The Application of Planned Behavior Theory to Consultant PT. X

Anasyiah Nurhamidah

Universitas Negeri Surabaya, Surabaya, Indonesia

Keywords: Entrepreneurial behavior, subjective norms, behavioral control, consultant.

Abstract: This research aims to understand, to test, and to analyze the direct effect entrepreneurial attitude toward

entrepreneurial behavior, subjective norms, and behavioral control to entrepreneurial intention of PT. X’s

consultant. The sample used in this study were 75 consultant at PT. X. The analysis in this study using PLS.

There are significant positive relationship between entrepreneurial attitude toward entrepreneurial behavior,

positive relationship between behavioral control toward entrepreneurial intention, insignificance relationship

between subjective norms toward entrepreneurial intention, positive significance relationship between

entrepreneurial intention toward entrepreneurial behavior, positive significance relationship between

entrepreneurial attitude toward entrepreneurial behavior, and positive significant relationship between

behavioral control toward entrepreneurial behavior of consultant PT. X.

1 INTRODUCTION

1.1 Introduction

The high unemployment rate is the empirical

phenomenon that occurs in Indonesia. The limited

field of work available has increased the number of

unemployed. In Indonesia, according to Central

Bureau of Statistics (BPS), the number of

unemployed workforce up to February 2013 was

5.92%, a further decline of 6.14% in August 2012.

The number of unemployed until February 2013 can

be estimated at 7.17 million people compared to

August 2012 which reached 7.24 million people.

While in terms of work, still contributed by the

private sector, trade, community services, and

industrial sectors that became the largest contributor

of employment in Indonesia.

Faced with such a situation, it is necessary to find

a more creative path and change the approach from

becoming a scholar looking for a job to become a

scholar who can create self-employment (self-

employment). At least college graduates have the

characteristics of entrepreneurial spirit, because the

world of entrepreneurship is a rational choice and

relevant at least in the current national economic

conditions. As many as 5.04% of university graduates

have a desire to become new entrepreneurs, meaning

they are still hesitant to become entrepreneurs. These

doubts can be seen from the predictors, namely; 1)

attitude towards entrepreneurship, students are still

not sure of the results to be obtained in

entrepreneurship. 2) Subjective norms, i.e. the

students perceive that the people around them are less

supportive to become entrepreneurs so that the

motivation to become entrepreneurs is also weak. 3)

Control of perceived behavior, namely the

understanding of things that facilitate or inhibit if you

want to run a business is still weak (wijaya, 2008).

According to Ajzen (1991) in the theory of

Planned behavior theory that perceived behavioral

control applies as a final analysis that determines a

person will decide to act or not to run a behavior

(including entrepreneurial behavior). Being an

entrepreneur is a brave decision, because the job

becomes entrepreneurial dealing with the

consequences of uncertain outcomes. Ajzen (1991)

explains that a person's decision is preceded by an

attitude toward the behavior that refers to the belief

and evaluation of the behavioral outcomes to be

undertaken; this subyektive norm refers to the

perceived social pressure to exercise behavior and

motivation to carry out the behavior; Perceived

behavior control refers to things that will be perceived

to be easier or will hamper if the behavior is

implemented, it is related to the experiences of the

past.

The decision to become an entrepreneur can be

seen from his intention or intention to become an

entrepreneur. Intention itself is a unanimous desire to

perform an action. (Dharmmesta, 1998) mentions

intention as a person's intention to perform an action.

Nurhamidah, A.

The Application of Planned Behavior Theory to Consultant PT. X.

In Proceedings of the 2nd International Conference on Economic Education and Entrepreneurship (ICEEE 2017), pages 83-91

ISBN: 978-989-758-308-7

Intention is a motivational factor that influences

behavior, which shows an indication of how strong a

business is doing to show the actual behavior of Ajzen

(1991). Intention plays a distinctive role in directing

action that is, connecting the deep considerations that

a person believes and desires with a particular action.

