Clustering Analysis and Mapping of ISPA Disease Spread Patterns in Bireuen District

Clustering Analysis and Mapping of ISPA Disease Spread Patterns in Bireuen District

clustering; DBCAN; distribution pattern detection; ISPA; mapping

ISPA disease can be detected by analyzing the regional distribution map of the disease. Early detection of ARI is very important
for effective prevention. The study conducted in Bireuen Regency used data from 2019 to 2021, sourced from dr. Fauziah
Bireuen Hospital, revealed that there was an increase in ARI cases from an average of 13.18 to 59.24 per year. The aims of
the study were to identify ARI clusters, analyze disease patterns using Spatial Pattern Analysis and Flexible Shaped Spatial
Scanning Statistics. The methodology involves collecting patient data for each ARI case and processing it using DBSCAN to
obtain cluster points on the map. Spatial Pattern Analysis is used to analyze these clusters and identify hotspot points on the
map. The analysis resulted in four clusters: Cluster 1 (6 subdistrict), Cluster 2 (4 subdistrict), Cluster 3 (1 subdistrict), and
Cluster 4 (6 subdistrict). The study identified 6 hotspots in 2019, 5 hotspots in 2020, and 6 hotspots in 2021. Each ARI disease
clustering map shows the distribution of ARI cases and identifies areas prone to the disease. These findings provide valuable
insights for targeted interventions and preventive actions in identified high-risk areas of ISPA.

Mutammimul Ula, Tsania Asha Fadilah Daulay, Richki Hardi, Sujacka Retno, Angga Pratama, Ilham
Sahputra

http://jurnal.iaii.or.id

Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association

June 2023

Sri Wahyuni

ISSN Media Electronic: 2580-0760

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