Analisis Pengaruh Dana Desa, Alokasi Dana Desa dan Pendapatan Asli Desa terhadap Jumlah Penduduk Miskin Desa di Kabupaten Tuban

2021 ◽  
Vol 4 (2) ◽  
pp. 238-250
Author(s):  
Tanti Auliya Agustina ◽  
Muchtolifah Muchtolifah ◽  
Sishadiyati Sishadiyati
Keyword(s):  
Panel Data ◽  
Fixed Effect Model ◽  
Coefficient Of Determination ◽  
Poor People ◽  
Analysis Tool ◽  
Rural Poor ◽  
Fund Allocation ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Village

This study aims to analyse the difference in the Number of rural poor people in Tuban Regency between 2019 and 2020 to examine the effect of the Village Fund, Allocation of village funds (ADD) and Village original income on the Number of rural poor people in Tuban Regency in 2019-2020. The analysis tool used is panel data regression which is testing the hypothesis with the F test, t test and Coefficient of Determination (R2) at an error rate of = 5%. The results of panel data regression analysis with the selected model is the Fixed Effect Model showing that there is a difference in the Number of rural poor people in Tuban Regency between 2019 and 2020, the variables used in the model, namely the Village Fund, Allocation of village funds (ADD) and Village original income are able to explain the variation of the variable Number of rural poor by 85% and 15% are influenced by other factors that are not included in the research variables. Keywords: Village Fund, Allocation of village funds (ADD) and Village original income

Dana pihak ketiga, Inflasi dan Pembiayaan Mudharabah terhadap Non Performing Financing pada Bank Islam di Indonesia dan Malaysia

2019 ◽  
Vol 16 (2) ◽  
pp. 74-80
Author(s):  
Afrillia Tiara Putri ◽  
Saadah Yuliana ◽  
Anna Yulianita
Keyword(s):  
Panel Data ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Third Party ◽  
Coefficient Of Determination ◽  
Islamic Banks ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Negative Effect

This study aimed to analyze the influence of third party funds, inflation, and mudharabah against non performing financing on Islamic Banks in Indonesia and Malaysia. Data used is secondary data. The method used in this analysis is the panel data regression. The results showed that in partial third party fund and mudharabah significant negative effect on the Non Performing Financing, while inflation is positive and not significant to the Non Performing Financing. Variable Third Party Funds, Inflation and mudharabah jointly significant effect on Non Performing Financing. Based on the regression equation fixed effect model results show the results of the coefficient of determination (R2) is 0.369198, or 36.91 per cent means that the variation of the variable third party funds, inflation and mudharabah have an influence on the non performing financing for the coefficient of determination, while the rest 63.09 percent influenced by variables outside the model

Analisis Tingkat Kesenjangan Pendapatan antar Provinsi di Indonesia Menggunakan Regresi Data Panel Model Pengaruh Tetap

2019 ◽  
Vol 7 (3) ◽  
Author(s):  
Thooriq Ghaith ◽  
Hari Wijayanto ◽  
Anang Kurnia
Keyword(s):  
Panel Data ◽  
Fixed Effect Model ◽  
Poor People ◽  
Income Disparity ◽  
Explanatory Variables ◽  
Income Disparities ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Using Data

THOORIQ GHAITH. Analysis of Income Disparity Rates among Provinces in Indonesia Using Panel Data Regression. Supervised by HARI WIJAYANTO and ANANG KURNIA.   Income disparities in Indonesia generally and in each province particularly is a serious problem from year to year. It is necessary to find out the factors that affect the income disparity rates (Gini ratio) to be taken into consideration in determining the economic policy. By using data of 33 provinces from 2007 until 2016, panel data regression with provincial fixed effect model approach was used to determine factors that affect Gini ratios in Indonesia and to capture the differences of Gini ratio characteristics of each province in form of intercept. Modeling was done for whole Indonesia and for five regions as well to find out what factors that affect the Gini ratio of provinces in Indonesia generally and what factors affect Gini ratios of provinces in each region particularly. The percentage of poor people is a significant factor to Gini ratio in the model throughout Indonesia and in the model of each region, except in Sumatera. Beside the percentage of the poor people, other explanatory variables affecting Gini ratios are GDP growth rates in Kalimantan, open unemployment rates in Sulawesi, and provincial minimum wage in Nusa Tenggara, Maluku and Papua. All of the predicted models are good enough because they produce MAPE values below 10%.

