ANALYSIS OF FACTORS INFLUENCING RICE PRODUCTION IN LABUHAN BATU DISTRICT

This study aims to analyze the factors that influence rice production in Labuhan Batu District. The research was conducted in Labuhanbatu Regency, North Sumatra Province. The determination of the research area was carried out purposively (deliberately) with the consideration that the area of Labuhanbatu Regency was because according to BPS data for 2021, there was a deficit in dry milled rice production and corn production in Labuhanbatu which was not proportional to the population growth. The population in this study were all sub-districts that existed in Labuhanbatu Regency, which totaled 9 sub-districts the method used in sampling was a census, and the selection of samples was taken from 9 sub-districts in Labuhan Batu District. Data analysis in this study used Multiple Regression Analysis (multiple regression) through the Cobb-Dougla function, while the results of this study were that in the study the variable area of land had an effect on rice production because t count > t table (6,184 > 2,010) and a significant level 0.000 < 0.05. In the research, the agricultural sector variable has an effect on rice production because of t-count > t table (3,398 > 2,010) and a significant level of 0.002 <0.05. In the research, the variable fertilizer has an effect on rice production because t-count > t table (5.075 <2.010) and a significant level of 0.000 <0.05. In this study, the seed variable has an effect on rice production because of t-count > t-table (4,341 < 2,010) and a significant level of 0.000 < 0.05. The form of a linear regression model of the Cobb-Douglas production function for the study of factors influencing rice production. Shows the results of (bx1+bx2+bx3+bx4) = 4,761 meaning that in this study the area of land, the contribution of the agricultural sector, the use of fertilizers, and the use of seeds can be projected to see the amount of rice production in harbor stone of 47.61%.


INTRODUCTION
Indonesia is one of the largest rice-producing countries in the world. World-grain launches from the November 2022 edition of the World Agriculture Supply and Demand Estimates (WASDE) report by the US Department of Agriculture (USDA), Indonesia is included in the top 10 world rice producers. In succession, referring to the projection of rice production in 2022/2023, the world's main producers are (www.cnbcindonesia.com): Meanwhile, Badan Pusat Statistik (BPS) noted that national rice production in 2021 was 31.36 million tons. And it is predicted to increase by 2.29% or 720 thousand tons to 32.07 million tons. Where actual production for the January-September 2022 period was 26.17 million tons. This figure decreased by 0.22% or around 60 thousand tons from the same period in 2021 which reached 26.23 million tons. this happened because Bulog's stock was only 295,337 tons (59.76%) of government reserve rice (CBP/medium) and as much as 198,865 (40.24%) of commercial rice (Irawan, 2015). It is far from the government's target of 1.2 million tons by the end of 2022. The stock position is considered too small and there are fears it will trigger new problems. This is because Bulog has to intervene in the market amid price spikes due to the famine season, while the government is focusing on controlling inflation (Hapsari & Rudiarto, 2017). Bulog must also have stock to meet needs during emergencies such as natural disasters (www.cnbcindonesia.com) North Sumatra Province is one of the areas where the food security index is considered quite stable, this is because, in the North Sumatra region, there are many areas that are agricultural centers, namely Karo, Deli Serdang, Bahorok, North Tapanuli, and so on, these areas make North Sumatra having sufficient food security can even export their crops to areas such as Batam, Riau and other areas on the island of Sumatra where their yields are insufficient (Peku Jawang, 2021).
The focus of this research is rice production in Labuhan Batu district because rice production will have direct implications for food security in Labuhanbatu, this is because the price position of rice as the main food determines a large amount of demand for this product, but rice as a food product the main ones have an inelastic demand elasticity because if the price of rice rises, buyers are reluctant to look for substitutes (because rice is the main food product) and therefore have to keep buying the rice so that the demand will not change much (Damayanti & Khoirudin, 2016).  Table 2. shows that it can be seen that from 2018 to 2020 there has been a significant decrease in rice production as shown in the table. This can be caused by a reduction in the area of rice fields in Labuhan Batu Regency. The factors that affect rice production are land area, number of workers, fertilizer, and rice seeds. (Ishaq et al., 2017) argues that if there are fluctuations in rice related to supply availability and price increases, it will have an impact on political stability. This shows the availability and price stability of rice is one of the keys to achieving national stability, especially economic stability.

