Analysis of the Student Background and Social Inﬂuence for Social

Media-based Learning

Surjandy

, Meyliana

, Yuli Eni

, Erick Fernando

, Kristianus Oktriono

and Chutiporn Anutariya

Information Systems Department, School of Infomration Systems, Bina Nusantara University, Jakarta, Indonesia

Management Department, Binus Business School Undergraduate Program, Bina Nusantara University, Jakarta, Indonesia

Language Center, Faculty of Humanities, Bina Nusantara University, Jakarta, Indonesia

School of Engineering and Technology, Asian Institute of Technology, Pathumthani, Thailand

Keywords:

social media learning, explanatory, correlation bivariate technique, social inﬂuence, social media based

learning.

Abstract:

The function of Social Media has developed over time since its inception. It tackles a speciﬁc challenge for

social activities instruments and learning tools. As the literature indicated, early spans of research drove the

initiative to elaborate on social media for learning purpose. In this frame, the research urges to expound

the relationship between university student background and social inﬂuence factor of social media used for

the objective of learning. At a closer look, the study engaged the causal or explanatory method to ﬁnd the

relationship between university background factors such as grade point, gender, strata, semester, age time

spent for social media and social inﬂuence factors such as family and friend. On that basis, the study used

SPSS to process the data and apply the correlation bivariate technique. With these lenses, the study obtained

twenty-four signiﬁcant pair factors. The result of the study contributes substantially to the development of

social media for future learning tools.

1 INTRODUCTION

At its core, learning method rapidly develops from

the conventional way into technological-based; the

changes are occurring in Indonesia similarly. Re-

cently, the data of active internet users accounted

for 143 million of the total population in Indone-

sia (APJII, 2018). As the study revealed, previous

research reported that most university students used

a smartphone for learning and social activities (Sur-

jandy, 2016) (Balakrishnan and Gan, 2016) (Gikas

and Grant, 2013) (Acarli and Sa

glam, 2015). In this

respect, the students accessed Facebook for learn-

ing supporting tool (Tanty, 2017). However, the re-

sult of previous research in social media for learning

drives(Deaton, 2015) an insistence debate such as

• lack of response from the participant,

• unfamiliar with the topic,

• encountering difﬁculty(Manca and Ranieri,

2016),

• another issues is fake degree provided by univer-

sity that provided online (social media) learning

activity(Abbas et al., 2019).

Therefore, this study attempts to explore the so-

cial inﬂuence of university student in using social

media and smartphone for learning purpose. In this

line, causal or explanatory research method is used in

this study to describe the relationship of inﬂuence be-

tween factors. Figure 1 represented the explanation

of the research design. In the scope of sampling, the

study involved four hundred and fortysix respondents

in this paper from several universities in Indonesia

and all participants posed as active users in the con-

text of social media.

The hypothesis of the study consists of two parts:

• The university student background has the inﬂu-

ence to use social media for learning. H0 Uni-

versity Student’s background has no inﬂuence to

use social media for learning. H1 University Stu-

dent’s background has the inﬂuence to use social

media for learning

• The social inﬂuence has a relation to use social

media for learning

H0 Social inﬂuence has no relationship to use

social media for learning.

H1 Social inﬂuence has a relationship to use

184

Surjandy, ., Meyliana, ., Eni, Y., Fernando, E., Oktriono, K. and Anutariya, C.

Analysis of the Student Background and Social Inﬂuence for Social Media-based Learning.

DOI: 10.5220/0009907601840192

In Proceedings of the International Conferences on Information System and Technology (CONRIST 2019), pages 184-192

ISBN: 978-989-758-453-4

social media for learning

The study found twenty-four signiﬁcant relations

between factors. In a speciﬁc context, there are six-

university student’s backgrounds who have inﬂuence

and relationship with social inﬂuence. It directs that

the result of this study contributed signiﬁcantly to the

development of social media for learning in the future.

