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JOSS :
Journal of Social Science
DECISION SUPPORT SYSTEM FOR MANAGER PLACEMENT IN THE
PLANTATION INDUSTRY USING TOPSIS METHOD
Teguh Widodo
1
, Nur Wening
2
, Rianto
3
Universitas Teknologi Yogyakarta, Indonesia
E-mail: widodoteguh308@gmail.com
1
, weninguty@gmail.com
2
, rianto@staff.uty.ac.id
3
KEYWORDS
Decision Support
System; Plantation
Industry Manager;
TOPSIS
ABSTRACT
Accuracy in placing employees determines the performance of a company.
Likewise done by PT XYZ in determining the placement of managers in
the plantation industry by using a decision support system. This is done in
order to minimize the level of subjectivity of the manager placement
determination system at PT XYZ. This research aims to provide alternative
preference values to prospective employees who will occupy manager
positions in the plantation industry. The method used in the placement of
managers with a decision support system is the technique for Order
Preference by Similarity to the Ideal Solution (TOPSIS) method. The
criteria used in this method are 7 criteria taken based on the criteria for
BUMN talent management according to the Regulation of the Minister of
BUMN Number PER-3 / MBU / 03/2023, these criteria are Professional
Work Period, Variety of Work Experience, Managerial Competence,
Technical Competence, Educational Strata, Performance Assessment
Results, Level of Punishment that has been received. The results of this
study are from the results of the calculation analysis through the TOPSIS
method on 7 alternatives, then there is name number 5 managed to get the
best score of 0.80 and was determined as a preference to be placed in class
A garden.
INTRODUCTION
The plantation industry is one of the main economic sectors in Indonesia, from the point
of view of contribution to the Indonesian state budget, the plantation sub-sector is currently
one of the largest contributors to national economic growth, with a contribution rate to
agricultural gross domestic product (GDP) of 34% or IDR 429.68 trillion. The role of
plantations is increasing from year to year. Moreover, the world energy crisis has increasingly
placed the position of plantations at a very important level because it is not only related to food
issues but also penetrates into related food, feed, fuel (Widodo & Mahagiyani, 2022).
PT XYZ is a group of state-owned companies engaged in the plantation industry that
manages various commodities, namely oil palm, rubber, sugar cane, and tea which are the main
commodities. The location of PT XYZ business units is spread across Sumatra, Java,
Kalimantan, and Sulawesi which are divided into 3 corporate entities and 13 Regions. As a
plantation industry company in general that is labor intensive (labor industry) and has a large
number of workers, the number of workers at PT XYZ in 2024 position is quite a lot, namely
80 thousand employees.
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p- ISSN 2963-1866- e-ISSN 2963-8909
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The large workforce of PT XYZ as a plantation company means that it requires excellent
human resource management because this HR management factor is a crucial factor in
achieving optimal productivity and profitability for individual employees and organizations.
Human resource management (HRM) is an important factor for achieving company goals
because it involves many common components such as human factors, attitudes, behavior, and
society. Human resource management itself can be classified into operational and managerial
forms. Operational responsibilities include policy-making, planning, implementation, auditing,
evaluation, and performance appraisal, while managerial roles include getting support from
upper management, increasing employee empowerment, providing continuous training,
implementing an efficient remuneration system, and building teamwork (Chams & García-
Blandón, 2019). With the classification of HR management, it will make the organization more
effective and efficient. However, before leading to this, of course, a process is needed first.
This is due to the need for HR management in terms of creating an optimal workforce
individually. The form includes determining the placement of employees in the organization
and providing opportunities for employees to develop their careers (Sahadewa & Rahmawati,
2021).
The previous explanation states that one of the important aspects of HR management is
employee placement. One way to get quality human resources is to place these human resources
based on their competencies and characteristics (Rivai, 2009). Proper employee placement will
have an impact on improving employee performance, operational efficiency, and employee job
satisfaction.
One of the problems during the employee position placement process is subjectivity so a
system is needed that is able to select employees who are suitable or feasible to occupy
positions in certain divisions. The criteria possessed by employees who are accepted must also
be in accordance with the criteria needed so that they can overcome the problems in the position
(Pramudita & Rizaldi, 2018). In plantation companies, one of the most crucial position
placement processes is the placement of the Garden Manager, considering that this position is
the top structure in the work unit of each garden. The Garden Manager is the top position in
the work unit that is a profit center, the person who sits in the position will manage all resources
in the garden and given the KPIs of production, productivity, and cost-effectiveness efficiency.
