Optimizing education primary selection in universities: A fuzzy inference system with the mamdani method
DOI:
https://doi.org/10.30762/f_m.v7i1.2596Keywords:
Pemilihan jurusan, Sistem inferensi fuzzy, Metode Mamdani.Abstract
Pemilihan jurusan pendidikan yang tepat sangat penting untuk perencanaan karir, terutama bagi calon-calon guru. Keputusan pemilihan jurusan ini seringkali sulit diambil karena berbagai faktor yang kompleks. Penelitian ini bertujuan untuk mengembangkan Fuzzy Inference System (FIS) dengan metode Mamdani untuk membantu calon mahasiswa guru di universitas pendidikan dalam memilih jurusan yang sesuai. Pengembangan sistem FIS menggunakan metode RAD (Rapid Application Development). Kriteria yang digunakan untuk pengolahan data melalui FIS meliputi nilai CBT pada tahun 2023, kapasitas jurusan, dan minat mahasiswa pada tahun 2022 khusus dalam kelompok SAINTEK di Indonesia. Mamdani digunakan untuk memberikan rekomendasi berdasarkan data calon mahasiswa terkait kemampuan kognitif, literasi bahasa, dan penalaran matematis. Hasilnya menunjukkan bahwa sistem ini dapat digunakan dalam membimbing calon mahasiswa saintek dalam memilih jurusan yang sesuai dengan minat dan potensi mereka. Penelitian ini secara khusus memberikan manfaat bagi calon mahasiswa SAINTEK yang ingin melanjutkan pendidikan ke perguruan tinggi di universitas-universitas pendidikan di Indonesia, dengan memberikan panduan yang terstruktur dan sistematis untuk pemilihan jurusan.
Choosing the right education major is very important for career planning, especially for prospective teachers. Choosing a major is often challenging due to various complex factors. This research aims to develop a Fuzzy Inference System (FIS) using the Mamdani method to help prospective student teachers at educational universities choose an appropriate major. FIS system development uses the RAD (Rapid Application Development) method. The criteria used for data processing through FIS include CBT scores in 2023, department capacity, and student interest in 2022, specifically in the SAINTEK group in Indonesia. Mamdani provides recommendations based on prospective student data regarding cognitive abilities, language literacy, and mathematical reasoning. The results show that this system can guide prospective science and technology students in choosing majors that suit their interests and potential. This research provides explicit benefits for prospective SAINTEK students who wish to continue their education at tertiary institutions at educational universities in Indonesia by providing structured and systematic guidance for selecting majors.
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