Analysis of Acceptance of Online

RS using Technology Acceptance

Model (TAM) Method: Case Study of STMIK Cipta Darma

Surakarta Student

Siti Rihastuti

, Afnan Ros

idi

and M. Nur Juniadi

Informatics Management, STMIK Cipta Darma Surakarta, Veteran street, Notosuman, Sukoharjo,, Indonesia

Keywords: Tam, online krs, usefulness, ease of use.

Abstract: This research was conducted to know how far the acceptance of student to utilization of facility of Study Plan

Card (KRS) based online by using approach model of Technology Acceptance Model (TAM) method. It is

important to know how the user's response to the information system and in the future can be developed an

information system that is more acceptable to the users. TAM is one of the theoretical approaches that can

describe the level of acceptance of technology. In this method there are 3 (three) variables tested and analyzed,

consisting of two independent variables (Perceived Usefullness and Ease of Use) and one dependent variable

(User acceptance of IT / Acceptance of IT). Respondents come from Information Management students of

STMIK Cipta Darma Surakarta. Through TAM model can be described that the user perception will determine

the reaction and attitude to the acceptance of information technology.

1 INTRODUCTION

The development of information technology so

rapidly in the current era of globalization. Almost all

areas and human activities are supported by the

existence of information technology. Information

technology is a technology used to process data,

including processing, obtaining, compiling, storing,

manipulating data in various ways to produce quality

information, ie relevant information, accurate and

timely. STMIK Cipta Darma Surakarta is one of the

computer universities in the city of Surakarta.

Management of good academic activities also support

the smooth running of learning process. One of the

services for students is the existence of online based

Study Card (KRS) system. After printing KHS (Card

Study Result) semester before and consultation

course to be taken to lecturer of academic supervisor,

then student fill KRS online at web

www.amikomsolo.ac.id without having to come to

campus.

Students can fill out KRS to choose courses to be

taken in the next semester. From existing KRS

information systems, connect between students and

campus parties. So if at the time of charging KRS

occurs obstacles, errors / errors, insecurity in

achieving its objectives, will lead to the possibility of

failure of management information systems KRS and

disruption of lecture continuity in the next semester.

Based on this, it can be seen that KRS is very

important for the continuity of teaching and learning

process on campus. So it is necessary to do analysis

and evaluation to find out what are the obstacles for

students when the use of information systems KRS.

From the implementation of KRS online use by

students, it has not been analyzed yet and it is not

known how far the benefit felt by students and

academic department. This analysis is important to

know the user's response to the information system

used and attempts to improve (evaluation) of the

student especially as the user, and the academic part

as the provider of information system, so it is

expected the academic part as the provider of

information system can develop the system to be

better and can more accepted by users in the future.

Evaluation done after seeing the number of students

who access (log in) into the information system KRS

using the username and password of other students.

In terms of security, it is still unclear how much

student confidence in KRS online benefit using the

account he uses. In this study, the questionnaires were

distributed to students of Informatics Management

course using KRS online at STMIK Cipta Darma

Surakarta.

Rihastuti, S., Rosyidi, A. and Junaidi, M.

Analysis of Acceptance of Online KRS using Technology Acceptance Model (TAM) Method: Case Study of STMIK Cipta Darma Surakarta Student.

DOI: 10.5220/0009946530513059

In Proceedings of the 1st International Conference on Recent Innovations (ICRI 2018), pages 3051-3059

ISBN: 978-989-758-458-9

3051

To know the extent to which users are willing to

accept and use KRS online it is necessary to evaluate.

There are many models developed by researchers to

measure the acceptance of technology by users. One

theory about the use of information technology

systems that are considered highly influential and

commonly used to describe individual acceptance of

the use of information technology systems is the

technology acceptance model (TAM). This theory

was first introduced by Davis (1986). This theory was

developed from Theory of Reasoned Action or TRA

by Ajzen and Fishbein (1980).

Technology Acceptance Model (TAM) is a model

of acceptance of information technology systems that

will be used by users. The technology acceptance

model (TAM) or TAM was developed by Davis et.al.

(1989) based on the TRA model. The TRA model can

be captured because the decisions made by

individuals to accept an information system

technology are conscious actions that can be

explained and predicted by their behavior interests.

TAM adds two main constructs to the TRA model.

The two main constructs are perceived usefulness and

perceived ease of use. TAM argues that individual

acceptance of information technology systems is

determined by the two constructs. perceived

usefulness and perceived ease of use both have an

effect on behavioral intention. Technology users will

have an interest in using technology (interest in

behavior) if they feel the technology system is useful

and easy to use. Perceived usefulness also affects

perceived ease of use but not vice versa. System users

will use the system if the system is useful whether the

system is easy to use or not easy to use. A difficult

system to use will still be used if the user feels that

the system is still useful. The model of TAM against

online KRS acceptance can be seen in figure 1.

 Perceived Usefulness

Defined as perceived usefulness is a level where

the user believes that the online KRS information

system will be able to improve the performance or

performance of users of the system.

Figure 1. Online KRS Acceptance Analysis

 Perceived Ease of Use

The definition of perceived ease of use is a level

at which users believe that the use of the online KRS

information system can reduce a person's business in

doing something. Ease is meaningless without

difficulty or unnecessary effort. This perceived ease

of use refers to the user's belief that the technology

system used does not require a great deal of effort

when used. In this case at the time of filling KRS

online, students do not need to come to campus,

students can make data entry in KRS information

system from anywhere based on the information

provided

2 METHOD

Figure 2. Research method

2.1 Study of Literature

The first step of this research method is to conduct a

literature study on online KRS and TAM methods to

be used.

According to research Fatmasari et al. with title

Applying Technology Acceptance Model (TAM)

Method to Acceptance of Online KRS (Case Study:

Computer Science Student of Bina Darma University

of Palembang) described that perceived usefulness

variable and perceived ease of use are very influential

against user behavior in receiving the technology it

uses. The higher the usability and the ease of using

information system technology, the higher the

acceptance for the user.

Putu Adi research in his writings entitled

Implementation of TAM Method (Technology

Acceptance Model) in Information System

Implementation Bazaar Banjar explained that the

belief that bazaar banjar information system is useful

Perceived

usefulness

Perceived

ease of use

Acceptance of

online KRS

(Intention to

Use)

Study of literature

Data collection

Conclusion

Analysis

ICRI 2018 - International Conference Recent Innovation

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will affect the attitude of acceptance or rejection of

bazaar banjar information system.

According to research Agusdi Syafrizal et al.

Under the title Applying Technology Acceptance

Model (TAM) Model for Understanding Interactive

Multimedia Based Media, TAM model can explain

that user perception will determine its attitude in

acceptance of use of Information Technology (IT).

This model more clearly illustrates that the recipient

of IT usage is affected by usefulness.

According to Kartika Gianina G. in the title

Applying Technology Acceptance Model On

Edmodo Application At Ciputra University Surabaya

Using Path Analysis, the perception of usage of direct

use has an effect on intention to use, so it can be

concluded that Edmodo users are still oriented to find

software that is easy to use view other features and

uses and user intentions directly affect real usage.

According to Siti Monalisa et al. In his research

Analysis of Acceptance of Information System of

Routine Statistics Data Processing (SISR) Using

Technology Acceptance Model Method (Case Study:

BKKBN Riau Province) got the result that

Quantitatively, correlation of variable of benefit to

receipt of Information System Data Processing

Routine Statistic (SISR) 58.6%, the ease of

acceptance of Information System Data Processing

Routine Statistics (SISR) is 52.3% and the correlation

between the ease and benefits simultaneously to the

acceptance of Information System Data Processing

Routine Statistics (SISR) of 64.6%. This value

indicates that ease and benefit variable have good

relation to user acceptance of Information System of

Routine Statistics Data Processing (SISR).

According to Fran Sayekti et al. In his research

entitled Implementation of Technology Acceptance

Model (TAM) In the Testing of Acceptance Model of

Regional Financial Information System, obtained the

result that the success of acceptance of SIPKD

depends on user perception. If the user thinks that

SIPKD is easy to use and useful then they will more

easily accept SIPKD in their work. For decision

makers regarding the use of information systems in

government agencies, with the results of this study it

is advisable to conduct trials and training on users

before the system is officially applied as a necessity.

With a trial and a structured training, the user will

more easily operate the information system

According to Marini et al. In her writings entitled

Technology Acceptance Model Analysis BPJS

Application On line Acceptance of the BPJS Online,

application model improve service to service users,

namely parties the community evaluates the

management of the party by asking for feedback from

the community receipt of online BPJS applications.

This evaluation is done to find out about the

acceptance of society BPJS Online application

technology. This research is only focused on the BPJS

Online Application Technology Acceptance Model

namely the usage phase based on Usability, Ease, and

intention to use Application Technology The

community's online BPJS feels. Model Analysis

researchers use is Path Analysis namely development

directly form Double Regression so that the level of

importance a significant variable causal relationship.

Method which is used to test the correlation

relationship pattern variable that is Structure

Equation Modeling (SEM) with using AMOS 16.0

Software.

According to Rini Oktofiyani et al in her

writings entitled Acceptance Of E-Learning System

Using Technology Acceptance Model (Tam) Case

Study Of Students / I Class X In Jakarta 92 State High

School, described that The current technology

developments led to the need for information

quickly, precisely and accurately. One of the

technological developments in the field of education

is the elearning. SMA Negeri 92 Jakarta is one of the

implemented system learning who made online and

are expected to help students improve their learning.

Instruments research on analysis of acceptance e-

learning systems using technology Acceptance

Model (TAM) is the questionnaire form and the

object of research is the grade X SMA Negeri 92

Jakarta 138 respondent of the student taken. Analysis

of the data done by the descriptive analysys

techniques using the categories and percentages

through the scale likert. The result showed that the

relationship between variable X (Perceived Ease Of

Use and Perceived Usefulness) and variable Y

(behavioral Intention to Use) in acceptance system e-

learning SMA Negeri 92 Jakarta is 0,727. The value

of the correlation of this very strong positive. The

relationship has a positive is the direct relationship

between variable X and Variable Y. Based on the

correlation coefficient analysis correlation, both

manually and using SPSS, can be concluded that the

relationship that occurs between

variable X (Perception of Ease of Use and Benefit

Perception) with variables Y (Perception of interest in

using behavior technology) in the acceptance of the

ELearning system Jakarta Public High School 92 is

0.722. The correlation value of this magnitude is

strong positive. Relationships are strong positive it

means that there is a directional relationship variable

X and variable Y. When Ease usage and benefits are

getting better then the user's interest in using

Analysis of Acceptance of Online KRS using Technology Acceptance Model (TAM) Method: Case Study of STMIK Cipta Darma Surakarta

Student

3053

technology is increasing. Contribution of the

influence of variable X (Ease Usage and Benefits)

variable Y (Interest in using behavior technology) in

the acceptance of the ELearning system Jakarta

Public High School 92 is 52.2%, while 47.8% is

determined by other variables. Results of significance

testing (Correlation Product Moment Person)

obtained the value of tcount = 12,177, with a

significance level of 5% value of t table = 1,978.

Because thitung is bigger from ttable, Ho is rejected,

so Ha be accepted. Thus there is significant influence

between Ease Usage and Use with Interest

technology use behavior towards acceptance of the

State High School E-Learning system 92 Jakarta.

According to Susy Rosyida in her writing entitled

Technology Acceptance Model (TAM) on Internet

Usage in Shopping Online. This research is to know

the utilization of internet technology in online

shopping. This research method is explanatory

research with quantitative approach. Data in this

research that is primary data and secondary data,

primary data that is used that is by spreading

questioner to respondent of internet user in doing

onlne or e-commerce shopping whereas secondary

data used is from report, journal and literature

relevant. By using the Technology Acceptance Model

(TAM) variables used are usability, ease, attitude,

intense and the use of online transactions or online

shopping or use of e-commerce. The results show that

ease has a significant influence on usability, ease,

attitude, intensity and usage with the utilization of

internet technology as a technology for conducting

online transactions or shopping online or using e-

commerce. Variable usability, convenience, attitudes

have the most dominant influence on intense and

usage in using e-commerce. Conclusions from the

results of research using This explanatory research

shows that respondents using the internet in the

business sector as an intermediary medium in

conducting online shopping transactions e-

commerce. By using variables usability, ease,

attitude, intense and internal use using e-commerce is

very influential significant so that it can make it easier

for good users as a buyer or as a seller get information

about what is needed or make transactions and give

satisfaction to the service.

According to Fatmasari et al in her writings

entitled Evaluation Of Acceptance Of E-Ktp System

Using Tam (Technology Acceptance Model) (Case

Study: Palembang Ilir Timur I Sub-district Office).