PT XYZ has special criteria in classifying the garden as a work unit, according to the
decision letter of the director of PT XYZ they set 3 garden classifications, namely class A,
class B, and class C gardens, where class A is the garden that has the highest complexity. The
level of complexity and difficulty in managing the plantation is seen from 3 factors and 9 sub-
factors. The first factor is technical culture complexity which consists of sub-factors of area,
number of commodities, topography, and number of farm activities. The second factor is
internal complexity consisting of sub-factors of the number of employees, employee education
level, employee compliance level, fixed costs & depreciation. The third factor is external
complexity which consists of 1 sub-factor, namely farm security.
Meanwhile, to classify personnel, PT XYZ seeks to guide the policy of the Ministry of
SOEs in the Regulation of the Minister of SOEs Number PER-3 / MBU / 03/2023 concerning
BUMN Organs and Human Resources which, among others, discusses the concept of talent
management that important criteria for attracting talent to be placed in a particular company
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are knowledge, experience, competency, personal attributes (Republik, 2023). The best
personnel according to these criteria will be recommended to occupy class A farms.
Currently, the division in charge of HR at the head office of PT XYZ still processes the
selection of manager placements to each garden class manually so the element of subjectivity
is still quite large, therefore PT XYZ really needs a Decision Support System to help the
placement of garden managers. In essence, the Decision Support System is a technique in the
form of a model-based set/collection that is able to interactively make decisions. Decision
Support Systems are useful for assisting decision-making in overcoming structured and semi-
structured problems to be more effective by using analytical models and available data. The
decision taken to solve a problem is seen from its structurality which consists of structured
decisions (Structured Decision), semi-structured decisions (Semi-Structured Decision), and
unstructured decisions (Unstructured Decision). So far, the concept of Decision Support
Systems has developed rapidly in solving several problems. So that the application of the
Decision Support System is able to provide quite effective results on a problem by providing
alternative recommendations in making the final decision (Guswandi et al., 2021). In addition,
decision support systems can also be defined as tools designed to assist users in making
decisions by providing relevant information, data analysis, and modeling capabilities (Forcina
et al., 2024).
TOPSIS (Technique for Order of Preference by Similarity to an Ideal Solution) is a multi-
criteria decision-making method used to evaluate alternatives based on multiple criteria. It
involves determining the distance of each alternative to the ideal solution and the distance to
the negative ideal solution. The alternative that has the smallest distance to the ideal solution
and the greatest distance to the negative ideal solution is considered the best choice (Jin et al.,
2024). TOPSIS is one method of solving multi-criteria decision-making problems based on the
concept that the best-selected alternative not only has the shortest distance from the positive
ideal solution but also has the longest distance from the negative ideal solution. However, the
alternative that has the smallest distance from the positive ideal solution does not necessarily
have the largest distance from the negative ideal solution. Therefore, TOPSIS considers both,
the distance to the positive ideal solution and the distance to the negative ideal solution
simultaneously. The optimal solution in the TOPSIS method is obtained by determining the
relative closeness of an alternative to the positive ideal solution. TOPSIS will rank alternatives
based on the priority of the relative closeness value of an alternative to a positive ideal solution.
The alternatives that have been ranked are then used as a reference for decision-makers to
choose the best solution (Surya, 2018).
TOPSIS is widely used because the concept is simple and easy to understand, has
efficient computation, and is able to measure the relative performance of alternative decisions
in a simple mathematical form, besides TOPSIS can combine the relative weights of important
criteria (Aqli et al., 2016). The steps in the TOPSIS method are as follows:
TOPSIS requires a normalized rating of each alternative AI on each criterion
.
(1)
With i = 1,2 ,m; and j=1,2,..n
Where :
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( y y )
n
2
j 1
i j
= normalized decision matrix
= weight of jth criterion on Ith alternative
The positive ideal solution A+ and negative ideal solution A- can be determined based on the
normalized weight rating (yij) as follows
=
;
= (y1+, y2+,...,yn+);
= (y1-, y2-, ..., yn-);
Where :
yij = weighted normalized matrix [i][j]
wi = weight vector [i]
yj+ = max yij, if j is a profit attribute min yij if j is a cost attribute
yj- = min yij, if j is a profit attribute max yij if j is a cost attribute
The distance between alternative AI and the positive ideal solution is formulated as:
; i=1,2,...,m (4)
Where :
= distance of alternative AI to the ideal solution
negative
= positive ideal solution [i]
= weighted normalization matrix [i][j]
The distance between alternative AI and the negative ideal solution is formulated as:
; i=1,2,...,m (5)
Where :
= distance of alternative AI to the ideal solution
negative
= positive ideal solution [i]
= weighted normalization matrix [i][j]
The preference value for each alternative (Vi) can be seen in the formula below.
