Paschal Muhammad Reza*, Sri Mintarti,
Doddy Adhimursandi
Faculty of Economics and
Business, Universitas Mulawarman,
Samarinda, East Kalimantan, Indonesia
Email: [email protected]*
|
ARTICLE INFO |
ABSTRACT |
|
Received: June 20, 2022 Revision: July 16, 2022 Received: July 26, 2022 |
In this digital era, it is essential for a
company to consistently grow in order to compete and meet the expectations of
stockholders and stakeholders. Achieving this requires good performance and
constantly sustainably making improvements and development. Employee
performance can be influenced by organizational culture, personality, and
motivation, either directly or indirectly. Organizational culture is one
factor that influences motivation, and personality can also influence
motivation, which ultimately affects employee performance. This study aims to
analyze the influence of organizational culture, personality, and motivation
on employee performance. This research sample is an employee of PT Jasa Raharja East Kalimantan
Branch. Data analysis using SEM-PLS. The results showed a positive and
significant influence of organizational culture and personality on
motivation, motivation to employee performance, and organizational culture
and personality to employee performance. |
|
Keywords: Organizational culture; personality; motivation;
employee performance |
|
|
|
|
INTRODUCTION
In
this digital era, it is essential for a company to continually develop in order
to compete and meet the expectations of stockholders and stakeholders. To
achieve this, it is necessary to have good performance and continuously make
improvements and developments on an ongoing basis. Good company performance can
be achieved if all company employees have good performance. Unquestionably,
training activities are a continual human resource management activity that
helps employees adapt to new conditions or situations and enhances their
decision-making and problem-solving skills in these settings (Ozkeser, 2019). Employee
performance can be measured by the targets achieved and increasing yearly. For
employee performance to meet company expectations, companies must pay attention
to factors that can affect performance, including organizational culture,
personality, and motivation, where these factors directly or indirectly
influence employee performance.
����������� Busro (2018)
states
that performance is the result of work that employees can obtain, both
individuals and groups in an organization, following the authority and
responsibility imposed by the organization to achieve the vision, mission, and
goals of the organization by including ability, perseverance, independence, the
ability to solve problems according to the time limit given legally, does not
violate the law and is by morals or ethics. Good performance is determined by
several factors, such as organizational culture�
(Yusof, Munap, Badrillah, Hamid, & Khir, 2017), personality (Rababah, 2019), and employee motivation (Mohamud, Ibrahim, & Hussein, 2017). Therefore, a company
must support these three things in a positive direction so that employee
performance can achieve company expectations and company targets can be
achieved.
����������� Busro (2018)
states
that organizational culture is a shared perception held by members of the
organization as an organizational value system adopted by members of the
organization, which in turn affects the way members of the organization work
and behave. Employee interaction, organizational functioning, the
decision-making process, and employees' ability to deal with difficult
situations are only a few of the components of the company that are strongly
influenced by organizational culture (Yoel, 2015). To achieve the
performance expected by the company, organizational culture is needed to
support it. Organizational culture can grow and be developed from the company's
values and norms that apply in the company. A good organizational
culture can create a work ethic and motivate employees to improve their
performance in order to achieve the targets set by the company. The results of
previous research conducted by Yusof et al. (2017) prove that
organizational culture influences employee motivation.
����������� In addition to organizational culture, personality also
affects employee performance. Robbins and Coulter (2012)
state
that personality is a unique blend of emotional thought and behavior patterns
that influence how a person reacts to situations and interacts with others.
Personality has an essential role in work because the employee's work results
are also influenced by the characteristics of the employee, such as the
employee's level of trust. Ilhami et al. (2020)
concluded that personality positively and significantly influences employee
performance. An employee with characteristics that support his work will be
able to work well and achieve the targets set by the company.
����������� Employee motivation has an essential role in employee
performance. Robbins and Coulter (2012) state that motivation
is a process that explains the intensity, direction, and persistence of a
person in achieving his goals. Every work carried out by an employee is always
based on motivation. The motivation can be in the form of incentives, the
desire to go home on time, or other personal goals. Therefore, in a job,
motivation is needed so that the work can be carried out effectively and efficiently.
By having motivation, employee performance can achieve
the company's desired results. The results of research conducted by Mohamud et al. (2017) prove that motivation is
related to employee performance.
����������� PT Jasa Raharja
is a State-Owned Enterprise (BUMN)
engaged in compulsory insurance by managing Law no. 33 of 1964 concerning the
Mandatory Passenger Accident Insurance Fund and Law no. 34 of 1964 concerning
the Road Traffic Accident Fund. Jasa Raharja prioritizes excellent service to people who
experience traffic accidents in carrying out its duties as a government
representative in protecting the community. To realize this, Jasa Raharja must be able to
prepare human resources who are competitive and competent in their fields. In
addition, to facilitate the services provided to the community, Jasa Raharja also collaborates
with related partners such as the Regional Revenue Agency (BAPENDA) in collecting funds from the community, which will be used
as a source of compensation funds for people who experience traffic accidents,
the Indonesian National Police (POLRI)
in terms of reporting people who experience traffic accidents, and hospitals in
terms of providing guarantees to victims of traffic accidents.
����������� The working area of PT Jasa
Raharja's East Kalimantan Branch includes the Branch
Office Counter and two Representative Offices, namely Samarinda
and Tarakan. The East Kalimantan Branch Office counters include Balikpapan, Paser, and North Penajam Paser. The working area of the Samarinda Representative includes Samarinda,
Bontang, Kutai Kartanegara, East Kutai, West Kutai, and Mahakam Ulu. While the working areas of the
Tarakan Representative include Tarakan, Berau, Bulungan, Malinau, Nunukan, and Tana Tidung. With
the condition of the large area, the right strategy is needed to maximize the
existing human resources to achieve the company's goals.
����������� Human resources in the company have different
backgrounds. The majority of employees are from outside East Kalimantan. This
becomes a challenge for employees in dealing with society and adapting to the
environment and culture. Some of the obstacles often faced by employees placed
in remote areas, such as language and culture, are certainly not easy to
overcome. With all the existing limitations, the company requires all employees
to be able to adapt to existing conditions, both inside and outside the
company.
