Smallest of Maximum to find α-predicate for DeterminingCattle Health Conditions

Abstract

Beef cattle is one of the livestock that can produce various human needs. All parts of a cattle, ranging from meat, skin, bones to cattle dung, can be utilized so that beef cattle are rate to have high economic value and become one of the common livestock to be cultivated. In beef cattle breeding, there are obstacles in maintaining and achieving the desired production results, one of which is cattle's death due to disease infection. Lose one or a group of cattle unpredictably, effecting a loss of investment and losses for the breeder. Biosecurity is required to reduce the risk of death from disease and maintain beef cattle's health and quality. However, the lack of awareness and concern of breeders in the biosecurity implementation has resulted in the high mortality rate for beef cattle in Indonesia. This study tries to apply the fuzzy algorithm into an animal inspection expert system at the Cimanggu Animal Clinic. The expert system can support collaboration between veterinarians and breeders in the implementation of biosecurity. The Smallest of the Maximum method provides to get the αpredicate from the ranking of possible diagnoses of cattle diseases. Then α-predicate is reprocessed by defuzzification of the Tsukamoto model and produces handling suggestions and information on the cattle's condition.

A Novelty Decision-Making Based on Hybrid Indexing, Clustering, and Classification Methodologies: An Application to Map the Relevant Experts Against the Rural Problem

“…In fuzzy theory, the Smallest of Maximum principles determines the predicate value by selecting the smallest domain value corresponding to the maximum membership value. In the defuzzification process, the output is generated through a transformation into a numeric value [12,13].…”