International Journal Education and Computer Studies (IJECS) 2 .
, 2022, 1-9 Published Online May 2022 in IJECS .
ttp://w.
org/index.
php/ijec.
P-ISSN : 2776-4729.
E-ISSN : 2776-3277.
DOI: https://doi.
org/10.
35870/ijecs.
The Implementation of Independent Learning Activity Units in the Semester Credit System Improves Learning Achievement May * Sekolah Tinggi Teologi Sunergeo Banten.
Indonesia.
Email: mayseminary77@gmail.
Received: 9 March 2022.
Accepted: 21 April 2022.
Published: 15 May 2022 Abstract: The purpose of this study was to find out how much contribution the application of the Independent Learning Activity Unit in the Semester Credit System to the Learning Achievement of Students at the Doyo Baru Adventist High School contributed.
This study uses quantitative methods with a correlational research design approach.
Based on the result of the study, there is a significant relationship between independent learning activity units in the semester credit system and learning achievement the is a correlation coefficient value (R) = 0.
coefficient of determination (R.
= The results of this study indicate the relationship between the application of the Independent Learning Activity Unit in the Semester Credit System and the Student Achievement of 46.
The remaining 53.
1% contributed by other variables not examined in this study.
The contribution of the Independent Learning Activity Unit from the Implementation of the Independent Learning Activity Unit in the Semester Credit System to the Student Achievement of 46.
Keywords: UKBM.
SKS.
Learning Achievement.
Quantitative.
Correlation.
Introduction The Independent Learning Activity Unit is a device used to support learning and individual students in the Semester Credit System that requires independence, flexibility, and completeness in learning .
According to Ahmadi and Amri, preparation is needed in the application of the Semester Credit System, namely, "preparing modules for students that must be equipped with the subject matter, student training tools or students, evaluation tools, independent work exercises, as well as general test kits for each subject .
Semester Credit System is a form of development of education administration designed to serve students in completing the learning load according to their abilities, talents, and learning speed .
This system requires all students to undergo the same learning system in completing their learning program.
This system is less aspirational when faced with the fact that students are basically diverse both in terms of talents and interests .
Students who have special intelligence will be hampered from completing their study programs because they have to wait for other friends, and vice versa students who have average abilities must follow the learning patterns of students who have special intelligence .
Through the Independent Learning Activity Unit in the Semester Credit System, students are expected and able to complete their educational program faster than the general study period that has been set in each educational unit .
The existence of UKBM will gradually change the system of teaching and learning activities that are often applied in general in the classroom.
So broadly speaking, the Independent Learning Activity Unit can have a broad influence and impact on The application of the Independent Learning Activity Unit is of special interest because the implementation process is directly related to individual participants, and there are many benefits and independence of learning for students .
Based on the guidebook for the development of independent learning activity units published by the directorate of senior high school development, the Ministry of Education and Culture, the UKBM development components include AuLesson Textbooks (BTP) as the main learning resource that can be enriched with more actual and relevant sources, core competencies (KI)Ay and basic components (KD), assignments and learning experiences following the competencies to be achieved, and self-evaluation toolsAy .
Learning achievement is the result that has been achieved by students with their abilities or potential in receiving the material that has been given to them or students' efforts to achieve the expected goals .
That is, learning achievement must include cognitive, affective, and psychomotor aspects.
The three aspects above do not stand alone but are inseparable units, even a hierarchical relationship .
Learning success and learning achievement are influenced by several factors, both internal and external .
According to Suryabrata .
, the factors that affect learning achievement are classified into two factors .
, namely:
Copyright A 2022 IJECS International Journal Education and Computer Studies (IJECS), 2 .
2022, 1-9 The Implementation of Independent Learning Activity Units in the Semester Credit System Improves Learning Achievement Factors originating from outside themselves or exogenous factors, these factors are classified into two parts, namely:
Physiological factors Psychological factors Factors that come from themselves or in doing, are also classified into two parts, namely:
Social factors Non-social factors According to Deasyanti & Aarmeini .
, the factors that affect academic achievement are as follows .
Cognitive Readiness (Cognitive Entry Behavio.
Cognitive readiness is a requirement of students learning skills needed before they can master new tasks.
This cognitive readiness is influenced by the student's background.
Affective Entry Behavior Affective characteristics refer to students' motivation to learn new material that includes students' emotional aspects, including interests, attitudes, and views.
Teaching quality Quality of lessons is the quality of teaching provided by educators and focuses on interactions that occur in the From the writer's observations in the field, in general, students have not been able to show maximum learning achievement because the teaching methods taught are not right.
Therefore, it is necessary to have an appropriate teaching method so that student achievement increases.
One of them is through the learning model of independent learning activity The advantage of the independent learning activity unit model is that the results can be felt by students through a more communicative experience and can increase learning achievement to the maximum.
Some of the benefits of the Independent Learning Activity Unit model in the semester credit system for students include .
sequential learning through UKBM-UKBM according to the speed of mastery in each unit of study time.
self-study to master competencies according to the speed of mastery of each UKBM.
achieve a higher level of competence following the ability to learn .
determine the learning load according to their talents, interests, and learning speed abilities.
With the learning model of the Independent Learning Activity Unit given by the teacher to students, it is hoped that there will be an increase in learning achievement.
The objectives of this study are .
To determine the relationship between the implementation of UKBM in the Semester Credit System with Student Achievement at the Doyo Baru Adventist High School? .
To find out how big is the contribution of the Implementation of the Semester Credit System UKBM to Student Achievement at Doyo Baru Adventist High School? Method The approach used in this study is a quantitative approach using a correlational research design.
Ary.
Jacobs & Razavich said that correlational research is research that explains whether there is a relationship between various variables based on the size of the correlation coefficient .
The place of this research is at the Doyo Baru Adventist High School.
The population in this study were all students of class X IPA 1,2.
Social Sciences and Language at Doyo Baru Adventist High School.
Waibu District.
Jayapura Regency, amounting to 81 people.
And with the sample in the form of part of a whole, that was chosen specifically to represent the entire class X IPA 1 SMA Adventist Doyo Baru totaling 18 people.
So this study was conducted on the entire population by using 17 people to try out the validity of the instrument The number of instruments tested is 30 statement items.
The results of Reliability Statistics with N .
as many as 27 items obtained Cronbach's Alpha of 0.
From the comparison results obtained rcount < rtable for significant level = 0.
and rcount < rtable .
413 < 0.
025 for significant level = 0.
so that the instrument questionnaire was declared reliable to be used as a research questionnaire.
Data processing is carried out with the help of the Statistical Product and Service Solution (SPSS) version 22.
The prerequisite test uses the classical pre-assumption test technique with 2 .
types of analysis requirements, namely the normality test and the linearity test.
The data normality test is intended to determine whether the data used in the study is normal or not.
To test the normality of the data, the Kolmogorov Smirnov test kit with the SPSS 22.
0 program will be used.
The data is said to be normally distributed if the significance is > 0.
005 at the significant level () = 5%.
The linearity test of the data was used to determine whether the two variables had a linear or insignificant relationship.
is said that two variables have a linear relationship if the significant value .
is less than 0.
Hypothesis testing was carried out using Bivariate Correlation analysis to determine the value of each variable or class interval dimension.
The author sets 3 class intervals to measure the level of understanding, namely lack of understanding, understanding enough, and very understanding.
Just like the first hypothesis test, the second hypothesis test was carried out using Bivariate Correlation analysis.
The author sets 3 class intervals to measure learning achievement, namely low, medium, and high.
The third hypothesis test was carried out by simple correlation analysis .
, determination of variance .
2 y.
, simple correlation significance test .
, linear regression equation with line equation =a Xn accompanied by pictures and the meaning of the equation and significance test.
regression (F) via Anova table.
