scholarly journals MODEL GEOGRAPHICALLY WEIGHTED PANEL REGRESSION (GWPR) DENGAN FUNGSI KERNEL FIXED GAUSSIAN PADA INDEKS PEMBANGUNAN MANUSIA DI JAWA TIMUR

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Dia Cahya Wati ◽  
Herni Utami
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Weighting Function ◽  
Average Length ◽  
Local Linear Regression ◽  
Coefficient Of Determination ◽  
Model Parameters ◽  
Panel Regression ◽  
Spatial Effects ◽  
Development Index

The Geographically Weighted Panel Regression (GWPR) model is a com-bination of panel data and GWR. The GWPR model is a development of the globalregression model where ideas are taken from non-parametric regression. This model is alinear regression model that is local (local linear regression) which produces an estima-tor of the model parameters that affects local for each point or location where the datais collected. The purpose of this study is form a GWPR model with a fixed gaussiankernel weighting function in overcoming the problem of spatial effects and geographicalfactors that affect an area to another region. The data used in this study is secondarydata taken from the Central Statistics Agency (BPS) website consisting of the HumanDevelopment Index in East Java 2013-2016. This study produces data for the making ofthe Human Development Index using the GWPR method in the formation of the model,where the coefficient of determination generated is 98,74%.Factors that increase HDI es-pecially Mojokerto Regency are average length of school (RLS), life expectancy (AHH),and the construction expensiveness index (IKK). Keywords: GWPR, Fixed Gaussian, Human Development Index, East Java.

scholarly journals ANALISIS PENGARUH ANGKA HARAPAN LAMA SEKOLAH, RATA-RATA LAMA SEKOLAH, DAN PENGELUARAN PER KAPITA TERHADAP INDEKS PEMBANGUNAN MANUSIA DI PROVINSI JAWA TENGAH

2021 ◽  
Vol 3 (2) ◽  
pp. 126-140
Author(s):  
A. Jauhar Mahya
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Local Governments ◽  
Average Length ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Development Index ◽  
Capita Expenditure ◽  
Central Java ◽  
Per Capita

The Human Development Index (HDI) is one of the data and information used by local governments to measure the achievement of human development. HDI is formed by three basic dimensions, namely a long and healthy life, knowledge, and a decent standard of living. This study explain whether there is an influence and to obtain the magnitude of the influence of the expected number of years of schooling, the average length of schooling, and the per capita expenditure together on the Human Development Index in Central Java Province. This study was completed using multiple linear regression analysis with the help of SPSS 1.6 (Statistical Package for Social Sciences) software. The results of this study indicate that the expected length of schooling, average length of schooling, and per capita expenditure have a significant effect on the human development index, which is 97.8% and only 2.2% is influenced by other factors.

An Analysis of The Relation Between Foreign Direct Investment and Sociopolitical Variables in MENA Countries by Panel Regression

2019 ◽  
Vol 8 (1) ◽  
pp. 15-30
Author(s):  
Betül Gür
Keyword(s):  
Foreign Direct Investment ◽  
Human Development ◽  
Human Development Index ◽  
Direct Investment ◽  
Multidimensional Poverty ◽  
Panel Regression ◽  
Poverty Index ◽  
Development Index ◽  
Mena Countries ◽  
Multidimensional Poverty Index

Foreign direct investment (FDI) plays the role of an accelerator for the economic growth in host countries. Countries that provide the suitable environment economically and politically get ahead in this race. Over the last five years, the weighted importance of sociopolitical variables in the decision-making process has increased. The countries of the Middle East and North Africa (MENA) region, although they have a potential to develop, are regarded as country groups that have not yet fully achieved this. This article reveals and interprets the relationship between FDI and sociopolitical variables such as political risk, human development index, terrorism risk index, multidimensional poverty index, the rule of law, regulatory quality, and control of corruption, utilizing panel regression analysis. In the analysis of the MENA countries covering the years 2010-2016, it was concluded that all independent variables except the human development index and multidimensional poverty index were statistically significant and effective on FDI.

