THE RELATIONSHIP BETWEEN SELF REGULATED LEARNING AND PEER CONFORMITY, ACADEMIC ANXIETY OF STUDENTS AT SMK NEGERI 3 PADANG

This research is motivated by a phenomenon that occurs at SMK Negeri 3 Padang, namely low academic anxiety. Self-regulated learning and peer conformity are factors that influence students' academic anxiety. This study aims to analyze (1) self-regulated learning, (2) peer conformity, (3) academic anxiety, (4) self-regulated learning with students' academic anxiety, (5) the relationship between peer conformity and students' academic anxiety and (6) ) the relationship between self-regulated learning and peer conformity with students' academic anxiety. The research method used is quantitative. This type of research is descriptive correlational. The population in this research is 1047 students and the sample of this research is 290 students. Sampling used the Slovin formula and sampling using proportional random sampling technique. The research instrument was a questionnaire with a Likert Scale measurement. Data were analyzed with correlational descriptive statistics with the help of SPSS version 20.00. The results of the study show that (1) students' self-regulated learning is in medium, (2) peer conformity is in the medium category, (3) students' academic anxiety is in the r category, low (4) there is a positive relationship and significant between self-regulated learning and academic anxiety beliefs, (5) there is a positive and significant relationship between peer conformity and students' academic anxiety, and (6) there is a positive and significant relationship between self-regulated learning and peer conformity support with anxiety student academic. So it can be concluded that there is a positive and significant relationship between self-regulated learning and conformity of seabya friends with students' academic anxiety.


INTRODUCTION
adults (Hurlock, 1976).Prayitno (2002) explains that students who are at the SMK level will experience a transitional period in the form of biological, cognitive, social-emotional, and moral changes.In addition, students also experience physical and psychological changes that cause confusion, resulting in emotional turmoil and mental stress.Ali & Asrori, (2006) stated that one of the developmental tasks that students experience is achieving new, more mature relationships with peers and trying to achieve social roles in their environment.Students who have barriers to self, will experience problems and unable to achieve happiness in life.Anxiety is a response to experiences that are felt unpleasant and are followed by feelings of anxiety, worry, and fear.Therefore, it can be stated that anxiety is a subjective aspect of a person's emotions involving feelings (Holmes, 1991).Individuals who are anxious have physical symptoms such as tense muscles, tremors, sweating and fast heart beats (Ottens, 1991).Academic anxiety can interfere with student learning if the anxiety continues at high intensity.Elliot (2004) explains that anxiety at low and moderate levels has a positive effect on learning performance, one of which can increase learning motivation.Rita L Atkinson (2001) academic anxiety is caused by internal factors in the form of self-regulated learning and external factors in the form of peer conformity.Ghufron & Risnawati (2014) stated that Self Regulated Learning is a very important factor in influencing individual academic anxiety.Good Self Regulated Learning will be able to control individual anxiety levels.Ghufron & Risnawati (2014) suggests that a person is said to carry out self-regulation in learning if they systematically regulate their behavior and cognition by paying attention to self-made rules, controlling the course of the learning process and integrating knowledge, training to remember information obtained, and developing and maintaining value.-the positive value of learning.
Zimmerman & Martinez-Pons (1990) defines Self-Regulated Learning as the level where participants actively involve metacognition, motivation, and behavior in the learning process.Selfregulated learning is also defined as a form of individual learning that depends on their learning motivation, autonomously develops measurements (cognition, metacognition, and behavior), and monitors their learning progress (Baumert, 2002).Self-Regulated Learning integrates many things about effective learning.Knowledge, motivation, and self-discipline are important factors that can influence self-regulated learning.(Woolfolk, 2008).The conformity of students' peers has an important influence in dealing with academic anxiety.Baron & Byrne (2005) peer conformity is support obtained from other individuals in the form of emotional support (giving attention, care and comfort), instrumental support, esteem support or self-esteem, information support or support from groups.The peer conformity environment obtained by individuals can affect individual anxiety levels.Based on the results of interviews SMKN 3 Padang is one of the best vocational schools in the city of Padang.The phenomenon that occurs is that many students experience pressure in learning, starting from the heavy workload to the target of getting satisfactory grades.According to the Guidance Teacher at SMKN 3 Padang Irsal, it was found that many students experienced anxiety because of unsatisfactory report card scores.In addition, the large number of assignments in the form of homework that must be completed is an additional pressure for students.This creates academic anxiety in students.Independence in managing learning strategies, namely Self Regulated Learning, which is good at overcoming academic anxiety in students.In addition, conformity between peers also contributes to regulating the level of student academic anxiety in the learning process.

