IMPLEMENTATION OF PROFILE MATCHING AND LINEAR INTERPOLATION METHODS FOR WEB-BASED EMPLOYEE SELECTION SYSTEM OF PT BERDIKARI MEUBEL NUSANTARA
Ariono Septian1, Dimas Wahyu Wibowo2, Ariadi Retno Ririd3
1,2 Informatics Engineering Study Program, Information Technology Department, Malang State Polytechnic
1[email protected], 2 [email protected], 3 [email protected]
Abstract
Recruiting employees by means of good selection can show the company's expertise to get competent candidates to support the company's performance well. Employee recruitment at PT BERDIKARI MEUBEL NUSANTARA is done manually and produces subjective decisions when the ability of prospective employees is not too different.In an effort to overcome these problems, this research was made to assist recruiters (HRD) in selecting and choosing prospective employees according to company needs, therefore researchers created a Decision Support System (DSS). In making this Decision Support System (DSS) using the Profile Matching method and Linear Interpolation, so that the method works well, several criteria for prospective employees are needed so that the method executes in the system and is able to provide alternative recommendations and according to company needs. The results of this study in the application of the Profile Matching method with Linear Interpolation can help users provide recommendations for prospective employees that are in line with what the company expects, the core factor and secondary factor values are very influential on the results of accuracy because they are used as a percentage, the results of the total score which will later be ranked those who get the highest total score will be recommended.
Keyword : Selection, Employee, Profile Matching , Linear Interpolation
1. Background
In the industrial era 4.0 like this, technological developments are increasing rapidly with the use of computers as a means of obtaining information and solving problems, the role of technology such as information systems is very important where information systems have become a friend in everyday life. To obtain maximum quality in a company must adopt information system technology in operational activities, especially in an effort to improve performance both in quantity and quality of human resources (Nicolas et al., 2021).
In a company, ability is also a benchmark or consideration so that the company is run according to procedures or according to plans. A company of any kind is founded with the hope that one day it will become a large and rapidly growing agency.
This hope is usually used as one of the visions for the future by considering many factors, both internal and external. The fact is that in order to develop according to what is desired, there are many obstacles that get in the way (Rakasiwi et al., 2021).
According to Nurhuda et al in the Business Administration Journal, recruitment is a two-way communication. Applicants want accurate information about what it's like to work in an
organization (Nurhuda et al., n.d.). Meanwhile, organizations really want accurate information about these applicants if they become employees in the future. Recruiting good employees is an opportunity to demonstrate the expertise of the company to get competent candidates(Purwantih et al., 2020).
Process of hiring new employees at PT BERDIKARI MEUBEL NUSANTARA is done manually so that it takes quite a long time and produces subjective decisions, especially if the prospective employees have abilities that are not much different. Conditions like this, if not addressed properly, will become a source of potential problems for the company in the future, both internally and externally to the company. In turn, if the new employee recruitment process is not positioned correctly, then the new employee candidates accepted do not meet the expected criteria, and will become a burden for the company in the future on an ongoing basis. (Erza, 2022).
Decision support system is a technological product that consists of a combination of individual intelligence sources with component capabilities to improve the quality of decisions. Decision support systems are also computer-based information systems for decision-making management that deal with semi-structural problems (Astuti, 2018).
Besides that, according to (Kelen) decision support system is a decision making process by using some data and certain models to solve some semi- structured problems. One method that can be used in making a decision-making system for hiring new employees is to use the Profile Matching method to provide recommendations in the form of new employees based on rank. By using the Profile matching method, it is possible to select new employees through predetermined criteria, by selecting the best alternative from a number of alternatives, then a ranking process is carried out to get the best alternative, namely new employees (R.
R. Santika, 2020). Profile matching is a method used in the comparison process between individual competitions and position competitions so that the differences can be identified. Apart from that according to (Kuswanto, n.d.), Profile matching is a very important process in human resource management (HR) where competencies (capabilities) required by a position are determined first. In this case, profile matching will be used in determining new employee candidates. In the profile matching process, broadly speaking, it is a process of comparing individual competitions to position competitions so that the differences can be identified. In addition, the Linear Interpolation method is also used which is a method for determining values between the ranges of values generated based on the function of the equation. By combining 2 points , then the point between the 2 points that has been determined will be a straight line approach and later a calculation can be carried out. Based on this explanation, the Linear Interpolation method will be used to calculate the weight value for each employee.
