Average Length Of School Research Articles

The Impact of Educational Conditions on Income Inequality and Economic Growth in South Sumatra

Before and during the COVID-19 pandemic, income inequality and economic growth in South Sumatra experienced fluctuating conditions that could hinder learning and education activities. This study aims to examine the effect of educational conditions, consisting of the average length of school (RLS), literacy rate (AMH), pure participation rate (APM), and percentage of 15+ population of senior high school level (PPTP) on income inequality and economic growth in South Sumatra. Data were obtained from the BPS-Statistics of South Sumatra. The current study implemented panel data regression analysis on cross-sectional data from 16 cities/regencies in South Sumatra and time series 2017–2021. The research findings in the first equation show that RLS has a significant effect on reducing income inequality. AMH, APM, and PPTP do not significantly reduce income inequality. The second equation shows that APM and PPTP have a significant effect on economic growth, while RLS and AMH have no significant effect on economic growth. The influence of education on several of these factors has not reduced income inequality and economic growth caused by the COVID-19 pandemic. Apart from that, the APBD’s focus has been redirected to coping with the COVID-19 case; therefore, education has received less attention for this condition. Regional government efforts need to be increased by utilizing school operational assistance for people experiencing poverty and increasing the allocation of education funds above 20% so that compulsory education becomes 12 years. Keywords: COVID-19, economic growth, income inequality, length of school average, pure participation rate

Identifying Factors Affecting Waste Generation in West Java in 2021 Using Spatial Regression

Responsible consumption and production is the 12th of the seventeen SDGs which is difficult for developing countries to achieve due to high waste production. Indonesia is the second largest producer of food waste in the world. Garbage is solid waste generated from community activities. Population density is an indicator to estimate the amount of waste generated in an area. The choice of West Java Province as the research area is based on the fact that this Province has the second highest population density in Indonesia. This study aimed to determine the predictors/factors that influence waste production in the districts/cities of West Java Province. The data used in this study are total waste as a response variable and GRDP (gross domestic product), total spending per capita, average length of schooling, literacy rate, number of MSMEs (micro, small, and medium enterprises), and several recreational and tourism places, the number of people's markets, and the number of restaurants as predictors. The methods used in this research are spatial autoregressive regression/SAR, spatial Lag-X/SLX, and spatial Durbin/SDM. The results of this study show that the SAR is the best model with the lowest BIC (74.442) and pseudo-R-squared (0.7934). Factors that significantly affect total waste production are literacy levels, the number of MSMEs, the number of traditional markets, and the number of recreational and tourist places. 

Determinants of Human Development Index in Indonesia with Maqashid Sharia approach

The study examines factors that influence the Indonesian Human Development Index using the Maqashid Sharia approach. This study's sample is made up of several provinces with the Human Development Index for different categories of people. Data analysis employs a panel data regression model with a fixed effect model. The study's findings indicate that whereas variables Hifzu al-din, Hifzu al-aql, and Hifzu al-mal have a significant impact on the Index of Human Development, variables Hifzu al-nafs and Hifzu al-nasl have no significant impact on the Index of Human Development. Simultaneously, the variables Hifzu al-din, Hifzu al-nafs, Hifzu al-aql, Hifzu al-nasl, and Hifzu al-mal exhibit significant effects on the Human Development Index. Results of the determination test show that 98% of independent variables can influence dependent variables, with the remaining 2% being affected by variables not examined in this study. The study's findings recommended to the government that they support Hifzu Al-din in reducing crime rates, Hifzu Al-Aql by increasing the average length of schooling, and Hifzu Al-Mal in raising per capita income. By paying more attention to these issues, human development will eventually reach its full potential.

Socio-enterprise as a Solution for Pro-poor Halal Tourism Project

The study discusses the influence of tourism on poverty and community welfare in NTB Indonesia which is supported by the theory of Pro-Poor Tourism through the concept of Socioenterprise in halal tourism. This study uses a mix method, namely panel data regression with the object of 10 provinces and districts in West Nusa Tenggara. Descriptive qualitative approach by proposing the concept of sociopreneur as a constructive solution to the implementation of pro-poor tourism. The data from this study were obtained from interviews with related departments, direct observations and from related documents. The results showed that the seven variables in this study, namely the number of tourist visits, the number of tourism businesses, the population, the average length of schooling, unemployment, GDP and PAD had a significant effect on poverty in 10 districts and cities in NTB both simultaneously and individually. The emergence of a concept of Sociopreneur Bajang Pacu, Bajang Pacu has a business unit consisting of Charity Holiday and Ecotourism, people's lodging with a guest concept, rental of climbing equipment and cars, positive hangout shops, while the social unit consists of the 1000 book movement for Lombok, orphaned safari, cinema orphans, and trainings related to tourism development.

