scholarly journals Perbandingan Metode Smart dan Maut untuk Pemilihan Karyawan pada Merapi Online Corporation

2021 ◽  
Vol 8 (6) ◽  
pp. 1205
Author(s):  
Musri Iskandar Nasution ◽  
Abdul Fadlil ◽  
Sunardi Sunardi
Keyword(s):  
Decision Making ◽  
Employee Selection ◽  
Decision Makers ◽  
Criteria Weights ◽  
Multi Attribute Decision Making ◽  
Waterfall Model ◽  
Ranking Order ◽  
Alternative Ranking ◽  
And Function ◽  
Employee Data

<p>Penelitian ini merancang sistem untuk menentukan pemilihan karyawan terbaik menggunakan Sistem Pendukung Keputusan (SPK). Perhitungan sistem menggunakan metode SMART dan MAUT. SMART merupakan metode pengambilan keputusan multiatribut yang setiap alternatif terdiri dari sekumpulan atribut dan setiap atribut mempunyai nilai-nilai. Sedangkan MAUT didasarkan pada konsep dimana pembuat keputusan dapat menghitung utilitas dari setiap alternatif menggunakan fungsi MAUT dan dapat memilih alternatif dengan utilitas tertinggi. Metode SMART digunakan karena perhitungannya lebih sederhana dan memungkinkan penambahan serta pengurangan alternatif tanpa mempengaruhi perhitungan pembobotan mengingat jumlah karyawan bisa berkurang dan bertambah secara tidak teratur. Sedangkan metode MAUT digunakan karena memunculkan hasil urutan peringkat dimana akan muncul hasil nilai terbesar sampai nilai terkecil sehingga dapat diketahui karyawan dengan terbaik dengan nilai tertinggi. Sehingga dapat mengambil keputusan dengan efektif atas persoalan yang kompleks dengan menyederhanakan dan mempercepat proses pengambilan keputusan. Metode penelitian yang digunakan adalah metode pengembangan sistem model waterfall, metodologi ini terdapat tahapan-tahapan kegiatan yang harus dilakukan dalam merancang suatu sistem. Perhitungan menggunakan 30 sampel data karyawan dan empat kriteria penilaian. Empat kriteria tersebut adalah presensi dengan bobot 40, masa kerja dengan bobot 30, ijin dengan bobot 20, dan disiplin dengan bobot 10. Data karyawan yang digunakan adalah karyawan yang sama dalam kedua metode serta mempunyai data penilaian yang sama. Hasil perhitungan menggunakan SMART dan MAUT menunjukkan bahwa keduanya dapat diimplementasikan dan berfungsi dengan baik untuk menentukan karyawan terbaik. Dengan menggunakan data alternatif, nilai alternatif, dan bobot kriteria yang sama diperoleh hasil bahwa metode SMART memberikan hasil yang lebih baik dengan 22 peringkat, sedangkan metode MAUT menghasilkan 18 peringkat. Semakin banyak jumlah peringkat yang muncul maka semakin baik karena mampu meminimalisir nilai preferensi yang sama, sehingga perankingan alternatif dapat dilakukan dengan baik.</p><p> </p><p><em><strong>Abstract</strong></em></p><p class="Judul2"><em>This study designed a system to determine the best employee selection using a Decision Support System (SPK). System calculations using the SMART and MAUT methods. SMART is a multi-attribute decision making method in which each alternative consists of a set of attributes and each attribute has values. Whereas MAUT is based on the concept where decision makers can calculate the utility of each alternative using the MAUT function and can choose alternatives with the highest utility. The SMART method is used because the calculation is simpler and allows the addition and subtraction of alternatives without affecting the weighting calculation given the number of employees can be reduced and increased irregularly. While the MAUT method is used because it raises the ranking order results in which the largest value will appear until the smallest value so that it can be known by the employee with the highest value. So that they can make decisions effectively on complex issues by simplifying and accelerating the decision making process. The research method used is the method of developing the system waterfall model, this methodology there are stages of activities that must be carried out in designing a system. The calculation uses 30 employee data samples and four assessment criteria. The four criteria are presence with a weight of 40, tenure with a weight of 30, permission with a weight of 20, and discipline with a weight of 10. Employee data used are the same employees in both methods and have the same assessment data. The results of calculations using SMART and MAUT indicate that both can be implemented and function properly to determine the best employees. By using alternative data, alternative values, and the same criteria weights, the results obtained that the SMART method gives better results with 22 ratings, while the MAUT method yields 18 ratings. The more number of ratings that appear, the better because it is able to minimize the same preference value, so that alternative ranking can be done well.</em></p><p><em><strong><br /></strong></em></p><p class="Abstrak"> </p>

scholarly journals Sensitive Analysis on Selection of Piston Material Using MADM Techniques

