scholarly journals Sistem Pendukung Keputusan Untuk Seleksi Penerimaan Dan Penentuan Posisi Karyawan

2016 ◽  
Vol 10 (1) ◽  
pp. 62
Author(s):  
Devi Martha Ariyanti ◽  
Fahrul Agus ◽  
Dyna Marisa Khairina

Sumber Daya Manusia (SDM) merupakan sumber daya yang paling penting bagi organisasi. Salah satu proses yang paling penting bagi perusahaan adalah proses rekrutmen dan seleksi sumber daya manusia. Pada kenyataannya pengambilan keputusan secara efisien dan efektif pada saat melakukan seleksi terhadap sumber daya manusia bukanlah hal yang mudah, maka diperlukan suatu Sistem Pendukung Keputusan (SPK) untuk membantu memecahkan masalah tersebut. Dalam hal ini Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) dan Fuzzy Multiple Criteria Decision Making (FMCDM) digunakan sebagai metode untuk memberikan penilaian calon karyawan yang akan diseleksi. Dari beberapa data yang diujikan terhadap aplikasi ini menunjukkan bahwa calon karyawan ideal terhadap suatu posisi bukan hanya memiliki nilai kedekatan pada kriteria ideal yang diinginkan oleh perusahaan, tapi juga memiliki nilai dengan rentang menjauhi kriteria ideal yang tidak diinginkan oleh perusahaan.

2010 ◽  
Vol 34-35 ◽  
pp. 1931-1935 ◽  
Author(s):  
Qi Bing Wang ◽  
An Hua Peng

Multiple criteria decision making(MCDM) is widely used in selection from a set of available alternatives with multiple criteria, approaches to which includes fuzzy comprehensive evaluation(FCE), grey relational analysis(GRA), and technique for order preference by similarity to ideal solution(TOPSIS), and so on. First analyzes the limitations of various methods: only considering the overall effect of attribute indicators in the method of FCE, only considering the shape similarity of data curve between comparative scheme and ideal solution in GRA and only considering position approximation in TOPSIS. Second proposes a new method of comprehensive evaluation which takes into account both shape similarity and position approximation. The validity of this method has been further proved by an example of suppliers selection.


2019 ◽  
Vol 5 (2) ◽  
pp. 85
Author(s):  
Nafis Sururi ◽  
Kusrini Kusrini ◽  
Sudarmawan Sudarmawan

Pendidikan merupakan salah satu hal yang penting dalam suatu negara. Pendidikan bisa didapatkan pendidikan formal, informal maupun nonformal. Contoh pendidikan formal adalah sekolah dan pergururan tinggi, di dalam sekolahan terdapat wali kelas yang bertanggung jawab terhadap peserta didik di satu kelas atau ruang belajar di lingkungan sekolah. Dalam menentukan wali kelas yang ideal kepala sekolah dapat melihat karakteristik dan kemampuan yang dimiliki guru secara objektif. Multiple Criteria Decision Making (MCDM) merupakan salah satu metode yang paling banyak digunakan dalam pengambilan keputusan. Salah satu metode MCDM adalah Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Penelitian ini menggunakan metode TOPSIS yang dapat menganalisis keputusan multi-kriteria dimana metode tersebut dapat memilih alternatif terbaik dengan jarak terdekat dari alternatif ideal. Hasil yang diperoleh dari penelitian ini adalah Penentuan wali kelas dilakukan dengan cara mencari nilai preferensi setiap guru yang paling besar dari 3 kelas yang digunakan. Perhitungan yang dilakukan menggunakan bobot berbeda pada setiap kelas agar mendapatkan nilai prefensi sebagai acuan penentuan wali kelas yang ideal.Kata Kunci—Wali kelas, Ideal, TOPSISEducation is one of the important things in a country. Education can be obtained from formal, informal or non-formal education. Examples of formal education are schools and high schools, in schools there is a homeroom teacher who is responsible for students in one class or study room in a school environment. In determining the ideal homeroom, the principal can see the characteristics and abilities of the teacher objectively. Multiple Criteria Decision Making (MCDM) is one of the most widely used methods in decision making. One of the MCDM methods is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This study uses the TOPSIS method which can analyze multi-criteria decisions where the method can choose the best alternative with the closest distance from the ideal alternative. The results obtained from this study are Determination of the homeroom teacher is done by finding the preference value of each teacher, the largest of the 3 classes used. Calculations performed using different weights for each class in order to get the value of the prefix as a reference for determining the ideal homeroom teacher.Keywords—Homeroom teacher, Ideal, TOPSIS


2010 ◽  
Vol 16 (1) ◽  
pp. 109-125 ◽  
Author(s):  
Jurgita Antuchevičienė ◽  
Edmundas Kazimieras Zavadskas ◽  
Algimantas Zakarevičius

