scholarly journals Pemodelan Indeks Pembangunan Manusia (IPM) Metode Baru Menurut Provinsi Tahun 2015 Menggunakan Geographically Weighted Regression (GWR)

2019 ◽  
Vol 2 (1) ◽  
pp. 21
Author(s):  
Akbar Maulana ◽  
Renny Meilawati ◽  
Vita Widiastuti
Keyword(s):  
Regression Analysis ◽  
Human Development ◽  
Geographically Weighted Regression ◽  
Human Development Index ◽  
Spatial Regression ◽  
Least Square ◽  
Gaussian Kernel ◽  
Weighted Regression ◽  
Development Index ◽  
Spatial Regression Analysis

<p>The Human Development Index (HDI) is a parameter of quality of life for an area. The HDI explains how residents can access the results of development in obtaining income, health and education. One method that can be used to find out the factors that influence the human development index in modeling is regression analysis of ordinary least square (OLS). In the Human Development Index data, there is a dependency between measuring data and the location of a region. Therefore, spatial regression analysis can be used in this study. The local form of spatial regression analysis is <em>geographically weighted regression</em> (GWR). GWR shows the existence of spatial heterogeneity (location). This study compares between OLS regression and GWR in the new human development index method by province in 2015. In the GWR model we use fixed Gaussian kernel and kernel fixed bisquare as weighted function. The optimal bandwidth value is obtained by minimizing the cross validation (CV) and Akaike information criterion (AIC) coefficients. The results showed that the GWR model with Gaussian kernel function is better than GWR with bisquare kernel function and OLS model.</p><p><strong>Keywords</strong><strong>: </strong>human development index, ordinary least square,<strong> </strong>geographically weighted regression, kernel fixed Gaussian,  kernel fixed bisquare</p>

scholarly journals FAKTOR–FAKTOR YANG BERPENGARUH SIGNIFIKAN TERHADAP INDEKS PEMBANGUNAN MANUSIA DI PROVINSI PAPUA

2020 ◽  
Vol 9 (1) ◽  
pp. 31
Author(s):  
INA AZIZAH KADRI ◽  
MADE SUSILAWATI ◽  
KARTIKA SARI
Keyword(s):  
Spatial Heterogeneity ◽  
Human Development ◽  
Geographically Weighted Regression ◽  
Human Development Index ◽  
Weighting Function ◽  
Human Life ◽  
Gaussian Kernel ◽  
Weighted Regression ◽  
Years Of Schooling

Geographically weighted regression (GWR) analysis is one of an analysis to resolve the problem with data contains effect of spatial heterogenity. One of the problems which considers spatial heterogeneity is human development index (HDI). HDI is an indicator that used to measure success in building quality of human life. One of the provinces with the lowest HDI in Indonesia is Papua. The purpose of this research  is to know the contribution of each HDI factors in Papua using GWR method. The weighting function used is adaptive gaussian kernel. The results of this research showed HDI’s dominant factors in Papua, expected years of schooling and mean years of schooling.

scholarly journals INDEKS PERSEPSI KORUPSI DAN PEMBANGUNAN MANUSIA TERHADAP PERTUMBUHAN EKONOMI DI NEGARA-NEGARA ASIA TENGGARA

Jurnal Ecogen ◽  
2019 ◽  
Vol 1 (3) ◽  
pp. 681
Author(s):  
Muhammad Fajar ◽  
Zul Azhar
Keyword(s):  
Economic Growth ◽  
Human Development ◽  
Human Development Index ◽  
Fixed Effect Model ◽  
Southeast Asian ◽  
Least Square ◽  
Asian Countries ◽  
Development Index ◽  
The Government ◽  
Southeast Asian Countries

This research aims to know and analyze determine of corruption and the human development index to economic growth in Southeast Asian countries. This research use panel least square and Fixed Effect Model. The estimation result should that corruption has a possitive and significant effect on economic growth in Southeast Asian countries and the human development Index has a possitive and significant effect on economic growth in Southeast Asian countries. From the result of this research, to increase economic growth, the government in SoutheastAsian countries must strengthen the bureaucratic and legal institutions of a country,increase the role of the government or related agencies in monitoring and crackingdown on corruption that results in lossof government productivity and allocating resources appropriately so that the creation of peace and prosperity among the countries in Southeast Asian. Keywords: Economic Growth, Corruption, Human Development Index

ANALISIS PENGARUH INDEKS PEMBANGUNAN MANUSIA DAN TINGKAT PENGANGGURAN TERBUKA TERHADAP KEMISKINAN DI INDONESIA

2019 ◽  
Vol 2 (2) ◽  
pp. 77-89
Author(s):  
Saparuddin Mukhtar ◽  
Ari Saptono ◽  
As’ad Samsul Arifin
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Human Development ◽  
Unemployment Rate ◽  
Human Development Index ◽  
Secondary Data ◽  
Lagrange Multiplier Test ◽  
Development Index ◽  
Analysis Techniques ◽  
Negative Effect

