@article{MAKHILLIBM20148325787,
    title = {Predicting the Income of Chicken Husbandry Using Artificial Neural Network: A Case Study of Chicken Farms in Blitar},
    journal = {International Business Management},
    volume = {8},
    number = {3},
    pages = {190-195},
    year = {2014},
    issn = {1993-5250},
    doi = {ibm.2014.190.195},
    url = {https://makhillpublications.co/view-article.php?issn=1993-5250&doi=ibm.2014.190.195},
    author = {Sugiono,Dewi and},
    keywords = {Chicken farm,BPNN,intelligent tool,income prediction,Indonesia},
    abstract = {The poor quality of management some farms today has been partly traced to inadequacies 
  of risk analysis which engaging a lot of factors. By these reason, the purpose 
  of the study is to deliver an intelligent tool that estimate directly the income 
  of chicken meat and chicken egg farmer in any different situations. The research 
  is started with study literature and early survey to identify various factors 
  that may likely influence the benefit of chicken farmers. Such, factors as field 
  areas, number of employers, time to harvesting, early modal, etc., were then 
  used as input variable for system and factor of benefit was to be an output 
  of the system. All the input and output information is used as database and 
  Back Propagation Neural Network (BPNN) is trained to configure the complex correlation 
  between input and output database. Finally, the software delivered an intelligent 
  tool which provided the user to find quickly the prediction of the income in 
  unique input without any investigations. Test data evaluation shows that BPNN 
  model is able to correctly predict the benefit of chicken famers >90% of 
  prospective farmers.}
    }