Based on the understanding as above then itensi can

be concluded as a decision to act or bring up a certain

behavior based on genuine.

1.2 Objective

The objective of this study is: a) To know, measure

and analyze the direct influence of entrepreneurship

attitude, subjective norms, and behavior control on

the intention of entrepreneurship consultant in PT. X,

b) To know the direct influence of the

entrepreneurship intent on the behavior of

entrepreneurship consultant in PT. X, and c) To know

the direct influence of the attitude of entrepreneurship

and behavioral control on the behavior of

entrepreneurship consultant in PT. X.

2 LITERATURE REVIEW

2.1 Entrepreneurial attitude

Murphy and Perck (in Alma, 2005) say that

entrepreneurial attitudes include capacity for hard

work, working with others (getting things done with

and through people), good looks, Confidence),

making decisions (makng decision), education

(collage education), ambition (drive) and batio

(communicate). Based on the understanding of

attitudes and entrepreneurship above, the attitude of

entrepreneur is the readiness of a person to respond

consistently to the six characteristics of

entrepreneurial behavior that include: confidence,

taskoriented and results, risk taking, leadership,

originality and oriented to the future that can be

measured direction And their intensity by showing

behaviors that reflect cognitive, affective, and

conative judgments.

2.2 Entrepreneurial intention

The intention of entrepreneurship can be interpreted

as a process of seeking information that can be used

to achieve the goal of forming a business (Katz and

Gartner, 1988). A person with an intention to start a

business will have better readiness and progress in the

business run than someone without the intention to

start a business. As stated by Krueger and Carsrud

(1993), the intention has proven to be the best

predictor of entrepreneurial behavior. Therefore, the

intentions can serve as a reasonable basic approach to

understanding who will become entrepreneurs (Choo

and Wong, 2006).

2.3 Entrepreneurial behavior

Behavior is a person's traits that are formed due to

daily habits. Entrepreneurial behavior is influenced

by internal and external factors. They are competency

/ ability, and incentive, while external factors include

the environment. Thus Attitudes and behavior can be

changed by self or by the existence of environmental

pressure / influence. The existence of influence from

within self and from outside of social environment

hence grow behavior of specific individual.

Entrepreneurial behavior is an individual action

that is indicated by the decision of entrepreneurship.

Entrepreneurship behavior is measured by the scale

of entrepreneurial behavior adapted from the

behavioral model of Azjen (2008) with real action

indicator has been running business, entrepreneurship

decisions, and revelation of existing business

development support.

2.4 Subjective norms

According to Kreitner and Kinicki (2001), subjective

norms are defined as acceptance of social pressure to

present a specific behavior. Furthermore, Fishbein

and Ajzen (1975) explained that "The Subjective

norm is the person's perception that most people who

are important to him think he should or should not

pemrform the behavior in question". They define if

subjective norms are individual perceptions related to

most of the people who are important to themselves

expecting individuals to do or not to perform certain

behaviors, people who are important to him then be

used as a reference or benchmark to direct behavior.

In Theory of Planned Behavior, subjective norms

are defined as individual perceptions about whether

the person is important to the individual thinking the

behavior should be done. The contribution of the

opinion of each given reference is weighted with the

motivation that an individual must abide by the wish

of that reference.

2.5 Perceived behavioral control

Ajzen (1988) defines Perceived Behavioral Control

(PBC) as follows:” this factor refresh to the perceived

ease or difficulty peforming the behavior and it

ICEEE 2017 - 2nd International Conference on Economic Education and Entrepreneurship

assume to reflect past experience as well as

anticipates impediment and obstacles”, This factor

illustrates the individual's perception of whether or

not the individual is capable of behavior and is

assumed to be a reflection of previous experience and

anticipated obstacles.

In Ajzen (2005), the thing to remember about the

theory of planned behavior is not directly with the

number of individual controls affecting the situation,

it considers the possible effects of Perceived

Behavioral Control in achieving the end of behavior.

3 METHODS

3.1 Research Approach

This research uses quantitative approach. This

research focuses on hypothesis testing with statistical

methods analysis tool and produces generalizable

conclusions. The assumptions used in this study are

in the form of measurable variables and useful for

explaining mutual relationships (causality) beginning

with hypotheses and theories.

3.2 Identify Variables

A variable is something whose value varies, changes

according to time or differs by place or element

(Supranto and Limakrisna, 2009: 12). This study uses

three types of variables, is: 1) Independent Variables.

The independent variable is a variable that influences

the dependent variable positively or negatively

(Sekaran, 2003: 89). The independent variable (X) in

this research is entrepreneurship attitude, subjective

norm and behavior control. 2) Dependent Variables.

The dependent variable is a predicted variable

through independent variables (Sekaran, 2003: 88).

Dependent variable (Y) in this research is

entrepreneurship behavior. 3) Intervening Variables.

The intervening variable is the variable that emerges

as an operational function of the independent variable

in various situations and helps to conceptualize and

explain the effect of the independent variable on the

dependent variable (Sekaran, 2003: 94). Intervening

variable (Z) in this research is Intensi

entrepreneurship.

3.3 Operational Definition of Variables

The operational definition is to define operational

variables based on observed characteristics that

enable the researcher to observe or accurately

measure an object or phenomenon (Hidayat, 2007).

The operational definition of the variables in this

study are as follows:

3.3.1 Entrepreneurial attitude

The attitude of entrepreneurship is the tendency to

react affectively in response to the risks that will be

deal with in a business. Entrepreneurship attitude is

measured by the scale of entrepreneurship attitude

(Gadaam, 2008) with indicators: 1) interested in

business opportunities, 2) a positive view of business

failure, and 3) Like to take on business risks.

3.3.2 Subjective norms

Subjective norm is individual belief to obey the

direction or suggestion of people around to participate

in entrepreneurship activity. Subjective norm is

measured by subjective norm scale (Ramayah and

Aaron, 2005) with indicator: 1) Belief of the family

role in starting a business, 2) Belief of support in the

business of the person who is considered important,

and 3) Belief of friend support in business.

3.3.3 Behavioral control

Behavioral control is the basis for the formation of

perceived behavioral controls on the strength of the

better or new factors (Gelderen, 2008) with

indicators: 1) Perseverance or persistence, 2)

Readiness of entrepreneurship, 3) Selfefficacy for

entrepreneurship, and 4) Creativity.

3.3.4 Entrepreneurial intention

Entrepreneurial intention is the tendency of

individual desire to do entrepreneurial action by

creating new products through business opportunities

and risk taking. The intention of entrepreneurship is

measured by entrepreneurial intention scale

(Ramayah and Harun, 2005) with indicators: 1)

choose the path of business rather than work on

others, 2) choose a career as an entrepreneur, and 3)

Planning to start a business.

3.3.5 Entrepreneurial behavior

Entrepreneurial is an individual action that is

indicated by the decision of entrepreneurship.

Entrepreneurship behavior is measured by the scale

of entrepreneurial behavior adapted from the

behavioral model of Azjen (2008) with indicators: 1)

the real action has been running the business, 2)

The Application of Planned Behavior Theory to Consultant PT. X

decision of entrepreneurship, and 3) statement of

existing business development support.

Measurement of variables Entrepreneurship

attitudes, subjective norms, control of

entrepreneurship behavior, and entrepreneurship

intentions based on respondents' answers or ratings

on the statements in the questionnaire whose value is

determined on a Likert scale, with the following

assessment: 1) the value of 1 represents a strongly

disagreeable answer, 2) The value of 2 represents the

disapproving answer, 3) The value of 3 represents a

neutral answer, 4) The value of 4 represents the

answer agreed, and 5) The value of 5 represents the

answer strongly agree.

