Advance Sustainable Science.
Engineering and Technology (ASSET) Vol.
No.
April 2023, pp.
0230108-01 0230108-08
ISSN: 2715-4211 DOI: https://doi.
org/10.
26877/asset.
v5i1/15062 Analysis Determination of the Best Employee with Simple Additive Weighting Method Haryo Kusumo*.
Achmad Solechan.
Febryantahanuji Faculty of Vocational Studies.
Universitas Sains dan Teknologi Komputer.
Jl.
Majapahit 605 Semarang.
Central Java.
Indonesia *haryo@stekom.
Abstract.
In a company, quality human resources are very important to carry out business processes in accordance with the vision and mission that has been set.
CV.
Jaya Abadi is a company engaged in the procurement and repair services of various electronic devices and was founded in 2015.
The purpose of this research is to encourage the creation of continuously increasing performance productivity by selecting the best employees at CV.
Jaya Abadi.
One of the methods used is the Simple Additive Weighting (SAW) method.
In the SAW method, there is a process of normalizing the decision matrix .
on a certain scale that can be compared with all existing ratings.
In this study, the data used consisted of internal data and external data.
There are several criteria that are taken into consideration in selecting the best employees, namely discipline, quality of work, cooperation, and behavior.
Based on the calculation of all existing criteria and alternatives, this study resulted in Abiyasa Alfarizi being the best employee with a total preference score of 1.
The SAW method is proven to be effective and practical in calculating to determine the best employee recommendations at CV.
Jaya Abadi.
Thus, decision makers can consider these recommendations according to the priorities set.
Keywords: Decision Support System.
Selection of the Best Employees.
Simple Additive Weighting (Received 2023-03-27Accepted 2023-04-20.
Available Online by 2023-04-.
Introduction CV.
Jaya Abadi is a private company that was established in 2015 and focuses on procurement and repair services for various electronic devices.
CV.
Jaya Abadi is a company that is growing and prioritizes quality in the procurement of electronic equipment and repair services.
Quality human resources is one of the important factors in running a company or business well .
Human resources have a very important role in the field of production, development and progress of a company.
If the human resources are of poor quality, it will be difficult for the company to achieve the vision, mission, goals and objectives that have been set .
Therefore, human resources must have a variety of competencies that can support and encourage an increase in employee productivity and performance.
addition, it is necessary to provide rewards or awards to employees as motivation to be more positive and work better .
In order to realize this.
CV.
Jaya Abadi requires an information system that can assist companies in selecting and deciding the best employees effectively according to certain criteria.
One of the previous studies related to the research to be carried out is "Decision Support System for Selection of the Best Employees Using the Analytical Hierarchy Process Method (Case Study at PT.
Bando Indonesi.
This study uses the AHP method, in which each criterion and decision alternative is compared to one another to provide a priority intensity value that assesses the performance of outstanding employees.
In addition, researchers also reviewed previous research entitled "The Best Employee Selection Recommendation System with the TOPSIS Method on Bussan Auto Finance".
This study used the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, which is one of the methods used in making decisions with multi-criteria.
The aim is to determine the relative proximity of an alternative that has an optimal solution by selecting the alternative that has the shortest distance from the positive ideal solution and the farthest distance from the negative ideal solution from a geometric point of view.
Through the SAW (Simple Additive Weightin.
method, this study aims to simplify CV.
Jaya Abadi in selecting the best employees according to the company's criteria.
By taking into account preference weights and match ratings, problems in selecting the best employees can be resolved and all alternative ratings can be compared objectively to achieve results that are in line with expectations.
Methods The data used in this study came from external data and internal data collected in several ways, such as searching for data directly in the field, conducting interviews with employees and management of CV.
Jaya Abadi, as well as conducting literature studies.
The criteria to be used are the alternatives to be compared.
There are six alternatives and four criteria that will be analyzed through fuzzy weighting.
Furthermore, the data will be processed so that it has a quantitative nature.
This study aims to make it easier for companies to choose the best employees according to company criteria using the SAW (Simple Additive Weightin.
method and provide objective results and in accordance with expectations.
The methods that can be used in decision support systems are quite diverse.
One of them is the SAW method, which is a weighted sum method.
In the SAW method, there is a process of normalizing the decision matrix .
on a certain scale that can be compared with all existing ratings.
, as seen in the equation below.
ycuycnyc ycAycaycu ycuycnyc ycycnyc = ycAycnycu ycu ycnyc ycu ycnyc Information:
ycycnyc = normalized performance rating value ycuycnyc = attribute value owned by each criterion ycAycaycu ycuycnyc = the largest value owned by each criterion ycAycnycu ycuycnyc = the smallest value that is owned by each criterion Where rij is the normalized performance rating of the Ai alternative on the Cj attribute.
i = 1,2,3A,m and j = 1,2,3,A,n.
In determining the preference value in each alternative (V.
the following equation is used:
ycu ycOycn = Oc yc=1 ycyc ycyc Information:
ycOycn = rating for each alternative ycOyc = weight value for each alternative ycycnyc = normalized performance rating value If ycOycn has the greatest value, this means that alternative yaycn is the best alternative.
Figure 1 is a flowchart of the SAW method.
Start Determining Criteria Determining The Weight Of Each Criterion Providing A Suitability Rating Value Matrix Normalization Ranking The Recommended Alternative Results Figure 1.
