A Combination Of Multi Factor Evaluation Process (MFEP) And The Distance To The Ideal Alternative (DIA) Methods For Majors Selection And Scholarship Recipients In SMAN 2 Tasikmalaya

Mufizar, Teuku; Mulyani, Evi Dewi Sri; Wiyono, Restu Adi; Arifiana, Wendi

doi:10.1109/citsm.2018.8674338

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…Anamisa et al [15] proposed to use SAW and TOPSIS methods for scholarship grantee selection. Mufizar et al [16] combined Multifactor Evaluation Process (MFEP) and Distance to the Ideal Alternative (DIA) to specify the majors and the scholarship recipient. Utami and Ruskan [17] developed a decision support system applying Multi-Objective Optimization method on the basis of Ratio Analysis (MOORA) to determine the eligible students among the participants for Yayasan Alumni scholarship.…”

Section: Introductionmentioning

confidence: 99%

Group decision making in best-worst method when the best and worst are not unique: case study of scholar selection

Adalı¹,

Çağlar²

2023

Pamukkale J Eng Sci

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Scholarships for the students are the financial supports provided by the government or institutions. There may be a great number of competing applicants with the knowledge, skills and abilities to successfully fulfill the scholarship needs. So, it is difficult to select the most suitable students among multiple applicants for these providers. In this study, scholarship students' selection is handled as a complex decision making problem, and this problem is solved by integration of two Multi Criteria Decision Making (MCDM) methods, Best-Worst Method (BWM) and COmbined COmpromise SOlution (CoCoSo). In order to demonstrate the applicability of these methods to the scholarship student selection problem, a real problem is solved. This problem is designed as a group decision making problem, and BWM, the improved Analytic Hierarchy Process method, is employed to derive the criteria weights. A solution to the problem where decision makers' best and worst criteria are not common and unique is suggested. On the other hand, CoCoSo method is used for the ranking purposes of the applicants. The novelty of this study is that scholarship selection problem is solved with BWM and CoCoSo methods for the first time. The integrated usage of BWM and CoCoSo methods is thought as suitable and effective methods to rank or select the best candidate or alternative among a number of candidates or alternatives because of satisfactory results. Öğrencilere yönelik burslar, devlet veya kurumlar tarafından sağlanan mali desteklerdir. Sağlanan bursun gerekliliklerini başarıyla yerine getirmek için gerekli olan bilgi, beceri ve yeteneklere sahip çok sayıda rakip öğrenci olabilir. Bu nedenle, burs sağlayıcılar için birden fazla başvuru arasından en uygun öğrencileri seçmek zordur. Bu çalışmada, burs seçimi karmaşık bir karar verme problemi olarak ele alınmış ve bu problem, Çok Kriterli Karar Verme (ÇKKV) yönteminlerinden olan En İyi-En Kötü Yöntemi (BWM) veBirleşik Uzlaşma Çözümü (CoCoSo yöntemi) birlikte kullanılarak çözülmüştür. Bu yöntemlerin burslu öğrenci seçme problemine uygulanabilirliği, gerçek bir problemin çözümü ile gösterilmiştir. Problem, grup karar verme problemi olarak tasarlanmıştır. Problemde kriterlerin ağırlıkları, Analitik Hiyerarşi Süreci yönteminin geliştirilmiş bir hali olan BWM ile hesaplanmıştır. Aynı zamanda, karar vericilerin en iyi ve en kötü kriterlerinin ortak ve tek olmadığı probleme bir çözüm önerilmiştir. Öte yandan, başvuran adayların sıralamaları için CoCoSo yöntemi kullanılmıştır. Bu çalışma ile bursiyer seçim problem, ilk kez BWM ve CoCoSo yöntemleri ile çözülmüştür. Çalışmadan elde edilen tatmin edici sonuçlar, bir dizi aday veya alternatif arasından en iyi adayı veya alternatifi sıralamak ya da seçmek için BWM ve CoCoSo yöntemlerinin birlikte kullanımının uygun ve etkili bir yaklaşım olacağını göstermektedir.

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Section: Introductionmentioning

confidence: 99%

Group decision making in best-worst method when the best and worst are not unique: case study of scholar selection

Adalı¹,

Çağlar²

2023

Pamukkale J Eng Sci

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Systematic Review of Recommendation Systems for Course Selection

Algarni

Sheldon

2023

MAKE

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Course recommender systems play an increasingly pivotal role in the educational landscape, driving personalization and informed decision-making for students. However, these systems face significant challenges, including managing a large and dynamic decision space and addressing the cold start problem for new students. This article endeavors to provide a comprehensive review and background to fully understand recent research on course recommender systems and their impact on learning. We present a detailed summary of empirical data supporting the use of these systems in educational strategic planning. We examined case studies conducted over the previous six years (2017–2022), with a focus on 35 key studies selected from 1938 academic papers found using the CADIMA tool. This systematic literature review (SLR) assesses various recommender system methodologies used to suggest course selection tracks, aiming to determine the most effective evidence-based approach.

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A Combination Of Multi Factor Evaluation Process (MFEP) And The Distance To The Ideal Alternative (DIA) Methods For Majors Selection And Scholarship Recipients In SMAN 2 Tasikmalaya

Cited by 2 publications

References 3 publications

Group decision making in best-worst method when the best and worst are not unique: case study of scholar selection

Group decision making in best-worst method when the best and worst are not unique: case study of scholar selection

Systematic Review of Recommendation Systems for Course Selection

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