scholarly journals Penerapan Metode TOPSIS & SAW Dalam Pemilihan Destinasi Wisata Di Jawa Timur

2020 ◽  
Vol 5 (1) ◽  
pp. 18
Author(s):  
Irfan Mahendra ◽  
Adynoto Suprapto

This research was conducted to test the application of the Technique Order Preference by Similarity to Ideal Solution (TOPSIS) method and the Simple Additive Weighting (SAW) method in the decision-making process of choosing tourist destinations in East Java. This research is motivated by the problems faced by the Jakarta Backpacker Community who often have difficulty in making choices about tourist destinations to be visited in East Java. The criteria used in this study are cost, destination, meeting point, trip length and facilities obtained. The results of this study indicate that The TOPSIS method and the SAW Method can be used for the decision-making process in the selection of tourist destinations in East Java, with the results of Explore Baluran and Menjangan being the most recommended choices as the primary choice. Besides, it is also known that there is a match between the TOPSIS and SAW methods, with the calculation results using the TOPSIS method that is 0.64 and the calculation using the SAW method is 0.86 as the highest calculated value. So as such, these two methods can be stated equally well used in the process of determining tourist destinations in East Java. However, this applies only to the highest value, because for the order of two and so on, the results of calculations on these two methods show differences in rank.

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Aditya Chauhan ◽  
Rahul Vaish

An attempt has been made to rank and classify potential fluids for power production through organic rankine cycle (ORC) using technique for order preference by similarity to ideal solution (TOPSIS) method. In order to calculate subjective weights for the attributes under study, the modified digital logic (MDL) method has been used. It has been observed under two different case studies that R601 (pentane) shows promising results. These fluids are further classified using dendrogram, a hierarchical clustering technique. Finally Pearson's correlation coefficient is calculated for the attributes to find out the nature and degree of correlation between different attributes under study.


Author(s):  
Merve Cengiz Toklu

Decision-making process is the selection of the most appropriate one among the alternatives. Different selection criteria are considered in the decision-making process. Simultaneous assessment of different evaluation criteria may not always be possible. Multi-criteria decision-making techniques provide an easily applicable mathematical solution in this respect. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is one of the multi-criteria decision-making techniques. This method is used in many problems in literature and allows multiple decision makers to choose the most suitable alternative by evaluating them together with different criteria. Assessments of decision makers may include linguistic statements. In this case, the Fuzzy Logic approach can be used. In this chapter, Fuzzy TOPSIS method is explained with a detailed numerical example.


2020 ◽  
Vol 12 (10) ◽  
pp. 4044
Author(s):  
Marko Stokic ◽  
Davor Vujanovic ◽  
Dragan Sekulic

The efficient vehicle procurement is an important business segment of different companies with their own vehicle fleet. It has a significant influence on reducing transport and maintenance costs and on increasing the fleet’s energy efficiency. It is indispensable that managers consider various criteria from several aspects when procuring a vehicle. In that sense, we defined 13 relevant criteria and divided them into four multidisciplinary aspects: Construction-technical, financial, operational, and environmental. Decision-Making Trial and Evaluation Laboratory-Based Analytic Network Process (DANP) method was applied to evaluate the significance of defined criteria and aspects and their interdependency. It is established that the three most important criteria for vehicle procurement are vehicle price, vehicle maintenance, and vehicle selling price. The most important aspect is construction technical aspect, while the aspect of the environment is the least important. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was used to rank eight different vehicles, which were considered by vehicle fleet manager at the observed company. This model assists fleet managers in the selection of the most suitable vehicle for procurement, while significantly reducing decision-making time and simultaneously observing all necessary criteria and their weights. Moreover, we have considered 10 different scenarios to establish whether and how the rank of the observed alternatives would change.


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.


2016 ◽  
Vol 16 (4) ◽  
pp. 1019-1033 ◽  
Author(s):  
Mariana Madruga de Brito ◽  
Mariele Evers

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.


2019 ◽  
Vol 8 (2) ◽  
pp. 121-129
Author(s):  
Febri Hadi ◽  
Dodi Guswandi

The decision-making system for the selection of new postgraduate student admissions which is carried out manually requires 7 days to submit the decision results. The selection is very important, so that the quality of input (input) of prospective students can be maintained in accordance with established standards. Therefore we need a system that can help in the decision making process quickly, precisely, and accurately. The purpose of this study is to help postgraduate master's study programs in conducting the selection of prospective graduate students in accordance with their abilities and disciplines. The method used in data processing using the Simple Additive Weighting (SAW) method, is a method of weighting the sum of the criteria values ​​of each alternative. The results of the decision in the form of ranking the number of values, based on the passing grade value that has been set> 0.70 declared passed, or <0.70 declared not passed.


Author(s):  
Ziya Gökalp Göktolga ◽  
Engin Karakış ◽  
Hakan Türkay

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.


2021 ◽  
Vol 11 (2) ◽  
pp. 19-30
Author(s):  
Derman Janner Lubis ◽  
Nur Amalina Anindita

The selection of vendors to work on a project is an activity that must be carried out effectively and precisely so that the project is carried out in accordance with business needs and does not suffer losses. To get the best vendor ranking, you can use the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) calculation method. TOPSIS method is a method that generates rankings by calculating the distance between the best solution and the worst solution. The steps to calculate using TOPSIS are identification of alternatives and their values, create a decision matrix, normalize the matrix, calculate the normalization matrix, look for positive and negative solutions, calculate the distance between positive and negative solutions, and calculate relative closeness and sort preferences. In this study using 8 criteria and 5 alternative vendors. Research method using research and development. This method will produce a prototype. The results of the calculation of TOPSIS obtained vendor c who gets the highest score and vendor b with the lowest rank


Author(s):  
Mohammad Azadfallah

In existing literature, there are several studies on supplier selection process, which opine that the suppliers information is usually incomplete and uncertain. Several methods have been proposed for solving this problem, one of which is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with interval data. There is no doubt that the TOPSIS with interval data method is a powerful technique in uncertain decision-making context. Despite its usefulness, it is logical that when data are imprecise, weight is imprecise too. To overcome this limit, the extended Shannons Entropy method with interval data is used. The main findings of this study confirm the effectiveness of the hybrid proposed models.


Author(s):  
Rahmat Doni ◽  
Faisal Amir ◽  
Dicky Juliawan

Promotion is one way to Rumah Bermain Bilal to improve the performance of tutors in educating their students. The problem of leadership in decision-making still uses the choice of methods and assessment processes subjectively so that the process is not in accordance with the goals of the career path. Therefore, it is necessary to make a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method to help make decisions. In this study, using the criteria set by the company, namely planning, learning, evaluation, and training. The ranking results obtained from testing the calculations that the alternative Tutor F is the best tutor with the results of the calculation of 0.804 when compared to the other twelve alternatives. The TOPSIS method has a data accuracy rate of 85% from thirteen alternatives and can be used as a support for leadership decisions to make recommendations for increasing the career path of tutors.


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