41 research outputs found
Detecting beef and pork adulteration using principal component analysis
Principal Component Analysis (PCA) is proposed for the automatic detection of beef and pork adulteration images in this paper. The method is used for the feature extraction phase. Two database resources are used in the research. They are Kaggle database to obtain the beef and pork images and previous research by L. Handayani et al. to get the adulteration images. The images are divided into two processes that are training and testing. For the training process, this experiment was conducted on 100 images of beef, 100 images of pork, and 50 images of adulteration. Whereas for testing, this study used 25 images for each category. The proposed research requires three phases to obtain the detection result, i.e., the first phase is resizing images to 300x300 pixels for both the training and testing dataset. The second is implementing the proposed method to obtain the featured images. The last is the detection process of testing images using Mean Squared Error (MSE). The results of this research show that the PCA method is very effective for detecting beef and pork adulteration, reaching average accuracy values up to 96%
Nash equilibrium selection using a hybrid two-player static game with trade-off ranking method
In the context of the game theory solution idea, the study seeks to suggest the ranking of an optimal solution when there are several Nash equilibria. The integration of the MCDM approach and game theory is a common strategy for addressing real-world challenges. This study introduces a novel hybrid method, combining a non-cooperative static game from game theory with the trade-off ranking (TOR) method from MCDM. The proposed hybrid method is used to rank multiple Nash equilibria concerning some criteria. The methodology for both static game and TOR method are explained in the paper. The game theory model used is a two-player non-constant-sum static game. The proposed methodology is tested using international cooperation in Iran. The result suggests the ranking of the combined strategies using the proposed method
A comprehensive review of hybrid game theory techniques and multi-criteria decision-making methods
More studies trend to hybrid the game theory technique with the multi-criteria decision-making (MCDM) method to aid real-life problems. This paper provides a comprehensive review of the hybrid game theory technique and MCDM method. The fundamentals of game theory concepts and models are explained to make game theory principles clear to the readers. Moreover, the definitions and models are elaborated and classified to the static game, dynamic game, cooperative game and evolutionary game. Therefore, the hybrid game theory technique and MCDM method are reviewed and numerous applications studied from the past works of literature are highlighted. The result of the previous studies shows that the fundamental elements for both frameworks were studied in various ways with most of the past studies tend to integrate the static game with AHP and TOPSIS methods. Also, the integration of game theory techniques and MCDM methods was studied in various applications such as politics, economy, supply chain, engineering, water management problem, allocation problem and telecommunication network selection. The main contribution of the recent studies of employment between game theory technique and MCDM method are analyzed and discussed in detail which includes static and dynamic games in the non-cooperative game, cooperative game, both non-cooperative and cooperative games and evolutionary gam
A review of game theory and multi-criteria decision-making methods with 10 application to the oil production and price
The oil production and price issues have been discovered a long time ago, and always be a continuous problem to the globe especially during the current global threats of the coronavirus pandemic. This paper provides a literature review that involves game theory and multi-criteria decision-making (MCDM) methods with its applications to oil production and price problems. This paper identifies and analyses the use of the game theory and MCDM methods on oil production and price to compare the situation studied, to determine the model that has been used, the trend of past literature and also the details of the basic elements for the game theory framework. Therefore, the oil production and price problem using the game theory and MCDM methods are reviewed and numerous applications studied from the past works of literature are highlighted. The trend of oil production and price which used the game theory and MCDM methods based on the year 2001 till 2021 is still lacking sources from the Web of Science and Scopus databases. The main contribution of the recent study is the employment of the game theory and MCDM methods to the oil production and price problem
A shapley trade-off ranking method for multi-criteria decision-making with defuzzification characteristic function
More studies tend to hybrid the game theory technique with the MCDM method to cater to real-situation problems. This paper provides a novel hybrid Shapley value solution concept in the cooperative game with the trade-off ranking method in MCDM. The fundamental methodology of the Shapley value solution concept and trade-off ranking method are explained to make the methodology clear to the readers. A Shapley trade-off ranking (S-TOR) method has been proposed to obtain the best solution to the fuzzy conflicting MCDM in the personnel selection problem. Thus, the triangular fuzzy number is used to represent the DMs evaluation. Then, the fuzzy number be transformed into crisp values using the defuzzification process. The future suggestions are the fuzzy system may be changed to real data for more practical problems, attempt to incorporate a comprehensive method to increase sharing-profit and decrease sharing-loss in the economy or financial problems, and other types of fuzzy numbers may be used to represent an evaluation of the DMs
Determination STEM (mathematics) blended learning criteria via fuzzy AHP method
Due to the decreasing number of students’ interest in the Science, Technology, Engineering, and Mathematics
(STEM) field in Malaysia, educators need to instill students of STEM education in teaching and learning to face the IR 4.0
revolution. However, due to the COVID-19 pandemic and the recent curriculum change may challenge educators in
implementing STEM (Mathematics). Thus, blended learning is relevant in maintaining the maximum students' higher
thinking skills by integrating the STEM-Mathematics criteria in teaching and learning. Proper selection of STEM
(Mathematics) criteria can ensure high-impact achievement and the fulfilment of the Ministry of Education's aspirations. This
study proposes the STEM criteria needed in Mathematics subjects via the fuzzy Analytic Hierarchy Process (AHP) method.
This study aims to evaluate the STEM (Mathematics) criteria weight for identifying the appropriate STEM (Mathematics)
criteria needed in blended learning. First, the potential of STEM (Mathematics) criteria and the standard curriculum for
secondary school were identified by the literature review and evaluated by distributing questionnaires to 31 expert
mathematics educators. Then, fuzzy AHP is utilised to illustrate the proposed approach. The results depicted the ranking
order of the STEM (Mathematics) criteria using linguistic scales
A view of MCDM application in education
The effectiveness of the teaching and learning process by educators plays a significant role for countries to prepare students' potential in the forthcoming new industrial revolution (IR). However, the current COVID-19 pandemic and dynamic changes in the curriculum have created a significant shift of emphasis to educators. Hence, the teaching and learning process problems nowadays, including selecting appropriate effectiveness learning, have become a tough decision for educators. It can be solved using multi-criteria decision-making (MCDM) methods. The MCDM technique is widely applied and accepted in various fields but less in the teaching and learning context. This paper reviews and analyses the type of decision problems that were paid most attention to MCDM approaches, the adopted fuzzy set theory as well as inadequacies of those approaches. The purpose is to analyse and identify the literature review related to the applications of MCDM in education so new attributes and appropriate MCDM models for decision making can be suggested. The process involved comparing and analysing the MCDM application and fuzzy set theory in education by reviewing related articles in international scientific journals and well-known international conferences. Some improvements and more future works are recommended based on the inadequacies. The reviewed result may create an interest to the Ministry of Education (MoE) as it proposes teaching and learning process improvement, which will help to achieve greater satisfaction among educators and students