����������� The different backgrounds of employees, in terms of
education and the area of origin, provide a variety of employee
characteristics that support work and those that do not. This can affect
employee performance, which in turn will affect the company's overall
performance.
����������� Based on initial observations that have been held at PT Jasa Raharja East Kalimantan
Branch, it can be seen that the performance of employees in the office is still
not optimal. This can be seen from the Employee Performance Assessment, which
has decreased over the last four years, as shown in the following table:
Table 1
Employee Performance Assessment
|
Year |
Average |
|
2016 |
107.85 |
|
2017 |
104.32 |
|
2018 |
102.11 |
|
2019 |
100.73 |
Source: PT Jasa Raharja,
East Kalimantan Branch
����������� The categories of
performance appraisal applied by the company are as follows:
1.
80������������� =
Very Poor
2.
81 � 90������ =
Less
3.
91 � 100���� =
Enough
4.
101 � 110�� =
Ordinary
5.
111 � 120�� =
Extraordinary
A
factor that results in a decrease in employee performance, namely the
characteristics of employees who are not by their work, where there are
employees who are not suitable for their field of work, such as employees who
have poor communication procedures are required to regularly communicate with
partners and the community to achieve company targets. Based on initial
observations, some employees do not have characteristics in their field of
work. These inappropriate characteristics cause the employee to be depressed in
his job, which then affects his performance and company performance.
����������� The next factor is organizational culture, in this case,
the norms and habits that apply in the company environment. The company's work
environment has a reasonably strong seniority culture based on initial
observations. This seniority culture negatively influences employees, where
employees with a longer tenure often order new employees to do the work of the
old employees, even though this is not the main task of the new employee. This
causes the relationship between some employees to be less good, affecting
employee motivation and performance.
����������� The next factor is employee motivation, where the factor
influencing motivation is the company's prevailing organizational culture. The
culture of seniority at work negatively influences employee motivation because
it causes employees to be not serious at work. This causes many employees to be
less motivated to work because even though they have worked well, the existing
organizational culture does not support them to maintain or improve their
performance.
����������� The factors described above have a significant influence
on employee performance. The seniority culture causes the relationship between
some employees to be less good, affecting employee motivation and performance.
Then, the inappropriate characteristics cause the employee to be unable to work
optimally, thus affecting the employee's overall performance.
����������� Based on initial observations of these phenomena, it is
interesting to study in-depth through research entitled "The Influence of
Organizational Culture and Personality on the Motivation and Performance of
Employees of PT Jasa Raharja
East Kalimantan Branch."
Based
on the problem formulation described above, the objectives to be achieved are:
in this study are; (1) analyzing the influence of organizational culture on
employee motivation of PT Jasa Raharja
East Kalimantan Branch, (2) analyzing the influence of organizational culture
on the performance of employees of PT Jasa Raharja East Kalimantan Branch, (3) analyzing the influence
of personality on the motivation of employees of PT Jasa
Raharja East Kalimantan Branch, (4) analyzing the
influence of personality on the performance of employees of PT Jasa Raharja East Kalimantan
Branch, and (5) analyzing the influence of motivation on the performance of
employees of PT Jasa Raharja
East Kalimantan Branch.
METHOD
A.
Data Collection Method
The data collection used in this study was to provide personal
questionnaires. Using this method, researchers can provide answers directly to
respondents who do not understand the questions. Questionnaire responses can be
collected immediately after being filled out by respondents. Personal
questionnaires were used to obtain data on the variables developed in this
study.
Questionnaires were distributed to all employees of PT Jasa Raharja East Kalimantan
Branch. Respondent's answers to the list of questions are filled out using a
Likert Scale ranging from 1 to 5, where the most positive response is given a
strongly agree response. In contrast, the most negative response is given a
strongly disagree response (Sugiyono, 2018).
B.
Population and Sample
Ferdinand (2014)
suggests
that the population is a combination of all elements in the form of events,
things, or people who have characteristics. The study's population was all PT Jasa Raharja East Kalimantan
Branch employees, totaling 66.
Sugiyono (2018)
suggests
that the sample is part of the number and characteristics possessed by that
population. Ferdinand (2014) stated that sample sizes greater than 30 and less than 500 were
sufficient for most studies. Therefore, the sample in this study is the same as
the employee population of PT Jasa Raharja East Kalimantan Branch, which amounted to 66 people
with the distribution below:
Table
2
Distribution
of the Research Sample
|
Work Area |
Number of Employees |
|
East Kalimantan Branch Counter |
26 people |
|
Samarinda
Representative |
22 people |
|
Tarakan Representative |
18 people |
������ Based on company regulations, PT Jasa Raharja East Kalimantan Branch is included in the Level IA
Branch category so that the Job Grade
of employees can be explained as follows:
Branch Head����������� ������ ��: Grade C
Head of Operations Section : Grade F
Head of Administration���� ��: Grade G
Head Representative ��� �����: Grade G
Head of Sub Division ������ ��: Grade I
Responsible for�������� ��������: Grade J
Staff����������������������� ������ ��: Grade K, L, M
The reliability test states the extent to which a measuring instrument can provide results that are not much different if repeated measurements are made on the same subject. The most widely used reliability test method is Cronbach's alpha. This method is very suitable for use on scores in the form of a scale (e.g., 1-4 or 1-5).
According to Sekaran & Bougie (2016), decision making for reliability testing is:
�
Cronbach's alpha < 0.6 = poor
reliability
�
Cronbach's alpha 0.6 - 0.79 =
accepted reliability
�
Cronbach's alpha 0.8 = good
reliability
Validity is used to determine the accuracy of an item in the questionnaire or scale and whether the items in the questionnaire are appropriate to measure what is to be measured. The Pearson correlation method correlates each item's score to the total score. The total item score is the sum of all items. In criterion validity, an indicator of a variable is declared valid if it has a correlation coefficient with a total score of 0.30 (Sugiyono, 2018).
