Keywords

Learning interest, learning motivation, emotional intelligence, learning achievement.

Introduction

Advances in science and technology resulted in changes in society. These changes resulted in social problems within society. Education here is tasked with solving social problems that occur in society in the form of educational renewal and improvement. Vocational High School (SMK) is one of the educational institutions that have complex activities and its implementation involves many parties. According to BPS data (2019), the number of vocational schools in DKI Jakarta is 581 vocational schools and as many as 224,600 thousand students studying in it. SMK Negeri 46 Jakarta has 3 expertise programs, namely Business & Management and Art, Information and Communication Technology, and Art and Creative Industries.

Measurement of student Financial Accounting learning achievement always pays attention to indicators that have been determined in advance. These indicators are in the form of knowledge, skills, and attitudes that must be acquired by students in order to be said to have mastered and understood the subjects that have been given. Each basic competency taught to students has different indicators. The achievement of studying Financial Accounting at 46 Vocational high schools Jakarta is measured by a written test or test.

The achievement of studying Financial Accounting is influenced by many factors. These factors come from within the student (internal) and from outside the student (external). One of the factors that affect learning achievement is the internal factor which includes psychological factors in which there are an interest in learning. Interest is a fixed tendency to pay attention and reminisce about some activity. Interest is very closely related to the feelings of individuals, objects, activities and situations. So it is clear that the interest in learning something, then the expected result is better than someone who is not interested in learning something (Haryati, 2017).

The next factor that affects learning achievement is learning motivation. Learning motivation has an important role in providing passion, enthusiasm and a sense of pleasure in learning. Students who are highly motivated are better able to participate in learning and make fewer mistakes in learning (Haryati, 2017). The last factor that affects the low achievement of learning Financial Accounting is the emotional intelligence of students. Intelligence is a behavior that is learned as a consequence of environmental influences and then actually behavior is formed because it is learned (Haryati, 2017). The lack of emotional intelligence possessed by students in the subject of Financial Accounting is caused by students being teenagers so they often experience unstable squeezes, resulting in a lack of empathy for others, selfishness, and difficulty managing feelings.

Literature Review

Interest in Learning

According to Singh (2011) mentions that interest is a high tendency and excitement or a great desire for something. Meanwhile, interest is a sense of liking or a sense of attachment to a thing or activity without anyone telling you to. From the explanations of the experts above, it can be concluded that the interest in learning is curiosity followed by a sense of desire and interest in learning activities with a sense of pleasure without coercion from any party.

According to Singh (2011) states that the factors that affect interest in learning are divided into three, namely: Internal factors, namely factors that come from within students. This factor is divided into two, namely physiological and psychological, external factors, namely factors that come from outside the student. This factor consists of two kinds of yairu social environment and non-social environment, and yairu learning approach factor that contains strategies used by students to support the effectiveness and efficiency of the process of studying certain materials.

Djamarah (2013) stated that the ways that teachers can do to arouse the interest of students are as follows: Comparing the existence of a need in the protégé, so that he is willing without coercion, Linking the lesson materials provided with the problem of experience that students have, so that students easily accept lessons , Providing opportunities for students to obtain good learning outcomes by providing a creative and conducive learning environment, and Using a variety of teaching forms and techniques in the context of students' individual differences.

According to Syahputra ( 2020) students who have a high interest in learning, have the following indicators: Students' desire to participate in learning, Sense of interest in learning activities, Have high active participation in learning, Student understanding in participating in learning Have a higher sense of attention in learning than anything else.

Learning Motivation

According to Sardiman (2018) motivation is something complex, motivation causes changes in the occurrence of energy changes in the human being that are related to psychiatric processes, feelings, and also emotions used at the time of performing an action. Meanwhile, according to Ngalim (2017) motivation is an absolute thing for students when studying. Kurniadin & Machali (2012) stated that motivation is something to increase work productivity so that it affects the achievement of goals, individuals, groups, and organizations.

According to Kurniadin & Machali ( 2012) the functions of learning motivation are: Motivation serves as energy or driving motor for students, Motivation serves to regulate in choosing alternatives between two or more activities that contradictory, and Motivation serves as a regulator or determines the direction of goals in carrying out activities.

According to Hamalik & Supriyono ( 2000) motivation can be divided into two types, namely: Intrinsic motivation is motivation that includes in learning situations, meeting needs and goals– student objectives, Extrinsic motivation is motivation caused by factors from outside the learning situation, such as credit numbers, diplomas, prize levels, conflict medals, and competition that are negative in nature, sarcasm, ridicule, and punishment, and According to Sardiman (2018) how to move learning motiavsi, namely: Giving numbers, gifts, rivals / Competitions, self-esteem, assessing tests, knowing results, praise, punishment, desire to learn, interests, and recognized goals.

According to Wena ( 2018) indicators of learning motivation in students include: Student awareness to follow learning, The level of students' desire to have good grades, the level of students' desire to do assignments according to the specified time, and It is not easy to get bored in following learning.

Emotional Intelligence

According to Yusuf (2018) emotions are a complex psychological aspect of a normal homeostatic state that begins with a psychological stimulation. Meanwhile, according to Djaali (2018) emotions are effective experiences accompanied by overall mental experiences where the physical and mental states are in an excited state by showing behavior that real and clear.

According to Goleman (1997) states that the main aspects in emotional intelligence that make an individual a humanist figure are the following: Self-awareness, managing feelings, communication, and opening up, understanding, group dynamics, and resolving conflicts.

According to Goleman (1997) states that emotional intelligence is said to be low if the person does not have emotional balance, is selfish, self-oriented oriented, cannot adjust to the burden that is being faced, and always restless. This selfishness causes people to be unable to get along with their surroundings, do not have good self-mastery.

According to Goleman ( 1997) indicators of emotional intelligence include: Recognizing and feeling his own emotions, managing his own emotions, being able to use his emotions for activities that good, Able to recognize the emotions of others, and can cultivate relationships with others.

Hypotheses

Based on the study of theories and thinking frameworks, hypotheses can be proposed as temporary answers to the problems faced, namely as follows:

H₁: There is an influence of interest in learning on learning achievement
H₂: There is an influence of learning motivation on learning achievement
H₃: There is an influence of emotional intelligence on learning achievement
H₄: There is an influence of interest in learning, motivation to learn, and emotional intelligence on learning achievement.

Methods

Sample and Data Collection

Researchers will conduct research on accounting students of SMK Negeri 46 Jakarta which is located at Jalan B7 Cipinang Pulo, Jatinegara, East Jakarta. The research time was carried out for 3 months starting from May 2022 to July 2022. The population of this study is all class XI and XII students at SMK Negeri 46 Jakarta for the 2020/2021 school year. While the affordable population is class XI and XII students of the Accounting Department at SMK Negeri 46 Jakarta which consists of two classes from each batch. This study used sampling by means of Propotional Random Sampling or proportional random samples. Proportional Random Sampling is a sample and is taken in such a way that each research unit or unit of an element of the population has an equal chance of being selected as a sample. (Andriani et al., 2018). The sample in this study was taken based on the Isaac and Michael table with an error rate of 5%. With an affordable population of 144 people, 105 students can be taken as samples in this study.

Data Analysis

This research uses a quantitative approach, so the data analysis technique uses statistical data. Data analysis in this study used regression analysis techniques. SPSS (Statistical Package for Social Science) program version 22 which is used to help the data analysis process. The analytical techniques used in this study are as follows:

Multiple Regression Analysis

Multiple regression analysis is also used to determine the magnitude of the influence of two or more free variables on one bound variable. According to Andriani et al. (2018) multiple linear regression analysis can be formulated as follows:

Test Analysis Requirements

Normality test: Statistically the normality test was carried out with the Kolmogorav- Smirnov or Shapiro Wilk test. The Kolmogorav-Smirnov test was used for large samples (>50) while Shapiro Wilk for small samples (<50). In the normality test, this study used the Kolmogorav-Smirnov test or through the Normal Probability Plot. The hypothesis of testing using the Kolmogorav-Smirnov test, namely: H₀= If the data is normally distributed and H₁= If the data is abnormally distributed

Linearity test: This test aims to find out whether the variables studied have a linear influence with other variables. The basis for decision making in the linearity test is: If the significance value < 0.05, then the relationship between the variables X and Y is linear and If the significance value > 0.05, then the relationship between the variables X and Y is not Linear.

Hypothesis Test

Regression coefficient test together (F Test): According to Supranto & Abdullah (2017) the formula of the value of F is obtained by:

With the value of F-count compared with the value of F-table, with degrees of freedom df denominator n–k and df numerator k–1. And the decision-making criteria of the F test are as follows: If F counts ≤ F table, then Ho is accepted and If F counts > F table, then Ho is rejected.

Partial regression coefficient test (t test): The partial regression coefficient test (Test t) aims to find out whether in the independent variable regression model (X) partially has a significant effect on the dependent variable (Y). According to Andriani et al. (2018) this test formula is calculated by:

Coefficient of determination test: The coefficient of determination test is used to measure the extent of the regression model's ability to describe variations in free variables. The value of the coefficient of determination is in the range from 0 to 1 (0<R described in percentage size. A small R² value means the ability of free variables to describe finite bound variable variations. Whereas a value close to one free variable provides almost all the information needed to predict the variation of bound variables. According to Andriani et al. (2018) the formula is:

Results

Multiple Regression Analysis

The calculation of the results of multiple regression analysis using SPSS version 26, as follows:

Based on the Table 1 above, the multiple regression equation can be expressed as follows:

Table 1 Multiple Regression Analysis
Unstandardized Coefficients			Standardized Coefficients Beta	t	Sig.
Model B		Std. Error
(Constant)	86.681	5.613		15.443	0.000
Interest in Learning (X1)	0.1 91	0.084	-0.289	-2.270	0.025
Learning Motivation (X2)	0.1 24	0.109	0.156	1.137	0.258
Emotional Intelligence (X3)	057	0.103	0.076	0.549	0.584

In the multiple regression equation, it is indicated that 86.681 is the value of the constant (a),-0.191 as the value of the coefficient b 1, 0.124 as the value of the coefficient b 2, 0.057 as the value of the coefficient b3. The coefficient values of b1, b2, and b3 are positive, which means that if interest in learning, motivation to learn, and emotional intelligence increase, then learning achievement also increases.

Test Analysis Requirements

Normality Test

Based on the data in the Table 2 above, the significance value shows the number 0.078. The figure indicates that the significance value is more than 0.05, which means that the data is normally distributed. It can be concluded that the distribution of questionnaire data meets the normality requirements, so that the data can be tested for subsequent analysis requirements. The normality of the data can also be seen from the following figure:

Table 2 One-Sample Kolmogorov-Smirnov Test Unstandardized Residual
N		146
Normal Parametersa,b	Mean	0.0000000
	Std. Deviation	7.78825213
Most Extreme Differences	Absolute	0.181
	Positive	0.095
	Negative	-0.181
Test Statistics		0.181
Asymp. Sig. (2-tailed)c		<0,061
Monte Carlo Sig. (2-tailed)d Sig.		0.078
a.Test distribution is Normal. b. Calculated from data. c.Lilliefors Significance Correction.

Decision making using Normal Probability Plot, that is, if the data spreads around the diagonal line and follows the direction of the diagonal line, the regression analysis meets the normality requirement, on the other hand, if the data spreads away from the diagonal line , the regression analysis does not meet the normality requirement. In the Figure 1, it can be seen that the data spreads around the diagonal line and follows the direction of the diagonal line, so the regression analysis meets the normality requirements.

Linearity Test

Based on the data in the Table 3 above, the deviation value from linearity shows the number 0.240. The figure indicates that the deviation value from linearity is more than 0.05, which means linear data. It can be concluded that the variables of Learning Interest (X1), Learning Motivation (X2), and Emotional Intelligence (X3) have a linear relationship.

Table 3 Deviation Value
Sumof Squares				Df	Mean Square	F	Sig.
Unstandardized Residual*	Between Groups	(Combined)	6629.848	104	63.749	1.207	0.251
		Linearity	0.000	1	0.000	0.000	1.000
Unstandardized Predicted Value
		Deviation from Linearity	6629.848	103	64.367	1.219	0.240
	Within Groups		2165.399	41	52.815
	Total		8795.246	145

Hypothesis Test

Partial Regression Coefficient Test (T Test)

The interest in learning (X1) has a t count of -2.179, a table t of 1.97635 obtained from df=n-k i.e. 146-3=143 with a significant degree of 0.05/2=0.025. So that in the learning interest variable (X1), t counts less than t of the Table 4. The next variable, namely Learning Motivation (X2) has a t count of 1.113. While t table of 1.97635 obtained from df=n-k-1 is 146-3=146 with a significant level of 0.05/2=0.025. So that in the study habit variable (X2), t count less than t table. While the Emotional Intelligence variable (X3) has a t count of 0.518, t table of 1.97635 obtained from df=n-k-1 which is 146-3=146 with a significant level of 0.05/2=0.025. So that in the emotional intelligence variable (X3), t counts less than t of the table.

