Journal of Electrical Engineering and Computer Sciences Vol.
Issue 2.
December 2020
ISSN: 2528-0260
SYSTEM FOR DETERMINING HOUSE CREDIT RECIPIENTS
BASED ON DATA OF COOPERATIVE MEMBERS USING
SIMPLE ADDITIVE WEIGHTING (SAW)
WIWIET HERULAMBANG, 2FARDANTO SETYATAMA, 3M ZULFIKKIH
Informatics Engineering Study Program.
Faculty of Engineering Bhayangkara University Ae Surabaya Jl.
A Yani 114.
Surabaya.
Telp, 031-8285602 e-mail : herulambang@ubhara.
id, 2fardanto@ubhara.
id, 3mochzulfikkih@gmail.
ABSTRACT
PMS Employee Cooperative is a savings and loan cooperative which aims to provide storage and loan services to employees who work at PT.
Pro Manunggal Solusi and does not yet have a Decision Support System (SPK).
A decision support system is needed in determining the eligibility of cooperative loans to employees.
This study aims to help simplify and accelerate and minimize errors that occur in the cooperative borrower feasibility assessment The method used for this decision is to use the Simple Additive Weighting (SAW) method.
Six criteria are used for the loan eligibility assessment process, namely criteria 1 (Loan siz.
, criterion 2 (Loan Purpos.
, criterion 3 (Salar.
, criterion 4 (Positio.
, criterion 5 (Ag.
, criterion 6 (Period of servic.
Based on the results of the calculation, it can be concluded that each loan employee will be approved according to the ranking and is limited by the balance.
If the balance is sufficient, the loan will be approved, but if the balance is less, the loan will be rejected.
Of the total value of the ranking results, loans approved with a sufficient balance were Susanto .
with a 12.
13% chance.
Sentot Sudiyantono .
with a probability of 11.
83%, and Siswandi .
with big chance 10.
Keywords: Decision Support System.
Simple Additive Weighting.
INTRODUCTION
The development of information technology has enabled decision making to be carried out quickly and This also applies to every government and private agency that needs a system to collect, process and review a decision.
One of the alternatives most likely to help complete work and handle the flow of large amounts of information, as well as help in making correct and accurate decisions is a computer.
Therefore, in an organization the use / utilization of computers should be maximized, including in the cooperative organization.
PMS Employee Cooperative is a savings and loan cooperative which aims to provide storage and loan services to every employee who works at PT.
Pro Manunggal Solusi and does not yet have a Decision Support System (SPK).
A decision support system is needed in determining the creditworthiness of a cooperative to an employee.
Therefore, we need a method that can process the calculation of the loan eligibility weight properly.
The method used for making this decision is the Simple Additive Weighting (SAW) method.
In connection with this, it is necessary to make a decision support system by analyzing employee data in the cooperative that existed in the previous year.
So that a more effective and efficient way is found to assist the cooperative in taking the right assessment for each employee.
In this final project, the topic chosen is "Determination of Home Loan Recipients Based on Data from Cooperative Members Using the Simple Additive Weighting (SAW) Method".
With the creation of a loan eligibility decision support system using the SAW method, it is expected to be able to help simplify and accelerate and minimize errors that occur in the process of assessing the feasibility of PMS Employee Cooperative borrowers.
DOI: https://doi.
org/10.
54732/jeecs.
Available online at: https://ejournal.
id/index.
php/jeecs Journal of Electrical Engineering and Computer Sciences Vol.
Issue 2.
December 2020
ISSN: 2528-0260
METHODOLOGY
Literature Review Designing a Decision Support System for Scholarship Admission with the SAW (Simple Additive Weightin.
Method (Sri Eniyati, 2.
Implementation of the Simple Additive Method.
Weighting in the Teacher Certification Decision Making System (Youllia Indrawaty.
Andriana.
Restu Adi Prasetya, 2.
Decision Support System.
SYSTEM PLANNING
1 Flowchart Figure 3.
Flowchart System The flowchart above (Figure 3.
illustrates the flow of the SAW Loan Feasibility DSS process 2 Context Diagram Figure 3.
Context Diagram In Figure 3.
2 the context diagram shows one user, namely an employee.
Before entering the system, you must first login by entering the username and pasword that have been registered in the database.
If you have entered the system, employees can see the ranking results.
The admin manages the operation of the decision support system, both creating, changing and storing data needed by the system to process data such as master data, view rankings, adjust SAW weights, view employee data, record borrower transactions, report transactions, and others.
