Fuzzy Simple Additive Weighting Research Articles

Analysing Factors Driving Purchase and Consumption Behaviour Towards Organic Food

Personal health, food safety and environmental concerns significantly contribute to the purchase and consumption of organic food. Several countries, including India, are turning their attention to encouraging organic food farming and purchasing to comply with sustainable development goals. This research identifies and analyses the motivational factors critical to the purchase and consumption of organic food and also extends a roadmap to the food industries for sustainable growth. A list of factors driving the purchase and consumption of organic food was extracted from the literature. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS), Fuzzy Simple Additive Weighting (Fuzzy SAW) and Borda method are used to prioritize the identified motivational factors followed by the sensitivity analysis to simulate dynamic various market requirements and challenges. The findings substantiate that chemical free, no artificial ingredients, good for body, healthy and awareness about health significantly influence the purchase and consumption of organic food products. To ensure sustainable production and consumption of organic food, it is vital for government policymakers, organizations involved in production, marketing and distribution of the organic food to understand and critically evaluate various factors affecting the purchase and consumption intensions of the consumers.

Neutrosophic Fuzzy Simple Additive Weighting with Artificial Intelligence for Sustainable Heart Disease Recognition and Classification

Heart disease (HD) is considered the main cause of death rate around the world. Multiple systems and biomedical instruments in hospitals take large amounts of medical data. Thus, understanding the data linked with HD is vital to enhance the prediction performance. The timely intervention of HD is the most important factor in preventing patients from additional damage. In recent times, non-invasive medical procedures, including artificial intelligence-based approaches have been used in the healthcare sector. Particularly machine learning (ML) applies various techniques and algorithms that are extensively applied and are especially effective in accurately detecting HDs within short period. However, HD prediction is a challenging task. The largest size of medicinal database has made it a challenge for clinicians to understand the complicated feature relations and make disease predictions. Therefore, this study presents a Neutrosophic Fuzzy SAW with Artificial Intelligence for Sustainable Heart Disease Recognition and Classification (NFSAW-AISHDC) technique in Healthcare Sector. The NFSAW-AISHDC technique mainly focuses on the adoption of neutrosophic fuzzy simple additive weighting (NFSAW) with feature selection process for HD detection. The NFSAW-AISHDC method exploits min-max scalar to scale the input medical data. For feature selection, the NFSAW-AISHDC method uses beluga whale optimization (BWO) algorithm to choose feature subsets. Moreover, the NFSAW-AISHDC technique applies NFSAW approach to the identification of HDs. The performance values of the NFSAW-AISHDC methodology undergoes using benchmark database. The experimental outcome underlined the promising results of the NFSAW-AISHDC method with other models.

ANALISIS KEPUTUSAN MENGGUNAKAN METODE CUT OFF POINT DAN FUZZY SIMPLE ADDITIVE WEIGHTING DALAM MENENTUKAN JENIS LAPTOPTERBAIK PADA MAHASISWA MATEMATIKA FMIPA UNIVERSITAS NEGERI PADANG

The emergence of various types and brands in the laptop industry poses problems for consumers in determining the best type of laptop. To assist consumers in determining the best type of laptop, a Decision Support System is needed. This research is an applied research. The data used is primary data obtained from the distribution of questionnaires through Google Form to students of the Department of Mathematics UNP batch of 2020, 2021, 2022. The variables used are Brand, Operating System, Processor, Solid State Drive, Random Access Memory, Battery, Screen Size, Laptop Weight, Color, Price. The methods used in this study are the Cut Off Point Method and the Simple Additive Weighting method. Based on the results of the problem analysis in determining the best laptop type using the Cut Off Point and Fuzzy Simple Additive Weighting methods, it shows that the Asus zenBook Pro laptop type is recommended as the best type of laptop with a preference value of 0.87

Renewable Energy Transition Task Solution for the Oil Countries Using Scenario-Driven Fuzzy Multiple-Criteria Decision-Making Models: The Case of Azerbaijan

