JRSSEM 2022, Vol. 01, No. 10, 1562 – 1572

E-ISSN: 2807 - 6311, P-ISSN: 2807 - 6494

DOI : 10.36418/jrssem.v1i10.169 https://jrssem.publikasiindonesia.id/index.php/jrssem/index

THE INFLUENCE OF COMPENSATION, COMPENSATION

AND LEADERSHIP STYLE ON THE PRODUCTIVITY OF

MSME PARTNERS IN PT. PERKEBUNAN NUSANTARA III

MEDAN

Ruby April Motani Larosa

Valentino Arjun Surbakti

Leo Tarigan

Deni Faisal Mirza

1,2,3,4

Prima University of Indonesia

e-mail: ruby04larosa@gmail.com

, surbaktiarjuna@gmail.com

, tarsilleo16@gmail.com

denifm.ukmcenter@yahoo.com

*Correspondence: denifm.ukmce[email protected]m

Submitted: 29 April 2022, Revised: 06 May 2022, Accepted: 18 May 2022

Abstract. Establishing a business requires good competence in the field, compensation is also

needed as a reward for achieving work and also the leadership style must be good and can be used

as an example for colleagues. This study aims to determine whether there is an influence of

competence and leadership style on the productivity of MSME Partners at PT. Nusantara III

Plantation, Medan. The object of this research is entrepreneurs who are members of the UMKM

Partners at PT. Perkebunan Nusantara III Medan with a total sample of 96 respondents. The tool

used to analyze the data is by using SPSS IBM 26. The data collection technique used is by

distributing questionnaires to the respondents as much as the number of samples. Tests in this

study using multiple linear regression analysis. From the results of data analysis, it can be concluded

that competence, compensation and leadership style affect the productivity of MSME Partners at

PT. Nusantara III Plantation, Medan. When viewed from the coefficient of determination test, the

magnitude of the influence of competence, compensation and leadership style on MSME Partners

at PT. Nusantara III Medan's plantations are 37%.

Keywords: competence; compensation; leadership style; productivity.

Ruby April Motani Larosa, Valentino Arjun Surbakti, Leo Tarigan, Deni Faisal Mirza           
 
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DOI :  10.36418/jrssem.v1i10.169  https://jrssem.publikasiindonesia.id/index.php/jrssem/index 
INTRODUCTION 
 
PT. Perkebunan Nusantara III Medan is 
one of the state-run companies engaged in 
plantations.  This  company  has  MSME 
partners which include a group of people 
who  own  plantations.  MSMEs  who  are 
members of this company hope to get a lot 
of  help  in  the  form  of  knowledge  in 
gardening,  funds,  how  to  deal  with 
problems  found  in  plantations  and  so  on 
related to the plantations that MSMEs are 
currently living. Therefore, it is necessary to 
have  someone  who  is  able  to  lead  the 
company  well  and  direct  the  MSMEs  to 
move in a better direction. 
The things that a leader needs are good 
competencies which include several things 
such as  the  ability to  teach,  the  ability to 
lead and direct SMEs, expertise or skills in 
their  fields  and  other  things  related  to 
competencies that will support or help to 
promote SMEs. According to  (Chouhan & 
Srivastava,  2014),  "Competence  must  be 
possessed by everyone who is given a trust 
to occupy a position or field of work, which 
includes  abilities,  expertise,  skills  in 
completing  tasks  and  responsibilities". 
According  to  (Mangkunegara,  2011) 
competency indicators are: 
1.  Performance 
2.  Quality performance 
3.  Work motivation 
In addition,  compensation is also  very 
much  needed  by  MSMEs  or  people  who 
work  in  a  company.  Where  it  will  greatly 
encourage  or  spur  MSMEs  to  work 
enthusiastically  and  work  optimally  and 
give the best for their work because their 
work  is  given  an  award.  According  to 
(Zopiatis, 2010), "Compensation is a reward 
given to individuals who do their jobs well 
and get very good grades, and the rewards 
are  obtained  outside  of  salary  or  wages”. 
According  to  (Baig  et  al.,  2021)  some 
compensation indicators are: 
1.  Wages and 
2.  Intensive 
3.  Allowances 
The leadership style which is meant by 
a consistent pattern of behavior is played 
by the leader when influencing employees, 
in  order  to  encourage  and  encourage 
MSMEs to be enthusiastic and have good 
motivation and outlook. to a job. According 
to  (Noviyudin  &  Hidayat,  2018), 
"Leadership style is a person's attitudes and 
actions in leading others which will be an 
example that can be imitated by those he 
leads  (Kartono,  2017).  Some  Leadership 
Style Indicators are: 
1.  Decision making 
2.  Motivation 
3.  Responsibility of 
MSME partners are things that include 
all  MSME  work  activities  such  as  in 
producing, managing and handling all work 
activities  whose  aim  is  to  produce  a 
product  and  provide  profits  which  the 
profits can be used for the survival of both 
individuals  and  groups.  According  to 
(Rasipin & Patriajati, 2020), "Productivity is 
a  pattern  of  behavior  to  continue  to  hone 
oneself  and  self-ability  to  move  forward". 
According to (Färe & Zelenyuk, 2019) some 
of the Productivity Indicators are: 
1.  The ability to carry out their duties and 
responsibilities. 
2.  Increase  the  achievement  of  work 
results. 
3.  Enthusiasm  in  carrying  out  tasks  and 
responsibilities. 

