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Rio Jumardi
Sekolah Tinggi Teknologi Bontang
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Journal : Jurnal Informasi dan Teknologi

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Pengelompokan Daerah Rawan Demam Berdarah Dengan Metode K-Means Clustering Sri Handani Widiastuti; Rio Jumardi
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i4.213

Abstract

The Dengue fever is a disease found in tropical and subtropical regions that is transmitted through the bite of the Aedes aegypti mosquito. Dengue fever is still a serious problem for public health in the city of Bontang. For that we need a system that can classify the areas of spread of dengue fever in the city of Bontang. The K-Means Clustering algorithm is a non-hierarchical data clustering algorithm that partitions data into one or more clusters or groups so that data with the same characteristics are grouped into the same cluster. To classify areas in the city of Bontang into three clusters, namely Sporadic, Potential, and Endemic. Three villages were selected as the centroid of each cluster, Bontang Kuala as the centroid of the sporadic cluster, Telihan as the centroid of the potential cluster, and Tanjung Laut as the centroid of the Endemic cluster. Village data, cluster data, and centroid data are processed using the K-Means Clustering algorithm, and application testing using Black Box Testing. The results of the application using the clustering method obtained information that there were five villages for sporadic clusters, five villages for potential clusters, and five villages for endemic clusters from a total of 15 villages used as samples for environmental health by the Bontang City Health Service.
Co-Authors Abadi Nugroho Al Rosyid Anggi Satrya Arfittariah Arfittariah Deanita Sari Maghfirah Maghfirah Nikita Adriyani Nur Fajariah Ramadhania Sri Handani Widiastuti Zaini Zaini