Evaluation of Acceptance toward Decision Support Systems for New

Student Admission Management

Darmawan Napitupulu

1,3

, Krisna Adiyarta

, Santosa Wijayanto

and Zulvia Khalid

Fakultas Teknologi Informasi, Universitas Budi Luhur, Petukangan, Jakarta, Indonesia

Fakultas Ekonomi dan Bisnis, Univesitas Budi Luhur, Petukangan, Jakarta, Indonesia

Indonesian Institute of Sciences, Tangerang Selatan, Banten, Indonesia

Keywords: Validity, Reliability, Critical Factors, ISO 9001, SMEs

Abstract: To be able to survive amid intense organizational competition, Small Medium Entrepreneurs (SMEs)

require strategies to improve the quality of products/services offered. Quality improvement is clearly needed

so that companies have high competitiveness. Good product/services can be produced by good internal

processes. ISO 9001 Quality Management System is a framework that has been used extensively by SMEs

to ensure the quality of the process. But not a few SMEs have successfully implemented and obtained QMS

certification. Many factors influence the process of implementing ISO 9001 QMS, especially in the context

of SMEs that have many limitations. This study aims to test the validity and reliability of scale for

implementing ISO 9001’s Critical Factors in SMEs level. The method used is a quantitative survey of four

SMEs that have successfully implemented and obtained ISO 9001 certification. Data from the survey were

analysed using the Aiken approach to show the level of validity and reliability. The results showed that of

the 20 items tested, only 19 items were met the criteria. Item of Employee Acceptance was eliminated from

scale because the implementation of ISO 9001 is mandatory for all stakeholders so the factors could be

ignored.

1 INTRODUCTION

The use of Information and Communication

Technology (ICT) today is an inevitable necessity.

Even the use of ICT is one of the opportunities that

can be used by organizations in increasing

competitive advantage. Ray (2007) states that ICT

users can support organizational business processes

and even increase business value. This has also

penetrated into the world of education, including

vocational high schools (SMK). At the vocational

level, there are several activities to support the

learning process, vocational school management or

vocational administration. These activities include:

learning process, student data processing, new

student admission, student data management,

delivery of information to the community, teachers

and students, library management, payment of

school fees, etc. ICT can be used to support these

activities so that the effectiveness and efficiency of

the use of existing resources can be optimized. One

of the uses of ICT is to automate existing business

processes (Wardani, 2017). Based on some

literature, it turns out there are still many SMKs that

have not used ICT optimally. Business processes

that are running are not yet automated, causing

problems such as slow processing, inaccurate

recording, difficulty tracing data, etc. Portraits that

are often found in schools in general are still manual

systems, printed media that is still attached, data

storage is still conventional, that is written on a book

and stored in a large closet that requires a special

room or place (Hartono, 2014; Hasbi, 2015;

Wardani, 2017). This study emphasizes the business

processes of new student admissions, especially in

the Information Technology Vocational High

School. The new student admission system in

vocational schools is still mostly manual where

prospective new students register by writing their

own data on the paper on the registration form

provided. After the form is filled in and then

recapitulated by the school into the computer. The

data collection process for new students also uses

paper and then processed in software such as

Microsoft Excel (Nugroho, 2007; Herdianto, 2014).

Processing of test scores and selection results is

announced through an information board so that

prospective students must be obliged to come to

school. Bina Informatika Vocational Schools, such

Napitupulu, D., Adiyarta, K., Wijayanto, S. and Khalid, Z.

Evaluation of Acceptance toward Decision Support Systems for New Student Admission Management.

DOI: 10.5220/0009491500190023

In Proceedings of the 1st Unimed International Conference on Economics Education and Social Science (UNICEES 2018), pages 19-23

ISBN: 978-989-758-432-9

as schools, generally select new student admissions

based on students' talents, interests and abilities.

This vocational school offers several departments

that are of interest to prospective students so that it

is expected that prospective students can choose an

appropriate department and are able to take part in

the productive learning process of the chosen

department. Therefore, the process of selecting new

prospective students must be done well, otherwise

losses will occur on both sides of the school and

students themselves. In addition, the limited capacity

of each department, the school is expected to be able

to select prospective students based on the highest

score in each entrance examination. To produce

information quickly, precisely and accurately from

the results of the overall value obtained by

prospective students, of course the school needs an

information technology developed. Decision support

systems have been developed to assist management

in selecting prospective students based on

established criteria. This study aims to evaluate the

extent to which the system can be accepted by users

so that it can eventually be used optimally. This is

because an application of the right information

technology in an organization is not an easy thing, it

often fails because of technical and non-technical

constraints (Saktiyanto, 2016). Therefore, evaluation

of user acceptance is very important to predict the

use of these technologies in the future. According to

Delon & McLean (2003), user acceptance of a

technology is directly proportional to its adoption

rate.

According to Jogiyanto (2007), technology users

will have behavioral interests using technology if

they feel the technology is useful and easy to use.