Copyright A 2022 IJECS International Journal Education and Computer Studies (IJECS), 2 .
2022, 1-9 The Implementation of Independent Learning Activity Units in the Semester Credit System Improves Learning Achievement Result and Discussion 1 Description of Research Result Data In the study, there were 17 respondents.
The results obtained for the average .
the midpoint .
of the standard deviation of 23,695.
the level of data spread .
is 561,471 while the lowest value .
is 44 and the highest value .
is 108 with a range of 64.
While the total number .
From the data analysis of variable X: Implementation of Independent Learning Activity Units in Semester Credit System (X) obtained the following data:
Table 1.
Description of Data Variable X Descriptive Statistics Variable X: Implementation of Independent Learning Activity Units in the Semester Credit System Valid Missing Range Minimum Maximum Sum Mean Std.
Devatiation Variance From table 2, it is known that variable Y has an average .
35 and a standard deviation of 3.
the level of data spread .
is 9,118 while the lowest value .
is 78 and the highest value .
is 88 with a range of 10.
While the total number .
The data analysis of variable Y: Student Achievement, it is obtained data as follows:
Table 2.
Description of Y.
Variable Data Descriptive Statistics Variable Y: Student Learning Achievement Valid Missing Range Minimum Maximum Sum Mean Std.
Devatiation Variance 2 Requirements Analysis Test Results Pre-requisite test is done by using the assumption test with SPSS 22.
0 for the Windows program.
Variable Y: Student Achievement.
Variable X: Implementation of Independent Learning Activity Unit in Semester Credit System.
Normality Test Results Santoso said that the Normality Test could be done by looking at the distribution of the data on the PP (Probability Plo.
The spread of data spreads around the diagonal line and follows the direction of the diagonal line, then the regression model fulfills the assumption of normality .
So, the spread that follows the diagonal axis indicates the normality of the data that meets the requirements.
The normality test was carried out on the dependent variable, namely Student Achievement (Y), and the independent variable, namely the Implementation of UKBM in the Semester Credit System (X).
The results of the calculation of the normality test successively are stated as follows:
Copyright A 2022 IJECS International Journal Education and Computer Studies (IJECS), 2 .
2022, 1-9 The Implementation of Independent Learning Activity Units in the Semester Credit System Improves Learning Achievement Figure 1.
Normality Test of UKBM Implementation Data in the System Semester Credits (X) From Figure 1 above, it can be concluded that the distribution of data spreads around the diagonal line and follows the direction of the diagonal line.
This is evidenced by the normality of the data for the independent variable.
Implementation of UKBM in the Semester Credit System meets the requirements.
Meanwhile.
Telaumbanua said that to find out whether normal or not a date can be seen on the results of the normality test in the Kolmogorov-Smirnov column.
To determine whether the data is normal or not, the Kolmogorov-Smirnov calculation obtained from the calculation needs to be compared with Sig = 0.
05 which is often referred to as the critical number.
Telambanua said that "if Sig based on the calculation is greater (>) than 0.
05 then it is declared normal" .
The results shown in the Kolmogorov-Smirnov column have data as shown in the image below:
Table 3.
Kolmogorov-Smirnov Analysis Results Test of Normality Unstandardized Residual Normal Parametersa,b Most Extreme Differences Mean Std.
Deviation Absolute Positive Negative Test Statistic Asymp.
Sig.
-taile.
Test distribution is Normal.
Calculated from data.
Lilliefors Significance Correction.
This is a lower bound of the true significance.
Based on the description of the data from the normality test, it can be concluded as follows: .
The UKBM Implementation Variable in the Semester Credit System (X) has Sig = 0.
200 and is greater (>) than 0.
05, so it is declared .
Student Learning Achievement Variable (Y) has Sig = 0.
200 and is greater (>) than 0.
05 then it is declared Linearity Test Results A linearity test is conducted to test whether the data between two variables is linear or not.
This is especially important for correlational analysis because the basic assumption of correlational analysis is linear.
This means that if one variable increases/increases then the other variables also increase and vice versa.
The following are the results of linearity testing using SPSS 22.
0 for Windows, which are shown in the Anova table, the details of which are as in table 4 below:
Copyright A 2022 IJECS International Journal Education and Computer Studies (IJECS), 2 .
2022, 1-9
The Implementation of Independent Learning Activity Units in the Semester Credit System Improves Learning Achievement
Y*X
Between Groups Within Groups Total Table 4.
Results of Linearity Test Analysis ANOVA Table Sum of Mean Squares df Square (Combine.
382 13 10.
Linearity Deviation from 921 12 5.
Linearity Sig.
By comparing Sig.
or Significance with 0.
If Sig based on the calculation is greater (O.
05 then it is declared .
Student Achievement (Y) against .
Implementation of UKBM in Semester Credit System (X), from the data above shows that Sig = 0.
222, this indicates that 0.
222 > 0.
05, thus the relationship between Student Learning Achievement The implementation of UKBM in the Semester Credit System above meets the assumption of linearity or Linear.
3 Hypothesis Testing Results The regression analysis used in this hypothesis test is intended to determine the relationship between variables.
Hypothesis testing can be done if the analysis requirements do not experience problems.
All the results of this regression analysis were completed with the help of SPSS 22.
0 for Windows.
First Hypothesis: There is a Relationship Between the Implementation of UKBM in the Semester Credit System and Student Achievement To see whether there is a relationship between the two variables, then in correlation research it can be seen from the results of the correlation analysis test and the analysis of the regression technique.
The correlation analysis uses Bivariate Correlation analysis and the method used in the regression technique is using the enter method.
Bivariete Correlation From the results of the bivariate correlation test, the correlation analysis of the data obtained was r = 0.
The correlation coefficient of 0.
685 with a significance level of 0.
000 or less than the given tolerance of 0.
05 indicates that H0 is rejected, meaning that the application of UKBM in the Semester Credit System has a relationship with Student Achievement in Adventist High School Doyo Baru.
This means that the relationship between the Implementation of UKBM in the Semester Credit System and Student Achievement is 68.
Simple Linear Regression Simple Linear Regression was conducted to determine the relationship between the independent variable and the dependent variable.
The results of a simple linear regression analysis of the implementation of UKBM in the Semester Credit System to improve Student Learning Achievement can be seen in table 5 below:
Table 5.
Results of Simple Linear Regression Analysis: Application of UKBM in SKS with Student Achievement Model Predictors: (Constan.
X Model Summary R Square Adjusted R Square Std.
Error of the Estimate Table 5 above shows that the R of 0.
685 shows that the correlation between the independent variable (UKBM Implementation in the Semester Credit Syste.
and the dependent variable (Student Learning Achievemen.
is significant (Sig.
F 0.
The value of R Square or the coefficient of determination is 0.
The adjusted coefficient of determination (Adjuste.
Furthermore, to find out whether the regression model can be used to predict the increase in student learning achievement, the results of a simple linear regression test are used in the Anova column, which is shown in table 6 below.
Copyright A 2022 IJECS International Journal Education and Computer Studies (IJECS), 2 .
2022, 1-9 The Implementation of Independent Learning Activity Units in the Semester Credit System Improves Learning Achievement Model Regression Residual Total Dependent Variable: Y Predictors: (Constan.
X Table 6.
ANOVA Test Results ANOVAa Sum of Squares Mean Square Sig.
In table 6 above.
Fcount is 13,264 with a significance level of 0.
000 which is much smaller than 0.
05 (Sig.
F 0.
This means that regression can be used to predict Student Learning Achievement has a correlation with the Implementation of UKBM in SKS or in other words the variable of Application of UKBM in SKS has a relationship with Student Learning Achievement.
as shown in table 7 below:
Model (Constan.
Table 7.
Coefficient Test Results Coefficientsa Standardized Unstandardized Coefficients Coefficients Std.
Error Beta Dependent Variable: Y Sig.
In table 7, the regression line equation = a X is = 75,042 0,087 (Implementation of UKBM in Semester Credit Syste.
With a constant of 75.
042, it can be said that the independent variable has a significant effect on the dependent Regression Line Equation Based on the multiple linear regression analysis data obtained from the results of data processing using SPSS 22.
for Windows, the resulting regression line equation is: = a bX.
The regression line equation from the results of SPSS analysis is: = 75,042 0,087 (Implementation of UKBM in Semester Credit Syste.
This regression line equation can be depicted in Figure 3.
as follows:
Figure 2.
Regression Line Equation The regression line equation aims to visualize the estimate that if the constant condition is increased by X, it will increase by a'.
From the data above, it can be seen that the constant condition is 75.
042 if estimated by X = 10, then it increases Second Hypothesis: How Much is the Implementation of UKBM in the Semester Credit System on Student Achievement Test this second hypothesis, it can be seen from the results of the regression analysis.
The results shown in the simple linear regression test have a regression coefficient, t Calculate and the level of significance in the study, as shown in table 8 below:
Copyright A 2022 IJECS International Journal Education and Computer Studies (IJECS), 2 .
2022, 1-9 The Implementation of Independent Learning Activity Units in the Semester Credit System Improves Learning Achievement Table 8.
Amount of Variable UKBM Contribution in Explaining Student Achievement Correlation R Square t Count Sig Variable Information Coefficient .
Alpha Application of UKBM in Semester Significant 0,685 0,469 3,642 0,002 Credit System Influence The UKBM implementation variable in the Semester Credit System has a significant level of 0.
This value is smaller than 0.
This shows that H0 is rejected at = 0.
05, meaning that the variable UKBM implementation in the Semester Credit System has a significant effect on Student Achievement.
This, seen from the regression coefficient, explains that the implementation of UKBM in the Semester Credit System influences Student Achievement.
Meanwhile, to see the magnitude of the contribution of the independent variable UKBM to the dependent variable, it can be seen from the magnitude of the coefficient of determination (R Squar.
From the results of the regression analysis, the coefficient of determination produced is 0.
This can be used to determine the percentage of the effect of the independent variable on the dependent.
Thus the effect of the independent variable on changes in the dependent variable is 46.
This means 9% of the Student Achievement variable can be explained by the UKBM variable in the Semester Credit System.
Judging from its significance in supporting Student Learning Achievement, there is 53.
1% which can be contributed by other variables not examined in this study.
In addition, to find out the contribution of the variable UKBM in explaining the increase in student learning achievement is the calculation of the multiplication between the correlation coefficient .
and beta (Standardized coefficient.
known as the formula.
SUKBM (Contribution of Independent Learning Activity Uni.
= r x beta x 100% .
The contribution of each variable referred to in this study is shown in table 9 below:
Table 9.
Calculation of the Amount of UKBM Contribution Variables UKBM Application in SKS in Explaining Student Achievement Using the SUKBM Formula Correlation Coefficient Variable Beta UKBM Contribution in % .
Application of UKBM in Semester 0,685 0,685 46,9% Credit System Based on table 9 above, it can be seen that the contribution of UKBM to the dependent variable of student learning achievement is 46.
In other words, the application of UKBM in the Semester Credit System is very effective in changing the percentage of student learning achievement.
Thus, the contribution of UKBM from the independent variable to the dependent variable proves that H0 is rejected and the hypothesis is accepted, namely that there is a contribution from the Implementation of UKBM in the Semester Credit System to Improve Student Achievement at Adventist High School Doyo Baru.
Discussion The purpose of this discussion is to analyze, interpret and relate the findings of this study to the relevant theory and the findings of previous studies.
The results of data analysis and hypothesis testing showed that the independent variable (UKBM Implementation in the Semester Credit Syste.
was significantly correlated with the dependent variable (Student Learning Achievemen.