Figure 1: Research Design

2 METHODOLOGY

In this session will explain about methodology used

in this study such as causal research, Pearson strength

tension correlation, bivariate technique

2.1 Causal Research

Causal Research or also known as Explanatory Re-

search is usually used for preliminary research to look

for a relationship between factors or inﬂuence of one

factor to another and used in marketing or sales area

(Ltd, 2006) (Businessdictionary, 2019).

2.2 Pearson Strength Tension

Correlation

The Pearson correlation (r) value can be used to de-

scribe the tension of the correlation where the value

between .1 to .3 refers to small or weak tension of

correlation. Meanwhile, the score of between .3 to

.5 reﬂects medium or moderate tension of correlation.

The score that is higher than .5 is large or strong cor-

relation (Yeager, 2019).

2.3 Bivariate Technique

In this part, one of the techniques to look for the rela-

tionship between factors by using SPSS application is

Bivariate correlation. In this line, this technique will

show the Pearson correlation (r) value or relationship

between factors (IBM, 2019). Meanwhile, the Pear-

son correlation (r) value describes the tension of the

relationship between factors.

2.4 Data Collection

Table 1: Respondent Background.

No Description Total

N=446

Percent

1 Grade Point(D1)

1. < 2 20 4.5%

2. 2.01 – 2.50 24 5.4%

3. 2.51 – 2.99 85 19.1%

4. > 3.00 317 71.1%

2 Gender(D2)

1. Female 279 62.6%

2. Male 167 37.4%

3 Strata(D3)

1. Diploma 37 24.0%

2. Bachelor 402 24.9%

3. Master 6 17.0%

4. Doctoral 1 34.1%

5 Age(D5)

1. <17 4 0.9%

2. 18 – 25 434 97.3%

3. 26 – 30 3 0.7%

4. >30 5 1.1%

6 Social Media(D6)

1. <3 hours 31 7.0%

2. 3 – 5 hours 105 23.5%

3. 6 – 8 hours 145 32.5%

4. 9 – 11 hours 88 19.7%

5. 12 – 14 hours 30 6.7%

> 15 hours 47 10.5%

In this section, the snowball technique is used to

gather the respondent. Technically, the researchers

used google form application to support the research.

Also, the sample of the respondent in this study con-

sisted of four hundred and forty-six. Based on In-

donesia Internet Service Association in 2018, the in-

ternet user in Indonesia is 143,26 million users, and

89.35% is active social media user or around 128 mil-

lion users(APJII, 2018). With this setting, the re-

searchers applied Slovin’s formula. The minimum re-

spondent required is 400 respondents. See Table 1.

2.5 Social Media

The ubiquitous social media has captured the atten-

tion of the learners. In this sense, the engagement of

the function and the attachment of the features also

attract the learners’ potential in exploring the util-

ity. In this spectrum, interaction and communication

have progressed over time and platform. In this area,

it integrates collaborative and collective preference.

Arguably, Faizi stated that social media embraces a

Analysis of the Student Background and Social Inﬂuence for Social Media-based Learning

185

myriad of tools that amalgamate technology, social

interaction and content creation (Faizi et al., 2013).

With this in mind, social media informs the learn-

ers of the two effect on learning. Firstly, it allows

learners to select appropriate media platforms. It en-

hances the learners’ preference to devise the learn-

ing plan(Deaton, 2015). On the other hand, global

access on the data and information to social media

emerges signiﬁcant engagement that decreased the

performance. Lahiri and Moseley listed the beneﬁt

and limitations of social media(Lahiri and Moseley,

2015) in Table 2.

Table 2: Beneﬁts and Limitations.

Beneﬁt Limitations

1. Social media en-

courages collaborative

learning

1. Making a safe com-

munity presence is a

challenge. Use and

access to social media

when used in school

work must be moni-

tored closely by the in-

structor.

2. Social media en-

ables the modelling of

behaviour

2. Social media can

pose as a distraction

for the learners and

shift the focus from

learning to other stuff

on the web.

3. Social Media moti-

vates the learner to be-

come active creators of

content and more par-

ticipation

3. Social media can

easily become a tool

for cyberbullying and

other forms of cyber-

crimes. Instructors

need to be vigilant of

any such possibilities

and address civil and

respectful cyber be-

haviour.

4. Social media pro-

motes the building of

learning communities

and foster productive

discussions and shar-

ing of knowledge and

information.

4. Use of social me-

dia for communication

might be a discourag-

ing factor for face to

face communication or

human interaction

5. Social media can

be used by instructors

to enhance student en-

gagement

6. Social media

can be used to im-

prove communication

among learners and

instructors

7. Alumni group can

connect and grow with

social media

CONRIST 2019 - International Conferences on Information System and Technology

186

3 RESULT AND DISCUSSION

In this segment, the research applied validity and reli-

ability test.

3.1 Validity Test Result

Table 3 portrays the detail of the validity test result.

Validity test is performed by comparing the Corrected

item-total Correlation score with Pearson r Table, and

the Pearson r Table value is 0.097824 (N=400, 0.05).

It reﬂects that if the CI-TC Score is greater than

0.097824, than the result is valid and not valid if the

CI-TC is lower than 0.097824.

Table 3: Validity Test

No Validity Result Test

Description CI-TC

Score

Status

1 D6 0.212 Valid

2 Friends inﬂuence me

to use social media to

improve academic per-

formance (SI1)

0.711 Valid

3 The Family inﬂuence

me to use social media

to improve academic

performance (SI2)

0.723 Valid

4 Friends think that I

have to use social me-

dia to learn (SI3)

0.720 Valid

5 The campus environ-

ment encouraged me

to use the smartphone

to complete my as-

signment (SI4)

0.732 Valid

6 The campus environ-

ment provides facili-

ties and allows to use

of social media in lec-

tures (SI5)

0.492 Valid

7 Lecture activities al-

low me to use social

media to ﬁnd informa-

tion (SI6)

0.565 Valid

8 Families recommend

using smartphones for

learning (SI7)

0.598 Valid

9 Friends recommend

using a smartphone

for learning (SI8)

0.715 Valid

3.2 Reliability Test Result

Following validity test results valid, the process con-

tinues with the reliability test to ensure the con-

sistency of data. The consistency of data will be

measured by checking the Cronbach’s Alpha if item

deleted or Cronbach Alpha score. If the Cronbach Al-

pha score is greater than 0.6, data is considered con-

sistent (UCLA, 2019). Table 4 shows the detail of the

data reliability test.

Table 4: Reliability Test

No Reliability Result Test

Description Score Status

1 D7 0.890 OK

2 SI1 0.844 OK

3 SI2 0.842 OK

4 SI3 0.842 OK

5 SI4 0.842 OK

6 SI5 0.864 OK

7 SI6 0.859 OK

8 SI7 0.855 OK

9 SI8 0.844 OK

Analysis of the Student Background and Social Inﬂuence for Social Media-based Learning

