scholarly journals APLEISTŲ PASTATŲ RACIONALAUS NAUDOJIMO MODELIAVIMAS TAIKANT GEOINFORMACINES SISTEMAS

2012 ◽  
Vol 31 (4) ◽  
pp. 129-133 ◽  
Author(s):  
Jurgita Antuchevičienė
Keyword(s):  
Decision Making ◽  
Ideal Solution ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Topsis Technique

Priimant erdvinius sprendimus geografinių informacinių sistemų (GIS) galimybės taikomos apleistų pastatų racionalaus naudojimo problemoms aplinkos ir visuomenės darnos požiūriu spręsti. Pasiūlytas pradinių duomenų parengimo ir jų taikymo skaičiavimams daugiatiksliais sprendimų priėmimo (Multi-attribute Decision Making – MADM) metodais modelis. Pateikta apleistų pastatų duomenų bazės struktūra ir parengtas šios bazės pildymo duomenimis apie nenaudojamus Lietuvos kaimo statinius pavyzdys. Sudaryti darnią ūkio plėtrą šalyje nusakančių socialinių, ekonominių ir aplinkos rodiklių sluoksniai. Numatytos duomenų analizės galimybės. Pateiktas GIS ir daugiatikslio sprendimų priėmimo metodo TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution) integravimo racionaliam apleistų pastatų Lietuvos kaimo vietovėse naudojimui modeliuoti pavyzdys.

scholarly journals INTEGRATED APPROACH OF FUZZY MULTI-ATTRIBUTE DECISION MAKING AND DATA MINING FOR CUSTOMER SEGMENTATION

2021 ◽  
Vol 24 (4) ◽  
pp. 174-188
Author(s):  
Manidatta Ray ◽  
Mamata Ray ◽  
Kamalakanta Muduli ◽  
Audrius Banaitis ◽  
Anil Kumar
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Fuzzy Ahp ◽  
Integrated Approach ◽  
Fuzzy Topsis ◽  
Ideal Solution ◽  
Fuzzy C Means ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Topsis Technique

This research work focuses on integrating the multi attribute decision making with data mining in a fuzzy decision environment for customer relationship management. The main objective is to analyse the relation between multi attribute decision making and data mining considering a complex problem of ordering customers segments, which is based on four criteria of customer’s life time value, viz. length (L), recency (R), frequency (F) and monetary value (M). The proposed integrated approach involves fuzzy C-means (FCM) cluster analysis as data mining tool. The experiment conducted using MATLAB 12.0 for identifying eight clusters of customers. The two multi attribute decision making tools i.e., fuzzy AHP (Analytic Hierarchy Process) and fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) are used for ranking these identified clusters. The applicability of the integrated decision making technique is also demonstrated in this paper considering the case of Indian retail sector. This research collected responses from nine experts from Indian retail industry regarding their perception of relative importance of four criteria of customer life value and evaluated weights of each criterion using fuzzy AHP. Transaction data of 18 months of the case retail store was analysed to segment 1,600 customers into eight clusters using fuzzy c-means clustering analysis technique. Finally, these eight clusters were ranked using fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The findings of this research could be helpful for firms in identifying the more valuable customers for them and allocate more resources to satisfy them. The findings will be also helpful in developing different loyalty program strategies for customers of different clusters.

scholarly journals A Comparative Study on Decision Making Methods with Interval Data

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Aditya Chauhan ◽  
Rahul Vaish
Keyword(s):  
Decision Making ◽  
Input Data ◽  
Multiple Criteria Decision Making ◽  
Interval Data ◽  
Cross Entropy ◽  
Ideal Solution ◽  
Order Preference ◽  
Topsis Technique ◽  
Selection Of ◽  
Novel Algorithm

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.

Interval Rough Neutrosophic TOPSIS Strategy for Multi-Attribute Decision Making

2020 ◽  
pp. 98-118
Author(s):  
Rumi Roy ◽  
Surapati Pramanik ◽  
Tapan Kumar Roy
Keyword(s):  
Decision Making ◽  
Euclidean Distance ◽  
Hamming Distance ◽  
Ideal Solution ◽  
Numerical Example ◽  
New Strategy ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Ranking Order ◽  
Negative Ideal Solution

In this chapter, the authors present a new strategy for multi-attribute decision making in interval rough neutrosophic environment. They define Hamming distance and Euclidean distance between interval rough neutrosophic numbers. They also define interval rough neutrosophic relative positive ideal solution (IRNRPIS) and interval rough neutrosophic relative negative ideal solution (IRNRNIS). Then the ranking order of the alternatives is obtained by the technique for order preference by similarity to ideal solution (TOPSIS) strategy. Finally, a numerical example is provided to demonstrate the applicability and effectiveness of the proposed interval rough neutrosophic TOPSIS strategy.