Based on the problems described above, the author proposes a thesis research with the title name
“IMPLEMENTATION OF PROFILE MATCHING AND LINEAR INTERPOLATION METHODS FOR WEB-BASED EMPLOYEE SELECTION
SYSTEM OF PT BERDIKARI MEUBEL
NUSANTARA”. In the research that will be carried out using a decision support system to make it easier for users to determine the best prospective employees according to company needs. Alternative decisions made will be very effective and accurate if using a decision support system application by determining several criteria such as age, gender, and others. The difference between the author and previous research is that there is an additional method in the form of linear interpolation which will support the profile matching method in making an objective and suitable decision according to needs.
2. Literature Review 2.1 Preview Research
1. Nicolas, Soetanto, Wahyudi, and Rossi conducted research on The Best Employee Selection
Decision Support System at PT. XYZ with the Profile Matching Method and Interpolation the main problem before In this research, employee assessment was carried out manually, of course Each appraiser has its own way of evaluating employees best. Thus causing the decision-making process requires long time and the results tend to be subjective. With problems This required a solution by creating a computerized system that helps decision makers select the best employees, i.e.
systems decision support (SPK) selection of the best employees at PT. XYZ using the Profile Matching and Interpolation methods. which variable used consists of Quality of Work, Quantity of Work, Discipline, Initiative, Motivation, Responsibility, Cooperation, Adaptation, Understanding of Tasks, Problem Solving, Leadership, and Decision Making.
Result of In this study, employee A099 on behalf of Dadap Hardiansyah received grades the highest, namely 3,875. So the employee is entitled to receive an award the best employees at PT. XYZ (Perdana et al., 2021).
2. Yohana Niis Molo1, Yoseph P.K Kelen, Yasinta O.L Rema conducted research at PT. NSS Kefamenanu. The problem with PT is that the process of hiring new employees is done manually so that it takes quite a long time and the company's managers are faced with a situation where the number of vacancies and prospective employees who are interested is still limited and the number of administrative requirements is many times what is needed. Such conditions if it is not addressed properly it will become a source of potential problems for the company in the future, both internally and externally to the company. In turn, if the process of accepting new employees is not positioned correctly, then the new employee candidates accepted do not meet the expected criteria, and will become a burden for the company in the future on an ongoing basis. Therefore the researcher builds an employee database as a support for decision making through a a decision support system to provide an objective assessment in the selection of prospective employee candidates. There are 3 aspects that become benchmarks for employee assessment in which each of the 3 criteria is used as a comparison reference and later used for the calculation process within the gap as well as the calculation of the final score for candidate ranking employees. With the calculation process that has been carried out, namely the process of looking for gaps and weights and multiplying each aspect with a predetermined percentage, the final score for Nova Naiheli is 3.7775.
3. Previously there had been research related to this research conducted by (Bernadhed, 2018) entitled “Implementation of a Decision Support System for Selection of New Employees with the Profile Matching Method” found ranking results using three criteria, namely cognitive criteria,
personality criteria, and work attitude criteria. These three criteria can be used to rank based on the number of core factors and secondary factors.
Related research was also carried out by (Fitriyani, 2019) which aims to get the right employees for a certain position, so that these employees are able to work optimally and can survive in the company for quite a long time. using 3 aspects of the 5 prospective new employee applicants. From these results applicant 1 as a prospective employee gets the best results with a weight of 4.9.
2.2 Decision Support System
Decision Support Systems, or in English better known as Decision Support Systems are usually built to support a solution to a problem or to an opportunity. Basically the decision support system is a further development of a computerized management information system that is designed in such a way that it is interactive with the user. This interactive nature is intended to facilitate integration between various components in the decision-making process, such as procedures, policies, analytical techniques, experience and managerial insights to form a flexible and accurate decision framework.(Kuswanto, n.d.).
2.3 Profile Matching
Profile matching is a very important process in human resource management (HR) where competencies (capabilities) required by a position or department are first determined. In this case, profile matching will be used in determining new employee candidates. In the profile matching process, in general, it is a process of comparing individual competitions to position competitions so that the differences can be identified (Kuswanto, n.d.).
Profile Matching (PM) method is a method of comparing individual competencies with ideal job competencies so that differences in competence are known (Tri Susilo, 2018). the smaller the value of the gap generated, the greater the value weight, which means that a person has a greater chance of getting a position (Nashrullah et al., 2016).