METHOD
The research was conducted in Labuhanbatu Regency, North Sumatra Province. The determination of the research area was carried out purposively (deliberately) with the consideration that the area of Labuhanbatu Regency was because according to BPS data for 2021, there was a deficit in dry milled rice production and corn production in Labuhanbatu which was not proportional to the population growth. The population in this study were all subdistricts that existed in Labuhanbatu Regency, which totaled 9 sub-districts the method used in sampling was a census, and the selection of samples was taken from 9 sub-districts in Labuhan Batu District. Data analysis in this study used multiple regression analysis through the Cobb-Douglas function (Rizky satria, 2013).
The purpose of Multiple Linear Regression Analysis is to study how close the influence of one or more independent variables is with one dependent variable.
The data analysis technique used in this study was carried out through the Cobb-Douglas production function. Mathematically, the Cobb-Douglas function can be written as follows: Yat = αX1β1X2 β2X3β3X4 β1ε…………………….. (1) The description of the formula is: Yat is the rice production number (tons) of Labuhan Batu for the last 10 years X1t is the area of Agricultural Land Area (Ha) Labuhan Batu in the last 10 years X2t is the Agriculture Sector (Ha) Labuhan Batu Labuhan Batu for the last 10 years X3t is the use of fertilizer (Rupiah) in Labuhan Batu in the last 10 years X4t is the use of seeds (Tons) of Labuhan Batu in the last 10 years By using the Cobb-Douglas model, the parameters/elasticity will be obtained directly from each variable X to Y. Estimate the elasticity coefficient, it can be done by making the Cobb-Douglas model a multiple regression equation with natural logarithms (ln) (Philip & Amstrong, 2013;Sinaga et al., 2018) lnYbt = lnα + β1lnX1t + β2lnX2t + β3 lnX3t + β3lnX3t + ε.

RESULTS AND DISCUSSION Classic Assumption Test
Before carrying out regression testing, classical assumption testing must be carried out first. (Imam Ghozali, 2016) stated that multiple linear regression analysis needs to avoid deviations from classical assumptions so that problems do not arise in the use of the analysis and to find out whether the regression model used in the study is the best model. In this study, several assumption tests were carried out including the Normality test Vol.

Multicollinearity Test
This test is used to test whether the regression model found a strong correlation between the independent variables tested to see whether or not symptoms of correlation between the independent multicollinearity variables can be seen from the large tolerance value and VIF (Variance Inflation Factor) (Sugiono, 2005). The general value commonly used is the tolerance value > 0.1 or VIF value < 10, then multicollinearity does not occur.  Table 4.3 shows that the Tolerance value for Land Area is 0.799 > 0.10 and the VIF value is 1.252 < 10, the Agricultural Sector Tolerance value is 0.807 > 0.10 and the VIF value is 1.239 < 10, Fertilizer Tolerance value is .941 > 0.10 and the VIF value is 1.063 < 10, the seed tolerance value is 0.961 > 0.10 and the VIF value is 1.040 <10.

Heterodexacity Test
How to detect whether there is heteroscedasticity in a model can be seen in the Scatterplot Model image. Analysis of the Scatterplot image states that the multiple linear regression model does not have heteroscedasticity if the data points spread above and below or around the number 0.

Figure 1 Heterodecacity Test
Through graphical analysis, a regression model is considered to have no heteroscedasticity if the points spread randomly and do not form a certain clear pattern, and are spread above or below zero on the Y-axis. So in Figure 1. shows that the points spread randomly then there is no heteroscedasticity.

Multiple Linear Regression Analysis
To test the effect of management accounting information systems on rice production in Labuhan Batu, a multiple regression analysis model was used. Multiple linear regression analysis serves to determine the effect of the independent variable on the dependent variable. The test criteria can be seen below Y = a + b1X1 + b2X2 + b3X3 + b4X4 +e The explanation from the table above is: Y = 20.033+ 1.521 X1 + 1.208X2 + 1.077X3 + 0.955X4 +e The explanation from the table above is: the (Constant) value of 24,797 indicates a positive constant value meaning that if the Land Area, Agricultural Sector, Fertilizers, Seeds do not change or are the same = 0 then it will increase rice production by 24,797. The regression coefficient for land area is 1,521 indicating that if the variable land area increases, it will increase rice production by 1,521%. The agricultural sector regression coefficient is 1.208 indicating that if the agricultural sector variable increases, it will increase rice production by 1.208%.
The Fertilizer Regression Coefficient is 1.077 indicating that if the Fertilizer variable increases, it will increase rice production by 1.077% The regression coefficient of the seed variable is 0.955 indicating that if the seed variable increases, it will increase rice production by 0.955%.
Based on the results of data processing, all independent variables have a positive influence on rice production in Labuhan Batu district. then all these variables can be included in the model. The form of the linear regression model of the Cobb-Douglas production function is to study the factors that influence rice production. The similarities are Y = 1.521 X1 + 1.208X2 + 1.077X3 + 0.955X4 +e (bx1+bx2+bx3+bx4) = 4,761 which means that in this study the area of land, the contribution of the agricultural sector, the use of fertilizers and the use of seeds can be projected to see the amount of rice production in harbor stone of 47.61%

Hypothesis Testing t-test
A partial test or t-test is a test carried out to determine the effect of the independent variable on the dependent variable, partially (individually) the criteria for partial testing can be modeled for testing the hypothesis as follows: a. H0: b1 = 0, meaning that partially there is no positive influence of the independent variables on rice production b. Ha: b1 ≠ 0, meaning that partially there is a positive influence from the independent variables, namely the effect on rice production t-table can be seen at α = 0.05 Denominator degree (df): nˉk = 33ˉ4 = 29, t-table 0.05 = 2.010 The decision-making criteria are as follows: a. Based on t-count • If t count <t table, then H0 is accepted or Ha is rejected.
• If t count > t table, then H0 is rejected or Ha is accepted.
• If the significance level is below 0.05 then H0 is rejected and Ha is accepted. b. Based on probability (Sig.) • If the probability is > 0.05 then H0 is accepted, meaning that there is no influence between the X and Y variables. • If the probability is <0.05 then H0 is rejected, meaning that there is influence between the X and Y variables. Effect of Land Area on Rice Production It can be seen in Table 6 that the t value of land area is 7,449 and a significant level is 0,000. In the study, the variable land area affects rice production because t count > t table (6,184 > 2,010) and a significant level of 0,000 <0.05 The Influence of the Agricultural Sector on Rice Production It can be seen in Table 4.5 that the t-value of the agricultural sector is 3,398 and a significant level is 0.002, in the study the variable of the agricultural sector has an effect on rice production because the t-count > t-table (3,398 > 2,010) and a significant level of 0.002 <0.05 The Effect of Fertilizer on Rice Production It can be seen in Table 4.5 the value of t count Fertilizer is worth 5.075 and a significant level of 0.000, in the study the Fertilizer variable affects rice production because t count > t table (5.075 <2.010) and a significant level of 0.000 <0.05 The effect of Seeds on Rice Production can be seen in Table 4.15, the t-count value of the seeds is 4,341 and a significant level is 0.000, in the study the seed variable affects rice production because t count > t table (4.341 <2.010) and a significant level is 0.000 <0.05

F-test
To test whether the proposed hypothesis is accepted or rejected, the F statistic (F test) is used. The F test aims to determine the effect simultaneously or jointly of the independent variables on the dependent variable. The test steps are as follows 1. Determine the model hypothesis H0 and Ha.
• Ho: b1 = b2 = 0, meaning that there is no significant effect of the independent variables simultaneously on the dependent variable. • Ha: b1 ≠ b2 ≠ 0, meaning that there is a significant influence of the independent variables simultaneously on the dependent variable. 2. Look for F-table values by determining the error rate (α) and determining the degrees of freedom, namely: • F-table can be seen at α = 0.05 • With the degree of the quantifier: k-1 = 3 1 = 2 • Denominator degrees: n k = 33 4= 29 • Then F-table 0.05 = 3.19 3. Find the F-count value using the SPSS 22.00 application. Find the F-count value using Table 7 ANOVA from the SPSS processing results as follows:  Table 7 shows the f count of 44,320 and a significant level of 0,000 meaning that in the study of seeds, land area, and fertilizers, the agricultural sector has a simultaneous effect on rice production because f count > f table because (44,320 > 3.19) and a significant level of 0.000 <0.05.

Coefficient of Determination
The coefficient of determination shows the size of the contribution of the variable influence on the dependent variable where 0 ≤R 2 ≤ 1. If the value of R2 is getting closer to the value 1 then it shows the stronger the relationship of the independent variable to the dependent variable. And conversely, if the determinant (R2) is smaller or closer to zero, then the influence of the independent variable on the dependent variable is getting weaker. The processing results of multiple linear regression analysis can be seen in Table 8 below  Table 7 shows an r-squared value of 0.864 meaning that in this study the variables of Seed, Land Area, Fertilizer, and Agricultural Sector were influenced by 0.864 or 86.4% of rice production in Labuhan Batu Regency while the remaining 13.7% were other variables not examined in this study.
Access to Food (Food Access), namely the ability of all households and individuals with the resources they have to obtain sufficient food for their nutritional needs which can be obtained from their own food production, purchase, or through food assistance. Household access from individuals consists of economic, physical, and social access. The indicators to explain food access can be categorized into physical indicators, including the smooth running of the distribution system, and the fulfillment of transportation facilities and infrastructure so as not to cause regional isolation. Economic indicators include the ability or increase in the purchasing power of the community or individuals due to job opportunities causing high incomes so that food prices are affordable. Indicators that are social include the absence of social conflict caused by bad customs or habits, and the level of knowledge that affects preferences or selection of food types (Arida et al., 2015).
1. In the study the variable land area has an effect on rice production because t count > t table (6,184 > 2,010) and a significant level of 0.000 <0.05 2. In the study of agricultural sector variables affect rice production because t count > t table (3.398 > 2.010) and a significant level of 0.002 <0.05 3. In the research, the variable fertilizer has an effect on rice production because t count > t table (5.075 <2.010) and a significant level of 0.000 <0.05 4. In the research, the seed variable has an effect on rice production because t count > t table (4,341 < 2,010) and a significant level of 0.000 < 0.05 Rice is one of the agricultural products that has an important role in meeting the needs of consumption in Indonesia. This is because rice is the staple food consumed by the majority of Indonesia's population. The high tendency to consume rice raises various kinds of problems, such as reduced availability of rice which causes prices to rise to an increase in the poor population due to increased spending to buy rice. So pad availability must remain in a stable condition that is maintained, so as to minimize the negative impact of shortages of availability. Government intervention and implementation of policies in domestic agriculture, especially agricultural products such as rice, are carried out with the hope of achieving self-sufficiency in rice and achieving prosperity for farmers as producers and the public as consumers. However, in reality, the results show a movement contrary to the expectations created by the government. Various phenomena have occurred which resulted in a decrease in the level of rice production in Indonesia. From the results of this study to answer the problem formulation and hypotheses in the previous, while the results of this study are.