2019 ◽  
Vol 69 (4) ◽  
pp. 45-56
Author(s):  
K Lakshmi Chaitanya ◽  
Kolla Srinivas
Keyword(s):  
Decision Making ◽  
Material Selection ◽  
Performance Score ◽  
Design And Manufacturing ◽  
Criteria Weights ◽  
New Material ◽  
Multi Attribute Decision Making ◽  
Selection For ◽  
Ranking Order ◽  
Selection Of

AbstractDecision making in material selection plays important role in selecting appropriate material based on design and manufacturing attributes. Proposing a new material is always a challenging task so the researchers used Decision making assistance tools. In the Present paper the application of Multi-Attribute Decision Making (MADM) methods are applied to the piston material selection for optimal design process. Comparative study of subjective and objective criteria weights on selected MADM methods are done. Sensitivity analysis is conducted to prove the consistency in performance score ranking order as the criteria weights for each alternative varies.

An Integrated Fuzzy Multi-Attribute Decision-Making Methodology for Evaluation of Mechanical Product

2010 ◽  
Vol 450 ◽  
pp. 534-538
Author(s):  
Yuan Chen ◽  
Bing Li ◽  
Xiao Jun Yang
Keyword(s):  
Decision Making ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Weighting Method ◽  
Fuzzy Environment ◽  
Design Alternatives ◽  
Concept Evaluation ◽  
Criteria Weights ◽  
Multi Attribute Decision Making ◽  
Topsis Technique

The concept evaluation of mechanical product is essentially a multi-attribute decision making (MADM) problem in the fuzzy environment. In order to reduce the adverse impact of preference or judgments of decision makers on the final evaluation results, this paper attempts to propose an integrated fuzzy multi-attribute decision making methodology that combines the fuzzy TOPSIS technique and the objective weighting to evaluate mechanical product. The fuzzy TOPSIS technique is applied to rank the design alternatives, and the objective weighting method is integrated into the fuzzy TOPSIS technique to determine the appropriate criteria weights. Finally, a real application to pan mechanism selection for a cooking robot is demonstrated.

scholarly journals Critic-entropy based fuzzy decision making models: a systematic analysis

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Aldring J ◽  
Ajay D
Keyword(s):  
Decision Making ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Systematic Analysis ◽  
Research Article ◽  
Criteria Weights ◽  
Fuzzy Madm ◽  
Multi Attribute Decision Making ◽  
Ranking Order ◽  
Weighting Methods

This research article presents a comprehensive analysis of weighting methods used in fuzzy multi attribute decision making (MADM) methods. These methods involve various criteria in order to evaluate alternatives and determining the weights of criteria is a significant problem that arises very often in many MADM problems. In this research paper, CRTITIC and Entropy weighting methods have been used for finding criteria’s weights like in many research works. Using these unsupervised methods of assigning criteria weights, seven fuzzy MADM methods are examined in the context of ranking the best company to invest in. From the results of these methods, ranking order of alternatives is obtained and are analysed for reliability.

scholarly journals Generalized Fuzzy Soft Power Bonferroni Mean Operators and Their Application in Decision Making

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 810
Author(s):  
Zitai Xu ◽  
Chunfang Chen ◽  
Yutao Yang
Keyword(s):  
Decision Making ◽  
Soft Power ◽  
Original Data ◽  
Decision Makers ◽  
Decision Making Process ◽  
Software Selection ◽  
Decision Method ◽  
Bonferroni Mean ◽  
Special Cases ◽  
Multi Attribute Decision Making

