Regresi Logistik dengan Metode Bayes untuk Pemodelan Indeks Pembangunan Manusia Kabupaten/Kota di Pulau Kalimantan
Date
2021-11Author
Syafitri, Febriana
Goejantoro, Rito
Wasono, Wasono
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Show full item recordAbstract
Human Development Index (HDI) is an indicator that can measure success in efforts to build the
quality of human life. HDI is also a measure of the prosperity of a region which is observed based on three
dimensions, namely health, education and economy. Based on HDI publication by the Central Statistics
Agency in 2018, it showed that the scores of HDI for 56 districts/cities in Kalimantan Island only has two
categories of HDI which are medium and high. Bayesian method is a parameter estimation technique that
combines the likelihood and prior distribution functions. The estimation with Bayesian method was solved
using Markov Chain Monte Carlo simulation (MCMC) with Gibbs Sampler algorithm. The aim of this study
is to examine the modelling of the factors that influence the HDI of districts/cities in Kalimantan Island
and determine the accuracy of the model classification using logistic regression with Bayesian method. The
data used is the HDI of districts/cities in Kalimantan Island in 2018. Bayesian method is a parameter
estimation technique that combines the likelihood and prior distribution functions. The estimation with
Bayesian method was solved using Markov Chain Monte Carlo simulation (MCMC) with Gibbs Sampler
algorithm. The results of modelling and analysis on districts/cities HDI data on Kalimantan Island showed
that the factors that significantly influence HDI are the number of paramedic, the number of health facility
and the participation rate of high school. The results of the classification accuracy of the model amounted
to 82,14% which resulted in 37 districts/cities are categorized as the HDI medium category and 19
districts/cities are categorized as the HDI high category