The renewable energy transition of oil- and gas-producing countries has specific peculiarities due to the ambivalent position of these countries in the global energy market, both as producers and consumers of energy resources. This task becomes even more challenging when the share of oil and gas in the country’s GDP is very high. These circumstances pose serious challenges for long-term energy policy development and require compromising decisions to better align the existing and newly created energy policies of the country. The scale, scope, and pace of changes in the transition process must be well balanced, considering the increasing pressure of economic and environmental factors. The objective of this paper is to develop models that allow the selection of the most appropriate scenario for renewable energy transition in an oil- and gas-producing country. The distinguishing feature of the proposed model is that alternatives in the decision matrix are presented as scenarios, composed of a set of energy resources and the level of their use. Linguistic descriptions of the alternative scenarios are formalized in the form of fuzzy statements. For the problem solution, four different Multiple-Criteria Decision-Making (MCDM) methods were used: the fuzzy simple additive weighting (F-SAW) method, the distance-based fuzzy TOPSIS method (Technique of Order Preference Similarity to the Ideal Solution), the ratio-analysis-based fuzzy MOORA method (Multi-Objective Optimization Model Based on the Ratio Analysis), and the fuzzy multi-criteria optimization and compromise solution method VIKOR (Serbian: VIekriterijumsko Kompromisno Rangiranje). This approach is illustrated using the example of the energy sector of Azerbaijan. The recommended solution for the country involves increasing natural gas (NG) moderately, maintaining hydro, and increasing solar notably and wind moderately.

A novel fuzzy SECA model based on fuzzy standard deviation and correlation coefficients for resilient-sustainable supplier selection

Selecting the best out of a pool of potential suppliers is one of the most significant challenges in supply chain management. Although numerous works have studied supplier selection (SS) as a function of individual criterion (e.g., sustainability or resiliency), few studies have explored it as an all-in-one. To address this gap, this study proposes a novel fuzzy multi-criteria decision-making (MCDM) framework for a real-world color and glaze case study. First, resilient-sustainable criteria are identified for evaluating the performance of the suppliers. Expert opinions and literature review are then utilized to establish a set of criteria in two different categories: sustainability and resiliency. This two-pronged approach ensured that important criteria are considered in the evaluation process. Next, a new fuzzy simultaneous evaluation of criteria and alternatives (FSECA) model is developed to highlight the most crucial criteria and the best supplier. The proposed model utilizes a predetermined set of criteria reference weights as benchmarks to calculate the final weights that closely align with these reference points. Moreover, the consideration of fuzzy standard deviation and correlation coefficients of fuzzy numbers are incorporated to take into account the inherent variability and uncertainty in the data, resulting in a more accurate and robust analysis of the data. To validate the proposed method, the findings are compared to the state-of-the-art fuzzy approaches for SECA method, and other MCDM techniques such as fuzzy weighted aggregated sum product assessment (FWASPAS), fuzzy technique for order performance by similarity to ideal solution (FTOPSIS), fuzzy Multi-Objective Optimization on the basis of Ratio Analysis (FMOORA), fuzzy simple additive weighting (FSAW), and fuzzy complex proportional assessment (FCOPRAS). Moreover, by applying the geometrical analysis for interactive aid (GAIA), a visualization approach, the results demonstrate that the performance of the proposed framework is satisfactory and highlight the most crucial criteria, such as the supplier responsiveness in resiliency and delivery in economic impact of sustainability categories. Since choosing supplier is a strategic decision, the proposed work can help managers to choose the right suppliers.

Penggabungan Metode Fuzzy Simple Additive Weighting dengan Rank Order Centroid sebagai Pendukung Keputusan Penilaian Kemiskinan di Jawa Timur

The purpose of this study is to determine the results of the combination of Fuzzy Simple Additive Weighting with Centroid Rank Order as a support for poverty assessment decisions in East Java Province. Using a combination of Fuzzy Simple Additive Weighting and Rank Order Centroid is expected to provide better results. Decision support systems can help the government to determine the poverty status of a district or city in poverty reduction. Poverty itself is an important problem in life in many provinces. The problem of poverty triggers social problems that are closely related to the quality of education, crime, hunger, and others, which cause indirect disruption of stability and sustainability. Therefore, a decision support system is needed to make it easier for the government to determine the poorest districts or cities so that the government can aid programs or make strategies to reduce poverty. Fuzzy logic is a method that can be used to overcome uncertainty in decision making. One method in fuzzy logic to overcome uncertainty is to use the Fuzzy Simple Additive Weighting method. In the Fuzzy Simple Additive Weighting method, there is a selection of criteria that will later be weighted based on importance or priority using the Rank Order Centroid method. The criteria used in this study are life expectancy (AHH), literacy rate (AMH), per capita expenditure, and population. The membership function used is the Tringular Fuzzy Number representation. In this study, twenty four rules were given which were obtained from giving different weights to each criterion. So that twenty four of the poorest districts or cities were obtained. Then the final result is the name of the most Regency or City from the twenty four results, namely alternatives twenty seven and twenty eight, namely Sampang Regency and Pamekasan Regency which were entitled to assistance programs from the government.

Performance assessment and comparison of online food delivery service providers based upon the aggregated perspectives of restaurant operators

Online food delivery businesses have grown rapidly during the past few years. To attract customers, food delivery service providers are forming partnerships with as many restaurants as possible. For restaurant entrepreneurs, the selection of the best service provider is a critical decision that influences their sales. However, many qualitative criteria make this problem difficult. Although rating scales can convert subjective judgments into quantitative analysis, linguistic scales may make a comparison of alternatives’ performances vague and unstandardised, especially for group decision making. The prioritisation of the criteria importance is also questionable, and reaching a consensus among decision makers might be difficult. To address such complications, this study proposes the use of fuzzy logic in determining the importance weights of the criteria in the direct rating approach, based on the perspectives of 60 restaurant operators in Thailand. The fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) is then used to rank alternatives, as demonstrated by a case of three food delivery providers in Thailand. Fuzzy simple additive weighting (fuzzy SAW), two rank-based weighting methods (rank sum and rank-order centroid), and two objective weighting methods (entropy and mean) are used to compare results. The results show that user-friendly apps, tracking systems, payment options, marketing campaigns, and service areas are among the important criteria that delivery service providers should address and improve in order to attract more restaurants and customers. Guidelines for restaurant operators to choose the appropriate weighting methodology and to rationally assess and compare the service providers’ performances are provided.

Application of Fuzzy Simple Additive Weighting Method in Group Decision-Making for Capital Investment

Investment management is a common process and practice used for achieving a desirable investment goal or outcome. Unfortunately, the systematic variation of economic situations in the marketplace effects the continuous and frequent change of investment conditions and environment in which the investor should act and operate. Hence, the rules required for providing a reasonable quality of investment projects can be based only on the investor’s management strategy, intuition and practice. There exists various decision-making approaches to investment management, and simple additive weighting (SAW) is one of the most well-known multicriteria decision-making (MCDM) methods aiming to provide an optimal decision for the decision-maker when solving various real-life problems, particularly investment problems. In this paper, the fuzzy simple additive weighting (FSAW) method is applied in group decision-making to undertake capital investment expenditure for purchasing cars with the purpose of renting them out to the public. A numerical example illustrates the importance and effectiveness of the suggested approach with the aim of ranking alternatives, and, hence, determining the preferred alternative in the MCDM problem.

Penerapan Metode Fuzzy Simple Additive Weigting Pada Interpretasi Hasil Penilaian Promosi Jabatan Pegawai Negeri Sipil

The Fuzzy Simple Additive Weighting (FSAW) method is a mechanism that can be used to support decision making. This method was chosen because a ranking process was carried out to determine the weight value of each attribute, which would select employees who were worthy of occupying the promoted position. This study aims to determine the results of the application of the FSAW method in the assessment of civil servant promotion at the Malang City Education and Culture Office to increase objectivity and fairness in the assessment of employee promotion. Some problems that often occur in employee evaluation are the employee evaluation process which is still conventional so that it is less effective in calculation. The solution to overcome this problem is to use a Fuzzy Multi Attribute Decision Making (FMADM) decision support system with the FSAW method. This method requires a process to normalize the decision matrix (X) against a scale that can be compared with all available alternative values. After each attribute has been determined its weight value, the ranking process is used to select the best alternative for this study. The criteria used in this decision support system are SKP score, length of service, class, and education. The membership function used is the Triangular Fuzzy Number (TFN) representation. The results of the ranking calculation or the best value show the highest value, namely 1 from alternative 1 (employee 1) who is entitled to a promotion. It is expected that by using the FSAW method, the task of selectors will be able to more quickly and precisely identify employees who are worthy of occupying positions promoted based on the desired conditions.

