scholarly journals KECENDERUNGAN PEMILIHAN LOKASI PEMUKIMAN BERDASARKAN ANALISIS MULTIKRITERIA DI KOTA MANADO

2013 ◽  
Vol 12 (2) ◽  
pp. 142
Author(s):  
Winsy Christo Deilan Weku
Keyword(s):  
Decision Making ◽  
Multicriteria Analysis ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Lower Income ◽  
Order Preference ◽  
Simple Additive Weighting ◽  
Ideal Technique

KECENDERUNGAN PEMILIHAN LOKASI PEMUKIMAN BERDASARKAN ANALISIS MULTIKRITERIA DI KOTA MANADO ABSTRAK Penelitian ini bertujuan untuk menentukan faktor-faktor dominan (kriteria) yang mempengaruhi individu dalam memilih lokasi pemukiman. Selanjutnya lokasi-lokasi pemukiman diurutkan sesuai dengan selera/kecenderungan yang ada pada responden. Untuk menjembatani berbagai kriteria yang saling berbeda dari para responden, maka dapat digunakan metode Multi Criteria Decision Making (MCDM) dengan metode yang terpilih yaitu metode Penjumlahan Terboboti/Simple Additive Weighting (SAW) dan metode Jarak Terdekat ke Titik Ideal/Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), dimana kedua metode ini saling melengkapi satu sama lainnya. Dari hasil penelitian didapatkan bahwa responden secara umum, responden berpendidikan sarjana dan responden berpendapatan kelas bawah cenderung memilih lokasi pemukiman Telkom Mas sebagai pilihan utama. Berbeda halnya dengan responden berpendidikan non-sarjana dan responden berpendapatan kelas atas cenderung untuk memilih Citra Land sebagai lokasi pemukimannya. Kata Kunci : Lokasi Pemukiman, MCDM, SAW, TOPSIS   HOUSING SUITABILITY LOCATION PREFERENCE BASED ON  MULTICRITERIA ANALYSIS IN MANADO ABSTRACT The purposes of this research are to determine the dominant factors from every individual to choose their district location. Furthermore, to organized the district location according the dominant factors. For the respondent with different background, it implies to their significant criteria. Decision making problems with these characteristics are basically members of Multi Criteria Decision Making (MCDM). Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods have been developed in this study to solve this problem as comprehensive. The results of this research reveals that general respondent, higher educated respondent and lower income respondent disposed to choose Telkom Mas as their district location. Furthermore lower respondent and higher income respondent disposed to choose Citra Land as their district location. Keywords : District Location, MCDM, SAW, TOPSIS

scholarly journals Sistem Pendukung Keputusan Dalam Memetakan Wilayah Risiko Banjir Menggunakan Fuzzy Multi Criteria Decision Making

d'CARTESIAN ◽  
2014 ◽  
Vol 3 (2) ◽  
pp. 24
Author(s):  
Glorya Ontah ◽  
Winsy Weku ◽  
Altien Rindengan
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Weighting Method ◽  
Order Preference ◽  
Simple Additive Weighting

Abstrak Banjir yang melanda di berbagai wilayah Indonesia merupakan suatu fenomena logis karena negara ini berada di daerah tropis dengan intensitas curah hujan yang sangat tinggi. Penelitian bertujuan untuk memetakan daerah berisiko banjir di Kota Manado. Pemetaan wilayah berisiko banjir di Kota Manado memerlukan beberapa pendapat atau masukan dari berbagai pihak. Atribut yang digunakan yaitu kemiringan lahan (%), ketinggian wilayah (%), DAS (km), luas pemukiman/wilayah tutupan lahan (%) dan curah hujan (mm). Penentuan wilayah banjir di Kota Manado menggunakan Fuzzy Multi Criteria Decision Making (MCDM) dengan dua (2) metode yaitu Simple Additive Weighting Method (SAW) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Hasil dengan menggunakan metode SAW dan SAW Fuzzy menunjukkan bahwa wilayah paling berisiko banjir yaitu Kecamatan Wenang. Hasil dengan menggunakan metode TOPSIS dan TOPSIS Fuzzy menunjukkan bahwa wilayah paling berisiko banjir yaitu Kecamatan Bunaken. Wenang sebagai wilayah banjir disebabkan lahan yang berada di dataran landai, ketinggian wilayah di bawah 240 meter, memiliki aliran sungai, intensitas curah hujan tinggi, dan besarnya tutupan lahan mencapai 94,59%. Bunaken menjadi wilayah banjir karena Bunaken memiliki aliran sungai terpanjang di Kota Manado yaitu 17,9 km. Kata kunci: Fuzzy, Kota Manado, MCDM, SAW, TOPSIS, Wilayah Banjir.

