scholarly journals Identification of Factors Affecting Tuberculosis in West Java using Spatial Modeling

2021 ◽  
pp. 9-17
Author(s):  
Yusma Yanti ◽  
Septian Rahardiantoro
Keyword(s):  
Spatial Modeling ◽  
Spatial Model ◽  
Alcoholic Beverages ◽  
Spatial Error Model ◽  
West Java ◽  
Spatial Error ◽  
Factors Affecting ◽  
The World ◽  
Spatial Autoregressive ◽  
Better Than

Tuberculosis (TB) is an infectious disease caused by the bacillus Mycobacterium tuberculosis. In 2017 WHO records there are 1.7 billion TB sufferers in the world. Whereas in the same year TB sufferers in Indonesia reached 421 thousand cases and 10 thousand of them were in the province of West Java. In this study, the factors that suspected to influence TB include poverty, population density and malnutrition were analyzed by looking at the spatial aspects. In addition to these factors, smoking and consuming alcoholic beverages can also trigger TB. The method used was Spatial Autoregressive Model (SARM), Spatial Error Model (SEM), and Generalized Spatial Model (GSM), then the best model is chosen based on the best criteria of lagrange multiplayer test. The result indicated that SEM performed better than others, with the following significant variables were malnutrition and unemployment factor.

scholarly journals Influence of overweight and obesity on the diabetes in the world on adult people using spatial regression

2016 ◽  
Vol 2 (3) ◽  
pp. 149
Author(s):  
Tuti Purwaningsih ◽  
Baharudin Machmud
Keyword(s):  
Spatial Model ◽  
Spatial Regression ◽  
Overweight And Obesity ◽  
Spatial Error Model ◽  
Spatial Error ◽  
Obesity And Overweight ◽  
The World ◽  
Level Of Significance ◽  
Global Nutrition ◽  
Level Order

This research discussed about the case of diabetes, overweight, and obesity which aimed to determine the factors that most affect the number of adult people with Diabetes from Obesity and Overweight in the world and looking for the best spatial model to make predictions in the next period. This research based on data WHO in 2015 from The 2016 Global Nutrition Report. At 5% level of significance for 2015, factor that influence diabetes is obesity and the most excellent spatial model used in the analysis is Spatial Error Model (SEM) that use Weight Level Order 1 and has R2 value 81.82%.

scholarly journals Model Regresi Spasial dan Aplikasinya pada Kasus Tingkat Kemiskinan Kabupaten Soppeng

2018 ◽  
Vol 4 (2) ◽  
pp. 102
Author(s):  
Anggi Ananda Putri ◽  
Wahidah Sanusi ◽  
Sukarna Sukarna
Keyword(s):  
Social Issues ◽  
Well Being ◽  
Error Model ◽  
Poor Household ◽  
Spatial Dependency ◽  
Spatial Error Model ◽  
Spatial Error ◽  
Sar Model ◽  
Spatial Autoregressive ◽  
Independent Variable

Poverty is one of the major problem that frequently faced by human. Begin from poverty, consequently emerged several social issues, such as homeless, beggar, defendant, and prostitution. On this research were conducted modeling poverty degree in Soppeng with using number of poor household as the dependent variable. Modeling were done by using area approach which is a Spatial Autoregressive (SAR) model and Spatial Error Model (SEM). As for the independent variable used on this research is the number of health services, school facility, population density, social well being disable, and the distance on village and centre of Soppeng.  Regarding to the analysis of Spatial Autoregressive (SAR) and Spatial Error Model (SEM) shows that there is a spatial dependency lag and error on number of poor household variable. As for the independent variable which have the significancy account for 5% on Spatial Autoregressive (SAR) and Spatial Error Model (SEM) are every variables with a number R2= 90,9% on SAR and R2= 90,1% on SEM.

scholarly journals Innovación en Ecuador: un enfoque espacial/Innovation in Ecuador: a spatial approach

2020 ◽  
Author(s):  
V Morales-Oñate ◽  
B Morales-Oñate
Keyword(s):  
Government Support ◽  
Spatial Error Model ◽  
Spatial Error ◽  
Spatial Spillovers ◽  
Spatial Influence ◽  
Spatial Approach ◽  
Palabras Clave ◽  
Proposed Model ◽  
Private Banks ◽  
Spatial Autoregressive