There are several stages of completion in the Profile Matching method, namely:
1. Determine aspects (criteria) and ideal value of each criterion.
2. GAP calculation (The difference between the profiles of each alternative and the standard profile or criterion value minus the ideal value
𝐺𝑎𝑝 = Criteria Value – Ideal Value (1) 3. Mapping GAP value
Table 2. 1 Mapping Gap Value
4. Core Factor (CF) and Secondary Factor (SF) grouping in this profile matching method
NCF = ∑NC
∑N Description:
NCF : Core factor average value NC : Total value of the core factor C : Total of core factor items While the secondary factor aspect is an aspect other than the primary factor. Calculation is as follows
NSF = ∑NS
∑N Description:
NCF : Secondary factor average value NC : Total value of the second factor C : Total of secondary factor items 5. Calculation of Total Value (NT) value is
obtained from the percentage of Core Factor (CF) and Secondary Factor (SF)
𝑁𝑡 = 𝑋% 𝑁𝐶𝐹 + 𝑋% 𝑁𝑆𝐹 (4) Description:
Nt : Total value
NCF : Core factor average value NSF : Secondary factor average value X% : Input percentage value
Ranking is done after the total aspect value is known, then the final stage is ranking. Ranking is obtained by sorting the highest total value to the lowest. Rank 1 object with the highest total value means that the object has the best performance and is entitled to receive the best object award.
2.4 Linear Interpolation
Interpolation is a way of determining the value that is between two known values based on an equation function. Interpolation is one of the easiest and most widely used value determination techniques to solve various problems, from ancient astronomy to the era of digital image processing.
Linear interpolation is a way of determining a value that is between two known values based on a linear equation (Meijering, 2002).
Linear equations are also called straight line equations because if the results of a linear equation are depicted on graph paper, the shape of the curve
is a straight line. Linear interpolation is based on comparison theory:
Picture 2. 1 Linear Interpolation
Weight value is the number assigned to each criterion whose value is determined based on the results of linear interpolation.
W(x) = 𝑥−𝑥1
𝑥0−𝑥1(𝑚𝑎𝑥 − 𝑚𝑖𝑛) + 𝑚𝑖𝑛 (5) Description:
W(x) : Weight value for the input value x 𝑥 : Parameter values (values before interpolation) are derived from values
𝑥0 : Smallest value range of parameter values 𝑥1 : Largest value range of parameter values Max : Highest rating value of the assessment
parameters for each criterion
Min : The lowest rating value of the assessment parameters for each criterion.
3. Research Methods 3.1 Resources Data
At the data collection stage used in this development, namely the face-to-face process directly to the working staff, the head of HRD PT Berdikari Meubel Nusantara. The data to be retrieved is data related to feature requirements that will be implemented in a web-based decision support system for selecting prospective employees.
The data requirements to be retrieved are data related to features in the PT Berdikari Meubel Nusantara web-based decision support system such as access rights, determining criteria, core data and configuration factors.
3.2 Development Method
Software development method used in this study is the SDLC (Software Development Life Cycle) method with a prototyping model approach.
Picture 3. 1 System Development Scenario
4. Result and Discussion 4.1 Data
At the data collection stage used in this development, namely the face-to-face process directly to the working staff, the head of HRD PT Berdikari Meubel Nusantara. The data to be retrieved is data related to feature requirements that will be implemented in a web-based decision support system for selecting prospective employees.
The data requirements to be retrieved are data related to features in the PT Berdikari Meubel Nusantara web-based decision support system such as access rights, determining criteria, core data and configuration factors.
4.2 Data Processing Techniques
Data processing is carried out when the manual preference value and the actual choice preference value are inputted, then the system can perform data processing until the results of the recommendation for the selection of prospective employees come out through the results of the ranking of prospective employees recommended by the system. Input data from the user to the system will be processed using the profile matching method with linear interpolation with the scenario shown below :
Picture 4. 1 Data Processing Techniques 1. Starting with inputting the criteria according to the preferences of the user / HRD in the selection of prospective employees. The data that is entered is the actual data of the prospective employees where the actual data means the real data that exists.
