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 The incidence and mortality of lip and oral cavity cancer and its relationship to the 2012 Human Development Index of Asia

2017 ◽  
Vol 4 (02) ◽  
pp. 1147 ◽  
Author(s):  
Amir Tiyuri ◽  
Abdollah Mohammadian-Hafshejani ◽  
Elham Iziy ◽  
Hamidreza Sadeghi Gandomani ◽  
Hamid Salehiniya
Keyword(s):  
Mortality Rate ◽  
Life Expectancy ◽  
Oral Cavity ◽  
Human Development ◽  
Human Development Index ◽  
Oral Cavity Cancer ◽  
Development Index ◽  
Life Expectancy At Birth ◽  
Incidence And Mortality ◽  
Years Of Schooling

Introduction: Lip and oral cavity cancer is one of the most prevalent cancers in Asia and considered to be a major public health problem due to the low survival rate. Because of the importance of access to information about this cancer (including incidence, mortality rate and relation to socioeconomic indicators), this study aims at investigating the incidence and mortality of lip and oral cavity cancer and its relationship with the Human Development Index (HDI) of Asia (from 2012). Method: This study was an ecological study in Asia for assessment of the correlation between age-specific incidence rate (ASIR) and age-specific mortality rate (ASMR) with the HDI and its components which include: life expectancy at birth, mean years of schooling and gross national income (GNI) per capita. Data on the standardized incidence ratio (SIR) and the standardized mortality ratio (SMR) for every Asian country for the year 2012 were obtained from the global cancer project and data on the HDI and its components were extracted from the World bank site.  We used a bivariate method for assessment of the correlation between the SIR and SMR with the HDI and its individual components. Statistical significance was assumed if P<0.05. All reported P-values were two-sided. Statistical analyses were performed using SPSS (Version 15.0, SPSS Inc.). Results: A total incidence of 162,506 cases and 95,005 deaths were recorded in Asian countries in 2012. Countries with the highest SIR (per 100,000) were the following: Maldives (11), Sri Lanka (10.3), Pakistan (9.8), Bangladesh (9.4), and India (7.2). The highest SMR was observed in the following countries: Pakistan (5.9), Bangladesh (5.6), Afghanistan (5.1), India (4.9), and Maldives (4.1). The correlation between SIR of lip and oral cavity cancer and HDI was -0.378 (p=0.010), with life expectancy at birth at -0.324 (p=0.028), mean years of schooling at -0.283 (p=0.057), and level of income per each person of the population at -0.279 (p=0.060). Moreover, the correlation was -0.664 (p≤0.001) between SMR and HDI. Conclusion: A significant reverse correlation was seen between the incidence and mortality rate of lip and oral cavity cancer and the HDI in Asia. The incidence and mortality of this type of cancer was high in developing or less developed countries.   

scholarly journals Comparative Study on Human Development Index (HDI): Indonesia and Bangladesh Context

2013 ◽  
Vol 3 (2) ◽  
Author(s):  
Soni Ahmad Nulhaqim ◽  
M D Kamrujjaman
Keyword(s):  
Comparative Study ◽  
Human Development ◽  
Human Development Index ◽  
Three Dimensions ◽  
Series Data ◽  
Development Index ◽  
Life Expectancy At Birth ◽  
Development Indicator ◽  
Clear Idea ◽  
Years Of Schooling