;i=1,2m,….,m (6)
Where :
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Vi = closeness of each alternative to the ideal solution
Di+ = distance of alternative Ai with the positive ideal solution
Di- = distance of alternative Ai with the negative ideal solution
TOPSIS algorithm is a decision support system algorithm with many criteria, TOPSIS
stands for Technique for Order Preference by Similarity to Ideal Solution which considers the
distance to the positive ideal solution and the distance to the negative ideal solution by taking
the shortest distance from the positive ideal solution and the longest distance from the negative
ideal solution, thus obtaining alternative preference values from comparisons to their relative
distances (SALATIGA, 2020). TOPSIS is used because the concept is simple, easy to
understand, computationally efficient, and has the ability to measure the relative performance
of decision alternatives in a simple mathematical form (Asrul & Zuhriyah, 2021).
Based on previous research as a reference for this research, the first is Lecturer
Performance Appraisal Using TOPSIS in the AMIK Mitra Gama case study. The research aims
to build a decision support system using the Technique For Others Reference by Similarity to
Ideal Solution (TOPSIS) method that will help and facilitate the assessment of lecturer
performance. In the study examined the performance of 5 lecturers, at AMIK Mitra Gama, data
collection and information used a descriptive or survey approach, namely collecting data from
several AMIK Mitra Gama lecturers who were used as a reference for assessing lecturer
performance. The conclusion is that the TOPSIS method can provide recommendations in
evaluating lecturers, where the final result is calculated based on the highest preference value
of each alternative. The highest value is the first priority as the lecturer who has the highest
performance (Surya, 2018).
Another research is, the Decision Support System for Clean Water Distribution Using
Tank Cars at PDAM Makassar City Using the TOPSIS Method. The research objective is to
facilitate the priority of clean water delivery, the application of the TOPSIS method in this
study makes it easier for PDAM Makassar City to distribute clean water using tank cars.
Because the TOPSIS method is able to prioritize ideal alternatives. The results obtained
manually and the results of the system obtained the same results and have been validated (Asrul
& Zuhriyah, 2021).
Another study was conducted using a decision support system and using the TOPSIS
method, to find preferences related to the effect of the company's employee turnover rate and
the results are one of the strongest preferences to reduce employee turnover rates by increasing
CSR programs for company employees themselves (Dobrosavljević & Urošević, 2022). Then
other research measures individual organizational performance based on criteria and ranks
individuals based on measurements. The technique used is one of them using the TOPSIS
method. The process by looking at the significance of indicators or alternatives by providing a
final human capital ranking that produces several Multi-Criteria Decision Making (MCDM)
approaches "which are effective, compatible and reliable given the research objectives (Masum
et al., 2019).
There is also another study that aims to determine the determinants of employee retention
of South Korean construction employees. It was identified that eight significant determinants
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affect employee retention in South Korean construction companies. The TOPSIS method
technique was used to prioritize the identified determinants. TOPSIS analysis shows that
personal characteristics, personal development, promotion opportunities, and work-life balance
are the four most important determinants. Construction companies are advised to focus on these
determinants to increase employee retention rates in their companies and achieve sustainable
development (Park et al., 2021). Based on the description above and the absence of a system
that can help make decisions on the placement of garden managers, especially at PT XYZ, it is
necessary to build a decision support system using the Technique For Others Reference by
Similarity to Ideal Solution (TOPSIS) method that will help and facilitate decision making on
the placement of garden managers.
METHOD RESEARCH
The research was conducted at PT XYZ, and data collection and information were
obtained from secondary data in the company, as a trial in this study, filling tests were carried
out on 7 people who had the potential to fill one of the class A gardens. The data is then
analyzed and used as a reference in making decisions on the selection of garden managers who
will be placed in one of the class A gardens. In decision-making, the Technique for Order
Preference by Similarity to Ideal Solution (TOPSIS) method is used (Guswandi et al., 2021).
At this stage, we will explain how the test works using the TOPSIS method. The testing
mechanism can be seen in Figure 1.
Figure 1
TOPSIS Mechanism
RESULTS AND DISCUSSION
Based on the testing mechanism above, it takes 8 stages to analyze who is the most
suitable employee to be placed in the class A garden. The following discussion is to analyze
employee preferences to fill the position of class A garden manager. The following data are 7
employees who are used as tests and will be assessed based on the level of importance of
existing criteria.
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Table 1
Alternatives
Alternative
Description
A1
Employee 1
A2
Employee 2
A3
Employee 3
A4
Employee 4
A5
Employee 5
A6
Employee 6
A7
Employee 7
After the alternative data is determined, testing is then carried out, namely:
a. Determine the criteria that will be used as a reference in the assessment.