scholarly journals Analisis Elastisitas Produksi Padi Di Provinsi Jawa Timur Tahun 2007-2015

2020 ◽  
Vol 4 (1) ◽  
pp. 56-69
Author(s):  
Pradityo Fahril Arrahman ◽  
Idah Zuhroh
Keyword(s):  
Panel Data ◽  
Agricultural Sector ◽  
Agricultural Land ◽  
Fixed Effect Model ◽  
Rice Production ◽  
Coefficient Of Determination ◽  
Land Area ◽  
A Value ◽  
Panel Data Regression ◽  
Data Regression

The purpose of this study is (1) to find out how the effect of land area and labor of the agricultural sector on rice production in East Java Districts and (2) to find out how the differences between productivity strata are related to the influence of agricultural land area and labor on rice production in Districts in East Java Province. The analytical tool used is panel data regression which is then tested by hypothesis F test, t test and coefficient of determination (R2) at the error rate α = 5%. The results of panel data regression with the selected model are Fixed Effect Model showing that the area of land has a positive and not significant effect on rice production with a value of 0.08 and labor has a significant negative effect on rice production with a value of -0.31. While the coefficient of determination (R2) is 0.94 or 94%. Conclusion for East Java, the highest production strata, medium production strata and low strata production coefficient values of land area and labor variables show less than 1, which means inelastic to rice production.

scholarly journals ANALISIS INTERVENSI FISKAL TERHADAP KEMISKINAN (STUDI KASUS DANA DESA PULAU KALIMANTAN)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
M. Zaky Mubarak Lubis ◽  
Aprian Subhan Dahraini
Keyword(s):  
Panel Data ◽  
Data Model ◽  
Fixed Effect Model ◽  
Poverty Rate ◽  
Panel Data Model ◽  
Fund Allocation ◽  
Effect Model ◽  
Descriptive Approach ◽  
Quantitative Descriptive ◽  
The Village

ABSTRACTOne of the government's strategies to help the village become independent and autonomous by giving the allocation of village funds. The funds allocated for the rural area, and expected to support the implementation of the people’s empowerment and the rural development, so that funds can improve the people’s prosperity. Furthermore, the aims of this study to look at the influence of Fiscal Intervention which are representated by Village Fund, Village Fund Allocation, and part of Local Earning and Retribution toward Poverty which is representated by Poverty Rate of Residences/Cities in Kalimantan Island during 2015-2017. This research used quantitative descriptive approach with Panel Data Model. The result showed of Fixed Effect Model regression that, Village Fund, Village Fund Allocation, and part of Local Earning and Retribution have have negative significant influence at Poverty Rate for 47 Residences/Cities in Kalimantan Island.

scholarly journals ANALISIS FAKTOR YANG MEMPENGARUHI PRODUKSI TEBU PADA SUB SEKTOR PERKEBUNAN DI PROVINSI JAWA TIMUR TAHUN 2011-2015

2017 ◽  
Vol 15 (2) ◽  
pp. 193
Author(s):  
Moch. Arif Dausin Nazula Achadin
Keyword(s):  
Random Effect ◽  
Random Effect Model ◽  
Coefficient Of Determination ◽  
Analysis Tool ◽  
Land Area ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Production Value ◽  
Plantation Labor

The goal of this research is to know the influence of the land area and the amount of sugar cane plantation labor in the plantation in East Java province year 2011-2015 and analysis whether there is a difference between production of Kabupaten/Kota cane producer on a plantation in East Java province year 2011-2015. Analysis tool used is a panel data regression then do hypothesis testing with F-test, t-test, and the coefficient of Determination () on error rate α = 5%.The results of the regression analysis of the data panel with the selected model is a Random Effect Model showed that the land area of influential labor and significantly to the amount of production value of each 0.97 to land area and 0.04 for amount of labor. While the value of the coefficient of determination () is 0.99 or 99%, this indicates that the ability of the variable land area and the amount of labor in explaining the amount of production of 99%.