The correlation coefficient of the dependent variable (Student Learning Achievemen.
with the independent variable, namely, the Implementation of UKBM in the Semester Credit System is 0.
In addition, the results of multiple regression analysis are known to have an R of 0.
To determine the strength of the correlation can be seen from the size of the correlation.
According to Young .
2: .
, the correlation measure is stated as follows:
70 to 1.
oth plus and minu.
indicates a high degree of correlation.
40 to < 0.
oth plus and minu.
indicates a substantial level of relationship.
20 s.
< 0.
oth plus and minu.
indicates a low level of relationship.
< 0.
oth plus and minu.
indicates no relationship .
This shows that the correlation of the independent variable (UKBM Implementation in Semester Credit Syste.
with the dependent variable (Student Learning Achievemen.
is substantial.
A positive number .
indicates a positive relationship between the independent variable (UKBM Implementation in the Semester Credit Syste.
and the dependent variable (Student Learning Achievemen.
, this means that if the independent variable is increased, the dependent variable will also increase, as well as if the independent variable is increased, the dependent variable will also increase.
If the Copyright A 2022 IJECS International Journal Education and Computer Studies (IJECS), 2 .
2022, 1-9 The Implementation of Independent Learning Activity Units in the Semester Credit System Improves Learning Achievement independent variable is decreased, the dependent variable will also decrease.
Likewise, the value of R Square (R.
or the adjusted coefficient of determination is 0.
This value means that the influence of the independent variable (UKBM Implementation in the Semester Credit Syste.
with the dependent variable (Student Learning Achievemen.
and the remaining 53.
10% are variables that affect Student Learning Achievement and were not examined in this study.
Based on the description above, it can be concluded that the implementation of UKBM in the Semester Credit System is very important in predicting Student Achievement.
The Relationship of the Implementation of UKBM in the Semester Credit System to the Learning Achievement of Students The analysis of the results of the study showed that there was a significant relationship between the implementation of UKBM in the Semester Credit System and Student Achievement, which was 0.
469 with a significance of 0.
This finding shows that the implementation of UKBM in the Semester Credit System Improves Student Achievement in Doyo Baru Adventist High School.
The Contribution of UKBM Implementation in the Semester Credit System to Students' Learning Achievements The amount of contribution given by the implementation of UKBM in the Semester Credit System to Improve Student Achievement in this study was 0.
This shows that the large contribution made by the Implementation of Independent Learning Activity Units in the Semester Credit System Improves Student Achievement in Doyo Baru Adventist High School by 46.
One variable UKBM implementation in the Semester Credit System has contributed almost 50% to learning achievement.
Conclusion Based on the results of the Bivariate correlation, it was obtained that r = 0.
685 was significant at the 5% significance This shows that the correlation relationship is positive, this is indicated by the regression line equation, which is equal to = 75.
087X, which confirms that the learning achievement of students has a unidirectional relationship 042 0.
087 (The Implementation of UKBM in the Semester Credit Syste.
This shows that if the implementation of UKBM in the Semester Credit System is increased or increased, the learning achievement of students will increase, and vice versa.
From the results of a simple linear regression analysis that has been done, the correlation coefficient (R) The coefficient of determination (R.
469 or 46.
Based on the magnitude of the correlation, it can be concluded that the independent variable (UKBM Implementation in the Semester Credit Syste.
can be used to predict or explain the dependent variable (Student Learning Achievemen.
This shows that there is a large contribution from the independent variable learning activity unit (UKBM Implementation in the Semester Credit Syste.
to the dependent variable (Student Learning Achievemen.
in Doyo Baru Adventist High School which is 46.
Calculation through the formula SUKBM (Contribution of Independent Learning Activity Uni.
= r x beta x 100%, also obtained the same value of UKBM contribution, which is 46.
That is, there are 9% of Student Achievement variables influenced by the Implementation of Independent Learning Activity Units in the Semester Credit System.
This means that there are 53.
1% of other factors that affect student achievement were not examined in this study.
References