The E-KTP project is motivated by a system that

makes conventional ID cards in Indonesia possible. A

person can have more than one ID card. This is due to

the absence of an integrated database collect data on

residents from all parts of Indonesia. To overcome

these duplications at once creating a single identity

card. So the E-KTP is based on the Population

Registration Number (NIK), E-KTP based on

national NIK, contains security codes and electronic

records as verification tools and validation of one's

identity data. This study aims to determine the factors

that influence acceptance of the Electronic Identity

Card (E-KTP) system with the Technology

Acceptance model Model (TAM), which was carried

out at the East Ilir Sub-District I (IT I) office. In this

study, the author using three variables that influence

the acceptance of the E-KTP system. This variable is

Perceived Usefulness (PU) and Perceived Ease of Use

(PEOU) as independent variables while receipt of

EKTP systems as related variables. Sampling in this

study was carried out in probability (random

selection) using the Area Sampling or Sample area

method, the researcher set a sample for the

community as many as 20 respondents from each

village to get it total respondents for the community

were 220 respondents representing each village.

Results This study shows that simultaneously or

partially there is a significant relationship and

positive between independent variables and related

variables. While the results of the Regression analysis

obtained facts that the contribution of these two

variables is 64.5% of the receipt of the E-KTP system.

Based on the description of theory and the results

of previous research, it can be formulated hypothesis:

1. If the student as the user of KRS online information

system has the perception that the system is easy

to use and easy access of KRS filling, the student

will increasingly use the online KRS system

actual (according to KRS filling schedule) to

complete the process of KRS management, so the

hypothesis is submitted is:

H1: Perceived Ease of Use has a positive effect on the

acceptance of KRS online information system.

2. If the student as the user of KRS online information

system has a perception that the system is easy to

use and easy access of KRS filling, then the

student will increasingly use the actual online

KRS information system (according to KRS

filling schedule) to complete the process of KRS

management, so the hypothesis filed are:

H2: Perceived Usefulness has a positive effect on the

acceptance of KRS online information system.

3. If students as users of KRS online information

system have a perception that the online KRS

information system is easy to use and useful in

completing the process of KRS management, the

students will increasingly use the online KRS

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information system. So the third hypothesis

proposed in this study are:

H3: Perceived Ease of Use and Perceived Usefulness

together have a positive effect on the acceptance of

KRS online information system

2.2 Data Collection

The second stage is to collect data. Data used in this

research are primary data and secondary data.

Primary data is data collected directly by researchers

or who need data in the field. Primary data is obtained

from individuals or individuals. Primary data in this

research is the result of quosinal answer is distributed

to the student of Information Management STMIK

Cipta Darma Surakarta. Respondents involved are

active students using KRS online information system.

Questionnaires were not distributed to all students,

only samples were taken. The sample is part of the

overall population used to describe a population.

While secondary data is data collected by researchers

or who need through existing sources. This data is

used to support the primary data already obtained.

Secondary data in this research is literature, books

and other library materials. One method that can be

used to determine sample size is the Slovin formula:

Where :

n = number of samples

N = population size

d = limit of accuracy (inaccuracy due to sampling

error). If the limit of accuracy is 10%, then this

sample has a 90% accuracy to describe the

population.

Based on the calculation of Slovin formula, we get

the sample size used as:

n = ( 100 )

(100 x (0,1)

) +1)

n = 100

n = 50

From the calculation, the minimum required

sample is 50 people. The questionnaire obtained from

the results of disseminating to the students of

Information Management is 55 questionnaires, so the

number of questionnaires is sufficient to describe the

user population of KRS online information system.

Respondents involved are students who have an 18-

22 year age range. The detail characteristics of

respondent questionnaires seen in Table 1.

Table 1. Characteristics of Respondents Questionnaire

Gender Percentage

Male Female Male Female

33 22 0,6 0,4

2.3 Analysis

In this study, researchers chose the TAM model

as a theoretical basis that has a strong ability to

explain the use of technology by users (Davis,

FD1989). This study used 3 (three) variables that

have been modified from the previous TAM research

model: Perceived Usefulness as the first variable (A),

convenience (Perceived Ease of Use) as the second

variable (B), and acceptance of online KRS users as

related variables (X) which according to the TAM

theory significantly usability variables and

convenience variables affect the acceptance of users

in the use of online KRS. More clearly can be seen in

Table 2 regarding the variables used to measure the

acceptance of online KRS users.

