Chicken Weight Prediction in Close House Farm Using Fuzzy Method
Kharis Suryandaru Pratama(1), Retantyo Wardoyo(2*)
(1) Universitas Gadjah Mada
(2) Department of Computer Science and Electronics, Universitas Gadjah Mada
(*) Corresponding Author
Abstract
This study aims to predict the weight of chicken on a close house farm using the Fuzzy Logic method by implementing the LUKASEWICZ method. The data used in this study are the factors that affect the weight of the chicken including the number of chickens entering, the initial weight of the chicken, the temperature of the cage, the humidity of the cage, the quantity of water, the quantity of feed, and air circulation (wind speed) in the cage. The results of the calculation of Fuzzy with the łukasiEwicz method of these factors can be used to predict the chicken boboy during the harvest period and according to the weight set during the harvest period. The accuracy of the prediction value with the Absolute Percentage Error (MAPE) mean test shows the value of 5,3981%. It was concluded that the calculation of fuzzy with the łukasiewicz method can be used to predict the weight of chicken during the harvest period.
Keywords
Fuzzy Logic; Łukasiewicz; Close House Farm; Chicken Weight
Full Text:
PDFDOI: https://doi.org/10.22146/ijccs.96406
Article Metrics
Abstract views : 750 | views : 641Refbacks
- There are currently no refbacks.
Copyright (c) 2024 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
View My Stats1