Multi Criteria Decision Making Techniques in Urban Planning and Geology

2018 ◽  
pp. 530-568 ◽  
Author(s):  
Kadriye Burcu Yavuz Kumlu ◽  
Şule Tüdeş
Keyword(s):  
Decision Making ◽  
Urban Planning ◽  
Spatial Information ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Analytic Hierarchy ◽  
Order Preference ◽  
Geological Science ◽  
Simple Additive Weighting ◽  
Hierarchy Process

In this paper, Multi Criteria Decision Making (MCDM) processes will be clarified in the context of the disciplines related with the spatial information, as urban planning and its geographical perspective. For this purpose, first Spatial MCDM will be introduced, then the relation between the geographical data and GIS is established. Therefore, following sections include the detailed explanation of three widely used Spatial MCDM techniques, as Simple Additive Weighting (SAW), Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). These techniques will be clarified by giving examples related with urban planning and geological science.

scholarly journals Multi-criteria decision-making for flood risk management: a survey of the current state of the art

2016 ◽  
Vol 16 (4) ◽  
pp. 1019-1033 ◽  
Author(s):  
Mariana Madruga de Brito ◽  
Mariele Evers
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Flood Risk ◽  
Flood Risk Management ◽  
Decision Making Process ◽  
Multi Criteria Decision Making ◽  
Wide Range ◽  
Order Preference ◽  
Criteria Weights ◽  
Simple Additive Weighting

Abstract. This paper provides a review of multi-criteria decision-making  (MCDM) applications to flood risk management, seeking to highlight trends and identify research gaps. A total of 128 peer-reviewed papers published from 1995 to June 2015 were systematically analysed. Results showed that the number of flood MCDM publications has exponentially grown during this period, with over 82 % of all papers published since 2009. A wide range of applications were identified, with most papers focusing on ranking alternatives for flood mitigation, followed by risk, hazard, and vulnerability assessment. The analytical hierarchy process (AHP) was the most popular method, followed by Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and Simple Additive Weighting (SAW). Although there is greater interest in MCDM, uncertainty analysis remains an issue and was seldom applied in flood-related studies. In addition, participation of multiple stakeholders has been generally fragmented, focusing on particular stages of the decision-making process, especially on the definition of criteria weights. Therefore, addressing the uncertainties around stakeholders' judgments and endorsing an active participation in all steps of the decision-making process should be explored in future applications. This could help to increase the quality of decisions and the implementation of chosen measures.

scholarly journals Comparison of the Economic Performance of Turkish Republics in Central Asia with TOPSIS Method

2015 ◽  
Author(s):  
Ziya Gökalp Göktolga ◽  
Engin Karakış ◽  
Hakan Türkay
Keyword(s):  
Decision Making ◽  
Central Asia ◽  
Economic Performance ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Economic Management ◽  
Macroeconomic Indicators ◽  
Order Preference ◽  
Negative Ideal Solution

The aim of this study is to compare the economic performance of Turkish Republics in Central Asia with Multi Criteria Decision Making (MCDM) methods. Turkish Republics have been experiencing a transition from a centrally planned economy towards a market economy since their independence. In this study important macroeconomic indicators are used to determine economic performance. Economic performance evaluation of the country is an important issue for economic management, investors, creditors and stock investors. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method outranks the countries according to the proximity of the positive ideal solution and distance of the negative ideal solution. Economic Performance of Turkish Republics in Central Asia (Azerbaijan, Turkmenistan, Kazakhstan, Kyrgyzstan, and Uzbekistan) are compared with TOPSIS method. İnvestigated with TOPSIS method countries best and worst economic performance years are detected during mentioned period and results are analyzed.

