GROSS (GDP) IN INDONESIA

This study aims to analyze tea exports and imports of gross domestic product in Indonesia. The data used in this study is secondary data sourced from BPS, the research model uses multiple linear regression. The results of the study partially show that tea exports have a positive and significant effect on Indonesia's gross domestic product, tea imports have a negative and significant effect on gross domestic product in Indonesia. Taken together, tea exports and imports have a positive and significant effect on gross domestic product in Indonesia. The recommendation is that the government is expected to develop the existing tea export market. Producing Indonesian tea is not only for the domestic market, but also for exporting Indonesian tea products abroad.


INTRODUCTION
Economic growth is very important for increasing the welfare of the people of a country. Increased economic growth is an indication of an increase in income, which in turn reflects the level of welfare. The importance of economic growth for improving people's welfare encourages the government of each country to try to increase its economic growth. Even economic growth in a country is often used as a benchmark for the government's success in improving the standard of living of its people. The indicator of economic growth that is often used is the Gross Domestic Product (GDP). GDP is basically the value of goods and services produced by the people of a country in a certain period of time calculated based on constant prices. (Aimmon, 2017). One important indicator to determine the economic conditions in a country in a certain period is the Gross Domestic Product (GDP) data, both at current prices and at constant prices. GDP is basically the total added value generated by all business units in a particular country, or is the total value of final goods and services produced by all economic units.
GDP at current prices illustrates the added value of goods and services calculated using prices that apply each year, while GDP at constant prices shows the added value of these goods and services calculated using prices prevailing in a particular year as a basis.GDP at current prices can be used to see shifts and economic structure, while constant prices are used to determine economic growth from year to year. Based on the above understanding, it can be concluded that economic growth is a process of increasing the productive capacity of the economy in a comprehensive and continuous manner, so that it can generate greater national income. You can see below the tables and figures on the development of tea exports and imports on economic growth in Indonesia in 2011-2020 as follows:  The table above can be explained through the following graphs to provide a complete picture of the development of the Gross Domestic Product (GDP) in Indonesia. Based on figure 1.1. it can be seen that the movement of the Gross Domestic Product (GDP) in Indonesia in 2011-2020 tends to experience a very significant increase every year. From these data we can see that the Gross Domestic Product (GDP) in 2011 was Rp.728,764 billion to reach a Gross Domestic Product (GDP) of Rp. 1,072,244 billion in 2020. Thus it can be seen that Indonesia's Gross Domestic Product (GDP) has increased quite significantly from year to year.The increase in the Indonesian economy was mainly driven by increased performance in exports, household consumption, investment and government consumption. The government is expected to maintain economic stability in Indonesia which can be seen from GDP because GDP has a large influence on the entry of foreign investment into Indonesia.
Export and import activities are one of the most important factors for increasing economic growth. Export and import activities provide benefits for a country that participates in them. Exports are one of the sources of foreign exchange that are urgently needed by countries whose economies are open, because exports can work widely in various countries which will enable an increase in the amount of production that encourages economic growth so that it is expected to make a major contribution to the growth and stability of the country's economy. Meanwhile, through imports, the country can meet its domestic needs which cannot be produced domestically so that the costs incurred for a product of goods and services will be cheaper. .
Exports are sales between two countries that are able to exert influence in order to increase domestic demand resulting in large industrial factories, and can provide impetus in the dynamics of foreign trade growth so that later developing countries can compete with developed countries. Romance (2018) inRamadhani et al., (2021. Exports can expand markets and make it possible for exporting regions to free up capital to import other goods has long been demonstrated by classical economists. Mainstream economics has long emphasized economic development, including capital goods. Rapid export growth will rapidly increase overall spending levels, which in turn can stimulate the acceleration of a developing economy (Kurniawati & Islami, 2022). According to (Khrisnawardhani, 2012) exports will encourage the growth of a country by increasing the consumption capacity of a country and increasing world output, as well as providing access to scarce resources and potential international markets for various export products which are without these products, then Poor countries will not be able to develop their national economic activities and life.
