A model to predict the live bodyweight of livestock using Back-propagation algorithm

Abstract

Cattle is the most popular livestock in Indonesia. Assessments of the live bodyweight of cattle can be conducted through weighing or predicting. Weighing is an accurate method, but it is not efficient due to the prices of scales that most traditional farmers cannot afford. Prediction is a more affordable technique however occurrences of error remains high. To deal with this issue this research has created a model predicting the live bodyweight of cattle through Back-Propagation algorithm. There are four morphometric variables examined in this study: (1) body length; (2) withers height; (3) chest girth; and (4) hip width. Based on comparative results with conventional prediction methods, Schoorl Indonesia and Schoorl Denmark, showed that the method offered has a lower error. Rate of error is 60.54% lower than Schoorl Denmark and 53.95% lower than Schoorl Indonesia.