scholarly journals Investigating Inequalities in Access to Healthcare: The Case of Townships of Kermanshah, Iran

2019 ◽  
Author(s):  
Sohyla Reshadat ◽  
Alireza Zangeneh ◽  
Shahram Saeidi ◽  
Raziyeh Teimouri ◽  
Shirin Zardui GolAnbari ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Medical Care ◽  
Human Development ◽  
Human Development Index ◽  
Hierarchical Cluster ◽  
Health Facilities ◽  
Unequal Distribution ◽  
Development Index ◽  
The Mean ◽  
Access To Medical Care

Abstract Background: Access to medical care is one of the major issues affecting human health. This study aims to investigate inequality in access to medical care in the townships in Kermanshah, Iran. Methods: Methodology approach includes a descriptive-analytic study followed by determining the degree of development of the townships calculated in terms of access to medical care through the hierarchical cluster analysis and the combined model of human development index. Additionally, the mean center and standard distance tests are handled in a geographic information system software to identify the deployment pattern of the status of access to medical care indexes. Results: As for the ratio of physicians, nursing staff, paramedical staff, administrative staff of health care, dentists, pharmacists, hospitals, general and specialized clinics, radiology, rehabilitation centers and laboratories to a population of 10,000, the results of analyzing the findings were indicative of unequal distribution of facilities at the level of townships. This is based on The results of comparing the mean centers of population and health facilities showed that the centers of both data categories were located in Kermanshah. The two standard distances (i.e., population and health facilities) demonstrated that the health facilities witnessed more dispersion in the northwestern regions than the concentration of population in the central and southeastern regions of the province. Conclusions: The results indicated that the indexes of development of facilities and healthcare resources were not distributed equitably and with a balance between the townships of the Kermanshah Province. Keywords: healthcare; medical care inequality; human development index; spatial analysis, cluster analysis; Kermanshah, Iran

scholarly journals Analisis Pengaruh Pengeluaran Pemerintah Terhadap Pertumbuhan Ekonomi dan Indeks Pembangunan Manusia di Indonesia

2016 ◽  
Vol 1 (1) ◽  
pp. 39-50
Author(s):  
Ginanjar Aji Nugroho
Keyword(s):  
Economic Growth ◽  
Human Development ◽  
Human Development Index ◽  
Random Sampling ◽  
Simple Random Sampling ◽  
Government Expenditures ◽  
Analysis Method ◽  
Statistical Average ◽  
Development Index ◽  
The Mean

