p–ISSN: 2723 - 6609 e-ISSN: 2745-5254
Vol. 5, No. 6 June 2024 http://jist.publikasiindonesia.id/
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 6, June 2024 2736
Decision Support System in Employee Admissions Using
Simple Additive Weighting Algorithm in CV.Source of
Shared Solutions
Syahrul Rofiq Abdillah Fadli
1*
, Dwi Hartanti
2
, Agustina Srirahayu
3
Universitas Duta Bangsa Surakarta
E-mail: [email protected]
1*
2
3
ABSTRACT
Keywords: decision
support systems; SAW;
employee reception.
CV. Sumber Solusi Bersama, a software house company in
Sukoharjo, faces challenges in the employee recruitment
process that is still done manually. This research aims to
develop a decision support system (SPK) for employee
admission using the Simple Additive Weighting (SAW)
algorithm. The SAW algorithm was chosen because of its
ability to analyze and give weight to each criterion for the
best decision-making. This research uses the waterfall
system development method which is part of the System
Development Life Cycle (SDLC). This system is expected
to increase efficiency and accuracy in the employee
selection process, as well as support fairer and more
appropriate decision-making. Software feasibility testing
conducted by CV. Implementation of SPK with SAW
algorithm in CV. Sumber Solusi Bersama provides an
alternative way to select employees that is more systematic
and structured, so that it can help in achieving the
company's strategic goals.
Introduction
The recruitment and selection process of employees is an important aspect of
human resource management that affects operational performance and the achievement
of company goals (Muryani et al., 2022). The selection of the right candidate not only
affects operational performance, but also contributes to the achievement of the
company's strategic goals. CV.Sumber Solusi Bersama as a growing company, faces the
challenge of screening a large number of applicants to find individuals who best suit the
needs and culture of the organization. The manual selection process is often time-
consuming and prone to subjectivity, so a method is needed that can increase efficiency
and accuracy in decision-making (Al Furat, 2023).
This Decision Support System (SCI) is a tool that can help managers make
better and more accurate decisions based on data and analytical models (Ariantini et al.,
2023). In the context of employee admission, SPK can be used to evaluate and compare
prospective employees based on various relevant criteria. One of the effective methods
in the application of SPK is the Simple Additive Weighting (SAW) algorithm (Rahayu,
Decision Support System in Employee Admissions Using Simple Additive Weighting
Algorithm at CV.Sumber Solusi Bersama
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 6, June 2024 2737
Handani, & Ramadiani, 2022). The SAW algorithm is known for its simplicity and
ability to process multi-criteria data by assigning weights to each criterion according to
its level of importance (Anita, Wahyudi, & Susanto, 2020). The general definition of a
decision support system is a system that can solve difficulties and communicate with
semi-structured challenges (Umar, 2023).
This research aims to design and implement SPK in the process of accepting
employees at CV.Sumber Solusi Bersama using the SAW algorithm. The study will also
evaluate the effectiveness of the implementation of the SAW algorithm in the context of
employee selection and identify the benefits and challenges faced in its implementation
(Yunita, Wibowo, Rizky, & Wardah, 2023).
The determination of the decision support system using a simple additive
weighting algorithm on CV. Sumber Solusi Bersama makes the selection process for
employee admissions have an alternative way of selection where the director can have
an employee admission decision with the existing system.
Research Methods
This research begins by formulating a problem and conducting a literature study.
The problem-solving process requires data collected through observation and
documentation methods (Apriliawati, 2020). After the data is collected, the next stage is
development, this time the author uses the Rapid Application Development (RAD)
method (Zakariah, Afriani, & Zakariah, 2020).
The RAD method was chosen because it has a high level of dynamism, short
processing time, and has similar features to those of users, and can quickly meet the
needs of the latest information. These are the steps of the research carried out:
a. This stage involves modeling business functions to identify the information that
needs to be created, the party responsible for creating the information, the flow of
information, and the processes involved. Researchers collect materials and make
observations on system needs, then this business modeling stage will be visualized
using a workflow diagram.
b. Data Modeling, this stage includes modeling the necessary data based on business
modeling, as well as defining its attributes. At this stage, the researcher created a data model
based on information about prospective employees and the criteria obtained by applying the
Simple Additive Weighting method.
c. Process Modeling, a business function defined based on data modelling is practiced. The
author uses Unified Modeling Language (UML) at this time to identify business processes,
including drawing use case diagrams. In addition, the author creates a system interface
consisting of input and output design.