In testing the validity of the instrument used is the
correlated item-total Correlation. The criteria for the validity of the
instrument items can be done by comparing the tables. If rcount>
rtable,
the item is said to be valid, and vice versa. If arithmetic < rtable,
then the item is said to be invalid with a significant level at = 0.05. To find
out whether an item or item is valid or not, it is done by comparing the calculation obtained with
rtable at a significance level of =
0.05.
In this study, path analysis is used to determine the causal relationship, to explain the direct and indirect effects of a set of variables as causal variables to other variables, which are effect variables. The aim is to explain the direct and indirect effects of a set of variables, as causal variables, to other variables, which are effect variables.
According to Sani and Maharani (2013), data analysis is collecting data from all respondents (in quantitative research). Data analysis was carried out using path analysis. Path analysis analyses the relationship pattern between variables (Sani & Maharani, 2013). This model aims to determine the direct or indirect effect of a set of independent variables (exogenous) on the dependent variable (endogenous).
Sani and Maharani (2013) stated that the path coefficient, a standardized regression coefficient, is a regression coefficient calculated from a database set in standard numbers (Z-score). Various tools such as SPSS, AMOS, and PLS analysis tools can be used in conducting data analysis tests for research models in path analysis.
This study uses the Partial Least Square (PLS) analysis tool for analyzing the existing data, with the provisions of the F test at Alpha = 0.05 or P 0.05 as the significance level of F (sig. F). Meanwhile, for the T-test, the significance level is = 1.96 or 1.96, which is used to determine the influence of the independent variable on the dependent variable, either directly or indirectly. In this study, the data analysis technique used can be described below:
Descriptive statistical analysis is a statistical method used to analyze data by describing or describing the data that has been collected without the aim of making valid conclusions to be generalized. Examples of descriptive statistics include data preparation in tables, graphs, median calculations, mean, standard deviation, and percentage calculations (Sugiyono, 2018).
Analysis Inferential analysis is a statistical technique used to
analyze sample data, and the results are generalized to the population.
Analysis tool Partial Least Square
(PLS) software Smart PLS Partial Least Square (PLS) was
developed as a general method for estimating the path model using latent constructs with multiple indicators (Sugiyono, 2018). PLS can be used on any data scale (nominal, ordinal,
interval, ratio) and with more assumptions. PLS is also used to measure the
relationship between each indicator and its construct. In addition, in PLS, a bootstrapping on structural models
that are outer models and inner models.
The use of reflexive and formative indicators to measure each construct in this study, as well as measurement models structural, and data in the form of intervals and ratios, is determined to use PLS as an analytical tool. PLS, besides being able to be used to explore relationships between variables whose theoretical basis is weak or does not yet exist (in the form of proposition testing), can also be used to confirm the theory or hypothesis testing (Solimun, Rinaldo Fernandes, Adji Ahmad, Nurjannah, & Fernandes, 2017).
Characteristics of respondents include job grade, gender, age, years of service, last education, and work unit. The following is the frequency distribution:
Table 3
Demographics
Statistics
|
Demographics |
Frequency |
Percentage |
|
|
Job Grade |
C |
1 |
1.52 % |
|
F |
2 |
3.03 % |
|
|
H |
2 |
3.03 % |
|
|
I |
6 |
9.09 % |
|
|
K |
18 |
27.27 % |
|
|
L |
17 |
25.76 % |
|
|
M |
20 |
30.30 % |
|
|
Gender |
Male |
54 |
81.82 % |
|
Female |
12 |
18.18% |
|
|
Age |
21 � 30 years |
36 |
54.55 % |
|
31 � 40 years |
24 |
36.36 % |
|
|
41 � 50 years |
3 |
4.55% |
|
|
> 50 years |
3 |
4.55% |
|
|
Working period |
1 � 5 years |
21 |
31.82 % |
|
6 � 10 years |
30 |
45.45 % |
|
|
> 10 years |
15 |
22.73% |
|
|
Last Education |
SMA / equivalent |
21 |
31.82 % |
|
Diploma |
1 |
1.52 % |
|
|
Bachelor (S1) |
37 |
56.06 % |
|
|
Postgraduate (S2) / more |
7 |
10.61 % |
|
|
Work Unit |
Branch Office |
26 |
39.39 % |
|
Samarinda Representative |
22 |
33.33 % |
|
|
Tarakan Representative |
18 |
27.27 % |
|
��� �� Based on Table 3, for category job grade is 30.30% or 20 respondents are dominated by job grade M, while the least is job grade C, which is 1.52% or 1 respondent. For the gender category, male respondents amounted to 54 respondents or 81.82% overall, while female respondents amounted to 12 or 18.18% of the total. The age category is dominated by the age of 21-30 years, namely 36 respondents or 54.55% overall, while the least are respondents aged 41-50 years and more than 50 years, namely 3 respondents each with their respective percentages. 4.55% overall. The tenure category is dominated by 5 � 10 years of service, which is 30 respondents or 45.45% overall. The least are respondents with more than 10 years of service, namely 15 respondents or 22.73% overall. For the last education category, S1 is dominated by 37 respondents, or 56.06% overall. At the same time, the least is respondents with Diploma education, which is 1 respondent or 1.52% overall. The work unit with the most employees is the Branch Office Counter, with 26 respondents or 39.39% overall. In contrast, the work unit with the least number of employees is the Tarakan Representative, with 18 respondents or 27.27% overall.
Validity states the extent to which the measuring instrument is used to measure what is being measured. The way to do this is by correlating the score obtained on each question item with the individual's total score. Validity testing was carried out with the help of a computer using the SPSS for Windows Version 22 program.
In this study, validity testing was only carried out on 66 respondents. Decision making is based on the value of rcount (Corrected Item-Total Correlation) > r-table which is 0.2423, for df = 66-2 = 64; = 0.05 then the item/question is valid and vice versa.
