Articles

Business Risk Management Strategy in Adaptation of Beef Caft Businesses to the Impact of Climate Change in Sumenep District

/in /by

This study aims to determine the mitigation strategies of farmers in Sumenep district in their strategic management when facing climate change. Climate change greatly affects livestock activities in Sumenep district in various factors, extreme weather changes can harm beef cattle farming in terms of selling value. Increased temperature causes stress in cattle. Drought can reduce forage and water availability. Dry conditions inhibit the growth of grass and other feed plants, forcing farmers to look for alternative feeds such as hay or commercial animal feed. Extreme climate change that occurs gradually over three months, twice the normal time and the following three months, facing extreme climate change that has an impact on the health of livestock in Sumenep District and the selling price of cattle that does not match the expectations of farmers. Research was conducted to outline strategies in business adaptation using the SWOT method to determine priority options from the general micro and macro impacts, the following knowledge aims to determine strengths, weaknesses, opportunities and threats. The right strategy in handling beef cattle business adaptation will minimize losses of farmers due to climate change and mitigation of greenhouse gas emissions from the livestock sector.

Feasibility Analysis of Beef Cattle Farming Business against Climate Change in Sumenep District Indonesia

/in /by

The objective of the study was to analyze the feasibility of beef cattle farming to climate change in Sumenep District, East Java Province, Indonesia. The research was conducted at the beef cattle Farm for one month from December to January 2023. The method used in the research is a survey with a quantitative approach while the sampling method is multistage sampling (multi-stage cluster sampling for data collection from a large group of areas with the largest to smallest population) and the method can be combined with other sampling methods namely purposive sampling (deliberate data collection) and data collection methods are interviews, questionnaires, observation, focus group discussions and documentation. The data used is cost data from beef cattle farming businesses with a sample size of 150 respondents. The data analysis used was feasibility analysis, namely R/C ratio, which collected production cost data consisting of variable costs, fixed costs and total revenue. The results showed that beef cattle farming in Sumenep district obtained an R/C ratio value of 0.99 for a population of 2 heads, an R/C ratio of 1.00 for a population of 3 heads, and an R/C ratio of 1.06 for a population of 4 populations. The conclusion is that climate change affects the R/C ratio value of the 2-tailed population which is declared not feasible to run while the 3-tailed and 4-tailed populations are feasible to run and develop.

A Study of Farmer Profiles under Climate Change Conditions in Sumenep District Indonesia

/in /by

The purpose of the study was to determine the profile of beef cattle farmers in Sumenep District and to determine the economic activities of beef cattle farming in Sumenep District before and during climate change which includes the ease of selling beef cattle, selling prices, and business profits. The research was conducted using a survey method with sampling techniques using purposive sampling with the criteria of farmers who have been doing beef cattle farming for at least two years with active livestock groups and have a minimum of two years of farming experience. Farmers who were used as respondents amounted to 150 respondents. The analysis used is descriptive with mode measurement or the most frequently occurring value. The results showed that beef cattle farmers in Sumenep district mostly have three beef cattle on their farms (65% or 97 people). Most respondents were between 15 and 64 years old (83%), had primary school education (36%) and had the most farming experience in the 20 to 30 years age range (42%). A total of 35% of respondents had three family members. Before climate change, farmers found it easy to sell their products, the selling price was good and it was easy to make a profit. Whereas during climate change, farmers found it difficult to sell their products, selling prices were lower and it was difficult to make a profit.

Are The Independent Area of Beef Cattle Development Ready for Big Data to Reduce the Volume of Imports?

/in /by

Stakeholders find it difficult to make decisions for both breeders and supporting sectors due to unorganized agribusiness data on beef cattle, it seems very limited information on it. The activities related to this business have not been recorded well, from male selection, feed management, cultivation, as well as marketing and traceability—these factors have caused price disparities in meat to become commonplace. Thus, a model of breeder empowerment is needed through big data maturity. Data play a crucial role in the planning and development of agriculture and agribusiness. The results of the analysis on efforts to digitalize and integrate data on beef cattle business confirm that the progress stops at the Nascent phase. Data digitalization at the Agency for Agriculture Extension of Kediri is at the Nascent phase, while at the Department of Food Security and Livestock Service is in between the Nascent and pre-adoption phase. Data integration in other agencies, such as the Regional Central Bureau of Statistics of Kediri, the Regional Information and Communication Office of Kediri, and the Directorate General of Livestock, fall into the corporate adoption and mature phase. As can be seen, data have not been well-integrated within one interconnected system. The availability of such a model of data integration will be a good alternative in empowering breeders of beef cattle and the public sector, it will also find communication easier with the existence of the model. The government eventually will be able to better improve performance based on the digital data available.