Abstract - This study aims to determine the effect of Human Development Index and Open Unemployment to poverty in Indonesia. The data in this study are secondary data about the human development index, the opened unemployment rate, and the percentage of poverty. The data is obtained from panel data of 33 provinces in Indonesia for 4 years from 2011 to 2014. The data analysis techniques uses regression analysis by using Random Effects based on the results of the Lagrange Multiplier test. The results showes that the Human Development Index hasa significant negative effect to poverty. Meanwhile, the level of opened unemployment has no significant effect to poverty in Indonesia. Keywords: Human Development Index, Opened Unemployment Rate, Poverty

scholarly journals ANALISIS PENGARUH INDEKS PEMBANGUNAN MANUSIA, PDRB PER KAPITA, DAN JUMLAH PENGANGGURAN TERHADAP JUMLAH PENDUDUK MISKIN DI PROVINSI JAMBI

2018 ◽  
Vol 2 (1) ◽  
pp. 165
Author(s):  
Yunie Rahayu
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Linear Regression Analysis ◽  
Geographic Location ◽  
Least Square ◽  
Gdp Per Capita ◽  
Development Index ◽  
The Poor ◽  
Per Capita ◽  
Poor Population

Poverty is a problem faced by all countries in the world, especially the developing countries, such as Indonesia. Poverty is a complex issue that is affected by a variety of interrelated factors, such as people's income levels, unemployment, health, education, access to goods and services, geographic location, gender, and location the environment. The number of poor population in Central Java is relatively lebihtinggi compared to laindi province of Indonesia, that is occupying ranked second in the number of poor population the largest in Indonesia after East Java. This research aims to analyze how and how much the variable influences the human development index, GDP per capita, and the number of poor population against unemployment in Jambi province in the year 2016. Methods of analysis in this study using multiple linear regression analysis with the method of Ordinary Least Square (OLS) that use data between spaces (cross section) district/town in Jambi province year 2016 with the help of software Eviews 4.1. The results of this research indicate that the variable is the human development index (HDI) a negative and significant effect against the poor population in the province of Jambi, the per capita GDP is negative and significant effect against the number of poor population in The province of Jambi, the unemployment and the number of positive and significant effect against the poor population in the province of Jambi.Keywords: population of the poor, the human development index (HDI), GDP per capita, and the number of Unemployed

scholarly journals PEMODELAN INCIDENT RATE DEMAM BERDARAH DENGUE DI INDONESIA YANG BERKAITAN DENGAN FAKTOR LINGKUNGAN MENGGUNAKAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION (GWR)

EKOLOGIA ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 64-73
Author(s):  
Kiki Amelia ◽  
Latifa Oktafiani Asril ◽  
Lasmi Febrianti
Keyword(s):  
Population Density ◽  
Dengue Hemorrhagic Fever ◽  
Geographically Weighted Regression ◽  
Physical Environment ◽  
Secondary Data ◽  
Hemorrhagic Fever ◽  
Least Square ◽  
Gaussian Kernel ◽  
Weighted Regression ◽  
Incident Rate

Dengue hemorrhagic fever cases in Indonesia often occur in cities and villages. Every year hundreds to thousands of people must be hospitalized due to this disease. There are several factors of the physical environment that directly or indirectly influence the transmission of this disease. Such as rainfall, air temperature, and humidity. In addition to the physical environment there are several other factors that can increase the occurrence of dengue cases, namely population density and the level of larvae free in an area. For this reason, we conducted a study of the above factors and their contribution in the addition of dengue cases that occurred in Indonesia in 2015 using secondary data. The purpose of this study is to identify and make a BDB iricident rate model related to environmental factors such as temperature, humidity, population density, and the amount of rainfall on the number of cases of dengue hemorrhagic fever in Indonesia in 2015. The method used is the Geographically Weighted Regression method. (GWR). In the GWR model the parameter estimation uses Weighted Least Square (WLS) by weighting the gaussian kernel function. The results of the study concluded that modeling with GWR was better than linear regression and the variables were significantly different in each region.

scholarly journals Dampak Pengeluaran Pemerintah Terhadap Pertumbuhan Ekonomi dan Indeks Pembangunan Manusia di Perbatasan Indonesia

2017 ◽  
Vol 6 (2) ◽  
pp. 120
Author(s):  
Windhu Putra
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Human Development ◽  
Government Spending ◽  
Human Development Index ◽  
Least Square ◽  
Estimation Model ◽  
Development Index ◽  
Ordinary Least Square ◽  
Education And Health

The purpose of this study is to analyze the effect of government spending - for building infrastructures, education and health - on economic growth and Indonesian community welfare that reside along the borderline during the period of 2007 to 2014. The data used in this research is panel data. Applying estimation model of Ordinary Least Square (OLS), this research indicates that government expenditures for infrastructures and education created significant effect oneconomic growth while the expenditure for healthcare did not significantly affect the economic growth. However, in the case of people welfare, government spending on infrastructure and economic growth showed a significant effect on it, butthe government spending for education and healthcare had insignificant impact on human development index.

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