Kholili, Hasbi Rizki (2024) Analisis Pola Persebaran Penyakit Melalui Sistem Informasi Geografi di Daerah Kabupaten Malang. Undergraduate thesis, Fakultas Teknologi Informasi Universitas Merdeka Malang.

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Abstract

This research on analyzing disease distribution patterns through Geographic Information Systems (GIS) in urban areas has great relevance in the context of public health. In urban areas, the population tends to be dense, and socio-economic activity is high, which makes it vulnerable to infectious diseases. The distribution pattern of this disease is very complex and sometimes difficult to identify without the help of technology. With the continued growth of cities, a better understanding of the distribution pattern of this disease has become very important for disease prevention and control efforts. This research is a type of quantitative research with quantitative methods. The result of this research is an information system map of the number of dengue fever cases in community health centers in Malang Regency in 2022 by month. The map is displayed using data grouping carried out by the K-Means Clustering algorithm. This algorithm takes input as data and outputs as a group map. The results of making a GIS map in geographic data for Malang Regency are a large and varied area, with topography that is mostly mountainous. This makes Malang Regency a major tourist destination in East Java. The dataset used in this research is data on the number of cases of dengue fever in community health centers throughout Malang Regency. The dataset has several attributes, namely number, health center, month, latitude, longitude, and total. There are 4
clusters formed, namely clusters 1 to 4. Based on the results of the GIS map, there are several months where the number of dengue fever cases fluctuates the highest. For example, in June and July, there was a significant increase in the number of dengue fever cases, especially in Cluster 4. 4. Dampit is the sub-district with the third largest population in cluster 4. In discussing the highest case centers, cluster 4 is one of the focuses of the highest cases. . Meanwhile, the largest number of residents, namely in cluster 1, is not the focus of the highest cases. The planning
strategy to prevent the spread of dengue fever is to increase surveillance in Clusters 2 and 4, especially in January, June and July.

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