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METHODS

Based on the background and main

problems in the title of this research is a

quantitative approach. The quantitative

approach according to (Bartol et al., 2014)

is a research based on real facts obtained

from the research field and then the data is

processed. This type of research is a causal

associative method. According to

(Nakagawa & Schielzeth, 2013), "This

associative method is a method obtained

based on the formulation of the problem

which will then be analyzed and described in

detail and factual so that it is easy to

understand. The nature of this research is

associative. According to (Sugiyono, 2011),

"Associative research is the method used by

the author to explain or provide an

explanation of the research results whether

a relationship is found in the variables

related to the study".

1. Population

According to (Sugiyono, 2011),

Population is a group that is used as an

object of research where the object is a

strong supporter of research conducted

to obtain accurate results, where this

object can be large or small. The total

population is 2,365 MSME actors who

are members of the PTPN III Medan

partnership program.

2. Sample

According (Lam et al., 2020), The

sample is a collection of objects where

this object is used as a determinant of

the research results obtained based on

strong supporting reasons in providing

the results of the research conducted.

Determining the number of samples

using the Slovin formula:

n= N/1+Ne²

n= 2.365/1+(2.365)(0,1)²

n=95.94

n = 96 people.

Based on the formula that has been

done, there are 96 respondents.

3. Data Collection Techniques

Collecting

Data to obtain results from

research, namely by distributing

respondent questionnaires contained

in a number of sample.

4. Test of Validity and Reliability of

Variable Instruments

a. Test of Validity

According to (Priyatno, 2014),

"The validity test is carried out to

show whether the items of the

questions used in the questionnaire

can be categorized as feasible or not

suitable for use". The questionnaire

can be said to be valid if the

statement on the questionnaire can

reveal in accordance with the

statement.

b. Reliability Test

According to (Erfan et al., 2020),

Reliability testing is used to

measure the scale of numbers

obtained from the results of

questionnaires that have been

carried out by respondents in which

the results of the questionnaire are

processed and determined at a

predetermined value.

5. Classical Assumption Test

a. Normality Test

According to (Ghozali, 2019),

the normality test is used in

Ruby April Motani Larosa, Valentino Arjun Surbakti, Leo Tarigan, Deni Faisal Mirza

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processing statistical data where

the results of the data processing

can show the data is normal or not.

b. Multicollinearity Test

According to (York, 2012), "this

test is conducted to show whether

there is a relationship between

independent variables and a

predetermined value".

c. Heteroscedasticity Test

According to (Ghozali, 2013),

"this test is carried out using a

statistical application to see the

regression model with a

predetermined value".

6. Research Data Analysis

a. Model

Based on the previous

description, this research model is

using multiple linear regression

analysis. Multiple linear regression

is carried out where there is more

than one independent variable

which will be processed using

statistical applications to obtain

certain information.

b. Coefficient of Determination

The coefficient of determination

is used in hypothesis testing to see

the extent of the influence of the

independent variable on the

dependent variable, which is by

looking at the percentage of the

effect of whether the influence of

the independent variable is large or

small on the independent variable.

c. Simultaneous Hypothesis Testing

(F-Test)

The F statistical test is used to

see the effect of the independent

variables together or

simultaneously whether there is an

effect on the dependent variable by

looking at the F table value

obtained based on the formula and

compared with the calculated F

obtained from statistical results and

also determined by the value of

significance.

d. Partial Hypothesis Testing (t-

test)

Test statistic is determined

based on the calculation of the t-

table obtained based on the

formula obtained manually which is

then compared with the t-count

obtained from statistical data and

then determined with a

predetermined significance value

and then concluded whether or not

there is an influence between the

independent variables on the

dependent variable.