Journal of Electrical Engineering and Computer Sciences Vol.
Issue 2.
December 2020
ISSN: 2528-0260
3 DFD Level 1 Figure 3.
DFD Level 1 DFD Level 1 above (Figure 3.
Calculating Normalized Matrices 3.
4 is a comprehensive picture of Tbl_Results Result Ranking Calculates the Normalization of Each Element flow of the system to be made.
For an explanation of DFD Level 1 in the loan eligibility system using the SAW method are as follows:
The flow of the employee and admin login process enters the username and password then the system processes it by checking the data in the database.
If the data is correct or valid, the admin and employees will go to the next page, according to the access rights they have.
Employees can see the ranking results.
Admin can control the flow of application calculations by determining the SPK and managing the data needed by the system such as employee data, loan data.
SAW weight data, yield data, transaction data, and credit data.
The SAW calculation process starts when the admin enters the data for each employee who applies for a loan into the system.
4 DFD Level 2 Process 2 The SAW SPK Process Figure 3.
DFD Level 2 Process 2 SPK SAW Process Figure 3.
is DFD Level 2 which is the translation of DFD Level 1.
The first stage is the admin gives weight to carry out the weight normalization process.
After forming the initial matrix, then calculating the normalized matrix to produce a normalized matrix.
The normalization results are then displayed in the ranking process after calculating the normalization of each element.
Then display the ranking in the results table that will be displayed by the admin.
6 ERD ( Entity Relationship Diagra.
ERD (Entity Relationship Diagra.
contains a collection of tables, where each table has a unique name and In each table, each data record organized in the same structure has a key field that will be a link between existing tables and those related to each other.
This system has 9 entities / tables, namely user, credit, employees, installments, finance, submissions.
SPK weights, matrices, and results.
Journal of Electrical Engineering and Computer Sciences Vol.
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ISSN: 2528-0260
Figure 3.
ERD (Entity Relationship Diagram 7 Calculation of Finding Weight The criteria for evaluating employees who are eligible for a loan are as follows:
Loan size = 0.
Loan Objectives = 0.
Salary = 0.
Position = 0.
Age = 0.
Working period = 0.
Table 3.
Employee Evaluation / Assessment Data From the assessment table, a rating table of the suitability of each alternative can be made for each criterion.
Table 3.
Match Rating Table Completion steps:
Weight vector: W = [.
, .
, .
, .
, .
, .
] .
Decision Matrix X based on the weight criteria:
Journal of Electrical Engineering and Computer Sciences Vol.
Issue 2.
December 2020 .
Matrix Normalization X Using equation 1:
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Journal of Electrical Engineering and Computer Sciences Vol.
Issue 2.
December 2020 From the results of the above calculations, it is obtained the normalized matrix R, namely :
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Journal of Electrical Engineering and Computer Sciences Vol.
Issue 2.
December 2020 .
Looking for the best alternative using equation 2 So the result of the ranking value is :
Rank 1: V3 = Susanto (Employee .
Rank 2: V1 = Refer to Wikno Handoko (Employee .
Rank 3: V5 = Wayan Suartana (Employee .
Rank 4: V2 = Subandi (Employee .
Rank 5: V4 = Bambang Hermanto (Employee .
Conclusions based on cooperative balances.
The balance amount is 10,000,000.
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Journal of Electrical Engineering and Computer Sciences Vol.
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December 2020 .
Loan Realization Plan .
Estimated Balance Current balance = 2,500,000 Next month = 3,061,111 Balance in 2 months = 3,622,222 Balance in 3 months = 4,183,333 Balance in 4 months = 4,744,444 Balance in 5 months = 5,305,555 Balance in 6 months = 5,866,666 Balance in 12 months = 9,233,333 Balance in 18 months = 11,200,000 SYSTEM VIEW Figure 4.
SPK Process Menu Display
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Journal of Electrical Engineering and Computer Sciences Vol.
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ISSN: 2528-0260
Figure 4.
SPK Results Menu Display Figure 4.
3 Initial Cash Setting Menu Display
RESULTS AND DISCUSSION
The experiment carried out was to carry out the SPK process on the data of employees who made loan To facilitate understanding in testing, the test is modeled in a table form as follows:
Cooperative Data Table 5.
is cooperative data containing the name of the cooperative, address, motto and balance of the Table 5.
Cooperative Data .
SPK Results without Cooperative Balance Limits Table 5.
is the result of SPK without limiting the balance of the cooperative, where the cooperative does not limit loans to every employee who applies for a loan.
The SPK 1 results table contains the Employee ID.
