International Journal of Education, Information Technology and Others (IJEIT), April 2023, 6 (2), 245-260

DOI: https://doi.org/10.5281/zenodo.7901708
p-ISSN: 2654-2528 e-ISSN: 2623-2324
Accredited by Directorate General of Strengthening for Research and Development
Available online at https://jurnal.peneliti.net/index.php/IJEIT

Factors Affect Students' Science Learning Outcomes

(Case Study in 8th Grade Junior High School Students in Masohi City,
Central Maluku Regency)

Hermalina Sinay1, Izaak Hendrik Wenno2, Sri Rahmadani Pulu3, Sally

Edoxiana Untajana4, Ashari Bayu Prasada Dulhasyim5

1,3,4,5
Physics Education Program, Faculty of Teaching and Education Pattimura
University, Indonesia
2
Biology Education Program, Faculty of Teaching and Education Pattimura
University, Indonesia.

Abstract
Received: 6 April 2023 Identification of the dominant factors that influence student learning
Revised: 13 April 2023 outcomes, aimed to find out (diagnose) the problems faced in learning
Accepted: 26 April 2023 so that improvements can be made to improve student learning
outcomes. The selection of the most influential factors can be done using
the analysis of the main components. The purpose of this study was to
find out the main factors that influence junior high school students’
science learning outcomes in the Masohi city, Central Maluku Regency.
The population in this study were 180 8th grade students at four junior
high schools in Masohi city. The research instrument was in the form of
a questionnaire to measure 8 variables compiled based on a Likert scale.
Determination of the main factors that affect student learning outcomes
was carried out using principal component analysis, with the assistance
of SPSS software version 18.0. The results showed that in Public Islamic
Junior High School 2 Masohi, the main factors influencing students'
science learning outcomes were interest, motivation, infrastructure, and
parents, while the second factor was teachers and peers, while in public
junior high school 1, 2 and 3 Masohi, it appeared that the main factors
influencing students' science learning outcomes were teachers,
infrastructure, peers and parents, while the second factor was interest
and motivation. Thus, it can be concluded that the main factors affecting
learning outcomes in junior high schools in Masohi City are different.

Keywords: principal components, student learning outcomes

(*) Corresponding Author: wennocak@gmail.com , elinasinay08@gmail.com,

srahmadanipulu@gmail.com, sallyuntajana@gmail.com,
asharibayu01@gmail.com

How to Cite: Sinay, H., Wenno, I., Pulu, S., Untajana, S., & Dulhasyim, A. B. (2023). Factors Affect
Students’ Science Learning Outcomes. International Journal of Education, Information Technology, and
Others, 6(2), 245-260. https://doi.org/10.5281/zenodo.7901708

INTRODUCTION
In junior high school, physics, biology, and chemistry are included in
natural science subjects. According to Faisal and Sonya. (2019) the purpose of
learning science is to prepare students to become good citizens based on the
Pancasila (basic ideology of the Indonesian state) and the 1945 Constitution by
focusing on developing individuals who can understand the problems in the
environment, both those in the social environment that discuss human interaction
and natural environment.

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As part of Natural Sciences, Physics, Chemistry and Biology are considered

