Analysis of Factors Affecting The Demand of Broiler Chicken Meat In Binjai City

Consumption of broiler chicken meat increase year by year in line with public awareness increased of animal products.The purpose of this research was identify the factor of family’s dependent number (X1), educational level (X2), family income (X3), price of broiler chicken (X4), taste (X5), age of respondent (X6), and price of substitution was egg (X7).The analysis method used in this research was multiple linear regression analysis method by using SPSS 22.0. Sampling technique with slovin method with the samples were100 consumers of broiler chicken meat. This research was conducted from October until November 2017. The results showed that value of determination (R 2 ) was 0,704. Simultaneously, the variables showed a significant effect (P<0,05) to the demand of broiler chicken meat. Partially, family’s dependent number, income, chicken meat’s prices and tastes had a significant effect to the demand of broiler chickens while the educational level, age of respondents and the price of egg did not give significant effect on the demand of broiler chicken meat in Binjai City. The conclusion of this research showed that the taste was the most significant variable to the demand of broiler chicken and then followed by the family’s dependent number, price of broiler chicken meat and family income.

The purpose of this research was to identify the factors of the number of dependents, level of education, family income, price of broiler meat, tastes, age of respondents, and prices of substitute items, namely eggs on demand for broiler chicken in Binjai City.

2.1.Time and Place of Study
This research was conducted in three traditional markets in the Municipality of Binjai. This research was conducted in October -November 2017.

2.2.Sampling Method
The sample in this study is consumers of broiler chicken meat. The method of determining consumer respondents is done by the search method (Accidental sampling), which is the retrieval of respondents from consumers who are shopping for broiler meat that is most easily obtained / found at the time of data collection and is willing to be interviewed in traditional markets where the research is located. According [1], the required sample size is calculated using the Slovin formula as follows:

2.3.Method of collecting data
The data used in this research are primary data and secondary data. Primary data collection is done by direct interview method using an instrument in the form of a questionnaire that has been made previously. Data collected included data on the number of family dependents, education level, family income, purchase price of broiler chicken meat, tastes, age of the respondent, and substitute items (eggs). Secondary data was obtained from related institutions or institutions, such as the Binjai City Fisheries and Animal Husbandry Office, Binjai City Central Bureau of Statistics (BPS), North Sumatra Central Statistics Agency (BPS) and from the literature and other supporting sources.

2.4.Data analysis method
The analytical method carried out by multiple linear analysis methods derived with the least squares method was analyzed using SPSS 22.0 with seven independent variables, namely the number of dependents, education level, family income, broiler chicken prices, tastes, age of respondents and eggs as a substitution commodity and as a dependent variable, namely the demand for broiler chicken meat.
Multiple regression analysis is used by researchers, if the researcher intends to predict the state of the dependent variable (criterion) (criterion), if two or more independent variables are raised to decrease their value and multiple regression allows some additional variables to be introduced. So multiple regression analysis will be carried out if the number of independent variables is two or more than two [2]. This analysis uses the OLS (Ordinary Least Square) method or the least squares method with the SPSS 22.0 tool. The form of the model can be formulated as follows: Y = a+b 1 X 1 +b 2 X 2 + b 3 X 3 + b 4 X 4 + b 5 X 5 + b 6 X 6 + b 7 X 7 +µ

Residual Normality Test
This test is conducted to find out whether in a regression model, the residual value has a normal distribution or not. Residual is the difference between the Y variable and the Y variable that is specified. In the linear regression method, this is indicated by the magnitude of the random error (e) value that is normally distributed. A good regression model is normally distributed or near normal so that the data is feasible to be tested statistically.

Multicollinearity Test
Multicollinearity is a situation where between two or more independent variables in the regression model there is a perfect or near-perfect linear relationship. A good regression model requires no muticolinearity problems. To detect the presence or absence of multicollinearity in general by looking at the Tolerance and VIF values in the linear regression results. 45

Heteroscedasticity Test
Heteroscedasticity is a condition in which the occurrence of residual variance inequalities in the regression model. A good regression model requires no heteroscedasticity problems.

F Test
The F test is used to test the effect of independent variables together on the dependent variable. The decision making is:

T Test
The t test is used to test the effect of partially independent variables on the dependent variable.
According to [4], the use of hypothesis test criteria is: If t count> t table or -t count <-   and prices of substitute goods egg. While the remaining 29.6% is explained by other variables outside the model. Based on the F test analysis conducted it can be seen that the calculated F is obtained at 34,681 with a significance of F = 0,000 < 0,05. This shows that the independent variables observed were family dependence, education level, family income, broiler meat prices, tastes, age of respondents, and egg prices together significantly affected the demand for broiler chicken meat in Binjai City.

Educational Level
The results showed that the educational variables calculated were 0.898 < 1.987 and could be stated partially that education did not affect the demand for broiler chicken in Binjai City.

Family Income
Based on the results of the analysis it can be seen that the partial regression coefficient of the income variable of the average family is equal to 9.19.10-7 and the value of t count is 6.773.
The significance value of the income variable shows 0,000 <0,05, it can be said that the income variable influences the demand for broiler chicken meat. The partial regression coefficient shows that if income increases by 1%, consumer demand for broiler chicken increases by 9.19x10-7%.

Price of Broiler Chicken
Significant value on the variable price of broiler chicken meat showed 0.013 <0.05, so it can be said that the variable price of broiler chicken meat itself affects the demand for broiler chicken meat. The partial regression coefficient shows that if the price of broiler chicken meat increases by 1%, the consumer demand for broiler chicken meat increases by 0,000%.

Taste
Significance value on consumer tastes variable shows 0,000 <0,05, so it can be said that variable consumer tastes influence the demand for broiler chicken meat. The partial regression 52 coefficient shows that if consumer tastes increase by 1%, the consumer demand for broiler chicken meat increases by 1.29%.

Age of Respondent
Based on the results of the analysis it can be seen that the partial regression coefficient of the age variable of the respondent is equal to 0.006 and the calculated t value is 0.487. The significance value of the respondent's age variable shows 0.628> 0.05, it can be said that the respondent's age variable did not influence the demand for broiler chicken meat. The partial regression coefficient shows that if the respondent's age increases by 1%, the consumer demand for broiler chicken meat increases by 0.006%.

Price of Egg
Based on the results of the analysis it can be seen that the partial regression coefficient of the egg price variable is equal to -0.001 and the value of t count is -1.230. The significance value of the egg price variable shows 0.222> 0.05, it can be said that the variable price of eggs does not affect the demand for broiler chicken meat. The partial regression coefficient shows that if the price of eggs increases by 1%, the consumer demand for broiler chicken meat decreases by 0.001%.

Conclusions
Based on regression analysis, it is known that the number of dependents, education level, family income, chicken prices, tastes, age of respondents, and egg prices have a positive effect on the demand for broiler chicken in Binjai City. Based on the partial analysis, it is known that the variables that have the most positive influence (increase) on the demand for broiler chicken are taste, then followed by the variable number of family dependents, price of chicken meat and family income. While the level of education, age of respondents and the price of eggs did not significantly affect the demand for broiler chicken in Binjai City.