Tea exports in Indonesia have been divided into two types, namely Green Tea and Black Tea. According to ITC (2017) during 2007-2016 Indonesia has become a tea exporter, most of which is in the form of green tea. However, in 2007 Indonesia exported more black tea than green tea, amounting to US$ 30,119. In the following year, Indonesia focused on green tea exports, where green tea exports annually exceeded black tea exports.Tea-producing areas in Indonesia are in mountainous areas such as in the provinces of North Sumatra, Jambi, South Sumatra, West Java, Central Java and East Java. In the province of West Java, tea plantations are located in several districts, such as Bogor, Sukabumi, Garut and Bandung. Based on the Tea Market Attractiveness analysis which looks at tea consumption per capita and the level of economic growth that influences tea consumption, it can be seen that the potential market for Indonesian tea exports is to several countries including Malaysia, USA, Pakistan, China, Europe and Australia. The world market today also prefers tea that is safe for consumption, which of course has been certified.
Most of Indonesian tea (70%) is exported so that Indonesia is listed as the fifth largest tea exporter in the world after Kenya, Sri Lanka, India and Vietnam. However, the price of Indonesian tea on the international market is still very low, that is, it is exported raw, priced at only US$ 1 per kilogram. It is very unfortunate indeed, amidst the increasingly exciting growth in world demand for tea, the domestic tea productivity is in a very apprehensive condition. In fact, if managed properly, this sector will be able to increase the country's foreign exchange and reduce unemployment, which today is a serious problem for the nation. The real condition is that the tea export market is still wide open. It can be seen from the lack of world tea supply which causes an excess demand of 13 thousand tons per year. It is estimated that in the following years the world demand for tea may increase and this condition must be followed by an increase in export offers from tea producing countries. This is an opportunity for Indonesia to increase the supply of tea exports to the world market(Sidabalok, 2017). The following is the movement in the value of Indonesian tea exports from 2011-2020, seen in Figure 1.2 as follows: Based on Figure 1.2, it can be seen that the movement of tea exports in Indonesia in 2011-2020 tends to experience a very significant decline. This decline was caused by several other constraints that reduced tea production, apart from land. The obstacles include rising production costs, low quality, and standardization targets that have not been met at the national and international levels. Then production equipment that is not yet modern, human resources, and prices at the farmer's level are still low. But tea exports experienced an increase in tea exports in 2013, 2017 and 2019 due to the fact that the world's demand for tea is of course very high considering that tea is part of a lifestyle. Import activity is an activity of purchasing or importing goods from abroad into the country. Large import activities will cause demand for other countries' currencies to increase so that the domestic currency weakens. According to Sedyaningrum (2016) high import activity will also reduce domestic production as a result, unemployment will increase and income will decrease so that people's purchasing power will also decrease. (Ismanto et al., 2019).
The positive impacts that limit imports in general are growing a sense of love for products made in the country, minimizing the release of foreign exchange reserves abroad, and also reducing the attitude of addiction to imported goods, as well as strengthening the position in the balance of payments (Mustafa & Andriyani, 2020). Tea is one of the main plantation commodities which has an important role in the Indonesian economy.There are quite a lot of imported tea in Indonesia, even though this country is rich in tea commodities. It turned out that the main cause was the cheap tea import duties in Indonesia. Director General of Foreign Trade of the Ministry of Trade Bachrul Chairi explained, the highest tea import duty in the world's tea producing countries is in Turkey with a percentage of 105%. Meanwhile, tea import duties in Indonesia are only 5%. Our tea import duties are the lowest, only 5%. China 15-30%, Sri Lanka 30%, Vietnam 50%, Russia 20%, Iraq 15%, even Turkey 105%. So that Indonesia is also a tea importer, but what is imported is low quality tea imports.
The Central Statistics Agency (BPS) report shows,importIndonesia's largest tea comes from Vietnam.In total, the supply of tea from other countries to Indonesia amounted to 14,909 tons with a value of US$ 25.85 million. Indonesia's tea imports come from various countries with more than 58 countries as tea suppliers. The largest volume of Indonesian tea imports is from Vietnam as much as 9,769 tons. This amount is equivalent to 65.52% of the total volume of tea imports to Indonesia with a value of US$ 9.4 million. Kenya is in second place with a volume of tea imports of 2,668 tonnes or 17.90%. India is third, with a volume of tea imports of 593 tons. The fourth and fifth positions are Malaysia and Thailand with tea import values of 451 tons (3.02%) and 394 tons Based on table 1.3 above, it can be seen that the movement of tea imports in Indonesia during the 2011-2020 period experienced fluctuations. In 2019 tea imports increased by US$ 36,037 million. This is because tea exports in 2019 experienced a decline which caused tea imports in Indonesia to increase. Furthermore, in 2020 tea imports decreased from US$ 36,037 million to US$ 25,857 million, a decrease of US$ 10,180 million. This is due to the covid-coronavirus pandemic. The value of imports fell due to the stronger dollar so that the market had more expectations of domestic products. The authors in this study took a time span of 10 years, namely from 2011-2020. From the description above, the authors are interested in analyzing the extent of the influence of tea exports and imports on Gross Domestic Product (GDP) in Indonesia. Because of that, the author raised the title "Export and Import Analysis of Gross Domestic Product (GDP) in Indonesia"

LITERATURE REVIEWS Tea Plant
The tea plant (synthetic camellia) is thought to have originated in Southeast Asia in 2737 BC tea was already known in China. Even since the 4th century AD, tea has been used as a component of medicinal herbs. Tea was first introduced by Dutch traders as a trading commodity in Europe in 1610 AD and has become a popular drink in England since 1664 AD (Ghani, 2002). Tea plants can grow from the coast to the mountains. In the mountainsAssam, tea is grown at an altitude of more than 2000 m asl. However, tea plantations are generally developed in mountainous areas with cool climates. Although it can thrive in lowland, tea plants will not produce good quality results. The higher the tea cultivation the higher the quality. (Ghani 2002).

Gross Domestic Product (GDP)
Gross domestic product (GDP) is the total production (output) produced by the government. GDP is the value of goods and services produced in a country in a certain period. Gross domestic product is a concept in calculating national income. In macroeconomic analysis, the term "national income" or "national income" is always used and this term is usually intended to express the value of goods and services produced in a country. Thus, in this concept, the term national income represents the meaning of gross domestic product (GDP) or gross national product (GNP) (Sukirno, 2015).

Export
Export is an activity of sending goods or services from within the country to abroad. Export is an achievement in delivering goods or services abroad to buyers across the ocean. Export is an activity of moving goods or services from one country to another. (Sutedi, 2014). According to Sukirno (2010), the most important factor in determining exports is the country's ability to produce goods that can compete in foreign markets. In this case both the quality and price of the goods to be exported must be as good as those traded in foreign markets. In addition to price, the tastes of consumers abroad have an important role in determining a country's exports. Export is an effort to sell commodities that our country has to other countries or foreign nations in accordance with government regulations by expecting payments in foreign currencies, as well as communicating in foreign languages Amir (2001) in . Meanwhile, according to Todaro (2004) exports are international trade activities carried out in order to foster stimulation of domestic demand which results in the growth of large industries, together with stable and flexible political structures and social institutions. As described above, international trade activities, in this case exports, will greatly support domestic production activities.

Import
Import is the process of legally transporting goods or commodities from one country to another, generally in the trading process. The import process in general is the act of bringing goods or commodities from other countries into the country. Large imports of goods require intervention from customs in both sending and receiving countries. Imports are an important part of international trade . Import is the purchase or entry of goods from abroad into a domestic economy (Sukirno, 2006). Imports greatly affect a country's economic growth, as explained in the Hecksher-Ohlin theory which states that a country will import products/goods that use factors of production that are not or rarely owned by that country. This activity will benefit the country compared to self-producing but not efficiently (Pridayanti, 2013)

Object of research
The object of this study is the analysis of tea exports and imports of Gross Domestic Product (GDP) in Indonesia. The location in this research is Indonesia.

Data collection technique
The type of research used in this research is quantitative research, where the data obtained is presented in the form of numbers and analyzed using statistical and econometric methods. The data used in this research is time series data. Time series data is data that describes a development over time or a historical period. The data used by researchers is secondary data sourced as follows: 1. Indonesia's GDP data for 2000-2020 from the Indonesian Central Bureau of Statistics (BPS). 2. Indonesian tea export data for 2000-2020 from the Indonesian Central Bureau of Statistics (BPS). 3. Indonesian tea import data for 2000-2020 from the Indonesian Central Bureau of Statistics (BPS).

Operational Definition
The variables used in this study are as follows:

Gross Domestic Product (Y)
Gross domestic product is data taken from the value of Indonesia's GDP at constant prices for the period 2000 to 2020 in billions of rupiah.

Export (X1)
Exports are the value of Indonesian tea exports as seen from the period 2000 to 2020 in units of US$ million. 4. Import (X2)

Data analysis method
The method of data analysis in this study is a quantitative research. According to Saebani (2007) quantitative research is research that uses numbers in data and analysis using statistical tests. To analyze the related data in this study by testing causal relationships using multiple linear regression, the aim is to find out how much influence the independent variables have on the dependent variable. In this study, the data analysis method uses multiple linear regression. Multiple linear regression analysis is a linear relationship between two or more independent variables (X1, X2, ….. Xn) with the dependent variable (Y), namely: tea exports (X1), tea imports (X2), to the dependent variable GDP (Y ).

Y = α + β1logX1 + β2logX2 + ei
=Indonesian tea export X2 =Indonesian tea imports ei = Error Term The above equation is the model used in this study which will explain the independent variable to the dependent variable to obtain parameter estimates, the OLS (Ordinary Least Square) technique is used.

Normality test
The normality test aims to test whether in the regression model, the confounding or residual variables have a normal distribution. If there is normality, then the residuals will be normally and independently distributed, i.e. the difference between the predicted value and the actual score or the error will be distributed symmetrically around the mean value equal to zero. (Ghozali, 2012) to test the normality of the data, to see the normality of the residuals the author looks at with Jarque-Bera. According to Winarno (2009) normality can be detected by looking at histogram images, but often the pattern does not follow the normal curve, making it difficult to draw conclusions. It's easier to look at the Jarque-Bera coefficient and the probability that these two numbers are mutually supportive.
1. If the JB value is not significant (smaller than 2), then the data is normally distributed. 2. If the probability is greater than 5% (if you use that level of significance), then the data is normally distributed (the null hypothesis is that the data is normally distributed).

Test Multicollinearity
The multicollinearity test is a situation where there is a correlation between one independent variable and another independent variable. The multicollinearity test is one of the tests in the classical assumption which is used to find out whether the independent variables in this study have a relationship or not. A good multiple linear regression model is that there is no relationship between the independent variables (Widarjono, 2017). To find out the results of the multicollinearity test, it can be seen through the centered VIF value.

Test Heteroscedasticity
The heteroscedasticity test is used to test whether in the regression model there is an inequality of variance from one residual observation to another. Whether or not heteroscedasticity occurs in the multiple linear regression model, namely by looking at the calculated F value (Widarjono, 2007). count is less than the level of 0.05 (5%) then there is heteroscedasticity which means Ho is rejected.

Autocorrelation Test
The autocorrelation test aims to test whether in multiple linear regression there is a correlation between the confounding errors in period t and the confounding errors in the t-1 (previous) period. If there is a correlation, then there is called an autocorrelation problem. Autocorrelation arises because successive observations over time are related to one another. This problem arises because the residuals (confounding errors) are not independent from one observation to another. This is often found in time series data due to disturbances in the same individual or group in the next period. In cross-sectional data, autocorrelation problems are relatively rare because the disturbances in different observations come from different individuals or groups. A good regression model is a regression that is free from autocorrelation (Ghozali, 2012).