RESULTS AND DISCUSSION

A. Classical Assumption Test

1. Normality Test

1566 | The Influence of Compensation, Compensation and Leadership Style on the Productivity

of MSME Partners in PT. Perkebunan Nusantara III Medan

Source: Research results, 2022

Figure 1. Histogram Graph

From Figure 3.1 above, it can be

seen that the histogram graph of the

data distribution is not skewed to the

left or right and there is no data that

is outside the curve so it can be

concluded that the data is normally

distributed.

Source: Research results, 2022

Figure 2. Normal P-Plot Grafik Graph

In Figure 3.2 the normal P-Plot

graph above, it can be seen that the

points do not spread around the

diagonal line and are slightly closer to

the diagonal line so it can be

concluded that the data is normally

distributed and the regression model

has met the assumption of normality.

Table 1. Normality Test Results KS

One-Sample Kolmogorov-Smirnov Test

Unstandardized Residual

Normal Parameters

a,b

Mean

.0000000

Std. Deviation

2.39612980

Most Extreme Differences

Absolute

.065

Positive

.058

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Negative

-.065

Test Statistic

.065

Asymp. Sig. (2-tailed)

.200

c,d

a. Test distribution is Normal.

b. Calculated from data.

c. Lilliefors Significance Correction.

d. This is a lower bound of the true significance.

Source: Research results, 2022

Based on Table 1, the results of the

KS test above, the Asymp value. Sig.

(2-tailed) obtained is 0.200, and the

statistical test is at 0.065, because the

significant value obtained is greater

than 0.1, it can be concluded that this

means that H1 is accepted, meaning

that the data is normally distributed

where the value of sig KS > 0.1 (0.200

> 0.1).

B. Multicollinearity Test

Table 2. Multicollinearity Test Results

Coefficients

Model

Collinearity Statistics

Tolerance

VIF

(Constant)

Competence

.737 1.357

.735

Compensation

1.361

1.359

Leadership Style

.736

Dependent Variable: Productivity

Source: Research results, 2022

From the test results in table 2 above,

it shows that competence has a

tolerance value > 0.1 (0.737 > 0.1) and a

VIF value <10 (1.549 < 10).

Compensation has a tolerance value >

0.1 (0.735 > 0.1) and a VIF value < 10

(1.575 < 10). Leadership style has a

tolerance value> 0.1 (0.736> 0.1) and a

VIF value <10 (1.1441 < 10), so it can be

concluded that there is no

multicollinearity.

C. Heteroscedasticity Test

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DOI : 10.36418/jrssem.v1i10.169 https://jrssem.publikasiindonesia.id/index.php/jrssem/index

Source: Research results, 2022

Figure 3. Scatterplot Graph

From Figure 3.3 the graph above it can

be concluded that there is no

heteroscedasticity because it does not

have a clear pattern and the points spread

above and below the number 0 on the Y

axis.

Table 3. Glejser

Coefficients

Model

Unstandardized

Coefficients

Standardized

Coefficients

Sig

Std. Error

Beta

(Constant)

1.128

-.060

.054

.002

Competence

3.536

-.133

3.136

1.111

.270

Compensation

.008

.058

.016

.130

.897

Leadership

Style

-.036

.056

-.076

-.633

.529

a. Dependent Variable: Abs_RES

Source: Research results, 2022

From Table 3 it can be seen that the

probability value (Sig.) for the

competency variable is 0.270,

compensation is 0.897 and leadership

style is 0.529. It can be seen that the

significant above the 10% confidence

level (0.1), then the regression model

does not contain heteroscedasticity.

D. Results of Research Data Analysis

1. Multiple Linear Regression

Analysis

Table 4. Regression

Coefficients

Model

Unstandardized

Coefficients

Standardized

Coefficients

Sig.

Std. Error

Beta

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Productivity = 3.745 + 0.245

Competence + 0.196 Compensation +

0.361 Leadership Style

(Constant)

3.745

1.958

1.913

.059

Competence

.245 .094

.246

2.596

.011

.196

Compensation

.101

1.942

.185

.055

.361

Leadership

Style

.098

.350

.000

3,687

Dependent Variable: Productivity

Source: Research results, 2022

From table 4 above, the first row is

a constant and the next row shows

the constant of the independent

variable. Based on the table above,

the following regression equation is

obtained:

Description:

a. The constant of 3.745 indicates

that if the value of the

independent variable

(Competence, Compensation and

Leadership Style) is zero, then

productivity (Y) is 3,745.

b. The coefficient of competence

(X1) is 0.245 and is positive,

meaning that every increase in the

competency variable (X1) by 1 unit

will be followed by an increase in

productivity (Y) of 0.245 with the

assumption that other variables

are constant.

c. The coefficient of compensation

(X2) is 0.196 and is positive,

meaning that every increase in the

compensation variable (X2) by 1

unit will be followed by an

increase in productivity (Y) of

0.196 assuming other variables

remain.

d. The Leadership Style Coefficient

(X3) is 0.361 and has a positive

value, meaning that every 1 unit

increase in the Leadership Style

(X3) variable will be followed by an

increase in Productivity (Y) of

0.361 assuming other variables

remain.

