JRSSEM 2022, Vol. 01, No. 10, 1791 – 1803
E-ISSN: 2807 - 6311, P-ISSN: 2807 - 6494
DOI : 10.36418/jrssem.v1i10.185 https://jrssem.publikasiindonesia.id/index.php/jrssem/index
SELF-REGULATED LEARNING AS MEDIATOR ON THE
DETERMINANTS OF MATHEMATICS ACHIEVEMENT IN
JUNIOR HIGH SCHOOL STUDENTS IN THE CITY OF DKI
JAKARTA PUSAT
Evi Syafrida Nasution
1*
Asmadi Alsa
2
Erdina Indrawati
3
1,2,3
Universitas Persada Indonesia YAI
e-mail: evi.syafrida@upi-yai.ac.id
1
,
asmalsa@ugm.ac.id
2
, erdina.indrawati@yahoo.com
3
*Correspondence: evi.syafrida@upi-yai.ac.id
Submitted: 27 April 2022, Revised: 15 May 2022, Accepted: 20 May 2022
Abstract. The purpose of this study was to determine the effect of parental support, attitudes
towards mathematics, and mastery goal orientation on mathematics learning achievement with
self-regulated learning as a mediator. The research method that the researcher uses is a structural
model with a total of 327 respondents who were taken using cluster random sampling technique.
The data analysis technique used in this research is SEM AMOS. Based on the results of the model
test, it is known that the influence of parental support, attitudes towards mathematics, and the
orientation of mastery goals on mathematics learning achievement with self-regulated learning as
a mediator, according to empirical data. Based on the results of statistical tests, it is known that
parental support, attitudes towards mathematics lessons, and orientation of mastery goals have no
effect on learning achievement in mathematics with self-regulated learning as a mediator.
Keywords: parental support; mastery goal orientation; self-regulated learning; math achievement.
Evi Syafrida Nasution, Asmadi Alsa,
Erdina Indrawati
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DOI : 10.36418/jrssem.v1i10.185 https://jrssem.publikasiindonesia.id/index.php/jrssem/index
INTRODUCTION
One of the subjects that are considered
important in formal education in Indonesia
and are given from elementary school to
high school is mathematics. The
achievement of the objectives of learning
mathematics at the junior high school level
is very important in the learning process.
This is as stated in the attachment of the
Minister of Education and Culture Number
58 of 2014 concerning the SMP curriculum,
it is explained that the objectives of
students to study mathematics are: a.
Understanding mathematical concepts is
competence in explaining the relationship
between concepts and using concepts and
algorithms flexibly, accurately, efficiently,
and precisely in problem-solving. b.
Communicating ideas, reasoning, and
being able to compile mathematical proofs
by using complete sentences, symbols,
tables, diagrams, or other media to clarify
situations or problems. c. Have an attitude
of appreciating the usefulness of
mathematics in life, namely having
curiosity, attention, and interest in learning
mathematics, as well as a tenacious and
confident attitude in problem-solving. d.
Using simple Praga tools and technology
results to carry out mathematical activities.
These skills or abilities are closely related,
one strengthening and needing the other.
Mathematical ability can be seen in a
person's ability to calculate, measure, and
solve mathematical things. Various
components of mathematical ability are
logical thinking, problem-solving,
sharpness in seeing patterns, quantitative
concept recognition, and time and causal
relationships. In some countries,
performance in mathematics continues to
be a problem, for example, Philippines
(Alpacion, Camañan, Gregorio, Panlaan, &
Tudy, 2014), Portugal (Mata, Monteiro, &
Peixoto, 2012), Tanzania (Mazana, Suero
Montero, & Olifage, 2019), Malaysia (Ayob
& Yasin, 2017), Kenya (Langat, 2015). In
Indonesia, student performance in
mathematics has also not shown optimal
results (Argina, Mitra, Ijabah, & Setiawan,
2017)
The initial data collection was carried
out on the achievement of students who
took the national exam in Indonesia by the
Education Assessment Center, there were
four subjects tested Indonesian, English,
Mathematics, and Science. Specifically for
mathematics, it can be seen that in the last
five years (2015 – 2019) public and private
education units showed average scores
that were below other subjects (Indonesian,
English, and science). The average score for
each subject is 50. In Table 1. it can be seen
that in 2015, the average score obtained by
students for mathematics was 56.4; in 2016
the average score was 49.84; in 2017 the
average score was 50.34; 2018 average
score is 44.05, and in 2019 the average
score was 46.56. Based on this data, it can
be seen that the mastery of mathematics
material is still not optimal.
