Suchergebnisse

This study aims to find out the volatility of the price of chicken eggs and compile a proper forecasting model for the price of chicken eggs in the Traditional and Modern market of Jambi City. The object of the study is the price of chicken eggs in the Traditional and Modern markets of Jambi City using quantitative descriptive methods using skunder data. For the type of data used in this study is time series data in the form of weekly data on the price of chicken eggs for the period 2018 to September 2021 sourced from the National Strategic Food Price Information Center. Data analysis is carried out through an econometric approach in answering its objectives, using model analysis (ARIMA), ARCH / GARCH model. Based on the results of data processing, the ARIMA model is the best model for forecasting the price of chicken eggs in the traditional jambi market. While the ARCH model is the best model for forecasting the price of chicken eggs in the Modern market of Jambi City. The results of high price forecasting are found in the Traditional Market of Jambi City with an average of Rp. 21,543.35,-per kg from October to December 2021. From the results, there is volatility in the Traditional and Modern markets of Jambi City which is seen based on CSD (conditional standard deviation), and high volatility and often occurs in the Traditional Jambi City market with a volatility value of 0.01009950. The policy of pricing the sale of chicken eggs that is set nationally every year must be reviewed again with regard to fluctuations in the price of chicken eggs at the consumer level that can increase beyond the price set by the government, and the government's policy for stabilization of the price of chicken eggs in the market both downstream needs to be followed by policies on upstream subsystems, for example, the production input price policy is specific to chicken farmers, especially the price of animal feed raw materials (especially corn). As well as the existence of market operations in Jambi's production should be able to be done and studied its sustainability in order to be one of the solutions to maintain the stabilization of chicken egg prices.

The lack of capital for investment and limited access for small beef cattle farming to obtain credit from financial institution have contributed to the occurrence of share-beef cattle in rural areas. Through share-beef cattle pattern, the farmers (tenant) can rent livestock from other parties (individual nor government) within a share-beef cattle contract agreement. The purposes of this study were to determine the technical efficiency and the factors which influence the inefficiency from 108 small beef cattlebreeding, which consists of 59 farming operated by owner and 49 operated by tenant. The unit samples were selected by snowball sampling method and analysed by Stochastic Frontier Production. Our study showed that the average technical efficiency of beef cattle breeding operated by owner was at 0.73, otherwise operated by tenant was at 0.790. The inefficiency of beef cattle breeding operated by owner has negatively corresponded to the number of cows, the farmer age, the age of cow and the application of artificial insemination (IA), but positively corresponded to allocation of family labour and level of farmer education. The inefficiency of beef cattle breeding operated by a tenant has negatively corresponded to the application of artificial insemination (AI). Specific conclusion of the study was the technical efficiency level of small beef cattle breeding was not only affected by the ownership of beef cattle but also by the pattern of share-beef cattle. The share-beef cattle based on share income(50:50) may improve the value of technical efficiency compared to share-beef cattle based on share in-kind (share-beef cattle revolving cow or share-beef cattle revolving calf).