important as a basis in relation to the mastery of science and technology (Barnabas
et al., 2019), as well as influencing and directly related to various fields of life and
jobs that are information and technology based (Das et al, 2014). According to
Mekonnen (2014), without the existence of natural science, humans will have
difficulty exploring the universe. Rull (2014) states that understanding natural
science helps in understanding the contents of the universe while for students, it
helps develop observation skills, accuracy, analytical skills, and creative thinking,
so natural science mastery is needed and cannot be avoided by students (Wenno,
2014; Wenno et al., 2016; Prachagool and Nuangchalerm, 2019).
Not only Physics, Biology is also a subject that is considered boring for
students, especially junior high school students. According to Gottlieb et al. (2007),
Biology is a science that is very useful in solving life's problems and in efforts to
understand other sciences. Although it is often regarded as one of the relatively
"easy" science lessons, in reality for some students, learning biology is always not
easy, because there are materials that require knowledge of basic concepts and
overall level of mastery of science in Biology. In addition, there are assumptions
that Biology as a subject that is boring, contains a lot of memorization, and is
monotonous, causing lower students’ learning outcomes.
The low student learning outcomes towards science are caused by many
factors, such as internal and external factors (Tatar et al., 2016). Internal factors can
be in the form of attitudes, motivation, interests, knowledge, skills, expectations,
assumptions, and goals (Nyoni et al., 2017), while external factors are the
conditions of student learning environment (Byers et al., 2018), such as the use of
teaching methods by teachers (Bal Tastan et al., 2018), family environment, and the
availability of learning facilities and infrastructure (Ramli and Zain, 2019; Sutriayu
et al., 2020). The low student learning outcomes in learning are also caused because,
science especially physics has been considered as a difficult subject by students,
especially if the material is related to mathematical calculations (Baran, 2016).
Likewise with junior high school students in Masohi City, Central Maluku
Regency. In these schools, generally students' perceptions and understanding of
Natural Sciences subjects are also still influenced by various aspects such as student
interest and motivation, learning support facilities in the form of laboratories,
teacher teaching styles or methods, as well as parental support and environmental
influences such as their peers.
Based on the results of preliminary observations and open interviews with
natural science subject teachers, it is known that student learning outcomes in junior
high schools in Masohi city are still low. This is because students still do not have
great interest in science. Students also do not understand the true benefits of their
learning. Students learn for a while and get grades for advancement and / or
graduation. On the other hand, the teaching methods and methods of teachers, as
well as very minimal supporting facilities, lead to lower student interest and
motivation, so that it determines and affects their learning outcomes.
According to Leinhard and Leinhard (2013) learning difficulties are very
complex because they relate to the emotional aspects of students, have the
opportunity to be a threat, a barrier or a disruption in learning, thus substantially
affecting student learning abilities, and also student academic achievement.

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Ma'rifah (2017) states that children who experience learning difficulties exhibit
traits such as difficulty in doing school academic tasks, to learning achievement that
decreases far from the actual potential expected.
Ullah et al. (2013) reported that student motivation in learning was
influenced by the school environment and also the family environment.
Identification of the dominant factors that influence learning outcomes by students,
aims to find out ot to diagnose problems encountered in learning both from within
(internal) students, or from outside (external) of students, so that the preventive and
corrective actions can be taken right so it is expected that the learning process can
go according to plan with maximum results.
Previously it has been explained that the factors that influence student
learning outcomes consists of many factors which are grouped into two major
groups namely the inside and outside factors. From both two factors, we will look
for which factors that most influence student learning outcomes in science lessons.
The selection of the most influential factors can be done using principal component
analysis. This is a part of factor analysis that carried out to reduce the large number
of variables to a number of new selected variables (Howard, 2016), so that the new
variables can be used as the most influential variables, in this case, the learning
outcomes of science students in junior high schools in Masohi City the Central
Maluku Regency. So, the objective of this research was to find out what are the
main dominant factors that are greatly affect the science learning outcomes of 8th
grade students at junior high school in Masohi City, the Central Maluku Regency.

METHOD
Research Population and Sample
The population in this study were all junior high schools in Masohi City, Central
Maluku Regency. Meanwhile, the school sample included 4 junior high schools.
School samples were determined randomly. All school names were written on
paper, rolled up, and then randomized and selected as many as 4 schools. This
selected school became the location for the research implementation.
Then, at each location, the classes that will be the samples were determined. In
each school, 2 8th grade classes were taken. The intended class was selected with
the same way as the school sample determination, The name of all 8th grades in the
school were written on papers and randomized. Then, the 2 classes were obtained
after the papers were raffled. Therefore, students in the two selected classes became
the samples for research, namely 8th grade students in the odd semester of the
2019/2020 academic year. The name of the school and the number of students in
each school are as follows:
School names Number of sample students
State Junior High School 1 Masohi 44
State Junior High School 2 Masohi 48
State Junior High School 3 Masohi 44
Islamic Junior High School 2 Masohi 42
Total number of samples 180

Research Instruments
The instrument used in this study was a non-test instrument in the form of

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questionnaires arranged on a Likert scale. The statements in the questionnaire were

favorable and unfavorable with 4 alternative answers, namely SA (strongly agree),
A (agree), DA (disagree), and SDA (strongly disagree). The scoring for each
statement item in the instrument is as follows:
Alternative answers Favourable (+) Unfavourable (-)
Strongly Agree 3 1
Agree 3 2
Disagree 2 3
Strongly Disagree 1 4