187

3.3 Bivariate Correlation Result

Table 5: Bivariate Result

D1 D2 D3 D4 D5 D6

SI1 -

.182**

0.000

.136**

0.000

.100*0

.034

NC -

.131**

0.006

.229**

0.000

H0 Reject Reject Reject Accept Reject Reject

H1 Accept Accept Accept Reject Accept Accept

SI2 -

.244**

0.000

.118*0

.013

NR -

0.01

.154**

NR .166**

0.000

H0 Reject Reject Accept Reject Accept Reject

H1 Accept Accept Reject Accept Reject Accept

SI3 -

.172**

0.000

NR 0.096*

0.043

.120*

0.011

.095*

0.044

.187**

0.000

H0 Reject Accept Reject Reject Reject Reject

H1 Accept Reject Accept Accept Accept Accept

SI4 NR NR NR NR NR .201**

0.000

H0 Accept Accept Accept Accept Accept Reject

H1 Reject Reject Reject Reject Reject Accept

SI5 NR NR -

.107*

0.024

NR NR .109*

0.022

H0 Accept Accept Reject Accept Accept Reject

H1 Reject Reject Accept Reject Reject Accept

SI6 NR NR NR -

.110

0.020

NR .215**

0.000

H0 Accept Accept Accept Reject Accept Reject

H1 Reject Reject Reject Accept Reject Accept

SI7 -

.136**

0.004

NR .099*

0.037

.114*

0.016

NR NR

H0 Reject Accept Reject Reject Accept Accept

H1 Accept Reject Accept Accept Reject Reject

SI8 NR NR NR -

.094*

0.047

NR .132**

0.005

H0 Accept Accept Accept Reject Accept Reject

H1 Reject Reject Reject Accept Reject Accept

After the result of validity and reliability test valid

and consistent, the following process performed Bi-

variate Correlation calculation. As the backdrop, the

process will produce a Pearson Correlation (r) score

and the indicator sign. The relationship between fac-

tors is gained by seeing the indicator sign. If the in-

dicator signs are lower than 0.05, it means there is

a relationship between factor. Meanwhile, there is

no relationship between factors if the indicator sign

is greater than 0.05. The hypothesis result described

that there is a relationship if H0 is rejected and H1

is accepted; no relationship if H0 is accepted and H1

is rejected. Table 5 shows the detail of the Bivariate

Correlation and hypothesis result.

Explanation of the Bivariate correlation result is

elaborated as follow. The obtained factors have a re-

lationship

Grade point (D1) has a negative correlation with

”friends inﬂuence me to use social media to im-

prove academic performance” (SI1). It means that the

greater inﬂuence from friends to use social media to

improve academic performance, the lower grade point

is gained. Table 6 informed the level of relationship

strength.

Grade point (D1) has a negative relationship with

”family inﬂuence me to use social media to improve

academic performance” (SI2). It indicates that the

greater inﬂuence from family inﬂuence to use social

media to improve academic performance, the lower

grade point is received.

Grade point (D1) has a negative relationship with

”friends think that I must use social media to learn”

(SI3). It reveals that the greater inﬂuence from friend

think that I have to use social media to learn, the lower

grade point is acquired.

Grade point (D1) has a negative relationship with

”lecture activities allow me to use social media to ﬁnd

information” (SI6). It signiﬁes that the greater inﬂu-

ence from lecture activities allow me to use social me-

dia to ﬁnd information (SI6), the lower grade point is

gained.

Gender (D2) has a relationship with ”friends in-

ﬂuence me to use social media to improve academic

performance” (SI1). It directs that the male has more

inﬂuence to use social media to improve academic

performance. On the other side, the female has less

inﬂuence to use social media to improve academic

performance.

Gender (D2) has a relationship with ”family in-

ﬂuence me to use social media to improve academic

performance” (SI2). It implies that male has more

family inﬂuence to use social media to improve aca-

demic performance, but the female has less family in-

ﬂuence to use social media to improve academic per-

formance.

Strata (D3) has a relationship with ”friends inﬂu-

ence me to use social media to improve academic per-

formance” (SI1). It suggests that the higher strata

have a stronger inﬂuence on the student to use social

media and improve academic performance. However,

the lower strata have less inﬂuence to use social me-

dia to improve academic performance. Strata(D3) has

a relationship with ”friends think that I must use so-

CONRIST 2019 - International Conferences on Information System and Technology

188

cial media to study” (SI3). It describes that the higher

strata have more inﬂuence on using social media to

study; however, the lower strata have less inﬂuence

on the necessity of using social media to study.

Strata (D3) has a negative relationship with ”the

campus environment provides facilities and allows to

use of social media in lectures (SI5). It means that

the higher strata have less inﬂuence for a campus en-

vironment that provides facilities and allows the stu-

dent to use social media in lectures. However, the

lower strata have more inﬂuence on the campus envi-

ronment in providing facilities and allowing the stu-

dent to use social media in lectures.

