Decision Support System Modeling with Fuzzy Combination Methods Retrograded and Simple Additive Weighting

Oct 13, 2025 by miodeya.com 11 views

Decision Support System Modeling with Fuzzy Combination Methods Retrograded and Simple Additive Weighting

Introduction

The Multi-attribute Decision Making Model (MADM) is a widely used method by decision makers in solving decision making problems. MADM methods are available to find the best solution, but research continues to develop better methods and provide more accurate results. This study combines two methods, namely Fuzzy against and Simple Additive Weighting (SAW), to achieve more optimal results. The focus of the research lies in the adjustment and integration of the two methods.

Background of the Study

Decision making is a complex process that involves considering various factors and alternatives. In order to make effective decisions, decision makers need to consider multiple criteria and evaluate different alternatives. The use of decision support systems (DSS) has become increasingly popular in recent years, as it can help decision makers in making more accurate and efficient decisions. A DSS is a computer-based system that uses data and models to support decision making.

The Fuzzy Method

The fuzzy method is used to weight each criterion. The criteria used in this study include age, education, honorarium SK, and length of work. Weighting criteria is divided into two types:

2 (Two) Fuzzy Set

SK honorarium and length of work have two fuzzy set, namely "old" and "new". This means that the decision maker can assign a weight to each criterion based on its level of importance, with "old" being more important than "new".
For example, if the decision maker assigns a weight of 0.8 to "old" and 0.2 to "new", it means that the criterion of honorarium SK is more important than the criterion of length of work.

3 (Three) Fuzzy Set

Age and education have three fuzzy set. For age, the fuzzy association used is "old", "parobaya", and "young". This means that the decision maker can assign a weight to each criterion based on its level of importance, with "old" being more important than "parobaya" and "young".
For example, if the decision maker assigns a weight of 0.6 to "old", 0.3 to "parobaya", and 0.1 to "young", it means that the criterion of age is more important than the criterion of education.
As for education, the fuzzy association used is "high", "medium", and "low". This means that the decision maker can assign a weight to each criterion based on its level of importance, with "high" being more important than "medium" and "low".
For example, if the decision maker assigns a weight of 0.7 to "high", 0.2 to "medium", and 0.1 to "low", it means that the criterion of education is more important than the criterion of age.

The Simple Additive Weighting (SAW) Method

The SAW method is a widely used method in decision making. It involves assigning a weight to each criterion based on its level of importance, and then calculating the overall score of each alternative based on the weights and the values of the criteria.

The Combination of Fuzzy Method and SAW

By combining the Fuzzy Method Raired and SAW, it is hoped that the resulting decision support system will be more accurate and efficient in providing recommendations for the best solutions. The use of this method can help decision makers in considering various factors and alternatives, so as to produce more appropriate and effective decisions.

Benefits of Using Decision Support Systems with Fuzzy Method and SAW

The use of decision support systems with the Fuzzy Method against and SAW has several benefits, including:

Helping Decision Makers in Prioritizing Criteria

Weighting with the Fuzzy Method Thanks allows decision makers to determine the weight of each criterion based on the level of importance.
This means that decision makers can assign a weight to each criterion based on its level of importance, and then use the SAW method to calculate the overall score of each alternative.

Increasing Objectivity in Decision Making

SAW method helps in carrying out systematic and objective calculations of each alternative based on the determined criteria weight.
This means that decision makers can use the SAW method to calculate the overall score of each alternative, without being influenced by personal biases or opinions.

Increasing Accuracy and Efficiency in the Decision Making Process

Decision support systems formed with a combination of these two methods can provide more accurate and efficient results, and facilitate decision makers in choosing the best solution.
This means that decision makers can use the decision support system to make more accurate and efficient decisions, without having to spend a lot of time and effort in evaluating different alternatives.

Conclusion

This research is expected to make a significant contribution in the development of decision support systems in various fields, such as business, government, and academics. The use of the fuzzy method is enduring and SAW in a decision support system can help decision makers in making more appropriate and effective decisions.

Future Research Directions

Future research can focus on developing more advanced decision support systems that can handle more complex decision making problems. Additionally, research can focus on evaluating the effectiveness of decision support systems in real-world settings.

References

[1] Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353.
[2] Saaty, T. L. (1980). The analytic hierarchy process. McGraw-Hill.
[3] Triantaphyllou, E. (2000). Multi-criteria decision making: A framework for decision analysis. Springer.

Note: The references provided are just examples and are not actual references used in the research.
Decision Support System Modeling with Fuzzy Combination Methods Retrograded and Simple Additive Weighting: Q&A

Introduction

In our previous article, we discussed the concept of decision support systems (DSS) and the use of fuzzy combination methods and simple additive weighting (SAW) in decision making. In this article, we will answer some of the frequently asked questions (FAQs) related to this topic.

Q: What is a decision support system (DSS)?

A: A DSS is a computer-based system that uses data and models to support decision making. It is designed to help decision makers in making more accurate and efficient decisions by providing them with relevant information and analysis.

Q: What is the fuzzy method?

A: The fuzzy method is a decision making method that uses fuzzy sets to represent the uncertainty and imprecision of the decision making process. It is used to weight each criterion based on its level of importance.

Q: What is the simple additive weighting (SAW) method?

A: The SAW method is a decision making method that involves assigning a weight to each criterion based on its level of importance, and then calculating the overall score of each alternative based on the weights and the values of the criteria.

Q: How does the combination of fuzzy method and SAW work?

A: The combination of fuzzy method and SAW involves using the fuzzy method to weight each criterion based on its level of importance, and then using the SAW method to calculate the overall score of each alternative based on the weights and the values of the criteria.

Q: What are the benefits of using decision support systems with fuzzy method and SAW?

A: The benefits of using decision support systems with fuzzy method and SAW include:

Helping decision makers in prioritizing criteria
Increasing objectivity in decision making
Increasing accuracy and efficiency in the decision making process

Q: What are the limitations of using decision support systems with fuzzy method and SAW?

A: The limitations of using decision support systems with fuzzy method and SAW include:

The need for accurate and reliable data
The need for a clear understanding of the decision making process
The potential for bias and subjectivity in the decision making process

Q: How can decision support systems with fuzzy method and SAW be implemented in real-world settings?

A: Decision support systems with fuzzy method and SAW can be implemented in real-world settings by:

Developing a clear understanding of the decision making process
Collecting and analyzing relevant data
Using the fuzzy method and SAW to weight and calculate the overall score of each alternative
Providing decision makers with relevant information and analysis

Q: What are the future research directions for decision support systems with fuzzy method and SAW?

A: Future research directions for decision support systems with fuzzy method and SAW include:

Developing more advanced decision support systems that can handle more complex decision making problems
Evaluating the effectiveness of decision support systems in real-world settings
Developing new methods and techniques for decision making

Conclusion

In this article, we have answered some of the frequently asked questions related to decision support systems with fuzzy method and SAW. We hope that this article has provided a clear understanding of the concept and benefits of using decision support systems with fuzzy method and SAW.

References

[1] Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353.
[2] Saaty, T. L. (1980). The analytic hierarchy process. McGraw-Hill.
[3] Triantaphyllou, E. (2000). Multi-criteria decision making: A framework for decision analysis. Springer.

Note: The references provided are just examples and are not actual references used in the research.