Effect of Land Area on Rice Production
Production is an activity of making an item or keeping it to meet a need. Some of the things that influence production are labor, capital and materials. In agriculture, a farmer must be able to use output as efficiently as possible to produce the maximum possible results. In agriculture, superior seeds, the quality of an intelligent workforce greatly influences agricultural output. However, land area and soil fertility also affect the amount of agricultural production and the quality of production produced.
In this study, the variable land area affects rice production because t count > t table (6,184 > 2,010) and a significant level of 0.000 <0.05. The cause of the decline in rice production is most related to current conditions, namely the widespread conversion of agricultural land. As a result, crop yields have decreased because the area of agricultural land has decreased. This condition prompted the government to import rice to meet domestic rice needs and to stabilize domestic rice prices.
The results of this study are in line with research conducted by Denny Afrianto (2017) with the title "Analysis of the effect of rice stocks, harvested area, average or production, rice prices and total rice consumption on food security in Central Java" The results of this study indicate that harvested area is significant and positively related to food security

Effect of Labor on Rice Production
The workforce consists of the labor force and non-labor force. The labor force is the entire population aged ten years and over who has the most activities working and looking for work. The important thing is that the workforce from farming families themselves plays an important role, not only in Indonesia. Also in countries with advanced agriculture, the wives and children of farmers actively contribute to production activities. The productivity of agricultural labor can be increased in various ways, including through education and training to improve the quality and results of work Most of the farmers' knowledge and skills in working are obtained from parents who have guided them since they were children. But it has already been mentioned that new technologies in agriculture sometimes come from places far away from farmers In this study the labor variable affects rice production because t count > t table (3.001 > 2.010) and a significant level of 0.002 <0.05, Rice as a food-producing crop is very important for the people in Indonesia, This statement is in accordance with the theory ( Anwar & Fatmawati, 2018) that the production function essentially lies between scarcity and economic action and he says that scarcity causes economic problems and measures that need to be resolved. This causes economic problems that arise because human needs are unlimited while the means of satisfying human needs are relatively very limited The results of research conducted by Catur Indra Gunawan (2017) with the title "The influence of harvested area, productivity, rice consumption, and farmer exchange rates on food security in Brebes Regency" shows that one that is able to provide food security from an area is the contribution of agricultural land in an area.

Effect of Fertilizer on Rice Production
To obtain high grain yields while maintaining soil fertility, it is necessary to apply a combination of inorganic and organic fertilizers. The advantage resulting from the combined application of the two types of fertilizers is that the deficiencies in the properties of organic fertilizers are met by inorganic fertilizers, on the other hand the deficiencies of inorganic fertilizers are fulfilled by organic fertilizers. So the combination of these two fertilizers is considered perfect, because it complements each other between the advantages and disadvantages of organic and inorganic fertilizers. Rice plants require a lot of N nutrients compared to P or K nutrients. N nutrients serve as a source of material for plant growth, tiller formation, chlorophyll formation which is important for the assimilation process, which in turn produces starch for growth and grain formation. Nutrient P functions as a source of energy to meet the quality of plant life such as the simultaneity of growth and maturation. Meanwhile, nutrient K functions as a supporting component of enzyme reactions in plants. It also functions to improve grain yield, drought resistance, plant disease resistance, and grain quality. Thus to get grain with high quantity and good quality, the plant needs to be given complete nutrients In this study, the variable Fertilizer has an effect on rice production because t count > t table (5.075 < 2.010) and a significant level of 0.000 < 0.05. To obtain high grain yields while maintaining soil fertility, it is necessary to combine inorganic fertilizers with organic fertilizers. The advantage resulting from the combined application of the two types of fertilizers is that the deficiencies in the properties of organic fertilizers are met by inorganic fertilizers, on the other hand the deficiencies of inorganic fertilizers are fulfilled by organic fertilizers. So the combination of these two fertilizers is considered perfect, because it complements each other between the advantages and disadvantages of organic and inorganic fertilizers.
The results of this study are in line with research conducted by Klivensi Ilona Mafor, (2015) with the title "Factor Analysis of Rice Production in Tompasobaru Dua Village". The results showed that fertilizer could increase rice production at the study site.

