ANALYSIS OF FACTORS AFFECTING THE IMPORT AND CONSUMPTION OF SUGAR CANE IN INDONESIA

, This study aims to analyze and determine the effect of (1) production, consumption, price and exchange rate on sugar imports in Indonesia (2) import, production and price of sugar on sugar consumption in Indonesia. This type of research is descriptive and associative. While the type of data is documentary data, the data source is secondary data and time series data from 2000 – 2021. The analysis tool is a simultaneous equation model using the Two Stages Least Squared (TSLS) method. The results of the study concluded that (1) sugar production and exchange rate had no significant effect on sugar imports in Indonesia. While sugar consumption and sugar prices have a significant effect on sugar imports in Indonesia (2) sugar imports have a significant effect on sugar consumption in Indonesia. Meanwhile, production and prices have no significant effect on sugar consumption in Indonesia. From the results of the cointegration test using the Unrestricted Cointegration Rank Test (Trace) approach, it was found that there was a long-term relationship or balance between the variables of sugar production, sugar consumption, sugar imports, sugar prices and the exchange rate. Based on these results, the policy that can be suggested is that the Government through the Ministry of Agriculture should issue policies to encourage the expansion of domestic production scale and improve the quality of sugar in order to suppress imports and at the same time control prices, because large imports will harm sugar farmers and also drain foreign exchange reserves.

INTRODUCTION Sugarcane (saccharum officinarum) is grown as raw material for sugar, originating from India and Indonesia, namely in the areas of Kalimantan, Maluku, Sulawesi and Papua. Meanwhile, sugar-producing countries in the world include Cuba, Taiwan, Indonesia, India, the Philippines and other countries. Meanwhile, in Indonesia the sugar-producing regions are Central Java, East Java, West Java, Nangro Aceh Darusslam and South Sulawesi. Expansion of the area is still underway to utilize grasslands to become sugarcane plantations. Sugarcane planted will be accommodated in existing factories. If the requirements for planting and maintenance are met properly, each hectare of land can produce around 750 -1,250 quintals of sugarcane. If the sugar content in sugarcane is 10-12 percent, it will produce 100-200 quintals of white sugar per hectare. Sugar is a staple food for the people of Indonesia Sugar is a commodity strategy in the Indonesian economy, with a land area of around 443,501 hectares in 2021. The sugar cane-based industry is a source of income for around 1.3 million farmers with a large workforce. involved around 1.7 million people. Sugar is also one of the basic needs of society and a relatively cheap source of calories. Because it is a basic need, the dynamics of sugar prices will have a direct influence on the inflation rate. Although in the last two years the performance of the national sugar industry has shown an increase, in 2013 its performance has decreased, both in terms of area, production and efficiency levels. In line with the revitalization of the agricultural sector, the national sugar industry, or the sugarcane-based industry in general, must revitalize. To realize this, increased investment is a mandatory requirement, in order to further increase sugar production, so it is expected to reduce sugar prices and reduce national imports, where currently sugar imports are relatively large at around 5,455,000 tons in 2021, where these imports are detrimental to farmers will also deplete foreign exchange reserves. In order to increase national cane sugar production, investment in the cane sugar industry is quite prospective. From the market side, the demand for sugar in the country is very large, both for industrial needs and for consumption needs. The government with its various promotive and protective policies has created a conducive trade climate for the development of the sugar cane-based industry. The international market, which in the last three years has experienced a decline as a result of the pressures faced by the world's main sugar producers, also indicates that investment in this sector is quite prospective. In sugar, various sugarcane derivative products such as ethanol, baker's yeast, inactive yeast, sugarcane top wafers, particleboard, fiberboard, pulp, and calcium citrate have quite open market opportunities, both in the domestic and international markets. In order to continue the target of developing a sugar cane-based industry, investment is needed both in farming, sugar factories and their derivative products. Overall, the total investment required is around IDR 16.5 trillion. Based on the type of investment, the total investment for primary businesses reaches more than Rp. 2 trillion. A very large investment is needed in the downstream industry business which reaches around Rp. 14 trillion. Investment for infrastructure is estimated at Rp. 500 billion. To achieve this, government support is needed, such as: consistency of government policies, creation of a fair competition field, provision of incentives for industrial development outside Java and financial support for the rehabilitation and consolidation of sugar production.