Research Procedure
Prior to the true implementation, and before preparing a questionnaire, the
observations at the schools sample was done. After that, the questionnaire compiled
was tested on 80 samples of students from 2 schools. Instrument testing aimed to
test the validity and reliability of the instrument. The validity test was based on the
value of the Pearson Product-Moment correlation coefficient (r) by comparing the
rcount and rtable values. If the rcount value is more than rtable, the statement item was
valid. If the rcount value is less than rtable, the statement item was invalid and
discarded so that it was not used as a research instrument. The reliability test was
based on the Alpha-Cronbach coefficient (ri). The variables is reliable if the ri value
is more than 0.6 and is not reliable if the ri value is less then 0.7 (Streiner, 2003).
As same as with the validity test results, unreliable statement items were discarded
and not used as an instrument for true research. The following is the number of
items before and after the validity and reliability test.

Table 1. Number of items before and after Validity Test and the result of
reliability test
Variable Validity test results Reliability test results
The number of items The number of Note
before the test items after the Alpha Note
test Cronbach Value
Interest 30 27 3 items .634 Reliable
discarded
Motivatio 50 45 5 items .843 Reliable
n discarded
Teacher 35 31 4 items .912 Reliable
discarded
Infrastruc 30 26 4 items .741 Reliable
ture discarded
Peers 25 21 4 items .873 Reliable
discarded
Parents 30 22 8 items .891 Reliable
discarded

Based on the data in Table 1, it can be seen that the number of statement items
for research are interest (27 items), motivation (45 items), teachers (31 items),
infrastructure (26 items), peers (21 items), and parents (22 points), while for
reliability, all variables were reliable so they could be used for data collection in
real research.

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Data analysis
The research data was in form of the results of filling out questionnaires by
students on six variables to determine which variable was the most dominant in
influencing student learning outcomes. Determination of the main factors or
dominant factors that affect student learning outcomes was carried out using
Principal Component Analysis (PCA), with the assistance of SPSS software version
18.0.
The main component analysis stages are as follows:
a. The test of analysis requirements
The requirements test for principal component analysis was the Kaiser Meyer
Olkin (KMO) test, which is used to determine sample adequacy or measure sample
feasibility. Factor analysis was considered feasible if the KMO value was > 0.5. In
addition to the KMO value, the analysis requirements test can also be done by
looking for the Barlett Test of Sphercity significance value, which tests that the
sample variables are correlated. The Barlett Test of Sphercity significance value
must be less than 0.05.
b. Factor rotation
A factor rotation was done to determine the number of main components that
are formed. This was done by looking at the Eigen value of each major component.
The components selected were those whose Eigen values are more than 1 (Zu´ska,
et al. 2019).
c. Determining the constituent variables of the principal components
The variables that make up the principal component were seen based on the
value of the partial correlation between a variable and a major component. If the
value was > 0.7 then the variable was included in the principal component (Zu´ska,
et al. 2019).
d. Identifying the main factors
Identification of the main factors that affect student learning outcomes was
carried out based on the variable's position in a major component. If a particular
variable was in the first principal component, that variable was the main factor.
Conversely, if a certain variable was included in the second principal component,
that variable was the second factor.

RESULTS
Factor analysis is an interdependency technique, which means that there is no
dependent variable or independent variable. The process of factor analysis tries to
find a relationship between a number of independent variables so that one or several
sets of variables that are less than the initial number of variables can be made
(Loehlin and Beaujean, 2017). Odunlami (2013) states that the main objective of
factor analysis is to summarize the information contained in the initial variable into
a new factor.
The principal component analysis (PCA) requirements test which was done
by looking to the value of the Kaiser-Meyer-Oikin (KMO) and the significance
value of the Bartlets Test of Sphericity which is a requirement or condition to
determine or testing the feasibility of a variable to be analyzed with PCA. The KMO
value requirement for the feasibility test data in the analysis of the PCA must be

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more than 0.5 with the significance of the Bartlets Test of Sphericity must be less
than 0.05 (Table 2).