scholarly journals ANALISIS K-MEANS CLUSTER PADA KABUPATEN/KOTA DI PROVINSI BANTEN BERDASARKAN INDIKATOR INDEKS PEMBANGUNAN MANUSIA

2021 ◽  
Vol 2 (3) ◽  
pp. 267-281
Author(s):  
Rindang Ndaru Puspita
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Average Length ◽  
Human Life ◽  
Provincial Government ◽  
Cluster Method ◽  
Development Index ◽  
Life Expectancy At Birth ◽  
The People ◽  
The City

The Human Development Index (HDI) is one of the parameters of success in the development of the quality of human life, besides that at the regional level, the HDI is an indicator of the primary performance measurement and allocation of Regional Incentive Funds in promoting the welfare of the people in the area. In 2020 the Banten Province Human Development Index 72.45 only rose 0.01% compared to 2019, lower than the growth in 2019, which reached 0.68% and is still stuck in the high category (70≤HDI≤80), this indicates the progress of human development in Banten experienced a slowdown, In addition, when compared to the growth of the HDI-forming indicators in 2019, all components that make up the HDI experienced a slowdown in growth except for RLS which experienced growth acceleration of 0.33% from 1.39% in 2019 to 1.72% in 2020. So it is necessary to do a deeper analysis to determine the characteristics of the indicators that make up the HDI in the City as a contributor to the HDI value of the Banten Province so that efforts can be made to increase human development as evidence of improving the welfare of the people in the Banten Province. The K-Means Cluster method is used to group cities in Banten Province based on similar characteristics in terms of the HDI compiler indicators, including Life Expectancy at Birth, Expected Years of Schooling, and Average Length of School in, and Expenditure per Capita. Based on the results of the analysis obtained three clusters consisting of cities with similar characteristics in each cluster. Cluster 1 is a City with a low HDI indicator consisting of Pandeglang, Lebak, Serang. Cluster 2 is a City with a medium HDI indicator consisting of Tangerang, Cilegon, Serang City. Cluster 3 has a high HDI indicator consisting of Tangerang City and South Tangerang City. After obtaining City information based on the characteristics of each cluster, then the Banten Provincial government can provide direction and policies to each City in Clusters 1 and 2 to be able to develop activity programs with more attention to the HDI compiler indicators so that the Human Development Index in the City can increase

scholarly journals Analisis Dimensi Pembentuk Indeks Pembangunan Manusia (IPM) Provinsi Jambi 2010-2019

2020 ◽  
Vol 4 (2) ◽  
pp. 389
Author(s):  
Jasasila Jasasila
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Average Length ◽  
Health Sector ◽  
Numerical Data ◽  
Living Standard ◽  
Human Capabilities ◽  
Human Welfare ◽  
Development Index ◽  
Life Expectancy At Birth

Human development is a process and an outcome that is the process of enlarging people's choices but also becoming a goal. Human development implies that people must influence the processes that shape their lives. Human development is the development of society through the building of human capabilities, by society through active participation in the processes that shape life and society by improving their lives. It is broader than other approaches, such as the human resources approach, the basic needs approach and the human welfare approach. The problem of this research is how the development of the Human Development Index in Jambi Province in 2010-2019, the second problem is how to analyze the dimensions that form the Human Development Index in Jambi Province in 2010-2019, while the purpose of this study is, To determine the Development of the Human Development Index in the Province Jambi in 2010-2019 and to analyze the dimensions forming the human development index of Jambi Province in 2010-2019. The type of research that the writer uses in this thesis is the type of qualitative analysis and quantitative analysis. The data that is sought in this study is in the form of numerical data which includes data on life expectancy at birth, expectations of length of schooling and average length of schooling which are obtained from the official website of the BPS (Central Statistics Agency) Jambi Province. The results of this study indicate that during the period 2010 to 2019 the HDI of Jambi Province showed great progress. In 2019, the HDI of Jambi Province has reached 71 points, which means that it has increased from the “Medium” to “High” level compared to 2017. During the 2010-2019 period, the HDI of Jambi Province in the Health Sector has always shown an increase, the highest development was in 2019 of 0.23% and the lowest development was in 2017 at 0.07%. During 2010-2019 the HDI of Jambi Province in the Education Sector has always shown an increase, the highest increase in the indicator of long school expectancy (HLS) was in 2013 at 3.75 % and the lowest development was in 2019 at 0.23% and the highest development in the average length of school (RLS) indicator was in 2012 at 2.80% and the lowest development was in 2015 at 0.50%. During 2010-2019, the HDI of Jambi Province in the Decent Living Standard Sector has always shown an increase, the highest development was in 2018 at 4.82% and the lowest development was in 2013 at 0.80%.

