Penerapan Metode Neural Network Berbasis Web Dalam Prediksi Harga Telur Ayam - Febiansyah Annaufal Ahnaf Fauzi; Sri Wulandari; Donny Avianto (STMIK Budi Darma, 2024)
The demand for animal protein consumption is increasing in line with the development and growth of the livestock industry. Chicken eggs are one of the choices as a source of protein due to their abundant availability and affordable price. However, Yogyakarta Province experiences unstable egg price fluctuations, as indicated by the imbalance between high demand and limited production. To overcome this challenge, the authors developed the use of the Neural Network Backpropagation method to predict chicken egg prices. The selection of this method is based on its reputation for providing accurate predictions in this case. The implementation of this method resulted in an accuracy rate of 85%, which provides farmers with one of the useful tools to better manage risks and plan their production. This research is expected to make a significant contribution to the livestock industry, by providing farmers with a useful tool to manage risks and plan their production activities. In addition, this research is also expected to provide a better understanding of market behavior for stakeholders in Yogyakarta Province and the wider community. Thus, it is expected that this effort will not only improve the sustainability of the local economy but will also advance the livestock industry as a whole. With the results of this study, farmers are expected to optimize their strategies in adjusting production to the fluctuating market demand. In addition, stakeholders in Yogyakarta Province can use this information to develop more effective policies to support the growth of the livestock sector, especially in chicken egg farming