2. Calculation of the gap value with an analysis of the actual value of the input and the ideal value. In this study using 12 criteria along with their ideal values, as follows
Pada penelitian ini terdapat 12 kriteria calon karyawan dan nilai idealnya, sebagai berikut:
Table 4. 1 Ideal Score Table
3. Identification related to input and grouped based on core and secondary factors.
Table 4. 2 Core and Secondary Factor
Then the magnitude of each core factor and secondary factor must also be determined. Here's the table:
Table 4. 3 Tabel Besaran Factor
4. Below is the actual value of each prospective employee that will be selected by the company. The range of scores that will be given is between 1 to 5, where each criterion is experience as, how long has the experience been, linear experience with the job candidate how long, age, education, gender, certification, additional skills, confidence and communication, leadership and directing others, integrity and commitment, as well as motivation and achievement. These values will be used as samples to determine gaps in the profile matching method.
Table 4. 4 Actual value of prospective employee
5. GAP calculation and mapping
After getting the GAP value, the next step is to give a score for each value criterion gap.
Table 4. 5 GAP calculation and mapping table
6. Convert the Profile Matching weight value Table 4. 6 Convert Profile Matching weight value
7. Calculation of weight values using the linear interpolation method
Then the weight data using the profile matching method will be processed again for a more accurate and appropriate weight determination using the linear interpolation method.With the sample example on employee code A001. Then the result is.
Table 4. 7 Interpolation weight value of prospective employees
Dengan menggunakan proses perhitungan pada tabel 3.7 diatas, didapatkan hasil sebagai berikut:
Table 4. 8 bobot interpolasi kriteria
8. Calculation of Core Factor and Secondary Factor values for each prospective employee
The next stage is to find the value of the core factor and secondary factor. An example of how to calculate it using prospective employee A001 as an example is as follows:
Table 4. 9 Core Factor dan Secondary Factor prospective Employee A001
Based on the grouping of core factors and secondary factors in the table of core factors and secondary factors for prospective employee A001, the core factor (NCF) for prospective employee A001 is as follows :
Kode S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12
A001 3 4 2 5 3 3 3 3 1 4 5 5
A002 3 4 5 1 2 3 4 4 1 1 4 4
A003 5 3 4 3 2 5 5 3 1 4 1 3
A004 3 4 1 2 2 1 1 5 5 1 4 1
A005 3 4 1 5 4 4 3 4 3 5 2 3
A006 3 5 5 2 2 3 5 5 2 3 5 4
A007 5 2 3 4 1 2 2 1 3 4 3 1
A008 4 3 3 1 1 1 1 3 3 4 3 3
A009 1 5 2 2 2 4 1 4 3 3 2 2
A010 2 2 2 1 4 5 5 5 4 2 4 5
A012 4 2 4 4 1 1 2 1 2 3 1 1
Nilai Aktual Kriteria S1 - S12
Kode S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12
A001 3 4 2 5 3 3 3 3 1 4 5 5
A002 3 4 5 1 2 3 4 4 1 1 4 4
A003 5 3 4 3 2 5 5 3 1 4 1 3
A004 3 4 1 2 2 1 1 5 5 1 4 1
A005 3 4 1 5 4 4 3 4 3 5 2 3
A006 3 5 5 2 2 3 5 5 2 3 5 4
A007 5 2 3 4 1 2 2 1 3 4 3 1
A008 4 3 3 1 1 1 1 3 3 4 3 3
A009 1 5 2 2 2 4 1 4 3 3 2 2
A010 2 2 2 1 4 5 5 5 4 2 4 5
A012 4 2 4 4 1 1 2 1 2 3 1 1
Nilai Standart 4 3 3 3 3 3 4 3 3 3 4 3
A001 -1 1 -1 2 0 0 -1 0 -2 1 1 2