Rice Planting Decision Support System Using the Fuzzy Simple Additive Weighting (SAW) Method

In the era of evolution 4.0 currently has very rapid technological advances. This technological advancement is very useful in several sectors including the agricultural sector. The agricultural sector in Indonesia is the most superior sector because it is the livelihood of the population in Indonesia as farmers. Human resources are important to improve the social or economic quality in society. Gadingsari Village is one of 4 villages in the Sanden sub-district which is located in the westernmost area which has potential in the agricultural sector. Most residents of Gadingsari village depend on work as farmers. Therefore, it can be said that the agricultural sector has a major role in the economy and welfare of the people of Gadingsari village. Using the FSAW method, it can assist in determining quality yields. This study aims to analyze rice cultivation in Gadingsari village which can help local communities to find out information about planting rice correctly and can produce quality rice. The result of this research is a website to analyze the best rice yields with the criteria of rice varieties, rice seeds, planting, fertilizers, harvesting age, and pests.

Investigating the Stability of the Hill of the Acropolis of Athens, Greece, Using Fuzzy Logic and Remote Sensing Techniques

The main objective of this study was to investigate the stability of the Acropolis Hill, Greece, by developing a Rock Instability Model (RIM) based on fuzzy logic and remote sensing techniques. RIM aimed to identify locations on the rock formations of the Acropolis Hill that will potentially have instability issues due to the action of geomorphological factors, weathering and erosive processes. Six factors including lithology, slope angle, density of discontinuities, density of faults, density of surface runoff elements, and the orientation of the stratigraphy of the geological formations in relation to the orientation of the slope were considered as the most appropriate for implementing the proposed novel approach, with each variable classified and weighted by a fuzzy simple additive weighting method. Lithology and slope angle were considered the most significant variables that contributed to the overall stability of the Acropolis Hill. The outcomes of the RIM model were verified by remote sensing data and field observation, showing an agreement and high accuracy. From the satellite data analysis, it was concluded that for the entire Acropolis Hill, minor displacement rates were recorded, probably because of the extensive mitigation measures and consolidation works established in the recent past. Overall, the study highlighted the ability of the proposed methodology to be used as an alternative investigation tool in rock instability-related assessments valuable to land use planning and development, helping reduce the anticipated losses in highly susceptible zones.

Application of Fuzzy TRUST CRADIS Method for Selection of Sustainable Suppliers in Agribusiness

This study deals with the selection of a sustainable supplier on the example of the agribusiness company Mamex from Bosnia and Herzegovina. The main problem of this research is the selection of a sustainable supplier as a part of the sustainable strategy of the Mamex company. One of the prerequisites is that suppliers must present sustainability principles in business by having an appropriate certificate. The results of the selection of sustainable suppliers are completed using a new hybrid fuzzy approach with the methods IMF SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) and fuzzy TRUST (multi-normalization multi-distance assessment) CRADIS (compromise ranking of alternatives from distance to ideal solution) methods. The innovative approach is reflected in the use of a combination of these methods, especially by combining the TRUST and CRADIS methods into one method. The IMF SWARA method shows that the most important main criterion is the economic criterion, while the least important is the social criterion. By applying the fuzzy TRUST CRADIS method, it is found that out of the observed six suppliers, the second supplier has the best indicators. These results are confirmed by other fuzzy methods: MABAC (multi-attributive border approximation area comparison), WASPAS (weighted aggregated sum product assessment), fuzzy SAW (simple additive weighting), MARCOS (measurement of alternatives and ranking according to compromise solution), ARAS (a new additive ratio assessment), and TOPSIS (technique for order preference by similarity to an ideal solution). This research shows that applying more normalization when ranking alternatives reduces the influence of individual normalizations, and this approach should be used in future research.

EFQM and business model relation effect on performance of manufacturing enterprises

In the changing business environment conditions, one of the primary management tasks is competitiveness enhancement. This goal can be achieved, among other things, by improving performance, which has the greatest impact on business success. This research paper aims to indicate that the alignment between the European Foundation for Quality Management (EFQM) model and the business model leads to an increase in enterprise performance. By applying the Fuzzy Simple Additive Weighting (FSAW) method and fuzzy algebra rules, the aggregated value of quality was calculated. Determining the value of the considered performance is set as a fuzzy decision-making problem. Aggregated performance value is given by fuzzy geometric mean with combined fuzzy algebra rules. By applying correlation analysis, the significance of the influence of business models and quality models on the value of performance was determined. The proposed model was tested on a sample of 20 SMEs that operate in the Republic of Serbia.

Energy Security Assessment Based on a New Dynamic Multi-Criteria Decision-Making Framework

Access to energy resources and broadly understood energy security are some of the critical factors influencing the economic development of countries. This article deals with the problem of assessing the energy security of countries, considering this problem in various periods of time, examining the past, present and forecasted future conditions at the same time. For this purpose, the Dynamic Multi-Criteria Decision Making (DMCDM) methodology was developed and applied, based on the classic and fuzzy Multi-Criteria Decision Making (MCDM) methods and the International Energy Security Risk Index (IESRI). In particular, the Simple Additive Weighting (SAW)/Fuzzy SAW and New Easy Approach to Fuzzy PROMETHEE II (NEAT F-PROMETHEE) methods were used. These methods are significantly different from each other in the calculation procedures used. The study showed that methodological differences between these methods cause large differences in the results of the assessment of energy security of countries. However, both methodological approaches indicated the high energy security of New Zealand, Norway, Denmark and the United States, and the very low security of Ukraine, Thailand and South Korea. The results of the assessment of energy security of countries over the 2015–2025 period are the main practical contribution of this article. The scientific contribution of the article consists in developing a framework for dynamic energy security assessment that allows for the aggregation of many periods of time and that defines the aggregation strategies, capturing data from the past, present and future state forecasts while taking into account changes in the weights of criteria and changes in the sets of alternatives and criteria.

The attitude of MCDM approaches versus the optimization model in finding the safest shortest path on a fuzzy network

This paper examines the performances of the multi-criteria decision-making (MCDM) methods and optimization model in solving multi-attribute shortest path problems such as the safest shortest path under a fuzzy environment. To the best of the knowledge of the authors, this is the first study performing comparative analysis on finding the multi-attribute shortest path by employing well-known techniques in terms of computational effort and results in a fuzzy environment. To this end, the safest shortest path problem, where the risk and distance values concerning arcs on a directed network are defined as triangular fuzzy numbers, is handled. The solution process is carried out under two main headings: (i) To start the solution with MCDM methods, an auxiliary algorithm that constructs a fuzzy decision matrix is proposed. Then, Fuzzy-Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS), Fuzzy Simple Additive Weighting (F-SAW), and Fuzzy Evaluation Based on Distance from Average Solution (F-EDAS), that are fuzzy-based MCDM methods, are employed to rank the alternative paths. (ii) A multi-objective fuzzy optimization model is formulated, and the most reasonable paths are obtained considering different α-cut levels. Following that, comparative analysis is performed through a set of scenarios considering the different weights of the criteria to see the variability in the rankings. Besides, the addressed fuzzy-based MCDM methods are compared in terms of computational complexity. Overall, the main findings and managerial insights regarding the effectiveness and performance of the methods discussed in the solution process are provided.

Evaluating the destination management performance of small islands with the fuzzy best-worst method and fuzzy simple additive weighting

ABSTRACT This work combines the fuzzy best-worst method for assigning weights of indicators and the fuzzy simple additive weighting method for evaluating performance, along with the TALC model, in generating a single-valued index that would holistically describe the performance of a destination (e.g. small islands). Grounded on a real-world application, the evaluation process proved useful in evaluating the performance of Bantayan Island (Philippines), with a high degree of flexibility in dealing with variations of domain applications with different groups of decision-makers in different settings. The findings, although highly case-specific, offer starting points of discussion in managing small island destinations.

The Assessment of the Key Competences for Lifelong Learning—The Fuzzy Model Approach for Sustainable Education

Contemporary education in higher education institutions has a goal to provide necessary competences determined by legislative demands, science trends and job market needs to graduated students intending to strengthen their employability. The main idea of this research is to assess the level of students’ competences for lifelong learning (LLL). Since it is a very complex task, it is characterized by a lack of information and the vagueness of the inherently subjective nature of human thinking. The uncertain values of the assessed level of students’ competences for LLL are represented by linguistic expressions which are modeled by the interval type 2 trapezoidal fuzzy numbers. Ranking of the level of students’ competences for LLL is stated as a fuzzy multi-criteria optimization task. The aggregation of students’ opinions into unique marks is given by using the proposed fuzzy Delphi technique. The rank of students’ competences for LLL is given by using the proposed fuzzy Simple Additive Weighting (FSAW). The order of measures that should be delivered to improve students’ competences is based on the obtained rank. The model is tested and discussed on the real data collected from a significant sample of the students with a proposal of future directions of the research.

