scholarly journals ANALISIS SPASIAL KELEMBAGAAN PETANI DAN KEMISKINAN PETANI TANAMAN PANGAN MENGGUNAKAN GEOGRAPHICALLY WEIGHTED REGRESSION DI PROVINSI JAMBI

2016 ◽  
Vol 18 (2) ◽  
pp. 83
Author(s):  
Inti Pertiwi Nashwari ◽  
Ernan Rustiadi ◽  
Hermanto Siregar ◽  
Bambang Juanda
Keyword(s):  
Rural Area ◽  
Geographically Weighted Regression ◽  
Poverty Reduction ◽  
Poverty Line ◽  
Weighted Regression ◽  
Agricultural Activity ◽  
Food Crop ◽  
Spatial Approach ◽  
The Government ◽  
Crop Farmer

<p class="judulabstrakindo"><strong>ABSTRAK</strong></p><p class="abstrak">Empat puluh persen (40%) masyarakat Indonesia yang terlibat dalam pertanian masih hidup di bawah garis kemiskinan. Berbagai upaya-upaya yang dilakukan pemerintah untuk mengurangi tingginya jumlah petani miskin belum mampu menurunkan kemiskinan petani secara berarti. Tujuan dari penelitian ini adalah menganalisis pengaruh kegiatan pertanian, fasilitas fisik pertanian dan akses kelembagaan petani terhadap pengurangan kemiskinan petani tanaman pangan di Provinsi Jambi. Provinsi Jambi dipilih sebagai lokasi penelitian karena wilayah ini memiliki kemiskinan di pedesaan yang tinggi dan Nilai Tukar Petani (NTP) yang paling rendah di Indonesia. Pendekatan spasial metode <em>Geographically Weighted Regression</em> (GWR) dipilih sebagai pendekatan alternatif dalam analisis kemiskinan petani karena dapat mempertimbangkan adanya keragaman karakteristik kemiskinan dan penyebab kemiskinan yang berbeda di masing-masing wilayah. Hasil yang diperoleh dalam penelitian ini menunjukkan bahwa banyaknya desa dengan jaringan jalan beton/aspal berpengaruh signifikan dalam menurunkan kemiskinan petani tanaman pangan di beberapa kecamatan Kabupaten Kerinci, satu kecamatan di Kabupaten Merangin dan seluruh kecamatan di Kabupaten Sungai Penuh. Semakin besar persentase desa yang melakukan kegiatan pemberdayaan dana bergulir/simpan pinjam untuk modal usaha pertanian selama tiga tahun terakhir di Kabupaten Sungai Penuh dan beberapa kecamatan di Kabupaten Kerinci akan menurunkan jumlah kemiskinan petani tanaman pangan di wilayah tersebut. Keberadaan fasilitas irigasi dan kegiatan pertanian tidak ada yang berpengaruh signifikan terhadap penurunan kemiskinan petani tanaman pangan.</p><p class="abstrak"><strong>Kata kunci</strong>: kemiskinan, petani tanaman pangan, analisis spasial, <em>Geographically Weighted Regression</em></p><p class="judulabstraking"><em><strong>ABSTRACT</strong></em></p><p class="keyword"><em>Forty percent (40%) of Indonesian people in agriculture sectors are still living under the poverty line. The government policies have been implemented to reduce poor farmers but it’s not significant. The purpose of this study is to describe the spatial pattern of agricultural activity, the agricultural facilities and farmers access to the farm institution and to analyze its impact on poverty reduction in food crop farmers in Jambi Province. Jambi Province is selected because have high number of poverty in rural area and the lowest Farmer’s Term of Trade Indices (NTP) in Indonesia. Spatial approach Geographically Weighted Regression (GWR) was used to analyze the factors influencing the poverty among food crops famers and consider the diversity of the characteristics of poverty and a cause of poverty is different in each region. The result of this study are rural area with asphaltroads was significantly influence reducing poverty food crop farmers in several districts Kerinci, districts Merangin and districts Sungai Penuh. Rural area with empowerment activities by revolving fund for agriculture also significantly influence reducing poverty food crop farmers in the district Sungai Penuh and district Kerinci in the last three years. The irrigation facilities and agricultural activities not significant reduce farmers crops poverty.</em></p><p class="keyword"><em><strong>Keywords</strong>: poverty, food crop farmer, spatial analysis, Geographically Weighted Regression</em></p>

SOCIO-ECONOMIC EMPOWERMENT OF WOMEN THROUGH MICRO CREDIT: AN EMPIRICAL STUDY

2021 ◽  
pp. 58-60
Author(s):  
T. Indumathi ◽  
G. Savaraiah
Keyword(s):  
Rural Women ◽  
Poverty Reduction ◽  
Rural Poverty ◽  
Poverty Line ◽  
Economic Empowerment ◽  
Political Empowerment ◽  
The Poor ◽  
The Government ◽  
The Impact ◽  
Micro Credit

The World Bank's Andhra Pradesh Rural Poverty Reduction Project supports the self helf groups of the women members. It promotes women's social, economic, legal and political empowerment to reduce poverty among the poor and the poorest of the poor. The important object of this article is to examine the impact of micronance on the socio economic empowerment of the rural women supported by the national reputed NGO- Rashtriya Seva Samithi (RASS). 184 women members of the SHGs promoted by Rasthriya Seva Samathi (RASS) an NGO which located in Tirupati town. 184 samples are selected randomly from 15 SHGs scattered throughout the Tirupati rural mandal (Taluk) from the area of the study have been considered to conduct the present research study. The study reveals that 87.71 percent of the sample women were below the poverty line before joining the SHGs. As a result of SHG, about 40 percent of the sample women crossed the poverty line. The highest intensive value indicates that more women have participated in social agitations for the welfare of the children and the society. The second highest intensity reveals that considerable numbers of women of SHGs have participated in the government sponsored schemes. The 1st point secured 3rd rank with total intensity value of 605 which status that the micro credit has resulted in increased social status and empowerment.

scholarly journals PERKEMBANGAN TINGKAT KEMISKINAN DAN KESENJANGAN SOSIAL REGIONAL DI INDONESIA 2011-2015

2017 ◽  
Vol 22 (1) ◽  
Author(s):  
Iwan Prasodjo
Keyword(s):  
Rural Area ◽  
Rural Areas ◽  
Urban Poor ◽  
Poverty Line ◽  
Poverty Rate ◽  
Poor People ◽  
Agriculture Sector ◽  
The Poor ◽  
The Government ◽  
Urban And Rural Areas

This article discusses on poverty rate and inequlity in urban and rural areas during 2011-15. It shows that poverty rate tends todecrease. The poverty in rural area is worse than that in the urban one. The urban poor people work in the informal sector or in the small business. The poor in the rural areas work in the agriculture sector. The majority of poorest provinces is in the east Indonesia. However, the majority of the poor people live in Java island. Eventough the income inequility in Indonesia is moderate, but it  has been increased since 2011. There are many more poor people above the national poverty line. The government could inprove rural and east Indonesia infstructure in order to increase agriculture production. In this way the poverty in rural area and the gap between east and west Indonesia could decrease.

scholarly journals Evaluation of the Effect of Farmer Input Support Program (FISP) on Small-Scale Farmers in the Kara Region of Togo

2019 ◽  
Vol 11 (4) ◽  
pp. 35
Author(s):  
John-Philippe Essiagnon Alavo ◽  
Emefa Adzowa-Sika Cogbe ◽  
Xiangmei Li ◽  
Gershom Mwalupaso Endelani ◽  
Ekram Abdalgadir Eltom ◽  
...  
Keyword(s):  
Poverty Reduction ◽  
Poverty Line ◽  
Support Program ◽  
Small Scale ◽  
Maize Production ◽  
Reduction Strategies ◽  
The Government ◽  
Cropping Seasons ◽  
Small Scale Farmers ◽  
The Impact

The government of Togo reintroduced Farmer Input Support Program (FISP) as one of its Poverty Reduction Strategies (PRS) in 2002. Since the introduction of the program, the studies that evaluate its effects on income have focused either on fertilizer or seed component, but not on both, which made it a challenge to find out what improvements in small-scale farmers&rsquo; productivity can be attributed to FISP as a whole. Using Propensity Score Matching technique with collected data from 150 randomly surveyed households in the Kara region of Togo, the authors of the study estimated the impact of FISP on beneficiary households&rsquo; output from maize production. The results show that FISP augmented household annual maize income by 30.8% and total household income by 13.9% for both 2016/17 and 2017/18 cropping seasons. However, even though FISP is achieving its objective of improving small-scale farmers&rsquo; income, this increment is still not large enough to take households above the poverty line, and the effects of FISP to reduce overall poverty is also limited.

