Risk Analysis for Beef Cattle Farmers in Banyuasin Regency
- DOI
- 10.2991/absr.k.220207.061How to use a DOI?
- Keywords
- Banyuasin Regency; Beef cattle; FMEA; Natural disaster; Risk analysis
- Abstract
This study aims to classify and map the risks faced by beef cattle farmers in Banyuasin Regency. This study employed a descriptive method using a survey as the main strategy of data collection. The study was carried out in two disaster-prone subdistricts in Banyuasin Regency, namely Tanjung Lago and Muara Telang. The sample selection of farmer respondents used a quota, based on which there were 30 farmers from each subdistrict. Therefore, according to the simple random sampling method, 60 farmers were involved in this study. Failure Mode and Effect Analysis (FMEA) was employed to identify sources of the risks. The results showed the mapping of risks experienced by beef cattle farmers illustrates the risks that occur in beef cattle business activities divided into four quadrants. The main risks that were prioritized are in quadrant one, namely natural disasters with an occurrence value of 0.35 and the value of severity of 2.57, availability of feed with an occurrence value of 0.17 and the value of severity of 2.16, government policies or regulations with an occurrence value of 0.12 and the value of severity of 2.31, and sick/dead cattle with an occurrence value of 0.10 and the value of severity of 2.09. It could be concluded the main risk in beef cattle farming in Banyuasin Regency was natural disasters, such as forest fires, floods, and tornadoes.
- Copyright
- © 2022 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - FAA Hafiz AU - B Guntoro AU - S Andarwati AU - NH Qui PY - 2022 DA - 2022/02/24 TI - Risk Analysis for Beef Cattle Farmers in Banyuasin Regency BT - Proceedings of the 9th International Seminar on Tropical Animal Production (ISTAP 2021) PB - Atlantis Press SP - 292 EP - 296 SN - 2468-5747 UR - https://doi.org/10.2991/absr.k.220207.061 DO - 10.2991/absr.k.220207.061 ID - Hafiz2022 ER -