ANALISIS PERILAKU BELAJAR SISWA DI ERA ARTIFICIAL INTELLIGENCE MENGGUNAKAN MODEL DEEP LEARNING TABNET DAN TABTRANSFORMER UNTUK PENGEMBANGAN REKOMENDASI STRATEGI PEMBELAJARAN

Ahmad Muhammad; Ahmad Musyafa; Tukiyat Tukiyat

doi:10.31539/t0adps90

Authors

Ahmad Muhammad Universitas Pamulang
Ahmad Musyafa Universitas Pamulang
Tukiyat Tukiyat Universitas Pamulang

DOI:

https://doi.org/10.31539/t0adps90

Abstract

Perkembangan teknologi kecerdasan artifisial (Artificial Intelligence/AI) telah membawa perubahan signifikan terhadap perilaku belajar siswa, terutama dalam cara siswa mengakses informasi, menyelesaikan tugas, dan membangun strategi belajar mandiri. Penelitian ini bertujuan untuk menganalisis perilaku belajar siswa di era AI menggunakan model deep learning TabNet dan TabTransformer untuk memprediksi capaian akademik siswa serta mengembangkan rekomendasi strategi pembelajaran yang adaptif. Penelitian menggunakan pendekatan kuantitatif dengan data tabular yang diperoleh dari 2.052 siswa SMA Plus PGRI Cibinong. Variabel penelitian mencakup aspek akademik, digital, psikologis, sosial, dan penggunaan AI dalam pembelajaran. Tahapan penelitian meliputi preprocessing data, encoding, pembagian data latih dan data uji, pemodelan menggunakan TabNet dan TabTransformer, evaluasi model menggunakan RMSE, MAE, dan R², serta analisis feature importance untuk segmentasi siswa. Hasil penelitian menunjukkan bahwa TabTransformer memiliki performa lebih baik dibandingkan TabNet dalam memodelkan hubungan antara perilaku belajar dan nilai akademik siswa. Variabel usaha belajar, penggunaan AI untuk memahami materi, dan motivasi belajar menjadi faktor dominan yang memengaruhi capaian akademik. Selain itu, penelitian menghasilkan empat segmentasi profil siswa yang digunakan sebagai dasar penyusunan rekomendasi strategi pembelajaran adaptif. Penelitian ini menunjukkan bahwa AI berperan sebagai faktor pendukung pembelajaran, sementara regulasi diri dan usaha belajar tetap menjadi faktor utama keberhasilan akademik siswa.

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