A002 -1 1 2 -2 3 0 0 1 -2 -2 0 1
A003 1 0 1 0 0 2 1 0 -2 1 -3 0
A004 -1 1 -2 -1 3 -2 -3 2 2 -2 0 -2
A005 -1 1 -2 2 0 1 -1 1 0 2 -2 0
A006 -1 2 2 -1 3 0 1 2 -1 0 1 1
A007 1 -1 0 1 0 -1 -2 -2 0 1 -1 -2
A008 0 0 0 -2 3 -2 -3 0 0 1 -1 0
A009 -3 2 -1 -1 0 1 -3 1 0 0 -2 -1
A010 -2 -1 -1 -2 3 2 1 2 1 -1 0 2
A012 0 -1 1 1 0 -2 -2 -2 -1 0 -3 -2
Nilai Aktual Kriteria S1 - S12
Kode S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13
A001 4 4,5 4 3,5 5 5 4 5 3 4,5 4,5 3,5 3,5
A002 4 4,5 3,5 3 4 5 5 4,5 3 3 5 4,5 4,5
A003 4,5 5 4,5 5 4 3,5 4,5 5 3 4,5 2 5 5
A004 4 4,5 3 4 4 3 2 3,5 3,5 3 5 3 3
A005 4 4,5 3 3,5 4,5 4,5 4 4,5 5 3,5 3 5 5
A006 4 3,5 3,5 4 4 5 4,5 3,5 4 5 4,5 4,5 5
A007 4,5 4 5 4,5 3 4 3 3 5 4,5 4 3 4,5
A008 5 5 5 3 3 3 2 5 5 4,5 4 5 4,5
A009 2 3,5 4 4 4 4,5 2 4,5 5 5 3 4 5
A010 3 4 4 3 4,5 3,5 4,5 3,5 4,5 4 5 3,5 4,5
A012 5 4 4,5 4,5 3 3 3 3 4 5 2 3 4
Nilai Bobot Kriteria S1 - S12
Kode S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13
A001 3,5 3,25 3,5 3,75 3 3 3,5 3 4 3,25 3,25 3,75 3,75
A002 3,5 3,25 3,75 4 3,5 3 3 3,25 4 4 3 3,25 3,25
A003 2,375 2 2,375 2 2,75 3,125 2,375 2 3,5 2,375 4,25 2 2
A004 2,75 2,375 3,5 2,75 2,75 3,5 4,25 3,125 3,125 3,5 2 3,5 3,5
A005 3,5 3,25 4 3,75 3,25 3,25 3,5 3,25 3 3,75 4 3 3
A006 3,875 4,0625 4,0625 3,875 3,875 3,5 3,6875 4,0625 3,875 3,5 3,6875 3,6875 3,5
A007 3,25 3,5 3 3,25 4 3,5 4 4 3 3,25 3,5 4 3,25
A008 2 2 2 3,5 3,5 3,5 4,25 2 2 2,375 2,75 2 2,375
A009 4,25 3,125 2,75 2,75 2,75 2,375 4,25 2,375 2 2 3,5 2,75 2
A010 4 3,5 3,5 4 3,25 3,75 3,25 3,75 3,25 3,5 3 3,75 3,25
A012 2 2,75 2,375 2,375 3,5 3,5 3,5 3,5 2,75 2 4,25 3,5 2,75
Nilai Bobot Kriteria Interpolasi S1 - S12
Nilai Bobot Interpolasi Secondary factor Nilai Bobot Interpolasi
Education (S1) 3,5 Gender (S3) 3,25
Age (S2) 3,5
How Long is the Linear Experience With That Field
(S7)
3
Apply For Division
(S6) 4
Leadership , Directing , and Developing Others
(S11)
3,25
3,25 Integrity and
Commitment (S12) 3,75 Additional Skills
Confidence and Communication
Experience As(S4) 3,75 3,5
Apply Job As Position
(S5) 3 3
Certification (S8)
NCF = 3.5 + 3.5 + 3.75 + 3 + 4 + 3.25
6 = 3.5
Meanwhile, the secondary factor (NSF) value for prospective A001 employees is as follows:
NSF = 3.25 + 3 + 3.5 + 3 + 3.25 + 3.75
7 =3.291
Meanwhile, the secondary factor (NSF) value for prospective A001 employees is as follows:
Table 4. 10 Core Factor and Secondary Factor score
9. Calculation of the total value of each prospective employee
After the NCF and NSF of each employee candidate is known, the next step is to find the total value of NCF and NSF using employee candidate A001 as an example of calculation, as follows :
𝑁𝑡 = 0.75 ∗ 𝑁𝐶𝐹 + 0.25 ∗ 𝑁𝑆𝐹 𝑁𝑡 = (0.75 ∗ 3.5) + (0.25 ∗ 3,29167)
𝑁𝑡 = 3,447
75% for the Core Factor and 25% for the Secondary Factor comes from the input value from the researcher
By using the calculation method above, the NCF and NSF of each ka candidate are as follows:
Table 4. 11 Total value of each prospective employee
10. Determining the ranking of the best prospective employees After knowing the total value of each prospective employee, the final stage is to rank by sorting the highest total value to the smallest total value. Prospective employees with the largest total value are prospective employees who have the
potential to be recruited by students. The following is the ranking table.
