scholarly journals IMPLEMENTATION OF LOCALLY COMPENSATED RIDGE-GEOGRAPHICALLY WEIGHTED REGRESSION MODEL IN SPATIAL DATA WITH MULTICOLLINEARITY PROBLEMS (Case Study: Stunting among Children Aged under Five Years in East Nusa Tenggara Province)

2020 ◽  
Vol 13 (2) ◽  
pp. 125-135
Author(s):  
Alfi Fadliana ◽  
Henny Pramoedyo ◽  
Rahma Fitriani
Keyword(s):  
Spatial Data ◽  
Factors Affecting ◽  
Under Five ◽  
Capita Expenditure ◽  
Geographically Weighted Regression Model ◽  
Per Capita ◽  
Gwr Model ◽  
Baseline Health ◽  
Model Approach

East Nusa Tenggara Province, according to the findings of 2013 Baseline Health Research and 2016 and 2017 Nutritional Status Surveys, was recorded as the province with the highest prevalence of stunting in Indonesia. Efforts should be made to formulate policies that are integrated with spatial aspects in order to reduce the prevalence of stunting. The LCR-GWR model approach is used by using locally compensated ridge, which were meant to adjusts to the effect of collinearity between predictor variables (i.e., the factors affecting the prevalence of stunting) in each area. Results of the analysis showed that factors affecting the prevalence of stunting in all districts/cities in East Nusa Tenggara Province are the percentage of children aged under five who were weighed ≥ 4 times, the percentage of children aged under five who receive complete basic immunization, the percentage of households consuming iodized salt, the percentage of households with decent source of drinking water and the real per capita expenditure. The analysis showed that LCR-GWR is able to produce a better model than the GWR model in overcoming local multicollinearity problems in stunting in East Nusa Tenggara Province, with lower RMSE value (0.0344) than the GWR RMSE model (3.8899).

scholarly journals Analysis on spatial distribution pattern of football fields: A case study in Wuhan, China

2021 ◽  
Vol 293 ◽  
pp. 02051
Author(s):  
Yuwei Wang ◽  
Kaicheng Wu ◽  
Wang Gao
Keyword(s):  
Spatial Data ◽  
Global Scale ◽  
Spatial Data Analysis ◽  
Wuhan City ◽  
The Sustainable Development ◽  
Aggregation Pattern ◽  
Per Capita ◽  
Football Field ◽  
Global And Local

In order to promote the sustainable development of sports facilities, the statistical data of football fields in 13 districts of Wuhan city were selected. Based on geographic information system (GIS) and exploratory spatial data analysis (ESDA) technology, this paper analyzed the global and local autocorrelation of the number of football fields per capita in Wuhan city. The results indicate that: (1) Comparing to the new districts in Wuhan, the number of football fields per capita in the central districts was relatively few. (2) In the global scale, the number of football fields per capita in Wuhan presented a spatial aggregation pattern. (3) In the local scale, the regional discrepancy and spatial clusters were confirmed in the local spatial autocorrelation analysis for football fields in Wuhan. At the same time, the research results could provide reasonable references for the planning of football field facilities.

scholarly journals Factors Affecting Income Distribution in Sulawesi

2022 ◽  
Vol 4 (1) ◽  
Author(s):  
Andi Riyanto ◽  
Syarwani Canon ◽  
Ivan Rahmad Santoso
Keyword(s):  
Regression Analysis ◽  
Life Expectancy ◽  
Income Distribution ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Factors Affecting ◽  
Capita Expenditure ◽  
Per Capita ◽  
Distribution Of Income ◽  
Central Statistics

This study aims to determine the factors that influence the distribution of income in Sulawesi. The data used is data sourced from the Central Statistics Agency, for the period 2011-2020 in 6 Sulawesi Island Provinces. The method used is multiple regression analysis with the help of the eviews 9 application. The results show that per capita expenditure has a positive and significant effect on income distribution, average years of schooling has a negative and significant effect on income distribution, life expectancy has a negative but not significant effect on income distribution.

scholarly journals Estimation of Geographically Weighted Regression Case Study on Wet Land Paddy Productivities in Tulungagung Regency

CAUCHY ◽  
2017 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Danang Ariyanto
Keyword(s):  
Spatial Data ◽  
Geographically Weighted Regression ◽  
Average Cost ◽  
Gaussian Kernel ◽  
Weighted Regression ◽  
Entire Study ◽  
Independent Variable ◽  
Gwr Model ◽  
Entire Study Area

<p>Regression is a method connected independent variable and dependent variable with estimation parameter as an output. Principal problem in this method is its application in spatial data. Geographically Weighted Regression (GWR) method used to solve the problem. GWR  is a regression technique that extends the traditional regression framework by allowing the estimation of local rather than global parameters. In other words, GWR runs a regression for each location, instead of a sole regression for the entire study area. The purpose of this research is to analyze the factors influencing wet land paddy productivities in Tulungagung Regency. The methods used in this research is  GWR using cross validation  bandwidth and weighted by adaptive Gaussian kernel fungtion.This research using  4 variables which are presumed affecting the wet land paddy productivities such as:  the rate of rainfall(X<span style="vertical-align: sub;">1</span>), the average cost of fertilizer per hectare(X<span style="vertical-align: sub;">2</span>), the average cost of pestisides per hectare(X<span style="vertical-align: sub;">3</span>) and Allocation of subsidized NPK fertilizer of food crops sub-sector(X<span style="vertical-align: sub;">4</span>). Based on the result, X<span style="vertical-align: sub;">1</span>, X<span style="vertical-align: sub;">2</span>, X<span style="vertical-align: sub;">3</span> and X<span style="vertical-align: sub;">4 </span> has a different effect on each Distric. So, to improve the productivity of wet land paddy in Tulungagung Regency required a special policy based on the GWR model in each distric.</p>

scholarly journals ANALYSIS OF FACTORS AFFECTING THE IMPORT OF DAIRY MILK (CASE STUDY: THE IMPORT OF DAIRY MILK IN INDONESIA)

2021 ◽  
Vol 5 (1) ◽  
pp. 27-33
Author(s):  
Kustopo Budiraharjo ◽  
Budi Raharjo ◽  
Solikhin Solikhin
Keyword(s):  
Milk Production ◽  
Secondary Data ◽  
Negative Influence ◽  
Positive Influence ◽  
Gdp Per Capita ◽  
Milk Consumption ◽  
Factors Affecting ◽  
Per Capita ◽  
Dairy Milk

The supply of fresh dairy milk in the country (SSDN) has not been able to meet the needs of domestic dairy milk consumption so that the fulfillment of dairy milk consumption needs is also done byimporting dairy milk. This study aims to analyze the factors that influence milk imports in Indonesia.The research method uses quantitative analysis techniques, namely multiple linear regression. This research was conducted in Indonesia using secondary data from 2006-2016 obtained at the Central Statistics Agency and the Ministry of Agriculture and other literature related to research. Research variables include exchange rates, GDP per capita, milk exports, and milk production. The results showed that variables GDP per capita, milk exports, and milk production have positive influence. Meanwhile, exchange rate has negative influence for milk imports.  

scholarly journals A Method of Population Spatialization Considering Parametric Spatial Stationarity: Case Study of the Southwestern Area of China

2019 ◽  
Vol 8 (11) ◽  
pp. 495 ◽  
Author(s):  
Xiong ◽  
Li ◽  
Cheng ◽  
Ye ◽  
Zhang
Keyword(s):  
Regression Models ◽  
Population Distribution ◽  
Percentage Error ◽  
Night Time ◽  
Geographically Weighted Regression Model ◽  
Southwestern Area ◽  
The Mean ◽  
Gwr Model ◽  
Better Than

