System for Determining Public Health Level Using the Agglomerative Hierarchical Clustering Method


View Publication Info
Field Value
Title System for Determining Public Health Level Using the Agglomerative Hierarchical Clustering Method
Creator Suhirman, Suhirman
Wintolo, Hero
Health Level, Health Indicators, Agglomerative Hierarchical Clustering, Cluster
Description Regions having higher level of welfare do not always have better indicator values than other regions having lower level of welfare. The problem is the lack of information related to the indicator values needed to determine the health level. Therefore, clustering using health data becomes necessary. Data were clustered to see the maximum or the minimum level of similarity. The clustered data were based on the similarity of four morality indicator values of the regional health level. Morality indicator values used in this research are infant mortality rate, child mortality rate, maternal mortality rate, and rough birth rate. The method used is Agglomerative Hierarchical Clustering (AHC) - Complete Linkage. Data were calculated using Euclidean Distance Equation, then Complete Linkage. Four clustered data were grouped into two clusters, healthy and/or unhealthy. The result, combining from all clusters into two large clusters to see healthy and unhealthy results.
Publisher Sekolah Tinggi Teknologi Adisutjipto Yogyakarta
Date 2019-03-22
Type info:eu-repo/semantics/article

Format application/pdf
Source Compiler; Vol 8, No 1 (2019): Mei; 95-104
Language ind
Rights Copyright (c) 2019 Compiler

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us


Copyright © 2015-2018 Simon Fraser University Library