Table 4 Partial Regression Coefficient Test( T Test )
Coefficientsa
Type		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	86.562	5.619		15.406	0.000
	INTEREST LEARNING (X1)	-0.185	0.085	-0.279	-2.179	0.031
	LEARNING MOTIVATION (X2)	0.122	0.109	-0.153	1.113	0.267
	EMOTIONAL INTELLIGENCE (X3)	0.054	0.104	-0.072	0.518	0.605
a. Dependent Variable: LEARNING ACHIEVEMENT (Y)

The basic criteria for decision making in the F test, namely if f calculates > f table then there is a significant influence of free variables together on bound variables, whereas f calculates < f the table then there is no significant influence of free variables together on bound variables. Based on the data in the Table 5 above, it can be seen that the calculated f value is 16.25, f table is 3.06 obtained from df (k, n-k) which is df (2, 105-2) with a significant level of 0.05. So that the value of f count is greater than f of the table. It can be concluded that there is a significant influence of the variables of interest in learning (X1), motivation to learn (X2), and emotional intelligence (X3) together on the variables of learning achievement (Y).

Table 5 Regression Coefficient Test Together (F Test)
ANOVAa
Type		Sum of Squares	Df	Mean Square	F	Sig.
	Regression	302.875	3	100.958	16.25	.186b
1	Residual	8.819.653	142	62.110
	Total	9.122.527	145
a. Dependent Variable: LEARNING ACHIEVEMENT (Y)
b. Predictors: (Constant), EMOTIONAL INTELLIGENCE (X3), LEARNING INTEREST (X1), LEARNING MOTIVATION (X2)

Multiple Regression Analysis

Based on the data in the Table 6 above, it can be seen that the value of r square is 0.360. So that the determination value is 36%. It can be concluded that the influence of the learning interest variable (X1), the learning motivation variable (X2), and emotional intelligence (X3) together has a contribution percentage of 36% to the learning achievement variable (Y). While the remaining 64% was influenced by other factors that were not studied in this study.

Table 6 Multiple Regression Analysis
ModelR		R Square	Adjusted R Square	Std. Error of the Estimate
1	0.189a	.360	0.160	7.870
a.Predictors: (Constant), EMOTIONAL INTELLIGENCE (X3), LEARNING INTEREST (X1), LEARNING MOTIVATION (X2) b.Dependent Variable: LEARNING ACHIEVEMENT (Y)

Discussion

The Effect of Interest in Learning on Learning Achievement

Based on the data analysis and hypothesis testing that has been carried out in this study, it can be concluded that the interest in learning has a partially significant positive influence on learning achievement. Then based on the multiple regression equation, it indicates that if the interest in learning has increased, then learning achievement has increased as well.

The results of this study are in line with previous studies, greater interest causes students to be more enthusiastic about learning hl this can affect student learning achievement which can increase optimally. Research according to Kpolovie et al. (2014), students ' interest in learning has a link to students' life choices that can significantly affect student learning achievement. From the point of view of the student and what he wants to achieve pedagogically, taking into account his interests may be of practical importance so that learning achievements can be achieved to the maximum.

Research according to Darajaad (2016), interest in learning is an energy that students have when doing learning. This is in the form of how students are interested in the learning. Learning without interest is very difficult to achieve optimal success later. In research interest in learning achievement is an inseparable whole. This is because, when a person's interest in learning increases, it can also be ascertained that student learning achievement will increase as well.

The Effect of Learning Motivation on Learning Achievement

Based on the data analysis and hypothesis testing that has been carried out in this study, it can be concluded that learning motivation has a partially significant positive influence on learning achievement. Then based on the multiple regression equation, it can be that if the motivation to learn increases, then learning achievement increases as well.

The results of this study are in line with previous studies, such as the research conducted by student motivation is a goal-oriented theory. So that when students have schoolwork, they set different personal goals and types of goals that have a direct influence on their academic success. Therefore, when students have high learning motivation, the student's learning achievement will increase. Learning motivation is a goal owned by students to obtain high scores in learning. In this case, when the student has determined the purpose of learning motivation, the student will get more optimal learning achievement.

Research conducted by Krijgsman et al. (2017), the increase in learning achievement is due to the high learning motivation possessed by students. Whereas according to research Krijgsman et al. (2017), considers motivation as an inherent belief that guides individual learning goals, encourages persistent learning behaviors, strengthens cognitive history, and strengthens and improves learning outcomes.