Decision making in construction management has been always complicated especially if there were more than one criterion under consideration. Multiple criteria decision making (MCDM) has been often applied for complex decisions in construction when a lot of criteria were involved. Traditional MCDM methods, however, operate with independent and conflicting criteria. While in every day problems a decision maker often faces interactive and interrelated criteria. Accordingly, the need of improving and supplementing the methodology of compromise decisions arose. It was proposed to supplement TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution) method and integrate the Mahalanobis distance in the usual algorythm of TOPSIS. Mahalanobis distance measure offered an option to take the correlations between the criteria into considerations while making the decision. A case study of building redevelopment in Lithuanian rural areas was presented that demonstrated the application of the proposed methodology. The case study proved that the proposed TOPSIS‐M (TOPSIS applying Mahalanobis distance measure) method could have substantial influence in carrying the proper decision. Santrauka Statybos valdymo spendimų priėmimas visuomet yra komplikuotas, ypač jei turime atsižvelgti į daugelį rodiklių. Kompleksiniams statybos sprendimams, kurie apibūdinami daugeliu rodiklių, taikomi daugiatiksliai sprendimų priėmimo metodai (MCDM ‐ Multiple Criteria Decision Making). Šie metodai skirti sprendimams priimti tuomet, kai vertinami konfliktuojantys bei nepriklausomi rodikliai. Tačiau realiose situacijose, priešingai, nuolat susiduriame su saveikaujančiais ir tarpusavio priklausomybę turinčiais rodikliais. Dėl šios priežasties kyla poreikis patobulinti sprendimų metodologiją. Straipsnyje siūloma papildyti variantų racionalumo nustatymo metoda TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution), taikant Mahalanobio metoda atstumams nustatyti. Mahalanobio atstumų nustatymo metodas suteikia galimybę įvertinti koreliacinės rodiklių priklausomybės priimant daugiatikslį sprendimą. Siūlomos metodologijos taikymas įliustruojamas sprendžiant apleistų pastatų Lietuvos kaimo vietovėse racionalaus sutvarkymo uždavinį. Pateiktas pavyzdys patvirtina, kad TOPSIS‐M metodo (t. y. TOPSIS naudojant Mahalanobio atstuma) taikymas gali turėti esminę įtaka priimant sprendimą.


2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Aditya Chauhan ◽  
Rahul Vaish

Multiple Criteria Decision Making (MCDM) models are used to solve a number of decision making problems universally. Most of these methods require the use of integers as input data. However, there are problems which have indeterminate values or data intervals which need to be analysed. In order to solve problems with interval data, many methods have been reported. Through this study an attempt has been made to compare and analyse the popular decision making tools for interval data problems. Namely, I-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), DI-TOPSIS, cross entropy, and interval VIKOR (VlseKriterijumska Optimiza-cija I Kompromisno Resenje) have been compared and a novel algorithm has been proposed. The new algorithm makes use of basic TOPSIS technique to overcome the limitations of known methods. To compare the effectiveness of the various methods, an example problem has been used where selection of best material family for the capacitor application has to be made. It was observed that the proposed algorithm is able to overcome the known limitations of the previous techniques. Thus, it can be easily and efficiently applied to various decision making problems with interval data.


2022 ◽  
Vol 19 (1) ◽  
pp. 1749
Author(s):  
Amnard Taweesangrungroj ◽  
Roongkiat Rattanabanchuen ◽  
Sukree Sinthupinyo

In developing countries, the government has played an important role in supporting startup businesses in various aspects, primarily through tech-focused government agencies. With a limited budget, the government agencies are critical to select plenty of tech startups for funding, leaving only promising tech startups. Consequently, government agencies inevitably face decision-making problems under uncertain circumstances, like private equity investment situations. Reviewing the relevant decision-making frameworks has identified that a classical multiple criteria decision-making (MCDM) approach is currently used, assuming decision-makers acquire complete information that is not realistic. Moreover, both qualitative and quantitative criteria used in evaluating startup businesses cannot represent the uncertainty which is the fundamental nature of the decision-making circumstance. Thus, this article presents a decision-making framework of tech-focused government agencies for selecting startup businesses based on a fuzzy MCDM of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Besides, it identifies selection criteria with mixed research methodologies and determines weights of importance criteria by the Delphi method. Finally, the proposed framework results are fairness, transparency, and eliminating bias in decision-making, including more efficiency when the framework’s ranking orders significantly correspond with actual performances. HIGHLIGHTS Criteria for selecting start-up businesses in technological-focused government agencies A decision-making framework of tech-focused government agencies for selecting startup businesses based on a fuzzy MCDM of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) The performance of the decision-making framework in selecting startup businesses to acquire high potential tech startups to drive the national economy GRAPHICAL ABSTRACT


2010 ◽  
Vol 1 (4) ◽  
pp. 56-75 ◽  
Author(s):  
Sarojini Jajimoggala ◽  
V.V.S. Kesava Rao ◽  
Satyanarayana Beela