3.4 Types and Data Sources

This research uses the types and sources of data as

follows:1) The data used in this study is primary data,

is the source of research data obtained directly from

the object (Supranto and Limakrisna, 2009: 3). The

data will be used to see the effect of entrepreneurship

attitude, subjective norm, and behavior control have

influence to entrepreneurship behavior, with intent

entrepreneurship as intervening variable. Primary

data to find out result of filling questioner by

consultant at PT. X that meets the criteria as the

research respondents. 2) Secondary data is the source

of research data obtained in the form of publication

(Supranto and Limakrisna, 2009: 3). Secondary data

is obtained from various sources and used to support

the necessary information related to research writing.

Sources of secondary data used in the form of national

and international journals, literature books on human

resources that support the theories in this study, as

well as company documents owned by PT. X.

3.5 Data Collection Procedures

To collect the required data in this research,

conducted several stages, is: 1) Preliminary survey,

by asking the company profile in the personnel

department, especially regarding the total of

consultants in PT. X, 2) Distribute questionnaires to

respondents, and 3) Collect questionnaires that have

been filled by respondents to then processed and

analyzed.

3.5.1 Determination of Population and

Sample Techniques

The techniques of population determination and

sample in this study are as follows: 1) in this research,

which is included in the population is all consultants

in PT. X. And 2) in this research, sample

determination was done by using purposive sampling

technique which included in nonprobability

sampling. Purposive sampling is used to obtain

specific information from specific target respondents,

where the target respondents are adjusted to the

characteristics specified by the researcher (Sekaran,

2003: 277). In connection with the existence of

entrepreneurship attitude variable, the criteria

assigned to the respondent in this research is the

permanent consultant who has joined in PT. X with a

minimum join period of one year. Furthermore, the

number of respondents taken for this study as many

as 75 consultants at PT. X. Questionnaires can be

given to the consultant in person.

3.6 Technical Analysis and Reliability

3.6.1 Data Processing Technique

This research uses technical analysis of Partial Least

Square (PLS). It is based on the reason that the test in

this study is done simultaneously and there are

variables that have formative construct dimension

(Ghozali, 2008: 22).

Jogiyanto (2009: 57) the path analysis model of

all latent variables in the PLS consists of two sets of

relationships: 1) Inner Model, describes the

relationship between latent variables based on

substantive theory. Inner model is a relationship to

test the influence between research variables. by

getting: a) The value of RSquare or coefficient of

determination is a value that describes the size of

model goodness, or the effect of the influence of

independent variables on the bound variables and the

value of Q2 or the relevance of the prediction. If the

value of Q2 is greater than zero and close to 1, It

provides evidence that the model has predictive

relevance but if it is obtained Q2 below zero then it is

proven that the model has no predictive relevance. b)

Significance of causality relationships, by obtaining

tstatistics that ultimately used to answer the

hypothesis. 2) Outer Model or weight, defines how

each indicator relates to its latent variable. The

indicator is said to be part of the constraint if the

model outer value is more than 0.5.

In processing Partial Least Square (PLS) in two

stages, is: 1) the first stage is to conduct a

measurement model test. In stage is essentially testing

the validity and reliability of the constituents of each

each indicator whether it is part of the constants or

research variables. The reading of validity and

reliability of the constants is from the outer weight or

outer model. The indicator is said to be valid and

ICEEE 2017 - 2nd International Conference on Economic Education and Entrepreneurship

reliable if it has a loading factor value greater than or

equal to 0.5. 2) The second stage is to perform

structural testing model. In this stage aims to

determine whether there is influence between

variables. Testing is done by using t test. The research

hypothesis is accepted if t count value> t table.