Employee Name, and the SPK Results.
Journal of Electrical Engineering and Computer Sciences Vol.
Issue 2.
December 2020
ISSN: 2528-0260
SPK Results with Cooperative Balance Limits Table 5.
is the result of SPK with a cooperative balance limit, where the cooperative limits loans to each employee who applies for a loan based on the ranking order and the cooperative balance.
The SPK 1 results table contains Rank.
Employee ID.
Employee Name.
SPK Results.
Size.
Cooperative Balance, and Information.
Table 5.
SPK Results 2 Journal of Electrical Engineering and Computer Sciences Vol.
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December 2020 .
Calculations on the Application .
Loan Data Figure 5.
Loan Data .
SPK Weight Matrix Figure 5.
SPK Weight Matrix .
Initial Matrix Figure 5.
Initial matrix .
Normalization Matrix Figure 5.
Normalization matrix
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Journal of Electrical Engineering and Computer Sciences Vol.
Issue 2.
December 2020 .
Ranking Results Figure 5.
Ranking Results .
Conclusion Figure 5.
Conclusion .
Manual Calculation Completion steps:
Vector weight: W = [.
, .
, .
, .
, .
, .
X Decision Matrix based on weight criteria:
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Journal of Electrical Engineering and Computer Sciences Vol.
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December 2020 Normalization of the X matrix using equation 1:
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Journal of Electrical Engineering and Computer Sciences Vol.
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December 2020
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Journal of Electrical Engineering and Computer Sciences Vol.
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December 2020
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Journal of Electrical Engineering and Computer Sciences Vol.
Issue 2.
December 2020 From the results of the above calculations, the normalized matrix R is obtained, namely:
Finding the best alternative using equation 2
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Journal of Electrical Engineering and Computer Sciences Vol.
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So the ranking results are: Rank 1: Susanto (Employee .
Rank 2: Sentot Sudiyantono (Employee .
Rank 3: Siswandi (Employee .
Rank 4: Sukahar (Employee .
Rank 5: Budi Santoso (Employee .
Rank 6: Atim Subagyo (Employee .
Rank 7:
Wayan Suartana (Employee .
Rank 8: Refer to Wikno Handoko (Employee .
Rank 9: Subandi (Employee .
Rank 10: Bambang Hermanto (Employee .
Percentage of Opportunities The percentage of opportunities for each loan application, namely:
Table 5.
Percentage Table Journal of Electrical Engineering and Computer Sciences Vol.
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Figure 5.
Pie Chart Analysis of the SPK Results The analysis carried out is to manually match the SAW calculation results using this application system whether it is appropriate or not.
From the results of the above calculations, it can be seen that the results obtained from the application system are in accordance with the SAW calculation manually.
Whereas in Table 6.
is the SPK result without the limit of the cooperative balance which only displays the ranking In Table 6.
is the SPK result with a cooperative balance limit stated in the Cooperative Data (Table 6.
Each employee loan will be approved according to the rank and limited by the balance.
So, after the ranking is done, then the loan size is added up according to the ranking order.
From the order of ranking and addition, you can know the loan is approved or rejected.
If the balance is sufficient, the loan will be approved, but if the balance is less, the loan will be rejected.
Of the total value of the ranking results, loans approved with a sufficient balance were Susanto .
with a 12.
13% chance.
Sentot Sudiyantono .
with a probability of 11.
83%, and Siswandi .
with big 80% .
CONCLUSIONS AND SUGGESTIONS
1 Conclusion This final project entitled "Decision Support System for Cooperative Loan Feasibility Based on Employee Data.
Using Simple Additive Weighting (SAW) Method.
Case Study: PT.
Pro Manunggal Solusi "aims to determine the creditworthiness of employees, so it can be concluded as follows :
Decision support system for loan eligibility for employees at PT.
Pro Manunggal This solution can provide appropriate results in making the decision making process more efficient.
The Simple Additive Weighting (SAW) method can be used for decision support systems.
Application of the Simple Additive Weighting (SAW) method to perform calculations to produce a value in accordance with the needs of the cooperative.
2 Suggestion After evaluating the system as a whole, it is hoped that this final project can be developed further with suggestions for development as follows:
For further determination, it is hoped that the system developed will perform other Decision Support System methods besides Simple Additive Weighting (SAW).
It is expected that the system developed further does not have a limit of only 6 criteria.
Journal of Electrical Engineering and Computer Sciences Vol.
Issue 2.
December 2020
ISSN: 2528-0260
REFERENCE