Strata (D3) has a relationship with ”families rec-

ommend using smartphones for learning ”(SI7). It

stated that the higher strata have more inﬂuence that

families recommend using smartphones for learning.

However, the lower strata have less inﬂuence that

families recommend using a smartphone for learning.

Semester (D4) has a negative relationship with

”family inﬂuence me to use social media to improve

academic performance” (SI2). It leads that the lower

semester has more inﬂuence on the family to use

social media in improving academic performance.

However, the higher semester has less inﬂuence on

the family to use social media in improving academic

performance.

Semester (D4) has a negative relationship with

”friends think that I must use social media to learn”

(SI3). It means that the higher semester has less inﬂu-

ence on ”friends think that I must use social media to

learn”. However, the lower semester has more inﬂu-

ence on ”.

Semester (D4) has a negative relationship with

”lecture activities allow me to use social media to ﬁnd

information” (SI6). It means that the higher semester

has less inﬂuence to ”lecture activities allow to use so-

cial media to ﬁnd information”. However, the lower

semester has more inﬂuence to ”lecture activities al-

low to use social media to ﬁnd information”.

Semester (D4) has a negative relationship with

”families recommend using smartphones for learn-

ing” (SI7). It means the higher semester have less

family inﬂuence to recommend using smartphones for

learning. However, the lower semester has more fam-

ily inﬂuence to recommend using smartphones for

learning.

Semester (D4) has a negative relationship with

”friends recommend using a smartphone for learning”

(SI8). It means that the higher semester has less friend

recommend using a smartphone for learning. How-

ever, the lower semester has more friend recommend

using a smartphone for learning.

Age (D5) has a negative relationship with ”friends

inﬂuence me to use social media to improve academic

performance” (SI1). It means that the older age has

less friend inﬂuence on using social media to improve

academic performance. However, the younger age

has more friend inﬂuence on using social media to

improve academic performance.

Age (D5) has a negative relationship with ”friends

think that I must use social media to learn ”(SI3). It

means that the younger age has more friend inﬂuence

on using social media to learn. However, the older

age has less friend inﬂuence on using social media to

learn.

Time spent on social media (D6) has a relation-

ship with ”friends inﬂuence me to use social media to

improve academic performance ”(SI1). It means that

the longer time spent on social media, the more friend

inﬂuences a student on using social media to improve

academic performance and vice versa.

Time spent on social media (D6) has a relation-

ship with ”family inﬂuence me to use social media to

improve academic performance ”(SI2). It means that

the longer time spent on social media has more fam-

ily inﬂuence on using social media to improve aca-

demic performance. However, the shorter time spent

on social media has less family inﬂuence to use social

media to improve academic performance.

Time spent on social media (D6) has a relation-

ship with ”friends think that I must use social media

to learn” (SI3). It indicates that the longer time spent

on social media, it has more inﬂuence on a friend that

think I must use social media to learn.

However, the shorter time spent on social media,

it has less inﬂuence on a friend that think I must use

social media to learn.

Time spent on social media (D6) has a relation-

ship with ”the campus environment that encouraged

me to use the smartphone to complete my assign-

ment” (SI4). It reﬂects that the longer time spent

on social media has more inﬂuence on-campus en-

vironment that encourages the student on using the

smartphone to complete the assignment. However,

the shorter time spent on social media, it has less in-

ﬂuence on the campus environment that encourages

the student on using the smartphone to complete the

assignment.

Time spent on social media (D6) has a relationship

with ”the campus environment that provides facilities

and allows to use of social media in lectures ”(SI5).

In this line, the longer time spent on social media has

more inﬂuence on-campus environment that provides

facilities and allows the student to use of social media

in lectures. Meanwhile, the shorter time spent on so-

cial media has less inﬂuence on-campus environment

provides facilities and allows the student to use of so-

Analysis of the Student Background and Social Inﬂuence for Social Media-based Learning

189

cial media in lectures.