MODELING OPEN UNEMPLOYMENT RATE IN KALIMANTAN ISLAND USING NONPARAMETRIC REGRESSION WITH FOURIER SERIES ESTIMATOR

Nonparametric regression is a regression approach that is used to determine the relationship between the response variable and the predictor variable if the shape of the regression curve is unknown. One of the popular estimators used in nonparametric regression is the Fourier series estimator. Fourier series nonparametric regression is generally used when the pattern of the investigated data is unknown and there is a tendency for the pattern to repeat. The purpose of this study is to estimate nonparametric regression using the Fourier series approach and to find out the factors that influence the open unemployment rate on the island of Borneo in 2021. The criteria for the goodness of the model used Generalized Cross Validation (GCV) and the coefficient of determination ( ). Based on the results, it was found that the best nonparametric regression model for the Fourier series was the model with 5 oscillations which indicated a minimum GCV of 10.47 and an  of 74.22%. Furthermore, based on the results of parameter significance testing either simultaneously or partially, it shows that all predictor variables have a significant effect on the open unemployment rate. The predictor variables include the labor force participation rate, the average length of schooling, the percentage of poor people, economic growth rate, and total population.

ESTIMATION OF GEOGRAPHICALLY WEIGHTED PANEL REGRESSION MODEL WITH BISQUARE KERNEL WEIGHTING FUNCTION ON PERCENTAGE OF STUNTING TODDLERS IN INDONESIA

Stunting is a condition of failure to thrive in children under five years old due to chronic malnutrition. Efforts that can be made to reduce the incidence of stunting in Indonesia are to identify factors that are thought to affect the incidence of stunting in Indonesia. The analysis methods used in this study are the global Fixed Effect Model (FEM) and the local Geographically Weighted Panel Regression (GWPR) model. FEM is a global regression model that assumes that each individual's model has a different intercept value. While GWPR is a local regression model from FEM that considers aspects of geographic location, by repeating data at each observation location, different times, and using spatial data. The weighting function used in this study is fixed bisquare and adaptive bisquare. This study aims to obtain a GWPR model on the percentage of stunting toddlers in Indonesia in 2019 until 2022 with independent variables, namely the percentage of children receiving exclusive breastfeeding , the percentage of households that have access to proper sanitation , the average per capita health expenditure of the population for a month , the average length of schooling for women , and the number of poor people . The variables are obtained from Statistics Indonesia (BPS) and Study of Indonesia’s Nutritional Status (SSGI). The results showed that the best weighting function, namely adaptive bisquare with a CV value of 264.80.

Classification of The Human Development Index in Kalimantan Using Random Forest Method

Random Forest is an ensemble classifier in a machine-learning algorithm. The ensemble classifier aimed to improve model accuracy and classification performance. Based on accuracy measures, Random Forest shows the best performance with existing ensemble classifiers like Support Vector Machine (SVM) and AdaBoost. Hence, this research will classify Human Development Index in Kalimantan using a Random Forest classifier. The predictor variables of classification are the average length of schooling, adjusted per capita additions, life expectancy, and length of school expectations. The Random Forest showed that the number of trees selected was 500 and the m being tried was 2. Adjusted per capita additions were the most influential variable in the increase of The Human Development Index with an importance of 10,61%. The Accuracy of classification was 58,33%.

Analisis Faktor-Faktor yang Mempengaruhi Penyerapan Tenaga Kerja di Kota Jambi

This study aims for analyzing the influence of the average length of study at school , minimum wage , number of company , Gross Regional Domestic Product (GRDP) and Domestic Investment (DI) on the absorption of labor in Jambi City. The data used in this study is secondary data in coherent time from 2000 to 2021 derived from Institute of Statistics Centre (ISC). Method analysis used in this research is analysis of quantitative multiple linear regression . The result study shows that the average length of schooling is positively influenced and leads to negative significant to absorption of labor. The minimum wage is positively and significantly influenced and to absorption of labor. Domestic Invesyment (ID) is positively and significantly influenced to absorption of labor.Gross Regional Domestic Product (GRDP) and numner of company have no influence to absorption of labor.

