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Application of correspondence analysis on the spread of foot and mouth disease in cattle in East Java, Indonesia
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Objective: This study aims to apply correspondence analysis to map the cases of Foot and Mouth Disease (FMD) in cattle across East Java. The primary objective is to identify the patterns of spread and severity of FMD cases by categorizing each case based on criteria of death, forced culling, and illness across various districts and cities in East Java.
Method: The data used in this study were obtained from reports by the Livestock Department, which recorded incidents of FMD in various districts and cities in East Java. After data collection, the data were processed using correspondence analysis with the help of SPSS software version 27. Through this method, we aim to identify and visualize the relationships between the location of the incidents and the three response categories of cases: death, forced culling, and sickness.
Results: The results of the correspondence analysis showed that the proportion of cattle deaths due to FMD was the highest, followed by forced culling actions and sickness cases. Data visualization indicated specific patterns of distribution and severity of FMD that varied between different districts and cities in East Java. Some locations showed higher death incidents, while in other locations, cases of sickness or forced culling were more predominant.
Conclusion: Correspondence analysis successfully grouped the FMD cases in cattle in East Java based on the criteria of death, forced culling, and sickness. This study provides significant insights regarding the geographic distribution and response variability to the FMD outbreak in East Java. With this understanding, strategic and location-specific steps can be taken to eradicate FMD, including increased vigilance, resource allocation for medical actions, and more effective disease control policies in the most affected areas. This research demonstrates the importance of in-depth data analysis in addressing disease outbreaks in the livestock sector, thus facilitating more informed and effective decision-making in efforts to combat the disease.
Title: Application of correspondence analysis on the spread of foot and mouth disease in cattle in East Java, Indonesia
Description:
Objective: This study aims to apply correspondence analysis to map the cases of Foot and Mouth Disease (FMD) in cattle across East Java.
The primary objective is to identify the patterns of spread and severity of FMD cases by categorizing each case based on criteria of death, forced culling, and illness across various districts and cities in East Java.
Method: The data used in this study were obtained from reports by the Livestock Department, which recorded incidents of FMD in various districts and cities in East Java.
After data collection, the data were processed using correspondence analysis with the help of SPSS software version 27.
Through this method, we aim to identify and visualize the relationships between the location of the incidents and the three response categories of cases: death, forced culling, and sickness.
Results: The results of the correspondence analysis showed that the proportion of cattle deaths due to FMD was the highest, followed by forced culling actions and sickness cases.
Data visualization indicated specific patterns of distribution and severity of FMD that varied between different districts and cities in East Java.
Some locations showed higher death incidents, while in other locations, cases of sickness or forced culling were more predominant.
Conclusion: Correspondence analysis successfully grouped the FMD cases in cattle in East Java based on the criteria of death, forced culling, and sickness.
This study provides significant insights regarding the geographic distribution and response variability to the FMD outbreak in East Java.
With this understanding, strategic and location-specific steps can be taken to eradicate FMD, including increased vigilance, resource allocation for medical actions, and more effective disease control policies in the most affected areas.
This research demonstrates the importance of in-depth data analysis in addressing disease outbreaks in the livestock sector, thus facilitating more informed and effective decision-making in efforts to combat the disease.
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