RESUMO
Background and Aim: The "Five Freedoms" concept has shaped the development and implementation of animal welfare assessments. This study aimed to analyze the determinants that impact the understanding of animal welfare among individuals who own cats in Banyuwangi, East Java, Indonesia. Materials and Methods: Questionnaires and interviews were used in this study to gather data from cat owners. One hundred cat owners in Banyuwangi Regency took part in the study. The classification considered factors such as gender, age, education level, occupation, income, and number of cats. The questionnaire passed both validity and reliability tests and was thus deemed suitable for data measurement. The Chi-square test was employed to investigate relationships within the dataset. Results: A statistically significant correlation (p < 0.05) was established between cat owners' level of education, occupation, monthly household income, and their grasp of animal welfare, with the number of cats in their household being a determinant factor. Some cat owners in Banyuwangi undervalue veterinarians' role in treating and preventing feline health issues. The cat owners' understanding of animal welfare was unaffected by their age or gender. 59% of the cat owners had a low understanding level, 22% had a moderate understanding level, and 19% had a high understanding level. Conclusion: In Banyuwangi Regency, 59% of cat owners lack understanding of animal welfare concerns. An owner's educational background, job, income, and whether they own a cat impact their comprehension of animal welfare principles. Limited awareness of animal welfare and veterinarians' roles exists in Indonesia. It is crucial to educate government officials, veterinarians, and regional leaders about animal welfare for the sake of sustainability. A complete understanding of this topic demands rigorous research, comprehensive studies, and reproducibility. Equally important is effective publicity for the cat population.
RESUMO
Indonesia needs to lower its high infectious disease rate. This requires reliable data and following their temporal changes across provinces. We investigated the benefits of surveying the epidemiological situation with the imax biclustering algorithm using secondary data from a recent national scale survey of main infectious diseases from the National Basic Health Research (Riskesdas) covering 34 provinces in Indonesia. Hierarchical and k-means clustering can only handle one data source, but BCBimax biclustering can cluster rows and columns in a data matrix. Several experiments determined the best row and column threshold values, which is crucial for a useful result. The percentages of Indonesia's seven most common infectious diseases (ARI, pneumonia, diarrhoea, tuberculosis (TB), hepatitis, malaria, and filariasis) were ordered by province to form groups without considering proximity because clusters are usually far apart. ARI, pneumonia, and diarrhoea were divided into toddler and adult infections, making 10 target diseases instead of seven. The set of biclusters formed based on the presence and level of these diseases included 7 diseases with moderate to high disease levels, 5 diseases (formed by 2 clusters), 3 diseases, 2 diseases, and a final order that only included adult diarrhoea. In 6 of 8 clusters, diarrhea was the most prevalent infectious disease in Indonesia, making its eradication a priority. Direct person-to-person infections like ARI, pneumonia, TB, and diarrhoea were found in 4-6 of 8 clusters. These diseases are more common and spread faster than vector-borne diseases like malaria and filariasis, making them more important.