scholarly journals ANALYSIS OF FOOD PRODUCTION AND POVERTY REDUCTION OF BANGLADESH

10.26458/1819 ◽  
2018 ◽  
Vol 18 (1) ◽  
pp. 191-205
Author(s):  
Haradhan Kumar MOHAJAN
Keyword(s):  
Developing Country ◽  
Food Production ◽  
Poverty Reduction ◽  
Poverty Line ◽  
Income Poverty ◽  
Healthy Life ◽  
Secondary Sources ◽  
Southern Asia ◽  
Economic Progress ◽  
The Government

This study aims to investigate the food production and poverty reduction of Bangladesh in brief. Although the country faces various problems for the economic progress since the independent in 1971, in the last forty eight years the increase of food production and poverty reduction of the country became remarkably. Bangladesh is a densely populated developing country in the southern Asia. The Government of Bangladesh is trying efficiently to reduce poverty of the country. In Bangladesh about 20% of the populations still live below the poverty line, heavily undernourished with inadequate access to safe and nutritious food for a healthy life. The data of the study were collected through the secondary sources of the country. In Bangladesh, during 2000 to 2005, income poverty reduced from 48.9% to 40.0%, 2010 to 2016 reduced from 31.50% to 20%, and in 2018 it is expected to reduce in 16%. An attempt has been taken here to show the ways to increase more food production and poverty reduction of the country.

scholarly journals Role of Internet Accessibility in Reducing the Poverty rates in Java; a Spatial Approach

2021 ◽  
Vol 9 (1) ◽  
pp. 21-31
Author(s):  
Andhy Hidayat ◽  
Ferry Prasetya ◽  
Farah Wulandari
Keyword(s):  
Poverty Reduction ◽  
Reduction Rate ◽  
Spillover Effects ◽  
Internet Infrastructure ◽  
Spatial Approach ◽  
Economic Survey ◽  
The Government ◽  
Household Heads ◽  
New Strategies

The poverty reduction rate in Java was considered very low, thus requiring new strategies and policies, such as the improvement of internet accessibility. This study, using the 2018 National Socio-Economic Survey (SUSENAS) data, aimed to examine the role of internet accessibility to reduce poverty rates in Java through a spatial approach. The results showed that internet accessibility had a significant effect on the reduction of poverty rates in Java. It also found that the poverty rates in an area in Java were influenced by the types of works of household heads in the same location and the poverty rates in neighboring areas (spatial spillover effects). This study recommended that the Government, in reducing poverty rates, focuses on providing internet infrastructure and, more, on spatial aspects.

ANALISIS GEOGRAPHICALLY WEIGHTED REGRESSION DENGAN PEMBOBOT KERNEL BI-SQUARE UNTUK ANGKA PENGANGGURAN DI KABUPATEN BOJONEGORO

2019 ◽  
Vol 2 (1) ◽  
pp. 51-59
Author(s):  
Alif Yuanita Kartini
Keyword(s):  
Regression Model ◽  
Unemployment Rate ◽  
Geographically Weighted Regression ◽  
Predictor Variable ◽  
Poverty Rate ◽  
Weighted Regression ◽  
Unemployed People ◽  
Global Regression ◽  
The Government ◽  
Gwr Model