2. Coefficient of Determination (R²)

Table 5. Results of Model Determination Coefficient

Summary

Model

R Square

Adjusted R Square

Std. Error of the Estimate

.623

.389

.369 2.435

Predictors: (Constant), Leadership Style, Competence, Compensation

Source: Research results, 2022

Based on Table 3.5, the Adjusted R

Square of 0.369 means that the ability

to vary the variables of Competence

(X1), Compensation (X2) and

Leadership Style (X3) can explain the

variation of Productivity

(Y) by 37% and the remaining 63 % is

explained by independent variables

that are not examined such as

intellectual capital, leadership, work

discipline and others.

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3. Simultaneous Hypothesis Testing (F Test)

Table 6. F Test Results

ANOVA

Model

Sum of Squares

Mean Square

Sig.

Regression

346,803

115,601

19,499

000

Residual

545,437

5,929

Total

892,240

a. Dependent Variable: Productivity

b. Predictors: (Constant), Leadership Style, Competence, Compensation

Source: Research results, 2022

From table 6 above, the calculated

F value is 19.499 with a significant

level of 0.000, while the F table is

2.006 with a significant level of 0.1. Or

that the calculated F value

> F table (19.499 > 2.006) and the

significant level is less than 0.1 (0.000

> 0.1).

4. Partial Hypothesis Testing (t-test)

Table 7. Results of t-test

Coefficients

Model

Unstandardized

Coefficients

Standardized

Coefficients

Sig.

Std. Error

Beta

(Constant)

3.745

1.958

1.913

.059

Competence

.245 .094

.246

2.596

.011

.196

Compensation

.101

1.942

.185

.055

.361

Leadership

Style

.098

.350

.000

3,687

Dependent Variable: Productivity

Source: Research results, 2022

From table 7 above, it shows that:

1. The t-count for the competency

variable (X1) is 2.596 with a significant

value of 0.011, so it can be concluded

that the t-count is 2.596 and the t-

table is 1.661. The test results show t

count > t table (2.596 > 1.661).

Judging from its significance, the

significant value of the competency

variable (X1) is 0.011, smaller than the

significant value of 0.1.

2. The t-count for the compensation

variable (X2) is 1.942 with a significant

value of 0.055, so it can be concluded

that the t-count is 1.942 and the t-

table is 1.661. The test results show t

count > t table (1,942 > 1,661).

Judging from its significance, the

significant value of the competency

variable (X2) is 0.055, smaller than the

significant value of 0.1.

3. The t-count for variable (X3) is 3.687

with a significant 0.000, so it can be

concluded that the t-count is 3.687

and the t-table is 1.661. The test

results show t count > t table (3.687

> 1.661). Judging from its

Ruby April Motani Larosa, Valentino Arjun Surbakti, Leo Tarigan, Deni Faisal Mirza           
 
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significance,  the  significant  value  of 
the leadership style variable is 0.000, 
smaller than  the significant value of 
0.1. 
 
CONCLUSIONS 
 
Based on the results of the research and 
discussion  described  in  the  previous 
chapter, the following conclusions  can  be 
drawn: 1) Partially, the competency variable 
(X1) has a positive and significant effect on 
productivity  (Y)  at  PT.  Nusantara  III 
Plantation,  Medan.  2)  Partially,  the 
compensation variable (X2) has a positive 
and significant effect on productivity (Y) at 
PT.  Nusantara  III  Plantation,  Medan.  3) 
Partially, the  leadership style variable (X3) 
has  a  positive  and  significant  effect  on 
productivity  (Y)  at  PT.  Nusantara  III 
Plantation,  Medan.  4)  Simultaneously,  the 
variables  of  competence  (X1), 
compensation  (X2)  and  leadership  style 
(X3)  have  a  positive and  significant  effect 
on the productivity (Y) of PT. Nusantara III 
Plantation, Medan. 
 
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© 2022 by the authors. Submitted  
for possible open access publication  
under  the  terms  and  conditions  of  the  Creative 
Commons  Attribution  (CC  BY  SA)  license 
(https://creativecommons.org/licenses/by-sa/4.0/). 
 
 