Grafik 1 Sugar Cane Imports in Indonesia 2000-2021 (Unit of Tons)
Source: BPS Indonesia Sugarcane Statistics, 2022  Based on Graph 2, it shows that sugar production in Indonesia tends to fluctuate. In 2008 there was a significant increase, where production was 2,668,428 tons, but decreased after that, especially there was a sharp decline in 2013 to 1,553,551 and rose again in 2014 to 2,9575392 tons, then in 2015 decreased by -1.57% to 2,534,872 tons, then production sugar in Indonesia again rose by 15.4% in 2017, which was 2,691,724 tons. But in 2021 production will decrease to 2,364,321 tons.

Grafik 3 Sugar Consumption in Indonesia (Unit of Tons)
Source: BPS Indonesia Sugarcane Statistics, 2022 Based on Graph 4 shows that the price of sugar in Indonesia tends to increase continuously where in 2000 the price was Rp 2,987/kg and continued to increase in 2010 at Rp. 10.502/kg. It can also be seen in 2013 the price of sugar in Indonesia was Rp 12,685/kg while in 2014 it was Rp 12,450/kg then in 2015 it was Rp 12,879/kg, then the price of sugar in Indonesia in 2016 was Rp 13,570/kg, in 2017 the price of sugar is Rp. 13,750 kg. And in 2020 there is an increase to 14,667/kg, although in 2021 it has decreased to Rp. 13,000/kg.

Grafik 5 Excange Rate Development in Indonesia from 2000 -2021 (Rp/USD)
Source: Bank Indonesia, 2022 Based on Graph 5, the data shows that the exchange rate tends to depreciate, which means that the value of the rupiah weakens or decreases in value against the USD, where in 2000 1USD was equal to Rp. 7,590 and in 2021 1 USD has become Rp. 14,312. Starting from the description of the background above, the author wants to analyze further by conducting a study entitled: "ANALYSIS OF FACTORS AFFECTING THE IMPORT AND CONSUMPTION OF SUGAR IN INDONESIA".

Consumption of Theory
According to Keynes, national consumption is determined by disposable income so that, C = f (Yd), ceteris paribus ………………………………………………………………………………. (1) And according to Marshal in a book written by Alfianlains (2015: 23) states that a consumer's demand is a function that shows the amount of a commodity that a consumer will buy and also as a function of the prices of commodities and consumer income, This statement is expanded again as stated by Richard A Billas (2016: 17) that the amount of goods demanded besides being determined by taste, is also determined by prosperity and other products produced within the country. On the other hand, it can also be said that food imports are part of consumption. Furthermore, Harry G Johnson in a book written by Revaldi (2016: 270) states that a country's imports are the difference between the needs of all imported goods produced domestically, then he gives the following formula; Where: M = Import Mt = Total needed in the country Md = Imported goods produced domestically Based on the statement above, it can be said that imports are a function of income M = F (Y)

Import of Theory
According to Romeo M Bautista (2016: 134) there are three factors that influence a country to import goods, namely: a. Limited domestic production, limited domestic production so that a country imports to cover this shortfall. b. There is a difference in the price of goods produced domestically with the prices of goods produced abroad. This is caused by differences in endowment or differences in the amount and price of factors of production owned by a country, this situation will cause a country to export or import certain goods. c. There are differences in the level of income and spending of a country. Income and costs will affect the demand for imported goods. Thus the mathematical function of demand for imports can be written as follows: Where: M = Number of imported goods Pl = price of imported goods abroad Pd = price of imported goods in the country Y = income which is usually measured in gross domestic product However, knowing the domestic and foreign price variables is very difficult, so the best way is to determine our imports using the exchange rate variable, so the formula above can be simplified to:

PREVIOUS RESEARCH
The previous research related to the author's research was research conducted by NOVA DEWITA entitled "Development of Indonesian Food Imports". Where he concluded that the decline in imports of food consumption goods is closely related to Indonesia's success in achieving self-sufficiency in food, and the magnitude of the influence of the decline in imports of food consumption goods is an indication that consumer goods in the form of food ingredients occupy the dominant place of all imports of consumer goods.

CONCEPTUAL FRAMEWORK
Conceptual framework or framework of thinking is a concept to explain, reveal and show the relationship between endogenous variables and exogenous variables to be studied based on the theories that have been stated above. Imports are influenced by sugar production, sugar consumption, sugar prices and exchange rates. When the exchange rate or exchange rate of a country's currency appreciates (its value increases relative to other currencies), the price of imported goods in a country decreases, so that country's imports increase. Vice versa, when the exchange rate or the exchange rate of a country's currency depreciates (its value decreases relative to other currencies), then the price of imported goods in a country increases, so that country's imports fall. Consumption in this study is influenced by production, prices and imports. An increase in production and imports will be able to increase salt consumption because there are many goods in the market, causing high demand which in turn will encourage increased consumption. Rising prices will reduce salt consumption because the price is a sacrifice for consumers.