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in Junior High School Students in the City of DKI Jakarta Pusat
DOI : 10.36418/jrssem.v1i10.185 https://jrssem.publikasiindonesia.id/index.php/jrssem/index
Figure 1. Results of the National Examination for Public & Private Education Units
One of the benchmarks for high and
low student learning outcomes in a country
is student achievement in the International
Student Assessment Program (PISA) in
mathematics organized by the
Organization for Economic Co-operation
Development (OECD). PISA aims to
measure how well students can apply the
knowledge and skills they are likely to have
learned in school in the types of situations
they are likely to encounter after school.
PISA measures the knowledge and abilities
of 15-year-olds. The main concepts for the
PISA assessment are reading, science, and
math: how well students can apply the
knowledge and skills they have learned in
school to real-life challenges (Stacey, 2010).
The achievements of Indonesian students
who took part in this competition in 2015
only ranked 63 out of 70 participants with
an average score of 386, which is below the
international average score of 490 (OECD,
2018).
Meanwhile, the results of the Trends
International Mathematics and Science
Study (TIMSS) survey in 2011, Indonesia
was ranked 38 out of 42 countries, and
provinces in Indonesia were far behind
compared to other ASEAN countries such
as Singapore, Thailand, and Malaysia
(Kusumaningrum & Alsa, 2016). The TIMSS
test is based on a careful analysis of the
expected curriculum in the participating
countries at the specified grade level. This
test is designed to assess performance as
fairly as possible on items that reflect the
core of the curriculum (Stacey, 2010).
Currently, in Indonesia learning
mathematics using the 2013 curriculum
follows the standard curriculum used by
TIMSS.
Although on average, the results of the
PISA and TIMSS studies show that students'
mathematical abilities in Indonesia are still
low, some of them have high abilities. This
can be seen from the achievements of
Indonesian students who won many
medals including gold medals at the India
International Mathematical Competition
(InIMC) in June 2017 (Fenanlampir,
Batlolona, & Imelda, 2019). This shows that
the ability of participants in mastering
mathematics is different.
Attitudes towards mathematics are
0
10
20
30
40
50
60
2015 2016 2017 2018 2019
Public & Private Education Unit National Examination
Series 1
Evi Syafrida Nasution, Asmadi Alsa,
Erdina Indrawati
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directly positively and significantly
correlated with student performance
(Alpacion et al., 2014). This is supported by
the results of research conducted by
(Ngussa & Mbuti, 2017) on high school
students in Arusha, Tanzania, who found
that students' positive attitudes can
improve students' performance in
mathematics. (Alpacion et al., 2014)
suggests that performance in Mathematics
can be improved by developing a positive
attitude towards the subject.
When students are involved in
mathematical activity, they will
continuously evaluate their learning
situation to keep them in line with their
personal goals (Hannula, 2002). The
process to activate and regulate thoughts,
behavior, and emotions in achieving a goal
is called self-regulation. When these goals
are related to learning, then the self-
regulation in question is self-regulation in
learning (self-regulated learning) (Mokhtar,
Tarmizi, Ayub, & Nawawi, 2013). The results
of research conducted by (Siregar, Solfitri,
& Siregar, 2021) found that students'
attitudes towards mathematics towards
self-regulation in learning have a
significant correlation with a contribution
of 58%.
Self-regulatory learning is seen as a
combination of skill and will. Skills refer to
the use of cognitive and metacognitive
strategies that include goal setting,
planning and organizing learning, self-
monitoring, self-evaluation, time
management, and resources. Meanwhile,
desire refers to an individual's motivational
orientation in terms of goals, values, and
expectations.
Previous research supports the
importance of self-regulation on academic
achievement. As has been pointed out by
Pintrich, Roeser, and De Groot, 1994; Chen,
2002. Students with high achievement use
more self-regulated learning strategies
than students with low achievement. In
addition, (Febrianela, 2013), of which
concluded that students who have high
self-regulation learning are followed by
high academic achievement.
Students' mathematical problem-
solving abilities are also influenced by
mastery goal orientation. The results of
experimental research conducted by
(Suwono, Pratiwi, Susanto, & Susilo, 2017)
provide treatment in the form of learning
using the mastery goal orientation learning
model. In this study, there are two groups
of classes, namely experimental and
control. In the experimental class,
treatment is given in the form of learning
by using the mastery goal orientation
learning model where mastery of learning
is the main point, and learning in the
control class is carried out conventionally
using lecture, question, and answer
methods, and giving assignments. Based
on the research data, it was found that the
average mathematical problem-solving
ability of students in learning using the
mastery goal orientation learning model
has increased compared to the control
group.
Therefore, variations in the level of
learning based on students' self-regulation
indicate a difference in the conditions of
motivation and strategies used by students
in completing their academic assignments.
In addition, the availability of a supportive
environment and precisely the actions
taken will bring a strong impetus to
1795 | Self-Regulated Learning as Mediator on the Determinants of Mathematics Achievement
in Junior High School Students in the City of DKI Jakarta Pusat
individuals in achieving their learning goals.
According to Schunk (2012), the creation of
a supportive environment will help
students maximize their learning activities.
Learning based on self-regulation can
also be taught and supported by parents
through modeling, encouraging,
facilitating, rewarding goal setting, using
good strategies, and other processes.
(Martine-Pons, 2002 in Latipah, 2010).
Students who get social support will be
able to reduce the pressure and anxiety felt
by students when students are cognitively
difficult to learn something or avoid
academic assignments. The role of the
environment is a source of support to meet
students' needs for anxiety and fear that
involve students emotionally
(Kusumaningrum & Alsa, 2016).
The results of research conducted by
(Solichin, Muchlis, & Ferdiant, 2021) found
that there was a significant influence
between learning based on self-regulation
and parental support on student learning
outcomes in economics subjects in the
Social Sciences study program at SMA
Negeri in Jombang. In addition, Martinez-
Pons, 2009 (Latipah, 2010) suggests that
parental involvement can improve learning
based on their children's self-regulation so
that academic achievement increases. The
existence of a combination of learning
based on self-regulation and social support
is expected to improve students'
mathematics learning outcomes.
METHODS
The approach that the researcher uses
in this research is a quantitative approach,
which is a research approach that uses
numerical data to explain phenomena and
answer research results. The research
model used in this study is a structural
model, namely a research model that wants
to know the direct and indirect effects of
one variable on other variables.
The subjects in this study were seventh-
grade students of State Junior High Schools
in Kemayoran District, Central Jakarta City,
DKI Jakarta Province. The sampling
technique used was Cluster Random
Sampling, with a total of 327 people. The
research instrument used to measure the
five variables in this study used a parental
support scale, an attitude scale towards
mathematics, a mastery goal orientation
scale, a self-regulated learning scale, and a
math test. The data analysis method used
Structural Equation Modeling (SEM) with
the SPSS-AMOS program.
RESULTS AND DISCUSSION
A. Confirmatory Analysis Results
The following are the results of the
confirmatory factor analysis of the
research variables:
1. Parental Support
Evi Syafrida Nasution, Asmadi Alsa,
Erdina Indrawati
| 1796
DOI : 10.36418/jrssem.v1i10.185 https://jrssem.publikasiindonesia.id/index.php/jrssem/index
Figure 2. CFA Results 5 Factors from Parental Support
The test of the 1 and order CFA
analysis for the parental support scale
in the final results displays indicators
with loading factor values above 0.5,
namely indicators represented by 12
items with variations in loading factor
values above 0.5. The suitability of
the variables in the 1 st Order CFA
test results can be seen from the
goodness of fit (GoF) value in the
table below:
Table 1. GoF Structural Model of Parental Support Scale
Source: Results of Data Processing with AMOS
The goodness of fit structural
model of parental support has met
the GoF standard, which means fit
(good) (Khuzaini & Santosa, 2016).
