Integration of FAHP and COPRAS Method for New Student Admission Decision Making

Kustiyahningsih, Yeni; Husni,; Aini, Ismy Qorry

doi:10.1109/icvee50212.2020.9243260

Cited by 18 publications

(10 citation statements)

References 7 publications

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“…The advantage of FAHP is the use of index consistency to control the error rate of the decision [5] [6]. The TOPSIS method is capable of making multi-criteria decisions based on the concept that the chosen alternative will be ranked for the MSME industry mapping process [7][8] [9].…”

Section: Intoductionmentioning

confidence: 99%

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Hybrid FAHP and TOPSIS to determine recommendation for improving SMEs facing Covid-19 pandemic

Kustiyahningsih

Rahmanita

Anamisa

2022

J. Phys.: Conf. Ser.

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The Covid-19 pandemic has had an impact on domestic economy, such as a decrease in people’s consumption and purchasing power, a decline in company performance, as well as SMEs. This situation, SMEs sector controls 99.99% of all existing businesses, employs 97.16% of private sector workforce, and contributes 57.5% to Indonesia’s gross product. Various government program efforts in helping Batik SMEs players face Covid-19 pandemic so that they are right on target. The large number of SMEs in Bangkalan is around 166,768, causing department to find it difficult to determine recommendations for improvement for each MSME. Based on these problems, a cooperative model for the SMEs industry is needed so that official work program runs smoothly on target. The method used is FAHP and TOPSIS integration method, FAHP method is used to determine weighting and TOPSIS method is used for ranking and recommendations for improvement. The advantage of FAHP is consistency index to control error rate of decision. TOPSIS method is capable of making multi-criteria decisions based on alternative SMEs industry mapping process. The purpose is make a recommendation model for improvement using hybrid method of FAHP and TOPSIS with balanced scorecard indicators for learning and growth perspective. The research contribution is to make decisions based on group recommendations and consistency ratio (CR) is less than 0.1. The findings research, that the influential indicators are batik business ownership and variations of batik motifs. The recommendations for improvement, the average MSME still does not have branding.

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Section: Intoductionmentioning

confidence: 99%

“…In this study, triangular fuzzy number TFN scale was used. The process of transforming fuzzy logic to AHP in this study was carried out by following method developed by Gungor [5]. Triangular Fuzzy Number (TFN) operation, defined three real numbers as low, middle, upper.…”

Section: 1fuzzy Analytic Hierarchy Process (Fahp)mentioning

confidence: 99%

Hybrid FAHP and TOPSIS to determine recommendation for improving SMEs facing Covid-19 pandemic

Kustiyahningsih

Rahmanita

Anamisa

2022

J. Phys.: Conf. Ser.

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“…A particular advantage of COPRAS is the accuracy of the provided rankings of alternatives due to the separate evaluation of profit and cost criteria [ 24 ]. Thus, the final COPRAS score is derived from the positive ideal solution and the negative ideal solution, and the best alternative should have the highest value for the positive ideal solution and the lowest value for the negative ideal solution [ 25 , 26 ].…”

Section: Literature Reviewmentioning

confidence: 99%

New Pythagorean Entropy Measure with Application in Multi-Criteria Decision Analysis

Gandotra

Kizielewicz

Anand

et al. 2021

Entropy

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The purpose of this paper is to propose a new Pythagorean fuzzy entropy for Pythagorean fuzzy sets, which is a continuation of the Pythagorean fuzzy entropy of intuitionistic sets. The Pythagorean fuzzy set continues the intuitionistic fuzzy set with the additional advantage that it is well equipped to overcome its imperfections. Its entropy determines the quantity of information in the Pythagorean fuzzy set. Thus, the proposed entropy provides a new flexible tool that is particularly useful in complex multi-criteria problems where uncertain data and inaccurate information are considered. The performance of the introduced method is illustrated in a real-life case study, including a multi-criteria company selection problem. In this example, we provide a numerical illustration to distinguish the entropy measure proposed from some existing entropies used for Pythagorean fuzzy sets and intuitionistic fuzzy sets. Statistical illustrations show that the proposed entropy measures are reliable for demonstrating the degree of fuzziness of both Pythagorean fuzzy set (PFS) and intuitionistic fuzzy sets (IFS). In addition, a multi-criteria decision-making method complex proportional assessment (COPRAS) was also proposed with weights calculated based on the proposed new entropy measure. Finally, to validate the reliability of the results obtained using the proposed entropy, a comparative analysis was performed with a set of carefully selected reference methods containing other generally used entropy measurement methods. The illustrated numerical example proves that the calculation results of the proposed new method are similar to those of several other up-to-date methods.

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“…According to Zavadskas, et al in [4] the COPRAS method is a Multi-Criteria Decision Making (MCDM) method that is used to evaluate alternatives where the ratio based on two measures, the sum of the performance of the favorable criteria and the sum of the unfavorable criteria. The COPRAS method is used for the assessment of ICT development in G7 countries [5], vulnerability mapping of subwatershed erosion [6], green logistics and green supply chain management [7], Decision Making for New Student Admissions at MTsN Bangkalan [8], motorcycle selection Electricity [9], multi-criteria decision making for hybrid wind power plants [10], Supplier Selection at ABC Mining Companies in Indonesia [11], and Determination of Potential Zones for the Pasir Batu Mine [12].…”

Section: Introductionmentioning

confidence: 99%

BPNT Program Beneficiaries Based on Copras and Codas

Midyanti

Bahri

Midyanti

2023

jitk

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Determination of recipients of the Non-Cash Food Assistance Program (BPNT) is a matter that causes problems if it is not carried out in an objective, transparent, and targeted manner. Previous studies on BPNT were based on a specific method, which did not use a negative trend in the criteria. In this study, the Multi-Criteria Decision Making (MCDM) approach was used to recommend the recipients of the BPNT program. Two MCDM models were used in this study, COPRAS and CODAS methods. Spearman's rank correlation method was used to determine the best model and measure the degree of similarity between the results obtained from different models. Spearman rank correlation shows that COPRAS and CODAS have a strong positive correlation of 0.89899. The combined COPRAS-CODAS ranking model produces a very strong positive correlation value of 0.9744 for both methods, so the model is used for recommendations for BPNT program recipients.

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Integration of FAHP and COPRAS Method for New Student Admission Decision Making

Cited by 18 publications

References 7 publications

Hybrid FAHP and TOPSIS to determine recommendation for improving SMEs facing Covid-19 pandemic

Hybrid FAHP and TOPSIS to determine recommendation for improving SMEs facing Covid-19 pandemic

New Pythagorean Entropy Measure with Application in Multi-Criteria Decision Analysis

BPNT Program Beneficiaries Based on Copras and Codas

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