Esra Butarbutar, H. H. Sianipar, Injen Pardamean Butarbutar, Universitas Hkbp Nommensen
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引用次数: 0
摘要
本研究旨在了解 2023/2024 学年 SMA Negeri 5 Pematang Siantar 第十一班学生的家庭环境和学习纪律对经济学习成果的影响。研究对象为 102 名学生。样本收集技术使用的是斯洛文公式。使用的数据收集技术是调查问卷。假设数据收集技术使用了简单回归分析、多元回归分析和判定系数(R2)。 研究结果表明1)家庭环境对学习成绩有积极而显著的影响,这一结果可以从 t 检验中看出,学习纪律的计算 t 值(0,0 8)> t 表值(1.318),这意味着变量是显著的。误差检验(Mukticolinearity Test)。公差或方差膨胀因子(VIF)的假设是:如果 VIF > 10 或标记公差 < 1.20,则能够进行多重共线性检验;如果 VIF < 10 或标记公差 > 0.10,则不能进行多重共线性检验。从附件(1.20)中可以看出,公差>0.10 或方差膨胀因子(VIF)<10,因此可以得出结论,数据不存在多重共线性的症状。
The Impact of Family Environment and Students Discipline for the Result of Economics Subject Grade XI SMA Negeri 5 Pematang Siantar Year 2023/2024
This research aims to gain knowledge regarding the influence of the family environment and learning discipline on the economic learning outcomes of students in class XI at SMA Negeri 5 Pematang Siantar FY 2023/2024 This type of research is quantitative research with a quantitative descriptive data analysis approach with the testing media used is Microsoft Excel . The total population in this study was 102 students. The sample collection technique used was the Slovin formula. The data collection technique used was a questionnaire. Hypothesis data collection techniques use simple regression analysis , multiple regression analysis and coefficient of determination (R2). The results of this research state that: 1) There is a positive and significant influence of the family environment on learning outcomes, this result can be seen in the t test where the calculated t value of learning discipline (0, 0 8) > t table value (1.318) which means the variable is significant. Mukticolinearity Test . The assumption of Tolerance or Variance Inflation Factor (VIF) is capable stated that If VIF > 10 ormark Tolerance < 1.20 so that capablemulticollinearity., or If VIF < 10 or mark Tolerance > 0.10 so it is not capable of multicollinearity. It can be seen in the attachment, (1.20) that Tolerance > 0.10 or Variance Inflation Factor (VIF) < 10, so it can be concluded that the data is not capable of symptoms of multicollinearity.