3.6.2 Validity Test

Validity indicates the extent to which accuracy and

accuracy of a measuring instrument in giving the

measuring function, or provide a measuring result in

accordance with the purpose of the measurement

(Jogiyanto, 2011: 70). At the inner evaluation stage

of the model, PLS examines construct validity

consisting of convergent validity and discriminant

validity. The validity of the construct shows how well

the results of the use of a measurement in defining a

construct (Jogiyanto, 2011: 70). Convergent validity

and discriminant validity are measured using the

following conditions: 1) Convergent validity is

related to the principle that the measurements or

instruments of a construct must have a high

correlation (Jogiyanto, 2011: 70). Convergent

validity measurement is based on the value of factor

loading or outer loading that must reach a value

greater than 0.5, meaning that there must be at least

50% of the data diversity of the variables to be

measured can be explained by the question items. If

the outer loading is smaller than 0.5, then the item is

declared invalid and must be reduced. Outer loading

is a value that describes the proportion of variable

data diversity that can be explained by question items.

2) Discriminant validity is related to the principle that

different construct measure or instruments must have

a low correlation (Jogiyanto, 2011: 71). The

measurement of discriminant validity is based on the

value of cross loading. An item is said to meet the

discriminant validity if the value of cross loading

items to the variable is the largest compared to other.

3.6.3 Reliability Test

PLS performs a reliability test to measure the

consistency of the measuring tool of a construct.

According to Sekaran (2003: 203), the reliability of a

measurement indicates the extent to which such

measurements can ensure the stability and

consistency of measurement. In other words, the

reliability of an instrument can be seen through the

results of accurate and stable measurements over

time.

Test reliability in PLS can use two methods, that

is Cronbach's alpha and composite reliability.

Cronbach's alpha measures the lower limit of the

reliability value of a measuring instrument, while

composite reliability measures the true value of the

reliability of the measuring instrument (Jogiyanto,

2011: 72). a measuring instrument is said to be

reliable when the value of composite reliability is

greater than 0.7.

In this test aims to determine the extent to which

the measurements used can give the same results if

remeasured against the same subject.

4 RESULTS AND DISCUSSION

4.1 Validity test

Testing validity in PLS consists of two parts, namely

convergent validity and discriminant validity: a)

Convergent Validity is the first evaluation of the outer

model is convergent validity. Measuring convergent

validity is done by looking at the value of each outer

loading. An indicator is said to meet convergent

validity if it has an outer loading value greater than

0.5. The following is presented a structural model to

determine the value of outer loading of each indicator

on the research variables on figure 1:

Figure 1: Structural Model of PLS

The Application of Planned Behavior Theory to Consultant PT. X

Based on the structural model above, it can be

seen that all indicators have outer loading value above

0.5, so that the concept of convergent validity has

been fulfilled, or in other words, each indicator in

each variable has good measurement capability, b)

Discriminate Validity is the second evaluation of the

outer model is discriminant validity. Measure

discriminant validity is done by using the value of

cross loading. An indicator is said to meet the

discriminant validity if the value of cross loading

indicator to the variable is the largest when compared

to other variables. Here is presented table of cross

loading more:

Table 1: Cross Loading Value

Indicator

Variabel

Entrepreneurial -

Intention

Behavioral Control

Subjective -Norms

Entrepreneurial

Behavior

Entrepreneuri

al Attitude

X1.1

0.298

0.337

0.351

0.392

0.594

X1.2

0.215

0.382

0.273

0.361

0.559

X1.3

0.146

0.300

0.237

0.307

0.589

X1.4

0.420

0.494

0.317

0.550

0.735

X1.5

0.459

0.386

0.261

0.480

0.769

X1.6

0.480

0.353

0.321

0.563

0.766

X2.1

0.152

0.354

0.578

0.256

0.174

X2.2

0.439

0.520

0.829

0.646

0.464

X2.3

0.145

0.178

0.601

0.316

0.154

X2.4

0.180

0.225

0.674

0.386

0.263

X2.5

0.143

0.264

0.689

0.432

0.191

X2.6

0.232

0.240

0.665

0.337

0.289

X3.1

0.446

0.763

0.421

0.534

0.336

X3.2

0.505

0.804

0.283

0.541

0.449

X3.3

0.420

0.722

0.335

0.398

0.306

X3.4

0.479

0.781

0.387

0.526

0.546

X3.5

0.450

0.720

0.460

0.542

0.507

X3.6

0.554

0.778

0.462

0.595

0.526

X3.7

0.520

0.736

0.337

0.447

0.314

X3.8

0.482

0.681

0.183

0.385

0.300

Y1.1

0.470

0.437

0.421

0.644

0.346

Y1.2

0.323

0.336

0.439

0.633

0.512

Y1.3

0.434

0.458

0.285

0.683

0.530

Y1.4

0.554

0.557

0.437

0.748

0.611

Y1.5

0.423

0.496

0.447

0.726

0.384

Y1.6

0.317

0.344

0.507

0.616

0.244

Y1.7

0.261

0.422

0.471

0.569

0.402

Z1.1

0.777

0.340

0.235

0.307

0.385

Z1.2

0.807

0.514

0.329

0.549

0.533

Z1.3

0.871

0.615

0.349

0.564

0.455

Z1.4

0.769

0.521

0.319

0.470

0.372

Z1.5

0.693

0.470

0.185

0.446

0.314

Z1.6

0.775

0.516

0.318

0.495

0.428

Based on the value of cross loading, it can be seen

that all the indicators that make up each variable in

this study (the value in bold) has met the discriminant

validity because it has the largest cross load value for

the variables it formed and not on other variables.

From this result, the concept of discriminant validity

has been fulfilled.

4.2 Reability test

The end result on the outer model is the composite

reliability. Composite reliability. Instrument

reliability on a variable. A variable states satisfy

composite reliability if it has composite reliability

value greater than 0.7. Here is the value of the

composite reliability of each variable:

Table 2: Composite Reliability

Variabel

Composite Reliability

Entrepreneurial Intention

0.905

Behavioral Control

0.911

Subjective Norms

0.834

Entrepreneurial Behavior

0.844

Entrepreneurial Attitude

0.831

ICEEE 2017 - 2nd International Conference on Economic Education and Entrepreneurship

Research value of more than 0.7. Thus it can be

concluded that each variable has met the concept of

expected reliability.

4.3 Inner Model Evaluation

The inner evaluation section of the model includes

rsquare assessment and causality testing. a) RSquare

value: The first evaluation of the inner model is seen

from the RSquare value or the coefficient of

determination. Based on data processing with PLS,

the resulting RSquare value as follows:

Table 3: Nilai RSquare

Variabel

R Square

Intensi Berwirausaha

0.463

Entrepreneurial attitude

0.603

The value of RSquare for entrepreneurship intention

is 0.463, meaning that the percentage of data diversity

in entrepreneurship intentional variable that can be

explained by entrepreneurship attitude variable,

subjective norm and behavior control is 46.3%. The

value of RSquare for entrepreneurial behavior is

0603, meaning that the percentage of data diversity in

entrepreneurship behavior variable can be explained

by entrepreneurship attitude variable,

entrepreneurship intention, and behavior control is

60.3%.

In the PLS model, the overall goodness of fit

assessment is known from the value of Q2 (predictive

relevance). The higher the QSquare, then the model

can be said to be more fit with the data. From Table

4.13 we can calculate the value of Q2 as follows:

The value of

Q2 = 1 - (1 - 0.463) x (1 - 0.603) = 0.787 ............. (1)

The calculation results show the value of Q2 of 0.787,

meaning that the magnitude of the research data that

can be explained by the structural model is 78.7%,

while the remaining 21.3% is explained by other

factors outside the structural model. Based on these

results, the structural model in the study can be said

to have goodness of fit good.

