Correlation of Self-Confidence and Student Learning Motivation Against Learning Outcomes of Class X Digital Simulation

This study aims to determine the relationship of trust and learning motivation on learning outcomes of simulation and digital communication in class X students. This type of research is quantitative by using correlational research methods. This research was conducted at SMK Negeri 6 Padang, in November 2019. The population in this study were all grade X students of SMK Negeri 6 Padang. The sampling technique uses proportional random sampling. The sample selected in this study were 228 students from 530 students of class X. the result is r count> r table (0.2733> 0.161), a positive and significant relationship and continued with the F-count test> FT table (12.33> 1,750). Copyright © Universitas Pendidikan Ganesha. All rights reserved. A R T I C L E I N F O Article history: Received February 2020 Received in revised Form 01 March 2020 Accepted 18 April 2020 Available online 30 May 2020


Introduction
Self Confidence and Student Learning Motivation greatly affects student learning outcomes. Vocational High School 6 Padang is one of the schools that is trying to produce graduates who are ready to compete in the world of work. In facing these challenges, SMK 6 Padang strives to improve the quality of its graduates through improving learning outcomes.
According to Nana Sudjana (2009: 3) student learning outcomes are essentially changes in behavior as a result of learning in a broad sense covering cognitive, affective, and psychomotor fields. Dimyati and Mudjiono (2006: 3-4) also mention learning outcomes are the result of an interaction of learning and teaching. From the student's side, the learning outcome is the end of teaching from the peak of the learning process. In reality what happens in daily practice, many students are still classified as poor learning outcomes. This was obtained from daily test scores less than KKM (Minimum completeness criteria).
Based on observations and observations that I made at SMK N 6 Padang, Complete Minimum Criteria set with a value of 75, and teachers who teach Digital Simulation Subjects are graduates from Padang State University who have been certified in these subjects. The purpose of this study was to determine a positive and significant relationship between self-confidence correlations and student learning motivation on student learning outcomes in digital simulation subjects.
Fatimah (2010: 153-155) suggests several characteristics or characteristics of individuals who have proportional self-confidence are as follows: 1) Believe in your abilities or competencies, 2) Dare to accept and face rejection, dare to be yourself, 3) Have good self-control (not in a stable mood and emotions, 4) Having an internal locus of control (looking at success or failure, and 5) Having a positive perspective on yourself According to Amyani, (2010: 25) self-confidence is a belief in one's own abilities. Self-confidence is an aspect of human personality that functions important to actualize the potential it has. Without a sense of confidence, many problems arise in humans. Due to self-confidence, a person is able to actualize all his potential. Confidence is needed either by a child or a parent, individually or in groups.
Digital Simulation subjects are subjects that equip students to be able to communicate ideas or concepts through digital media. Digital Simulation subjects for vocational students are tools to communicate ideas through digital presentations. In its function as a tool, these subjects provide mastery skills so students know to use them when needed.

Methods
This type of research used in this study is quantitative with the method used correlational. In this study, the population was all students of class X in SMK Negeri 6 Padang as many as 530 students with samples This study uses Proportional Random Sampling technique, so that the sample of this research is 228 students.
The higher student motivation will have an impact on student learning outcomes. Motivation can affect business drivers and student achievement. For more details can be seen in Figure 1. Chart conceptual framework. Data analysis was performed using a statistical program on a computer namely Microsoft Excel and the SPSSl program, to find out the relationship between the independent variable (X) and the dependent variable (Y). This technique is only implemented if it meets several requirements, namely sample data for each variable normally distributed, homogeneity test, linearity test and hypothesis testing, as below. Journal of Education Research and Evaluation, Vol. 4, No. 2, Tahun 2020, pp. 216-220 218 JERE, P-ISSN: 2597-422x E-ISSN: 2549-2675 a. Normality test is used to determine whether or not the normal distribution of data is a prerequisite to determine the type of statistics that will be used in subsequent analyzes, the normality test uses the lilliefors test.
b. Regression linearity test with simple regression techniques, to see whether the regression line is linear or not. This test aims to determine the strength of the contribution between variables X1 and X2 to the variable Y. Hypothesis testing about the similarity of two averages is done if the data is normally distributed and the two data groups are homogeneous, then in testing the statistical hypothesis the t test is used.

Result And Discussion
The data display of the basic statistical calculation of the three variables can be seen in table 1 based on the processed data using Microsoft Excel 2010 application.  Based on table 5 above it can be seen that the significance score for motivation and learning style on student learning outcomes obtained L0 for the X1 variable of 0.0062for variable X2 of 0.0008 and for variable Y of -0.0179. Whereas Lt of 0.0721 was obtained from the critical value of L for the Lilliefors test. Because the result is L0 <Lt, the sample is said to be normally distributed. Then the linearity test requirements can be done.

b. Linearity test
Linearity test aims to determine whether two variables have a linear relationship or not significantly. Linearity tests are usually used as a prerequisite in correlation analysis or linear regression. The results of data linearity using MS.Excel 2010 can be seen in Table 3.

c. Hypothesis
Based on the results of the analysis of research on the calculation of the correlation of Learning Motivation with Learning Outcomes is rcount> rtable (0.366> 0.113), Then a t test was conducted between Learning Motivation and learning outcomes tcount> t table (2.726> 1.960), so as to obtain positive and significant results between variables X2 (self confidence) and Y (learning outcomes).Based on the calculation of the correlation of self-confidence and motivation to learn with learning outcomes is r count> r table (0.273> 0.161), and an F test was carried out for both between self-confidence and learning motivation with learning outcomes obtained Fcount> FTabel (12.33> 1.334).So it can be said that the relationship in research is said to be positive and significant between self-confidence and learning motivation with learning outcomes of simulation subjects and digital communication of class X students of SMK Negeri 6 Padang. It is stated that the third hypothesis is accepted.So the three hypotheses in this study were first accepted self confidence with learning motivation, the second is learning motivation with learning outcomes and the third is self confidence and learning motivation with learning outcomes. This research is relevant to the thesis of Rona Diana, 2019. Correlation of Learning Interests and Learning Motivation with Learning Outcomes of Digital Simulation Class X Even Semester in SMK Negeri 4 Padang.

Conclussion
From the research that has been done about the correlation of self-confidence and learning motivation with learning outcomes, it can be concluded that the correlation in research is said to be positive and significant between the correlation of self-confidence and learning motivation with learning outcomes of class X digital simulation subjects, with the meaning of the hypothesis being accepted.