2. Attitude towards Mathematics
Lessons
Fit Index
Fit Criteria
Results
Conclusion
CHI-SQUARE
Expected small
156.088
Fit
RMSEA
0.08
0.068
Fit
GFI
0.90
0.954
Fit
AGFI
0.90
0.919
Fit
TLI
0.90
0.941
Fit
1797 | Self-Regulated Learning as Mediator on the Determinants of Mathematics Achievement
in Junior High School Students in the City of DKI Jakarta Pusat
DOI : 10.36418/jrssem.v1i10.185 https://jrssem.publikasiindonesia.id/index.php/jrssem/index
Figure 3. CFA Results 6 Factors of Attitude towards Mathematics Lessons
The test of the 1 st order CFA
analysis for the attitude scale towards
mathematics in the final results
displays indicators with loading
factor values above 0.5, namely
indicators that are
represented by 9 items with
variations in loading factor values
above 0.5. The suitability of the
variables in the results of the 1st
order CFA test can be seen from the
goodness of fit (GoF) value in the
table below:
Table 2. GoF Structural Model of Attitude Scale towards Mathematics Lessons
Source: Results of Data Processing with AMOS
The goodness of fit structural
model of attitudes towards
mathematics lessons that have met
the GoF standard value is defined as
fit (good) (Khuzaini & Santosa, 2016).
3. Mastery Goal Orientation
Fit Index
Fit Criteria
Results
Conclusion
CHI-SQUARE
Expected small
276,468
Fit
RMSEA
0.08
0.062
Fit
GFI
0.90
0.942
Fit
AGFI
0.90
0.912
Fit
TLI
0.90
0.927
Fit
Evi Syafrida Nasution, Asmadi Alsa,
Erdina Indrawati
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DOI : 10.36418/jrssem.v1i10.185 https://jrssem.publikasiindonesia.id/index.php/jrssem/index
Figure 4. Results of CFA 4 Factors from Mastery Goal Orientation
The test of the 1st order CFA
analysis for the mastery goal
orientation scale in the final results
displays indicators with loading
factor values above 0.5, namely
indicators represented by 10 items
with variations in loading factor
values above 0.5. The suitability of
the variables in the 1 st Order CFA
test results can be seen from the
goodness of fit (GoF) value in the
table below:
Table 3. GoF Structural Model of Mastery Goal Orientation Scale
Source: Results of Data Processing with AMOS
The goodness of fit structural
model of mastery goal orientation
has met the standard of GoF value
which means fit (good) (Khuzaini &
Santosa, 2016).
4. Self-Regulated Learning
Fit Index
Fit Criteria
Results
Conclusion
CHI-SQUARE
Expected small
106,995
Fit
RMSEA
0.08
0.070
Fit
GFI
0.90
0.963
Fit
AGFI
0.90
0.929
Fit
TLI
0.90
0.945
Fit
1799 | Self-Regulated Learning as Mediator on the Determinants of Mathematics Achievement
in Junior High School Students in the City of DKI Jakarta Pusat
DOI : 10.36418/jrssem.v1i10.185 https://jrssem.publikasiindonesia.id/index.php/jrssem/index
Figure 4. CFA Results 3 Factors from Self-Regulatory Based Learning
The test of the 2nd order CFA
analysis for learning based on self-
regulation in the final results displays
indicators with loading factor values
above 0.5, namely indicators
represented by 12 items with
variations in loading factor values
above 0.5. The metacognitive
dimension is represented by four
items, the motivation dimension is
represented by four items, and the
behavioral dimension is represented
by four items. The suitability of
variables in the results of the 2 and
Order CFA test can be seen from the
goodness of fit (GoF) value in the
table below:
Table 4. GoF Structural Model of Learning Scale Based on Self-Regulation
Source: Results of Data Processing with AMOS
The goodness of fit structural
model of mathematics learning
outcomes has met the GoF standard
value which is defined as fit (good)
(Khuzaini & Santosa, 2016).
5. Math Achievement
Fit Index
Fit Criteria
Results
Conclusion
CHI-SQUARE
Expected small
198,877
Fit
RMSEA
0.08
0.072
Fit
GFI
0.90
0.940
Fit
AGFI
0.90
0.908
Fit
TLI
0.90
0.920
Fit
Evi Syafrida Nasution, Asmadi Alsa,
Erdina Indrawati
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DOI : 10.36418/jrssem.v1i10.185 https://jrssem.publikasiindonesia.id/index.php/jrssem/index
Figure 5. Mathematics Achievement Test
CFA analysis for the mathematics
learning outcomes tests in the final
results displays indicators with
loading factor values above 0.5,
namely indicators represented by 4
items with variations in loading factor
values above 0.5. The algebraic
dimension is represented by 3 items
and the PLSV dimension is
represented by four items. The
suitability of variables in the results of
the 2 and Order CFA test can be seen
from the goodness of fit (GoF) value
in the table below:
Table 5. GoF Structural Model of Mathematics Achievement Test
Source: Results of Data Processing with AMOS
The goodness of fit structural
model of mathematics learning
outcomes has met the GoF standard,
which means fit (good) (Khuzaini &
Santosa, 2016).
B. Full Model Equation Estimation
Fit Index
Fit Criteria
Results
Conclusion
CHI-SQUARE
Expected small
28.089
Fit
RMSEA
0.08
0.046
Fit
GFI
0.90
0.986
Fit
AGFI
0.90
0.969
Fit
TLI
0.90
0.947
Fit
1801 | Self-Regulated Learning as Mediator on the Determinants of Mathematics Achievement
in Junior High School Students in the City of DKI Jakarta Pusat
DOI : 10.36418/jrssem.v1i10.185 https://jrssem.publikasiindonesia.id/index.php/jrssem/index
Figure 6. Structural Relationship Model
Based on the AMOS output above,
in Figure 7 above, this structural
equation model shows a chi-square
value of 278,965. Likewise with other
criteria values such as RMSEA, GFI,
AGFI, and TLI. RMSEA 0.067 0.08, GFI
0.936 0.90, AGFI 0.904 0.90, TLI 0.938
0.90, it can be concluded that all criteria
show fit.
The results show that parental
support has a positive and significant
effect on self-regulated learning,
parental support has no effect on math
achievement, and parental support has
no effect on math achievement with
self-regulated learning as a mediator.
Attitudes toward mathematics lessons
have a positive and significant effect on
self-regulated learning, attitudes
toward mathematics lessons have a
negative and significant effect on
mathematics achievement, and
attitudes toward mathematics lessons
have no effect on mathematics
achievement with self-regulated
learning as a mediator. Mastery goal
orientation has a positive and
significant effect on self-regulated
learning, mastery goal orientation has
no effect on math achievement, and
mastery goal orientation has no effect
on math achievement with self-
regulated learning as a mediator.
CONCLUSIONS
Based on the results of the research
and analysis above, it can be concluded
that parental support, attitudes towards
mathematics lessons, and mastery goal
orientation have a positive and significant
effect on self-regulated learning.
Meanwhile, parental support, attitudes
towards mathematics, and mastery goal
orientation do not affect mathematics
achievement. Parental support, attitudes
towards mathematics lessons, and mastery
goal orientation have no effect on
mathematics achievement with self-
regulated learning as a mediator.
Evi Syafrida Nasution, Asmadi Alsa,
Erdina Indrawati
| 1802
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for possible open access publication
under the terms and conditions of the Creative
Commons Attribution (CC BY SA) license
(https://creativecommons.org/licenses/by-sa/4.0/).