Este trabajo explora la distribución espacial del éxito innovador de las empresas en Ecuador entre 2012 y 2014. Los datos cuentan con una muestra de 6275 empresas con representatividad provincial. En base a esta información, los objetivos que persigue esta investigación están orientados a i) establecer si existe o no relaciones espaciales en las provincias del Ecuador y ii) resaltar políticas estatales que contribuyan a la innovación. Los resultados muestran que existe influencia espacial en el éxito innovador. Asimismo, el modelo planteado sugiere políticas orientadas a la innovación mediante apoyo del Gobierno así como financiamiento por parte de la banca privada. This paper explores the spatial distribution of the innovative success of companies in Ecuador between 2012 and 2014. The data has a sample of 6275 companies with provincial representation. Based on this information, the objectives pursued by this research are aimed at i) establishing whether or not there are spatial relationships in the provinces of Ecuador and ii) highlighting state policies that contribute to innovation. The results show that there is a spatial influence on innovative success. Likewise, the proposed model suggests policies oriented towards innovation through government support as well as financing from private banks. Palabras clave: Spillovers espaciales, Modelo espacial autorregresivo, Modelo de error espacial, Modelo espacial de Durbin. Keywords: Spatial spillovers, Spatial autoregressive model, Spatial Error Model, Spatial Durbin Model.

scholarly journals Income Absolute Beta-Convergence of NUTS 3 Level Regions in New EU Member States before and During a Crisis

2016 ◽  
Vol 16 (2) ◽  
pp. 151-162 ◽  
Author(s):  
Paweł Folfas
Keyword(s):  
Spatial Model ◽  
Ordinary Least Squares ◽  
Spatial Error Model ◽  
Spatial Error ◽  
Member States ◽  
Absolute Income ◽  
Eu Member States ◽  
Spatial Dependencies ◽  
Beta Convergence ◽  
New Eu Member States

Abstract This paper is aimed at answering the question of whether absolute income (GDP per capita) beta-convergence exists in the case of regions in new EU Member States before the period of 2000–2008 and during the 2008–2011 crisis. The sample consists of 211 regions (NUTS 3-level) of Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovenia and Slovakia. The research is based on econometric models, namely on the spatial lagged model (SLM), the spatial error model (SEM) and the Durbin spatial model which contrary to the ordinary least squares the (OLS) model include possible spatial dependencies. The SLM and SEM models as well as the Durbin spatial model detect the absolute income beta-convergence on the level of about 1% during the years 2000–2008. Additionally, models do not confirm the existence of absolute income beta-convergence during the crisis of 2008–2011. SLM models (which offer the most reliable findings) find a spatial correlation (measured by the rho-parameter) at a level of 0.75 during 2000–2008 and 0.35 during 2008–2011. Thus, absolute income beta-convergence in the case of NUTS 3 regions in 10 new EU Member States existed only in the pre-crisis period and this period is characterized by much stronger spatial dependencies than the period of 2008–2011.

scholarly journals Empleo en el sector terciario. Una estimación espacial para los municipios de la región centro de México, 1999-2009

2016 ◽  
Vol 29 (68) ◽  
Author(s):  
Leobardo De Jesús Almonte ◽  
Yolanda Carbajal Suárez
Keyword(s):  
Spatial Autocorrelation ◽  
Central Region ◽  
Spatial Econometrics ◽  
Error Model ◽  
Moran’S I ◽  
Spatial Error Model ◽  
Tertiary Sector ◽  
Spatial Error ◽  
Moran's I ◽  
Spatial Autoregressive

