

Based on the results of data processing, it is known

that the P value (probability) is 0,000. These results

meet the requirements of < 0.05 so it can be

concluded that H2 in this study can be accepted.

This is consistent with Park's study which states that

subjective norms can affect the usefulness of e-

learning to users (Park, 2009). Fang Xu's study also

states that subjective norms have a positive influence

on the usefulness of the MOOC (Massive Open

Online Courses) (Xu, 2015). This means that the

social environment such as friends, family, and

employers in the company has an influence on

participants' perceptions of the benefits of the

BPJSTK Mobile application. Participants will

consider the BPJSTK Mobile application useful if

the social environment is the same.

H3: Image (IMG) has positive impact(s) towards

perceived usefulness (PU)

Based on the results of data processing, it is known

that the P value (probability) is 0.719. These results

do not meet the requirements of < 0.05 so it can be

concluded that H3 in this study was not accepted.

This is not in line with Fang Xu's research which

states that image has a positive influence on the

usefulness of the MOOC (Massive Open Online

Courses) (Xu, 2015). But in line with Ying Wu's

research on user acceptance of the Web 2.0 website

which states that the image has no positive effect on

perceived usefulness (Wu et al., 2011). This means

that the social status does not affect participants'

perceptions about the usefulness of the BPJSTK

Mobile application, even though the use of the

BPJSTK Mobile application does not improve social

status both in the work environment and other social

environments, they still consider BPJSTK Mobile

useful.

H4: Computer self-efficacy (CSE) has positive

impact(s) towards perceived ease of use

(PEOU)

Based on the results of data processing, it is known

that the P value (probability) is 0,000. These results

meet the requirements of < 0.05 so that it can be

concluded that H4 in this study can be accepted.

This study proves that the higher the level of trust of

participants in the ability to use the BPJSTK Mobile

application, the easier the use of BPJSTK Mobile.

This is in line with Fang Xu's research which states

Analysis of Factors Which are Able to Inﬂuence the Admittance of BPJS Ketenagakerjaan Participants towards BPJSTK Mobile by using

Technology Acceptance Model 3 (TAM 3)

801

that computer self-efficacy has a positive influence

on the ease of use of MOOC (Massive Open Online

Courses) (Xu, 2015). After participants are

convinced of their ability to use the BPJSTK Mobile

application, participants will get the ease of

downloading and using the BPJSTK Mobile

application without having to drain their energy and

mind, this is also consistent with the research

conducted by Park (2009). Through the BPJSTK

Mobile application, participants can check fast and

accurate online old-age (JHT) balances, calculate the

Old Age Guarantee (JHT), Pension Insurance

simulation (JP), get program and Co-Marketing

information, branch office information, central

information service and social media, and complaint

services.

H5: System anxiety (CANX) has negative

impact(s) towards perceived ease of use

(PEOU)

Based on the results of data processing, it is known

that the P value (probability) is 0,000. These results

meet the requirements of < 0.05 so that it can be

concluded that H5 in this study can be accepted.

This is in line with the research of Saade and Kira

which states that computer/system anxiety has a

significant influence on perceived ease of use from

the use of LMS technology (Learning Management

System) (George Saadé and Kira, 2009). Celik's

study of consumer acceptance of online retail

shopping states that anxiety has a negative influence

on perceived ease of use (Çelik, 2011). This means

that if the level of anxiety, concern or even fear of

the participants when faced with the possibility of

using the BPJSTK Mobile application increases,

their perception of the ease of using BPJSTK Mobile

will decrease

H6: Perceived ease of use (PEOU) has positive

impact(s) towards perceived usefulness

(PU)

Based on the results of data processing, it is known

that the P value (probability) is 0,000. These results

meet the requirements of < 0.05 so that it can be

concluded that H6 in this study can be accepted. The

ease of using the BPJSTK Mobile application and

obtaining the information needed in connection with

participation in the BPJS Employment provides

usefulness in the use of the BPJSTK Mobile

application by participants. This is in line with the

research of Venkatesh and Davis that perceived ease

of use can affect perceived usefulness because the

more easily a technology is used, the more useful the

technology is (Venkatesh and Davis, 2000). (Igbaria

and Chakrabarti, 1990) explains in his research that

perception has an impact on individual behavior.