Based on the
results of the calculation of the validity of the organizational culture
variable with 5 question items, namely:
Table 4
Validity Test Results for Organizational Culture
Variables
|
Item |
Value Corrected Item Total Correlation / r calculate |
the value of Prob |
�r-table |
Criterion |
|
1 |
0.750 |
0.000 |
0.2423 |
Valid |
|
2 |
0.748 |
0.000 |
Valid |
|
|
3 |
0.837 |
0.000 |
Valid |
|
|
4 |
0.911 |
0.000 |
Valid |
|
|
5 |
0.802 |
0.000 |
Valid |
������� Source: Primary data processed
Based on the table above, it can be seen that all questions for the organizational culture variable have valid status because the value of r count (Corrected item-total Correlation) > r- table of 0.2423.
Based on the calculation results of the personality variable validity test with 5 question items, namely:
Table 5
Personality Variable Validity Test Results (X2)
|
Item |
Value
Corrected Item Total Correlation / r calculate |
the
value of Prob |
r -Table |
Criteria |
|
1 |
0.753 |
0.000 |
0.2423 |
Valid |
|
2 |
0.901 |
0.000 |
Valid |
|
|
3 |
0.745 |
0.000 |
Valid |
|
|
4 |
0.817 |
0.000 |
Valid |
|
|
5 |
0.795 |
0.000 |
Valid |
� Source: Primary data that is processed
Based on the table above, it can be seen that all questions for the personality variable have valid status because the value of r -count (Corrected item-total Correlation) > r-table, which is 0.2423.
Based on the calculation results of the personality variable validity test with 5 question items, namely:
Table 6
Motivational Variable Validity Test
|
Item |
Value
Corrected Item Total Correlation / r calculate |
the
value of Prob |
r-table |
Criterion |
|
1 |
0.895 |
0.000 |
0.2423 |
Valid |
|
2 |
0.826 |
0.000 |
Valid |
|
|
3 |
0.852 |
0.000 |
Valid |
|
|
4 |
0.883 |
0.000 |
Valid |
|
|
5 |
0.895 |
0.000 |
Valid |
�� �����Source: Processed primary data
Based on the table above, it can be seen that all questions for motivational variables have valid status because the r-count value (Corrected item-total Correlation) > r-table is 0.2423.
Based on the calculation results of the personality variable validity test with 4 question items, namely:
Table 7
Employee Performance Variable Validity Test Results
|
Item |
Value
Corrected Item Total Correlation / r calculate |
the
value of Prob |
�r-table |
Criterion |
|
1 |
0.902 |
0.000 |
0.2423 |
Valid |
|
2 |
0.866 |
0.000 |
Valid |
|
|
3 |
0.749 |
0.000 |
Valid |
|
|
4 |
0.870 |
0.000 |
Valid |
�� Source: Primary data processed
Based on the table above, it can be seen that all questions for employee performance variables have valid status because the r-count value (Corrected item-total Correlation) > r-table is 0.2423.
Test The test is held for question items that are declared valid. A variable is declared reliable or reliable if the answers to questions are always consistent. The reliability coefficient of the instrument is intended to see the consistency of the respondents' answers to the statement items. For the analysis tool using the split-half method by correlating the total odd versus even score, the reliability is calculated using the "Alpha Cronbach" formula. The calculations were carried out with the help of the computer-assisted SPSS program. As for the reliability of each variable, the results are described in the table below.
Table 8
Reliability Test Results
|
No |
Variable |
Cronbach Alpha |
r-critical |
Criteria |
|
1 |
Organizational
Culture |
0.868 |
0.60 |
Reliable |
|
2 |
Personality |
0.858 |
0.60 |
Reliable |
|
3 |
Motivation |
0.918 |
0.60 |
Reliable |
|
4 |
Employee
Performance |
0.867 |
0.60 |
Reliable |
� Source: Primary data processed
A variable is declared reliable or reliable if the answers to questions are always consistent. Based on the table above, a reliability test was conducted on the question items declared valid. So the results of the reliability coefficient of the organizational culture instrument are all = 0.868, the personality instrument is all = 0.858, motivation is all = 0.918, and the employee performance variable instrument is all = 0.867. It has a "Cronbach's Alpha" value greater than 0.600, which means the four instruments are declared reliable or following the requirements.
Meanwhile, the average motivation has a Cronbach alpha value of 0.9204, which indicates that the instrument complies with the requirements, which is more than 0.600. Then, intrinsic motivation also obtained a value of 0.8520 while extrinsic motivation obtained a value of 0.8792, which indicates that both intrinsic and extrinsic motivation is stated under the requirements of
Table 9
Cronbach
alpha value
|
Variable |
Alpha |
|
Overall |
0.918 |
|
0.852 |
0.879 |
|
Extrinsic |
Intrinsic |

Figure
1. Testing the Measurement Model (Outer Model)
2) Convergent
Model measurement
shows how variable manifest or observed
variable represent variable latent To use be measured (Ghozali,
2016). Based on results analysis model measurement, the is known if there
are several variable manifests which
score factor loading its <
0.4 so that To use Fulfill rules of
thumb his, so manifest variable which value < 0.4 required next in drop from a model. Convergent
validity is measured with the use of parameter outer loading. Size reflexive
individual can declare correlate when value more than 0.4 with a construct
which will be measured (Ghozali, 2016).
Table 10
Loading
Factor Value
|
Variable |
Code |
Loading Factor |
|
|
|
||||
|
Organizational Culture |
X1.1 |
0.7755 |
||
|
X1.2 |
0.8329 |
|||
|
X1.3 |
0.8140 |
|||
|
X1.4 |
0.8962 |
|||
|
X1.5 |
0.7723 |
|||
|
Personality |
X2.1 |
0.7365 |
||
|
X2.2 |
0.9082 |
|||
|
X2.3 |
0.7471 |
|||
|
X2.4 |
0.8131 |
|||
|
X2.5 |
0.8038 |
|||
|
Motivation |
Y1. 1 |
0.9379 |
||
|
Y1.2 |
0.9286 |
|||
|
Y1.3 |
0.8214 |
|||
|
Y1.4 |
0.9353 |
|||
|
Y1.5 |
0.9356 |
|||
|
Employee Performance |
Y2.1 |
0.9098 |
||
|
Y2.2 |
0.8887 |
|||
|
Y2.3 |
0.6975 |
|||
|
Y2.4 |
0.8839 |
Based on table 10, the loading factor of all manifest variables is > 0.4, and nothing is removed or dropped. This means that all items can validly represent each variable. Thus,� all manifest variables have met the rules of the measurement model and can be forwarded for the next test.