Resumen: el objetivo es identificar un patrón de aglomeración en la división espacial del empleo en el sector servicios entre los municipios de la región centro de México. Con el método de la econometría espacial, se estimó un modelo de error espacial para el sector terciario. Según los resultados, la elasticidad ingreso del empleo es baja, el peso de las unidades económicas es importante y hay poca sensibilidad al incremento en las remuneraciones. A pesar de que el análisis exploratorio, a partir de Índice de Moran, sugiere efectos de autocorrelación espacial del empleo en la región de estudio, esto no se puede confirmar con suficiente robustez a partir de los resultados de la estimación de un modelo de error espacial. Aunque esta técnica no es novedosa, en México hay pocos trabajos aplicados al empleo en el sector terciario. El parámetro autorregresivo espacial del término de error l aporta evidencia de que existe una asociación espacial local del empleo, más que una global. Se concluye que en el sector terciario, la vecindad espacial entre los municipios de mayor dinamismo ha generado más crecimiento y aglomeración, que en el resto de ellos.Palabras clave: división espacial del empleo; sector terciario de México; autocorrelación espacial (I de Moran); análisis económico espacial; modelo de error espacial; región centro de México.Employment in the tertiary sector. A spatial estimation for municipalities in Mexico’s central region, 1999-2009Abstract: the aim is to identify an agglomeration pattern in the services sector’s spatial division of employment among municipalities in Mexico’s central region. By using the method of spatial econometrics, a spatial error model was estimated for the tertiary sector. According to results, the income elasticity of employment is low, the weight of economic unities is significant and there is little sensitivity to an increase in wages. Although the exploratory analysis, based on Moran’s I, suggests effects of spatial autocorrelation of employment in the region studied, this cannot be confirmed with enough certainty from the results of the estimation of a spatial error model. Despite this estimation technique is not new, in Mexico there are few studies dealing with employment in the tertiary sector. The spatial autoregressive parameter of the error term provides evidence that there is a local rather than global spatial association of employment. It therefore follows that in the tertiary sector spatial vicinity among the most dynamic municipalities has generated more growth and agglomeration than in the rest of them.Key words: spatial division of labor; Mexico’s tertiary sector; spatial autocorrelation (Moran’s I); spatial economic analysis; spatial error model; Mexico’s central region.

scholarly journals Dampak Spillover Pekerja Migran Indonesia (PMI) Asal Jawa Tengah Terhadap Pertumbuhan Ekonomi Propinsi Jawa Tengah

2019 ◽  
Vol 1 (2) ◽  
pp. 191-207
Author(s):  
Caroline Caroline ◽  
FX Sugiyanto ◽  
Achmad Syakir Kurnia ◽  
Etty Puji Lestari ◽  
Ceacilia Srimindarti
Keyword(s):  
Saudi Arabia ◽  
Autoregressive Model ◽  
Euclidean Distance ◽  
Error Model ◽  
Spatial Error Model ◽  
Spatial Autoregressive Model ◽  
Spatial Durbin Model ◽  
Spatial Error ◽  
Spatial Autoregressive

Spillover tenaga kerja Propinsi Jawa Tengah tahun 2019 cukup tinggi 60.432 pekerja setelah Propinsi Jawa Timur, yaitu 68.740 pekerja. Spillover tenaga kerja Propinsi Jawa Tengah diduga karena jumlah penduduk yang banyak di Propinsi Jawa Tengah. Faktor pendorong Pekerja Migran Indonesia (PMI) berniat bekerja keluar negeri adalah untuk memperoleh pendapatan yang layak sehingga selisih pendapatan dan biaya hidupnya dapat dikirim keluarganya di Indonesia. Tujuan penelitian ini adalah menganalisis dampak spillover Pekerja Migran Indonesia (PMI) terhadap pertumbuhan ekonomi Propinsi Jawa Tengah. Metode penelitian ini menggunakan matriks bobot spasial dengan pendekatan Euclidean Distance untuk menghitung Spatial Autoregressive Model (SAR), Spatial Error Model (SAR), dan Spatial Durbin Model (SDM). Simpulan Hasil penelitian ini adalah sebagai berikut : Spillover tenaga kerja Propinsi Jawa Tengah yang diwujudkan dalam bentuk pekerja Migran Indonesia asal Jawa Tengah kebanyakan berasal dari Kabupaten Cilacap, Kabupaten Kendal, Kabupaten Brebes, Kabupaten Banyumas, Kabupaten Pati, Kabupaten Grobogan, Kabupaten Kebumen, Kabupaten Wonosobo, dan Kabupaten Batang dengan tingkat pendidikan Sekolah Menengah Pertama (SMP) dengan jenis kelamin wanita kebanyakan bekerja pada negara Negara Hongkong, Negara Taiwan, Negara Malaysia, Negara Singapura, Negara Korea Selatan, Negara Brunai Darussalam, dan Negara Saudi Arabia.

scholarly journals MEMODELKAN ANGKA GIZI BURUK DI PROVINSI BALI DENGAN PENDEKATAN REGRESI SPASIAL

2021 ◽  
Vol 10 (2) ◽  
pp. 103
Author(s):  
ANAK AGUNG ISTRI AYU PRATAMI ◽  
I KOMANG GDE SUKARSA ◽  
NI LUH PUTU SUCIPTAWATI ◽  
I PUTU EKA NILA KENCANA
Keyword(s):  
Birth Weight ◽  
Exclusive Breastfeeding ◽  
Spatial Regression ◽  
Geographic Location ◽  
Regression Method ◽  
Spatial Error Model ◽  
Spatial Autoregressive Model ◽  
Spatial Error ◽  
Regression Methods ◽  
Spatial Autoregressive