The technology acceptance model that has been

widely used is the Technology Acceptance Model

(TAM) which identifies two key factors of

individual acceptance of technology namely

perceived usefulness and perceived ease of use. This

study uses the TAM model to determine the level of

user acceptance of the decision support system in the

new student admissions process that has been

developed.

2 METHODS

This research is quantitative descriptive which aims

to describe the extent of acceptance of the decision

support system of new students in Bintaro

Informatics Development Vocational School from

the user's perception. Decision support system

(DSS) was developed to assist schools in selecting

prospective new students who take the entrance

screening test, making it easier for management to

obtain data quickly and accurately in making

decisions.

A total of 24 people were involved in the

research survey including the Principal, Deputy

Principal, Deputy Head of Education, Deputy Head

of Student Schools, Deputy Principal of Facilities

and Infrastructure, Head of Information and

Communication Technology, Head of Arts and

Creative Industries and members of the New Student

Admissions Team which was formed to manage the

running PSB process. This is due to the many

criteria tested which include academic tests, aptitude

tests, psychological test, interview tests and physical

tests. All respondents filled out a questionnaire that

had been tested for validity and reliability.

The distribution process and filling out the

questionnaire takes a long time, namely for 1 month

(July 2018). This is because filling out the

questionnaire must simultaneously use the decision

support system directly so that there is an element of

practice. Previously using DSS, respondents were

given an explanation of how the system works and

what features are included in it. After the respondent

uses the system, a questionnaire can be done. The

questionnaire distributed in this study consisted of a

total of 15 statement items (indicators), including 2

independent variables and 1 dependent variable. The

independent variable used to predict the level of user

acceptance is the perception of benefits consisting of

4 statement items and perceived ease of use as many

as 6 statement items. While the dependent variable

measured is the level of user acceptance which

consists of 5 items (indicators). The assessment

dimension uses a Likert scale, starting from a scale

of 1 = "strongly disagree (SDA) to score 5 ="

strongly agree (SA)". The level of approval of the

benefits and ease of use aspects can predict the level

of user acceptance of the developed DSS. In

addition, it can be evaluated what aspects are still

lacking in the performance of the system so that it

becomes a recommendation for future

improvements.

This study uses the technology acceptance model

(TAM) which aims to predict the level of user

acceptance of technology. The original TAM model

actually consists of five variables: perception of ease

of use, perception of usefulness, attitude towards

use, interest in the use of actual systems and use of

behavior. However, in the literature study

conducted, several studies show that attitude

attitudes variables have not proven to be significant

and are dropped from the TAM model (Venkatesh &

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

Davies, 1996; Venkatesh & Davies, 2000;

Venkatesh et. Al, 2003; Chuttur, 2009). They are

arguing that the role of attitude in explaining

behavioral intention or actual adoption is the

behavior is very limited and is a partial mediator in

the relationship between beliefs and the adoption

behavior or intention. Several other studies (Gahtani,

2001; Sanjaya 2002) simplify the TAM model by

combining the use behavior variable with actual

system use into a variable, user acceptance. The

operational model in this study can be presented in

Figure 1 as follows:

Figure 1: Growth of ISO 9001 Penetration (ISO, 2014)

The operational table of the research can be seen in

Table 1 where each variable both independent and

bound variables are latent (abstract) so it needs to be

operationalized by adding several items/

measurement indicators. The measurement

instrument in this study consist of perceived

usefulness (6 items/indicators), perceived ease of use

has 6 items/indicators and user acceptance has 3

items/indicators (Davies, 1989) as presented in

Table 1 below:

Table 1: Measurement Instrument

Testing of user acceptance of DSS is analyzed

descriptively with the first two levels based on the

number of frequencies of the respondent's answer

distribution and the second, with a statistical

indicator in the form of the average value of the total

respondents' answers to each variable and item. In

this study it is assumed that the mean value of a

variable exceeds 4 then it can be concluded that the

level of agreement of respondents is assumed to be

high. For example, if the ease of use perception

variable has an average value equal to or greater

than 4 (4), it can be said that the system proved easy

to use by the user. Conversely, if the mean value is

below 4 (<4), the system is assumed to be difficult to

use. Statistical calculations are also carried out not

only for variable levels, but also for each item in the

questionnaire.