Table 2. KMO-Bartlett's Test of Sphericity values for principal component analysis

(PCA)
No. School names KMO Value Significance Value of Bartlett's
Test of Sphericity
1. Public 0.682 0.000
Islamic Junior High
School 2 Masohi
2. Public Junior 0.735 0.000
High School 1
Masohi
3. Public Junior 0,762 0.000
High School 2
Masohi
4. Public Junior 0,752 0.000
High School 3
Masohi

Table 2 shows that at all sampling locations, the data collected was eligible
to be tested by PCA because all KMO values were more than 0.5 (KMO> 0.5), and
the Bartlets Test of Sphericity significance value was all less than 0.05 (sig. <0.05).
The next stage in PCA is determining the number of new components to be formed.
That is why this analysis is called principal component analysis or factor analysis
because the aim is to find a number of new components or new factors that can
define the variable which was want to know. The purpose of this principal
component analysis is also to reduce the large number of variables into a number
of new variables that can be categorized into new components or factors. At this
step, the analysis is based on the size (less or more) of the Eigenvalue. According
to Brunelli (2015) Eigenvalue is a value that shows how much a variable will affect
the formation of new components. The greatest Eigenvalue is what gives the
strongest characteristics for a major component. Eigenvalue criteria that can be used
are more than one (Brunelli, 2015) (Table 3).
Table 3. Number of principal components (PC) with Eigen values for each
component
School names The number of Eigenvalues Contribution of Cumulative
new principal that form the variables to the Contribution
components Principal formation of (%)
formed Component Principal
Components (%)
Public 1 2.377 39.618 39.618
Islamic Junior 2 1.167 19.454 59.072
High School 2
Masohi
Public Junior 1 2,825 48,751 48,751
High School 1 2 1,143 19,044 67,796
Masohi
1 3,206 53,430 53,430

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Public Junior 2 1,083 18,055 71,485

High School 2
Masohi
Public Junior 1 3,122 52,035 52,035
High School 3 2 1,034 17,230 60,265
Masohi

Table 3 shows that in general in all scholls, there was two principal
components (PC) were formed with an Eigenvalue more than 1. With these result,
the next analysis was done to determine which one of these variables affected
student learning outcomes, which were included in the first or second Principal
component. This analysis was done through the correlation test between variables
and the components which were formed, with the required value of the correlation
test results is more than 0.5 (Table 4 - Table 6).
Table 4. The correlation values between variables and principal components in
Public Islamic Junior High School 2 Masohi
School names Variables The number of principal components
formed by the value of the relationship between
the variable and its main component
PC1 PC2
Public Interest .763 .118
Islamic Motivation .571 .485
Junior High Teacher .054 .819
School 2 Infrastructure .706 .284
Masohi Peers .085 .760
Parents .728 -.135

Table 5. Correlation values between variables and principal components in Public

Junior High School 1 Masohi
School names variables The number of principal components formed by
the value of the relationship between the variable and
its main component
PC1 PC2
Public Junior Interest .004 .880
High School 1 Motivation .326 .782
Masohi Teacher .782 .283
Infrastructure .817 .021
Peers .801 .228
Parents .719 .071

Table 6. The correlation value between variables and principal components

in Public Junior High School 2 Masohi
School names variables The number of principal components
formed by the value of the relationship between
the variable and its main component
PC1 PC2
Public Junior Interest -.028 .919
High School 2 Motivation .553 .625
Masohi Teacher .692 .517
Infrastructure .784 .156
Peers .887 -.052

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Parents .736 .180

Table 7. The correlations between variables and main components in Public Junior
High School 3 Masohi
School names variables The number of main components formed by
the value of the relationship between the variable
and its main component
PC1 PC2
Public Junior Interest -.028 .919
High School 3 Motivation .553 .625
Masohi Teacher .692 .517
Infrastructure .784 .156
Peers .887 -.052
Parents .736 .180

Data in Table 4 untill Table 7, shows that there are two main components
were formed based on their correlation values between variables and one of the
principle component, namely the First Principal Component (PC1), and the second
Principal component (PC2). After this analysis, the final step of principal
component analysis was done to determine the main variables or factors and the
second one which is be the most influence tfactors which affect he science learning
outcomes of students in each school were identified (Table 8).
Table 8. The results of Variable Identification that affect the Science Learning
Outcomes of Junior High School in Masohi City
Name of school Factors affecting student learning outcomes
Principal Factors Second Factors
Public Islamic interest, motivation, facilities, Teacher, and peers
Junior High School 2 and parent
Masohi
Public Junior Teacher, facilities, peers, and Interest and
High School 1 Masohi parent Motivation
Public Junior Teacher, facilities, peers, and Interest and
High School 2 Masohi parent, Motivation
Public Junior Teacher, facilities, peers, and Interest and
High School 3 Masohi parent, Motivation

Based on the table above, it can be explained that the main factors that
influence students learning outcomes in science in Public Islamic Junior High
School 2 Masohi are interest, motivation, infrastructure, and parents, while the
second factor is the teacher and peers. In the public junior high school 1, 2 and 3
Masohi, it appears that the main factors that influence students' science learning
outcomes are teachers, infrastructure, peers and parents, while the second factor is
interest and motivation.