METHOD
The data for all variables in this study starts from 2000 to 2021 with a total of 21 years of data. The population in this study is all data obtained from the Central Statistics Agency In obtaining the data in this study, documentation and library methods were used. The method of documentation is to find data from the official website that has been recorded by Bank Indonesia, the Central Statistics Agency and the Directorate General of Plantations from 2000-2021. While the library method is obtained from several books, notes or research results that have been carried out by previous researchers that can support the theory and discussion in this study. The analysis technique used is stationary test, cointegration, Granger causality, multiple linear regression and classical assumption test. The equations in this study are as follows: IM = α0 + α1 PG + α2 KG + α3 HG + α4 E + µ1 (4) KG = β0 + β1 PG + β2IM + β3 HG + µ2 (5)

RESULTS AND DISCUSSION
Before carrying out the stages of analyzing the variables of Cane Sugar Import, Cane Sugar Production, Cane Sugar Consumption, Cane Sugar Price and Exchange Rate shortened to IM, PG, KG, HG and E, then some tests are carried out first.

Stationary Test
Table 1 describes each stationary variable at a certain level, namely at Level and 1nd difference. From the table it can be seen that the variable sugar production is stationary at the level, sugar consumption, sugar imports, sugar prices and the stationary exchange rate at the 1nd difference level and all variables have a small probability value of = 0.05, then all variables in this study it can be said that the mean, variance and autocovariance are constant over time (for different lags the values are the same, it doesn't matter where to start measuring).

Cointegration Test
From the results of the cointegration test using the Unrestricted Cointegration Rank Test (Trace) approach, it shows that there is a relationship or long-run equilibrium (long run equilibrium) between the variables PG, KG, IM, HG and E, where in the lines None, At most 1, At most 3, At most 4 The probability that is smaller than = 0.05 or the Critical Value is less than the Trace Statistics, except for the At most 2 line where the probability is greater than = 0.05. Table 3 shows the results of the estimation of the sugar import equation. Partially, sugar consumption affects sugar imports in Indonesia significantly and positively. This means that if sugar consumption increases but is not matched by an increase in sugar production, there will be an increase in sugar imports. This is because when the increased consumption of sugar is not driven by an increase in sugar imports, there will be a shortage of sugar in the market. Therefore, imports are needed. Partially, the exchange rate has no significant effect on sugar imports. This means that the ups and downs of sugar imports are not caused by exchange rate fluctuations. This condition is because sugar is a basic need for the people of Indonesia. So even though the exchange rate depreciates, causing the price of imported goods to be expensive, people will still ask for sugar. As nowadays many foods and beverages in Indonesia contain sugar, so the demand for sugar remains high.

Multiple Linear Regression 3.1. Sugar Import Equation Model
Partially, sugar production has no significant effect on sugar imports. This means that the increase in sugar production has only a slight effect on the decline in sugar imports and is negative, ie if sugar production increases, sugar imports will decrease. Partially, sugar prices affect sugar imports significantly and positively in Indonesia. When the price of sugar increases, the import of sugar will also increase. Since rising sugar prices indicate increased demand, this increase in demand will increase sugar imports.

Sugar Consumption Equation Model
Table 4 shows the results of the estimation of the sugar import equation. Partially, sugar production has no significant and negative effect on sugar consumption in Indonesia. In other words, the increase in sugar consumption is not determined by sugar production. When sugar production goes up, sugar consumption actually goes down. Partially, sugar imports have a significant and positive impact on sugar consumption in Indonesia. The increase in sugar imports with the assumption that it is not accompanied by an increase in sugar production, this condition will increase sugar consumption. This is because the increase in sugar imports will increase the supply of sugar in the market so that the price of sugar will decrease. The decline in sugar prices will lead to an increase in people's purchasing power for sugar. Therefore, this will increase the consumption of sugar. Partially, the price of sugar has no significant and negative effect on sugar consumption in Indonesia. If the price of sugar increases, the people's sacrifice to buy sugar will also increase so that it will reduce purchasing power. Of course, this condition will result in lower sugar consumption.