RESEARCH METHODS
This study aims to describe how self-regulated learning, peer conformity and academic anxiety and find out how big the correlation is between the three variables.The method used is descriptive correlational with multiple regression analysis techniques, the research sample is 1047 students obtained through purposive sampling technique.the sample in this research is 290 students.Data were collected using self-regulated learning instruments, peer conformity and academic anxiety using a Likert scale with 5 alternative answers, Very Appropriate (SS), Appropriate (S), Fairly Appropriate (CS), Not Appropriate (TS) and Very Inappropriate (S) STS) with a total of 85 items.Data collection was carried out directly by seeking information from the counseling teacher.Then the data were analyzed using the percentage formula, simple regression and multiple regression with the help of the SPSS version 20.00 application

RESULTS AND DISCUSSION Self Regulated Learning (X1) Uji Normalitas
The data normality test is carried out to find out the data comes from a population that is normally distributed or is in a normal distribution.There are several ways that can be done to test data normality (Widiyanto, 2013).n this study, the normality test was carried out using the Kolmogorov-Smirnov test, which was carried out by comparing the Asymp coefficients.Sig. or P-value with a significance level of 0.05.If Asymp.Sig. or P-value ≥ 0.05 (significance level) then the data comes from a normally distributed population.Conversely, if Asymp.Sig. or P-value < 0.05 (significance level), then the data comes from a population that is not normally distributed.The results of calculating the three variables using SPSS version 20 are presented in table 4.7 below..

Uji Linieritas
The linearity test aims to determine whether there is a linear relationship between variables.The linearity test in this study uses the regression line equation/multiple regression.If Rcount > Rtable at a significance level α = 0.05, it can be said to be linear (Yusuf, 2013).To avoid errors in manual calculations, the calculations use the help of the SPSS version 20.00 program.The results of the data linearity test can be seen in table 4.8 below.Based on table 4.8 above the results of the data linearity test from the three variables of selfregulated learning (x1), peer conformity (x2) and academic anxiety (y) with a sig.0.66 > 0.05.That is, the data for each variable is linear.

Uji Multikolinieritas
The multicollinearity test in the study was carried out by looking at the value of the Variance Inflation Factor (VIF) for each predictor, to be free from multicollinearity symptoms the VIF value is below 10 (Widiyanto, 2013).In this case, the calculation uses the SPSS 20.00 program.The calculation results can be seen in the following table 4.9..

Pengujian Hipotesis
The calculation results in table 4.9 above show that the VIF value of the three variables is 1.343 and the second VIF conformity VIF value is less than 10.00.That is, there is no multicollinearity between self-regulated learning and peer conformity.
1.There is a significant relationship between self-regulated learning and academic anxiety 2. There is a significant relationship between peer conformity and academic anxiety 3.There is a significant relationship between self-regulated learning and peer conformity together with academic anxiety..

First Hypothesis
The first hypothesis to be tested in this study is stated in the following sentence form.
``H0: There is no significant relationship between self-regulated learning and academic anxiety.. H1: There is a significant relationship between self-regulated learning and academic anxiety The basis for decision making is as follows.
The basis for decision making is as follows.H0 : If the significance ≥ Alpha 0.05 H1 : If the significance ≤ Alpha 0.05 The results of simple regression calculations using SPSS version 20.0, the results of which can be seen in table 4.10 below.4.10 R value which is the symbol of the coefficient.In the table above the correlation value is 0.429.This value can be interpreted.This value can be interpreted that the relationship between the two research variables is in the sufficient category.The table above also shows the value of R Square or the coefficient of determination (KD) which shows how well the regression model is formed by the interaction of the independent variables and the dependent variable.KD value obtained is 18.4%.So it can be interpreted that the independent variable X1 has a contribution effect of 18.4% on variable Y.  4.11 displays the results of the significance test with an Fcount value of 64,785, while the Ftable value is 1,968.These results indicate that Fcount > Ftable with a significance level of 0.000 which is less than 0.05.Thus, it can be concluded that there is a significant relationship between self-regulated learning and academic anxiety.In the F test, we compare the Fcount value (which is calculated based on actual data) with the Ftable value (which is taken from the F distribution table with a certain level of significance).If the Fcount value is greater than the Ftable value at the specified significance level (in this case 0.000 <0.05), then the independent variable (self-regulated learning) has a significant influence on the dependent variable (academic anxiety).
With a Fcount value that is greater than the Ftable value and a very small significance, it can be concluded that the relationship between self-regulated learning and academic anxiety is statistically significant.This means that self-regulated learning has a significant effect on the level of academic anxiety in the sample studied Furthermore, to find out the simple regression equation can be seen in table 4.12 below: The simple regression results in table 4.12 above show that the B value is -0.340.This means that self regulated learning has a significant relationship with academic anxiety.The table above also describes the regression equation as follows.
The constant value (a) is 107.028meaning that if self-regulated learning is worth 0 then academic anxiety is worth -0.340.The value of the regression coefficient of self-regulated learning (b1) is negative, meaning that every increase in self-regulated learning by 1 will increase academic anxiety by 0.34 So, it can be concluded that the hypothesis is accepted, there is a negative relationship and has a significant influence between self-regulated learning and academic anxiety.If the value of r is negative, the relationship between the two is negative, which means that when self-regulated learning increases, academic anxiety also tends to increase.Meanwhile, if the value of r is negative, the relationship is negative, indicating that an increase in self-regulated learning is associated with a decrease in academic anxiety..

Second Hypothesis
The second hypothesis to be tested in this study is stated in the following sentence form.`H0 : There is no significant relationship between peer conformity and academic anxiety.H1 : There is a significant relationship between peer conformity and academic anxiety.The basis for decision making is as follows.
H0 : If the significance ≥ Alpha 0.05 H1 : If the significance ≤ Alpha 0.05 The results of simple regression calculations using SPSS version 20.0, the results of which can be seen in table 4 4.13 R value which is the symbol of the coefficient.In the table above the correlation value is 0.430.This value can be interpreted.This value can be interpreted that the relationship between the two research variables is in the sufficient category.The table above also shows the value of R Square or the coefficient of determination (KD) which shows how well the regression model is formed by the interaction of the independent variables and the dependent variable.KD value obtained is 18.5%.So it can be interpreted that the independent variable X2 has a contribution effect of 18.5% on variable Y. as can be seen in table 4.13 below:  4.14 shows that the Fcount value is 65.261 while the Ftable value is 1.968.This indicates that Fcount is greater than Ftable at a significance level of 0.000, which is much smaller than the value α (0.05).Given this significant difference, it can be concluded that there is a significant relationship between peer conformity and the level of academic anxiety.These results indicate that peer conformity variables significantly affect the level of academic anxiety in the context of this study.While these conclusions provide a preliminary understanding of the relationship between the two variables, it is important to consider the context and limitations of the research before drawing broader conclusions.Furthermore, to find out the simple regression equation analysis can be seen in table 4.15 below.= significant relationship between variables The simple regression results in table 4.15 above show that the B value is 0.342.This means that peer conformity has a significant relationship with academic anxiety .The table above also describes the regression equation as follows.Ỹ = a + bX1 = 47,740 + 0.342X1 The equation model contains meaning. he value of the constant (a) is 47.740 meaning that if peer conformity is worth 0 then academic anxiety is worth.0.342 The value of the peer conformity regression coefficient (b1) is positive, meaning that every increase in peer conformity by 1 will decrease academic anxiety by 0.342 So, it can be concluded that the hypothesis is accepted, there is a positive relationship and has a significant influence between peer conformity and academic anxiety

