Analisis Faktor yang Mempengaruhi Lama Studi Mahasiswa dengan Metode SMARTER

One of the criteria in the assessment of college accreditation is student graduation. Factors that affect the students' study period need to be analyzed. In this study, the SMARTER method was used to find these factors. Data were obtained from a questionnaire with 133 respondents. Validity and reliability tests were conducted to determine the validity of the test equipment. The test was carried out with a significance test of 0.05 for the validity test and a reliability test of 0.811, which means the reliability is very high. The data is processed by the SMARTER method. The SMARTER method is a settlement method where the weights are calculated using the Rank Order Centroid (ROC) weighting calculation for each criterion and sub-criteria. Actual data shows that the lecturer factor is the main factor that affects the students' study period, followed by student factors, facilities and infrastructure factors, and external factors. From the results of the SMARTER method, it is found that the element that most influences student graduation is the lecturer factor, with a utility value of 15.918. The second factor is the student factor, which has a utility value of 8.297, followed by the facilities and infrastructure factor of 4.425, and external factors of 1.312. From the results of the SMARTER method and actual data, it is found that the lecturer's guidance is a factor that significantly influences the students' study period.Salah satu kriteria dalam penilaian akreditasi perguruan tinggi adalah kelulusan mahasiswa tepat waktu. Faktor yang mempengaruhi lama studi mahasiswa perlu dianalisis. Dalam penelitian ini metode SMARTER digunakan untuk menemukan faktor-faktor tersebut. Data diperoleh dari kuesioner dengan 133 responden. Uji validitas dan reliabilitas dilakukan untuk mengetahui kevalidan alat uji. Pengujian dilakukan dengan uji signifikansi 0,05 untuk uji validitas dan uji reliabilitas sebesar 0,811 yang berarti reliabilitasnya sangat tinggi. Data diolah dengan metode SMARTER. Metode SMARTER merupakan metode penyelesaian dimana bobot dihitung menggunakan perhitungan pembobotan Rank Order Centroid (ROC) pada setiap kriteria dan sub kriteria. Data real menunjukkan bahwa faktor dosen merupakan faktor utama yang mempengaruhi lama studi mahasiswa, disusul dengan faktor mahasiswa, faktor sarana dan prasarana, serta faktor dari luar. Dari hasil metode SMARTER diperoleh bahwa faktor yang paling mempengaruhi kelulusan mahasiswa adalah faktor dosen dengan nilai utility sebesar 15,918. Faktor kedua adalah faktor mahasiswa yang mempunyai nilai utility sebesar 8,297, disusul faktor sarana dan prasarana sebesar 4,425, dan faktor dari luar sebesar 1,312. Dari hasil perhitungan metode SMARTER dan data real didapat bahwa faktor bimbingan dosen merupakan faktor yang mempunyai pengaruh besar dalam perhitungan lama studi mahasiswa. &nbsp

Decision Support System for Single Tuition Scholarship Awardees in Higher Education Using Mamdani Fuzzy Inference

Universitas Madura implements the Single Tuition Fee (UKT) scholarship program in the Informatics department. The current UKT scholarship selection system uses a traditional model that is still not effective, causing obstacles such as inflexibility in registration time. The print-out documents are vulnerable to damage or loss and difficulty searching when it required. The criteria in the current system consisted of a minimum Grade Point Average (GPA) of 3, a letter of family condition, and also student status in semesters 3 to 7. The three criteria are not enough to determine a scholarship candidate. The recruitment process involves only the Head of the Study Program (Kaprodi). The Informatics study program still has many candidates applying for scholarships reaching around 280%. This research proposes a Decision Support System (DSS) using Fuzzy Mamdani with six criteria, including GPA, Achievement, Parents' Income, Parents' Dependents, Semester, and History of not receiving scholarships with the aim of overcoming these problems. The results show that the performance of the proposed SPK is very good, it is shown by the MAPE value of less than 10% and more efficient time than the current system. This system has also been in accordance with the required functions through the black test

FUCOM-MOORA and FUCOM-MOOSRA: new MCDM-based knowledge-driven procedures for mineral potential mapping in greenfields

AbstractIn this study, we present the application of two novel hybrid multiple-criteria decision-making (MCDM) techniques in the mineral potential mapping (MPM), namely FUCOM-MOORA and FUCOM-MOOSRA, as robust computational frameworks for MPM. These were applied to a set of exploration targeting criteria of skarn. The multi-objective optimization method on the basis of ratio analysis (MOORA) and the multi-objective optimization on the basis of simple ratio analysis (MOOSRA) approaches are used to prioritize and rank individual cells. What makes MOORA and MOOSRA more reliable compared to many other methods is the fact that the optimizations procedure is applied to calculate the prospectivity score of individual unit cells. This reduces the uncertainty stemming from erroneous mathematical calculations. The full consistency method (FUCOM), on the other hand, is useful for assigning weights to the spatial proxies. The FUCOM method, as a pairwise comparison method, reduces a large number of pairwise comparisons of similar and popular approaches such as analytic hierarchy process (AHP) with $$n\left( {n - 1} \right)/2$$ n n - 1 / 2 and the best–worst method (BWM) with $$2n - 3$$ 2 n - 3 number of pairwise comparisons with $$n - 1$$ n - 1 which leads to a less time-consuming and more consistent performance compared with AHP and BWM. These were applied to a set of exploration targeting criteria of skarn iron deposits from Central Iran. Two potential maps were retrieved from the procedures applied, the comparison of which using correct classification rates and field checks revealed the superiority of FUCOM-MOOSRA over the FUCOM-MOORA