The Effect of Emotional Intelligence on Learning Achievement

Based on the analysis of data and hypothesis testing that has been carried out in this study, it can be concluded that emotional intelligence has a partially significant positive influence on learning achievement. Then based on the multiple regression equation, it can be that if the motivation to learn increases, then learning achievement increases as well.

The results of this study are in line with previous research, such as research conducted by Febiyanti & Rachmawati (2021), Emotional intelligence is the ability to recognize emotions or feelings of one and others and be able to manage their emotions. This is very useful when students are able to control their emotions, then the student will be more receptive to the learning provided so that student learning achievement will increase. Research according to Ike et al. (2016), this emotional intelligence can be used to filter information received through actions and thoughts. This is useful for students to more easily absorb the given learning material. This can improve student learning achievement.

According to Ardian et al. (2019), emotional intelligence (EQ) is the ability to recognize and understand the emotions of one and others (empathy). The ability to create selfmotivation. The ability to manage emotions both for oneself and in relationships with others and the ability to interact with others. This positively affects the success at the end of the study. Emotional intelligence also has a beneficial effect on students ' fieldwork. It is because of this that emotional intelligence greatly affects the learning achievement of students.

The Effect of Interest in Learning, Learning Motivation, and Emotional Intelligence on Learning Achievement

Based on data analysis and hypothesis testing that has been carried out in this study, it can be concluded that there is a significant influence of variables of interest in learning, motivation to learn, and emotional intelligence together on the variables of learning achievement. Then to find out how much the percentage of contribution influences the variables of interest in learning, motivation to learn, emotional intelligence together–the same for the variable of learning achievement, it is carried out by analyzing the coefficient of determination. It can be concluded that the influence of learning interest variables, learning motivation variables, and emotional intelligence together has a percentage contribution of 36% to the learning achievement variable. While the remaining 64% was influenced by other factors that were not studied in this study.

The results of this study are in line with previous studies, such as research conducted by Irawan ( 2016), good learning achievement also requires good emotional intelligence as well, because learning achievement also reflects ability in affective aspects. Actually, psychological factors that affect learning achievement include talents, attitudes, interests, motivation and intelligence. So that when students have a high interest in learning, students will be more enthusiastic about learning. Meanwhile, when students have high learning motivation, students will focus more on the goals they want to achieve namely maximum learning achievement. And for emotional intelligence, when students have stable emotions, students will more easily absorb the learners given so that they can improve their learning achievement as well.

Conclusion

Based on the results and discussion of research that has been made, it can be concluded as follows:

1. The interest in learning has a significant positive impact on student learning achievement at 46 Vocational high schools Jakarta. This shows that interest in learning and learning achievement have a unidirectional relationship. This means that if the interest in learning increases, then student learning achievement will increase as well. On the other hand, if interest in learning decreases, learning achievement will decrease as well.

2. Learning motivation has a significant positive impact on student learning achievement at SMK Negeri 46 Jakarta. This shows that learning motivation and learning achievement have a unidirectional relationship. This means that if the motivation to learn increases, then student learning achievement will increase as well. On the other hand, if learning motivation decreases, learning achievement will decrease as well.

3. Emotional intelligence has a significant positive impact on student learning achievement at 46 Vocational high schools Jakarta. This shows that emotional intelligence and learning achievement have a unidirectional relationship. This means that if emotional intelligence increases, then student learning achievement will increase as well.

4. Interest in learning, motivation to learn, and emotional intelligence together have a significant positive influence on student learning achievement at 46 Vocational high school Jakarta. This shows that interest in learning, motivation to learn, and emotional intelligence with learning achievement has a unidirectional relationship. This means that if interest in learning, motivation to learn, and emotional intelligence increase, then student learning achievement will increase as well. On the other hand, if interest in learning, motivation to learn, and emotional intelligence decrease, learning achievement will decrease as well.

Acknowledgement

In this study, researchers realized that there were several limitations in conducting research, namely:

1. This research was conducted with a limited sample consisting of only class XI and XII students majoring in Accounting at 46 Vocational high schools Jakarta.

2. The study was conducted during the COVID-19 pandemic, causing researchers to be limited in understanding the characteristics of the sample (students) in depth.

3. The samples in the study are still general without paying more attention to the differences in one sample from another such as gender, age, and others.

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Received: 03-Mar-2023, Manuscript No. AJEE-22-13289; Editor assigned: 06-Mar-2023, Pre QC No. AJEE-22-13289(PQ); Reviewed: 20- Mar-2023, QC No. AJEE-22-13289; Published: 28-Mar-2023