The puposes of this study are (1) to analyze the effects of government expenditures on education, health and infrastructure sectors toward economic growth and human development index in Indonesia, (2) to investigate the impacts of economic growth on human dvelopment index, (3) and to examine the effects of government expenditures on education, health and infrastructure sectors toward human development index both directly and through the economic growth. The study used samples from twenty provinces, which were selected using simple random sampling, divided into two groups; the first group comprised higher HDI provinces; the second group consisted of lower HDI provinces. To examine the model, the study applied path analysis method. The mean test was also applied to determine whether there were statistical average differences between the two groups. The results of this study show different responds between the higher HDI provinces and lower HDI provinces. The higher HDI provinces show that government expenditures on health and infrastructure have positive and significant impacts on human development index through economic growth indirectly; on the other hand, the lower HDI provinces show that only expenditure on education gives positive and significant impacts on human development index. Meanwhile, the economic growth shows positive and significant impacts on human development index in both higher HDI and lower HDI provinces.  Abstrak Penelitian ini bertujuan untuk: (1).Mengetahui pengaruh pengeluaran pemerintah pada sektor pendidikan, kesehatan dan infrastruktur terhadap pertumbuhan ekonomi dan indeks pembangunan manusia (IPM) di Indonesia, (2).Mengetahui pengaruh pertumbuhan ekonomi terhadap IPM, dan (3).Mengetahui pengaruh pengeluaran pemerintah pada sektor pendidikan, kesehatan dan infrastruktur terhadap IPM, baik secara langsung maupun melalui pertumbuhan ekonomi. Penelitian ini menggunakan sampel dua puluh provinsi yang dipilih dengan teknik simple random sampling yang kemudian dibagi kedalam dua kelompok, yaitu kelompok daerah dengan angka IPM tinggi dan kelompok daerah dengan angka IPM rendah. Metode yang digunakan dalam penelitian ini adalah analisis jalur. Sebagai pendukung, juga dilakukan uji beda rata-rata untuk mengetahui ada tidaknya perbedaan rata-rata secara statistik terhadap dua kelompok tersebut. Hasil estimasi menunjukkan bahwa terdapat perbedaan respon diantara dua kelompok daerah tersebut. Pada kelompok daerah dengan angka IPM tinggi, terlihat bahwa pengeluaran kesehatan dan infrastruktur mempunyai pengaruh positif dan signifikan terhadap IPM melalui pertumbuhan ekonomi, sedangkan pada kelompok daerah dengan angka IPM rendah terlihat bahwa hanya pengeluaran pendidikan yang mempunyai pengaruh positif dan signifikan terhadap angka IPM. Adapun pertumbuhan ekonomi, terlihat menunjukkan pengaruh yang positif dan signifikan terhadap IPM. Hal ini terjadi pada kedua kelompok daerah, baik kelompok daerah dengan IPM tinggi maupun IPM rendah.

scholarly journals Metode Analisis Diskriminan dalam Pengelompokan Kabupaten/Kota di Provinsi Sulawesi Selatan Berdasarkan Indikator Indeks Pembangunan Manusia

2020 ◽  
Vol 2 (1) ◽  
pp. 40
Author(s):  
Novi Afryanthi S. ◽  
Muhammad Arif Tiro ◽  
Ansari Saleh Ahmar
Keyword(s):  
Cluster Analysis ◽  
Statistical Analysis ◽  
Discriminant Analysis ◽  
Life Expectancy ◽  
Human Development ◽  
Human Development Index ◽  
Statistic Analysis ◽  
Development Index ◽  
South Sulawesi ◽  
Life Expectancy Increase

Abstract. Discriminant analysis is a method in multivariat statistic analysis that related with object which have separated into the defined group defined and see the accuracy  of the formed group. In this research, clustera analysis is used for the first grouping,  cluster  analysis is a statistical analysis which aims to classify some objects based on the characteristics similarity among the object. Data for this study is HDI (Human Development Index)  of indicator in south sulawesi in 2016. The result of this research are 1st cluster (lower  HDI indicator) which have 21 city/ distric and the 2nd cluster (higher  HDI indicator) which have 3 city/distric as the closeness value between the cluster that formed is 0.902 which shows the closeness between the cluster is high . Furthermore, the discriminant function that have formed explains that if the life expectancy increase, the HDI indicator in city/distric in south sulawesi province will decrease but if school  expectation duration in school , average of duration in school, and parity of pur hasing power is increasing, the HDI indicator in city/distric in aouth sulawesi will also increase.Keywords: Cluster analysis, Discriminant analysis , Human development index indicator.

Infrastructure, Gross Regional Domestic Product, and Convergence of Human Development Index

2021 ◽  
Vol 22 (2) ◽  
Author(s):  
Joko Susanto
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Health Facilities ◽  
Domestic Product ◽  
Development Index ◽  
Education And Health ◽  
Catch Up ◽  
The Government ◽  
Special Region