Indeks Pembangunan Manusia Kabupaten Wonosobo Tahun 2014-2023 Ditinjau dari Indeks Pendidikan dan Kesehatan

The aim of this research is to determine the human development index (HDI) in Wonosobo Regency from 2014 to 2023 based on the education index which consists of average length of schooling (ALS) and expected length of schooling (EYS) as well as health expressed by life expectancy at birth (LEB). Research data was obtained from data from the BPS-Statistic of Wonosobo Regency, Central Java Province, as well as the national BPS. The analysis in this research includes the classical assumption test, multiple linear regression analysis, coefficient of determination test, and anova test. The research results show that partially the ALS and LEB variables have a positive and significant effect on HDI, while the EYS variable has an insignificant effect. Meanwhile, the third variable has a positive and significant effect on HDI simultaneously with an influence level of 98%.

Manajemen Program Satu Keluarga Satu Sarjana Kota Pariaman

This article explains the management of the One Family One Scholar Program in the city of Pariaman. The background of this research is based on the observation that the college participation rate in Indonesia is still very low, and the average length of schooling is also low. As a result, several educational programs have been created by the government, including the Pariaman City Government's One Family One Scholar Program. This program has been established since 2018 with the aim of eradicating poverty and improving the quality of human resources. The research was analyzed using a qualitative method with the management function theory by Ricky W. Griffin, which consists of planning, organizing, directing, and controlling. The results of the research indicate that the management of the One Family One Scholar Program in Pariaman has been running well, and all stages of management, including planning, organizing, directing, and controlling, have been carried out. However, there are still some challenges in its implementation, such as the absence of specific planning made since the beginning to address all obstacles. The city government only relies on the initial planning of this program, even though it is no longer effective. For example, the target set by the Pariaman City Government has never been achieved in the past 5 years, despite several evaluations and improvements made to the program

Panel Data Spatial Regression Modeling with a Rook Contiguity Weighting Function on the Human Development Index in West Sumatera Province

The achievement of the level of welfare of a region or country can be seen from the level of human development as measured by the Human Development Index (HDI). West Sumatra is one of the provinces with HDI achievements above the national average. However, there are still regencies/cities in West Sumatra Province that have HDI achievements below the national average and HDI achievements in West Sumatra Province Regencies/Cities have changed in 2017-2021. Therefore, in this study, spatial analysis of panel data was used. The aim of this research is to find out the general description of the HDI of West Sumatra Province, obtain a panel data spatial regression model and obtain variables that significantly influence on HDI in West Sumatra Province 2017─2021because differences in HDI achievement were suspected to have influences from areas that were side by side and the area was observed more than once. The model formed from this analysis using the rook contigutiy weighting function is Random Effect Spatial Autoregressive because the spatial interactions formed in human development index data in West Sumatra Province are real at lag. This model is a suitable model based on panel spatial model selection and has an R2 value of 92.94%. Analysis of human development index data in regencies/cities in West Sumatra Province using spatial regression panel data obtained results that expectations of school length (X1), average length of schooling (X2), and population density (X3) significantly directly influenced the human development index in regencies/cities in West Sumatra Province.  

Analisis Spasial Angka Kematian Balita di Pulau Papua Menggunakan Mixed Geographically Weighted Regression

<p>One of the goals of the Sustainable Development Goals is to end under five mortality which can be prevented by at least 25 per 1000 live births by 2030. Based on Badan Pusat Statistik (BPS) data, in 2020 the Under Five Mortality Rate (U5MR) in Papua Province is 49.04, while in West Papua Province of 47.23. This figure makes the island of Papua the island with the highest U5MR compared to other islands in Indonesia. The problem of U5MR has different influencing factors for each region, so it is important to include spatial effects in the analysis. The Mixed GWR model can be used to overcome spatial linkages between regions, accommodate variations in the form of spatial heterogeneity, and handle variations in parameters that are global and local in nature. Therefore, this study aims to analyze the variables that affect U5MR in Papua Island using Mixed GWR. This study uses secondary data sourced from BPS. The unit of analysis for this research is the districts/cities in Papua Island. The dependent variable in this study is U5MR, while the independent variables include the percentage of women aged at first pregnancy less than 21 years, Gross Regional Domestic Product per capita, the percentage of households with the main type of fuel in the form of solid fuel, the average length of schooling, and the percentage of households with access to source of proper drinking water. The results showed that the percentage of women aged at first pregnancy less than 21 years, the percentage of households with the main type of fuel in the form of solid fuel, the average length of schooling, and the percentage of households with access to source of proper drinking water had a significant effect on U5MR in several districts/cities on the island of Papua. Therefore, it is hoped that district/city governments on the island of Papua in developing programs/policies to reduce U5MR can adjust to the conditions of each region.</p><p><strong>Keywords: </strong>Under Five Mortality Rate; Papua island; Mixed GWR</p>

