Algoritma Hybrid K-Means dan Jaringan Saraf Tiruan untuk Meningkatkan Prestasi Akademik Siswa
Suriani Suriani(1); Muhammad Faisal(2*); Darniati Darniati(3); Emil Agusalim H. T(4); Muhammad Syafaat S. Kuba(5); Swa Lee Lee(6); Nurdiansyah Nurdiansyah(7);
(1) Informatika, Universitas Muhammadiyah Makassar, Makassar, Indonesia
(2) Informatika, Universitas Muhammadiyah Makassar, Makassar, Indonesia
(3) Informatika, Universitas Muhammadiyah Makassar, Makassar, Indonesia
(4) Informatika, Universitas Muhammadiyah Makassar, Makassar, Indonesia
(5) Teknik Pengairan, Universitas Muhammadiyah Makassar, Makassar, Indonesia
(6) School Science and Technology, Asia E University, Selangor, Malaysia
(7) Bisnis Digital, Universitas Dipa Makassar, Makassar, Indonesia
(*) Corresponding Author
AbstractKetersediaan data pada Learning Management System (LMS) mendorong penerapan pembelajaran adaptif di pendidikan tinggi. Penelitian ini mengusulkan kerangka kerja hybrid berbasis kecerdasan buatan yang mengintegrasikan K-Means clustering dan Neural Network untuk profil mahasiswa berbasis perilaku dan prediksi kinerja akademik. Model divalidasi menggunakan Open University Learning Analytics Dataset yang mencakup data demografi, interaksi, dan performa akademik. Hasil menunjukkan akurasi sebesar 0,68 dan F1-score sebesar 0,66, melampaui metode dasar dengan stabilitas yang lebih baik. Clustering menghasilkan silhouette score 0,62 yang menunjukkan pemisahan kelompok yang jelas. Selain itu, sistem meningkatkan relevansi konten sebesar 27% dan menurunkan risiko putus studi sebesar 18%, dengan waktu inferensi rata-rata 0,85 detik. Temuan ini menunjukkan efektivitas kerangka dalam mendukung pembelajaran adaptif yang dipersonalisasi dan skalabel. Model hybrid yang diusulkan dapat mendukung pembelajaran adaptif melalui jalur belajar yang dipersonalisasi serta membantu perguruan tinggi melakukan intervensi dini terhadap mahasiswa berisiko berdasarkan pemantauan berbasis data.
KeywordsPembelajaran Adaptif; K-Means Clustering; Jaringan Saraf; Sistem Manajemen Pembelajaran; Prediksi Kinerja Mahasiswa
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Digital Object Identifier https://doi.org/10.33096/busiti.v7i2.3467
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