scholarly journals Human development index modelling in South Kalimantan province using panel regression

2021 ◽  
Vol 2106 (1) ◽  
pp. 012004
Author(s):  
M Istiqhomah ◽  
N Salam ◽  
A S Lestia
Keyword(s):  
Quality Of Life ◽  
Data Analysis ◽  
Human Development ◽  
Human Development Index ◽  
Fixed Effect Model ◽  
Time Effect ◽  
Panel Regression ◽  
Development Index ◽  
Effect Model

Abstract Human development is a paradigm and becomes the focus and target of all development activities. Development is a way to improve welfare and a better quality of life. The Human Development Index (HDI) is one indicator to measure the success of a development. The purpose of this research is to describe the factors that are thought to influence HDI in South Kalimantan Province, estimate the parameters of the HDI panel regression model, and determine the best model. The data of this research is sourced from the Central Statistics Agency (BPS) of South Kalimantan Province with a period from 2015-2018. Based on the results of data analysis it can be concluded that the Fixed Effect Model with the time effect is the best model of the HDI panel regression in South Kalimantan Province with an R-Squared value of 99,81.

scholarly journals Pengaruh pertumbuhan ekonomi, indeks pembangunan manusia dan kepadatan penduduk terhadap tingkat kemiskinan kabupaten/kota di Provinsi Jambi

2019 ◽  
Vol 8 (2) ◽  
pp. 96-107
Author(s):  
Rahma Wardana Putri ◽  
Junaidi Junaidi ◽  
Candra Mustika
Keyword(s):  
Economic Growth ◽  
Population Density ◽  
Human Development ◽  
Human Development Index ◽  
Time Series Data ◽  
Secondary Data ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Poverty Level ◽  
Development Index

This study deals with the effect of economic growth, Human Development Index (HDI) and population density on the poverty levels of districts/cities in Jambi Province in 2013-2017. The type of data used in this study are combined secondary data from time series data and cross section data from 2013-2017. The data used is obtained from the official website of the Central Statistic Agency of Jambi Province. The analytical method used is panel data regression analysis. The result showed that the variabels of economic growth and population density had a siginificant effect on the poverty level of districts/cities in Jambi Province in 2013-2017. The coefficient of determination is 0.982702, which means that the independent variabels of economic growth, Human Developmet Index (HDI) and population density affect 98.27% of the dependent variabels of poverty in districts/cities in Jambi Province. Simultaneous test results (F test), show taht economic growth, Human Development Index (HDI) and population density simultaneously have a significant effect on the poverty level of districts/cities in Jambi Province. Keywords: Economic Growth, Human Development Index (HDI), Population Density, Poverty Level.

scholarly journals The Nexus Between Good Governance Indicators And Human Development Index In Africa: An Econometric Analysis

2020 ◽  
Vol 10 (2) ◽  
pp. 1
Author(s):  
Paulos C Tsegaw
Keyword(s):  
Regression Analysis ◽  
Human Development ◽  
Human Development Index ◽  
Good Governance ◽  
Political Stability ◽  
Development Effort ◽  
Panel Regression ◽  
African Countries ◽  
Development Index ◽  
Governance Indicators