scholarly journals A fuzzy multi-criteria decision-making method for purchasing life insurance in India

2021 ◽  
Vol 10 (1) ◽  
pp. 344-356
Author(s):  
Chinmaya Ranjan Pattnaik ◽  
Sachi Nandan Mohanty ◽  
Sarita Mohanty ◽  
Jyotir Moy Chatterjee ◽  
Biswajit Jana ◽  
...  
Keyword(s):  
Decision Making ◽  
Life Insurance ◽  
Complex Problem ◽  
Insurance Companies ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Insurance Company ◽  
Proposed Model ◽  
Decision Making Problem ◽  
Order Preference

Life insurance is an agreement between an insured and an insurer, where the insurer pays out a sum of money either on a specific period or the death of the insured. Now a day, People can buy a policy through an online platform. There are a lot of insurance companies available in the market, and each company has various policies. Selecting the best insurance company for purchasing an online term plan is a very complex problem. People may confuse to choose the best insurance company for buying an online term. It is a multi-criteria decision making (MCDM) problem, and the problem consists of different criteria and various alternatives. Here in this paper, a model has been proposed to solve this decision-making problem. In this model, a fuzzy multi-criteria decision-making approach combined with technique for order preference by similarity to ideal solution (TOPSIS) and it has been applied to rank the different insurance companies based on online term plans. The experimental results show that the life insurance corporation of India (LIC) gets the top rank out of 12 companies for purchasing an online term plan. A sensitivity analysis has been performed to validate the proposed model.

scholarly journals Review Article: Multi-criteria decision making for flood risk management: a survey of the current state-of-the-art

2015 ◽  
Vol 3 (11) ◽  
pp. 6689-6726 ◽  
Author(s):  
M. M. de Brito ◽  
M. Evers
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Flood Risk ◽  
Flood Control ◽  
Flood Risk Management ◽  
Multi Criteria Decision Making ◽  
Coping Capacity ◽  
Order Preference ◽  
Criteria Weights ◽  
Simple Additive Weighting

Abstract. This paper provides a review of Multi-Criteria Decision Making (MCDM) applications to flood risk management, seeking to highlight trends and identify research gaps. Totally, 128 peer-reviewed papers published from 1995 to June 2015 were systematically analysed and classified into the following application areas: (1) ranking of alternatives for flood mitigation, (2) reservoir flood control, (3) susceptibility, (4) hazard, (5) vulnerability, (6) risk, (7) coping capacity, and (8) emergency management. Additionally, the articles were categorized based on the publication year, MCDM method, whether they were or were not carried out in a participatory process, and if uncertainty and sensitivity analysis were performed. Results showed that the number of flood MCDM publications has exponentially grown during this period, with over 82 % of all papers published since 2009. The Analytical Hierarchy Process (AHP) was the most popular technique, followed by Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and Simple Additive Weighting (SAW). Although there is greater interest on MCDM, uncertainty analysis remains an issue and is seldom applied in flood-related studies. In addition, participation of multiple stakeholders has been generally fragmented, focusing on particular stages of the decision-making process, especially on the definition of criteria weights. Based on the survey, some suggestions for further investigation are provided.

Identification of User Preference for Multi-Criteria Reporting in Business Intelligence

2018 ◽  
pp. 16-47
Author(s):  
Martin Aruldoss ◽  
Miranda Lakshmi Travis ◽  
Prasanna Venkatesan Venkatasamy
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
User Preference ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Order Preference ◽  
Banking Business ◽  
Different Levels ◽  
Support Decision Making

Business intelligence (BI) is an integrated set of tools used to support the transformation of data into information in order to support decision making. Among different functionalities, reporting plays a significant role that provides information to its readers to make better decisions. BI lacks user-specific reporting to the different levels of users of an organization. Different users require different kinds of reporting with respect to different requirement (criteria) in an organization. A multi-criteria reporting (MCR) finds the suitable information to suitable user based on the multiple conflicting preferences of a user. Technique for order preference by similarity to ideal solution (TOPSIS) is the most popularly applied multi-criteria decision-making (MCDM) technique selected to identify different levels of user preference for MCR. Banking business is considered as a case study to identify user preference for MCR. This research also designs evaluation metrics for TOPSIS.

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