Table 2. Variables used in the study

Variable Definition Indicator

Perceived

Usefulness

Explain

that users

believe that the

KRS

information

system will be

able to improve

work

performance or

performance

a. Charging

KRS is faster

b. Charging is

easier to do

c. Improve

effectiveness

d. Useful

Perceived

Ease of

Use

A level

where users

believe that the

use of KRS

information

systems can

reduce a

person's

business in

doing

something

a. Easy to learn

b. Easy to use

c. Available

information

is clear

d. Free from

trouble

Intention to

use

Online

acceptance

level of KRS by

user

a. Interest in

using the

system in

real time

b. Frequency of

system usage

c. User

satisfaction

d. Motivate

other users

Analysis of Acceptance of Online KRS using Technology Acceptance Model (TAM) Method: Case Study of STMIK Cipta Darma Surakarta

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2.4 Data Analysis Technique

Test Prerequisite (instrument) is done by using data

validity test and data reliability test. This prerequisite

test is performed using SPSS for windows program.

a. Validity test

Validity test is done to find out whether all

research (instrument) question that is proposed to

measure research variable is valid. Validity test is

done by looking at the significant value of each

instrument. To calculate the value of correlation

between data on each question with total score using

product moment correlation technique formula, the

formula as follows:

Information :

r: correlation value

n: number of respondents

X: score of each item

Y: total score

XY: score of each item x total score

ΣY

: sum of squares total score

ΣX

: sum of squares of item scores

(ΣY)

: the square of the total total score

(ΣX)

: Squares the number of item scores

b. Test Reliability

The constructs need to be tested for their

reliability. Reliability testing is used to measure the

consistency of respondents' answers. Test performed

with Cronbach Alpha (CA). If the measuring

instrument is valid, then the measuring instrument is

tested. Reability is a value that shows the consistency

of a measuring device in measuring the same

phenomenon. Reliability measurement technique

used is Cronbach technique. Looking for instrument

reliability whose score is not 0-1, but it is between

several values. The scores used by the authors are 1

to 5.

The formula used is:

Information :

r11: Instrument reliability

k: Many questions

αt2: Total standard deviation

Σαb2: The number of standard deviations of the

item

For the number of variance of grains determined

by determining the variance value of each item by

using the following formula:

information :

n: Number of respondents

X: Score value selected from the item in question

Table 3. Interpretation of Cronbach Alpha Numbers

Cronbach’s Alpha Interpretation

α≥0,9 Very Good

0,8≤α<0,9 Good

0,7≤α<0,8 Acceptable

0,6≤α<0,7 Questionable

0,5≤α<0,6 Not good

α<0,5 Unacceptable

c. Multiple Linear Regression Testing

Hypothesis testing is done by statistical test using

multiple linear regression method because

independent variable used more than one variable.

Multiple regression analysis is used to see the

influence between more than one variable, which in

this research is the usefulness and ease of acceptance

of online KRS system in STMIK Cipta Darma

Surakarta.

The multiple regression equation is:

Y = a + b

+ b

+ e……(4)

Information :

Y: Acceptance of online KRS system

a: Constants

: regression coefficient

: Benefit variable

: Variable convenience

e: Error

2.5 Results

2.5.1 Characteristics of Respondents

1) Gender

Based on the research on 55 questionnaires, the

majority of respondents were Male (33%), while the

rest were 22 respondents (40%) female. The age

range of respondents who filled out the questionnaires

was from 18 years old to 22 years old.

2) Length of Computer Use

Of 55 questionnaires, 25 respondents used

computers less than 6 years (45%), 18 respondents

used computers more than 6 years (32%), 7

respondents used computers for less than 10 years

(12%), and 5 respondents use computers for more

than 10 years (9%).

3) Frequency of Internet Usage per day

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Respondents who used the internet per day consisted

of 5 respondents or 9% for less than 3 hours, 17

respondents or 30% for 3 hours to 6 hours, 23

respondents or 41% for 6 hours to 10 hours, and 10

respondents or 18% for more than 10 hours per day.

4) Do You Know about the existence of KRS

Online

Of 55 questionnaires that have been filled, all

respondents claimed to have known the existence of

online krs on AMIK Cipta Darma. This means that

100% of respondents involved have known and

understood the existence of the information system.

2.6 Test Validity and Data Reliability

Based on the data obtained from the questionnaire

given to the respondents who entered into the sample

and then tested the questionnaire to measure the level

of goodness of the questionnaire is to conduct the

validity and reliability analysis of the questionnaire.

Validity indicates the extent to which the question

relates to what is being asked or what it wants to

measure in the research. The validity level of the

questionnaire is measured by the validity coefficient

which in this case uses the Pearson correlation

coefficient, while the reliability of the data to see how

reliable the data is based on the Cronbach's alpha

coefficient If the output display in the tested column

(r value) is marked with a star, or the question is

declared valid (Ghozali, 2010).

2.6.1 Variable Usefulness (Perceived of

usefulness)

For validation test of usability variable (PU) (A), the

result can be seen in Table 4.

