Prediction of the Number of New Student UnregistrationBased on Mamdani

Authors

  • Aries Setiawan Aries Universitas Dian Nuswantoro
  • Achmad Wahid Kurniawan Wahid Universitas Dian Nuswantoro
  • Retno Astuti Setijaningsih Retno Universitas Dian Nuswantoro
  • Ida Farida Ida Universitas Dian Nuswantoro
  • Budi Widjajanto Budi Universitas Dian Nuswantoro
  • Jaka Prasetya Jaka Universitas Dian Nuswantoro
  • Andi Hallang Lewa Andi Universitas Dian Nuswantoro
  • Maria Safitri Maria Universitas Dian Nuswantoro

DOI:

https://doi.org/10.59934/jaiea.v3i3.554

Keywords:

Prediction, Unregistration, Mamdani

Abstract

One of the annual routine events carried out by a private university is the admission of new students (PMB). From a number of prospective students who register, there are usually a number of students who unregister or cancel registration. Several factors for unregistration of new students are (1) acceptance of state universities, the interest of prospective students to study at state universities is still high, (2) there are doubts about the study program chosen by students, (3) Inadequate ability to pay. Some of the above factors must be taken seriously so that there is no decrease in the number of registrations. The mamdani method is one of the calculation methods that can be used to predict the number of new student registrations, with 4 main stages, namely creating fuzzy sets, implementing implication functions, applying rules and regulations, and affirming. Prediction of unregistration using the Mamdani method will make it easier for academics, in this case the academic bureau, to find solutions to reduce the number of unregistration itself.

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References

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Published

2024-06-15

How to Cite

Aries, A. S., Wahid, A. W. K., Retno, R. A. S., Ida, I. F., Budi, B. W., Jaka, J. P., Andi, A. H. L., & Maria, M. S. (2024). Prediction of the Number of New Student UnregistrationBased on Mamdani. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 3(3), 882–886. https://doi.org/10.59934/jaiea.v3i3.554

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