PENERAPAN ALGORITMA DECISION TREE UNTUK DETEKSI DINI SISWA MEMERLUKAN INTERVENSI PEMBELAJARAN DI MI NURUL JIHAD
Keywords:
Decision Tree, deteksi dini, intervensi pembelajaran, klasifikasi, madrasah ibtidaiyahAbstract
Penilaian kondisi belajar siswa di sekolah dasar masih sering dilakukan secara subjektif dan hanya bertumpu pada nilai akademik, sehingga siswa yang sesungguhnya memerlukan intervensi pembelajaran berisiko tidak terdeteksi secara tepat waktu. Penelitian ini bertujuan untuk menerapkan algoritma Decision Tree guna mendeteksi dini siswa yang memerlukan intervensi pembelajaran secara lebih objektif dan sistematis di MI Nurul Jihad Tembilahan Hulu. Data diperoleh dari dokumen akademik dan observasi guru terhadap 69 siswa kelas 4 hingga kelas 6 tahun pelajaran 2023/2024. Variabel yang digunakan meliputi nilai akademik, persentase kehadiran, pengumpulan tugas, dan keaktifan siswa di kelas. Model dibangun menggunakan algoritma Decision Tree dengan pembagian data training dan testing sebesar 80:20. Hasil penelitian menunjukkan bahwa model mampu mengklasifikasikan siswa ke dalam dua kategori, yaitu perlu intervensi dan tidak perlu intervensi, dengan akurasi 90,91%, presisi 92,31%, recall 88,89%, dan F1-Score 90,57%. Penelitian ini menyimpulkan bahwa algoritma Decision Tree terbukti efektif sebagai alat bantu berbasis data yang dapat mendukung guru dalam mengidentifikasi siswa yang membutuhkan perhatian khusus secara lebih cepat, tepat, dan terukur.
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Copyright (c) 2026 Regina Zulaikha Tizar, Gita Novi Yanti, Muhammad Regi Nidzra Kurniawan, Muh Rasyid Ridha (Author)
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