Prioritization of equipment is an important factor for decision making to optimize maintenance management in Reliability Centered Maintenance (RCM). Many factors must be considered as part of the prioritization of equipment for maintenance activities. Consequently, evaluation procedures involve several objectives and it is often necessary to compromise among conflicting tangible and intangible factors. Multiple Criteria Decision Making (MCDM) is a useful approach to solve these problems. In this study, a hybrid model is developed for prioritizing the equipment in hybrid flow systems. The first stage involves identifying the criteria. The second stage is prioritizing the different criteria using fuzzy Analytical Network Process (ANP), in which the weight of each criterion is calculated using modified fuzzy Logarithmic Least Square Method (LLSM) to overcome the criticism of inconsistency, unbalanced scale of judgments, uncertainty and imprecision in the pair-wise comparison process, then finally ranking of equipment using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).


Author(s):  
Sarojini Jajimoggala ◽  
V. V. S. Kesava Rao ◽  
Satyanarayana Beela

Prioritization of equipment is an important factor for decision making to optimize maintenance management in Reliability Centered Maintenance (RCM). Many factors must be considered as part of the prioritization of equipment for maintenance activities. Consequently, evaluation procedures involve several objectives and it is often necessary to compromise among conflicting tangible and intangible factors. Multiple Criteria Decision Making (MCDM) is a useful approach to solve these problems. In this study, a hybrid model is developed for prioritizing the equipment in hybrid flow systems. The first stage involves identifying the criteria. The second stage is prioritizing the different criteria using fuzzy Analytical Network Process (ANP), in which the weight of each criterion is calculated using modified fuzzy Logarithmic Least Square Method (LLSM) to overcome the criticism of inconsistency, unbalanced scale of judgments, uncertainty and imprecision in the pair-wise comparison process, then finally ranking of equipment using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).


2015 ◽  
Vol 40 (4) ◽  
pp. 299-315 ◽  
Author(s):  
Huan-jyh Shyur ◽  
Liang Yin ◽  
Hsu-shih Shih ◽  
Chi-bin Cheng

Abstract This paper proposes a new multiple criteria decision-making method called ERVD (election based on relative value distances). The s-shape value function is adopted to replace the expected utility function to describe the risk-averse and risk-seeking behavior of decision makers. Comparisons and experiments contrasting with the TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) method are carried out to verify the feasibility of using the proposed method to represent the decision makers’ preference in the decision making process. Our experimental results show that the proposed approach is an appropriate and effective MCDM method.


Techno Com ◽  
2017 ◽  
Vol 17 (1) ◽  
pp. 48-60
Author(s):  
Tri Widayanti

Dengan adanya penyelenggaraan pemilihan dosen berprestasi di tingkat nasional, maka diharapkan setiap perguruan tinggi terdorong untuk memiliki sistem penghargaan yang terprogram bagi dosen yang memiliki prestasi tinggi dalam pelaksanaan tridarma perguruan tinggi. Dalam pemilihan dosen berprestasi tersebut sering muncul subyektifitas para pengambil keputusan.Tujuan dari penelitian ini adalah dengan penunjang keputusan, pengambilan keputusan akan lebih objektif dalam memilih dosen berprestasi. Penelitian Multiple Criteria Decision Making dilakukan dengan menggunakan 2 metode yaitu Analytical Hierarchy Process (AHP) dan Technique for Order by Similarity to Ideal Solution (TOPSIS). AHP digunakan untuk menentukan bobot kepentingan dari setiap kriteria dan sub kriteria penilaian dosen berprestasi, kemudian TOPSIS digunakan untuk memilih alternatif dosen berprestasi yang memerlukan pertimbangan. Hasil penelitian  menunjukkan bahwa AHP dan TOPSIS dapat digunakan sebagai pendukung pembuat keputusan yang multi kriteria dan memerlukan banyak pertimbangan dalam pemilihan dosen berprestasi di perguruan tinggi. Metode AHP dan TOPSIS dapat membedakan dengan jelas  berdasarkan nilai preferensi yang dihasilkan sehingga memberikan keputusan yang objektif.


2015 ◽  
Vol 21 (5) ◽  
pp. 705-719 ◽  
Author(s):  
Guangxu LI ◽  
Gang Gang KOU ◽  
Yi PENG

The paper proposes a dynamic fuzzy multiple criteria decision making (DFMCDM) method. The method considers the integrated weight of the decision makers with the subjective and objective preference and the effect of time weight. In the proposed method, a mathematical programming model is used to determine the integrated weight, and a basic unit-interval monotonic (BUM) function based approach is used to calculate the time weight. In addition, a distance measure of membership function is introduced to effectively measure the degree of difference between the alternatives in the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS). Finally, a numerical example is introduced to illustrate the proposed method.


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