Population is a crucial basis for the study of sociology, geography, environmental studies, and other disciplines; accurate estimates of population are of great significance for many countries. Many studies have developed population spatialization methods. However, little attention has been paid to the differential treatment of the spatial stationarity and non-stationarity of variables. Based on a semi-parametric, geographically weighted regression model (s-GWR), this paper attempts to construct a novel, precise population spatialization method considering parametric stationarity to enhance spatialization accuracy; the southwestern area of China is used as the study area for comparison and validation. In this study, the night-time light and land use data were integrated as weighting factors to establish the population model; based on the analysis of variables characteristics, the method uses an s-GWR model to deal with the spatial stationarity of variables and reduce regional errors. Finally, the spatial distribution of the population (SSDP) of the study area in 2010 was obtained. When assessed against the traditional regression models, the model that considers parametric stationarity is more accurate than the models without it. Furthermore, the comparison with three commonly-used population grids reveals that the SSDP has a percentage error close to zero at the county level, while at the township level, the mean relative error of SSDP is 33.63%, and that is >15% better than other population grids. Thus, this study suggests that the proposed method can produce a more accurate population distribution.

scholarly journals Factors affecting Mortality Rate of Infants and under Five in the Philippines: An application of Structural Equation Modeling

2017 ◽  
pp. 21-25
Author(s):  
Sherwin S. Fortugaliza
Keyword(s):  
Mortality Rate ◽  
Gross Domestic Product ◽  
Health Expenditure ◽  
Structural Equation ◽  
The Philippines ◽  
Domestic Product ◽  
Equation Modeling ◽  
Factors Affecting ◽  
Under Five ◽  
Per Capita

A gradual decrease of the mortality rate of infants and under five in the Philippines was recorded from 1996 to 2013. However, this sign of progress still requires additional efforts to achieve the Millennium Development Goal of reducing the risk. This paper attempts to test empirically the different factors affecting mortality rate of infants and under five in the Philippines, an indicator in gauging health security using a time series data (1996-2013). This will serve as a basis in crafting policies that will critically and efficiently reduce the number of deaths. The average mortality rate of infants and under five was selected as the endogenous variable, Gross Domestic Product per capita and out of the pocket health expenditure were treated as the exogenous variable. Health expenditure total percentage of Gross Domestic Product and average percentage of immunization were the mediating variables. Using structural equation modeling, all these variables were tested for possible complex causality. Result showed that both Average Immunization and Gross Domestic Product per capita significantly affect mortality rate (β=-.510, p<.000; β=-1.340, p<.05). Thus, it is strongly recommended that the country should critically undertake measures to increase Gross Domestic Product per capita and should widen immunization rate.

Factors Affecting The Sustainability Of The Asphalt Roads: A Case Study Of Irbid Inner Ring Road, Jordan

2011 ◽  
Vol 1 (5) ◽  
pp. 93-94
Author(s):  
Eng. Nasr Ahmad Eng. Nasr Ahmad ◽  
◽  
Dr. Mihai Iliescu
Keyword(s):  
Factors Affecting ◽  
Ring Road

Factors Affecting Financial Literacy of Vietnamese Adults: A Case Study for Hanoi and Nghe An

2017 ◽  
Vol 33 (2) ◽  
Author(s):  
Tue Nguyen Dang
Keyword(s):  
Higher Education ◽  
Multiple Regression ◽  
Financial Literacy ◽  
Urban Areas ◽  
Logistic Models ◽  
Factors Affecting ◽  
Financial Behaviors ◽  
Financial Decisions ◽  
Literacy Level

This research examines the factors affecting the financial literacy of Vietnamese adults. Using a sample of 266 observations of adults in 2 big cities in Vietnam (Hanoi and Vinh in Nghe An Province), the author evaluates the literacy level of adults in these urban areas. The financial literacy of the interviewed people is low. The multiple regression results show that lower financial literacy levels associate with higher age and married status and higher financial literacy levels associate with higher education, more family members, the person making financial decisions and the person attending a useful financial course. This research also explores the association between financial literacy and financial behaviors of individuals employing logistic models. It is found that higher financial literacy associates with less probability of overspending and higher probability of saving money and careful spending. Higher financial literacy is also found to associate with higher probability of opening a savings account and making various investments. 

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