scholarly journals ANALISIS FAKTOR YANG MEMPENGARUHI PRODUKSI TEBU PADA SUB SEKTOR PERKEBUNAN DI PROVINSI JAWA TIMUR TAHUN 2011-2015

2017 ◽  
Vol 15 (2) ◽  
pp. 193
Author(s):  
Moch. Arif Dausin Nazula Achadin
Keyword(s):  
Random Effect ◽  
Random Effect Model ◽  
Coefficient Of Determination ◽  
Analysis Tool ◽  
Land Area ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Production Value ◽  
Plantation Labor

The goal of this research is to know the influence of the land area and the amount of sugar cane plantation labor in the plantation in East Java province year 2011-2015 and analysis whether there is a difference between production of Kabupaten/Kota cane producer on a plantation in East Java province year 2011-2015. Analysis tool used is a panel data regression then do hypothesis testing with F-test, t-test, and the coefficient of Determination () on error rate α = 5%.The results of the regression analysis of the data panel with the selected model is a Random Effect Model showed that the land area of influential labor and significantly to the amount of production value of each 0.97 to land area and 0.04 for amount of labor. While the value of the coefficient of determination () is 0.99 or 99%, this indicates that the ability of the variable land area and the amount of labor in explaining the amount of production of 99%.

scholarly journals Analisis Regresi Panel pada Pemodelan Tingkat Kematian Bayi di Provinsi Sulawesi Selatan

2020 ◽  
Vol 2 (2) ◽  
pp. 115
Author(s):  
Syafruddin Side ◽  
S. Sukarna ◽  
Raihana Nurfitrah
Keyword(s):  
Panel Data ◽  
Infant Mortality ◽  
Regression Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Dummy Variable ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Penelitian ini membahas mengenai estimasi parameter model regresi data panel pada pemodelan tingkat kematian bayi di Provinsi Sulawesi Selatan dari tahun 2014 sampai dengan 2015. Data yang digunakan adalah data sekunder dari Dinas Kesehatan Provinsi Sulawesi Selatan yang berupa jumlah kematian bayi, berat bayi lahir rendah, persalinan yang ditolong oleh tenaga kesehatan, penduduk miskin, bayi yang diberi ASI ekslusif dan rumah tangga berperilaku bersih sehat di seluruh Kabupaten/Kota di Provinsi Sulawesi Selatan tahun 2014-2016. Analisis data dilakukan dengan menggunakan penghitungan manual dan dengan menggunakan software EViews 9. Pembahasan dimulai dari melakukan estimasi parameter model regresi data panel, menentukan model regresi data panel terbaik, , menguji asumsi model regresi data panel, pengujian signifikansi parameter dan interpretasi model regresi. Dalam penelitian ini diperoleh kesimpulan yaitu estimasi model regresi data panel terbaik dengan pendekatan fixed effect model.Kata kunci:Regresi Data Panel, Kematian Bayi, Fixed Effect Model, Least Square Dummy Variable. This research discusses about parameter estimation of panel data regression model of infant mortality level modelling in South Sulawesi from 2014 to 2015. The data used were secondary data from Dinas Kesehatan Provinsi Sulawesi Selatan in the form of number of infant mortality, low weight of infant, childbirth rescued by health workers, poor population, infants who were given exclusive breast milk and household that behaves well in the whole district/town in South Sulawesi year 2014-2016. Data analysis was performed using the calculation manually and by using EViews 9 software. The discussion started from doing parameter estimation of panel data regression model, determining the best panel data regression model, testing the assumption of panel data regression model, testing the signification of parameter and interpretation of regression model. Conclusion of this research are the estimation of regression model is the best panel data regression model with fixed effects model approach.Keywords:Panel Data Regression, Infant Mortality, Fixed Effect Model, Least Square Dummy Variable.