The Human Development Index (HDI) is a development indicator since 1990, operated by theUnited Nations Development Programme. Our entitled “Comparative Study on HumanDevelopment Index (HDI): Indonesia and Bangladesh Context” paper will focus oncomparison of both countries situation. In common scenes Indonesia is in advance thanBangladesh but what is the real situation are exist in both countries will be explained by ourstudy. Here we will compare series data (1980-2011) & its trends, value comparison (2011-2012), of two countries. In this paper we have analysis following segments of two countriesnamed Inequality-adjusted HDI(IHDI), Gender Inequality Index (GII), Multidimensional PovertyIndex (MPI) and Cross-Analysis of Indonesia & Bangladesh related to others relevant data like:Demographic Situation, Education Condition, Health Situation, Gender Observation etc. In ourpaper we have used New method for 2011 data onwards that Published on 4 November 2010(and updated on 10 June 2011), starting with the 2011 Human Development Report the HDIcombines three dimensions: A long and healthy life: Life expectancy at birth, Education index:Mean years of schooling and Expected years of schooling, A decent standard of living: GNI percapita (PPP US$). Hopefully this paper will give us a clear idea about two countries currentsocio-economic condition as well.

scholarly journals Estimates of global HIV/AIDS mortality, prevalence and incidence rates, and their association with the Human Development Index

2017 ◽  
Vol 4 (06) ◽  
pp. 1399
Author(s):  
Kamyar Mansori ◽  
Erfan Ayubi ◽  
Fatemeh Khosravi Shadmani ◽  
Shiva Mansouri Hanis ◽  
Somayeh Khazaei ◽  
...  
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Developed Countries ◽  
Incidence Rates ◽  
Global Public Health ◽  
Development Index ◽  
Life Expectancy At Birth ◽  
Global Age ◽  
Hiv Aids ◽  
Years Of Schooling

Background: HIV/AIDS is one of greatest global public health concerns today due to the high incidence, prevalence and mortality rates. The aim of this research was investigate and estimate the global HIV/AIDS mortality, prevalence and incidence rates, and explore their associations with the Human Development Index. Methods: The global age-standardized rates of mortality, prevalence and incidence of HIV/AIDS were obtained from the UNAIDS for different countries in 2015. The human development indexes (HDIs) were obtained from the World Bank database. The surveyed countries were divided into four groups according to the HDI distribution. The Spearman correlation coefficient and one-way ANOVA test were used for assessing the association of HIV/ AIDS indicators and HDI. Results: The highest rates of HIV/AIDS prevalence and incidence, and associated mortality in East and Southern Africa countries were 51.73%, 46.33% and 42.3%, respectively. Moreover, the highest and lowest global age-standardized rates of incidence and prevalence of HIV/AIDS was seen in adults ranging from 15-49 years of age for both low and high HDI countries. The prevalence and incidence rates of HIV/AIDS each had an inverse correlation with HDI and its four indicators (life expectancy at birth, mean years of schooling, expected years of schooling, and GNI per capita). Conclusion: Less developed countries with lower HDI show greater severity of the AIDS epidemic. Thus, it is essential to pay more attention to HIV/AIDS control and prevention programs in these countries. 

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 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 An Evaluation of Human Development Index in Central Asian Countries

2011 ◽  
Author(s):  
Volkan Öngel ◽  
İlyas Sözen ◽  
Ahmet Alkan Çelik
Keyword(s):  
Economic Development ◽  
Human Development ◽  
Gender Discrimination ◽  
Human Development Index ◽  
Asian Countries ◽  
Political Preference ◽  
Equal Distribution ◽  
Development Index ◽  
Life Expectancy At Birth ◽  
Economic Development And Growth

Economic development and growth had been the most important target among all goverments throughout the history. In this respect, Kazakhstan, Turkmenistan, Uzbekistan, Tajikistan and Kyrgyzstan in Middle Asian Region had chosen development as primary target in 20 years time after their independence. Human capital is the leading factor to maintain economic development and growth. Development and growth terms over which different meanings and concepts were imposed in time, necessitated several political economic alterations. Before 1970’s, increase in income had been sufficient criterion for the development of a government. But nowadays economic development incorporates factors such as life expectancy at birth, school enrolment ratio, literancy rate, gender discrimination, poverty alleviation, equal distribution of income beyond economic growth. Herewith this change political preference and priorities has started to differentiate. The aim of this study is to discuss human development index (HDI) data of 5 Middle Asian countries in 2010 and changes in HDI in years after their independence. Comparisan between Gross Domestic Product (GDP) and HDI rates are also performed within this analysis. This study consists of data of 5 Middle Asian countries between years 1990-2010. Basic, retrospective, illustrative library method is used as the study method. In conclusion, we find that increase in GDP did not reflect over HDI in Middle Asian Countries within 20-years period.

