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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References
Akhyar, M. K. (2019). “Hasil UN buruk HOTS yang salah, Benarkah?”: Analisis HOTS pada Soal UNBK terhadap hasil UN Matematika SMA di Indonesia. Factor M, 1(2). https://doi.org/10.30762/f_m.v1i2.1518
Aryani, F., & Umar, N. F. (2020). Factors affecting z generation on selecting majors in the UniversityUniversity: An Indonesian case. Journal of Social Studies Education Research, 11(3), 109–133.
Azeez, N. A., Towolawi, T., Van der Vyver, C., Misra, S., Adewumi, A., Damaševičius, R., & Ahuja, R. (2019). A fuzzy expert system for diagnosing and analyzing human diseases. Advances in Intelligent Systems and Computing, 939, 474–484. https://doi.org/10.1007/978-3-030-16681-6_47
Bisht, D. C. S., Srivastava, P. K., & Ram, M. (2018). Role of Fuzzy Logic in Flexible Manufacturing System. In M. Ram & J. P. Davim (Eds.), Management and Industrial Engineering (pp. 233–243). Springer International Publishing. https://doi.org/10.1007/978-3-319-65497-3
Budi, S., & Rezi, W. (2021). The fuzzy clusterwise generalized structured component method is used to evaluate the implementation of national education standards in Indonesia. Management Science Letters, 11, 1379–1384. https://doi.org/10.5267/j.msl.2020.11.002
Febrianti, I., Anam, M. K., Rahmiati, R., & Tashid, T. (2020). Tren milenial memilih jurusan di perguruan tinggi menggunakan metode social network analysis. Techno.Com, 19(3), 216–226. https://doi.org/10.33633/tc.v19i3.3483
Gabriel, E. C. G., Manuel, A. O. A., & Saba, M. (2023). Fuzzy system for perception level estimation in e-commerce websites. TEM Journal, 12(4), 1939–1947. https://doi.org/10.18421/TEM124-03
Keller-Schneider, M., Zhong, H. F., & Yeung, A. S. (2020). Competence and challenge in professional development: Teacher perceptions at different stages of career. Journal EduTeach, 46(1), 1–19. https://doi.org/10.1080/02607476.2019.1708626
Laili, U. F. (2020). Prediksi Hasil Ujian Nasional Siswa Menengah Atas: Pendekatan Data Mining. Factor M, 3(1). https://doi.org/10.30762/f_m.v3i1.2450
Lent, R. W., & Brown, S. D. (2020). Career decision making, fast and slow: Toward an integrative model of intervention for sustainable career choice. Journal of Vocational Behavior, pp. 120, 1–15. https://doi.org/10.1016/j.jvb.2020.103448
Maharani, F. P., Karmiyati, D., & Widyasari, D. C. (2021). Kecemasan masa depan dan sikap mahasiswa terhadap jurusan akademik. Cognicia, 9(1), 11–16. https://doi.org/10.22219/cognicia.v9i1.15292
Mulyani, E. D. S., Hidayat, C. R., & Ulfa, T. C. (2018). Sistem pakar untuk menentukan jurusan kuliah berdasarkan minat dan bakat siswa SMA dengan menggunakan metode forward chaining. CSRID (Computer Science Research and Its Development) Journal, 10(2), 80–92. https://doi.org/10.22303/csrid.10.2.2018.80-92
Muriithi, S., Swanson, Z., & Genchev, S. (2021). The effects of expectancy and heuristics on the major selection process. Journal of Higher Education Theory and Practice, 21(4), 223–235. https://doi.org/10.33423/JHETP.V21I4.4220
Mwantimwa, K. (2021). What motivates students’ decisions on programmes to pursue at university level: The role of information and knowledge. Higher Education, 82(2), 349–367. https://doi.org/10.1007/s10734-021-00698-4
Pourjavad, E., & Mayorga, R. V. (2017). A comparative study and measuring performance of manufacturing systems with Mamdani fuzzy inference system. Journal of Intelligent Manufacturing, 30, 1085–1097. https://doi.org/10.1007/s10845-017-1307-5
Prayitno, S. H. (2023). Sikap pilihan jurusan akademik dan kecemasan masa depan terhadap motivasi belajar mahasiswa. Jurnal Ilmiah Kesehatan Rustida, 10(02), 122–133. https://doi.org/10.55500/jikr.v10i2.199
Resti, N. C., & Resti, N. C. (2019). Penerapan Metode Fuzzy Tsukamoto untuk Menentukan Jumlah Produksi Obat Ikan di UD. Indo Multi Fish Tulungagung. Factor M, 1(2). https://doi.org/10.30762/f_m.v1i2.1426
Rifanti, U. M., Pujiharsono, H., & Pradana, Z. H. (2023). Implementasi logika fuzzy pada penilaian kegiatan merdeka belajar kampus merdeka (MBKM). JST (Jurnal Sains Dan Teknologi), 12(1), 250–260. https://doi.org/10.23887/jstundiksha.v12i1.50057
Rizdania, R. (2021). Sistem pendukung keputusan (SPK) pemilihan jurusan perguruan tinggi menggunakan algoritma fuzzy mamdani. Jurnal Tecnoscienza, 6(1), 30–42. https://doi.org/10.51158/tecnoscienza.v6i1.529
Seising, R. (2020). Lotfi Zadeh: fuzzy sets and systems. In R. Moreno-Díaz, F. Pichler, & A. Quesada-Arencibia (Eds.), Computer Aided Systems Theory–EUROCAST 2019: 17th International Conference (pp. 101–108). Springer International Publishing. https://doi.org/10.1007/978-3-030-45093-9
Sridharan, M. (2021). The application of the Mamdani fuzzy inference system in predicting the thermal performance of solar distillation is still ongoing. Journal of Ambient Intelligence and Humanized Computing, 12(11), 10305–10319. https://doi.org/10.1007/s12652-020-02810-5
Sukirno, Setyoko, & Indriaty. (2020). Pengembangan bahan ajar biologi SMA kontekstual berbasis potensi lokal hutan mangrove. BIOEDUSAINS: Jurnal Pendidikan Biologi Dan Sains Volume, 3(2), 208–216. https://doi.org/10.31539/bioedusains.v3i2.1780
Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008). What drives successful e-learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers and Education, 50(4), 1183–1202. https://doi.org/10.1016/j.compedu.2006.11.007
Syaharuddin, Pramita, D., Nusantara, T., & Subanji. (2019). Accuracy analysis of ANN back propagation, neuro-fuzzy, and radial basis function: A case of HDI forecasting. International Journal of Engineering and Advanced Technology (IJEAT), 9(1), 1299–1304. https://doi.org/10.35940/ijeat.A9640.109119
Tundo, T., & Mahardika, F. (2023). Fuzzy inference system tsukamoto–decision tree C 4.5 in predicting the amount of roof tile production in Kebumen. JTAM (Jurnal Teori Dan Aplikasi Matematika), 7(2), 533–544. https://doi.org/10.31764/jtam.v7i2.13034
Turzhanska, O., Galetskyi, S., & Topishko, N. (2022). Model of the decision support system for career guidance of young people based on the apparatus of fuzzy logic. Youth Voice Journal, 3(3), 54–71.
Yuliana, D. T., Fathoni, M. I. A., & Kurniawati, N. (2022). Penentuan Penerima Kartu Indonesia Pintar KIP Kuliah Dengan Menggunakan Metode K-Means Clustering. Journal Focus Action of Research Mathematic (Factor M), 5(1). https://doi.org/10.30762/f_m.v5i1.570
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
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