Table 4. 12 Prospective Employee Ranking
4.3 Testing
a. System Functional Testing i. Reccomendation Table 4. 13 Functional Testing Recommendations
ii. Change Password Table 4. 14 Change Password Functional Testing
b. User Acceptance Testing Table 4. 15 System assessment questionnaire table
Result every question :
Is the website interface easy to use??
Based on the score above, it is calculated by an average with the following calculation
(1x0) + (2x0) + (3x0) + (4x0) + (5x3) / 3 = 5
Kode NCF NSF Nt A001 3,5 3,291667 3,447917 A002 3,791667 3,125 3,625 A003 2,5625 2,625 2,578125 A004 3,0625 3,125 3,078125
A005 3,541667 3,375 3,5
A006 3,84375 3,78125 3,828125 A007 3,291667 3,75 3,40625 A008 2,5625 2,75 2,609375 A009 2,75 3,0625 2,828125 A010 3,583333 3,5 3,5625
A012 2,5 3,5 2,75
Kode NCF NSF Nt Ranking
A001 3.5 3.291667 3.447917 5
A002 3.791667 3.125 3.625 2
A003 2.5625 2.625 2.578125 11
A004 3.0625 3.125 3.078125 7
A005 3.541667 3.375 3.5 4
A006 3.84375 3.78125 3.828125 1
A007 3.291667 3.75 3.40625 6
A008 2.5625 2.75 2.609375 10
A009 2.75 3.0625 2.828125 8
A010 3.583333 3.5 3.5625 3
A012 2.5 3.5 2.75 9
Kode NCF NSF Nt Ranking
A001 3.5 3.291667 3.447917 5
A002 3.791667 3.125 3.625 2
A003 2.5625 2.625 2.578125 11
A004 3.0625 3.125 3.078125 7
A005 3.541667 3.375 3.5 4
A006 3.84375 3.78125 3.828125 1
A007 3.291667 3.75 3.40625 6
A008 2.5625 2.75 2.609375 10
A009 2.75 3.0625 2.828125 8
A010 3.583333 3.5 3.5625 3
A012 2.5 3.5 2.75 9
Are all the features on the website easy to operate ?
Based on the score above, it is calculated by an average with the following calculation
(1x0) + (2x0) + (3x0) + (4x1) + (5x2) / 3 = 4,6
Are the calculation results are as expected by entering the appropriate criteria ? Based on the score above, it is calculated by an average with the following calculation
(1x0) + (2x0) + (3x0) + (4x0) + (5x3) / 3 = 5
Is the recommendation feature function easy to use ?
Based on the score above, it is calculated by an average with the following calculation
(1x0) + (2x0) + (3x0) + (4x0) + (5x3) / 3 = 5
Are the business process or program flow is as expected by the partner (PT Berdikari Meubel Nusantara) ?
Based on the score above, it is calculated by an average with the following calculation
(1x0) + (2x0) + (3x0) + (4x0) + (5x3) / 3 = 5
5. Conclusion and Suggestion
Based on the research results from the implementation of the Profile Matching method with Linear Interpolation, the conclusions are obtained:
1. Making a recommendation support system for selecting prospective employees using the Profile Matching method with Linear Interpolation based on the problems experienced by PT Berdikari Meubel Nusantara, namely the manual selection process takes quite a long time and produces subjective decisions, especially if the prospective employees have abilities that are not much different , therefore a decision support system was created aimed at providing the right candidate employee recommendations for PT Berdikari Meubel Nusantara as needed.
2. The proposed decision support system can produce a recommendation ranking for the best prospective employees for PT Berdikari Meubel Nusantara.
3. Criteria for prospective employees that are in accordance with the user's ideal assessment can produce the same value according to the calculations and execution in the system.
4. The test results show that the user interface of the decision support system is in accordance with user expectations.
From the results of research on the recommendation system for selecting prospective employees using the profile matching method with linear interpolation, there are still some deficiencies. Suggestions that can be given for the development of this application in the future are :
1. Further research can be carried out by creating programs or features for selected candidates to make it easier to view sorted and selected data.
2. Subsequent developments can be carried out by separating employees according to the divisions that have been sorted.
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