Pemetaan Sebaran Kasus Demam Berdarah Dengue  (DBD) Menggunakan Geographic Information System (GIS) di Puskesmas Karangsari Tahun 2025

Putri Amelia; Yanto Haryanto; Bhakti Aryani; Fitria Dewi Rahmawati

doi:10.55606/jig.v4i3.9086

Authors

Putri Amelia Poltekkes Kemenkes Tasikmalaya, Indonesia
Yanto Haryanto Poltekkes Kemenkes Tasikmalaya
Bhakti Aryani Poltekkes Kemenkes Tasikmalaya
Fitria Dewi Rahmawati Poltekkes Kemenkes Tasikmalaya

DOI:

https://doi.org/10.55606/jig.v4i3.9086

Keywords:

Dengue Hemorrhagic Fever (DHF), Geographic Information System (GIS), Karangsari Health Center, QGIS, Spatial Mapping

Abstract

Dengue Hemorrhagic Fever (DHF) remains a major public health problem in Indonesia, particularly in densely populated areas. Control efforts require accurate data and spatial analysis to understand disease distribution patterns. Geographic Information System (GIS) is an effective tool for visualizing case distribution and supporting surveillance and planning of control programs at the primary healthcare level. This study aims to describe the spatial distribution of Dengue cases based on medical record data and produce a geographic distribution map to support Dengue control efforts at the Puskesmas level. This study used a quantitative descriptive design with secondary data from medical records at Karangsari Health Center. The sample consisted of 255 DHF patients in 2025, selected using a total sampling technique. Data were processed through editing, geocoding patient addresses, and spatial analysis using QGIS software.The results showed 255 Dengue cases in 2025 with fluctuating monthly trends, peaking in April and lowest in December. Case distribution was uneven and tended to cluster. High-risk areas accounted for 15.7%–21.2%, moderate-risk areas 9.8%–15.7%, and low-risk areas 7.1%–9.8%. Megu Cilik Village had the highest proportion of cases, while other villages were categorized as moderate and low risk. This pattern indicates that Dengue incidence is influenced by environmental conditions, vector density, host factors, rainfall, and Aedes aegypti presence. GIS provides clearer spatial visualization, helping identify high-risk areas and supporting targeted public health interventions.

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