Table 2
Criteria
Criteria Code
Criteria
Cluster
Criteria
K1
Teneur (Professional Tenure)
Experience
K2
Variance (Variation of Work Experience)
K3
Managerial Competence
Knowledge &
Competency
K4
Technical Competence
K5
Education Strata
K6
Performance Appraisal Results
Personal
Attribute
K7
Level of Punishment ever received
Table 2 describes the criteria that will be used to assess lecturer performance, the
criteria start from K1 to K8.
a. Determine the level of importance of each criterion, with a value of 1 to 5, namely :
Table 3
Level of Importance
Level of Importance
Value
Very High
5
High
4
Middle
3
Low
2
Very Low
1
After the criteria are determined (Table 3), then the level of importance of each criterion
is determined, the level of importance of the criteria can be seen in Table 4.
Table 4
Level of Importance of Each Criterion
Criteria
Description
Value
K1
Teneur (Professional Tenure)
0,1
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K2
Variance (Variation of Work Experience)
0,1
K3
Managerial Competence
0,15
K4
Technical Competence
0,15
K5
Education Strata
0,1
K6
Performance Appraisal Results
0,3
K7
Level of Punishment ever received
0,1
Based on Table 4, the preference weight (W) is obtained:
Table 5
Importance of weight value of employees
Alternatives
K1
K2
K3
K4
K5
K6
K7
A1
2
4
1
1
3
1
2
A2
1
4
2
2
3
2
2
A3
2
3
3
3
3
2
3
A4
3
3
2
2
2
2
2
A5
4
4
3
3
4
2
3
A6
5
2
2
2
5
2
2
A7
3
2
2
2
2
3
3
In Table 5, all alternative data is input according to the data obtained in the data
collection process, namely 7 employees as a test sample.
a. Creating a normalized decision matrix In this section, the value of each criterion will be
sought using the formula (1).
K1 = Finding the Teneur Of Experience Value
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K2: Find the Variance of Experience value
K3: Find the value of Managerial Competence
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K4: Find the value of Technical Competency
K5: Find the value of Strata Education
K6: Find the Work performance value
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K7: Find the Work performance value
And so on so as to obtain the following R matrix:
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b. Determining the weighted normalized decision matrix using formula (2)
And so on so as to obtain the matrix Y
c. Determine the positive ideal solution (Y Max) and negative ideal solution (Y Min) Positive
ideal solution (Y Max) using formula (3)
Negative ideal solution (Y Min) using formula (3)
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d. Determining the distance between the weighted values of each alternative Positive ideal
solution using formula (4)
0,06-0,2
2
+
0,05-0,05
2
+
0,08-0,03
2
+
0,08-0,03
2
+
0,06-0.03
2
+
0,16-0,05
2
+
0,05-0,03
2
+(0,45-0,24)
2
= 0,25
0,06-0,1
2
+
0,05-0,05
2
+
0,08-0,05
2
+
0,08-0,05
2
+
0,06-0.03
2
+
0,16-0,11
2
+
0,05-0,03
2
+(0,45-0,33)
2
= 0,14
0,06-0,2
2
+
0,05-0,03
2
+
0,08-0,08
2
+
0,08-0,08
2
+
0,06-0.03
2
+
0,16-0,11
2
+
0,05-0,05
2
+(0,45-0,40)
2
= 0,09
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0,06-0,04
2
+
0,05-0,03
2
+
0,08-0,05
2
+
0,08-0,05
2
+
0,06-0.02
2
+
0,16-0,11
2
+
0,05-0,03
2
+(0,45-0,34)
2
= 0,14
0,06-0,05
2
+
0,05-0,05
2
+
0,08-0,08
2
+
0,08-0,08
2
+
0,06-0.05
2
+
0,16-0,11
2
+
0,05-0,05
2
+(0,45-0,45)
2
= 0,06
0,06-0,06
2
+
0,05-0,02
2
+
0,08-0,05
2
+
0,08-0,05
2
+
0,06-0.06
2
+
0,16-0,11
2
+
0,05-0,03
2
+(0,45-0,38)
2
= 0,10
0,06-0,04
2
+
0,05-0,02
2
+
0,08-0,05
2
+
0,08-0,05
2
+
0,06-0.02
2
+
0,16-0,16
2
+
0,05-0,05
2
+(0,45-0,39)
2
= 0,08
e. Determining the distance between the weighted values of each alternative Positive ideal
solution using formula (5)
0,01-0,2
2
+
0,02-0,05
2
+
0,03-0,03
2
+
0,03-0,03
2
+
0,02-0.03
2
+
0,05-0,05
2
+
0,03-0,03
2
+(0,24-0,24)
2
= 0,03
0,01-0,1
2
+
0,02-0,05
2
+
0,03-0,05
2
+
0,03-0,05
2
+
0,02-0.03
2
+
0,05-0,11
2
+
0,03-0,03
2
+(0,24-0,33)
2
= 0,12
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0,01-0,02
2
+
0,02-0,05