3) Composite Reliability
������ In the measurement model, a reliability test is also carried out. The reliability test was held to prove the instrument's accuracy, consistency, and accuracy in measuring a construct. In PLS-SEM SEM using SmartPLS, measuring the reliability of a construct can be done in two ways, namely with Cronbach's Alpha and Composite reliability. However, using Cronbach's Alpha to test the reliability of a construct will give a lower value (underestimate). As a result, it is more advisable to use Composite Reliability.
Table 11
�Constructs
of Reliability and Validity
|
Variables |
Cronbach's Alpha |
rho_A |
Composite Reliability |
(AVE |
|
Organizational |
0.8770 |
0.8878 |
0.9106 |
0.6714 |
|
Extrinsic |
0.8792 |
0.8791 |
0.9265 |
0.8083 |
|
Intrinsic |
0.8520 |
0.8548 |
0.9310 |
0.871087 |
|
Personality |
0.860.7092 |
0.864 |
0.8624 |
0.982 |
|
0.871087 |
0.864 |
0.892 |
0.9310 |
0.9310 |
|
Culture |
Extracted |
Variance |
) |
0.7588 |
Source: Smart-PLS 2021 data processing
The table above shows that the value of all variables in reliability testing using both Cronbach's Alpha and Composite Reliability is > 0.7. Therefore, it can be concluded that the variables tested are valid and reliable, so they can be continued to test the structural model.
4) Measurement of
the Significance of Indicators
Measurement of indicators is the theoretical relationship between latent variables or high-order constructs with the dimensions of the constructs below them (Jogiyanto, 2011).

Figure 2. Results of Bootstrapping Analysis
In order to assess the significance of the effect between variables, a bootstrapping. The bootstrap procedure uses all the original samples for resampling. In the bootstrap resampling method, the significance value used (two-failed) t-value is 1.96 (significance level = 5). Table 5.8 is the result of the t-statistical test to test the significance of the indicator on the latent variable in the second-order construct:
Table 12
�Path Coefficient Measurement of Significance
|
Original Sample (O) |
Sample Mean (M) |
Standard Deviation (STDEV) |
T Statistics (|O/STDEV|) |
P Values |
|
|
X1.1 <- Organizational Culture |
0.776 |
0.774 |
0.050 |
15.427 |
0.000 |
|
X1.2 <- Organizational Culture |
0.833 |
0.830 |
0.052 |
16.062 |
0.000 |
|
X1.3 <- Organizational Culture |
0.814 |
0.809 |
0.061 |
13.343 |
0.000 |
|
X1.4 <- Organizational Culture |
0.896 |
0.896 |
0.022 |
40.117 |
0.000 |
|
X1.5 <- Organizational Culture |
0.772 |
0.776 |
0.051 |
15.249 |
0.000 |
|
X2.1 <- Personality |
0.737 |
0.741 |
0.079 |
9.382 |
0.000 |
|
X2.2 <- Personality |
0.908 |
0.909 |
0.017 |
53.711 |
0.000 |
|
X2.3 <- Personality |
0.747 |
0.742 |
0.059 |
12.611 |
0.000 |
|
X2.4 <- Personality |
0.813 |
0.818 |
0.041 |
19.669 |
0.000 |
|
X2.5 <- Personality |
0.804 |
0.799 |
0.052 |
15.368 |
0.000 |
|
Y1.1 <- Intrinsic |
0.938 |
0.937 |
0.015 |
62.511 |
0.000 |
|
Y1.1 <- Motivation |
0.906 |
0.903 |
0.026 |
34.848 |
0.000 |
|
Y1.2 <- Intrinsic |
0.929 |
0.926 |
0.024 |
38.540 |
0.000 |
|
Y1.2 <- Motivation |
0.847 |
0.848 |
0.045 |
18.858 |
0.000 |
|
Y1.3 <- Extrinsic |
0.821 |
0.826 |
0.063 |
12.941 |
0.000 |
|
Y1.3 <- Motivation |
0.869 |
0.871 |
0.042 |
20.800 |
0.000 |
|
Y1.4 <- Extrinsic |
0.935 |
0.935 |
0.019 |
49.628 |
0.000 |
|
Y1.4 <- Motivationa |
0.859 |
0.859 |
0.042 |
20.485 |
0.000 |
|
Y1.5 <- Extrinsic |
0.936 |
0.935 |
0.017 |
54.923 |
0.000 |
|
Y1.5 <- Motivation |
0.874 |
0.875 |
0.039 |
22.684 |
0.000 |
|
Y2.1 <- Performance |
0.910 |
0.909 |
0.022 |
41.609 |
0.000 |
|
Y2.2 <- Performance |
0.889 |
0.890 |
0.022 |
39.684 |
0.000 |
|
Y2.3 <- Performance |
0.698 |
0.705 |
0.121 |
5.764 |
0.000 |
|
Y2.4 <- Performance |
0.884 |
0.888 |
0.026 |
33.785 |
0.000 |
Source: Smart-PLS data 2021
The results of
the path coefficient presented
in the table above state that all items are significant to the construct with
t-statistical values> 1.96 and p-values <0.05. Therefore,
it can be stated that all indicator items are valid in forming the manifest
variables, namely organizational culture, personality, motivation, and employee
performance.
The structural or inner model's evaluation predicts the relationship between latent variables. The structural model is evaluated by looking at the variance percentage explained by looking at the R-Square value for endogenous latent constructs and the AVE for predictiveness by using resampling such as jackknifing and bootstrapping in order to obtain stability from the estimate.