Third Hypothesis
The third hypothesis to be tested in this study is stated in the following sentence form.H0 : H0: There is no significant relationship between self-regulated learning of peer conformity and academic anxiety.H1 : There is a significant relationship between self-regulated learning and peer conformity with academic anxiety The basis for decision making is as follows.H0 : If the significance ≥ Alpha 0.05 H1 : If the significance ≤ Alpha 0.05 The results of simple regression calculations using SPSS version 20.0, the results of which can be seen in table 4.16 below:  4.16 above shows that the r value is 0.430, which shows the correlation coefficient of multiple regressions of self-regulated learning and peer conformity with academic anxiety.The r Square value is 0.185, meaning that self-regulated learning and peer conformity are related to academic anxiety of 18.5%.After knowing the correlation coefficient of self-regulated learning and peer conformity to academic anxiety, the next step is to carry out a significance test which aims to explain whether the variation in the value of the independent variable can explain the variation in the dependent value using the magnitude of the F value, as can be seen in table 4.17 below.4.17 above shows the variation in the value of the independent variables (X1 and X2) can explain the dependent variable (Y) by looking at the magnitude of the Fcount obtained at 32.604 with a significance of 0.000 which is smaller than 0.05.Thus, it can be stated that there is a relationship between self-regulated learning and peer conformity with academic anxiety.This means that self-regulated learning and peer conformity can be used to predict academic anxiety.It was concluded that the multiple regression coefficients obtained in this study were significant.The findings of this study are that there is a significant relationship between self-regulated learning support and peer conformity together with academic anxiety.Furthermore, to find out the multiple regression equation can be seen in table 4.18 below.Based on the results of the multiple regression analysis in table 4.18 above, it is known that self-regulated learning and peer conformity have a positive relationship with academic anxiety.Ỹ = a + b1X1 + b2X2 = -16.001+ 0.366X1 + 0.708X2 1) The constant value (a) is -16.001,meaning that if self-regulated learning and peer conformity is 0, then academic anxiety is 16.001 2) The value of the regression coefficient of self-regulated learning b1) The value of the regression coefficient is 0.366, meaning that every increase in self-regulated learning by 1 will increase academic anxiety by 0.366 assuming other variables are constant.
3) The regression coefficient value of peer conformity (b2) The regression coefficient value is 0.708, meaning that every increase in peer conformity by 1 will decrease academic anxiety by 0.708 assuming other variables have a fixed value.
Based on testing the third hypothesis, based on the results of the multiple regression test of self-regulated learning and peer conformity on academic anxiety, it can be concluded that the third hypothesis is accepted, meaning that there is a significant relationship.Based on the test results above, it can be concluded that the results of the research are in the form of an image of the relationship between self-regulated learning and peer conformity towards academic anxiety as shown below.
The image above shows the relationship between Self-Regulated Learning (SRL) and Peer Conformity with Academic Anxiety.The Self-Regulated Learning variable is negatively and significantly related to academic anxiety, with a correlation (r) of 0.429 and R2 of 0.184 Peer Conformity Variable is also positively and significantly related to academic anxiety, with a correlation coefficient (r) of 0.430 and R2 of 0.185.When the two variables are combined, they are significantly related to academic anxiety, with a correlation (r) of 0.430 and R2 of 0.185.Based on the results of this study, it can be concluded that the level of academic anxiety is influenced by the level of each variable Self-Regulated Learning and Peer Conformity.Therefore, to reduce academic anxiety, improvement in Self-Regulated Learning and good Peer Conformity is needed.

CONCLUSION
Based on the findings and discussion of the research results, the following conclusions can be put forward.
1. Students' self-regulated learning is in the Medium category.This means that students are able to be enthusiastic about learning and have the desire to be independent in learning.2. Student peer conformity is in the Medium category.This means that students are able to adjust to their peers so as to provide good things in the individual 3. Students' academic anxiety is in the low category.This means that students have not been able to provide understanding according to the conditions that are in the school so that giving is still in the low category 4.There is a positive and significant relationship between self-regulated learning and students' academic anxiety.That is, the level of students' academic anxiety can be explained by students' self-regulated learning.It can be concluded that the higher the self-regulated learning, the lower the academic packaging.5.There is a positive and significant relationship between peer conformity and students' academic anxiety.That is, the level of peer conformity with academic anxiety can be concluded that the higher the peer conformity, the lower the academic anxiety.6.There is a positive and significant relationship between self-regulated learning and peer conformity on academic anxiety.This means that the level of student academic anxiety is influenced by self-regulated learning and peer conformity.Thus, it can be explained that the higher self-regulated learning and peer conformity, the lower students' academic anxiety.

Table 4 .
10 Results of Simple Linear Regression Analysis of Self Regulated Learning (X1) with

Table 4 .
11 Significance Test Results of Self Regulated Learning (X1) with Academic Anxiety (Y)

Table 4 .
12 Results of Simple Regression Analysis of Self Regulated Learning (X1) with Academic Anxiety (Y) B = direction value as a determinant of forecast (prediction) T = t test coefficient Sig = significant relationship between variables .13 below.

Table 4 .
14 Results of Significance Test of Peer Conformity (X1) with Academic Anxiety (Y)