The Influence of Expected Years of Schooling, Average Years of Schooling and Per Capita Expenditures on the Human Development Index in North Sumatra Province 2010-2022

This research aims to find out how the expected number of years of schooling, average length of schooling, per capita expenditure affect the human development index in Indonesia. The components of the independent variable X1 are the expected number of years of schooling, and variable X2 is the average number of years of schooling and variable X3 is per capita expenditure. The dependent variable (Y) is the Human Development Index. The population and sample for this study are data from BPS regarding the expected number of years of schooling, average length of schooling, per capita expenditure in North Sumatra province for the 2010-2022 period via the official website www.bps.go.id. The method used is a quantitative method with research data, namely secondary data. The collected data is processed using IBM SPSS 25, as well as journals and theses as references. The data analysis used is descriptive tests, classical assumption tests, regression tests, coefficient of determination and significance tests. The results of this research partially show that the average length of schooling and per capita expenditure have a significant effect on the human development index, while the expected number of years of schooling does not have a significant effect on the human development index.

Identification of factors affecting the cases of under-age female marriage using geographically weighted panel regression approach in south kalimantan province.

The topic of this study was chosen because the percentage of underage female marriages in South Kalimantan Province was the highest in Indonesia over the last five years, from 2018 to 2022. This signifies that there are social issues in the local community that the government must address. One possible answer is to identify the factors that contribute to the creation of these conditions in each region. Using the Geographically Weighted Panel Regression (GWPR) method, this study attempts to determine the factors that influence the rise of underage female marriage instances in South Kalimantan Province. The number of poor individuals, population density, average duration of schooling, adjusted per capita expenditure, and total population were chosen as independent variables. Data acquired from South Kalimantan Province's Central Bureau of Statistics' periodic releases. Because there was high spatial heterogeneity between each location in this study, it was quite practical to employ the GWPR approach in developing a conjectural model. The results of evaluating the GWPR model with adaptive Gaussian kernel weights provide significant results and the model can explain the variance of data by 55 percent. Testing the parameters of the GWPR model reveals two (two) regional groupings with distinct influencing variables. The first group consists of ten (ten) regions that are considerably impacted by both the number of impoverished people and the average length of schooling, whereas the second group consists of three (three) regions that are impacted solely by the average length of schooling.

Determinan Perencanaan Pembangunan Manusia Di Pulau Jawa

The quality of human resources has an important contribution to the success of development in the context of increasing people's welfare. This research aims to identify the factors that make a major contribution to the increase in the HDI and examine the effect of poverty and unemployment on the achievement of quality human resource development. By using secondary data sources sourced from the Central Bureau of Statistics and the Directorate General of Fiscal Balance as well as the EViews analysis tool, the research results show that life expectancy, expected length of schooling, average length of schooling, spending per capita have a significant effect on the development of the quality of human resources on the island of Java. Meanwhile, poverty and unemployment have a negative impact on the development of the quality of human resources on the island of Java. The results of this research might be become a foundation for policy makers to explore education spending and health spending instruments to improve the quality of human resources. The results of the research also show that quality human resources are able to improve people's welfare through economic development, reducing poverty and unemployment. Keywords: Human development; economic development; education; health; poverty; unemployment

Pengaruh Angka Harapan Hidup, Rata-rata Lama Sekolah dan Paritas Daya Beli Terhadap PDRB di Kalimantan Selatan

This study shows the effect of life expectancy, average length of schooling, and purchasing power parity on GRDP in South Kalimantan. This study uses secondary data obtained from the Central Statistics Agency in 2011-2020, with time series analysis data; the results of the study state: life expectancy has a negative and insignificant effect on GRDP in South Kalimantan; the average length of schooling has a positive and significant impact on GRDP in South Kalimantan; Purchasing power parity has a positive and significant effect on GRDP in South Kalimantan; The value of the determinant coefficient (R2) is 0.974301 with the intention that GRDP is influenced by three variables, namely life expectancy, average length of schooling and purchasing power parity 97% and the rest is influenced by other factors 3%.

