Main Article Content
Abstract
This study presents an economic analysis of white shrimp farming at the different size of ponds. Forty white shrimp farms were selected from two different size of ponds. The sample sizes then were categorized into two scales small size was <1000 m2, and a large size was >1000 m2. The first set was the biological, survival rate, and feed conversion ratio, whereas the second set was the economic type, which consisted of input intensity. Multivariate statistical concepts were applied, which included multivariate analysis (MANOVA) is a generalized from of univariate analysis of variance (ANOVA) and principal component analysis. The results showed that both ponds set was significant different (P>0.05) on biological and economic variable. As a result, three major input cost (feed, labor, electricity) were considered in the analysis as they represented more than 80% of the total production cost in the system. The principal component analysis showed that large ponds farm had higher intensity in overall input than a small pond. The study also reported the small size pond was much better according to its overall performance in the benefit cost ratio.
Keywords
Article Details
Copyright (c) 2020 Aquacultura Indonesiana

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
- Boyd, C.E., & Clay, J.W. 1998. Shrimp aquaculture and the environment. America:Scientific American. 58-65p.
- Duraippah, Israngkura A., & Sae Hae, S. 2000. Sustainable Shrimp Farming: Estimation of Survival Fuction. CREED Publicion. 31p.
- Halim, D. 2017. Indonesia’s Aquaculture Industry. Ipsos Business Consulting.
- Hatch, U., and T.C. Feng. 1997. A survey of Aquaculture Production Economics and Management. Aquaculture Economics & Management, 1(2):13-27.
- Johnson R.A., & D.W Wichern. 1998.Applied Multivariate Statistical Analysis,2nd edn. Prentice-Hall, Englewood Cliffs,NJ. 607p.
- Liao. I. C.,& Chien. Y. H. 2011. The Pacific White Shrimp, Litopenaeus vannamei, in Asia: The World’s Most Widely Cultured Alien Crustacean. In the Wrong Place-Alien Marine Crustaceans: Distribution,Biology and Impacts 10:489-519.
- Manly, B.F.J. 2004. Multivariate statistical methods: a primer (3rd edition ed.). New York: Chapman and Hall. 159p.
- Shakir C., Lipton A. P., Manilal A., Sugathan S., Selvin J. 2014 Effect of stocking density on the survival rate and growth performance in Penaeus monodon. Journal of Basic & Applied Sciences 10:231-238.
- Shang, Y. 1990. Aquaculture economic analysis: an introduction In: Advances in World Aquaculture. Baton Rouge, LA. World Aquaculture Society.
- Steven, J.P. 2002. Applied multivariate statistic for the social sciences. Mahwah, New Jersey. Lawrence Erblaum Associate. Inc.
References
Boyd, C.E., & Clay, J.W. 1998. Shrimp aquaculture and the environment. America:Scientific American. 58-65p.
Duraippah, Israngkura A., & Sae Hae, S. 2000. Sustainable Shrimp Farming: Estimation of Survival Fuction. CREED Publicion. 31p.
Halim, D. 2017. Indonesia’s Aquaculture Industry. Ipsos Business Consulting.
Hatch, U., and T.C. Feng. 1997. A survey of Aquaculture Production Economics and Management. Aquaculture Economics & Management, 1(2):13-27.
Johnson R.A., & D.W Wichern. 1998.Applied Multivariate Statistical Analysis,2nd edn. Prentice-Hall, Englewood Cliffs,NJ. 607p.
Liao. I. C.,& Chien. Y. H. 2011. The Pacific White Shrimp, Litopenaeus vannamei, in Asia: The World’s Most Widely Cultured Alien Crustacean. In the Wrong Place-Alien Marine Crustaceans: Distribution,Biology and Impacts 10:489-519.
Manly, B.F.J. 2004. Multivariate statistical methods: a primer (3rd edition ed.). New York: Chapman and Hall. 159p.
Shakir C., Lipton A. P., Manilal A., Sugathan S., Selvin J. 2014 Effect of stocking density on the survival rate and growth performance in Penaeus monodon. Journal of Basic & Applied Sciences 10:231-238.
Shang, Y. 1990. Aquaculture economic analysis: an introduction In: Advances in World Aquaculture. Baton Rouge, LA. World Aquaculture Society.
Steven, J.P. 2002. Applied multivariate statistic for the social sciences. Mahwah, New Jersey. Lawrence Erblaum Associate. Inc.