SAW Method Flowchart Figure 1 is the completion steps using the SAW (Simple Additive Weightin.
method based on the SAW method flowchart.
A value is given to each alternative .
aycn ) on each predetermined criterion .
ayc ), where the value ycn = 1,2,3,.
,yco and yc = 1,2,3,.
,ycu.
The decision maker assigns a weight value .
cO) to each criterion.
Calculation of the normalized performance rating value for attribute C of each alternative Ai is performed to normalize the matrix.
The ranking process is carried out by multiplying the preference weight value with the normalized The preference value is determined by the sum of the multiplication results between the preference weights and the normalized matrix.
In this study, a multi-attribute decision making (MADM) approach was applied to find alternatives that meet certain criteria and are optimal.
The MADM approach is carried out in two steps.
Aggregating decision alternatives for each objective in each alternative.
Ranking the alternatives based on decision aggregation.
The results of this study will provide recommendations for the best employees based on four criteria, namely cooperation, quality of work, discipline, and behavior.
This recommendation information will be given to the management of CV.
Jaya Abadi to be taken into consideration in selecting the best employees.
This process is carried out using the SAW method which processes input from users to produce a list of the best employee recommendations.
Results and Discussion Determination of Criteria In determining the best employee using the SAW method, the first step is to determine the criteria and weights.
These criteria are obtained from the results of observations at CV.
Jaya Abadi.
In Table 1 and Table 2 are the criteria and alternatives that have been obtained in determining the best employees:
Table1.
Criteria Criteria Discipline Quality of Work Cooperation Behavior Table2.
Alternatives Alternatives Wahyu Ardito Jamaluddin Nana Triahapsari Rani Febriyana Abiyasa Alfarizi Ahmad Chaerudin In table 3 there are 5 .
Fuzzy numbers for criterion weights, namely:
Table3.
Fuzzy Numbers Weight Information Very Low Low Moderate Very High Determination of Weigh of Each Criterion Before determining the best employees using the SAW method, it is necessary to determine the criteria and weights first.
These criteria were obtained through observations at CV.
Jaya Abadi.
The following are the criteria and alternatives that have been obtained to determine the best employees.
There are 2 weightings used in this system, namely the importance level weighting and the suitability level weighting contained in each alternative.
Match level weighting aims to simplify data processing and then convert it into a fuzzy form.
The following is the weighting for each criterion.
Table 4 is a nursery with criteria C1.
C2.
C3.
C4.
Ae Discipline.
Quality of Work.
Cooperation.
Behavior Table4.
Weighting Value Mark Information Discipline Quality of Work Cooperation Behavior Assign a Match Rating After setting all the criteria, the next step is to match the values of each alternative based on the criteria.
From these employees the best employee will be selected, alternative data can be seen in table 5 below:
Table 5.
Match Rating Value Alternative Criteria Very High Very High Very High Very High Very High Very High Very High Very High Very High Very High Very High The decision matrix x is formed from the table above and then converted into fuzzy numbers in Table 6 below.
Table6.
Alternative Match Rating on Criteria Alternative Criteria Matrix Normalization The purpose of using the data in table 6 in the matrix normalization process is to obtain calculation results for each criterion.
Meanwhile.
Table 7 below shows the results of calculations for each criterion.
Table7.
Normalized Matrix Alternative Criteria Ranking of Alternative Recommendation Result After normalizing the matrix, the next step is to multiply each normalized value with the appropriate criterion weight.
Then, the results are summed and ranked.
The alternative with the highest value is considered the best recommendation in decision making.
The importance level of each criterion is used as the basis for giving weight by management.
ycO = 0.
Next, calculations are carried out using Equation 2 and adding up the multiplication results to get the best alternative recommendation.
ycO1 = .
35 ycu 0.
35 ycu 0.
35 ycu 0.
35 ycu 1.
= 1.
ycO2 = .
35 ycu 1.
35 ycu 0.
35 ycu 0.
35 ycu 1.
= 1.
ycO3 = .
35 ycu 0.
35 ycu 1.
35 ycu 1.
35 ycu 0.
= 1.
ycO4 = .
35 ycu 1.
35 ycu 0.
35 ycu 0.
35 ycu 0.
= 1.
ycO5 = .
35 ycu 1.
35 ycu 1.
35 ycu 0.
35 ycu 1.
= 1.
ycO6 = .
35 ycu 1.
5 ycu 0.
35 ycu 0.
= 1.
Below is table 8 which displays the ranking calculation results of the alternatives that have been calculated previously.
The alternative with the biggest V5 value is alternative A5, which can be considered as the best alternative.
Based on the data in table 8.
Abiyasa Alfarizi has the highest V5 score, so he can be recommended as the best employee at CV.
Jaya Abadi.
Table8.
Total Preference Value Alternative Criteria The final result Conclusion The SAW method can be used in a decision support system to select the best employees at CV.
Jaya Abadi.
Criteria and sub-criteria data in this study are dynamic and can be changed according to the needs of decision makers.
Service orientation criteria have the biggest contribution in determining the best Abiyasa Alfarizi was chosen as the best employee with a total score of 1.
The SAW method is effective and practical in determining the best employee recommendations so that decision makers can consider these recommendations with a predetermined priority.
References