Diminishing Choquet Hesitant 2-Tuple Linguistic Aggregation Operator for Multiple Attributes Group Decision Making

In this article, we develop a diminishing hesitant 2-tuple averaging operator (DH2TA) for hesitant 2-tuple linguistic arguments. DH2TA work in the way that it aggregate all hesitant 2-tuple linguistic elements and during the aggregation process it also controls the hesitation in translation of the resultant aggregated linguistic term. We develop a scalar product for hesitant 2-tuple linguistic elements and based on the scalar product a weighted diminishing hesitant 2-tuple averaging operator (DWH2TA) is introduced. Moreover, combining Choquet integral with hesitant 2-tuple linguistic information, the diminishing Chouqet hesitant 2-tuple average operator (DCH2TA) is defined. The proposed operators higher reflect the correlations among the elements. After investigating the properties of these operators, a multiple attribute decision making method based on DCH2TA operator is proposed. Finally, an example is given to illustrate the significance and usefulness of proposed method

Introducing a multi-criteria evaluation method using Pythagorean fuzzy sets: A case study focusing on resilient construction project selection

© 2020, Emerald Publishing Limited. Purpose: Project selection is a critical decision for any organization seeking to commission a large-scale construction project. Project selection is a complex multi-criteria decision-making problem with significant uncertainty and high risks. Fuzzy set theory has been used to address various aspects of project uncertainty, but with key practical limitations. This study aims to develop and apply a novel Pythagorean fuzzy sets (PFSs) approach that overcomes these key limitations. Design/methodology/approach: The study is particular to complex project selection in the context of increasing interest in resilience as a key project selection criterion. Project resilience is proposed and considered in the specific situation of a large-scale construction project selection case study. The case study develops and applies a PFS approach to manage project uncertainty. The case study is presented to demonstrate how PFS is applied to a practical problem of realistic complexity. Working through the case study highlights some of the key benefits of the PFS approach for practicing project managers and decision-makers in general. Findings: The PFSs approach proposed in this study is shown to be scalable, efficient, generalizable and practical. The results confirm that the inclusion of last aggregation and last defuzzification avoids the potentially critical information loss and relative lack of transparency. Most especially, the developed PFS is able to accommodate and manage domain expert expressions of uncertainty that are realistic and practical. Originality/value: The main novelty of this study is to address project resilience in the form of multi-criteria evaluation and decision-making under PFS uncertainty. The approach is defined mathematically and presented as a six-step approach to decision-making. The PFS approach is given to allow multiple domain experts to focus more clearly on accurate expressions of their agreement and disagreement. PFS is shown to be an important new direction in practical multi-criteria decision-making methods for the project management practitioner

MOORA under Pythagorean Fuzzy Set for Multiple Criteria Decision Making

The multiobjective optimization on the basis of ratio analysis (MOORA) method captures diverse features such as the criteria and alternatives of appraising a multiple criteria decision-making (MCDM) problem. At the same time, the multiple criteria problem includes a set of decision makers with diverse expertise and preferences. In fact, the literature lists numerous approaches to aid in this problematic task of choosing the best alternative. Nevertheless, in the MCDM field, there is a challenge regarding intangible information which is commonly involved in multiple criteria decision-making problem; hence, it is substantial in order to advance beyond the research related to this field. Thus, the objective of this paper is to present a fused method between multiobjective optimization on the basis of ratio analysis and Pythagorean fuzzy sets for the choice of an alternative. Besides, multiobjective optimization on the basis of ratio analysis is utilized to choose the best alternatives. Finally, two decision-making problems are applied to illustrate the feasibility and practicality of the proposed method

MOORA under Pythagorean Fuzzy Set for Multiple Criteria Decision Making

The multiobjective optimization on the basis of ratio analysis (MOORA) method captures diverse features such as the criteria and alternatives of appraising a multiple criteria decision-making (MCDM) problem. At the same time, the multiple criteria problem includes a set of decision makers with diverse expertise and preferences. In fact, the literature lists numerous approaches to aid in this problematic task of choosing the best alternative. Nevertheless, in the MCDM field, there is a challenge regarding intangible information which is commonly involved in multiple criteria decision-making problem; hence, it is substantial in order to advance beyond the research related to this field. Thus, the objective of this paper is to present a fused method between multiobjective optimization on the basis of ratio analysis and Pythagorean fuzzy sets for the choice of an alternative. Besides, multiobjective optimization on the basis of ratio analysis is utilized to choose the best alternatives. Finally, two decision-making problems are applied to illustrate the feasibility and practicality of the proposed metho

MOORA under Pythagorean Fuzzy Set for Multiple Criteria Decision Making

The multiobjective optimization on the basis of ratio analysis (MOORA) method captures diverse features such as the criteria and alternatives of appraising a multiple criteria decision-making (MCDM) problem. At the same time, the multiple criteria problem includes a set of decision makers with diverse expertise and preferences. In fact, the literature lists numerous approaches to aid in this problematic task of choosing the best alternative. Nevertheless, in the MCDM field, there is a challenge regarding intangible information which is commonly involved in multiple criteria decision-making problem; hence, it is substantial in order to advance beyond the research related to this field. Thus, the objective of this paper is to present a fused method between multiobjective optimization on the basis of ratio analysis and Pythagorean fuzzy sets for the choice of an alternative. Besides, multiobjective optimization on the basis of ratio analysis is utilized to choose the best alternatives. Finally, two decision-making problems are applied to illustrate the feasibility and practicality of the proposed method

Optimization for Decision Making II

In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner