THE EFFECT OF CURRICULUM 2013 ON ECONOMICS LEARNING ACHIEVEMENT: MOTIVATION AS MEDIATING VARIABLE

The National Standard of Education (NSE) in Indonesia is a legitimate instrument to reach the best achievement. Yet, there are still the other positive factors, especially on economics subjects. This research aimed to find out the direct effect of the national standard of education (NSE) involving in a standard of content (SC), standard for educator and education staff (SEE), standard of facilities (SF), standard of assessment (SA), standard of the process (SP) and competence graduate standard (CGS) on achievement motivation (AM) and economics learning achievement (ELA), and to find out the indirect influence of SC, SEE, SF, SA, SP, and CGS on ELA through AM. This descriptive quantitative research used a survey to collect the data. The population is Indonesian senior high school students who have learned the economy for, at least. A total of 1065 students were selected through using proportional stratified random sampling with the Slovin formula (error = 1%). The data in this study were collected through The data were subsequently analyized using Structural Equation Modeling (Partial Least Square approach). The result of this research showed that there was a direct effect of SC, SEE, SF, SA, SP, and CGS and AM on ELA. Then, there was an indirect effect of SC, SEE, SF, SA, and CGS on ELA through AM as a mediating variable.


INTRODUCTION
and until national Curriculum.
In the implementation, however, some curricula were applied based on the school authority and stuff. One of the curricula temporarily used is Curriculum 13 (K-13). The Curriculum itself began as a Latin word currere, which means the yard of a race. Saylor & Alexander (1974) stated that curriculum broadly defines as a reflection of assessing volume about assessment property. This definition also affects how the curriculum will be playable and profitable. Ornstein & Hunkins (2013) said that the Curriculum is a confusing, difficult, and fragment study to understand. The curriculum involves the whole stakeholder, of course, teachers and students, in line with this theory. Shawer (2017) explained that the Curriculum is altogether creating corporately a good person, both teacher and student.
Besides of Bussmaker, Trokanas & Franjo (2017) said that knowledge needed in the curriculum is very large for teachers to maintain gradually a developed Curriculum. Then, according to Moss & Harvie (2015), the definition of classic curriculum is also for principle, students, and policymakers. Law number 20 in 2003 about the National Education System and Rule of Indonesia Government no. 19 in 2005 about the National Standard of Education (NSE) explained that curriculum is a set of plans and a set of purpose, content, teaching materials, and the method as a basic guideline of learning to reach the goal of education. Then, curriculum raises issues concerning students of control and power over the learning process, that conditions will give achievement and enjoyment of learning for students (Hopkins, 2008;Robinson & Fieldling, 2010;Robinson, 2014;Hargreaves, 2017;Manyukhina & Wyse, 2019). Short (1987) stated that curriculum scope is policymaking, development, evaluation, change, decision making, activity or study field, and form and investigation language. According to Hargreaves & Moore (2000) described that many theoretical discussions about curriculum have been separated from practical in the class, and many practical discussions about curriculum rarely consider the theoretical connection. The Curriculum 2013 (K-13) is the one based on competence designed to anticipate what people need in this 21st century. K-13 aims to create creative effective productive people by attitude, skill, and knowledge (Mulyasa, 2014).
Similarly, the objective of K-13 is to prepare Indonesian in order to be better ones who have a good belief, and become productive, creative, innovative, effective and afford to contribute what they can do in social, national and statue life, and in civilization (Ministry of Education Law No.70 Year 2013). Hosnan (2016) said that scientific learning is instead of 5 steps, observing, questioning, associating, experimenting, and networking. There are schools that have not yet provided counseling guidance services.
A few problems found in research field namely education has not provided maximum academic service, school ventilation systems have not been functioning optimally, textbook needs are incomplete, there are students who do not have a high level of confidence, there are students who are not responsible for their learning duties, teacher Unpreparedness employs an interactive learning method that is required in K-13 and low motivation for achieving students.
Standard of content (SC) is a criterion about learning material and competency level to reach a minimum standard of competence on one level and type (Mulyasa, 2014). Standard of the process (SP) is a criterion about organizing the learning in education to reach that standard itself. Competence graduate standard (CGS) is a criterion about qualification on students' ability to pass the minimum standard, instead of, affective, cognitive, and psychomotor. Standard of educator and education staff (SEE) is a criterion about positional educational level, both worth on mental, and education on one level. Standard of the facility (SF) is a criterion on the place to study, to the sport, the library, the worship place, laboratory, the place to play, and supporting things to espouse to the learning process (Mulyasa, 2014). Then, the facility of education as like online facility and offline facility or blended learning, facility of education is very important to improve the learning outcome of Senior High School Students (Sari & Setiawan, 2018).
Education financing standard (EFS) is a criterion about component and operational cost in education in one year. Standard of assessment (SA) is a criterion about the mechanism, procedure, and instrument to assess the students' achievement. One of the assessments is by giving them an exam. It is done to measure the achievement of students' competence (Mulyasa, 2014). Singh (2011) Achievement motivation (AM) is a will to do the best on those standardizations. Motivation is likely related to academic things, cognitive, emotion, and indicator of students' in education (Tucker, Zayco, & Herman, 2002). Motivation is the study of why humans think, feel, and behave (Wood & Graham, 2015). Most of the shows there is a very strong relationship between motivation there is learning success and academic achievement (Corpus, McClintic-Gilbert, & Hayenga, 2009). Motivation can also be defined as a plan or a wish to head towards success and avoid failure (Papilaya, Tuakora, & Rijal, 2019). The findings revealed that the achievement motivation moderated the relationship of learning approaches and academic achievement significantly (p < .05) (Bakhtiarvand, Ahmadiana, Delrooza & Delrooza, 2011), and there is a relationship between achievement motivation and performance (Hardin, Mustari, & Sari, 2019). But there has been no previous research that makes achievement motivation as a moderating variable between curriculum implementation of economics learning outcomes.
Implementing the curriculum according to the plan will produce good learning outcomes. However, there need to be other endeavors outside the curriculum instrument to support learning outcomes. one that can be maximized is student achievement motivation. Winkel (2004) explains that students' achievement is the result given to the students themselves. Cognitive learning includes knowledge, comprehension, application, analysis, synthetic, and evaluation. In addition, the object of the effective involves five levels: accept, respond, assess, organize, and characterize. Lastly, the object of psychomotor is a reflex and basic movement, perception skill, physical ability, skilled movement, and no discursive communication (Ornstein & Hunkins, 2013).
As mentioned, the National Standard of Education (NSE) in Indonesia is a legitimate instrument to reach the best achievement. Yet, there are still other positive factors to students' achievement, especially on economics subjects. One of them is AM. AM is a desire to do well relative to some standard of excellence (Singh, 2011). It has been assigned as a reference for a different need in each people to achieve appreciation like satisfaction, praise from other people, and self-satisfaction (McClelland, 1985).
This research aimed to find out the direct effect on the national standard of education (NSE) involving in a standard of content (SC), standard for educator and education staff (SEE), standard of facilities (SF), standard of assessment (SA), standard of the process (SP) and competence graduate standard (CGS) on achievement motivation (AM) and economics learning achievement (ELA), and to find out the indirect influence between SC, SEE, SF, SA, SP, and CGS on ELA through AM.

Research Design
This research was conducted in senior high school which has been applied K-13, taking the place in Serdang Bedagai district, North Sumatera, Indonesia. Implementation of K-13 in some districts instead of eight NSE that has been assigned by the Government, those are SC, SP, CGS, SEE, SF, MS, EFS, and SA. However, in this research, these variables did no longer exist as a whole. The researcher only focused on NSE in K-13, SC, CGS, SEE, SF, SP, and SA (exogenous variable) and AM and ELA (endogenous variable). Analysis data was by using Structure Equation Modeling-Partial Least Square (SEM-PLS). SEM-PLS has the advantage of analysis that is data does not have to be normally distributed. Therefore, this study does not test data normality and linearity. The conceptual model was being applied (see Figure  1).

Population and Sampling
The population in this research was state high school students which were applied K-13 in their schools and for them who have learned economics, at least, for one year in some districts whose total was 1192 students, at the time of the survey. The respondent was in the 11th and 12th grades. This research used a quantitative descriptive through the survey method. The sample was 1065 students by proportional stratified random sampling technique with Slovin's formula (error = 1%).

Instrument and Measurement
The instrument in this research is to measure SC, CGS, SEE, SF, SP, SA, and AM by using questionnaires. Participant responses to items use a 7-point continuous scale (1 = strongly disagree to 7 = strongly agree). The questionnaires were developed from the national standard of education (Government regulation number 32 in 2013; Poerwati & Amri, 2013). The instrument was developed from variables because similar instruments had never existed.
The statement which is used inside was easy to understand for the respondent. After that, the instrument of ELA was used to the final score, it was categorized, then (1 to 7). ELA was divided into 3, knowledge about economics, attitude, and skill (Bussmaker et al., 2017;Kurniasih & Sani, 2014). The result was taken from the final score in the class when it had been categorized.

Validity for a Research Instrument
Convergent validity relating to the measurement is a value of loading factor (LF) with the rule of thumb > .7, LF value > .7 is ideal which means the indicator is valid. The result of the questionnaire test could be described in Figure 2. It shows that the whole instrument could be regarded as a valid instrument because of the LF value known through data tabulation.

Reliability of Research Instrument
The reliability test can be viewed on the value of Cronbach's alpha and composite reliability (CR) or well-known as Dillon-Goldstein's. Rule of thumb which can be used to measure the reliability by the value of CR > .7 for confirmatory research and value of CR .6 -.7 could be said as reliable to measure the reliability of explanatory research. Then, the value of the average variance extracted (AVE) is more than .5 (Haryono, 2017). The reliability constructs. To check the reliability construct can be used convergent validity based on reliability result for each variable. See Table 1. Table 1 shows the Cronbach's alpha values > .7, CR> .7, and AVE > .5. So these results indicate that all research variables can be said to be reliable and can be used as research instruments. The validity and reliability show that the instruments built have a quality that can be accounted for as research instruments.

FINDINGS AND DISCUSSION Findings Evaluation of Measurement Model
The entire variable has reflexive indicators which, then, are validated by using the value of discriminant validity. After all, to test the reliability one variable can use convergent validity by CR values, Cronbach's Alpha, AVE value, and compare the root value of AVE by correlation-construct.

Construct Validity Test
The questionnaire of the research can be valid or can be used in this research if the LF value more than .7 (Haryono, 2017). Parameter of the validity-convergent test in the measurement model by using reflexive indicators so the LF value > .7 can be used (Haryono, 2017). Based on Figure 3 describes that the entire research questionnaire was valid. It could be viewed by the entire items showing that LF value > .5.

Reliability Testing of Research Construct
Convergent validity test was done to find out the reliability of one research construct. Evaluation for reliability-construct value could be measured by composite reliable, cronbach's alpha, AVE value (Average Variance Extracted) and compare the AVE root value to the correlation among the construct. Cronbach's alpha value and composite reliability value more than .7 and have AVE value more than .5 can be said as reliable (Haryono, 2017) That result data showed that the entire research construct is reliable and worthy to hypothesis test. Reliability test, then, is to evaluate Discriminant validity (DV) which involves Cross Loading (CL) and compare to coefficient value of indicator correlation or question item in to construct block by correlated coefficient on the other column (Haryono, 2017).
Each result of output cross-loading can be viewed in appendix 2. The construct research result of output cross-loading showed that each construct has a questionnaire item more than the construct itself. Therefore, it can conclude that each questionnaire item becomes the indicator of the construct itself. After having the result of output cross-loading on the whole fit construct. The next testing is to compare AVE root value to correlation among constructs. The comparative value is shown in Table 2 and Table 3.
Based in Table 2, the comparative value of AVE and the root value of AVE on Table 3 latent variable correlation can be explained that AVE root value is for the whole construct, SC, SEE, SF, SA, SP, CGS, AM, and ELA more than other construct coefficient correlated value. It showed that the requirements of discriminant validity have been completely fulfilled.

Evaluation of Structural Model
Evaluation of structural model will be analyzed through the significant value of relation among construct showed by t statistic value on to output coefficients which should be more than 1.96, then model evaluation also can be said as fit if it has p-value ≤ .05. The value is a basic to hypothesis test by viewing how many quantities of correlation among exogenous construct is to endogenous construct is. t statistic value and p-value are showed by output path coefficients by using SmartPLS 3.0. It is shown in Table 4. Based on Table 4 showed that from 13 lines are insignificance at all. Then, based on the test, the hypothesis test can be conducted. The line analysis can be seen in Figure 4. After the model showed the compatibility (fit), making the coefficient decomposition, then, by counting direct effect, indirect effect, and the total effect of an exogenous variable on the endogenous variable. The total effect is direct effect plus an indirect effect. Those three things are shown in Table 5.   Table 5, we can be seen the impact of direct and indirect effects among research variables. Those three things can be defined that direct effect based direct effect on figure 4 is the direct effect to SC on AM is showed by γSC.AM = .289, direct effect to SEE on AM is showed by γSEE.AM = .414, direct effect to SF on AM is showed by γSF.AM = .135, direct effect to SA on AM is showed by γSA.AM = .145, direct effect to SP on AM is showed by γSP.AM = .342, and direct effect to CGS on AM is showed by γCGS.AM = .453.
Then, the amount of indirect effect which is showed the influence to SC on ELA through AM is showed by γSC.AM x γAM.ELA = .088, the influence to SEE on ELA through AM is showed by γSEE.AM x γAM.ELA = .125, the influence of SF on ELA through AM is showed by γSF.AM x γAM.ELA = .041, the influence to SA on ELA through AM is showed by γSA. AM x γAM.ELA = .044, the influence to SP on ELA through AM is showed by γSP.AM x γAM. ELA = .104 and the influence of CGS on ELA through AM is showed by γCGS.AM x γAM. ELA = .137.

Hypotheses Test
H1: the coefficient of SC on ELA getting the value of t statistic is 2.605 ≥ 1.96, with p-Value or significant level .009, H2: the coefficient of SEE on ELA getting the value of t statistic is 3.189 ≥ 1.96, with p-value or significant level .002 or less than ɑ = .05, H3: the coefficient of SF on ELA getting the value of t statistic is 2.954 ≥ 1.96, with p-value or significant level .003 or less than ɑ = .05 (5%), H4: the coefficient of SA on ELA getting the value of t statistic is 4.866 ≥ 1.96, with p-value or significant level .000 or less than ɑ = .05, H5: the coefficient of SP on ELA getting the value of t statistic is 2.506 ≥ 1.96, with p-value or significant level .013 or less than ɑ = .05, H6: the coefficient of CGS on ELA getting the value t statistic is 2.601 ≥ 1.96, with p-value or significant level .010 or less than ɑ = .05.
Then H7: the coefficient of AM on ELA getting the value of t statistic is 2.506 ≥ 1.96, with p-value or significant level .013 or less than ɑ = .05, H8: there is a effect of SC on AM, that is t stat value = 2.605> 1.96 with the sig value < .05, then, direct effect of AM on ELA, that, t stat value = 2.506 > 1.96 with sig value < .05, H9: there is effect of SEE on AM that is t stat value = 3.323> 1.96 with sig value < .05, then, direct effect of AM on ELA that is t stat = 2.506 > 1.96 with sig value < .05, H10: there is a direct effect of SF on AM that is t stat value = 3.067 > 1.96 with sig value <.05, then, direct effect of AM on ELA that is t stat value = 2.506 > 1.96 with sig value < .05, H11: there is a direct effect of SA on AM that is t stat value = 12.922 > 1.96 with sig value < .05, then direct effect of AM on ELA that is t stat value = 2.506 > 1.96 with sig value < .05, H12: there is a direct effect of SP on AM that is t stat value = 2.211 > 1.96 with sig value < .05, then, direct effect of AM on ELA that is t Furthermore, determinated coefficient of exogenous variables on endogenous variables (R 2 ). Then, the total of R 2 value or determinated coefficient can be earned through data processing with SmartPLS 3.0 of each substructure to know the prediction of the mode. Determinated Coefficient among Research construct obtained are the structural model in Table 6.