The unemployment rate in Bojonegoro Regency has increased every year. Based on data from the Bojonegoro Regency Industry and Manpower Office (Disperinaker), at the end of June 2018 the number of unemployed people increased from the original 23,000 people to 24,000 people. It is far away from the government target to decrease this rate in the same year. The Great amount of the unemployment number is closely related to unequitable of developing program. As a result, the left areas with a great number of unemployment appears. There are several population indicators that are considered to have a great effect on the unemployment rate. Due to of those indicators, it is urgently needed to analyze the correlation between they did the analysis of correlation those factors toward poverty rate in Bojonegoro regency. Unfortunately, unemployment is spatial matter which there is correlation between unemployment rate and used predictor variable is not constant for all districts in Bojonegoro regency. That situation commonly becomes a problem in analyzing especially when applied global regression. Dealing with the problem, the researcher intended to analyze by applying Geographically Weighted Regression (GRW) method by applying Kernel Bi-square. The result shows that global regression model is able to explain variation of data is about 69,8%, but the use of regression model is not able to fulfil residual assumption. It appears heterokedasticity which shows that various residual model regression is not constant. Those problems can be solved by applying GWR which it is chosen by the center of Bojonegoro district. GWR model approved that it has better result than the previous one because it is able to explain variation and it is better in explaining the variation, it is about 72,11%.    Angka pengangguran di Kabupaten Bojonegoro dari tahun ke tahun semakin meningkat. Berdasarkan data dari Dinas Perindustrian dan Tenaga Kerja (Disperinaker) Kabupaten Bojonegoro, pada akhir Juni 2018 jumlah pengangguran semakin meningkat dari semula 23.000 orang menjadi 24.000 orang. Kondisi tersebut masih jauh dari target pemerintah untuk menurunkan angka pengangguran pada tahun 2018. Tingginya angka pengangguran tersebut tidak terlepas dari adanya ketidakmerataan pembangunan, sehingga memunculkan daerah tertinggal dengan angka pengangguran yang tinggi. Ada beberapa indikator kependudukan yang dianggap berpengaruh besar terhadap tingkat pengangguran, oleh karena itu ingin dilakukan analisa hubungan antara indikator kependudukan terhadap angka kemiskinan di Kabupaten Bojonegoro. Namun pengangguran merupakan suatu permasalahan spasial, dimana hubungan antara angka pengangguran dengan variabel prediktor yang digunakan tidak konstan (non-stationer) untuk seluruh Kecamatan di Kabupaten Bojonegoro. Kondisi tersebut seringkali menjadi masalah pada analisa ketika menggunakan regresi global. Oleh karena itu ingin dibandingkan jika dilakukan analisa menggunakan metode Geographically Weighted Regression(GWR) dengan Pembobot Kernel Bi-Square. Hasil model regresi global yang diperoleh mampu menerangkan keragaman data sebesar 69,8%, namun penggunaan regresi global tersebut tidak mampu memenuhi asumsi residual yaitu terjadi heterokedasticity yang menunjukkan bahwa varians dari residual model regresi global masih belum konstan. Permasalahan tersebut dapat diselesaikan dengan menggunakan GWR, dimana model GWR yang dipilih adalah model dengan pusat Kecamatan Bojonegoro. Model GWR yang diperoleh terbukti lebih baik karena mampu menerangkan keragaman dengan lebih baik yaitu sebesar 72,11%.

scholarly journals Non-Stationary Modeling of Microlevel Road-Curve Crash Frequency with Geographically Weighted Regression

2021 ◽  
Vol 10 (5) ◽  
pp. 286
Author(s):  
Ce Wang ◽  
Shuo Li ◽  
Jie Shan
Keyword(s):  
Geographically Weighted Regression ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Random Parameter ◽  
Information Criterion ◽  
Weighted Regression ◽  
Spatial Methods ◽  
Spatial Approach ◽  
Binomial Regression ◽  
Superior Approach

Vehicle crashes on roads are caused by many factors. However, the influence of these factors is not necessarily homogenous across locations, which is a challenge for non-stationary modeling approaches. To address this problem, this paper adopts two types of methods allowing parameters to fluctuate among observations, that is, the random parameter approach and the geographically weighted regression (GWR) approach. With road curvature, curve length, pavement friction, and traffic volume as independent variables, vehicle crash frequencies are modeled by two non-spatial methods, including the negative binomial (NB) model and random parameter negative binomial (RPNB), as well as three spatial methods (GWR approach). These models are calibrated in microlevel using a dataset of 9415 horizontal curve segments with a total length of 1545 kilometers for a period of three years (2016–2018) over the State of Indiana. The results revealed that the GWR approach can capture spatial heterogeneity and therefore significantly outperforms the conventional non-spatial approach. Based on the Akaike Information Criterion (AICc), geographically weighted negative binomial regression (GWNBR) was proved to be a superior approach for statewide microlevel crash analysis.

scholarly journals Use of Geographically Weighted Regression (GWR) Method to Estimate the Effects of Location Attributes on the Residential Property Values