In decision-making process, decision-makers may make different decisions because of their different experiences and knowledge. The abnormal preference value given by the biased decision-maker (the value that is too large or too small in the original data) may affect the decision result. To make the decision fair and objective, this paper combines the advantages of the power average (PA) operator and the Bonferroni mean (BM) operator to define the generalized fuzzy soft power Bonferroni mean (GFSPBM) operator and the generalized fuzzy soft weighted power Bonferroni mean (GFSWPBM) operator. The new operator not only considers the overall balance between data and information but also considers the possible interrelationships between attributes. The excellent properties and special cases of these ensemble operators are studied. On this basis, the idea of the bidirectional projection method based on the GFSWPBM operator is introduced, and a multi-attribute decision-making method, with a correlation between attributes, is proposed. The decision method proposed in this paper is applied to a software selection problem and compared to the existing methods to verify the effectiveness and feasibility of the proposed method.

scholarly journals A BI-OBJECTIVE SCORE-VARIANCE BASED LINEAR ASSIGNMENT METHOD FOR GROUP DECISION MAKING WITH HESITANT FUZZY LINGUISTIC TERM SETS

2018 ◽  
Vol 24 (3) ◽  
pp. 1125-1148 ◽  
Author(s):  
Seyed Hossein RAZAVI HAJIAGHA ◽  
Meisam SHAHBAZI ◽  
Hannan AMOOZAD MAHDIRAJI ◽  
Hossein PANAHIAN
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Assignment Method ◽  
Linguistic Term ◽  
Criteria Weights ◽  
Individual Evaluation ◽  
Fuzzy Linguistic ◽  
Linear Assignment

Decision makers usually prefer to express their preferences by linguistic variables. Classic fuzzy sets allowed expressing these preferences using a single linguistic value. Considering inevitable hesitancy of decision makers, hesitant fuzzy linguistic term sets allowed them to express individual evaluation using several linguistic values. Therefore, these sets improve the ability of humans to determine believes using their own language. Considering this feature, in this paper a method upon linear assignment method is proposed to solve group decision making problems using this kind of information, when criteria weights are known or unknown. The performance of the proposed method is illustrated in a numerical example and the results are compared with other methods to delineate the models efficiency. Following a logical and well-known mathematical logic along with simplicity of execution are the main advantages of the proposed method.

An Application of the Integrated IBA-TOPSIS Model in Supplier Selection

2015 ◽  
Vol 7 (1) ◽  
pp. 15-30 ◽  
Author(s):  
Ksenija Mandić ◽  
Boris Delibašić ◽  
Dragan Radojević
Keyword(s):  
Decision Making ◽  
Boolean Algebra ◽  
Supplier Selection ◽  
Selection Process ◽  
Real Life ◽  
Decision Makers ◽  
Proposed Model ◽  
Qualitative Variables ◽  
Hidden Knowledge ◽  
Multi Attribute Decision Making

The supplier selection process attracted a lot of attention in the business management literature. This process takes into consideration several quantitative and qualitative variables and is usually modeled as a multi-attribute decision making (MADM) problem. A recognized shortcoming in the literature of classical MADM methods is that they don't permit the identification of interdependencies among attributes. Therefore, the aim of this study is to propose a model for selecting suppliers of telecommunications equipment that includes the interaction between attributes. This interaction can model the hidden knowledge needed for efficient decision-making. To model interdependencies among attributes the authors use a recently proposed consistent fuzzy logic, i.e. interpolative Boolean algebra (IBA). For alternatives ranking they use the classical MADM method TOPSIS. The proposed model was evaluated on a real-life application. The conclusion is that decision makers were able to integrate their reasoning into the MADM model using interpolative Boolean algebra.

scholarly journals Weight Approximation for Spatial Outcomes

2020 ◽  
Vol 12 (14) ◽  
pp. 5588
Author(s):  
Jay Simon
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Approximation Methods ◽  
Water Usage ◽  
Census Block ◽  
Ordinal Ranking ◽  
New Methods ◽  
Policy Alternatives ◽  
Multi Attribute Decision Making ◽  
Geographic Regions

When preferences explicitly include a spatial component, it can be challenging to assign weights to geographic regions in a way that is both pragmatic and accurate. In multi-attribute decision making, weights reflect cardinal information about preferences that can be difficult to assess thoroughly in practice. Recognizing this challenge, researchers have developed several methods for using ordinal rankings to approximate sets of cardinal weights. However, when the set of weights reflects a set of geographic regions, the number of weights can be enormous, and it may be cognitively challenging for decision makers to provide even a coherent ordinal ranking. This is often the case in policy decisions with widespread impacts. This paper uses a simulation study for spatial preferences to evaluate the performance of several rank-based weight approximation methods, as well as several new methods based on assigning each region to a tier expressing the extent to which it should influence the evaluation of policy alternatives. The tier-based methods do not become more cognitively complex as the number of regions increases, they allow decision makers to express a wider range of preferences, and they are similar in accuracy to rank-based methods when the number of regions is large. The paper then demonstrates all of these approximation methods with preferences for water usage by census block in a United States county.

