Image of Analisa Algoritma Agglomerative Hierarchical Clustering Terhadap Pola Penyebaran Penyakit Pasien Pengguna Bpjs (Studi Kasus : Rumah Sakit Jiwa Tampan)
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Analisa Algoritma Agglomerative Hierarchical Clustering Terhadap Pola Penyebaran Penyakit Pasien Pengguna Bpjs (Studi Kasus : Rumah Sakit Jiwa Tampan)

Tampan Mental Hospital (RSJ) is an institution that implements BPJS in the realm of mental health. However, RSJ Tampan experienced problems in managing information and data on mental disorder patients using BPJS. This is influenced by the fact that there is not yet a qualified database system available so that internal RSJ Tampan does not know the picture of the disease distribution patterns of BPJS patients. The aim of the research is to produce a pattern of disease spread in the patient's area of origin based on the average percentage of sufferers. This research uses CRISP-DM modeling, the Agglomerative Hierarchical algorithm and Rstudio. The research data comes from 500 data records of mental disorder patients using BPJS in 2021 which focuses on variables of regional origin and type of disease. The final clustering results show that the Average Linkage is the best method with a Cophenetic Correlation of 0.9925086 which forms 4 clusters with very low, low, high and very high criteria. Criteria labeling is based on the average percentage of sufferers in the patient's area of origin.

Keywords : Agglomerative Hierarchical, BPJS, Clustering, Disease Spread Pattern

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Perpustakaan Universitas Riau 1903112470
1903112470
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No. Panggil
1903112470
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Pekanbaru : Universitas Riau – FMIPA – Sistem Informasi.,
Deskripsi Fisik
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Bahasa
Indonesia
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1903112470
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SISTEM INFORMASI
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