Table 4. Test results of validity of usability variables

A-PEU

Person

correlation

PU1 .734**

PU2 .651**

PU3 .783**

PU4 .762**

B-PU 1

N 54

In table 4 it can be seen that all statement items

are marked (flag) which means that all items can be

declared valid.

In reliability testing all items used in measuring

the benefit variable yield reliability coefficient

(cronbach's alpha) of 0.842. Value of reliability

coefficient is greater than the benchmark value of 0.6,

so it can be said that the indicators used to measure

the variable benefits are expressed to have high

reliability.

Table 5. Reliability test results of usability variables

Cronbach’s

Alpha

Cronbach’s Alpha

based on standardized

items

N of

items

,842 ,864 5

2.6.2 Variable Perceived Ease of Use

For Perceived ease of use (A), the results can be seen

in Table 6.

Table 6. Test results of validation of perceived ease of use

variables

B-PEU

Person

correlation

PEU1 .632**

PEU2 .699**

PEU3 .701**

PEU4 .742**

X2-PEU 1

N 54

In table 6 it can be seen that all statement items

are marked (flag) which means that all items can be

declared valid.

In reliability testing all items used in measuring

the benefit variable yield reliability coefficient

(cronbach's alpha) of 0.762. Value of reliability

coefficient is greater than the benchmark value of 0.6,

so it can be said that the indicators used to measure

the variable benefits are expressed to have high

reliability.

Table 7. Reliability test results of perceived ease of use

variables

Cronbach’s

Alpha

Cronbach’s Alpha

based on

standardized items

N of items

,762 ,802 5

2.6.3 Variable Attitude of User Behavior

Table 8. Test results of the validity of behavioral behavior

variable of the user

X-C

Person

correlation

C1 .722**

C2 .541**

C3 .472**

C4 .632**

X-C 1

N 54

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In table 8 it can be seen that all statement items

are marked (flag) which means that all items can be

declared valid.

In reliability testing all items used in measuring

the benefit variable yield reliability coefficient

(cronbach's alpha) of 0.652. Value of reliability

coefficient is greater than the benchmark value of 0.6,

so it can be said that the indicators used to measure

the variable benefits are expressed to have high

reliability.

Table 9. Reliability test results of user behavior attitudes

Cronbach’s

Alpha

Cronbach’s Alpha

based on

standardized items

N of items

,652 ,748 5

2.7 Multiple Linear Regression Test

2.7.1 Correlations

It is the result of data processing with multiple linear

regression analysis using SPSS application. This

output is used to show the relationship partially

between independent variables with the dependent

variable. The results of Correlations in this study are

presented in table 10, it is known that the correlation

coefficient (r) between variable A-Use (PE) and C-

Admission (BI) variable is 0.542. While the

correlation coefficient between variables B- Ease

(PEU) with C-Reception (BI) is equal to 0.636. The

result showed that in the sample of 55 respondents,

the independent variables (A and B) partially have a

direct (positive) relationship with the dependent

variable (Y), where the closeness of the relationship

is strong.

Table 10. Result corellation

BI PE PEU

Pearson

correlation

BI 1.000 .542 .636

PE .542 1.000 .641

PEU .636 .641 1.000

Sign

(1-tailed)

BI . .000 .000

PE .000 . .000

PEU .000 .000 .

N BI 55 55 55

PE 55 55 55

PEU 55 55 55

2.7.2 Model Summary

Summary model shows the relationship together

between independent variables with dependent

variable. The relationship shows that the correlation

coefficient is R = 0.618. This means that together A

and B have a strong relationship with C. While the

determination is (R2) = 0.399, it means that together

A and B are able to explain the variation of C change

by 39%.

3 CONCLUSIONS

Based on the analysis that has been done before, can

be drawn some hypothesis and conclusions related to

the analysis of acceptance of online krs using TAM

as described earlier, that is

• Perceived Ease of Use has a positive effect on

the acceptance of KRS online information

system. This hypothesis is seen based on the

increasing increment of ease of KRS online

information system owned, increasing the

system acceptance by the users of the system.

• Perceived Usefulness has a positive effect on

the acceptance of KRS online information

system. This hypothesis is seen based on the

increasing use of online KRS information

system owned, increasing the system

acceptance by users of the system.

Perceived Ease of Use and Perceived Usefulness

together have a positive effect on the acceptance of

KRS online information system. This hypothesis is

the most acceptable statement, because based on the

analysis that has been done, the addition of usefulness

and usefulness possessed by the online KRS

information system will further increase the user's

confidence in receiving and using the information

system.

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