Results and Discussion
1. Business Modeling
Syahrul Rofiq Abdillah Fadli, Dwi Hartanti, Agustina Srirahayu
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 6, June 2024 2738
Admin and user access permissions are included in the basic definition of
business modeling for employee hiring decision support systems. The following Picture
1 illustrates the workflow of the decision support system that is created:
Picture 1. Decision Support System Workflow
Picture 1 :
a. Admin as a data manager for prospective employees who register through the
decision support system, assigns values and attribute weights for final calculations
using the Simple Additive Weighting (SAW) method (Poornama, Putra, Adi, &
Harthanti, 2022). This makes it easier for the director of CV. Sumber Solusi
Bersama in selecting employee admissions according to needs.
b. Prospective employees can access the main page of the decision support system
without logging in and seeing the list of names that have passed the selection, and on
the main page there is already a page that is integrated into the data so that it can
display the names of prospective employees.
2. Data Modeling
The information used in this study is data on prospective employees who are
running for CV. With 8 criteria for each prospective employee. The data on the criteria
for prospective employees to be used is displayed in Table 1.
Table 1 Table of Codes and Criteria for Selecting Prospective Employees
It
Criterion
Symbol
Benefit
Cost
1
Skill
K1
✓
-
2
Experience
K2
✓
-
3
Certification
K3
✓
-
4
Interview
K4
✓
-
5
Sikap
K5
✓
-
6
Knowledge
K6
✓
-
7
Test Scores
K7
✓
-
8
Troubleshooting
K8
-
✓
a. Weight table
Equation (3) is used to calculate the preference weight (W) (Sukaryati &
Voutama, 2022) in the following way:
Wj
=
Information:
Wj = preference weight
Decision Support System in Employee Admissions Using Simple Additive Weighting
Algorithm at CV.Sumber Solusi Bersama
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 6, June 2024 2739
Wlamaj
= nonot value in the To column j
Σj = Total overall weight value
Based on the equation that has been explained as shown in Table 2.
Table 2 Weight Table
No
Criteria Symbol
Weight
1
K1
14
2
K2
12
3
K3
12
4
K4
10
5
K5
15
6
K6
12
7
K7
12
8
K8
13
b. Criterion matrix
After the director of CV.Sumber Solusi Bersama completed the questionnaire
data table, the values were constructed in the form of a matrix as follows.
X=
c. Normalization of the R Matrix
To generate the normalization matrix R, the equation of the normalization matrix
can be modified according to the type of attribute (profit or cost). Utilizing Equation (1),
obtain the value of R. For each alternative (i), the normalization on K1 (j) is listed in
the following order:
R11 = = 0,6
So the values of R
11
, R21, and R71 have a value of 0.6. While R
31
, and R61 have
a value of 0.8 and the values of R41, R51, and R81 have the same value, namely 1.
The R matrix is obtained as follows based on the same formula used to obtain
the matrix normalization equation:
R =
d. Ranking Determination
Find out the value of each option or potential employee who submitted a resume.
Unify Source Solutions. Here's how to calculate the value of V1 for each of the eight
choices using equation (2):
V1 = (0,6 x 0,14) + (0,8 x 0,12) + (0,5 x 0,12) + (1 x 0,10) + (1 x 0,15) + (0,6 x 0,12) +
(0,8 x 0,12) + (0,6 x 0,13)
Syahrul Rofiq Abdillah Fadli, Dwi Hartanti, Agustina Srirahayu
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 6, June 2024 2740
= 0,084 + 0,096 + 0,06 + 0,1 + 0,16 + 0,072 + 0,096 + 0,078
= 0.746
Targeting the results of the calculation of the Vi value for each prospective
employee who is an alternative in determining the acceptance of employees in
CV.sumber solusi bersama using the same formula, the ranking table can be compiled
as seen in Table 3.
Table 3. Ranking Determination
Alternative / kriteria
Vi
Rangking
Dita Adiguna, Amd
0,762
V
Wibisana Budi Iswara, S.Kom
0,727
VII
Nooryadi, S.Kom
0,836
I
Wisno Ajisudrajat, AMD
0,751
VI
Rizki Priakasa Setiaji, S.Kom
0,791
IV
Dhea kalingga, S.Kom
0,817
III
Rangga Waspada, S.Kom
0,709
VIII
Ahmad Kurniawan, S.Kom
0,798
II
3. Process Modeling
Unified Modeling Language, or UML, is used to model the design process in
research Ini. In industry, UML is used for design, analysis, and definition of needs. A
use case diagram that illustrates the relationship between actors and systems is one of
the UML diagrams generated (Setiyani & Setiawan, 2021). Two actors are involved in
the modeling of the recommendation system process: the admin and the user.
Administrators have the ability to add criteria, assign weights, manage prospective
employee data, run system operations, and view the results of prospective employee
decisions taken in the system. Picture 3 shows the process of designing this
recommendation system in the form of a use case diagram.
Picture 2. Use Case Diagram
The interface architecture of the decision-making system as a decision-maker in
selecting prospective employees is as follows, based on the results of the process
modeling in Picture 2:
a. System interface modeling
The main page of this system has a login page that can be used by the director of
CV.Sumber Solusi Bersama to enter the system, and there is also a page to display the
final results of the data for the names of prospective employees according to the ranking
set by the employee admission decision-making system, the interface can be observed in
Picture 4.
Decision Support System in Employee Admissions Using Simple Additive Weighting
Algorithm at CV.Sumber Solusi Bersama
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 6, June 2024 2741
b. Modeling of potential employee data interfaces
This page is used to record prospective employees and brief identities about each
prospective employee, this decision-making system records each prospective employee
according to an attachment containing the place of birth, photo, experience, and skills
possessed. The interface of the prospective employee data page is as seen in Picture 5.
c. Modeling the tpa results master data interface
This result page is used by the Director of CV Sumber Solusi Bersama to
display the score data of each assessment test criteria. The interface of the results page
of this decision support system is as seen in Picture 6.
d. Modeling the master data setting interface
The results page of this decision support system is used to display the weight
data that has been determined by the director of CV.Sumber Solusi Bersama, which
later this weight value data will be used to process employee data and the scores of each
criterion in order to get the ranking results used as a reference for employee admissions.
The interface is as seen in Picture 7.
e. Modeling of the process interface of the decision support system
The decision support system results page is used to display the final results
based on the value of each prospective employee that can be seen and exit the ranking
results according to the assessment of the decision support system and the weight data
that has been entered by the director of CV.Sumber Solusi Bersama. The interface can
be as seen in Picture 8.
4. Software testing
Software testing is the process of running and assessing software known as
software testing.
1. Software Test Case Design
Blackbox Testing includes the evaluation of the suitability, usability, and output
of the process with respect to the tasks performed by administrators in the decision
support system to select prospective employees.
2. Implementation.
Based on the software testing design described earlier, the following individuals
directly test the best employee selection decision support system: 1) the author, who is
responsible for testing the software functionality, testing the suitability of the system
process, and testing the correctness of the algorithm; 2) The Head of the General and
Press Subdivision who is in charge of testing the feasibility of the system and the
accuracy of the results. Here's a summary of the exam.
a. Blackbox testing
Blackbox testing is intended to test system functionality and compatibility
between input and output has been carried out on Tuesday, June 18, 2024. This test
went well, where the output produced by the system was in line with expectations.
b. White box testing
This test was carried out by the authors themselves according to the white box
test design, which seeks to evaluate the feasibility of implementing procedures and
Syahrul Rofiq Abdillah Fadli, Dwi Hartanti, Agustina Srirahayu
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 6, June 2024 2742
algorithms in the decision support system to select the best prospective employees. The
following are the results of the algorithmic testing of the employee selection decision
support system:
It
Algorithm name
Information
1
Setting up a rating matrix
Succeed
2
Normalizing the matrix
Succeed
3
Set the weight matrix
Succeed
4
Multiplication of the weight matrix by the
normalized maatric
Succeed
c. Testing the accuracy and feasibility of the system
On Tuesday, June 18, 2024, the accuracy and feasibility testing of the system
implementation has been completed. This test was carried out by a company represented
by the Director of CV Sumber Solusi Bersama. The test results show that the system
operates efficiently. Because system calculations and manual calculations are
compatible with each other. In addition, it was decided that a decision support system
for selecting the best personnel could be implemented. Software testing, which includes
Whitebox (algorithm correctness validation), Blackbox (functional and process
conformity validation), and System Accuracy and Feasibility testing, has been
successfully implemented. All test cases are found to be appropriate through
functionality and process compliance testing, which indicates that administrators should
handle this task. All algorithms have been implemented correctly, as evidenced by
algorithm accuracy testing. Furthermore, the accuracy test of the system's computing
output shows that the SAW calculations performed by the system are in accordance
with the calculations performed manually (Gunawan, Ariany, & Novriyadi, 2023).
Based on the feasibility test of the CV.Sumber Solusi Bersama software, CV can
implement an employee admission decision support system in CV.Sumber Solusi
Bersama.
Conclusion
Based on the results and discussion, it can be concluded that the decision support
system to select prospective employees is able to implement the Simple Additive
Weighting method well. In addition, the calculations made by the decision support
system for staff recruitment are proven to be in accordance with the calculations made
manually, thus demonstrating the accuracy and reliability of the system in assisting the
selection process of prospective employees.
Decision Support System in Employee Admissions Using Simple Additive Weighting
Algorithm at CV.Sumber Solusi Bersama
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 6, June 2024 2743
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