4.4 Discussion

Table 4: Path Coefficient and t-count

Effect

Relationship

CoefficientPath

Statistic

Information

Entrepreneurial

Attitude ->

entreprenurial

Intention

0.248

2.929

Significant

Subjective

Norms ->

Entrepreneurial

Intention

0.031

0.361

Unsignificant

Behavioral

Control ->

Entrepreneurial

Intention

0.493

4.998

Significant

Entrepreneurial

Intention ->

Entrepreneurial

Behavior

0.198

2.082

Significant

Entrepreneurial

Attitude ->

Entrepreneurial

Behavior

0.391

4.602

Significant

Behavioral

Control ->

Entrepreneurial

behavior

0.324

3.006

Significant

From table 4 can be structured model to prove the

research hypothesis as follows: 1) Effect of

Entrepreneurship Attitude → Intent of

Entrepreneurship Based on table 4:14 it can be seen

that the coefficient path of entrepreneurship attitudes

toward entrepreneurship intentions is 0.248 with

tstatistics of 2.929 greater than the value of ttable

1.96, it shows that there is a significant positive

influence between entrepreneurship attitudes towards

the intentions of entrepreneurship. That is, an increase

in the attitude of entrepreneurship will result in

increased intentions of entrepreneurship

significantly, 2) Influence of Subjective Norms →

Intent of Entrepreneurship. The value of path

coefficient of influence of subjective norm toward

entrepreneurship intention is equal to 0.031 with

tstatistic equal to 0361 smaller than ttable value 1.96,

it shows that there is positive influence but not

significant between subjective norm to intense

entrepreneurship, 3) The Influence of Behavior

Control → Intent of Entrepreneurship. The

coefficient of path influence of behavior control to

entrepreneurship intention is equal to 0.493 with

tstatistic equal to 4,998 which is bigger than ttable

value 1.96, it shows that there is significant positive

influence between behavior controls to

entrepreneurship intention. That is, an increase in

behavior control will result in a significantly

enhanced intention of entrepreneurship, 4) Effect of

The Application of Planned Behavior Theory to Consultant PT. X

Intensi Entrepreneurship → Entrepreneurship

Behavior. Path coefficient of entrepreneurship

intentional influence to entrepreneurship behavior is

0.198 with tstatistic equal to 2,082 which is bigger

than ttable value 1.96, it shows that there is significant

positive influence between entrepreneurship intent to

entrepreneurship behavior. That is, an increase in the

intention of entrepreneurship will result in the

improvement of entrepreneurship behavior

significantly, 5) Effect of Entrepreneurship Attitudes

→ Entrepreneurial Behavior. The coefficient of the

path of entrepreneurship attitudes toward

entrepreneurship behavior is 0.391 with tstatistics of

4,602 which is greater than the value of ttable 1.96, it

shows that there is a significant positive influence

between entrepreneurship attitudes towards

entrepreneurship behavior. That is, an increase in

entrepreneurship attitudes will result in an increase in

entrepreneurial behavior significantly, 6) Influence of

Behavioral Control → Entrepreneurial Behavior.

Path coefficient of influence of behavior control to

entrepreneurship behavior is equal to 0.324 with

tstatistic equal to 3,006 bigger than ttable value 1.96,

it shows that there is significant positive influence

between behavior controls to entrepreneurship

behavior. That is, an increase in behavior control will

result in a significant increase in entrepreneurial

behavior.

5 CONCLUSIONS

Based on the results of data management using Partial

Least Square (PLS) analysis, the following

conclusions can be drawn: 1) There is a significant

positive influence between entrepreneurship attitudes

towards the intention of entrepreneurship at the

consultant PT. X, 2) There is a positive but

insignificant influence between subjective norms on

the intention of entrepreneurship at the consultant PT.

X, 3) There is a significant positive influence between

the behavior control on the intention of

entrepreneurship at the consultant PT. X, 4) There is

a significant positive influence between the intention

of entrepreneurship on entrepreneurship behavior at

the consultant PT. X, 5) There is a significant positive

influence between entrepreneurship attitudes toward

entrepreneurship behavior at the consultant PT. X, 6)

There is a significant positive influence between

behavior control on entrepreneurship behavior at the

Consultant PT. X.

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The Application of Planned Behavior Theory to Consultant PT. X