PERANCANGAN LOGIKA FUZZY METODE SUGENO UNTUK MENENTUKAN DOSEN PEMBIMBING SKRIPSI BERDASARKAN SPESIFIKASI KEAHLIAN DOSEN

Authors

  • Rachel Yukabit Rosyidah Ilahi Universitas Muhammadiyah Prof. DR. HAMKA
  • Estu Sinduningrum Universitas Muhammadiyah Prof. DR. HAMKA
  • Rizky Zein Adam Universitas Muhammadiyah Prof. DR. HAMKA

DOI:

https://doi.org/10.22236/semnas/11787-797232

Keywords:

Decision Support System, Thesis Supervisor, Sugeno Method Fuzzy Logic

Abstract

Thesis preparation in Study Program of Informatics Engineering, Faculty of Engineering, University of Muhammadiyah Prof. DR. HAMKA is composed by students and guided by thesis supervisors. Process of determining the thesis supervisor is conducted by students, by asking information about the specifications of supervisors expertise to the alumnus. The process is not accurate because the determination of the supervisor is based on personal opinion and not based on the actual specifications of the supervisors's expertise. In this study, author used the Sugeno Fuzzy Logic Method to determine the thesis supervisor. The results obtained in this study are the Sugeno Fuzzy Logic Method can be applied to determine the thesis supervisor by using four input variables namely Software Engineering, Network and Security, and Multimedia. And using the output variables (alternative) on this system are Software Engineering, Network and Security, and Multimedia. Based on the questionnaire that has been done there are 14 supervisors data with an average value for z score of Software Engineering is 1.642 (Enough), the average value for z score of Network and Security is 1.50 (Enough), and the average value for z Multimedia score is 1.50 (Enough).

 

References

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Published

2020-09-01

How to Cite

Rachel Yukabit Rosyidah Ilahi, Estu Sinduningrum, & Rizky Zein Adam. (2020). PERANCANGAN LOGIKA FUZZY METODE SUGENO UNTUK MENENTUKAN DOSEN PEMBIMBING SKRIPSI BERDASARKAN SPESIFIKASI KEAHLIAN DOSEN. Prosiding Seminar Nasional Berseri, 1(1), 787–797. https://doi.org/10.22236/semnas/11787-797232