DISCUSSION AND CONCLUSSION

These results indicate that in the three public schools, namely Public Senior
High Schools 1, 2, and 3, the main factors that influence student learning outcomes
were the same, namely facilities, teachers, parents, and friends, as well as the second
factor, namely interest, and motivation. This means that students' interest and
motivation in these three schools can be said to be good. However, other supporting

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factors such as facilities, teachers, parents, and peers that affected student learning
outcomes were not good. Because the facilities, teachers, parents, and peers were
not supportive, students' interests and motivation were affected, and this overall
affects their learning outcomes.
The role of motivation and interest in influencing student learning outcomes is
not something new and has been the subject of discussion among education experts,
teachers, and all those who are involved in the field of education, and have been
reported by many researchers at various levels of education from elementary school
(Wijaya dan Bukhori, 2017; Phuntsho, 2018) to tertiary level (Sulistiyarini and
Sukardi, 2016) as well as in the higher education (Taurina, 2015; Schumacher and
Ifenthaler, 2018). It is undeniable that interest and motivation are the biggest
movers that greatly affect student learning outcomes. With a high level of interest
and motivation, students will have the encouragement and drive to enable them to
learn and carry out learning activities. However, according to Chue & Nie (2016)
motivation as an internal factor is not only activated by students themselves, but
also stimulated by external stimuli that usually come from the environment
(parents) and the school environment including teachers and learning facilities in
the schools. Therefore, teachers, staff, parents and the community need to
encourage and foster student motivation in learning both through attitude,
performance, creating a good learning environment, and good teaching methods
and strategies, so that students can be motivated to learn more which in turn can
love what they learn, and obtain maximum learning outcomes.
In these three schools, the main components that influenced student learning
outcomes were facilities, teachers, parents, and friends. This means that these four
components or the four factors must be fixed. Nepal and Maharjan (2018) state that
if schools want to improve student learning outcomes, learning support facilities
must be maximized. It is not only quantity and availability but also quality. Hofstein
(2017) states that Natural Science is learning that emphasizes process and requires
many experiments. According to Kwok (2015), the essential components in
learning science in schools is a laboratory's presence. This is because science
learning is not just memorizing theories. However, it is necessary to implement the
theory obtained through real work in form of experiments nor observations and
correlate between concepts and facts. By conducting experiments and or
observations, it allows students to learn to construct their knowledge, link theory
and practice, have the ability to solve problems, practice skills in using tools and
materials, and improve scientific thinking and working skills. All of this can be
achieved if the infrastructure is available and can be used by students (Harman et
al., 2016; Cullin et al., 2017).
Apart from infrastructure, the quality of teacher teaching also affected student
learning outcomes. In fact, at Public Junior High Schools 1, 2, and 3 in Masohi. The
factors of infrastructure and teachers are the main factors affecting student learning
outcomes. On the one hand, the infrastructure was not adequately available. If the
teacher is not qualified or the teacher's teaching method is not suitable, this will
worsen student learning outcomes. According to Duban et al. (2019), Science
teachers must realize that their presence in the classroom is not only for reading
supporting books, explaining material, asking questions and assessing student
learning outcomes but also creating a learning environment that is supportive for

