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.

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.

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.

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.

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.

Dynamic Multi-Attribute Decision Making Model with the Area Closeness Degree

2013 ◽  
Vol 321-324 ◽  
pp. 2557-2560
Author(s):  
Xi Juan Lou
Keyword(s):  
Decision Making ◽  
Ideal Solution ◽  
Raw Data ◽  
New Information ◽  
Multi Attribute Decision Making ◽  
Decision Making Model

The aim of this paper is to explore dynamic multi-attribute decision making (DMADM) problems in which the decision making information of alternatives is collected at different stages. Firstly, the area closeness degree is applied in normalizing the raw data. Secondly, the weights of different stages are determined by according to the principle of new information priority. The technique for preference by similarity to ideal solution (TOPSIS) is improved to aggregate the information from different stages. Finally, the example is illustrated to demonstrate the practicality and effectiveness of the proposed methods.

scholarly journals TOPSIS Method Based on Complex Spherical Fuzzy Sets with Bonferroni Mean Operators

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1739
Author(s):  
Zeeshan Ali ◽  
Tahir Mahmood ◽  
Miin-Shen Yang
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Unit Interval ◽  
Polar Coordinates ◽  
Topsis Method ◽  
Bonferroni Mean ◽  
Operational Laws ◽  
Special Cases ◽  
Order Preference ◽  
Multi Attribute Decision Making

The theory of complex spherical fuzzy sets (CSFSs) is a mixture of two theories, i.e., complex fuzzy sets (CFSs) and spherical fuzzy sets (SFSs), to cope with uncertain and unreliable information in realistic decision-making situations. CSFSs contain three grades in the form of polar coordinates, e.g., truth, abstinence, and falsity, belonging to a unit disc in a complex plane, with a condition that the sum of squares of the real part of the truth, abstinence, and falsity grades is not exceeded by a unit interval. In this paper, we first consider some properties and their operational laws of CSFSs. Additionally, based on CSFSs, the complex spherical fuzzy Bonferroni mean (CSFBM) and complex spherical fuzzy weighted Bonferroni mean (CSFWBM) operators are proposed. The special cases of the proposed operators are also discussed. A multi-attribute decision making (MADM) problem was chosen to be resolved based on the proposed CSFBM and CSFWBM operators. We then propose the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method based on CSFSs (CSFS-TOPSIS). An application example is given to delineate the proposed methods and a close examination is undertaken. The advantages and comparative analysis of the proposed approaches are also presented.

Sign in / Sign up

Export Citation Format

Share Document