Implementasi Algoritma K-Means Dalam Pengelompokan Kasus Penyakit Tuberkulosis Paru Berdasarkan Provinsi

Vivi Febriyanti, Heru Satria Tambunan, Ilham Syahputra Saragih, Irfan Sudahri Damanik, Harly Okprana

Abstract


Pulmonary tuberculosis is a lung disease caused by germs that cause symptoms of excessive coughing. In Indonesia, pulmonary tuberculosis is a disease in the top five countries with many pulmonary tuberculosis. The purpose of this study was to determine the high and low number of cases of pulmonary tuberculosis in the province. In this study the data used were sourced from the National Statistics Agency for 2007-2015. For this reason the authors use data mining techniques in the data processing with k-means clustering method to obtain information based on data that is processed as a reference to find out the number of cases of pulmonary tuberculosis that most suffered by province. The results of this study are grouping the number of cases of pulmonary tuberculosis with 3 clusters, namely high cluster, medium cluster, low cluster. From the calculation of k-means, there were 3 provinces as high clusters, 3 provinces as medium clusters, and 28 provinces as low clusters. The implementation process using the RapidMiner 5.3 application is used to help find accurate values.

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References


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DOI: http://dx.doi.org/10.30645/senaris.v2i0.194

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