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student learning. Teachers' teaching methods must be innovative and creative,

especially in science learning. The teacher must simplify the subject matter so that
students can easily understand it by using interesting learning methods and models.
Teachers also have to balance theory and practice. The teacher must master the
equipment and be skilled at using it. Teachers must be good at designing
experimental and or practicum activities so that students learn many theories and
are guided to do the practicum. With a combination of good theory delivery by the
teacher and direct experiments by students, it allows students to learn well, achieve
learning completeness, and improve learning outcomes.
When discussing infrastructure and teachers, these are the elements that exist in
the school. However, it is not just these two components because students do not
stay at school all day. After studying at school, students will return home. Home is
a component that also has a significant influence on student learning habits. Wijaya
and Bukhori (2017) reported a significant influence between family factors and
student learning outcomes majoring in administration at Public Vocational High
School 2 Blitar. According to Ngussa and Mundula (2019), a comfortable home
condition with parents who support the student learning process will have an
excellent influence. Parents are also required to provide supporting equipment for
students to study, such as a special study room at home with the appropriate
equipment, providing facilities such as books and the internet.
In addition, the students’ peers is a factor that also determines the success of
student learning. Peers who always do positive learning activities will undoubtedly
influence and encourage students to study together, such as doing assignments
together, or looking for and discussing lessons that have not been understood.
However, the habits of study partners who do not support student learning will
worsen student learning outcomes. In Masohi 1, 2, and 3 public junior high schools,
if these four factors are corrected, it is likely that student interest and motivation
will be better so that their learning outcomes will also be good.
In contrast to the results at Senior High School 1, 2, and 3, student learning
outcomes at Islamic Junior High School 2 Masohi School were influenced by the
main factor, which was a combination of internal factors (interest and motivation),
as well as external factors (facilities and parents). If in public schools 1, 2, and 3
the factors of interest and motivation were not the main factors, at public Islamic
junior high school 2 Masohi, interest, and motivation were the main factors besides
facilities and parents, while the second factor was teachers and peers.
For the facilities and parents factors, the situation is almost the same as
described in public schools 1, 2, and 3, while teachers and peers might be better
than in public schools 1, 2, and 3. Students' special findings at Public Islamic Junior
high School 2 were interest and motivation as the main factors. This shows that the
school and parents have to work extra hard to revive students' interest and
motivation. Conditions in which interest and motivation significantly affect
students' learning outcomes are very important to be considered by all parties,
because this factor comes from within students. That means students have no
interest and liking for the subject, which is very dangerous and should be a warning.
There can be low student interest and motivation due to other factors that
cumulatively give students a bad impression. Thus it worsens the students'
impression towards the object that must be studied.

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If we look at the main factors in all schools, it is generally found that the
facilities and parents. It cannot be denied that students in these four schools come
from similar family backgrounds, in terms of education level, occupation, and also
parents' income. Some students come from families with low educational
backgrounds of parents. Their parents do not have permanent jobs, and also have
uncertain income. Some work as farmers, fishers, market sellers, bricklayers, car
drivers, pedicab drivers, and only a small proportion of them are office workers.
This, of course, affects student learning outcomes. Parents with irregular and
uncertain income may not provide learning facilities that meet standards and
support student learning situations. Sometimes, after completing learning activities
at school, students help their parents working at home, such as gardening, fishing
in the sea, selling, or collecting wood in the forest. This condition is exacerbated by
the fact that students' peers have almost the same conditions. They often spend their
time playing football, bathing in the river or on the beach, or just relaxing in certain
places after helping their parents. There are no learning activities carried out by
students outside of the main study hours at school with such circumstances. When
students have spent much time working or playing at home, they no longer have
their attention to study.
When they returned to school the next day, students did not have sufficient
provisions about the lessons they learned. They hope to be taught by the teacher. If
the quality of teachers and learning facilities in schools is inadequate, students will
suffer further. This situation was ongoing and repeated. Cumulatively, student
learning outcomes will decrease.
The principal’s leadership also supports teachers who teach well. As an
inseparable part of a school organization, the principal has the duty and
responsibility to lead the management of the organization in the school including
providing space to support the improvement of the quality and creativity of teachers
so that it eventually has an impact on improving student learning outcomes (Kempa
et al., 2017).
The school, including the principal, teachers, and parents, must improve this
condition, because student learning outcomes are the main thing that must be
considered to improve the quality of education, especially in the four schools
studied in this study.
Based on the results of research and discussion, it is concluded that the science
learning outcomes of junior high school students in Masohi City, Central Maluku
Regency are different. In Public Islamic Junior High School 2 Masohi the main
factors that influence students science learning outcomes are interest, motivation,
infrastructure, and parents, while the second factor is the teacher and peers. In the
public junior high school 1, 2 and 3 Masohi, it appears that the main factors that
influence students' science learning outcomes are teachers, infrastructure, peers and
parents, while the second factor is interest and motivation.