scholarly journals PENINGKATAN TARIF CUKAI ROKOK DAN DAMPAKNYA TERHADAP PEREKONOMIAN DAN PENDAPATAN SEKTORAL JAWA TENGAH

KINERJA ◽  
2017 ◽  
Vol 19 (2) ◽  
pp. 99
Author(s):  
Fatoni Ashar ◽  
Firmansyah ,
Keyword(s):  
Panel Data ◽  
Household Income ◽  
Fixed Effect Model ◽  
Cigarette Consumption ◽  
Input Output ◽  
Output Analysis ◽  
Central Java ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

This study analyzes the effect of excise of cigarette price changes to the consumption of cigarette and Central Java’s economy and household income. In the first stage, with employing panel data regression model,i.e. fixed effect model (FEM) which include 35 regencies/cities in Central Java Province during 2009-2013, the study examines the effect of cigarette excise to cigarette consumption. On the next stage, the study simulatesthe impact of cigarette consumption shock to the Central Java’s sectoral economy and household income using the Central Java 2013 Input-Output table. The findings indicate that the cigarette excise has a tradeoff effect tohousehold’s cigarette consumption. The increase of cigarette excise reduces cigarette consumption, and next, reduces output and sectoral household income. The cigarettes industries suffered the highest impact of thedecrease of the cigarette consumption, followed by other sectors which is has a high link to cigarette industries such as agricultures and tobacco sectors.Keywords: cigarette, excise, panel data regression, input-output analysis

scholarly journals PENGARUH DANA DESA DAN PRODUK DOMESTIK REGIONAL BRUTO (PDRB) TERHADAP TINGKAT KEMISKINAN DI PROVINSI ACEH

2022 ◽  
Vol 6 (1) ◽  
Author(s):  
Muliza Muliza
Keyword(s):  
Fixed Effect Model ◽  
Model Parameters ◽  
Infrastructure Development ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Aceh Province ◽  
Estimation Of Model Parameters ◽  
Regional Product ◽  
The Village

This study aims to see the effect of Village Fund and Gross Domestic Regional Product on poverty in districts / cities in Aceh Province during the 2017-2019 period. To analyze the data, the method used is panel data regression analysis with the estimation of model parameters using a fixed effect model (FEM). The results showed that the village funds variable did not have a significant effect on poverty, this happened because most of the village funds were allocated more to the infrastructure development sector, causing village funds to still not have a direct effect on reducing poverty. The Gross Domestic Regional Product variable has a negative but significant effect on poverty in the District / City of Aceh Province, which means that with an increase in Gross Domestic Regional Product it will significantly affect the reduction of poverty levels in Aceh Province.

scholarly journals MODEL REGRESI DATA PANEL UNTUK MENGETAHUI FAKTOR YANG MEMPENGARUHI TINGKAT KEMISKINAN DI PULAU MADURA

2020 ◽  
Vol 9 (3) ◽  
pp. 355-363
Author(s):  
Artanti Indrasetianingsih ◽  
Tutik Khalimatul Wasik
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Series Data ◽  
Poverty Level ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Poverty arises when a person or group of people is unable to meet the level of economic prosperity which is considered a minimum requirement of a certain standard of living or poverty is understood as a state of lack of money and goods to ensure survival. Panel data regression is the development of regression analysis which is a combination of time series data and cross section data. Panel data regression is usually used to make observations of data that is examined continuously for several periods. The purpose of this study is to determine the factors that influence the level of poverty in Madura Island in the period 2008 - 2017. In this study the variables used in this study are life expectancy (X1), average length of school (X2), level open unemployment (X3), and labor force participation (X4) with the Comman Effect Model (CEM) approach, Fixed Effect Model and Random Effect Model (REM). To choose the best model from the three is the chow test, the hausman test and the breusch-pagan test. In this study, the best model chosen was the Fixed Effect Model. Keywords: CEM, Fixed Effect Model, Data Panel Regression, REM, Poverty level.

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