Density Based Spatial Clustering of Applications and Spatial Pattern Analysis In Mapping the Distribution of ISPA Disease in Bireuen Regency

Abstract

ISPA is an infectious disease transmitted through the air. ISPA disease can be detected through the regional distribution maps of disease. ISPA disease can be prevented in the early detection before the disease gets worse. This can prevent the spread of the disease further. Data on ISPA cases in 2019 to 2021 in Bireuen Regency from the medical records of dr. Fauziah Bireuen from an average of 13.18 to 59.24 per year. This research aims to determine the clusters of ISPA spread areas across the district of Bireuen and to analyze the distribution of disease patterns with Spatial Pattern Analysis and to map the respiratory diseases in each area with Flexibly Shaped Spatial Scan Statistics. The methodology in this research are collecting the data at the hospital for each area of ISPA patients and the data processed by using DBSCAN to obtain the cluster points on the map. The result of the DBSCAN model are clusters. The cluster results are next processed with the distribution of hotspot point on the map using the Spatial Pattern Analysis model, and the map of the prone of the spread of ISPA in Bireuen Regency is processed by using the Flexibly Shaped Spatial Scan Statistic method. Information from the map obtained that the first 4 clusters of the area are formed, namely 3 clusters and 1 outlier. Cluster 1 and outliers consist of 6 sub-districts, cluster 2 consist of 4 sub-districts and cluster 3 only has 1 sub-district. There are 6 hotspot areas in 2019, 5 hotspot areas in 2020, and 6 hotspot areas in 2021. The results of this research are each ISPA disease clustering map shows the results of the ISPA distribution on the map and areas that are prone to ISPA disease in Bireuen Regency are Jeunieb and Peusangan

Keywords

• clustering, ispa, dbcan, mapping, distribution pattern detection