Table 13
R� Value R-Square
(R�)
|
Endogenous
Variable |
R
Square |
Q
Square |
|
Motivation |
0.762 |
Q2
= 1 � (1 � 0.7622)(1 � 0.6502)
= 0.759 |
|
Employee
Performance |
0.650 |
���� Source: Smart-data processing PLS 2021
Based on the table above, it can be stated that the model of the influence of organizational culture and personality on motivation gives a value of 0.762, which can be interpreted if the variability of the motivational construct that can be explained by the variability of organizational culture and personality is 76.2%. In contrast, others are explained by other variables outside the study. This. Likewise, the model of the influence of organizational culture, personality, and motivation on employee performance give a value of 0.650, which can be interpreted if the variability of the employee performance construct can be explained by the variability of organizational culture, personality, and motivation are 65%%. In contrast, others are explained by variables outside of this study.
6) Q-Square (Q2)
Based on the
results obtained from the R-Square table, it can be seen that the Q-Square
value is 0.759, so it can be concluded that the model in this study has a
relevant predictive value, where the model used can explain the information
provided. there is 75.9% in the research data
![]()
![]()
![]()
![]()

Figure 3.
Structural Model Testing
In order to determine whether a hypothesis is accepted or rejected, it can be carried out by taking into account the significance values between constructs, t-statistics, and p-values. This way, measurement estimates, and standard errors are no longer calculated with statistical assumptions but are based on empirical observations. In the bootstrapping method in this study, the hypothesis is accepted if the significance value of t-values > 1.96 and or p-values < 0.05, then Ha is accepted, and Ho is rejected and vice versa. Below are the hypotheses formulated in this study
Table 14
Test Results
|
Hypothesis |
Original Sample (O) |
T Statistics (|O/STERR|) |
P-value |
Information |
|
|
H1 |
Organizational Culture -> Motivation |
0.3870 |
11.3082 |
0.0000 |
Positive significant (Hypothesis accepted) |
|
H2 |
Organizational Culture -> Employee Performance |
0.4811 |
11.1981 |
0.0000 |
Positively significant (Hypothesis accepted) |
|
H3 |
Personality -> Motivation |
0.4518 |
11.9305 |
0.0000 |
Positively significant (Hypothesis accepted) |
|
H4 |
Personality -> Employee Performance |
0.2075 |
6.8136 |
0.0000 |
Positively significant (Hypothesis accepted) |
|
H5 |
Motivation -> Employee Performance |
0.2415 |
6.0520 |
0.0000 |
Significantly positive (Hypothesis accepted) |
Source:
processed data, 2021
The results of hypothesis testing in the table can explain the first and fifth hypotheses. The first hypothesis shows that the magnitude of the path coefficient is 0.3870, with an absolute value of t-count 11.3082 and a p-value of 0.000. Because the p-value (0.000) is smaller than alpha 5%, there is a significant influence of organizational culture on motivation. With a coefficient of 0.3870, it can be interpreted that if the employee's perception of organizational culture is higher or better, it will increase employee motivation. As a result, the hypothesis that organizational culture has a significant and positive effect on employee motivation is accepted.
The second hypothesis shows that the magnitude of the path coefficient is 0.4811, with an absolute value of t-count 11.1981 and a p-value of 0.000. Because the p-value (0.000) is smaller than alpha 5%, organizational culture significantly influences employee performance. With a coefficient of 0.4811, it can be interpreted that if the employee's perception of the organization's culture is higher or higher, it will increase employee performance. So the hypothesis that formulates if organizational culture has a significant and positive effect on employee performance is accepted.
������ The third hypothesis shows that the path coefficient is 0.4518, with an absolute value of 11.9305 t count and a p-value of 0.000. Because the p-value (0.000) is smaller than alpha 5%, there is a significant influence of personality on motivation. With a coefficient of 0.4518, it can be interpreted that if the employee's perception of the employee's personality increases, it will increase employee motivation. So the hypothesis that formulates if personality has a significant and positive effect on employee motivation is accepted.
The fourth hypothesis shows that the magnitude of the path coefficient is 0.2075, with an absolute value of t-count 6.8136 and a p-value of 0.000. Because the p-value (0.000) is smaller than alpha 5%, there is a significant influence of personality on employee performance. With a coefficient of 0.2075, it can be interpreted that if the employee's perception of the employee's personality increases, it will increase employee motivation. So the hypothesis that formulates if personality has a significant and positive effect on employee performance is accepted.
The fifth hypothesis shows that the magnitude of the path coefficient is 0.2415, with an absolute value of t-count of 6.0520 and a p-value of 0.000. Because the p-value (0.000) is smaller than alpha 5%, work motivation significantly affects employee performance. With a coefficient of 0.2415, it can be interpreted that if the employee's perception of motivation increases, it will increase employee performance. So the hypothesis that formulates if work motivation has a significant and positive effect on employee performance is accepted.
The results show that organizational culture significantly and positively affects employee motivation. Thus, the higher or better the employee's perception of the organizational culture will increase employee motivation. So the hypothesis that formulates if organizational culture has a significant and positive effect on employee motivation is accepted.
The results of the distribution of employee answers to the perception of organizational culture stated that what management must pay attention to improve organizational culture is a friendly attitude in association; this is because the statement item has the highest average.
The results of model testing are in line with several supporting studies. Nawawi et al. (2018) analyze organizational culture's influence on motivation in coal companies located in East Kalimantan. The results of this study prove that organizational culture has a positive and significant influence on employee motivation. Another study by Weerasinghe (2017) in Sri Lanka which analyzed the influence of organizational culture on employee motivation of garment companies, showed that organizational culture had a positive influence on employee motivation. In addition, Cheeran et al. (2015), which analyze the influence of organizational culture on employee motivation in the software industry, shows that organizational culture positively influences employee motivation.
Existing organizational culture is very important for employee motivation because if the organizational culture applied is not good. With the friendliness between employees, it will feel like family in the company and make employees feel comfortable at work so that employees become motivated to work. Then employees will be less motivated to work.
The results showed that the higher or better the employee's perception of organizational culture, the higher the employee's performance. So the hypothesis that formulates if organizational culture has a significant and positive effect on employee performance is accepted.
The results of the distribution of employee answers to perceptions of organizational culture stated that what management must pay attention to improve organizational culture is a friendly attitude in association; this is because the statement item has the highest average.
This result is corroborated by Uddin et al. (2012) that organizational culture's influence on employees' performance in the telecommunications sector in Bangladesh. The research shows that organizational culture positively and significantly influences employee performance. Another study conducted by Nuryasman and Suryaman (2018) analyzed the influence of organizational culture and motivation on the performance of PT. Inoac Polytechno Indonesia shows that organizational culture positively and significantly influences employee performance. In addition, research conducted by Awadh and Alyahya (2013), which analyzes the influence of organizational culture on employee performance, proves that organizational culture positively influences employee performance.
Organizational culture is one of the factors that can be considered by company management to improve employee performance. If the organizational culture supports employees at work, employee performance will increase, which will improve company performance. Employees will feel comfortable at work, individually, with a friendly attitude between employees. In teams, so they can bring out their best abilities at work. To improve friendliness among employees, management can consider policies or activities that support this, such as taking employees out for a walk to build intimacy between employees.
The results of the study state that if the employee's perception of the employee's personality increases, it will increase employee motivation. Thus, the hypothesis that formulates if personality has a significant and positive effect on employee motivation is accepted.
The results of the distribution of employee answers to personality perceptions stated that management must pay attention to improving personality to cooperate with other employees because the statement item has the highest average.
These results are supported by several similar studies, namely Komarraju et al. (2008), which analyzed the relationship between personality and student motivation. This study proves that personality positively influences student motivation in obtaining grades and GPA (Grade Point Average). Another study by Chen et al. (2010) analyzed the relationship between personality and employee motivation in the marine tourism sector, showing that personality positively and significantly influences employee motivation. In addition, Seibokaite and Endriulaitiene (2010) also analyzes the relationship between personality and motivation of professional drivers. The research proves that personality has a positive and significant influence on the motivation of professional drivers.
To achieve the company's goals, it is necessary to have good cooperation within the team. Therefore, companies must pay attention to whether employees can work together in teams or not. To improve teamwork, the company can build communication between employees outside the work environment to help employees understand each other. Employees will feel comfortable with their environment if they understand each other, which can increase employee motivation at work.
The results of the study state that the higher or better the employee's perception of the employee's personality, the higher the employee's performance. So the hypothesis that formulates if personality has a significant and positive effect on employee performance is accepted.
The distribution of employee answers to personality perceptions shows that management must pay attention to improving employee performance to cooperate with other employees. This is because the statement item has the highest average.
These results are supported by several similar studies, namely Rababah (2019) in his research analyzing the relationship between personality and the performance of hospital employees in Jordan. The study states that personality positively and significantly influences employee performance. Another study by Yang and Hwang (2014), which analyzed the relationship between personality and the performance of bank employees in China, showed that personality positively and significantly influences employee performance. In addition, Pujiwati and Susanty (2015), in their research that analyzed the influence of personality on the performance of the West Java Provincial Government Civil Servants, showed that personality has a positive and significant influence on performance.
The personality
of the employee influences employee performance. If employees have
personalities that support their performance, they can work optimally. The
results showed that being cooperative at work indicates the highest
contribution to personality. If employees can work together in teams, employee
performance will also be positively impacted. To improve cooperation between
employees, the company can build communication between employees outside the
work environment. If there is good communication between employees, employees
will feel comfortable with their work environment, so they can work together in
teams and optimally.
The study's results prove that the higher or better the employee's perception of motivation, the higher the employee's performance. So the hypothesis that formulates if work motivation has a significant and positive effect on employee performance is accepted.
The results of the distribution of employee answers on perceived motivation stated that management should pay attention to increasing motivation because employees feel that the company's salary and benefits can motivate them at work.
Several similar
studies support this result. Ghaffari et al. (2017) analyzed the
effect of motivation on the performance of Universiti
Teknologi Malaysia employees. The research shows that
motivation positively and significantly influences employee performance.
Another study conducted by Nuryasman and Suryaman (2018) analyzed the
influence of organizational culture and motivation on the performance of PT. Inoac Polytechno Indonesia shows
that motivation has a positive influence on employee performance. In addition, Mohamud et al. (2017), in their
research that analyzed the effect of motivation on the performance of
telecommunication company employees in Mogadishu, Somalia, showed that
motivation had a positive influence on employee performance.
Humans need the motivation to do something, likewise with employees. Employees need the motivation to work in order to achieve optimal performance. The results showed that the most motivated employees to work were the salary and benefits provided by the company. That is, if employees feel that the salary and benefits provided by the company are adequate. Following their workload, employees will be motivated to achieve optimal performance. To increase employee motivation, companies can provide bonuses in the form of money or additional days of leave.
CONCLUSION
Organizational culture has a positive and significant
effect on employee motivation. If the organizational culture in the company is
good, it will encourage an increase in employee motivation and vice versa. The
test results show that the indicator of organizational culture influencing
employee motivation is a friendly attitude in the association between
employees. This shows that the friendliness between employees will feel like
family in the company and make employees feel comfortable at work so that
employees become motivated to work.
Organizational culture has a positive and significant
effect on employee performance. If the organizational culture applied in the
company is good, it will improve employee performance and vice versa. The test
results show that the indicator of organizational culture that influences
employee performance is a friendly attitude in the association between
employees. This shows that with a friendly attitude between employees,
employees will feel comfortable at work, individually, and in teams so that
employees can bring out their best abilities at work.
Personality has a positive and significant effect on
employee motivation. If employees have a good personality, employee motivation
will increase, and vice versa. The test results show that the personality
indicator influencing employee motivation is cooperation in working with other
employees. This shows that employees will be motivated to do their jobs if they
work in teams.
Personality has a positive and significant effect on
employee performance. If the employee has a good personality, the employee's
performance will increase, and vice versa. The test results show that the
personality indicator influencing employee performance is cooperation in
working with other employees. This shows that if employees can work together in
teams, employees will provide optimal performance.
Motivation has a positive and significant effect on
employee performance. If employees are motivated to work, employee performance
will also increase, and vice versa. The test results show that the indicators
of motivation that have a dominant influence on employee performance are
salaries and benefits provided by the company. This shows that employees will
be motivated to achieve optimal performance if the company's salary and
benefits are adequate and follow their workload.
Awadh, A. M., & Alyahya, M. S. (2013). Impact of
organizational culture on employee performance. International Review of
Management and Business Research, 2(1), 168. Google Scholar
Busro, M. (2018). Teori
� Teori Manajemen Sumber Daya Manusia. Jakarta: Prenadamedia Group. Google Scholar
Cheeran, M. T., Saji,
K. S., & Joseph, G. (2015). Employee Motivation and Organizational Culture:
A Study with Special Reference to Software Industry. International Journal
of Innovative Research & Development, 4(10), 78�81. Google Scholar
Chen, S.-C., Wu,
M.-C., & Chen, C.-H. (2010). Employee�s personality traits, work motivation
and innovative behavior in marine tourism industry. Journal of Service
Science and Management, 3(02), 198. Google Scholar
Ferdinand, A. (2014). Metode
Penelitian Manajemen: Pedoman Penelitian untuk Penulisan Skripsi Tesis dan
Desrtasi Ilmu Manajemen. Google Scholar
Ghaffari, S., Shah,
I., Burgoyne, J., Nazri, M., & Salleh, J. (2017). The influence of
motivation on job performance: A case study at Universiti Teknoligi Malaysia. Sara
Ghaffari, Dr. Ishak Mad Shah, Dr. John Burgoyne, Dr. Mohammad Nazri, Jalal Rezk
Salleh., The Influence of Motivation on Job Performance: A Case Study at
Universiti Teknologi Malaysia. Aust. J. Basic & Appl. Sci, 11(4),
92�99. Google Scholar
Ghozali, I. (2016). Aplikasi
analisis multivariate dengan program IBM SPSS 23. Semarang: BPFE
Universitas Diponegoro. Google Scholar
Ilhami, S. D., Armanu,
A., & Noermijati, N. (2020). The impact of individual characteristics
towards employee performance of millennial employees: The moderating effect of
training. International Journal of Research in Business and Social Science
(2147-4478), 9(4), 323�329. Google Scholar
Komarraju, M., Karau,
S. J., & Schmeck, R. R. (2008). Role of the Big Five personality traits in
predicting college students� academic motivation and achievement. Learning
and Individual Differences, 19(1), 47�52. Scopus
Mohamud, S. A.,
Ibrahim, A. A., & Hussein, J. M. (2017). The effect of motivation on
employee performance: Case study in Hormuud company in Mogadishu Somalia. International
Journal of Development Research, 9(11), 17009�17016. Google Scholar
Nawawi, M.,
Syarifuddin, A., Sehe, M., & Ekawati, H. (2018). The effect compensation
and organization culture on the motivation and commitment organization coal
company in East Kalimantan Province. International Journal of Scientific and
Technology Research, 7(9), 11�14. Google Scholar
Nuryasman, M. N.,
& Suryaman, E. A. (2018). The influence of organizational culture and work
motivation toward employee performance (case study on employees of pt inoac
polytechno indonesia). Jurnal Manajemen, 22(1), 74�90. Google Scholar
Ozkeser, B. (2019).
Impact of training on employee motivation in human resources management. Procedia
Computer Science, 158, 802�810. Scopus
Pujiwati, A., &
Susanty, E. (2015). The Influence of Individual Characteristics and Work
Motivation on Employee Performance. Conference In Business, Accounting, And
Management (CBAM), 2(1), 46�52. Google Scholar
Rababah, N. M. (2019).
An Evaluation of the Relationships between Personality Traits, Job
Satisfaction and Job Performance: An Empirical Study of Jordanian Hospitals.
Google Scholar
Robbins, S. P., &
Coulter, M. (2012). Management (11th ed.). United States of America:
Prentice Hall. Google Scholar
Sani, A., &
Maharani, V. (2013). Metodologi Penelitian Manajemen Sumber Daya
Manusia : Teori, Kuesioner, dan Analisis Data. Malang: Uin Press. Google Scholar
Seibokaite, L., &
Endriulaitiene, A. (2010). The role of personality traits, work motivation and
organizational safety climate in risky occupational performance of professional
drivers. Baltic Journal of Management, 7(1), 103 � 118. Google Scholar
Sekaran, U., &
Bougie, R. (2016). Research methods for business: A skill building approach.
john wiley & sons. Google Scholar
Solimun, Rinaldo
Fernandes, Adji Ahmad, Nurjannah, & Fernandes, A. A. R. (2017). Metode
Statistika Multivariat, Pemodelan Persamaan Struktural (SEM) Pendekatan WarpPLS.
Malang: UB Press. Google Scholar
Sugiyono. (2018). Metode
Penelitian Kuantitatif, Kualitatif, dan R&D. Bandung: Alfabeta. Google Scholar
Uddin, M. J., Luva, R.
H., & Hossian, S. M. M. (2012). Impact of organizational culture on
employee performance and productivity: A case study of telecommunication sector
in Bangladesh. International Journal of Business and Management, 8(2),
63. Google Scholar
Weerasinghe, G.
(2017). Organization culture impacts on employee motivation: A case study on
an apparel company in Sri Lanka. Google Scholar
Yang, C.-L., &
Hwang, M. (2014). Personality traits and simultaneous reciprocal influences
between job performance and job satisfaction. Chinese Management Studies.
Google Scholar
Yoel, S. (2015).
Cultivating organizational culture within globalized companies using the
wellness kickoff tool. Procedia-Social and Behavioral Sciences, 209,
533�539. Scopus
Yusof, H. S. M.,
Munap, R., Badrillah, M. I. M., Hamid, N. R. A., & Khir, R. M. (2017). The
relationship between organizational culture and employee motivation as
moderated by work attitude. Journal of Administrative and Business Studies,
3(1), 21�25. Google Scholar
|
Copyright holder: Paschal Muhammad Reza, Sri Mintarti, Doddy Adhimursandi (2022) |
|
First publication right: |
|
This article is licensed under: |