Due to a disparity in Human Development Index (HDI) among regencies and cities in Special Region of Yogyakarta, this study aimed to examine whether HDI convergence occurred in this province. The data were sourced from the Statistics of Special Region of Yogyakarta, including HDI, infrastructure, and gross regional domestic product in four regencies and one city from 2001 to 2019. The infrastructure consists of installed electricity, education, and health facilities. The results showed an absence of HDI convergence between regions in the Special Region of Yogyakarta. Furthermore, HDI growth in the impoverished region was slower than in leading ones, resulting in a gap. The infrastructure gap made the impoverished region unable to catch up with leading ones, causing an HDI divergence. In contrast, Gross Regional Domestic Product (GRDP) has no impact on HDI. Therefore, the government needs to improve infrastructure in disadvantaged areas to increase HDI.

scholarly journals Classifying regencies and cities on human development index dimensions: Application of K-Means cluster analysis

2021 ◽  
Vol 5 (2) ◽  
pp. 913-918
Author(s):  
Nurhasanah Nurhasanah ◽  
Nany Salwa ◽  
Lyra Ornila ◽  
Amiruddin Hasan ◽  
Martahadi Mardhani
Keyword(s):  
Cluster Analysis ◽  
Human Development ◽  
Human Development Index ◽  
Development Process ◽  
Clustering Algorithm ◽  
Development Plan ◽  
Clustering Method ◽  
Development Index ◽  
The Third

The Human Development Index (HDI) is a measurement that analyzes a region's development in improving human development. The government's development plan aims to create a successful and peaceful life. The unbalanced development in every regency and city in Indonesia is a typical issue during the development process. It may also be shown that the HDI level changes across regencies and cities in Indonesia. This research aims to identify Indonesian regencies and cities based on HDI indices. K-Means clustering algorithm is the clustering method adopted. The results of the analysis formed 4 clusters. The first cluster consisted of 20 regencies with a low average HDI indicator. The second cluster consisted of 148 regencies and cities with an average HDI indicator is medium. The third cluster consisted of 88 regencies and cities with an average HDI indicator. The fourth cluster consists of 258 regencies and cities with high HDI indicators.

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 Analisis Pengaruh Pengeluaran Pemerintah Terhadap Pertumbuhan Ekonomi dan Indeks Pembangunan Manusia di Indonesia

2016 ◽  
Vol 1 (1) ◽  
pp. 39-50
Author(s):  
Ginanjar Aji Nugroho
Keyword(s):  
Economic Growth ◽  
Human Development ◽  
Human Development Index ◽  
Random Sampling ◽  
Simple Random Sampling ◽  
Government Expenditures ◽  
Analysis Method ◽  
Statistical Average ◽  
Development Index ◽  
The Mean

The puposes of this study are (1) to analyze the effects of government expenditures on education, health and infrastructure sectors toward economic growth and human development index in Indonesia, (2) to investigate the impacts of economic growth on human dvelopment index, (3) and to examine the effects of government expenditures on education, health and infrastructure sectors toward human development index both directly and through the economic growth. The study used samples from twenty provinces, which were selected using simple random sampling, divided into two groups; the first group comprised higher HDI provinces; the second group consisted of lower HDI provinces. To examine the model, the study applied path analysis method. The mean test was also applied to determine whether there were statistical average differences between the two groups. The results of this study show different responds between the higher HDI provinces and lower HDI provinces. The higher HDI provinces show that government expenditures on health and infrastructure have positive and significant impacts on human development index through economic growth indirectly; on the other hand, the lower HDI provinces show that only expenditure on education gives positive and significant impacts on human development index. Meanwhile, the economic growth shows positive and significant impacts on human development index in both higher HDI and lower HDI provinces.  Abstrak Penelitian ini bertujuan untuk: (1).Mengetahui pengaruh pengeluaran pemerintah pada sektor pendidikan, kesehatan dan infrastruktur terhadap pertumbuhan ekonomi dan indeks pembangunan manusia (IPM) di Indonesia, (2).Mengetahui pengaruh pertumbuhan ekonomi terhadap IPM, dan (3).Mengetahui pengaruh pengeluaran pemerintah pada sektor pendidikan, kesehatan dan infrastruktur terhadap IPM, baik secara langsung maupun melalui pertumbuhan ekonomi. Penelitian ini menggunakan sampel dua puluh provinsi yang dipilih dengan teknik simple random sampling yang kemudian dibagi kedalam dua kelompok, yaitu kelompok daerah dengan angka IPM tinggi dan kelompok daerah dengan angka IPM rendah. Metode yang digunakan dalam penelitian ini adalah analisis jalur. Sebagai pendukung, juga dilakukan uji beda rata-rata untuk mengetahui ada tidaknya perbedaan rata-rata secara statistik terhadap dua kelompok tersebut. Hasil estimasi menunjukkan bahwa terdapat perbedaan respon diantara dua kelompok daerah tersebut. Pada kelompok daerah dengan angka IPM tinggi, terlihat bahwa pengeluaran kesehatan dan infrastruktur mempunyai pengaruh positif dan signifikan terhadap IPM melalui pertumbuhan ekonomi, sedangkan pada kelompok daerah dengan angka IPM rendah terlihat bahwa hanya pengeluaran pendidikan yang mempunyai pengaruh positif dan signifikan terhadap angka IPM. Adapun pertumbuhan ekonomi, terlihat menunjukkan pengaruh yang positif dan signifikan terhadap IPM. Hal ini terjadi pada kedua kelompok daerah, baik kelompok daerah dengan IPM tinggi maupun IPM rendah.