This study examines the association between good governance indicators and the human development index in Africa. Accordingly, it uses the panel data of 49 African countries from 2000-2018 on the six World Bank governance indicators (WGIs) and the UNDP aggregate human development index (HDI). The data are analyzed using descriptive statistics and panel regression analysis. The descriptive statistical analysis shows that most of the countries that are scoring high in the governance indicators are also scoring high in the human development index. It also indicates that Africa's average score in all governance indicators from 2000-2018 ranges between 36.2 % and 40.4%, while the score for human development was 50.8%. Using a one-year moving average, the calculated improvement rates for the eighteen years in all the governance and human development indicators were meager. The finding from the panel regression analysis attests only the three good governance indicators - the rule of law, regulatory quality, and political stability and absence of violence - are significantly and directly associated with the human development index. The finding implies that policy makers in African countries should give emphasis on these three good governance indicators to augment their human development effort.

scholarly journals The Model of Per-Capita Expenditure Figures in Sumatera Selatan uses a Geographically Weighted Panel Regression

2021 ◽  
Vol 5 (1) ◽  
pp. 61-74
Author(s):  
Dia Cahya Wati ◽  
Dea Alvionita Azka ◽  
Herni Utami
Keyword(s):  
Regression Model ◽  
Weighting Function ◽  
Secondary Data ◽  
Coefficient Of Determination ◽  
Panel Regression ◽  
Spatial Effects ◽  
Capita Expenditure ◽  
Expenditure Rate ◽  
Global Regression ◽  
Per Capita

The Geographically Weighted Panel Regression (GWPR) is a development of a global regression model where the basic idea is taken from a combination of panel data and GWR. The GWPR model is built from the point approach method, which is based on the position of the coordinates of latitude and longitude. The parameters for the regression model at each location will produce different values. GWPR can accommodate spatial effects, so that it can better explain the relationship between response variables and predictors. The purpose of this study is to compare the GWPR model with the Fixed Gaussian and Adaptive Bisquare weighting functions based on the AIC value. The data used in this study is secondary data taken from the website of the Central Statistics Agency (BPS) in the form of Per-Capita Expenditure Figures in South Sumatra in 2013-2019. This research results that in the case of the Per-Capita Expenditure Rate (AP), it is better to use the GWPR method with a fixed gaussian weighting function in the modeling, where the resulting coefficient of determination is 95.81% rather than adaptive bisquare with a determination coefficient of 93.3%. The factors that influence the Per-Capita Expenditure Rate (AP) in South Sumatra on the fixed gaussian weighting are divided into 6 groups, while the adaptive bisquare is divided into 2 groups.

scholarly journals Spatial Investment Attractiveness Analysis for Regional Economic Development of Sumatera Selatan Province in 2010-2016

2019 ◽  
pp. 31-38
Author(s):  
Emawati . ◽  
Bambang Juanda ◽  
Alla Asmara
Keyword(s):  
Human Development ◽  
Geographically Weighted Regression ◽  
Human Development Index ◽  
Spatial Effect ◽  
Panel Regression ◽  
Development Index ◽  
Fixed Capital Formation ◽  
Per Capita ◽  
Regional Product ◽  
Gwr Model

Invesment attractiveness in Sumatera Selatan Province is interesting to be observed because it will make economic growth increased. As we know that distribution of investment in Indonesia was not same in many regions. Java and Bali island are known as majority location of investment. This study will determine what is the most significantly determinants that influence of investment in Sumatera Selatan Province, and how spatial effect influence the investment in this region. As proxy of investment of the region, this study take gross fixed capital formation. This study used of panel regression model and Geographically Weighted Regression (GWR) model for analysis. The results of this study, the Human Development Index, GDRP per capita, and quantity of labour have significantly influence of investment in Sumatera Selatan Province. The elasticity of Human Development Index (HDI) influence for investment as positively at 3.699 percent. The Elasticity of Gross Domestic Regional Product (GDRP) per capita influence for investment as positively at 0.933 percent. And the elasticity quantity of labour influence for investment as positively at 0.844 percent. Spatially, every region has a model of investment that weighted of location. The results of GWR model showed that determinants of investment influenced of investment in every district of Sumatera Selatan Province with different significantly.

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