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Expert System to Determine the Fermentation Quality of Sheep Feed Using Forward Chaining Method Yunita, Farida; Sadya, Siwi Bi'arfina; Mubarrok, Fatih Syariful; Widiarto, Ragil; Pamungkas , Setyo
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 3 (2024): Volume 4 Issue 3, 2024 [August]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i3.780

Abstract

Livestock productivity is strongly influenced by three main pillars: breeding, feeding, and management. The quality of animal feed, especially for sheep, is highly dependent on the raw materials used, which must have a balanced nutritional content and quality. Grass as the main feed is becoming increasingly difficult to obtain due to land conversion, so the use of concentrates and feed fermentation techniques is a promising solution. This research focuses on the development of an expert system to determine the quality of fermented sheep diets using the forward chaining method. The forward chaining method is used to organize the facts and data collected to arrive at the optimal solution. Feed quality is classified into three grades (G1, G2, G3) based on the ingredients used and certain criteria. Through observation, interviews, problem identification, understanding, analysis, and literature study, this system is designed to assist farmers in choosing the right and efficient feed ingredients. The results show that this expert system is effective in identifying and classifying the quality of fermented sheep diets and provides clear guidance to feed manufacturers in selecting suitable ingredients. The system is also expected to be developed into a mobile application to help users obtain information quickly and accurately, thereby increasing the efficiency and effectiveness of sheep feed management.