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 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 Human Development Index (HDI) in Lampung Province Period 2013-2018

2021 ◽  
Vol 4 (2) ◽  
pp. 119
Author(s):  
Ambya Ambya
Keyword(s):  
Human Development ◽  
Government Spending ◽  
Human Development Index ◽  
Capital Expenditure ◽  
Human Life ◽  
Health Sector ◽  
Life Quality ◽  
Development Index ◽  
The Government

Human development index (HDI) is one of the benchmarks used to see the quality of human life as measured by looking at the level of human life quality of education, health and economy. This study aims to determine the effect of government spending from the education, health and capital expenditure sectors as well as income on the human development index. The data used is a secondary data in 7 districts in Lampung Province period of 2013-2018 which was obtained from the Directorate General of Fiscal Balance (DGFB Ministry of Finance) and the Central Statistics Agency (CSA) in Lampung province. The results of the analysis show that the government spending in the education sector and capital expenditure have a positive and significant effect on the human development index while the health sector spending as well as income have a negative and significant effect on the human development index.

scholarly journals WHY IS THE TARGET OF HUMAN DEVELOPMENT INDEX HARD TO BE ACHIEVED? AN ANALYSIS OF THE STRATEGIC ENVIRONMENT

2020 ◽  
Vol 10 (4) ◽  
Author(s):  
Iis Sandra Yanti
Keyword(s):  
Local Government ◽  
Human Development ◽  
Human Development Index ◽  
Qualitative Method ◽  
Human Life ◽  
Task Environment ◽  
Industrial Region ◽  
Development Index ◽  
And Task

Human Development Index (HDI) is still used for determining the quality of human life in local government. In local government, specially in industrial region, HDI is to hard to be achieved. Bekasi regency as the biggest industrial region of the South-East Asia also has same problem about achieving HDI target annually. With qualitative method, this research tries to identify factors that causing HDI target of Bekasi Regency is not achieved in 2012-2017 period. Some results shows that the factors are natural environment, social environment, and task environment.

scholarly journals Pengaruh Kemiskinan, Pengangguran, Pertumbuhan Ekonomi, dan Belanja Modal Terhadap IPM Di Kabupaten Nganjuk Tahun 2010-2019

Syntax Idea ◽  
2021 ◽  
Vol 3 (7) ◽  
pp. 1523
Author(s):  
Andhita Astriani ◽  
Muchtolifah Muchtolifah ◽  
Sishadiyati Sishadiyati
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Capital Expenditure ◽  
Human Life ◽  
Research Data ◽  
Time Data ◽  
Development Index ◽  
Directorate General ◽  
Financial Balance

Development is included in the tools used to achieve success in building the nation. Human development can be seen from the level of quality of human life in an area with a size that can be seen from the human development index. The purpose of this research is to test the influence between Youth, Youth, Economy, and Clear Capital Expenditure Human Development Index in Nganjuk District in 2010-2019. Which method in this study quantitative method with samples in this study is Nganjuk Regency in 2010-2019. Research data which data at that time data from the Central Bureau of Statistics East Java Province and directorate general of financial balance. In the result of the creation, it is concluded that: 1) Districts are high and flat against HDI. 2) No government is not beber against HDI. 3) Economy Is Not High On HDI. 4) Capital Expenditure is not good timing outside the HDI.

scholarly journals Classification of the Human Development Index in Indonesia Using the Bootstrap Aggregating Method

SinkrOn ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 100-106
Author(s):  
Noor Ell Goldameir ◽  
Anne Mudya Yolanda ◽  
Arisman Adnan ◽  
Lusi Febrianti
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Human Life ◽  
Classification Performance ◽  
Development Index ◽  
Life Expectancy At Birth ◽  
Bootstrap Aggregating ◽  
Bagging Method ◽  
Years Of Schooling

Successful development of the quality of human life in a region is determined by the Human Development Index (HDI). Human development performance based on the HDI can be measured: long and healthy life, knowledge, and a decent standard of living. The HDI is usually grouped into several categories to facilitate the classification of the HDI level of each region. This study aimed to determine the ability of the bootstrap aggregating (bagging) method to classify the HDI by district/city. Bagging is a stochastic machine learning approach that can eliminate the variance of the classifier by producing a bootstrap ensemble to obtain better accuracy results. The dependent variable in this study was the HDI by district/city in 2020. In contrast, life expectancy at birth, expected years of schooling, mean years of schooling, and real expenditure per capita are adjusted as independent variables. Bagging was applied to the high and low categories of HDI data. The bagging method demonstrated good classification performance due to only eight classification errors, namely the HDI data which should be in the high category but classified into the low category by the bagging method. Based on the results of calculations with 25 replications, it can be concluded that the bagging method has a very good performance, with an accuracy value of 92.3%, the sensitivity of 100%, and specificity of 83.33%. The bagging method is considered very good for the classifying the HDI by district/city in Indonesia in 2020 because it has a balanced accuracy of 91.67%.

scholarly journals Pemodelan Kriminal di Jawa Timur dengan Metode Geographically Weighted Regression (GWR)

2018 ◽  
Vol 4 (2) ◽  
pp. 150-158
Author(s):  
Imanudin Nurhuda ◽  
I Gede Nyoman Mindra Jaya
Keyword(s):  
Economic Growth ◽  
Spatial Heterogeneity ◽  
Geographically Weighted Regression ◽  
Weighting Function ◽  
Motor Vehicles ◽  
Weighted Regression ◽  
Model Parameters ◽  
Independent Variables ◽  
Fixed Kernel ◽  
Gwr Model

