A Fuzzy Topsis Multiple-Attribute Decision Making for Scholarship Selection

As the education fees are becoming more expensive, more students apply for scholarships. Consequently, hundreds and even thousands of applications need to be handled by the sponsor. To solve the problems, some alternatives based on several attributes (criteria) need to be selected. In order to make a decision on such fuzzy problems, Fuzzy Multiple Attribute Decision Making (FMDAM) can be applied. In this study, Unified Modeling Language (UML) in FMADM with TOPSIS and Weighted Product (WP) methods is applied to select the candidates for academic and non-academic scholarships at Universitas Islam Negeri Sunan Kalijaga. Data used were a crisp and fuzzy data. The results show that TOPSIS and  Weighted Product FMADM methods can be used to select the most suitable candidates to receive the scholarships since the preference values applied in this method can show applicants with the highest eligibility.      

Fuzzy TOPSIS method for a tourism destination

In this study, we intended to create a methodology in order to have a Multi Criteria approach for choosing a tourist destination region or place as Multi Criteria Decision Making (MCDM) is widely used to outrank, choose or cluster the alternatives with respect to multiple criteria and, in general, refers to making decisions among multi alternatives in the presence of multiple, usually conflicting criteria. Conflicting criteria often makes the problem difficult to decide and select the best alternative among the possible choices. To do this, we propose a Fuzzy TOPSIS Method to choose a Tourism destination in Portugal.info:eu-repo/semantics/publishedVersio

Surat Keterangan dan Artikel Supplier Selection of 40th Container in PT Tribudhi Pelita Indonesia Using Analytical Hierarchy Process (AHP) Method

Supplier selection is one of the most important things in business. The pattern of selecting suppliers that is not right at this time will affect business continuity; therefore this study was conducted to analyze problems related to supplier selection. Data collection was carried out by interview to related department, observation and literature study. The location and focus of this research are at PT Tribudhi Pelita Indonesia, the first company in Jakarta. PT Tribudhi Pelita Indonesia is engaged in buying and selling container 40th. From the data collection, it was obtained several alternative suppliers, namely "A", "B" and "C". Meanwhile, the criteria include delivery quality, product quality and cost. Data processing uses one of the MCDM (Multi Criteria Decision Making) methods, namely AHP (Analytic Hierarchy Process), so that the supplier "B" is determined to be the best supplier. It is hoped that this research can be an alternative in choosing a 40th container supplier, so that the business can sustainably be maintained

Evaluation of e-learning web sites using fuzzy axiomatic design based approach

High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered

مکانیابی بهینه حسگرهای مانیتورینگ ترافیکی با استفاده از روش سلسله مراتبی فازی و روش تاپسیس

امروزه شبکه حسگرهای هوشمند به عنوان یکی از روش های نوین اخذ اطلاعات، در مدیریت ترافیک مطرح است که با امکان پایش هوشمند معابر شهری منجر به کاهش سوانح جاده ای می گردد. علیرغم اهمیت نصب و استقرار چنین تجهیزاتی مهمترین دغدغه تعیین مکان بهینه جهت نصب آنهاست. بنابراین آنچه در این تحقیق هدف ماست ارائه روشی مناسب در جهت مکانیابی بهینه حسگرهای ترافیکی است، روش پیشنهادی ترکیبی از روش های فازی سلسله مراتبی و تاپسیس است. لازم به ذکرست که برای تست روش پیشنهادی در این تحقیق بخشی از شبکه معابر شهری در شمال آمریکا به عنوان داده نمونه انتخاب گردید. در مرحله بعد با نظر کارشناسان ترافیک معیارهای تعیین مکان بهینه انتخاب گردید که در این تحقیق عبارت بودند از ترافیک متوسط سالیانه، شدت تصادفات، شیب متوسط و فاصله هر اتصال در شبکه شهری تا مکان های نیازمند کنترل ترافیک.برای مشخص کردن میزان اهمیت معیارهای ورودی از روش سلسله مراتبی فازی استفاده گردید، این روش با استفاده از اعداد فازی در مقایسه زوجی معیارها برای محاسبه وزن آنها، منجر به افزایش دقت محاسبات می گردد. در مرحله بعد وزن های محاسبه شده با استفاده از روش تاپسیس به رتبه بندی اتصالات شهری در محدوده مورد مطالعه پرداخت. در نهایت بعد از اجرای تحلیل مذکور با استفاده از نمره حاصل از روش تاپسیس اتصالات شهری در منطقه مورد مطالعه به سه کلاس متفاوت طبقه بندی شدند. اتصالات شهری قرار گرفته در کلاس اول به عنوان اتصالات شهری با بیشترین اولویت برای نصب حسگرها انتخاب شدند. بنابراین اتصالات مذکور در بیشترین اولویت برای نصب حسگرهای ترافیکی خواهند بود