ACKNOWLEDGMENTS
This research was funded through the 2019 Faculty of Teaching and
Education Research grants. The author would like to express deepest gratitude for
the financial assistance.

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Biodata of the Author

Izaak Hendrik WENNO, was born on January 25, 1974 in
Ambon. Elementary, junior and senior high school was completed
at the Public Elementary 1 School, Public Junior High School 1
and Public Senior High School 1 in Masohi, Central Maluku.
Undergraduate program in 1999 at the Physics Education Study
Program of the Teaching and Education Faculty, Pattimura
University, then continued his master's study at the Jakarta State
University Postgraduate Program and obtained a Masters in
Education in 2003. In 2006 he continued his studies at the Doctoral
Program of the Yogyakarta State University and graduated in 2010.
Starting his career as a lecturer since 2000 at the Physics Education
Study Program Faculty of Teaching and Education, Pattimura
University until now. Apart from teaching, he is also active in
conducting research, writing various books on research and
evaluation of education, and is active in scientific meetings both
nationally and internationally.
Affiliation : Pattimura University of Ambon
E-mail: wennocak@gmail.com
Phone number: (+62)081343018564
Orcid Number: 0000-0002-7796-2342

Hermalina SINAY, was born on August 22, 1975 in Aboru,

Central Maluku. Elementary, junior and senior high school was
completed at Public Elementary 2 School in Aboru, Public
Junior High School 9 and Public Senior High School 4 in
Ambon. The undergraduate program was completed in 1999 at
the Biology Education Study Program, Faculty of Teaching and
Education, Pattimura University, then continued his master's
studies at the Postgraduate Program Faculty of Biology, Gadjah
Mada University Yogyakarta and obtained a Master of Science
degree in 2008. In 2012 she continued her studies at the Doctoral
Program of Biology, Faculty of Mathematics and Natural
Sciences, Brawijaya University in Malang and graduated in
2016. She started her career as a lecturer since 2002 in the
Biology Education Study Program, Faculty of Teaching and
Education, Pattimura University until now. Apart from teaching,
she is also active in conducting research, writing books and
articles published in international journals, and being active in
scientific meetings both nationally and internationally.
Affiliation : Pattimura University of Ambon
E-mail: elinasinay08@gmail.com
Phone number: (+62)085204150790
Orcid Number: 0000-0003-2147-7046

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Information Technology and Others (IJEIT) 6 (2), 245-260

Sri Rahmadani PULU was born in Wahai, Maluku

Tengah, Indonesia. She Obtained a bachelor’s degree in
Study Program of Physic Education, Faculty of Teacher
Training and Education, Pattimura University (2008-
2013), Indonesia. And She Graduated a Master’s degree
in Study Program of Science Education, The State
University of Surabaya (2014-2016), Indonesia. She is a
lecturer in Pattimura University of Ambon, Indonesia.
Her Research focusing on Misconception Student in basic
science concept.
Affiliation : Pattimura University of Ambon
E-Mail: srahmadanipulu@gmail.com
Phone:(+62)81391200670

Sally Edoxiana UNTAJANA, was born in Yamtel, Southeast Maluku -

Indonesia. She Obtained a bachelor’s degree in Study Program Of Physic
Education, Faculty of Teacher Training and Education, Pattimura University (2006-
2011), Indonesia. And She Graduated a Master’s degree in Study Program Of
Science Education, The State University Of Surabaya (2012-2014), Indonesia. She
is a lecturer in Pattimura University of Ambon, Indonesia. Her Research focusing
on students’ mutliple intelligences.
Affiliation : Pattimura University of Ambon
E-Mail : sallyuntajana@gmail.com
Phone : (+62) 82232168206

Ashari Bayu Prasada DULHASYIM was born in

Ambon, Indonesia. He Obtained a bachelor’s degree in
Study Program Of Physic Education, Faculty of Teacher
Training and Education, Pattimura University (2009-
2013), Indonesia. He Graduated a Master’s degree in
Study Program Of Physics, Sebelas Maret University
(2014-2016), Indonesia. He is a lecturer in Pattimura
University of Ambon, Indonesia. His Research focusing
on Material Physics in basic concept Dye Sensitized Solar
Cells.
Affiliation : Pattimura University of Ambon
E-Mail : asharibayu01@gmail.com
Phone : (+62) 81356078201

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