Criminality constitutes all kinds of actions that are economically and psychologically harmful in violation of the law applicable in the state of Indonesia as well as social and religious norms, while the criminal data is the number of cases reported to the police institution. The higher the number of complainants the higher the number of criminals in the region. The greater the risk the community represents the more insecure a region is. This study aims to obtain the best model affecting crime or crime in East Java. The number of crimes in this study is limited to the number of theft cases (whether ordinary theft, theft by force, theft with theft, and the theft of motor vehicles). In this study, we use the Geographically Weighted Regression (GWR) model because this method is quite effective in estimating data that has spatial heterogeneity (uniformity in location / spatial). In essence, the model parameters in GWR can be calculated at the observation location with the dependent variable and one or more independent variables that have been measured at the sites where the location is known, where criminal acts in the research conducted in East Java involves the effects of spatial heterogeneity, with fixed kernel weighting function. The results showed that the variables affecting criminality in East Java Province are population density, economic growth, Gini Ratio, and poverty.

scholarly journals Classification of Human Development Index Using K-Means

2019 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Retno Tri Vulandari ◽  
Sri Siswanti ◽  
Andriani Kusumaningrum Kusumawijaya ◽  
Kumaratih Sandradewi
Keyword(s):  
Cluster Analysis ◽  
Human Development ◽  
Human Development Index ◽  
Human Life ◽  
Important Indicator ◽  
Development Index ◽  
Multivariate Technique ◽  
Central Java ◽  
High Estimate ◽  
Years Of Schooling

<p>Human development progress in Central Java. It is characterized by a continued rise in the human development index (HDI) of Central Java. HDI is an important indicator for measuring success in the effort to build the quality of human life. HDI explains how residents can access the development results in obtaining a long and healthy life, knowledge, education, decent standard of living and so on. HDI is affected by four factors, namely life expectancy, expected years of schooling, means years of schooling, and expenditure per capita. Currently the Central bureau of statistics do grouping HDI, using calculation formula then known how the value HDI each regency or city in Central Java. In this research we classified the regency or city in Central Java based on the HDI be high, middle, and under estimate area. We used cluster analysis. Cluster analysis is a multivariate technique which has the main purpose to classify objects based on their characteristics. Cluster analysis classifies the object, so that each object that has similar characteristics to be clumped into a single cluster (group). One of the cluster analysis method is <em>k</em>-means. The result of this research, there are three groups, high estimate area, middle estimate area, and under estimate area. The first group or the under estimate area contained 12 regencies, namely Cilacap, Purbalingga, Purworejo, Wonosobo, Grobogan, Blora, Rembang, Pati, Jepara, Demak, Pekalongan, and Brebes. The second group or the middle estimate area contained 8 regencies, namely Banjarnegara, Kebumen, Magelang, Temanggung, Wonogiri, Batang, Pemalang, and Tegal. The third group or the high estimate area contained 11 regencies, namely Banyumas, Kudus, Boyolali, Klaten, Sukoharjo, Karanganyar, Sragen, Semarang, Kendal, Surakarta, and Salatiga.</p><p><strong>Keywords</strong><strong> : </strong>cluster analysis, <em>k</em>-means, the human development index.</p>

scholarly journals MODEL GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) FAKTOR-FAKTOR YANG MEMENGARUHI KECELAKAAN LALU LINTAS DI PROVINSI BALI

2019 ◽  
Vol 8 (2) ◽  
pp. 140
Author(s):  
NI KADEK ENDAH YANITA UTARI ◽  
I GUSTI AYU MADE SRINADI ◽  
MADE SUSILAWATI
Keyword(s):  
Spatial Heterogeneity ◽  
Geographically Weighted Regression ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Gaussian Kernel ◽  
Weighted Regression ◽  
Geographic Position ◽  
Average Rainfall

The number of traffic accidents in Bali kept increasing since 2015 until 2017. The factors that affected the traffic accidents in every region were suspected to be varied according to geographic position. This geographic effect was known as  spatial heterogeneity. Spatial heterogeneity was analized by using Geographically Weighted Regression (GWR). This study aim to model the factors which affected the traffic accidents in every subdistrict in Bali by using fixed and adaptive gaussian kernel. The result showed that GWR with adaptive gaussian kernel was better at estimated the models because it had higher value of  which was at . The factors which significantly affected the number of traffic accident in 57 subdistrict in Bali were the average rainfall and the number of population within age of 15 to 29 years old.

scholarly journals PENGARUH TINGKAT KEMISKINAN DAN PERTUMBUHAN EKONOMI TERHADAP INDEKS PEMBANGUNAN MANUSIA INDONESIA

2018 ◽  
Vol 15 (2) ◽  
pp. 177-185
Author(s):  
Heppi Syofya
Keyword(s):  
Economic Growth ◽  
Human Development ◽  
Human Development Index ◽  
Human Life ◽  
Three Dimensional ◽  
Poverty Line ◽  
Poverty Rate ◽  
Healthy Life ◽  
Development Index

Human development is defined as a process for enlarging people's choices, the Human Development Index is a benchmark of human development achievement based on a number of basic components of the quality of life of IPM is built through a basic three-dimensional approach that is 1). Dimensions of longevity and healthy life (a long and healthy life), 2). Knowledge and 3). Decent standard living, through the improvement of these three indicators is expected to increase the quality of human life due to individual heterogeneity, geographical disparity and societal conditions vary so that the level of income is no longer the main benchmark in calculating the success rate of development and success, poverty is a condition that is below the minimum standard of needs, both for food and non-food items called the poverty line or poverty treshold, the poverty rate and economic growth have a significant effect on the Index Human Development in Indonesia and economic growth have an influence on the Human Development Index in Indonesia

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