3 RESULT & DISCUSSIONS

Based on the results of the questionnaire that has

been processed obtained descriptive statistics that

can be presented in Table 2 as follows:

Table 2: Response Frequency : Perceived Usefulness

SA= Strongly Agree, A=Agree, N=Netral, DA=Disagree,

SDA=Strongly Disagree

Based on Table 2 of the perceived usefulness aspect

that is assessed, the majority of respondents' answers

are neutral and agree. The indicator "accelerating

completion of work" gets the highest percentage of

59% of respondents agree and 33% of respondents

said strongly agree. In addition, if the average value

of each indicator calculated for indicators obtained

for PU1 items, the average score of 4.25, PU2 4.00,

PU3 and PU4 has the same score of 3.92. From the

average scores obtained, almost all get a mean score

of 4.00 so that it can be said that the decision

No Variab

Item/Indicator

1. Perceived

Usefulness

Accelerate completion of tasks (PU1)

Improve performance (PU2)

Simplify work (PU3)

Increasing Effectiveness (PU4)

2. Perceived

Ease of Use

Easy to learn (PE1)

Easily calculate participant value (PE2)

Easily get ranking information (PE3)

Easy to understand (PE4)

Skill using (PE5)

Easy to use (PE6)

3. User

Acceptance

Increase frequency (UA1)

Interest in using (UA2)

Real use (UA3)

User satisfaction (UA4)

Motivate others (UA5)

Item/Indicat

Response Frequency

SA A N DA SDA

Accelerate

completion

of tasks

(PU1)

33% 59% 8% - -

Improve

performance

(PU2)

17%

43% 50

- -

Simplify

work (PU3)

17%

34% 58

- -

Increasing

Effectivenes

s (PU4)

18%

33% 58

- -

Evaluation of Acceptance toward Decision Support Systems for New Student Admission Management

support system developed is considered useful for

users, especially in accelerating task execution,

improving work performance and effectiveness in

helping new student admission activities in school.

The results in terms of perceived ease of use can be

shown in Table 3 below:

Table 3: Response Frequency : Perceived Ease of Use

In Table 3 it can be seen that the majority of

frequency answers are at the agreed level where the

highest agreed frequency is on the indicator "easy to

calculate the value of participants (PE2)" and "easy

to get information (PE3)". When viewed in PE2 and

PE3 items, users find that the decision support

system can provide information quickly and easily

regarding the rank of prospective students who have

taken the exam based on the calculation of the value

criteria tested. Based on the average value

calculated, the PE1 items obtained got a score of

4.17, PE2 & PE3 4.25, PE4 3.92, PE5 & PE6

reaching 3.83. In general, the average score obtained

is 4.00 although there are several indicators that

must be improved. Thus it can be said that the

decision support system can provide ease of use for

users to select prospective new students in the

school environment.

Furthermore, in this section also analysed aspects

of user acceptance which can be presented in Table

4. Based on Table 4 below, it can be shown from the

overall indicators that are assessed, the frequency of

respondents' answers at the level strongly agrees and

agrees is higher than the other alternative answers.

For example, the item "interest in using (UA2)", the

number of respondents who chose a very agreeable

answer reached 50% (12 of 24 respondents) and

agreed also 50%.

There are no other answers besides the two

answers. This means that the interest of respondents

to use the system is very high. The average value

obtained for each item is as follows: UA1 4.42, UA2

4.50, UA3 4.33, UA4 4.33 and UA5 get an average

score of 4.08. From the average score it can be

shown that all items measured have a mean value

above 4 (> 4) so that it can be said that each

indicator shows that user acceptance is also high for

the decision support system that has been developed.

The mean score summarized for each variable that

also shows the same results as the analysis carried

out is for perceived usefulness (4.02), perceived ease

of use (4.04) and user acceptance (4.39). All varaibel

have an average score above the number 4 (<4)

where the variable perceived ease of use has a higher

value than perceived usefulness.

Table 4: Response Frequency : User Acceptance

This shows that the factor of ease of use is

preferred by the user in this case which encourages

high user acceptance. This will certainly greatly

support its adoption in the future.

4 CONCLUSIONS

Based on the research that has been carried out, it

can be concluded the survey results of user

acceptance evaluation that the user considers the

decision support system developed is very useful in

supporting the completion of work more effectively

and efficiently and improving performance,

especially management and the new student

admission team. In terms of ease of use, users are

also perceived to be very good, especially easy to

calculate the value of participants and easily get

information on the rankings of the participants

resulting from the selection. Both of these

independent variables proved to be in line with the

level of user acceptance which was also perceived as

high especially for the interest in using the system.

The evaluation results provide input and

Item/Indicator

Response Frequency

SA A N DA SDA

Easy to learn

(PE1)

33% 50% 17% - -

Easily calculate

participant value

(PE2)

34% 58% 8%

- -

Easily get

ranking

information

(PE3)

34% 58% 8%

- -

Easy to

understand

(PE4)

25%

42% 33%

- -

Skill using (PE5)

17%

50% 33%

- -

Easy to use

(PE6)

17%

50% 33%

- -

Item

Response Frequency

SA A N DA SDA

Increase

frequency

(UA1)

50% 42% 8% - -

Interest in

using (UA2)

50% 50% -

- -

Real use

(UA3)

42% 50% 8%

- -

User

satisfaction

(UA4)

42% 50% 8%

- -

Motivate

others (UA5)

3% 42% 25% -

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

recommendations for the school management in

increasing the use of the system in the future.

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Evaluation of Acceptance toward Decision Support Systems for New Student Admission Management