PENGARUH MODEL PEMBELAJARAN DEEP LEARNING TERHADAP HASIL BELAJAR EKONOMI SISWA KELAS X DI SMA PEMBANGUNAN NASIONAL PAGAR MERBAU PEMNAS - Fransiska Dewi, Fajar (Pendas : Jurnal Ilmiah Pendidikan Dasar, 2026)
This study aims to determine and analyze the effect of the Deep Learning model on the economics learning outcomes of Grade X students at SMA Pembangunan Nasional Pagar Merbau (PEMNAS) during the 2025/2026 academic year. The study employs a quantitative approach using a quasi-experimental design, specifically the Nonequivalent Control Group Design. The population consists of all Grade X students at the school, comprising two classes with a total of 60 students. A total sampling technique was used, designating Class X-1 (30 students) as the experimental group applying the Deep Learning model and Class X-2 (30 students) as the control group applying the conventional learning model. Data were collected using economics learning outcome instruments specifically pre-tests and post-tests that met validity and reliability requirements. Data analysis techniques included simple linear regression analysis, the t-test (partial test), and the calculation of the coefficient of determination (R²). The results indicate that the average post-test score in the experimental class (78.27) showed a significantly greater increase compared to the average pre-test score (60.80), with a gain of 17.47 points; meanwhile, the control class saw an increase from an average pre-test score of 61.60 to an average post-test score of 71.73, a gain of 10.13 points. Simple linear regression analysis yielded the equation Y = 48.79 + 0.485X. Hypothesis testing via the t-test resulted in a calculated t-value of 4.693 (or 5.76 in manual calculation), which exceeds the t-table value of 1.701 at a significance level of α = 0.05 and degrees of freedom (df) of 28 (p = 0.000 < 0.05). These findings indicate that the null hypothesis (H₀) is rejected and the alternative hypothesis (Hₐ) is accepted. Furthermore, the coefficient of determination (R-squared) value of 0.440 indicates that the implementation of the Deep Learning instructional model contributes 44% to the improvement of students' economics learning outcomes, while the remaining 56% is influenced by other internal and external factors. Thus, it can be concluded that the implementation of the Deep Learning instructional model has a positive and significant effect on the economics learning outcomes of Grade X students at SMA Pembangunan Nasional Pagar Merbau (PEMNAS).