This study investigates how Electronic Livestock Health Recording Systems (ELHRs)
facilitates the detection of disease burden and make cluster analysis by applying data
analytics tools and techniques. A sample size of 18333 livestock disease cases reported from
2007-2015 by the Ministry of Agriculture of the Federal Democratic of Ethiopia was used for
data collection. The results showed that ELHRs are important as livestock disease data
preservers, saving costs, and facilitating the extraction of up-to-date and complete
information. Euclidean and Manhattan distance performed well at 98%, while cosine distance
measurement metrics performed poorly. Finally, with the application of the selected
clustering techniques, metrics, tools, and dataset, it has been attempted to successfully detect
an optimal number of disease clusters and meet the objectives of the study.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.