scholarly journals Suatu Pendekatan Hibrid Menggunakan Topsis - Entropi pada Penentuan Siswa Penerima Beasiswa Prestasi Berbasiskan Kriteria Objektif

2021 ◽  
Vol 8 (1) ◽  
pp. 167
Author(s):  
Maria Ulfah Siregar ◽  
Titik Nasiroh ◽  
Muhammad Mustakim
Keyword(s):  
Decision Making ◽  
Economic Condition ◽  
Hybrid Approach ◽  
Entropy Method ◽  
Ideal Solution ◽  
A Value ◽  
Economic Difficulty ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Negative Ideal Solution

<p class="Abstrak">Kondisi ekonomi Indonesia yang turun seiring pandemi Covid-19 yang belum juga berakhir menyebabkan sebagian masyarakat menghadapi kesulitan ekonomi dalam pemenuhan kebutuhan hidup sehari-hari, salah satunya adalah dalam pembiayaan sekolah anak. Salah satu solusi bagi permasalahan ini adalah dengan pemberian beasiswa bagi siswa. Keterbatasan dana beasiswa ditambah dengan siswa yang berhak menerima bantuan adalah berjumlah banyak, menghendaki adanya suatu sistem yang dapat membantu dalam penentuan siswa penerima beasiswa.  Penelitian kami menerapkan pendekatan hibrid dari <em>Multi-Attribute Decision Making</em> (MADM) metode Entropi dan <em>Technique for Order Preference by Similarity to Ideal Solution </em>(TOPSIS). Metode Entropi digunakan untuk memberikan pembobotan pada kriteria secara objektif. Metode TOPSIS mencari alternatif terbaik dari sejumlah alternatif, yaitu yang semakin mendekati solusi ideal positif dan menjauhi solusi ideal negatif. Penelitian ini diimplementasikan di SMP N 1 Kokap Yogyakarta dengan menggunakan data siswa kelas 8 sejumlah 146 orang siswa. Terdapat sepuluh kriteria untuk menentukan siswa penerima beasiswa prestasi yaitu nilai pengetahuan, nilai keterampilan, catatan prestasi, keaktifan berorganisasi, jumlah ekstrakurikuler, jumlah ketidakhadiran, penghasilan ayah, penghasilan ibu, jumlah tanggungan orang tua dan status beasiswa. Berdasarkan sebaran dari evaluasi nilai kriteria dengan perhitungan bobot Entropi tanpa menggunakan bobot awal dari sekolah, diperoleh bahwa kriteria catatan prestasi adalah kriteria utama dalam penentuan siswa penerima beasiswa ini dan semua kriteria adalah valid. Output dari sistem ini adalah <em>ranking</em> siswa berdasarkan nilai preferensinya. Pe-<em>ranking</em>-an ini bisa dijadikan sebagai rekomendasi siswa penerima beasiswa prestasi di SMP N 1 Kokap.</p><p class="Abstrak"> </p><p class="Abstrak"><em><strong>Abstract</strong></em></p><p class="Abstrak"><em>Economic condition in Indonesia which is gradually decreased during Covid-19 pandemic which has not stopped yet causes some of citizens face economic difficulty in fulfilling their daily life, one of which is to pay their children’ school fees. One solution for this problem is to provide scholarship for students. The limited money for scholarship and students who are eligible to get the aids are many in number require a system which can ease in determining the merit scholars objectively. This study applies the hybrid approach of Multi-Attribute Decision Making (MADM) method, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Entropy. Entropy method is used to define objectively a weight of each criteria. TOPSIS method finds the best alternative from several alternatives that getting closer to the positive ideal solution and farther from the negative ideal solution. This study is implemented in SMP N 1 Kokap Yogyakarta and use data of 146 students on Kelas 8. There are ten criteria to determine merit scholars, these are a value of knowledge, a value of skills, a record of merits, organizational activities, the number of extracurriculars, for the number of absences, father's income, mother's income, the number of dependents of parents and scholarship status. Based on disperity of evaluation of criteria’ values, the achievements record is the important criteria for this system and all the criteria are valid. The result of this system is a rank of students based on their preference values. This rank could be used as a reference to recommend merit scholars in SMP N 1 Kokap.   </em></p>

scholarly journals GDSS MULTI KRITERIA PENENTUAN STRATEGI MARKETING TERBAIK PERGURUAN TINGGI

2019 ◽  
Vol 9 (1) ◽  
pp. 15
Author(s):  
Sumiyatun Sumiyatun
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Analytical Hierarchy Process ◽  
Group Decision ◽  
Group Decision Support ◽  
Ideal Solution ◽  
Group Decision Support System ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Hierarchy Process

Dunia  pendidikan  telah  mengalami  evolusi  secara  kontinyu.  Salah  satu faktor  pemicunya  adalah  kompetisi  antar  perguruan  tinggi  yang  semakin  ketat. Oleh karena itu pemasaran menjadi unsur yang strategis dalam menjaga eksistensi perguruan  tinggi. Dalam membuat keputusan pemilihan strategi marketing, terdapat beberapa kriteria yang perlu dipertimbangkan, diantaranya adalah biaya, waktu, tingkat pengaruh, capaian target dan lain sebagianya. Pada perguruan tinggi swasta pengambilan keputusan terkait strategi marketing tidak hanya ditentukan oleh bagian Humas saja, akan tetapi  harus meminta pertimbangan dari pihak manajemen dan yayasan pemilik perguruan tinggi. Berdasarkan  kompleknya permasalahan  yang  dihadapi,  diperlukan  sebuah  sistem pendukung  keputusan  kelompok  atau  Group  Decision  Support  System  (GDSS) dalam menentukan strategi marketing pergurauan tinggi.  Pada  penelitian  ini,  penulis  mengajukan  GDSS  menggunakan metode Analytical  Hierarchy Process (AHP) yang mendukung model Multi Attribute Decision Making (MADM) dan  Technique for  Order  Preference by  Similarity  to  Ideal  Solution  (TOPSIS)  sebagai  model  untuk  pengambilan keputusan. Penggunaan  GDSS  pada penelitian ini bertujuan  untuk  mengakomodir  penilaian  lebih  dari  satu  evaluator  dan meningkatkan  kualitas  keputusan.  Dengan  demikian  diharapkan  penilaian  yang dilakukan lebih obyektif, karena tidak dilakukan oleh satu pihak saja. Perangkat lunak yang dibangun dari hasil penelitian ini diharapkan  mempermudah dan mempercepat dalam menentukan strategi marketing perguruan tinggi.

Benchmarking CNC Machine Tool Using Hybrid-Fuzzy Methodology

2015 ◽  
Vol 4 (2) ◽  
pp. 28-46 ◽  
Author(s):  
Anoop Kumar Sahu ◽  
Nitin Kumar Sahu ◽  
Atul Kumar Sahu
Keyword(s):  
Decision Making ◽  
Machine Tool ◽  
Global Market ◽  
Numerical Control ◽  
Cnc Machine Tools ◽  
Ideal Solution ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Order Preference ◽  
Topsis Technique

In today's era, managerial decision making has become a very momentous component due to the leverage of attention on achieving organizational goal i.e. enhancing effective utilization of input assets, satisfying customers' demand and minimizing loss (maximize profit). The evaluation of the most appropriate Computer Numerical Control (CNC) machine tool has become one of the key factors for sustaining the organization/manufacturing sectors/production units at competitive global market place. Productivity, precision and accuracy etc. are the most important issues behind adaptation/exploration of CNC machine tools. So, in such a cases, subjective indices are considered beside the objective indices and complexity of the CNC machine tool evaluation decision problems is solved via subjective assessments (judgment) of expert panel, also called the decision-making group. In this reporting, TOPSIS (technique for order preference by similarity to ideal solution) based Multi-Criteria Decision Making (MCDM) approach has fruitfully applied to emphasize the decision making scenario at the subjective information evaluation index (indices) platform. So, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) analytical methodology conjunction with Trapezoidal Fuzzy Number (TFN) has been explored for assessing and benchmarking the most preferable CNC machine tool from a group of preferred options/alternatives. Finally, an empirical case study has been carried out check the feasibility, efficiency and validity of proposed methodology and the benchmarking of preferred alternative machine tool has been derived in accordance with descending value of the ‘collective index'. Higher value of ‘collective index' reflects higher degree of performance extent.

scholarly journals ANALISIS OPTIMAL PENJUALAN PETIS MADURA MENGGUNAKAN METODE TOPSIS

2015 ◽  
Vol 1 (1) ◽  
pp. 17
Author(s):  
Sumiatun Sumiatun ◽  
Kuzairi Kuzairi
Keyword(s):  
Decision Making ◽  
Ideal Solution ◽  
Order Preference ◽  
Multi Attribute Decision Making

Petis merupakan jenis makanan yang digemari orang banyak, selain dijadikan bahan untuk usaha yang ditekuni, petis juga bemanfaat untuk bahan pendamping makanan rigan seperti gorengan, uniknya petis Madura ini awet dan dijual sampai keluar Madura. Dalam penelitian ini metode yang digunakan adalah Technique For Order Preference By Similarity To Ideal Solution (TOPSIS). Metode TOPSIS adalah salah satu metode yang digunakan untuk menyelesaikan masalah Multi Attribute Decision Making (MADM). Metode TOPSIS didasarkan pada konsep dimana alternatif terpilih yang terbaik tidak hanya memiliki jarak terpendek dari solusi ideal positif, namun juga memiliki jarak terpanjang dari solusi ideal negatif. Metode TOPSIS memiliki beberapa kelebihan, diantaranya konsepnya yang sederhana dan mudah dipahami, komputasinya efisien, dan memiliki kemampuan untuk mengukur kinerja relatif dari alternatif-alternatif keputusan dalam bentuk matematis yang sederhana.