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 Analysis of the Relationship between Human Development Index and Regional Development of West Sulawesi Province

2021 ◽  
Vol 2 (4) ◽  
pp. 31-38
Author(s):  
Muhammad Haekal Ansyar ◽  
Rusnadi Padjung ◽  
Muslim Salam
Keyword(s):  
Life Expectancy ◽  
Regional Development ◽  
Human Development ◽  
Human Development Index ◽  
Power Index ◽  
Regional Inequality ◽  
Purchasing Power ◽  
Development Index ◽  
The Relationship ◽  
Years Of Schooling

This study aims to analyze the relationship between the human development index and the regional development of West Sulawesi Province. This study uses panel data analysis that combines time series-cross section data and uses the Two Stage Least Square (2SLS) method. The type of data in this study is secondary data taken from the Central Statistics Agency (BPS) of West Sulawesi. The variables of the human development index are life expectancy, average length of schooling, expected length of schooling and purchasing power index. While the variables of regional development are poverty, unemployment, regional inequality and GRDP. The results of the analysis using the 2SLS method. In the HDI equation, the PW variable partially has a negative but not significant effect on the HDI for =5%. However, if for =20% PW has a negative and significant effect on HDI. While in the PW equation, the HDI variable partially has a negative but not significant effect on PW for = 5%. The R2 in the HDI equation is 97.5% and the remaining 2.5% which shows that the influence of PW, Life Expectancy, Average Years of Schooling, Expected Years of Schooling, and Purchasing Power Index together have an effect on HDI. While in the PW equation, the determination of R2 is 99.2% and the remaining 0.8% which shows HDI, Poverty Level, Unemployment Rate, Regional Inequality and Gross Regional Domestic Product together affect PW. So, there is a simultaneous relationship between the Human Development Index and Regional Development

scholarly journals Disparities in incidence and mortality of pancreatic cancer in the world

2018 ◽  
Vol 5 (02) ◽  
pp. 1986-1999
Author(s):  
Yousef Khani ◽  
Masoumeh Arabsalmani ◽  
Reza Pakzad ◽  
Mahshid Ghoncheh ◽  
Abdollah Mohammadian-Hafshejani ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Human Development ◽  
Human Development Index ◽  
Significant Positive Correlation ◽  
Men And Women ◽  
Development Index ◽  
Positive Correlation ◽  
Life Expectancy At Birth ◽  
Incidence And Mortality ◽  
The World

Background: Pancreatic cancer (PC) is as the twelfth most frequent cancer and the seventh most important cause of mortality by reason of cancer in the world. Being informed about the incidence and mortality of this cancer and the potential role of development is useful in health policy. The aim of this research is investigating disparities in the incidence and mortality of PC in the world countries in the year 2012. Methods: This study was an ecologic study in the World for assessing the correlation between Human Development Index (HDI) and its details (Gross national income (GNI) per capita, average years of schooling and life expectancy at birth) with age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) of PC. Results: In total, 337872 new cases of PC occurred in 2012 around the world , that 178116 and 159711 cases take happen in men and women respectively, also at the same year 330391 deaths of PC occurred ,that 173,827 and 156564 cases were in men and women. In assessment the relationship between HDI and ASIR and ASMR of PC there is significant positive correlation equal to 0.767 (p <0.001) between HDI and ASIR of PC, and a significant positive correlation equal to 0.776 (p <0.001) between HDI and ASMR of PC. Conclusion: The incidence and mortality of PC has a significant positive correlation with the Human Development Index.  

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