Measuring inequalities of development at the sub-national level: From the human development index to the human life indicator

Development in the country is growing including in the West Borneo Province. However in 2015, the achievement of human development at the National level is quite low, while the District and City varied considerably. Human Development Index is one of the parameter for human development that are affected by many factors. In this paper, analysis for identify the factors for human development index in West Kalimantan Province by using Regression Analysis was conducted. Regression was based on time series data from 2012 until 2015. It is found that Fixed Effect Model is the best regression model with the R2 of 0.99853%. The influencing variables are Life Expectancy (AHH), Adjusted Per Capita (Expenditure), School Average (RLS), School Expectation (HLS), and Gross Regional Domestic Product at Constant Price (GRDP).

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

SRIWIJAYA INTERNATIONAL JOURNAL OF DYNAMIC ECONOMICS AND BUSINESS ◽

10.29259/sijdeb.v4i2.119-128 ◽

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.

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

Journal of Public Administration and Governance ◽

10.5296/jpag.v10i4.17819 ◽

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.

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Education Budget Through Central or Local Government Spending: Which Is More Effective in Improving the Quality of Human Life?

Journal of Accounting and Strategic Finance ◽

10.33005/jasf.v4i2.227 ◽

2021 ◽

Vol 4 (2) ◽

pp. 242-255

Author(s):

Ignatia Martha Hendrati ◽

Putra Perdana

Keyword(s):

Local Government ◽

Human Development ◽

Government Spending ◽

Human Development Index ◽

Central Government ◽

Human Life ◽

Government Expenditure ◽

Development Index ◽

Vector Auto Regression ◽

Auto Regression

Regional autonomy demands a division of authority between the Center and the regions, which in turn has an impact on budgeting policies. On the one hand, central government spending is oriented towards equity, but on the other hand, the regions understand very well their respective characteristics. The government's budget is always results-oriented, so this research can later be used as a benchmark in planning budgeting. In terms of spending on Education in Indonesia, the budget is channeled through central government spending and local government spending. This research is structured to see between the Central Government or Local Government, more significant in accelerating human quality (IPM) in Indonesia. This study uses Vector Auto Regression with Bayesian Vector Auto Regression model specifications to determine the effect between the variables studied. The variables used in this study are the Central Government Expenditure budget, Regional Government Expenditure on Education through Transfers from the Center to the Regions, Adjusted Per Capita Expenditure, and the Human Development Index from 2007 – 2020. The estimation results show a tendency for local government spending to be more able to increase Human Development Index compared to the Education budget through central government spending. This finding indicates that in the end, the results of decentralization, one of which is the delegation of authority for local government spending, can accelerate the human development index higher than the expenditure issued by the central government.

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

Syntax Idea ◽

10.36418/syntax-idea.v3i7.1331 ◽

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.

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

Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika ◽

10.46306/lb.v2i3.85 ◽

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

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Investigating the Temporal and Spatial Dynamics of Human Development Index: A Comparative Study on Countries and Regions in the Eastern Hemisphere from the Perspective of Evolution

Remote Sensing ◽

10.3390/rs13122415 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2415

Author(s):

Hanwei Liang ◽

Na Li ◽

Ji Han ◽

Xin Bian ◽

Huaixia Xia ◽

...

Keyword(s):

Human Development ◽

Human Development Index ◽

National Level ◽

Spatial Dynamics ◽

Data Availability ◽

Evolutionary Trajectory ◽

Development Index ◽

Eastern Hemisphere ◽

South Central ◽

Increasing Trend

The Human Development Index (HDI) is a prevailing indicator to present the status and trend of sustainability of nations, hereby offers a valuable measurement on the Sustainable Development Goals (SDGs). Revealing the dynamics of the HDI of the Eastern Hemisphere countries is vital for measurement and evaluation of the human development process and revealing the spatial disparities and evolutionary characteristics of human development. However, the statistical data-based HDI, which is currently widely applied, has defects in terms of data availability and inconsistent statistical caliber. To tackle such an existing gap, we applied nighttime lights (NTL) data to reconstruct new HDI indicators named HDINTL and quantify the HDINTL at multispatial scales of Eastern Hemisphere countries during 1992–2013. Results showed that South Central Asia countries had the smallest discrepancies in HDINTL, while the largest was found in North Africa. The national-level HDINTL values in the Eastern Hemisphere ranged between 0.138 and 0.947 during 1992–2013. At the subnational scale, the distribution pattern of HDINTL was spatially clustered based on the results of spatial autocorrelation analysis. The evolutionary trajectory of subnational level HDINTL exhibited a decreasing and then increasing trend along the northwest to the southeast direction of Eastern Hemisphere. At the pixel scale, 93.52% of the grids showed an increasing trend in HDINTL, especially in the urban agglomerations of China and India. These results are essential for the ever-improvement of policy making to reduce HDI’s regional disparity and promote the continuous development of humankind’s living qualities. This study offers an improved HDI accounting method. It expects to extend the channel of HDI application, e.g., potential integration with environmental, physical, and socioeconomic data where the NTL data could present as well.

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

SinkrOn ◽

10.33395/sinkron.v6i1.11173 ◽

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%.

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International Migration Level and Trends

Patan Pragya ◽

10.3126/pragya.v7i1.35109 ◽

2020 ◽

Vol 7 (1) ◽

pp. 91-100

Author(s):

Laxman Singh Kunwar

Keyword(s):

Developing Countries ◽

Human Development ◽

International Migration ◽

Human Development Index ◽

National Level ◽

Population Data ◽

Developed Countries ◽

Middle Level ◽

Sources Of Information ◽

Development Index

International migration is an issue growing concern at global, regional and national level because its volume has been increasing at all level. Among the four migration corridors (North-North, North-South, South-North and South-South) of international migration South-South migration(developing countries –developing countries) occupies largest and North- South (developing countries -developed Countries) second largest share of international migration. The objective of this study is to introduce the situation of international migration at global, regional and national level by using secondary sources of information. The volume of refugees in relation with volume of international migration also has been increasing. Similarly the volume of emigrants have increased in those countries or regions with having very low, low and middle level human development index. Whereas the volume of more immigrants was observed in countries or regions of high and very high human development index. In the context of Nepal, international migration (absentee population data in censuses) has been gradually increasing but up to 2001 censuses major destination was India but on the basis of 2011 census destination of Nepalese migrants have been shifted to Middle East and ASEAN countries but India still remains as a major destination. The lack of uniform data regarding to international migration has been a problem to analyze migration level and trends properly.

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Classification of Human Development Index Using K-Means

Indonesian Journal of Applied Statistics ◽

10.13057/ijas.v2i1.28566 ◽

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

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 k-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.Keywords : cluster analysis, k-means, the human development index.

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