Decision Support System Two Dimensional Cattle Weight Estimation using Fuzzy Rule Based System

Cattle weight estimation technology is needed in the present era. Cattle scales are very expensive and not all cattle farmers can afford this. When weighing cattle, farmer must bring their cattle to the cattle market or a place provided by the government for cattle weighing. This becomes impractical, so technology is needed to make it easier for farmers. This research proposes decision support system for farmer estimating of cow weight using the Fuzzy Rule Based System. The method used in this research is first to capture cows from a certain distance, then through image processing, the length of the cow's body and chest circumference are measured. On the other hand, the cow is weighed, and the cow's body length and chest circumference are measured directly. The next process is to build a decision support system based on the data that has been obtained. Fuzzy used in this research is Mamdani by using fuzzification defuzzification centroid, bisector, mean of maxima (mom), and som. The membership function used gaussian with five membership function for input (2 input) and output. The test results obtained using fuzzification defuzzification centroid and mom are 81.24%. While when implement bisector 80.945 and using mom produced accuracy 73.36%.