ANALYSIS OF FACTORS AFFECTING THE HUMAN DEVELOPMENT INDEX IN DISTRICTS/CITIES IN BALI PROVINCE

The aim of this research is to 1) determine the influence of life expectancy on the human development index in districts/cities in Bali Province; 2) Knowing the effect of average length of schooling on the human development index in districts/cities in Bali Province; 3) Knowing the effect of poverty levels on the human development index in districts/cities in Bali Province; 4) Knowing the effect of life expectancy, average length of schooling, and poverty level on the human development index in districts/cities in Bali Province. Research was conducted in districts/cities in Bali Province. This research was conducted in districts/cities in Bali Province using 117 observation points taking into consideration the occurrence of disparities in life expectancy, average length of schooling, poverty level, and human development index between districts/cities in Bali Province. This research uses data released by the Bali Province Central Statistics Agency (BPS). The object of this research focuses on four main variables, namely life expectancy, average years of schooling, poverty level, and human development index. The data analysis techniques used to solve the problems in this research are: Classic Assumption Test and Hypothesis Testing with Multiple Linear Regression Analysis Techniques.Based on the results of the analysis, it is known that with a confidence level of 98.1 percent, all independent variables have a significant effect, both simultaneously and partially, on the dependent variable. This means that the factors studied which consist of life expectancy, average length of schooling and poverty level influence the human development index in districts/cities in Bali Province have a significant effect both partially and simultaneously. If we look at the high coefficient of determination, 98.1 percent of the variation in life expectancy, average years of schooling and poverty levels, which can explain variations in the human development index in districts/cities in Bali Province, so that they can provide different contributions for each model. Studies.

The Effect of Education, Workforce, Economic Growth and Labor Force Participation Rate on City Labor Absorption in Aceh Province, Indonesia

The Labor Force Participation Rate (LFPR) provides an overview of the population aged 15 years and over who are active at working age, whether they are currently working, not yet working, or looking for work. By knowing the LFPR, the percentage of the working-age population that is economically active in a region can be known. The higher the LFPR, the higher the supply of available labor to produce goods and services. This study aims to analyze the effect of education, junior and senior high school workforce, economic growth, and labor force participation rates on employment absorption in the districts/cities of Aceh Province. The data used is secondary data with a time series from 2014 to 2021 and cross-sections from 23 districts/cities in Aceh Province. Data analysis used the Panel Regression Model with the Generalized Least Squares Method. The results showed that the workforce has a junior high school education, the average length of schooling, and the labor force participation rate positively affect employment. In contrast, the workforce has a high school education, and economic growth does not affect employment. Considering that the number of junior high school education staff is the largest, educational improvement must be carried out with government policies in remote areas in Aceh Province so that more highly educated workers can be absorbed.

The determinants of poverty in the West Papua province

Poverty has become a serious development problem, including in West Papua Province. This research has become a fundamental issue because West Papua tends to be difficult to get out of poverty problems, which has the second-highest percentage of poverty in Indonesia. This study aims to analyze the determinants of poverty in West Papua. The dependent variable is poverty, and the independent variables are population density, unemployment, human development index, and the average length of schooling. This research uses multiple regression analysis time series, 11 years period. The finding of this study is that unemployment has a positive and significant effect on poverty. Meanwhile, the human development index and the average length of schooling have a negative and significant effect. The implication is that the human development index and the average length of schooling must be expanded in scope to open access to people living in remote areas. The region's characteristics and the population tend to live in the interior, so accessibility is an important factor in alleviating poverty in West Papua.

POVERTY PANEL DATA MODELING IN SOUTH SUMATERA

Poverty is still a major problem on Sumatra's island, despite abundant natural resources potential, such as mining and plantation products. Sumatra Island consists of 10 provinces divided into three regions: Northern Sumatra, Central Sumatra, and Southern Sumatra. The island of Sumatra has the highest number of poor people in the Southern Sumatra region, which reaches 2.88 million people. Poverty is an integrated concept with five dimensions: poverty, powerlessness, vulnerability to emergencies, dependency, and alienation, both geographically and sociologically. One method that can be used to analyze poverty data problems is panel data regression analysis, which combines two data, namely cross-sectional data and time series data. It is expected to produce more in-depth and comprehensive information, both the interrelationships between the variables and their development within a certain period. The panel data was related to poverty and included 60 districts in the southern Sumatra region from 2018 to 2020. This study aimed to model poverty panel data in Southern Sumatra. Three estimation methods were used in the panel data regression, including the Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM. The results of the model specification test show that the best model for estimating the percentage of poor people in the Southern Sumatra region is the Fixed Effect Model (FEM), with a value of R2 = 75.57%. The results of the significance test show that the variables that significantly influence the percentage of poverty in the Southern Sumatra region using the FEM model are the open unemployment rate (), life expectancy (), and the average length of schooling ().