Modification of the Logarithm Methodology of Additive Weights (LMAW) by a Triangular Fuzzy Number and Its Application in Multi-Criteria Decision Making

The Logarithm Methodology of Additive Weights (LMAW) method is a very young method and in its basic form is defined for crisp values. In this paper, the LMAW method was improved by being modified with triangular fuzzy numbers. The modification significantly improved the capacity of the LMAW method to consider uncertainty in decision making. The special importance of the method is reflected in a relatively simple mathematical apparatus due to which it is possible to define, with high quality, weight coefficients of criteria and rank alternative solutions in uncertain environments. The method was tested in solving the problem of the location selection for a landing operations point (LOP) in combat operations of the army. The validation of the obtained results was performed: (1) by means of comparison with the Fuzzy Simple Additive Weighting (FSAW) Method, the Fuzzy Multi-Attributive Border Approximation area Comparison (FMABAC), the fuzzy Višekriterijumsko KOmpromisno Rangiranje (FVIKOR), the fuzzy COmpressed PRoportional ASsessment (FCOPRAS), and the fuzzy Multi Attributive Ideal-Real Comparative Analysis (FMAIRCA); (2) by means of sensitivity analysis by changing the weight coefficients of criteria; and (3) using simulation software. In comparison with other methods, the quality of the ranking of alternative solutions was confirmed, which highlighted the special importance of the fuzzy LMAW method relative to that of certain standard methods, respectively, the ones that are often used and confirmed in practice. On the other hand, the sensitivity analysis, including the changing of the weight coefficients of criteria, showed that the model could tolerate smaller errors in defining the weight coefficients of criteria, and it provided stable results. Finally, the validation of results achieved with the use of simulation software confirmed the obtained output results. The output results confirmed the quality of the modified method.

PENERAPAN FUZZY MULTIPLE ATTRIBUTE DECISION MAKING DALAM PEMILIHAN TEMPAT INDEKOS

Boarding house is an alternative choice for students to fulfill their need for a place to live. The variety of boarding houses, along with their respective advantages and disadvantages, becomes a challenge for students in determining the boarding house that suits their desires and needs. An in-depth evaluation is needed by comparing boarding houses based on certain criteria. In this study will be known the best boarding house based on four assessment criteria, price, facility, location, and room area. This research was conducted in Mathematics Department, Udayana University, using the combination of Fuzzy Analytic Hierarchy Process (FAHP) and Simple Additive Weighting (SAW) method. Sample in this study amounted to 118 respondents, with purposive sampling was the sampling technique. FAHP method is used to obtain the weight of each criterion, with the use of triangular fuzzy numbers for pairwise comparison scale of FAHP, and the use of the extent analysis method for the synthetic extent value of the pairwise comparison. SAW method is used for the ranking process of 75 boarding houses alternative. The result showed that the weight of each criterion being 32% (price), 23% (facility), 40% (location), and 5% (room area), obtained A46 as the best boarding houses with a percentage gain value of 71%.

Sistem Pendukung Keputusan Rekomendasi Objek Wisata Di Kabupaten Berau Menggunakan Metode Fuzzy SAW

Berau Regency is an administrative area in East Kalimantan Province. Berau Regency has been named the area with the most and most beautiful tourist attractions in East Kalimantan, both in terms of culinary, culture, customs, and even natural tourism. Of course this becomes a deja vu if there is no special tourism information system to determine decisions for choosing tourist attractions based on tourist backgrounds.In science there is a system called Fuzzy Multi Attribute Dicision Making (FMADM) or commonly known as; with Simple Additive Weighting (SAW). This system can be an option to get a solution for the selection of tourist attractions in Berau Regency. With this support system, it is hoped that it can help the Berau Regency Government in managing tourism in Berau Regency.In the decision to choose tourist attractions, it is necessary to classify the criteria needed by tourists as well as similar tourism alternatives. With the Fuzzy SAW method, it is expected to be able to help tourists to get information and recommendations for the desired tourist attractions in Berau Regency.The system of this method is useful for processing data on tourist criteria, until finally producing a recommendation of the expected tourist attractions. It is also hoped that this Decision Support System can help the Berau Regency Government, especially the Berau Regency Tourism and Culture Office.