Hypothesis test Partial test (t)
The t test was conducted to see the effect of the independent variables on the dependent variable partially. The criteria in the test is if t count > t table with a significant level of 5%, it can be concluded that partially the independent variables have a significant effect on the dependent variable. If tcount < ttable with a significant level of 5%, it can be concluded that the independent variables have no effect on the dependent variable (Ghozali, 2006).

Test f
The f test was carried out to see the effect of the independent variables together on the dependent variable with a significant value of f, if f count > f table with a significant level of 5%, it can be concluded that partially the independent variables have a significant effect on the dependent variable. And conversely, if f count <f table with a significant level of 5%, it can be concluded that the independent variables have no effect on the dependent variable (Ghozali, 2006).

Correlation Coefficient (R) and Determination (R 2 )
The coefficient of determination (Adjusted R²) basically measures how far the model's ability to explain the variation of the dependent variable. The value of the coefficient of determination is between zero and one. The small adjusted R² value means that the ability of the independent variables to explain the variation in the dependent variable is very limited. A value close to one means that the independent variables provide almost all the information needed to predict the variation in the dependent variable (Ghozali, 2012). According to Gujarati in Ghozali (2012) if the empirical test results in a negative adjusted R² value, then the adjusted R² value is considered to be zero. Mathematically, if the value of R² = 1, then adjusted R² = R² = 1, while if the value of R² = 0, then adjusted R² = (1-k)/(nk), if k . 1, then adjusted R² will be negative.

RESULTS AND DISCUSSION Normality test
The data normality test was carried out to see whether in the regression model, the dependent variable and the independent variable have a normal distribution or not. To detect normality in the data, the Jarque-Bera test tool is used. By comparing the probability value of Jarque-Bera with α (5% or 0.05). Following are the normality test results obtained from the Eviews 10 program which can be seen in the following figure:

Figure 2
Based on the results of the normality test above, it can be seen that the probjarque-bera> 0.05 which is equal to 15.90 > 0.05it can be concluded that the residuals in this study were normally distributed

Multicollinearity Test
Multicollinearity relates to situations where there is a definite or near-certain linear relationship between the independent variables (Gujarati, 2003). This multicollinearity aims to determine whether each independent variable is linearly related to each other in the regression equation model used. Multicollinearity test results can be seen in Table 4.1 below:  (2022) Judging from table 4.1 above, it can be seen that between the independent factors, especially LOG EX, LOG IM variables in this review, there is no multicollinearity relationship considering that the centered VIF value of each autonomous variable is below 10 or 5. This means that it is free from multicollinearity.

Heteroscedasticity Test
Heteroscedasticity occurs when the residuals and predictive values have a correlation or relationship pattern. The assumption used is that if the calculated X2 value (Obs*R-Squared) <X2 the Obs*R-Squared probability value is > 0.05 or ɑ 5%, then there is no heteroscedasticity problem (Gujarati, 2012). The results of the heteroscedasticity test are as follows:  (2022) The results of the model in the study indicate heteroscedasticity if Obs*R-squared is greater than chi-squared. Based on the table above we can see that Obs*R-squared is smaller than prob. Chi-squared on df(2), namely 5.656 < 5, 99 and a probability of 0.059 > 0.05. So it can be concluded that this research is free from heteroscedasticity.

Autocorrelation Test
Autocorrelation is the existence of a relationship between the confounding errors that appear in the time series data. In the estimation of the linear regression model, it contains the assumption that there is no autocorrelation between confounding errors. According to Gujarati (2012) if the Obs*R-Square value is < X2 (chi-square), then there is no autocorrelation. Furthermore, the results of the autocorrelation test can also be seen by comparing the Chi-Squared probability and a significant value of 5% if the Chi-Squared Prob value is > 5%, then there is autocorrelation. Based on the results of the autocorrelation test using the Eview 10 program:  (2022) Based on the results of the Obs * R-squared output of 0.452 compared to the Chi-Squared table on df (2) of 5.99, then 0.452 <5.99 means that in this model there is no indication of autocorrelation. This can also be seen from the Chi Square Probability of 0.797 > 0.05.

