Decision Support System Cattle Weight Prediction using Artificial Selected Weighting Method

Animal agriculture in Indonesia is a very important need. Beef production in Indonesia experienced fluctuations from 2015 to 2019. In that period, 2016 reached its highest point with 518,484 tons. Even so, the use of technology for animal husbandry is needed to help farmers improve the quality and quantity of livestock products. One of the needs of farmers is cattle scales. This scale is expensive so not all farmers can afford this. They weighing cattle by bringing it to the cattle market or a place that has been facilitated by the government. This causes farmers have to require transportation just only weighing cows. Another way is approximating the weight, but this method can only be done by someone who has high experience. The aim of this paper to propose a system for predicting the weight of cattle using a novel artificial selected weighting method. This method is based on hybrid image processing results combined with Danish Schoorl, Schoorl Indonesia, Winter Europe/Scheiffer, and Winter Indonesia calculations. The initial stage is image processing, the results of the parameters obtained will be calculated using Denmark Schoorl, Schoorl Indonesia, Winter Europe/Scheiffer, and Winter Indonesia formula. Calculation obtained will be learned by comparing it with the actual weight of livestock. The results of this learning process obtained weights that can be used to predict cattle weight. The results show using an artificial selected weighting method, the accuracy of prediction can be increased.