What Does Human Development Index Rating Mean in Terms of Individualism/Collectivism?

2003 ◽  
Vol 8 (2) ◽  
pp. 97-100 ◽  
Author(s):  
Maria José Sotelo ◽  
Luis Gimeno
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Principal Component ◽  
General Idea ◽  
Development Index ◽  
Low Levels ◽  
The Relationship

The authors explore an alternative way of analyzing the relationship between human development and individualism. The method is based on the first principal component of Hofstede's individualism index in the Human Development Index rating domain. Results suggest that the general idea that greater wealth brings more individualism is only true for countries with high levels of development, while for middle or low levels of development the inverse is true.

Capaian pembangunan manusia: analisis komparatif Provinsi Banten, Jawa Barat dan DKI Jakarta

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Adriwati Adriwati
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Human Population ◽  
Provincial Government ◽  
Healthy Life ◽  
Development Index ◽  
Long Life ◽  
The Difference ◽  
The Government ◽  
Development Paradigm

Human development is a development paradigm that puts human (population) as the focus and final target of all development activities, namely the achievement of control over resources (income to achieve decent living), improvement of health status (long life and healthy life) and improve education. To see the success rate of human development, UNDP publishes an indicator of Human Development Index (HDI). This study discusses the achievements of human development that have been pursued by the government. The problem analyzed in this research is the difference of human development achievement in some provincial government in Indonesia. This paper aims to compare the achievements of human development in some provincial governments seen from the achievement of human development index of each province. Research location in Banten Province, West Java and DKI Jakarta.Keywords:Human Development Index, Human Development Achievement

The comparison of MCDM Methods including AHP, TOPSIS and MAUT with an Application on Gender Inequality Index

2016 ◽  
Vol 4 (2) ◽  
pp. 183 ◽  
Author(s):  
Latife Sinem Sarul ◽  
Özge Eren
Keyword(s):  
European Union ◽  
Human Development ◽  
Gender Inequality ◽  
Human Development Index ◽  
The European Union ◽  
Inequality Index ◽  
Development Index ◽  
Important Barrier ◽  
Alternative Ranking

Gender Inequality Index is a major indicator presenting level of development of the countries as Human Development Index, which is calculated regularly every year by UN. In this study, an alternative calculation has been proposed for measuring gender inequality index which is an important barrier for the human development. Each indicator in the index integrated as MAUT- AHP and also AHP-TOPSIS and these methods carried out again for the alternative ranking member and candidate countries of the European Union. The main objective here is to represent that the indicators form gender inequality index can be reclassified with different weights for each indicator.

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