The Selection of KORPRI Scholarship Recipients Using Sugeno's Fuzzy Logic

Authors

  • Dona Kurnia Universitas Prima Nusantara Bukittinggi, Indonesia
  • Efmi Maiyana AMIK "Bukittinggi", Indonesia

DOI:

https://doi.org/10.30983/knowbase.v3i2.6585

Keywords:

Scholarship, Selection, Fuzzy Sugeno

Abstract

Student Scholarship Allowance Selection is a routine practice carried out by the Bukittinggi City KORPRI (Civil Servants Corps), which is given to the sons and daughters of civil servants in the Bukittinggi City area who are currently pursuing higher education. Determining scholarship recipients always goes through a strict selection process due to the large number of applicants each year. The selection of scholarship recipients is based on specific criteria and requirements set by KORPRI Bukittinggi City. The criteria/requirements for awarding scholarships are based on three factors: Grade Point Average (GPA), parental income/salary, and number of dependents. In this research, the author applies Sugeno's fuzzy logic in determining scholarship allocation because Sugeno's fuzzy logic can select candidates validly, transparently, and fairly, thus guaranteeing that the selected candidates truly deserve to receive a scholarship. To conduct research effectively, the author designed a research framework that helps the scholarship allocation process using Sugeno fuzzy logic, implemented through the Visual Basic 2010 and MySQL programming languages. Research findings show that the Sugeno fuzzy method can provide accurate and objective recommendations in the scholarship recipient selection process using relevant variables and predetermined rules. This recommendation system can produce fair and transparent decisions. This research aims to contribute to the development of a more effective and efficient scholarship recipient selection system.

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Published

2023-12-31

How to Cite

Kurnia, D., & Maiyana, E. (2023). The Selection of KORPRI Scholarship Recipients Using Sugeno’s Fuzzy Logic. Knowbase : International Journal of Knowledge in Database, 3(2), 116–130. https://doi.org/10.30983/knowbase.v3i2.6585

Issue

Vol. 3 No. 2 (2023): December 2023

Section

Articles

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