2
+
0,03-0,05
2
+
0,03-0,05
2
+
0,02-0.03
2
+
0,05-0,11
2
+
0,03-0,05
2
+(0,24-0,40)
2
= 0,19
0,01-0,04
2
+
0,02-0,03
2
+
0,03-0,05
2
+
0,03-0,05
2
+
0,02-0.02
2
+
0,05-0,11
2
+
0,03-0,03
2
+(0,24-0,34)
2
= 0,12
0,01-0,05
2
+
0,02-0,05
2
+
0,03-0,08
2
+
0,03-0,08
2
+
0,02-0.05
2
+
0,05-0,11
2
+
0,03-0,05
2
+(0,24-0,45)
2
= 0,23
0,01-0,06
2
+
0,02-0,02
2
+
0,03-0,05
2
+
0,03-0,05
2
+
0,02-0.06
2
+
0,05-0,11
2
+
0,03-0,03
2
+(0,24-0,38)
2
= 0,17
0,01-0,04
2
+
0,02-0,02
2
+
0,03-0,05
2
+
0,03-0,05
2
+
0,02-0.02
2
+
0,05-0,11
2
+
0,03-0,05
2
+(0,24-0,39)
2
= 0,19
a. Determining the preference value of each alternative
using formula (6)
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Table 6
Preference values for alternatives
Alternative
Description
Preference value
A1
Employee 1
0,10
A2
Employee 2
0,45
A3
Employee 3
0,69
A4
Employee 4
0,46
A5
Employee 5
0,80
A6
Employee 6
0,63
A7
Employee 7
0,71
Table 6 explains the preference value for each alternative and the results of the
calculation of the preference value for each alternative, the highest value is in V_2 so
alternative A5 (Employee 5) is the alternative chosen as the employee who has the highest
value in this TOPSIS calculation so that alternative A5 (Employee 5) preference will be
recommended to occupy class A garden.
The results of the study were ultimately able to draw objective conclusions based on
preference results using the TOPSIS method with A5 (Employee 5) as the alternative chosen
as the employee who has the highest value. The results of this study are in line with research
conducted by Surya (2018), Asrul & Zuhriyah (2021), Dobrosavljević & Urošević (2022),
Masum et al., (2019), Park et al., (2021) which all of these studies use the topsis method in
determining individuals to occupy certain positions. In addition, the results of these studies are
able to provide more objective preferences in determining these individuals. Likewise, what
happened in this study was that the topsis method was able to provide preferences for selecting
managers at PT. XYZ. This means, TOPSIS (Technique for Order of Preference by Similarity
to an Ideal Solution) is a multi-criteria decision-making method used to evaluate alternatives
based on multiple criteria (Jin et al., 2024). TOPSIS can also provide more objective
preferences.
CONCLUSION
In the test conducted, there were 7 employees who were assessed based on the level of
importance of the criteria which were generally taken based on the criteria for SOE talent
management based on the policy of the Ministry of SOEs in the Regulation of the Minister of
SOEs Number PER-3/MBU/03/2023 concerning SOE Organs and HR. These criteria include
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Professional Work Period, Variety of Work Experience, Managerial Competence, Technical
Competence, Educational Level, Performance Assessment Results, and Level of Punishment
that has been received.
After the criteria and their level of importance are determined, the preference weight (W)
for each employee is calculated based on the level of importance of the criteria given. A
weighted normalized decision matrix is also created using a predetermined formula.
Furthermore, the calculation of the Positive Ideal Solution (Y Max) and Negative Ideal
Solution (Y Min) is carried out to determine the preference value of each alternative. The
calculation results show that the highest preference value is for Employee 5 (Alternative A5),
with a preference value of 0.80.
Based on the preference value, it can be concluded that Employee 5 is the best alternative
that has the highest value in employee performance assessment to be placed as a class A garden
manager.
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Copyright holders:
Teguh Widodo
1
, Nur Wening
2
, Rianto
3
(2024)
First publication right:
JoSS - Journal of Social Science
This article is licensed under a Creative Commons Attribution-ShareAlike 4.0
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