Multi-Attribute Decision Making in Risk Analysis

2016 ◽  
pp. 246-290
Author(s):  
William P. Fox
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Risk Analysis ◽  
Analytical Hierarchy Process ◽  
Data Envelopment ◽  
Ideal Solution ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Simple Additive Weighting ◽  
Hierarchy Process

Multi-Attribute Decision Making (MADM) is commonly used when we are comparing more than two courses of actions or alternatives based upon many selected criteria. This chapter presents methodologies to conduct MADM analysis for risk analysis and risk assessment across a variety of topics. These methodologies include Data Envelopment Analysis (DEA), Simple Additive Weighting (SAW), Analytical Hierarchy Process (AHP), and the Technique of Order Preference by Similarity to Ideal Solution (TOPSIS). The author describes each methodology, provide some strengths and limitations of each, discuss tips for sensitivity analysis, and provide two risk analysis examples to illustrate each method.

scholarly journals District Heating Systems Performance Analyses. Heat Energy Tariff

2014 ◽  
Vol 13 (1) ◽  
pp. 32-43 ◽  
Author(s):  
Jelena Ziemele ◽  
Girts Vigants ◽  
Valdis Vitolins ◽  
Dagnija Blumberga ◽  
Ivars Veidenbergs
Keyword(s):  
Decision Making ◽  
District Heating ◽  
Evaluation Methodology ◽  
Ideal Solution ◽  
Low Carbon ◽  
Renewable Energy Resources ◽  
Heating Systems ◽  
Multi Attribute Decision Making ◽  
Multi Criteria Analysis ◽  
Topsis Technique

Abstract The paper addresses an important element of the European energy sector: the evaluation of district heating (DH) system operations from the standpoint of increasing energy efficiency and increasing the use of renewable energy resources. This has been done by developing a new methodology for the evaluation of the heat tariff. The paper presents an algorithm of this methodology, which includes not only a data base and calculation equation systems, but also an integrated multi-criteria analysis module using MADM/MCDM (Multi-Attribute Decision Making / Multi-Criteria Decision Making) based on TOPSIS (Technique for Order Performance by Similarity to Ideal Solution). The results of the multi-criteria analysis are used to set the tariff benchmarks. The evaluation methodology has been tested for Latvian heat tariffs, and the obtained results show that only half of heating companies reach a benchmark value equal to 0.5 for the efficiency closeness to the ideal solution indicator. This means that the proposed evaluation methodology would not only allow companies to determine how they perform with regard to the proposed benchmark, but also to identify their need to restructure so that they may reach the level of a low-carbon business.

scholarly journals SISTEM PENDUKUNG KEPUTUSAN SELEKSI PENERIMAAN MAHASISWA BARU JALUR BEASISWA DENGAN METODE TOPSIS (TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION)

2018 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
M Panji Ismail
Keyword(s):  
Decision Making ◽  
Selection Process ◽  
System Development ◽  
Ideal Solution ◽  
Order Preference ◽  
Negative Ideal Solution ◽  
Written Test ◽  
Topsis Technique ◽  
The Right ◽  
The Ideal

The scholarship path is one of the paths used by the University of Technology Yogyakarta (UTY) in accepting new students. The track consists of seven criteria: school accreditation, family condition, report card score, achievement, written test, interview test. In order to process the criteria, it is necessary to have a Decision Support System (DSS) capable of conducting the scholarship selection process quickly, accurately and objectively. DSS is a system that can perform a decision-making process based on the human mindset. SPK can tolerate any kind of data whether it is certain or uncertain. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a Multi-Criteria Decision Making (MCDM) category which is a decision-making technique of some alternative options, especially Multi Attribute Decision Making (MADC). TOPSIS aims to determine the ideal ideal solution and the ideal negative solution of the scholarship criteria. A positive ideal solution maximizes benefit criteria and minimizes cost criteria, whereas a negative ideal solution maximizes cost criteria and minimizes benefit criteria. The research methodology used is SDLC (System Development Life Cycle) and system implementation built using Delphi 7 programming language and data processing using DBMS SQL Server 2012.. The results of the system show that the system provides accurate and valid results in accordance with the data owned by prospective students so that full scholarship can be given in the right target.

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