Discussion
H1 clearly shows the value of t statistic > t table (2.605 > 1.96) with p = .009. Besides the findings, there is path coefficient value among the implementation of SC on ELA is about .547, and the correlation coefficient is about .608 which means there is a meaning in the effect among both latent variables. The finding is alike to Raharjo's findings in his research Raharjo (2014) that there is a significant effect among SC on ELA. Then, on H2 shows that the value of t statistic > t table (3.189 > 1.96) with p = .002. Besides the findings, there is path coefficient value among the implementation of SEE on ELA is about .479 or the correlation is about .632 which means there is a meaning in the effect among both latent variables. The findings are alike to Raharjo (2014) which found that there is a significant effect between students' perception of the SEE on ELA. Then, Teachers have planned on Pedagogical practice integration on social justice, using Curriculum materials and parent-teacher meetings (Aguirre, Turner, Bartell, Kalinec-Craig, Foote, McDuffie & Drake, 2013;Aguerre, Mayfield-Ingram & Martin, 2013;Turner, Drake, McDuffie, Aguirre, Bartell, & Foote, 2012;Bartell, Cho, Drake, Petchauer, & Richmondal, 2019 (2017) wrote that there is a positive and significant effect in facility aspects and the school environment on ELA. Then according to Toha & Wulandari (2016), social environment and administration staff can impact students' enthusiasm in learning.
Also, according to Raharjo in his research (2014), there is a significant effect among SF on ELA. Similarly, the finding of Mushtaq & Khan (2012); Isa & Yusoff (2015); O'Brennan, Bradshaw & Furlong (2014) wrote that there is a significant correlation among the facility to the students' accomplishment or advancement through the learning process.
Based on this research, on H4 clearly shows the value of t statistic > t table (4.866 > 1.96) with p = .000. Besides the findings, there is path coefficient value among the implementation of SA on ELA is about .278 or the correlation is about .610 which means there is a meaning in the effect among both latent variables. The findings are alike to Raharjo (2014) wrote that there is a significant effect among standards of assessment towards students' achievement in learning.
Then, on H5 shows the value of t statistic > t table (2.506 > 1.96) with p = .013. Besides this finding, there is path coefficient value among SP on ELA is about .255 or the correlation is about .515 which means there is a meaning in the effect among both latent variables. This finding supports the research of Akinoglu (2008); Raharjo (2014) said that there is a significant X 7 = γ 17 X 1 + γ 27 X 2 + γ 37 X 3 + γ 47 X 4 + γ 57 X 5 + γ 67 X 6 + ς 1 X 7 = .289X 1 + .414X 2 + .135X 3 + .145X 4 + .342X 5 + .453X 6 + ς1 .601 X 8 = γ 18 X 1 + γ 28 X 2 + γ 38 X 3 + γ 48 X 4 + γ 58 X 5 + γ 68 X 6 + γ 78 X 7 + ς 1 X 8 = .547X 1 + 497X 2 + 370X 3 + .278X 4 + .255X 5 + .177X 6 + .303X 7 + ς1 .619 effect among various learning including the indicators of SP on students' learning attitude including ELA. Based on this research, H6 clearly shows the value of t statistic > t table (2.601 > 1.96) with p = .010. Besides this finding, there is path coefficient value among SP on ELA is about .171 or the correlation is about .694 which means there is a meaning in the effect among both latent variables. This finding is alike to the Raharjo research (Raharjo, 2014) thought that there is a significant effect among CGS on ELA. Next, on H7 shows that the value t statistic > t table (2.506 > 1.96) with p = .007. Besides the findings, there is path coefficient value among AM on ELA is about .303 or the correlation is about .661 which means that there is a meaning in the effect of both latent variables. This finding proves that there is a direct and significant effect among the AM on ELA on the students of Senior High School. It shows that there is an improvement in ELA through AM. The resulting test is similar to than alike to the research of Cleopatra (2015); Tella (2007); Singh (2011) show the positive and significant effect among motivation towards learning achievement. In similar findings is on the research of Asvio et al. (2017) which means that there is positive and significant among AM on ELA.
On H8, there is a clearly indirect effect among SC on ELA through AM. It describes that the standard of content is positively influenced in AM to improve the students' achievement in the learning economy. H9 also shows that there is an indirect effect among SEE on ELA students through AM. SEE effected on AM (Gobena, 2018). It seems that AM obviously puts a good contribution to increasing ELA. Moreover, H10 explains that it provides the data that there is an indirect effect among SF on ELA through AM. Similarly, H11 says that there is an indirect effect among SA on ELA through AM. In addition, H12 tells that there is an indirect effect among SP on ELA through AM. Lastly, H13 shows that there is an indirect effect among CGS on ELA through AM. The entire hypothesis describing the new model, achievement motivation as a connecting media NSE on ELA, shows that there is a positive effect of motivation variable in running NSE as an effort in improving ELA. NSE familiarly can be influenced by AM in improving ELA. Therefore, to maximizing the ELA is necessarily shaped the AM both internally and externally. The AM which is in the students will result in the achievement of the NSE instrument as the main major for the Indonesian Government.

