Efektivitas Model Problem Based Learning Berbasis Deep Learning terhadap Kemampuan Berpikir Kritis pada Mata Pelajaran Matematika Siswa

Penelitian ini bertujuan untuk mendeskripsikan efektivitas model Problem Based Learning. (PBL) berbasis Deep Learning terhadap kemampuan berpikir kritis siswa pada mata pelajaran matematika serta mendeskripsikan aktivitas siswa selama penerapan pembelajaran. Penelitian ini menggunakan pendekatan kuantitatif dengan metode Pre-Experimental Design melalui desain One Group Pretest-Posttest. Sampel penelitian ini adalah kelas X SMA YAPITA Surabaya tahun ajaran 2025/2026. Teknik pengumpulan data menggunakan tes, observasi, dan angket. Analisis data dilakukan menggunakan uji Paired sample t-test dan uji N-Gain. Hasil penelitian menunjukkan bahwa model PBL berbasis Deep Learning efektif terhadap kemampuan berpikir kritis siswa. Hal ini ditunjukan dari hasil uji paired sample t-test yang memperoleh t_{tabel}<t_{hitung} yaitu 1,729<\ 27,741 maka H_0 ditolak dan H_1 diterima. Nilai rata-rata uji N-Gain sebesar 63,59% dengan kategori cukup efektif. Selain itu, aktivitas siswa selama penerapan model PBL berbasis Deep Learning memperoleh persentase 100% dengan kategori sangat aktif. Respon siswa terhadap model PBL berbasis Deep Learning menunjukkan respon positif dengan perolehan persentase 82,08% kategori sangat baik. Berdasarkan hasil analisis tersebut, maka menggunakan model PBL berbasis Deep Learning efektif terhadap kemampuan berpikir kritis pada mata pelajaran matematika siswa.

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This study aims to describe the effectiveness of the Problem- Based Learning (PBL) model (PBL) based on Deep Learning on students’ critical thinking skills in mathematics and to describe student activities during the implementation of the learning process. This study used a quantitative approach with a Pre-Experimental Design method through a One-Group Pretest-Posttest design. The research sample was the 10th-grade class at YAPITA High School, Surabaya, for the 2025/2026 academic year. Data collection techniques included tests, observations, and questionnaires. Data analysis was conducted using the Paired-Sample t-test and the N-Gain test. The results indicate that the Deep Learning-based PBL model is effective in enhancing students’ critical thinking skills. This is evidenced by the Paired-Sample t-test results, where t_(table) < t_(calculated) (1.729 < 27.741), leading to the rejection of H₀ and acceptance of H₁. The average N-Gain score was 63.59%, categorized as moderately effective. Additionally, student activity during the implementation of the Deep Learning-based PBL model achieved a 100% rate, categorized as highly active. Student responses to the Deep Learning-based PBL model showed a positive response with an 82.08% rate, categorized as very good. Based on these analysis results, the use of the Deep Learning-based PBL model is effective in enhancing students’ critical thinking skills in mathematics.