Models and Research Results
This regression test aims to determine how the influence of tea export and tea import variables on gross domestic product variables. Based on the results of the multiple linear regression analysis test with computer aids using the Eview 10 program, it can be seen in Table 8, as follows:  (2022) The model in this study is as follows:

Y = α + β1 logEX + β2 logIM + ei
Based on Table 4.4 above, the multiple linear regression model is as follows: Pdb =5.355939 + 0.9869 logEX -0.2969 logIM From the model above, the results of multiple linear regression analysis can be interpreted as follows: 1. From the above model shows that the constant value is equal to5.3559 means that if tea exports and tea imports are constant (fixed) then the value of gross domestic product will also be constant at 5.3559. 2. The variable coefficient of tea exports has a value of0.9869, This shows a positive relationship. This means that if tea exports increase by 1% then the gross domestic product increases by0.9869% assuming constant tea exports and gross domestic product. 3. The variable coefficient of tea imports has a value of-0.2969, this shows a negative relationship. This means that if tea imports decrease by 1% then gross domestic product increases by 0.2969% assuming constant tea imports and gross domestic product

Effect of Tea Exports on Gross Domestic Product (GDP)
Based on the results of the data processing above, it shows that tea exports have a positive and significant effect on gross domestic product. This is evident from the results of statistical tests with a value (tcount < ttable or 1.925> 1.740 ) so that if tea exports increase by 1% then gross domestic product increases by 0.9869%. This shows that tea exports have a positive and significant effect on gross domestic product in Indonesia. This significant tea export shows thattea exports will directly provide an increase in revenue in a country's income. An increase in a country's income receipts will result in an increase in the level of GDP.

Effect of Tea Imports on Gross Domestic Product (GDP)
Based on the data processing above, it shows that tea imports have a negative and significant effect on gross domestic product. This is evident from the results of statistical tests with a value (tcount > ttable or 2.4781 > 1.740) so that if Indonesian tea imports decrease by 1%then the gross domestic product increased by 0.2969%. This shows that tea imports have a negative and significant effect on gross domestic product in Indonesia. Tea imports have a negative and significant effect.Import activity is an activity of public consumption of goods from abroad. Higher imports are certainly supported by gross domestic product (GDP). Imports are very dependent on gross domestic product, because GDP is one source of import financing.So it can be seen that the increase in tea imports will reduce gross domestic product in Indonesia.Imports will reduce the demand for people in the country. Imports will reduce national income in balance and cause economic problems that will be faced by the country.

CONCLUSIONS Conclusion
Based on the results of research and discussion conducted using multiple linear analysis methods and discussion of the analysis of tea exports and imports of gross domestic product (GDP) in Indonesia, the authors draw the following conclusions: 1. The results of the t test show that the tea export variable has a positive and significant effect on gross domestic product. This is evident from the results of statistical tests with the value of t count > t table, namely 1.925 > 1.740. 2. The results of the t test show that the tea import variable has a negative and significant effect on gross domestic product. This is evident from the results of statistical tests with the value of t count > t table, namely-2.4781 > 1.740 3. The results of the f test also show that the variable exports and imports of tea simultaneously has a positive and significant effect on gross domestic product in Indonesia. This result can be seen from a significant probability0.0381 < 0.05.

Suggestion
1. With the results of the analysis of tea exports and imports to gross domestic product (GDP) in Indonesia. It is expected that the government can develop the existing tea export market. Orienting Indonesian tea production not only to the domestic market, but also to export tea products abroad. considering that Indonesian tea has the potential to become a source of foreign exchange for the country. 2. For academics, this research can be used as reference material for teaching materials or conducting further research which can also be used as material to add insight. 3. For future researchers to expand the limitations in this study, such as extending the research period, increasing the number of other research variables that can also affect gross domestic product (GDP) in Indonesia.