Effect of Seeds on Rice Production
Seeds are a supporting commodity in labor which can later affect rice production. What must be available when carrying out rice planting activities, if the seeds are planted in accordance with the portion of the availability of paddy fields and also the quality of the seeds meets the standards, the more likely the success of the resulting rice production is, in other words the seed variable is a variable that affects the level of rice productivity. Seeds are the most important factor that must be considered by farmers if they want to have superior quality rice production. Therefore farmers must be careful in selecting seeds. According to (Sutopo, 2004) seeds are plant seeds that are used for the breeding process in plants. Especially for rice plants, farmers must use the best quality seeds, because the rice that will be planted goes through the process of becoming rice and is processed again into rice which is a staple food for the people of Indonesia.
In the study of the seed variable, it affected rice production because t count > t table (4,341 <2,010) and a significant level of 0.000 <0.05. Seedlings are a supporting commodity in labor which can later affect rice production. What must be available when carrying out rice planting activities, if the seeds are planted in accordance with the portion of the availability of paddy fields and also the quality of the seeds meets the standards, the more likely the success of the resulting rice production is, in other words the seed variable is a variable that affects the level of rice productivity. Seeds are the most important factor that must be considered by farmers if they want to have superior quality rice production. Therefore farmers must be careful in selecting seeds. According to (Sutopo, 2004) seeds are plant seeds that are used for the breeding process in plants.
The results of this study are in line with research conducted by Klivensi Ilona Mafor, (2015) with the title "Factor Analysis of Rice Production in Tompasobaru Dua Village". The results showed that seeds could increase rice production at the study site.

Contribution of Land Area, Labor, Use of Fertilizers and Seeds to Rice Production
The form of the linear regression model of the Cobb-Douglas production function shows the results of (bx1+bx2+bx3+bx4) = 4,761 meaning that in this study land area, labor contribution, use of fertilizers and use of seeds can be projected to see the amount of rice production in harbor stone of 47.61%. The r square value of 0.864 means that in this study the variables of Seed, Land Area, Fertilizer, Labor affect 0.864 or 86.4% of rice production in Labuhan Batu Regency while the remaining 13.7% are other variables not examined in this study.
The results of this study are in line with research conducted by Catur Indra Gunawan (2017) with the title "The effect of harvested area, productivity, rice consumption, and farmer exchange rates on food security in Brebes Regency. The results showed that harvested area is significant and has a positive relationship. Productivity is significant and positively related. Which has similarities with the results of research conducted by the author, meaning that if the area of paddy fields is increased and productivity is increased, it will increase rice production The results of research conducted by (Ishaq et al., 2017) with the title "Analysis of Factors Influencing Rice Production in East Java Province" The results of spline semiparametric regression show the factors that have a significant effect on rice production, namely rice harvest area and bulk rain, while the factors that do not have a significant effect are the area of paddy puso, the realization of subsidized fertilizers, and the average height, the results of this study have differences with the author's research, in terms of the use of fertilizers, this can happen due to nutrient factors, fertility and contours that differ from one location to another.

CONCLUSION
In the study the variable area of land has an effect on paddy production because of t count > t table (6,184 > 2,010) and a significant level of 0,000 <0.05. In the study, the agricultural sector variable has an effect on paddy production because t count > t table (3,398 > 2,010) and a significant level 0.002 < 0.05, in the study the variable Fertilizer has an effect on rice production because t count > t table (5,075 < 2,010) and a significant level of 0,000 < 0.05, in the study the seed variable has an effect on rice production because t count > t table (4,341 < 2,010) and significant level 0.000 < 0.05. The form of the linear regression model of the Cobb-Douglas production function is to study the factors that influence rice production. Shows the results of (bx1+bx2+bx3+bx4) = 4,761 meaning that in this study the area of land, the contribution of the agricultural sector, the use of fertilizers, and the use of seeds can be projected to see the amount of rice production in harbor stone of 47.61%.