CONCLUSION
Finally, this research findings that there is a direct effect among SC on ELA and it directly impacts the ELA itself is about 54.7%. Then there is a direct effect among SEE on ELA and it directly impacts the ELA itself is about 47.9%. So, there is a direct effect among SF on ELA and it directly impacts the ELA itself is about 37 %. Next, there is a direct effect among SA on ELA and it directly impacts the ELA itself is about 27.8%. In addition, there is a direct effect among SP on ELA and it directly impacts the ELA itself is about 25.5%. Similarly, there is a direct effect among CGS on the ELA and it directly impacts the ELA itself is about 17.1%. Furthermore, there is a direct effect among AM on ELA and it directly impacts the ELA itself is about 30.3%.
Then, based on this research, there is an indirect effect among SC on ELA through AM. In addition, there is an indirect effect among SEE on ELA through AM. In similar, there is an indirect effect among SF on ELA through AM. Also, there is an indirect effect among SA on ELA through AM. Next, there is an indirect effect among SP on ELA through AM. And, there is an indirect effect among CGS on ELA through AM. Future research can be conducted by using a different mediation/moderation from this research. It is due to many types of research that have been conducted that there are many variables influencing students' achievement in the learning economy. The AM Variable can be shaped through many variables, the condition also becomes a big opportunity for the next research as a contribution or novelty research that can probably put an improvement or advancement in the coming education process.

AKNOWLEDGMENTS
I should like to thank the Editors of the journal of Cakrawala Pendidikan (CP) as well as the following reviewers who have generously given up valuable to review this paper. The success of this paper depends on their care and competence. Their conscientiousness is much appreciated. I also express my appreciation to all respondents who provided data.

Dimension
Indicator Item Code Appropriate and relevant Curriculum The Curriculum is made by considering local characteristic 1 SC_001 The Curriculum is made by considering the social needs in society 2

SC _002
The Curriculum is made by considering the learning needs

SC _003
The Curriculum has showed the remedial program plan 4 SC _004 School provides the needs of students' improvement School provides a service of guidance and counceling 5 SC _005 School provides ex-school to meet the students' needs 6 SC _006 Source: Government regulation number 32 in 2013, Poerwati & Amri (2013) The Teacher motivates the students 27 SP_004 The learning process is done by usig interactive learning method Teacher does the learning process based on interactive lesson plan

SP_005
Teacher delivers the goal of the learning process in the beginning

SP_006
Students have a same chance to explore the learning

SP_007
Students have a same chance to do confirmation 31 SP_008 Source: Government regulation number 32 in 2013, Poerwati & Amri (2013)