Work

Chicken Weight Prediction in Close House Farm Using Fuzzy Method

Year: 2024

Type: article

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.

Source: IJCCS (Indonesian Journal of Computing and Cybernetics Systems)

DOI: 10.22146/ijccs.96406

Authors: Kharis Suryandaru Pratama, Retantyo Wardoyo

Institution: Universitas Gadjah Mada

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $13