The Effect of Evaluating Student Learning Outcomes on National

Exam Scores with Final School Exams as an

Intervening Variable

Alia Lestari, Riswan

Institut Agama Islam Negeri Palopo, Sulawesi Selatan,Indonesia

Keywords: Daily Test, Evaluation, Final School Exam, National Examination, Midterm Test, Path Analysis, Task.

Abstract: The purpose of this study was to examine the relationship between evaluating student learning outcomes

conducted by teachers in State High Schools in Palopo City and National Examinations held by the

government nationally. The study also aims to determine whether the final school exam mediates the

relationship between the evaluation of learning outcomes and national examinations. The data used in this

study were obtained from the documentation of the State High School in Kota Palopo in the 2016/2017

academic year consisting of 6 (six) schools with a total of 1,631 students. Sampling is done by using the

Probability Sampling Stratified Random Sampling technique. The sample used was 321 students. Data is

processed using Path analysis techniques. The results of this study indicate that the evaluation of student

learning outcomes consisting of tasks, daily tests, midterm tests and final school exams affect the score of

national exams directly and simultaneously, but not all evaluation outcomes of learning outcomes partially

affect the score of national examinations. while the relationship between evaluating student learning

outcomes is not all mediated by the Final School Exam.

1 INTRODUCTION

Palopo City, one of the cities in the province of

South Sulawesi, continues to strive to improve the

quality of education. Morris Kline in

LisnawatiSimanjuntak stated that "the ups and

downs of countries today depend on progress in the

field of mathematics" (LisnawatiSimanjuntak,

1993). But this year, the average score of the

national examination (UN) level of South Sulawesi's

academic year 2017 decreased from the previous

year. This was acknowledged by the South Sulawesi

Education Office, IrmanYasinLimpo, Thursday

(Rakyatku, 2017).In 2014, the national examination

average for high school in Palopo City was ranked

the 4th highest in South Sulawesi Province, while

this year, Palopo city was not included in the top 5

list. The decline in the average national exam scores

of high school students is certainly something that

needs to be studied more deeply, given that national

exams are one indicator of the success of the

teaching and learning process.

In the teaching and learning process, especially

in the evaluation of learning outcomes, both those

carried out by the teacher in the form of daily

assignments and tasks, carried out by schools such

as Midterm Test (UTS) and Final School Exam

(UAS) and those conducted by the government in

the form of National Examinations through several

stages. The stages of evaluation with one another

correlate and form a causal relationship that has a

pattern of direct or indirect relationships.

Based on the observations, the scores of the

national exam is determined by several variables

such as: Tasks, Daily Tests, and Final School Exam.

These variables form the structure of relationships

between variables. The relationship between these

variables is a correlation and regression relationship

in the form of direct or indirect relationships.

Evaluation of learning outcomes is carried out

continuously to monitor the process, progress and

improvement of results in the form of Tasks, Daily

Tests, Midterm Tests, Final School Exams, and

National Exams. Assignments are given to students

at the end of the learning meeting. Daily tests can be

done if you have completed one or several indicators

or one basic competency, while the final school

exam is done after completing some basic semester

competencies in question. National exams are

carried out nationally at the level of elementary and

secondary education at the end of the school year to

Lestari, A. and Riswan, .

The Effect of Evaluating Student Learning Outcomes on National Exam Scores with Final School Exams as an Intervening Variable.

DOI: 10.5220/0008524004790486

In Proceedings of the International Conference on Mathematics and Islam (ICMIs 2018), pages 479-486

ISBN: 978-989-758-407-7

479

find out the extent of students' ability to handle all

the material that has been learned.

The research conducted by IkhsanJailani stated

that there was no significant positive relationship

between semester national exams and national

examinations (Jailani, 2015), while according to

FitriYunita in her research results stated that there

was a significant correlation between final school

exam scores and national examinations(Yunita,

2014). The results of the research by Siti Harlian

have a very strong positive correlation between the

formative test scores and the semester exam scores

(harlian, 2013).Formative tests in school experience

are equated with daily tests because formative tests

are carried out at the end of each. material.

According to FadliHidayat, PujiNugraheni, and

Budiyono in the results of their research stated there

was a positive and significant relationship between

UTS with UAS(Hidayat, Nugraheni, & Budiyono,

2013). Based on several studies above, it can be

concluded that daily tests affect the midterm exam.

The final school exam also influences the national

exam. Whereas the midterm exam does not

influence national exams. But the midterm exam

influences the final school exam.

This study will examine the contribution of

evaluation of learning outcomes conducted in

Palopo City Senior High Schools in the form of

assignments, daily tests, midterm tests on the

national exam scores directly, and through Final

School Exams as intervening variable.

2 RESEARCH METHODS

This type of research is ex post facto research with

descriptive quantitative approach. Student value data

was taken from 6 schools in Palopo District, 312

students from 1,631 students. Sampling was done by

Probability Sampling technique in the Proportionate

Stratified Random Sampling type in 6 schools,

namely SMA 1 Palopo, SMA Negeri 2 Palopo, SMA

Negeri 3 Palopo, SMA Negeri 4 Palopo, SMA

Negeri 5 Palopo, and SMA Negeri 6 Palopo. The

data obtained will be analyzed using Path Analysis.

In the structural equation model, this study has

exogenous variables, endogenous variables, and

intervening variables. Exogenous variables are

variables that are not influenced by previous

variables (antecedents), while endogenous variables

are variables that are influenced by previous

variables. Exogenous variables in this study are

evaluation of student learning outcomes and their

endogenous variables are national examinations.

There is one variable that has an antecedent variable

(previous variable) and consequent variable

(variable afterward) in the equation model, namely

the final school exam which is then referred to as the

intervening variable. The steps to test path analysis

(Path Analysis) 1. Determine the paradigm of

relationships between variables; 2. make a path

diagram model; 3. determine the path coefficient and

the structure equation (Subana, Rahadi, & Sudrajat,

2000).

Figure 1: Structural Relationships Variable X

, X

and

Y to Z

▪ Hypothesis Model 1:

Tasks, daily tests and midterm replications

directly influence the school final exam

Sub-Structure 1:

Y =

▪ Hypothesis Model 2:

Task, daily test, midtermtestand final school

exam have a direct effect on national examination

Sub-Structure 2:

Y =

▪ Hypothesis Model 3:

Task, daily tests and midterm replications have a

total effect on national exams through final school

exams.

Sub-Structure 3:

Y =

3 RESULTS AND DISCUSSION

3.1 Descriptive Statistics

The results of the descriptive statistics with SPSS 22

program are obtained as follows;

Table 1: Descriptive Statistics

UTS

Tgs

Vali

d N

(list

wise

)

321

Range

82.50

74.00

35.00

38.00

31.00

Min.

12.50

24.00

65.00

60.00

67.00

Max

95.00

98.00

100.00

98.00

Mean

455.2

841.5

829.01

834.2

851.4

ICMIs 2018 - International Conference on Mathematics and Islam

480

Std.

Deviatio

1509.

653.6

542.31

604.6

507.5

Variance

22.78

42.72

2.941

3.656

25.7

Skewnes

.341

-2.402

.436

-.588

-.369

Kurtosis

-.159

22.627

.790

1.378

1.230

3.2 Analysis Requirements

Testing with ANOVA statistics requires that the

analyzed data come from the population with normal

distribution and the variance between sample groups

must be homogeneous. For this reason, normality

and homogeneity tests were carried out. Normality

test uses the Lilliefors test, while homogeneity uses

the Bartlett test.

3.2.1 Normality Test

The results of the normality test with SPSS 22

program are obtained as follows;

Table 2: Data Normality Test

Tgs

UTS

UAS

321

Normal

Parameter

s, b

Mean

85.14

83.43

82.9

84.34

44.73

Std.

Deviation

5.076

6.046

5.43

6.493

14.81

Most

Extreme

Differenc

Absolute

.087

.108

.097

.118

.077

Positive

.063

.052

.097

.092

.077

Negative

-.087

-.108

-.087

-.118

-.048

Test

.087

.108

.097

.118

Asymp. Sig. (2-tailed)

.000c

Ho: Data normally distributed

Ha: Data not normally distributed

Basic decision making is based on probability. If

the probability value> 0.05 then Ho is accepted

If the probability value is 0.05 then Ho

rejected

Kolmogorov-Smirnov results above, the task is

0.087 which means> 0.05 then the data is normally

distributed. Daily Test Rate is 0.108 which means>

0.05, the data is normally distributed. Midterm test

(UTS) is 0.097 which means > 0.05, the data is

normally distributed. The Final School Exam Value

is 0.118 which means> 0.05, the data is normally

distributed. National Examination Value is 0.77

which means> 0.05, the data is normally distributed.

So that the sample data coming from the population

are normally distributed.

3.2.2 Linearity Test

Test aims to determine whether two variables have a

significant linear relationship or not. Linearity test

results obtained in the following tables;

Table 3: Summary of results of Linearity Test

Effect of Variables

Sig. Value

Ket.

Tgs (X1) to UAS (Y)

0,945Test

Linear

UH(X2) to UAS (Y)

0,001

Not

linear

UTS (X3) to UAS (Y)

0,595

Linear

UAS (Y) to UN (Z)

0.063

Linear

Tgs (X1) against UN (Z)

0.001

Not

linear

UH (X2) against UN (Z)

0.001

Not

linear

UTS (X3) against UN

(Z)

0.079

Linear

It can be concluded that Tasks and UTS have a

linear relationship with UAS. In addition, UTS also

has a linear relationship with the UN. While Daily

test does not have a linear relationship with the

(UAS) and National Examination. Likewise, Daily

Tests with the UN do not have a linear relationship.

so that it is tested to find the right model.

3.2.3 Model Test

Testing aims to determine the right model used to

analyze research data. The test results of the table

model above show that the right model is a quadratic

model with the highest R-square value with a

contribution of 26.0%.

Based on the test results of the models of the

three relations of the three variables in Table 4 it can

be concluded that the right model used is a quadratic

model non-linear regression.

3.2.4 Quadratic

Test A quadratic test is a non-linear regression

which aims to determine the relationship between

the dependent variable (Y) and the independent

variable (X) so that a curve that forms an ascending

curved line (β2> 0) or decreases (β2 <0) will be

obtained (Yusnandar, 2004). So that nonlinear data

will be tested for non-linear quadratic models as in

Table 5.

The Effect of Evaluating Student Learning Outcomes on National Exam Scores with Final School Exams as an Intervening Variable

481

Table 4: Summary of Model Test Results

Variable

R Square

tests used were

Linear

Logarithmic

Inverse

Quadratic

Cubic

Compound

UH-

UAS

0.061

6.1%

0.061

6.1%

0.059

5.9%

0.062

6.2%

0.061

6.1%

0.028

2.8%

Quadratic

6.2%

Tgs-

0.215

21.5%

0.208

20.8 %

0.198

19.8%

0.232

23.2%

0.230

3.0%

0.229

22.9%

Quadratic

23.2%

UH- UN

0.237

23.7%

0.225

22.5%

0.210

21.0%

0.260

26.0%

0.258

5.8%

0.256

25.6%

Quadratic

26.0%

Table 5: Summary of Quadratic Test Results

Influence

variables

Value

path

coeffic

ients

Sig.

Value

Remark

UH (X2)

to UN (Z)

Height

0.227

0.001

Influence

Low

0.180

0.064

No effect

Tgs (x1)

on UN (Z)

Height

0.465

0.000

Influence

Low

0.085

0.384

No effect

UH (X2)

on UN (Z)

Height

0.421

0.000

Influence

Low

0.146

0.134

No effect

3.2.5 Multicollinearity Test

Multicollinearity

Aims to test whether the regression model found

correlation between independent variables. A good

regression model should not have a correlation

between the independent variables (not

multicollinearity). Based on the results of the data

processing by the SPSS Version.22 Program it is

known that the tolerance value of the Tgs(X1), UH

(X2), UTS (X3) successive variables is 0.369; 0.382

and 0.666 greater than 0.10. Meanwhile, the VIF

values of Tgs (X1), UH (X2), UTS (X3) variables

were 2.710, 2.616 and 1.501 respectively, which

means less than 10.00. So, it can be concluded that

there is no Multicollinearity.

Based on Table 6 output is known that the value

of the variable tolerance Instructions (X1), UH (X2),

UTS (X3) and UAS (Y) in a row of 0.359; 0,382;

0.653 and 0.886 greater than 0.10. Meanwhile, the

VIF values of the Tgs (X1), UH (X2), UTS (X3) and

UAS (Y) variables were 2.783; 2,617; 1,526 and

1,129 which means less than 10.00. So, it can be

concluded that there is no multicollinearity.

Table 6: Multicollinearity Test Results of Task

Value Data, UH, UTS, and UAS against UN

Model

Unstandardized

Coefficients

Standardized

Coefficients

Sig.

Std.

Error

Beta

Tgs Value

.459

.234

.157

1.961

.051

UH Value

.704

.190

.288

3.697

.000

UTS

.330

.162

.121

2.033

.043

US value

.116

.051

.996

.320

3.3 Research Hypothesis Test through

Path Analysis

3.3.1 Section Titles

To determine the path coefficients in this one sub-

structure, the researcher previously showed Figure 6

which is a picture of Sub-Structure one, taken from

Figure 5. Sub Structure one is the direct relationship

between Task and Daily Test with Midterm Test

(UTS).

Figure 2: Sub Structure One direct relationship Tgs, UH,

and UTS with UAS

● Test Overall

Hypothesis Testing Hypothesis

Testing Data test as a whole as follows:

ICMIs 2018 - International Conference on Mathematics and Islam

482

Table 7: Summary Model

R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

R Square

Change

df1

df2

Sig. F

Change

0.114

0.106

6.141

0.114

13.59

317

.000

Ho: Tgs, UH, UTS no direct influence UAS.

Ha: Tgs, UH, UTS directly influence UAS.

The Table 7 above shows the calculated F value

of 13.590 with a probability value (sig) = 0.000.

Because the sig value is 0.000 <0.05, then Ho is

rejected, Task, Daily Test, UTS influences UAS.

Therefore, individual testing can be carried out or

continued.

● Hypothesis Testing Individually

The results of individual hypothesis testing are

shown in the table as follows:

Table 8: Tgs, UH, and UTS Regression Coefficients

on UAS

Model

Unstandardized

Coefficients

Standardized

Coefficients

Sig.

Std.

Error

Beta

44,396

6,275

7,076

.000

(Constant)

Tgs

.111 .254

.324

2.913

.004

-.032

.092

-.030

-.345

.730

UTS

.078 .151

.180

2.328

.021

Ho:Tgs do not have a direct effect on the UAS

Ha:Tgs have a direct effect on UAS;

The table above obtained a beta value of 0.254

and a sig value of 0.004 <0.05, so Ho was rejected,

meaning that the task had a direct effect on the UAS

Ho: UH had no direct effect on the UAS.

Ha: UH has a direct effect on UAS.

From Table 8, the beta value is -0.030 and the

sig value is 0.730 <0.05, so Ho is accepted. This

means that Deuteronomy does not have a direct

effect on UAS

Ho: UTS does not have a direct effect on UAS

Ha: UTS has a direct effect on UAS.

From Table 8 above, the beta value is 0.151 and

the sig value is 0.021 <0.05, Ho is rejected. This

means that UTS has a direct effect on UAS.

So, it can be concluded that the task has a direct

effect on the UAS value. While Daily test does not

directly affect the value of UAS and UTS directly

affects UAS.

a. Hypothesis Testing Sub Two Structure

To determine the path coefficients in these two

previous sub-structures the researcher shows Figure

3 which is part of Figure 1 Sub Structure two is a

direct relationship between Tgs, UH, UTS and UAS.

Figure 3: Sub Structure of two direct relationships

Task, Daily Test, UTS, and UAS with UN

Test Overall Hypothesis Testing The results of

the overall data test are as follows:

Table 9:Summary Model

R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

R Square

Change

df1

df2

Sig. F

Change

.269

.260

12.737

.269

29.04

316

.000

Ho:Tgs, UH, UTS and UAS do not directly affect

the UN

Ha:Tgs, UH, UTS and UAS directly influence the

From the Table 9, the calculated F value is

29.039 with a probability value (sig) = 0.000.

Because the sig value is 0.000 <0.05, Ho is rejected.

This means that Task, Daily Tests, UTS, and UAS

affect the National Examination. Therefore,

individual testing can be carried out or continued.

• Hypothesis Testing Individually Tests

Based on the results of the linearity test shows

that Daily Task and do not have a linear relationship

so there is no individual hypothesis testing, while the

UTS and UAS have linear relationships then the

individual hypotheses will be tested as shown in the

table as follows:

Table 10: UTS regression coefficient of the UN

Model

unstandardize

d Coefficients

Standar

dized

Coeffic

ients

Sig.

Std.

Error

Beta

(Constant)

-40

163

11 768

-3

413

.001

UTS Value

1.02

.142

.375

722

.000

The Effect of Evaluating Student Learning Outcomes on National Exam Scores with Final School Exams as an Intervening Variable

483

Ho: UTS has no direct influence on the UN

Ha: UTS direct impact on the UN

From Table 10, the beta value is 0.375 and the

sig value is 0.000 <0.05 so Ho is rejected. This

means that UTS directly affects the National

Examination.

From Table 11, the beta value is 0.205 and the

sig value is 0.000 <0.05, so Ho is rejected. This

means that UAS directly affects the National

Examination. So that it can be concluded that Task,

Daily Test, UTS and UAS directly influence the

National Examination.

Table 11: The regression coefficients of UAS to UN

Model

Unstandardiz

Coefficients

Standardized

Coefficients

Sig.

Std.

Erro

Beta

(Constant)

5.335

0.56

.505

.614

UAS

value

.467

.125

.205

3.73

000

Ho: UAS does not directly affect the National

Examination.

Ha: UAS directly affects the National

Examination.

3.3.2 Direct and indirect

Influences As for the direct and indirect influences

of Tasks, Daily Tests, UTS, and UAS on the

National Examination are as follows:

Figure 4: New diagram changes from the path

diagram hypothesized

Table 12: Summary of the path coefficients Effect of

Direct, indirect and total

Influence

variables

Influence of Causal

Direct

Indirect (via

Total

X1 THP Y

0.254

X1t THP z

0.465

0.052

0.517

X2t THP Y

0.227

X2t THP z

0.421

0.046

0.467

X3 THP Y

0.151

X3 THP Z

0.375

0.030

0.715

The results of the above table, it can be seen that

the direct effect of UTS on UAS by 0.375 and

indirect influences of 0.030, which means that the

direct effect is greater than the indirect effect, the

results show that it directly has a significant

influence on the National Examination.

3.4 Discussion of Research Results

3.4.1 The Influence of Tasks, Daily Tests,

Middle test on School Final Exams

The Results of this study are not in accordance with

the expectations of researchers who consider the

value of Tasks, Daily Tests, Midterm test

Examination to influence the National Examination.

Previously, researchers had tested the normality of

the sample data and obtained normal distribution

data. Some of the three evaluations have no effect on

the Final School Exam or on the National

Examination, after being tested on the linearity test.

The results in the field indicate that Daily test has no

direct effect on the Final School Exam.

Task and Midterm test have a linear relationship

to the Final School Exam. Next hypothesis testing.

Hypothesis testing shows a beta value of 0.254 with

a significant value of 0.000 <0.05 for the task

towards the final School Exam so that the Ho

hypothesis is accepted. This means that the task

directly influences the Final School Exam. Whereas

the Midterm test towards the Final School Exam

obtained a beta value of 0.151 with a significant

value of 0.021 <0.05 so that Ho accepted. This

means that Midterm test directly affects the Final

School Exam.

The results of this study, in line with previous

research, especially on the evaluation of Midterm

test on the Final School Exam by FadliHidayat,

Budiyono, PujiNugraheni stated that there was a

positive and significant relationship between the

Midterm test and the Final Examination for School

Mathematics subjects(Jailani, 2015). Likewise, the

results of research by the researchers stated that

there was a linear relationship between Midterm test

and the Final School Exam. However, what is

ICMIs 2018 - International Conference on Mathematics and Islam

484

different from the research of researchers is that it

does not only show the relationship between

Midterm test and the Final Examination of the

School, but shows the relationship between Tasks,

Daily Tests, and Midterm test towards the Final

School Exam. So, this study is a research that shows

whether there is an influence of Tasks, Daily Tests

and Midterm test on the Final School Exam.

Previous research was only on the relationship

between Midterm test and the Final School Exam.

3.4.2 The Influence of Task, Daily Tests,

Middle test on National Exams

The results of this study indicate that Daily Test and

Deuteronomy does not affect the National

Examination. These results are based on a linearity

test that Deuteronomy Daily Tasks and not a linear

relationship, so it is not continuous right on

hypothesis testing. However, after testing the model,

the exact model used was a quadratic model, so that

after the quadratic test it was obtained that a high

Daily Task and Deuteronomy had an effect on the

National Examination.

This study is different from the previous research

conducted by IkhsanJalali on mathematics subjects

in Muhammadiyah I SMP Banda Aceh in

2013/2014, that there was no significant positive

relationship between midterm exams and national

exams(Jailani, 2015). Whereas the results of the

research conducted by the researchers, that UTS has

a direct influence on the national exam in the high

school of Palopo city. So that in the city of Palopo

especially the high school level needs to be

implemented against UTS because it influences the

National Examination.

3.4.3 The Influence of Tasks, Daily Tests,

Middle test, and School Exams on

National Exams through School Final

Exams as intervening variables

The results of the study show that school exams

affect national exams. This is based on linearity test

that there is a linear relationship of UAS variables to

the UN variable. In addition to the hypothesis test

obtained a beta value of 0.375 with a significant

value of 0.000 <0.05 so that the Ho hypothesis is

accepted, meaning that the Final Examination of the

School directly affects the National Examination.

This results in the indirect influence of Tasks, Daily

Tests, Mid-Semester Exams, and school

Examinations on National Exams through the Final

School Exam as intervening variables.

The results are consistent with research

conducted by Fitri Yunita against-IA class XII

student of SMAN 8 Banda Aceh, that there is corella

significant action between the school final exam

scores of National Exam (yunita, 2014). Based on

the results in table 4.13. the summary model shows

that the R square task, daily tests, midterm test, and

final school exam influence simultaneously that

directly affects the National Examination at 0.285.

This means that the contribution of Tasks, Daily

Tests, Middle test, and final School Exam have a

simultaneous effect which directly affects the

National Examination is 26.9%, while the rest is

influenced by other factors that cannot be explained

in this study.

4 CONCLUSIONS

Based on the results and discussion with path

analysis, we can conclude that the evaluation of

student learning outcomes consisting of tasks, daily

tests, midterm tests and final school exams affect the

score of national exams directly and simultaneously,

but not all evaluation outcomes of learning partially

affect the score of national examinations. while the

relationship between evaluating student learning

outcomes is not all mediated by the final school

exam. The contribution of evaluating student

learning outcomes which is only 26.9% indicates

that the evaluation of learning outcomes conducted

by teachers and schools has not fully supported

students to obtain the expected national exam scores.

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Skripsi Fakultas.

Yusnandar, M. E. (2004). Aplikasi Analisis Regresi Non-

Linear Model Kuadratik Terhadap Produksi Susu

Kambing Peranakan Etawah ( Pe ) Selama 90 Hari

Pertama Laktasi. Informatika Pertanian, 13(Desember

2004), 735–743.

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