Analysis and Design of Web-Based Intelligent Livestock System Prototypes
Abstract
Smart Livestock System is a livestock platform that brings together farmers and investors. The emergence of the Smart Livestock System platform is due to the difficulty of farmers who want to spread their livestock business. The beef cattle population is still insufficient to meet domestic consumption needs and still depends on imported beef cattle. Smart Livestock System means a system that will be the solution to the conflict. The method used in testing the design of the Smart Livestock System is usability testing. This method tests the utilization of the system by the user. This method was chosen to determine the level of benefits generated by users from the solution offered by the Smart Livestock system. What will happen comes from the analysis and design in this paper is a documentation of analysis and design for the development of Smart Livestock System software, as a result it can be used by software developers to become acum and additional science certificates on making a software engineering development document.
Full Text:
PDFReferences
Sarkar, S dan Cleaveland, C. (2001). Code Generation using XML Based Document Transformation. The Server Side - Your J2EE Community.
Arantes, L.O. dan Falbo, R.A. 2010. An Infrastructure fo r Managing Semantic Documents. Prosiding Konferensi: Enterprise Distributed Object Computing Conference Workshops. Institute of Electrical and Electronics Engineers. Australia
Dewi Anggadini, S. (2013). Analysis of Computer-Based Management Information Systems in the Decision Making Process. Volume. ISSN 1411-9374.
Conover MD, Gonçalves B, Flammini A, Menczer F. 2012. Partisan asymmetries in online political activity. EPJ Data Science 1 Article 6
Doris-Down A, Versee H, Gilbert E. 2013. Political blend: an application designed to bring people together based on political differences. In: Proceedings of the 6th international conference on communities and technologies. New York. ACM. 120-130
Flaxman S, Goel S, Rao JM. 2013. Ideological segregation and the effects of social media on news consumption. In: SSRN Scholarly Paper ID 2363701. New York: Social Science Research Network.
Fortunato S, Flammini A, Menczer F, Vespignani A. 2006. Topical interests and the mitigation of search engine bias. Proceedings of the National Academy of Sciences of the United States of America 103(34):12684-12689
Gilbert E, Bergstrom T, Karahalios K. 2009. Blogs are echo chambers: blogs are echo chambers. In: Proceedings of HICSS. Piscataway. IEEE. 1-10
Google. 2009a. Introducing google social search: I finally found my friend’s New York blog! Available at http://googleblog.blogspot.com/2009/10/introducing-google-social-search-i.html (accessed 6 January 2015)
Google. 2009b. Personalized search for everyone. Available at http://googleblog.blogspot.com/2009/12/personalized-search-for-everyone.html (accessed 25 August 2014)
Refbacks
- There are currently no refbacks.

This work is licensed under a Creative Commons Attribution 4.0 International License.