Nutritional problems in toddler are still a serious problem in various districts/cities in Indonesia. The case of malnutrition in Bali Province vary in many regions and hypothesized to be influenced by geographic location, which is often known as spatial heterogeneity. To overcome this problem, a spatial regression method is used on this research. This study aims to model the factors that are hypothesized affect malnourished toddlers in Bali Province using spatial regression methods, i.e. spatial autoregressive model (SAR) and spatial error model (SEM). Both models have 5 predictors variable, i.e. the percentage of toddlers aged between 6 - 59 months who received vitamin A, the percentage of babies with low birth weight (LBW), the percentage of households with clean and healthy living behavior (PHBS), the percentage of children under five receiving exclusive breastfeeding, and the percentage of toddler health services, which are obtained from Bali Provincial Health Office. The results showed SEM method produced smaller AIC value and higher , with  and  AIC values ??of 96.24% and 60.84, respectively.

scholarly journals A Fixed Effect Panel Spatial Error Model in Identifying Factors of Poverty in West Java Province

2021 ◽  
Vol 1776 (1) ◽  
pp. 012062
Author(s):  
Sudartianto ◽  
Firman ◽  
Y. Suparman ◽  
I. Ginanjar
Keyword(s):  
Error Model ◽  
Fixed Effect ◽  
Spatial Error Model ◽  
West Java ◽  
Spatial Error

Sanitation Practices and Policies in India: Exploring Determinants and their Interlinkages

2016 ◽  
Vol 5 (6) ◽  
pp. 197-204
Author(s):  
Binay Kumar Pathak ◽  
Aishna Sharma ◽  
Saumen Chattopadhyay
Keyword(s):  
Critical Evaluation ◽  
Point Of View ◽  
Open Defecation ◽  
Factors Affecting ◽  
Poor Countries ◽  
Secondary Sources ◽  
Hygiene Practices ◽  
The World ◽  
Better Than

India, one of the emerging economies of the world, is plagued with preva-lence of inadequate and poor sanitation facilities. Unhealthy hygiene practices and menace of open defecation still persist in the country which seeks to be counted as one of the superpowers. While some of the poor countries of the world fare better than India in terms of sanitation, it becomes essential to look beyond economic factors to understand the problem. The problems are manifold and appear in many dimensions. While sixty percent of popula-tion does not have access to toilet facilities, the instances of non-utilisation of existing toilet facilities are also reported. The non-utilisation of existing toilet facilities may range from planning related concerns to attitudinal issues. The planning or policy related concerns stem from problems related to maintenance of toilets, lack of plumbing and drainage facilities, lack of water and sewage systems etc. To understand these problems and the efforts to address them, critical evaluation of sanitation policies is needed. Sanitation policies and perceptions of masses towards sanitation practices can be complementary factors for cost of access to sanitation facilities. This paper seeks to look into the factors affecting inadequate sanitation facilities from a broader point of view focussing on policy and practices. The paper utilises secondary sources and a case study to unravel the factors and their interlinkages.

scholarly journals PEMODELAN REGRESI SPASIAL DEPENDENSI PADA TINGKAT PARTISIASI ANGKATAN KERJA DI INDONESIA TAHUN 2020

2021 ◽  
Vol 15 (4) ◽  
pp. 687-696
Author(s):  
Rahmayunda Usali ◽  
Nurwan Nurwan ◽  
Franky Alfrits Oroh ◽  
Muhammad Rezky Friesta Payu
Keyword(s):  
Labor Force ◽  
Labor Force Participation ◽  
Average Length ◽  
Spatial Regression ◽  
Participation Rate ◽  
Labor Force Participation Rate ◽  
Spatial Error ◽  
Factors Affecting ◽  
Sar Model ◽  
Spatial Autoregressive

This study discusses the regression modeling with spatial dependence to determine the factors affecting the labor force participation rate in Indonesia 2020. The spatial regression models used in this study are spatial Autoregressive Model (SAR) and Spatial Error Model (SEM), The finding concludes that the SAR model is better used in spatial modeling. At the same time, provincial minimum wage, the average length of school or educational level, and population are factors that affect the labor force participation rate in Indonesia 2020.

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