2017 ◽  
Vol 49 (1) ◽  
pp. 97 ◽  
Author(s):  
Mohd Faris Dziauddin ◽  
Zulkefli Idris
Keyword(s):  
Geographically Weighted Regression ◽  
Geographical Area ◽  
Property Values ◽  
Weighted Regression ◽  
Residential Property ◽  
Spatial Effects ◽  
Kuala Lumpur ◽  
Global Parameter ◽  
Residential Property Values ◽  
The Government

This study estimates the effect of locational attributes on residential property values in Kuala Lumpur, Malaysia. Geographically weighted regression (GWR) enables the use of the local parameter rather than the global parameter to be estimated, with the results presented in map form. The results of this study reveal that residential property values are mainly determined by the property’s physical (structural) attributes, but proximity to locational attributes also contributes marginally. The use of GWR in this study is considered a better approach than other methods to examine the effect of locational attributes on residential property values. GWR has the capability to produce meaningful results in which different locational attributes have differential spatial effects across a geographical area on residential property values. This method has the ability to determine the factors on which premiums depend, and in turn it can assist the government in taxation matters.

scholarly journals The Impact of Suramadu Bridge on Rural Poverty in Kabupaten Bangkalan, East Java, Indonesia

2020 ◽  
Author(s):  
C. Henry Kusumas Karyadinata ◽  
M. Pudjihardjo . ◽  
Asfi Manzilati ◽  
Wildan Syafitri
Keyword(s):  
Rural Area ◽  
Poverty Reduction ◽  
Negative Impact ◽  
Natural Capital ◽  
Rural Poverty ◽  
Physical Capital ◽  
Poverty Level ◽  
Limited Mobility ◽  
The Government ◽  
The Impact

Poverty can be found in a developing country especially in the rural area, including Kabupaten Bangkalan, East Java, Indonesia. One of the reasons is the limited mobility and accessibility. To overcome this problem, the government has built the Suramadu bridge which connects Kabupaten Bangkalan in Madura island with Kota Surabaya in Java Island so that the mobility and accessibility in both areas can be better. This study aims at measuring how big the impact of Suramadu bridge development on rural poverty in Kabupaten Bangkalan, using village potential data in 2007 and 2017 by Badan Pusat Statistik (Central Agency of Statistic). The dependent variable is the amount of poor population and the independent variable consists of physical capital, human capital, natural capital and financial capital which analyzed by using OLS. Suramadu bridge has negative impact on poverty which means after the Suramadu bridge operates, the poverty level in rural area is decreased. Before the Suramadu bridge operates, it was only natural capital that gives impact on poverty while after the Suramadu bridge operates, all of the independent variables give an impact on poverty reduction. The existence of Suramadu bridge can ease the government on issuing the poverty reduction policy in rural area. Keywords: Poverty, Infrastructure, Village, Regional

scholarly journals PENGUKURAN PENGARUH BELANJA DESA TERHADAP KINERJA PEMBANGUNAN DESA DENGAN MENGGUNAKAN GEOGRAPHICALLY WEIGHTED REGRESSION

2018 ◽  
Vol 20 (1) ◽  
pp. 23
Author(s):  
Eka Purna Yudha ◽  
Bambang Juanda ◽  
Lala M Kolopaking ◽  
Rilus A Kinseng
Keyword(s):  
Rural Communities ◽  
Asset Management ◽  
Rural Areas ◽  
Geographically Weighted Regression ◽  
Financial Management ◽  
Economic Conditions ◽  
Weighted Regression ◽  
The Government ◽  
Gwr Model ◽  
The Village

In 2014, the Government enacted Law No. 6/2014 on Villages with a view to reconstructing village financial and asset management arrangements to accelerate the inclusive and sustainable development of rural areas. The purpose of this study is to analyze the influence of village financial management on the performance of rural development. The study was conducted on 326 Villages in Pandeglang District. The analytical tool of the study using Geographically Weighted Regression (GWR) modeling will look at how the village expenditure is included in the Village Revenue and Expenditure Budget (APBDes). Expenditure of development (infrastructure) of the village has the greatest impact on the performance of village development with the value of elasticity of 0.637. The influence of village expenditure on the GWR model is strongly influenced by the geographical, demographic, and socio-economic conditions of rural communities, resulting in varying outcomes in each village.

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