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All Journal APTEKINDO Sainstek Jurnal Teknik Jurnal Penelitian Pertanian Terapan MUDRA Jurnal Seni Budaya Jambura Journal of Informatics Vocatech : Vocational Education and Technology Journal Jurnal Pendidikan Teknologi Informasi dan Vokasional IJITEE (International Journal of Information Technology and Electrical Engineering) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Sibermas (Sinergi Pemberdayaan Masyarakat) Jurnal Dedikasi Journal Automation Computer Information System (JACIS) Inverted Research Review: Jurnal Ilmiah Multidisiplin Jurnal Rekayasa elektrika Jurnal Vokasi Sains dan Teknologi Empiris Jurnal Pengabdian Pada Masyarakat (EJPPM) Diffusion: Journal of Systems and Information Technology Jurnal Vokasi Keteknikan
Mukhlisulfatih Latief
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Perbandingan Algoritma Supervised Learning dalam Memprediksi Jalur Seleksi Masuk Mahasiswa di Universitas Negeri Gorontalo Manda Rohandi; Mukhlisulfatih Latief; Mohamad Ilyas Abas
Jurnal Teknik Vol 24 No 1 (2026): Jurnal Teknik
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37031/jt.v24i1.750

Abstract

The choice of university admission pathway (SNBT, SNBP, or independent selection/Mandiri) is closely related to students' demographic and administrative characteristics, and understanding this pattern benefits higher education institutions in designing more targeted recruitment strategies. This study aims to compare the performance of four supervised learning algorithms Decision Tree, Random Forest, Naïve Bayes, and k-Nearest Neighbor (k-NN) in predicting the admission pathway of Informatics Engineering students at Universitas Negeri Gorontalo (UNG). Data were obtained from UNG's Integrated Academic Information System (SIAT) for 1,237 students from the Information Technology Education and Information Systems study programs (2018–2024 cohorts), which after data cleaning resulted in 1,232 samples across three pathway classes (SNBT = 682, SNBP = 417, Mandiri = 133). Feature selection using information gain identified five informative features: selection type (national/local), age, cohort year, initial registration semester, and gender. Evaluation was conducted through three scenarios: 80:20 hold-out with Synthetic Minority Oversampling Technique (SMOTE), and 10-fold stratified cross-validation, followed by a Friedman significance test. The 10-fold cross-validation results show mean accuracies of 64.61% for Random Forest, 64.37% for Decision Tree, 63.47% for Naïve Bayes, and 61.03% for k-NN. The Friedman test indicated no statistically significant difference in performance among the four algorithms (χ² = 4.39; p = 0.222). The confusion matrix revealed that all algorithms perfectly classified the Mandiri class due to a definitional dependency with the selection-type feature, while most misclassifications occurred between the SNBP and SNBT classes. Applying SMOTE consistently improved minority-class (SNBP) recall across all four algorithms, but its effect on macro F1-score and overall accuracy varied by algorithm and was not uniformly positive. This study recommends incorporating academic behavioral features to improve the model's discriminative ability between national selection pathways.
Co-Authors Abdul Aziz Bouty Abdul Muis Mappalotteng Abdul Muis Mappalotteng Agus Lahinta Agustian Asril Ahmad Azhar Kadim Ahmad Musa Alfian Zakaria Amanda Nurhaliza E. Budiman Amirudin Y. Dako Arip Mulyanto Astuti, Wahyu Bait Syaiful Rijal Budiyanto Ahaliki Dadi, Heru Hartato Dai, Roviana H. Dian Novian Dwi Novita Hasan Dwinanto, Arif Edi Setiawan Eka V. Dangkua Eka Vickraien Dangkua, Eka Vickraien Fadila N Sagi Friscilla Anggriani Husain Ghama Yaskara Luli H, Haeriani H. Dai, Roviana Haeriani Haeriani Haikal Z.W Isa Hasda Damopolii Hayatiningsih Gubali Hermila A Huraju, Risnawati M Huraju, Risnawati M. Husen, Parif Priano Palewangi Huzaima Mas'ud Huzaima Mas’ud I Made Yasa Ibrahim Harun Ihsanulfu’ad Suwandi Ihza Zubair Abdullah Indhitya R Padiku isra, mohamad nur Jazid Muslich Podungge Jemmy A Pakaya Jumiati Ilham K Wakiden, Yurahma Desqia Kamba, Ainun Labuna, Ardiyanita R Lalu, Widi Natasya Lanto Miriatin Amali Lanto Ningrayati Amali Latena, Greys Lillyan Hadjaratie Magfira Hasan Mahmud, Fikran Manda Rohandi Mangundap, Kirana Zahra M. Mania, Nurpita Sukmaya Mas'ud, Huzaima Mas'ud, Huzaimah Maudy Putery Hasan Moh Ramdhan Arif Kaluku Moh. Hidayat Koniyo mohamad fahri ismail Mohamad Ikbal Bahua Mohamad Ilyas Abas Mohamad Lihawa, Mohamad mohammad syafri tuloli Muchlis Polin Murni Setyani Gusti Muthia Muthia Muthia, Muthia Nevita Larasati Mokoginta Nikmah Musa Nikmasari Pakaya Nova Damayanti Girsang Novri Youla Kandowangko Nur Afifah Olii, Salahuddin Ongku, Sriwahyuni A. Pakaya, Jemmy A Pakaya, Jemmy A. Pakaya, Nikmasari Paputungan, Salsabila Nakia Pobela, Elvira Ningsih Pomalo, Nurdian Potohu, Rahmatika Putri, Muthiah Rahman Takdir Rampi Yusuf Rochmat Mohammad Thohir Yassin Roviana Dai S Supriyadi Sagga, Hairun Nissa Salahudin Olii Salmawaty Tansa Sardi Salim Septiyanti Puti Sitti Suhada Sri Ayu Ashari Sri Rahmawati Adam Suleman, Adriansyah R Sulfina M. Razak Sunardi Sunardi Suwandi, Ihsanulfu'ad Suwandi, Ihsanulfu’ad Syahrul Syahrul Syahrul Syahrul Tajuddin Abdillah Tuloli, Moh.Syafri Wulan Natasya Umar Yassin, Rochmad M Thohir Yassin, Rochmad Mohammad Thohir Zulzain Ilahude