Open AccessFormulation of city health development index using data mining
Author(s) -
Bertalya Bertalya,
Prihandoko Prihandoko,
Lilis Setyowati,
Febrian Iftikhar Irawan,
Syahifa Rahmita Irlianti
Publication year - 2021
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v23.i1.pp362-369
Subject(s) - public health , index (typography) , environmental health , data collection , business , computer science , medicine , mathematics , statistics , nursing , world wide web
Every five years Public Health Research publishes a Public Health Development Index that describes public health in Indonesia. The Public Health Development Index is measured using data from the Public Health Research and the National Socio-Economic Survey, and the Village Potential Survey which is obtained by surveying from sampling data. In fact, the Provincial and City Health Offices have health profile data reports every year. For this reason, this study analyzes existing health profile data using data mining techniques to obtain indicator data that are very influential in formulating the City Health Development Index. This City Health Development Index was successfully formulated by adopting the Model of Public Health Development Index in 2013 and using indicators from annual health profile data which obtained from the data mining process, i.e., Random Forest algorithm. The proposed model can be used as the annual report of a city to describe the health condition of that city. For the future research, the model can be adopted to measure some specific aspects of city health condition.