Classic Assumption Test Normality Test
Normality test aims to test whether the regression model, the data used has a normal distribution or not. Good data is data that has a normal distribution or is close to normal, as we know that the F test and t test assume that the residual value follows a normal distribution. To detect this, the Jarque -Bera test is used, a test that uses a probability distribution (Gujarati, 2006). The results of the normality test are shown in the following figure: Table 5 Normality Test Results

Source: Processed Data
It is assumed that H0 is normally distributed data, and Ha is data that is not normally distributed. If probability > alpha then the decision is H0 accepted, Ha is rejected. If probability < alpha then the decision is H0 rejected and Ha accepted. Based on Table 5, it is known that the probability value > alpha 0.05, r, then H0 is accepted, Ha is rejected, which means that the variables contained in equations one and two are normally distributed.

Multikolinierity Test
The multicollinearity test aims to test whether the regression model found a linear correlation between the independent variables. Where there should be no linear correlation. In this study, the multicollinearity test was performed using a correlation matrix. Multicollinearity test results can be seen in the centered VIF column, if the VIF value is not greater than 10, then we can say that there is no multicollinearity in all independent variables.

Heteroskesdastisity Test
Heteroscedasticity test is used to test the category data group that has unequal variance among group members. If the variance is the same, then homoscedasticity occurs, while if the variance is different, then what will happen is heteroscedasticity (Gujarati, 2006). In this study, heteroscedasticity testing was carried out using the Glejer heteroscedasticity test. It is assumed that H0 is no heteroscedasticity symptom and Ha is heteroscedasticity symptom. If the value of Prob. F(4,17) and Prob. F(3.18) where this can also be called the probability value F count value > from the alpha level 0.05 (5%) then H0 is accepted and Ha is rejected which means there is no heteroscedasticity, whereas if the probability value F count is < from the alpha level 0.05 (5%) then H0 is rejected and Ha is accepted, which means there is heteroscedasticity. The results of the heteroscedasticity test are shown in the following table:

Autokorelation Test
The autocorrelation test aims to test whether in linear regression there is a correlation between the confounding error (residual) in period t with errors in period t-1 (previous).

Autocorrelation Test Results Confounding Error Equation 2
Source: Processed Data Prob value. F(2,15) and Prob. F(2.16) can also be called the probability value of calculated F. If F count > from = 0.05 then there is no autocorrelation.

Coefficient of Determination Test
The Coefficient of Determination (R2) aims to determine how far the variation of the independent variable can explain well the variation of the dependent variable. The concept of OLS is to minimize residuals, so that a high correlation is obtained between the dependent variable and the independent variable. The perfect R2 value can be fully explained by the independent variables included in the model. From the results above, it can be seen that from the results of the coefficient of determination test equation 1 R2 = 0.87. This means that 87 percent of the up and down variation in sugar cane imports in Indonesia 87 percent is influenced by sugar cane production, cane sugar consumption, sugar cane prices and exchange rates in Indonesia, while the remaining 13 percent is influenced by variables outside the model. And from the results of the coefficient of determination equation 2 R2 = 0.76. This means that 76 percent of the variation in the ups and downs of cane sugar consumption in Indonesia 76 percent is influenced by sugar cane production, sugar cane prices and imports in Indonesia, while the remaining 24 percent is influenced by variables outside the model.

F-statistic Test
The F test basically shows whether all the independent variables included in the model have a joint effect on the dependent variable. The test is carried out by comparing the probability values obtained from calculations with an error rate of of 5%, with the following conditions: Probability < alpha (0.05), then Ho is rejected and Ha is accepted (significant effect). Probability > alpha (0.05), then Ho is accepted and Ha is rejected (no significant effect).

Table10 F-Statistic Test Results Equation 1 F-Statistic Test Results Equation 2
From the results of the f-statistics test of the two equations, the probability values of 0.000000 and 0.000007 are smaller than the significant level of 0.05. This means that the production of cane sugar, consumption of cane sugar, and the price of cane sugar, together (simultaneously) have a significant effect on the import of sugar cane in Indonesia.

CONCLUSIONS
Based on the estimation results of the multiple linear regression equation with the discussion of the results of several tests carried out in this study, it can be concluded that (1) sugar production and exchange rate have no significant effect on sugar imports in Indonesia. While sugar consumption and sugar prices have a significant effect on sugar imports in Indonesia (2) sugar imports have a significant effect on sugar consumption in Indonesia. Meanwhile, production and prices have no significant effect on sugar consumption in Indonesia. From the results of the cointegration test using the Unrestricted Cointegration Rank Test (Trace) approach, it was found that there was a long-term relationship or balance between the variables of sugar production, sugar consumption, sugar imports, sugar prices and the exchange rate.
And based on these results, the policy that can be suggested is that the Government through the Ministry of Agriculture should issue policies to encourage the expansion of domestic production scale and improve the quality of sugar in order to suppress imports and at the same time control prices, because large imports will harm sugar farmers and also