Prioritizing Barriers and Strategies Mapping in Business Intelligence Projects Using Fuzzy AHP TOPSIS Framework in Developing Country

Business Intelligence (BI) is an essential technology in an increasingly competitive landscape since it helps make decisions more accurately. To achieve an effective BI implementation, the organization must formulate the right strategy to overcome its challenges. This research aimed to develop a framework to map barriers into strategies using qualitative and quantitative methods. The qualitative approach is driven by interviewing BI experts to validate the barriers and strategies previously obtained. Based on the interview, there are 19 barriers and 9 strategies that could be used. The quantitative approach compiles a priority list of the most significant barriers and the most effective strategies to overcome these barriers using fuzzy AHP TOPSIS, an MCDM method to eliminate inconsistencies during ranking. The results indicate that the lack of collaboration between the IT and BI departments, the BI implementation demands to be done quickly, and low data quality are the main barriers that hinder BI's success. This research also found that business people's involvement in a BI project is the best strategy to overcome the obstacles. The chances of a successful BI implementation will increase by having good cooperation between IT and business units within the company. Doi: 10.28991/ESJ-2022-06-02-010 Full Text: PD

Return on strategic effectiveness – the need for synchronising growth and development strategies in the hotel industry using revenue management

The purpose of this paper is to identify the essential determinants, and highlight the importance, of synchronising the growth and development strategies of hotel companies. The paper aims to analyse preconditions to successful and stable business performance and customer loyalty. The paper is based on the hypothesis that strategic and organisational effectiveness helps to create preconditions to stable business in the future, which is reflected in satisfactory growth, financial strength and solvency, and results in creating added value. The five-year financial data of three hotel companies with similar business orientation from Istria County (Croatia) were used to test the model for synchronising growth and development strategies in the hotel industry and the fuzzy logic-based growthdevelopment synchronisation coefficient. The model was tested on multi-annual results (the period 2010–2014), and conclusions and recommendations were made for a future work

Decision-making in fuzzy environment

Decision-making is a logical human judgment process for identifying and choosing alternatives based on the values and preferences of the decision maker that mostly applied in the managerial level of the concerned department of the organization/ supply chain. Recently, decision-making has gained immense popularity in industries because of their global competitiveness and to survive successfully in respective marketplace.Therefore, decision-making plays a vital role especially in purchase department for reducing material costs, minimizing production time as well as improving the quality of product or service. But, in today’s real life problems, decision-makers generally face lot of confusions, ambiguity due to the involvement of uncertainty and subjectivity in complex evaluating criterions of alternatives. To deal such kind of vagueness in human thought the title ‘Decision-Making in Fuzzy Environment’ has focused into the emerging area of research associated with decision sciences. Multiple and conflicting objectives such as ‘minimize cost’ and ‘maximize quality of service’ are the real stuff of the decision-makers’ daily concerns. Keeping this in mind, this thesis introduces innovative decision aid methodologies for an evaluation cum selection policy analysis, based on theory of multi criteria decision-making tools and fuzzy set theory. In the supplier selection policy, emphasis is placed on compromise solution towards the selection of best supplier among a set of alternative candidate suppliers. The nature of supplier selection process is a complex multi-attribute group decision making (MAGDM) problem which deals with both quantitative and qualitative factors may be conflicting in nature as well as contain incomplete and uncertain information. Therefore, an application of VIKOR method combined with fuzzy logic has been reported as an efficient approach to support decision-making in supplier selection problems. This dissertation also proposes an integrated model for industrial robot selection considering both objective and subjective criteria’s. The concept of Interval-Valued Fuzzy Numbers (IVFNs) combined with VIKOR method has been adapted in this analysis