Local double quantitative fuzzy rough sets over two universes

Lin, Guoping; Xie, Linlin; Li, Jinjin; Chen, Jinkun; Kou, Yi

doi:10.1016/j.asoc.2023.110556

Cited by 7 publications

(1 citation statement)

References 38 publications

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“…The Rough Set Method is a method of mathematical tools for dealing with clarity and uncertainty that is introduced to process uncertainty and imprecise information (Yu et al, 2019;Lin et al, 2023). This method can produce new information in the form of rule patterns that are used as a reference for selection assistance, so it is very helpful for the selection team in making decisions that are right on target (Rashid et al, 2019;Abubakar et al, 2019).…”

Section: Rough Setmentioning

confidence: 99%

Development of the Rough Set Method to Determine Lecturer Scholarship Opportunities

Surmayanti,

Defit

2024

jppipa, pendidikan ipa, fisika, biologi, kimia

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Currently, all groups can experience the development of artificial intelligence, this happens because artificial intelligence has experienced very significant changes. Artificial Intelligence (AI) consists of several branches, one of which is machine learning. Machine Learning (ML) technology is a branch of AI that is very interesting because it is a machine that can learn like humans. The method used here is the rough set method. In this research, a case will be raised to determine scholarship opportunities for lecturers based on predetermined criteria. To solve the problem above, machine learning was used using the Rough Set method, using Rosetta software. By the regulations determined by the scholarship provider, in this case, the institution concerned where the lecturer is registered as teaching staff to obtain a scholarship, criteria are needed to determine who will be selected to receive the scholarship. The distribution of scholarships is carried out to improve lecturer performance, as an achievement as well as an appreciation for the lecturer concerned for his long service to the institution.

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Section: Rough Setmentioning

confidence: 99%