Time spent on social media (D6) has a relationship

with ”lecture activities allow me to use social media

to ﬁnd information” (SI6). It denotes that the longer

time spent on social media has more inﬂuence on”

lecture activities allow to use social media to ﬁnd in-

formation.” However, the shorter time spent for social

media has less impact on lecture activities allow to

use social media to ﬁnd information.

Time spent on social media (D6) has a relation-

ship with friends recommend using a smartphone for

learning (SI8). It means that the longer time spent

on social media has more inﬂuence on friends recom-

mend using a smartphone for learning.

However, the shorter time spent on social media

has less impact on friends recommend using a smart-

phone for learning

3.4 Strength Tension of the Relationship

Table 6: Strength Relationship

No Relation |r| |r|

Tension Strength

1 D1 – SI1 .182 0.033 Small 3.3%

2 D1 – SI2 .244 0.060 Small 6.0%

3 D1 – SI3 .172 0.030 Small 3.0%

4 D1 – SI7 .136 0.018 Small 1.8%

5 D2 – SI1 .136 0.018 Small 1.8%

6 D2 – SI2 .118 0.014 Small 1.4%

7 D3 – SI1 .100 0.01 Small 1.0%

8 D3 – SI3 .096 Not

De-

ﬁned

9 D3 – SI5 .107 0.011 Small 1.1%

10 D3 – SI7 .099 Not

De-

ﬁned

11 D4 – SI2 .154 0.024 Small 2.4%

12 D4 – SI3 .120 0.014 Small 1.4%

13 D4 – SI6 .110 0.012 Small 1.2%

14 D4 – SI7 .114 0.013 Small 1.3%

15 D4 – SI8 .094 Not

De-

ﬁned

16 D5 – SI1 .131 0.017 Small 1.7%

17 D5 – SI3 .095 Not

De-

ﬁned

18 D6 – SI1 .229 0.052 Small 5.2%

19 D6 – SI2 .166 0.028 Small 2.8%

20 D6 – SI3 .187 0.035 Small 3.5%

21 D6 – SI4 .201 0.040 Small 4.0%

22 D6 – SI5 .109 0.012 Small 1.2%

23 D6 – SI6 .215 0.046 Small 4.6%

24 D6 – SI8 .132 0.017 Small 1.7%

The strength tension of a relationship can be mea-

sured by checking the absolute (r) of the Pearson cor-

relation. At the same point, the square of absolute (r)

of Pearson correlation will show how signiﬁcant the

percentage of inﬂuence among a factor with another

one. Table 6 presented the detail of the inﬂuence of a

factor with another factor.

The explanation of table V elaborates the follow-

ing information:

Grade point (D1) will inﬂuence 3.3% to the friend

inﬂuence to use of social media to improve academic

performance (SI1), it means the friend inﬂuence to

use social media to learn inﬂuence 3.3% to get higher

university student grade point.

Grade point (D1) will inﬂuence 6.0% to the family

inﬂuence to use of social media to improve academic

performance (SI2), it means the family inﬂuence to

use social media for learning will inﬂuence 6.0% to

get higher university student grade point.

Grade point (D1) will inﬂuence 3.0% to friends

think that a university student must use social media

to learn (SI3). It means the friend think that a uni-

versity student must use social media to learn will in-

ﬂuence 3.0% to get higher university student’s grade

point.

Grade point (D1) will inﬂuence 1.8% to lecture

activities allow me to use social media to ﬁnd infor-

mation (SI6). It means the lecture activities that will

enable university student to use social media to ﬁnd

information will inﬂuence 1.8% to get higher univer-

sity student’s grade point.

Gender (D2) will inﬂuence 1.8% to friends inﬂu-

ence me to use social media to improve academic per-

formance (SI1).

Gender (D2) will inﬂuence 1.4% to family inﬂu-

ence me to use social media to improve academic per-

formance (SI2). It means the family inﬂuence to use

social media to improve academic performance will

inﬂuence 1.4% for male university student.

Strata (D3) will inﬂuence 1.0% to ”friends in-

ﬂuence me to use social media to improve aca-

demic performance” (SI1), it means the friend inﬂu-

ence to use social media to improve academic per-

formance will inﬂuence 1.0% to the higher strata

(Bachelor/Master/Ph.D.) rather than for senior high,

diploma.

Strata (D3) will inﬂuence 1.1% to ”the campus en-

CONRIST 2019 - International Conferences on Information System and Technology

190

vironment provides facilities and allows to use of so-

cial media in lectures” (SI5). It means the campus

environment provided facilities and allow to use so-

cial media in lecturing will inﬂuence 1.1higher strata

(Bachelor/Master/Ph.D.) rather than for senior high,

diploma.

Semester (D4) will inﬂuence 2.4% to ”use social

media to improve academic performance” (SI2). It

means the social media used to improve academic

performance will affect 2.4% to the higher semester

university student.

Semester (D4) will inﬂuence 1.4% to ”friends

think that I must use social media to learn” (SI3). It

means the friend think that I must use social media to

learn will inﬂuence 1.4% to the higher semester uni-

versity student.

Semester (D4) will inﬂuence 1.2% to ”lecture ac-

tivities allow me to use social media to ﬁnd informa-

tion” (SI6). It means the lecture activities that allow

student to use social media to ﬁnd information will in-

ﬂuence 1.2% to higher semester of university student.

Semester (D4) will inﬂuence 1.3% to ”families

recommend using smartphones for learning” (SI7). It

means the families recommend using smartphone for

learning will inﬂuence 1.3% for higher semester of

university student.

Age (D5) will inﬂuence 1.7% to ”friends inﬂuence

me to use social media to improve academic perfor-

mance” (SI1).

Time spent on social media (D6) will inﬂuence

5.2% to ”friends inﬂuence me to use social media to

improve academic performance” (SI1).

Time spent for social media (D6) will inﬂuence

2.6% to ”family inﬂuence me to use social media to

improve academic performance” (SI2). Time spent

on social media (D6) will inﬂuence 3.5% to ”friends

think that I must use social media to learn” (SI3).

Time spent on social media (D6) will inﬂuence

4.0% to ”campus environment encouraged me to use

the smartphone to complete my assignment” (SI4).

Time spent on social media (D6) will inﬂuence 1.5%

to ”the campus environment provides facilities and al-

lows to use of social media in lectures” (SI5). Time

spent on social media (D6) will inﬂuence 4.6% to

”lecture activities allow me to use social media to ﬁnd

information” (SI6).

Time spent on social media (D6) will inﬂuence

1.7% to ”friends recommend using a smartphone for

learning” (SI8).

4 CONCLUSIONS

This study addressed the hypotheses of university stu-

dent background and social inﬂuence of social me-

dia learning-based. The in-depth examination has re-

vealed that the six-university student’s background

and grade point has a relationship and inﬂuence on

social inﬂuence factor. In this corridor, gender in-

ﬂuences social inﬂuence; strata inﬂuence social in-

ﬂuence; the semester has an inﬂuence on social in-

ﬂuence, age has an inﬂuence on social inﬂuence and

time spent to use social media also has an inﬂuence

on social inﬂuence eventually. Taking into account all

these facts, the researchers strongly believe that social

media plays an important role in promoting university

student learning at the end.

This study required future research to elaborate

another related factor such as ease of use factor, per-

ceive usefulness factor, and risk factor.

ACKNOWLEDGEMENTS

Thanks to Dhyaksa Abi Satrio, Rizki Adha and Irfan

Nurfauzi who contribute to collect the respondent for

this paper and this paper is part of the ﬁnal project of

Abi, Rizki, and Irfan to get their bachelor’s degree.

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