scholarly journals Risky Multi-Attribute Decision-Making Method Based on the Interval Number of Normal Distribution

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 264
Author(s):  
Sha Fu ◽  
Xi-Long Qu ◽  
Ye-Zhi Xiao ◽  
Hang-Jun Zhou ◽  
Guo-Bing Fan
Keyword(s):  
Decision Making ◽  
Normal Distribution ◽  
Interval Number ◽  
Information Environment ◽  
Decision Makers ◽  
Standard Normal Distribution ◽  
Risky Decision ◽  
Possibility Degree ◽  
Standard Normal ◽  
Multi Attribute Decision Making

Focusing on risky decision-making problems taking the interval number of normal distribution as the information environment, this paper proposes a decision-making method based on the interval number of normal distribution. Firstly, the normalized matrix based on the decision maker’s attitude is obtained through analysis and calculation. Secondly, according to the existing properties of standard normal distribution, the risk preference factors of the decision makers are considered to confirm the possibility degree of each scheme. The possibility degree is then used for establishing a possibility degree matrix and, consequently, sequencing of all schemes is conducted according to existing theories of possibility degree meaning and the value size of possibility degree. Finally, the feasibility and validity of this method is verified through calculation example analysis.

scholarly journals A Novel Extension of the Technique for Order Preference by Similarity to Ideal Solution Method with Objective Criteria Weights for Group Decision Making with Interval Numbers

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1460
Author(s):  
Dariusz Kacprzak
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Ease Of Use ◽  
Decision Makers ◽  
Ideal Solution ◽  
Interval Numbers ◽  
Group Matrix ◽  
Order Preference ◽  
Criteria Weights

This paper presents an extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with objective criteria weights for Group Decision Making (GDM) with Interval Numbers (INs). The proposed method is an alternative to popular and often used methods that aggregate the decision matrices provided by the decision makers (DMs) into a single group matrix, which is the basis for determining objective criteria weights and ranking the alternatives. It does not use an aggregation operator, but a transformation of the decision matrices into criteria matrices, in the case of determining objective criteria weights, and into alternative matrices, in the case of the ranking of alternatives. This ensures that all the decision makers’ evaluations are taken into account instead of their certain average. The numerical example shows the ease of use of the proposed method, which can be implemented into common data analysis software such as Excel.

scholarly journals Application of Multi-Attribute Decision-Making Methods for the Selection of Conveyor

2021 ◽  
Author(s):  
Satyam Fulzele ◽  
Satywan Khatke ◽  
Shubham Kadam ◽  
Avinash Kamble
Keyword(s):  
Decision Making ◽  
Analytical Hierarchy Process ◽  
Material Handling ◽  
Selection Process ◽  
Decision Makers ◽  
Variable Cost ◽  
Fixed Cost ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Hierarchy Process

Abstract In the present time of innovation, conveyor assume an exceptionally indispensable part and have huge significance for material handling in different enterprises. A conveyor is essentially utilized for moving any sort of material from one area to other. It is made with nearer precisions, hence the expense related with manufacturing is additionally high. In this manner, it should work with better productivity. The choice of the best conveyor is a crucial activity for designers. Designers need to recognize different variables that will influence the functionalities of the conveyor system to limit bottlenecks in the system. An efficient methodology should be accomplished for the conveyor selection. Subsequently, the current work aims to the selection process of the best option for conveyor by using four decision making methods such as analytical hierarchy process, technique of order preference by similarity to ideal solution, compromise ranking method and Deng’s similarity based method. The selection is done among four alternatives based on six attributes viz: fixed cost each hour, variable cost each hour, conveyor speed, product width, product weight and flexibility. The analytical hierarchy process is used to determine weights of the attributes based on relative importance of each attribute. It is also observed that A3 conveyor is best suitable conveyor. Hence the above proposed strategies help decision-makers to examine and choose the best conveyor by considering the rank obtained of the alternatives.

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