This is explained in more detail that the greater the

individual has the perception of ease in using a new

system, it will lead to an increase in the use of

information technology. Through the BPJSTK

Mobile application participants can access JHT and

JP balances and calculation simulations, complaint

services, information on the BPJS Ketenagakerjaan

branch office, as well as other information regarding

the BPJS Ketenagakerjaan program anytime and

anywhere via a smartphone without having to come

to the office of BPJS Ketenagakerjaan. With a little

skill and internet access, participants can find the

information they need without wasting time so

participants will feel the use of the BPJSTK Mobile

application will be very useful in increasing the

productivity of their effectiveness.

H7: Perceived ease of use (PEOU) has positive

impact(s) towards intention to use (IU)

Based on the results of data processing, it is known

that the P value (probability) is 0.009. These results

meet the requirements of < 0.05 so that it can be

concluded that H7 in this study can be accepted.

This study proves that the easier use of the BPJSTK

Mobile application, the higher the intention to use it.

In line with Park's research, perceived ease of use

has a significant direct effect on intention and

behavior using e-learning (Park, 2009). Cheng's

study states that perceived ease of use will

encourage the use of e-resources (Cheng, 2014). To

use the BPJSTK Mobile application, participants

simply download it on the Play Store via

smartphone. Then, in the initial display, there are

instructions and guidelines for using BPJSTK

Mobile so that participants will not have difficulties.

When the BPJSTK Mobile service makes it easy for

users to download and search for the required

information, the participants' intention to use Mobile

BPJSTK will also increase.

H8: Perceived usefulness (PU) has positive

impact(s) towards intention to use (IU)

Based on the results of data processing, it is known

that the P value (probability) is 0,000. These results

meet the requirements of < 0.05 so that it can be

concluded that H8 in this study can be accepted. In

line with Park's study, perceived usefulness has a

significant direct effect on intention and behavior

using e-learning (Park, 2009). Cheng's study states

that someone who has a perception that using e-

resources will bring benefits to him, and of course

will affect the intention to use it (Cheng, 2014).

UNICEES 2018 - Unimed International Conference on Economics Education and Social Science

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TAM states that the factor of user's perception of

perceived usefulness is believed to be the basis for

determining the acceptance and use of various

information technologies (Handayani, Kusrini and

Sunyoto, 2013). Through the BPJSTK Mobile

application, participants are going to be able to

check quickly and accurately regarding online old

age (JHT) balance, simulation of Old Age Insurance

(JHT) calculation, Pension Guarantee simulation

(JP), Program Information and Co-Marketing

information, branch office information, central

information service, and social media, as well as

complaints service, so that participants feel very

helped by the existence of this application.

Therefore, it will make the perception of usefulness

and usefulness of the BPJSTK Mobile application

becomes a factor that influences participants'

intention to use BPJSTK Mobile.

6 CONCLUSIONS

Based on the results of the research and discussion

in the previous chapter, the conclusions obtained

from this study are as follows:

1. The H1 hypothesis which states that subjective

norm positively influences intention to use is not

accepted

2. The H2 Hypothesis which states that subjective

norm positively influences perceived usefulness

is accepted.

3. The H3 Hypothesis which states that image

positively influences perceived usefulness is not

accepted

4. The H4 Hypothesis which states that computer

self-efficacy positively influences perceived ease

of use is accepted

5. The H5 Hypothesis which states that system

anxiety negatively influences perceived ease of

use is accepted

6. The H6 Hypothesis which states that perceived

ease of use positively influences perceived

usefulness is accepted

7. The H7 Hypothesis which states that perceived

ease of use positively influences intention to use

is accepted

8. The H8 Hypothesis which states that perceived

usefulness positively influences intention to use

is accepted.

Based on the conclusions above, some suggestions

can be given as follows:

1. The researcher hopes that further research will be

carried out related to the TAM technology

acceptance model, especially mobile application

technologies with the use of different variables,

such as job relevance.

2. Future research will be conducted qualitatively,

namely by taking primary data not only by

questionnaire but by field observations and direct

interviews with respondents so that the results of

the analysis are comprehensive.

3. This study proves that perceptions of usefulness

and perceived ease of use have a positive effect

on the intention to use BPJSTK Mobile.

Therefore, BPJS Ketenagakerjaan should be able

to add new features that are useful and easy to

use on the BPJSTK Mobile application.

Additionally, the institution should be willing to

further promote BPJSTK Mobile in terms of

perceived benefits and convenience, so that more

participants are willing to be using the BPJSTK

Mobile application.

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