scholarly journals Faktor-Faktor Yang Mempengaruhi Profitabilitas Perbankan Indonesia (Factors Affecting the Profitability of Indonesian Banking)

2021 ◽  
Vol 28 (2) ◽  
pp. 1
Author(s):  
Intan Anjeli Renta ◽  
Juliana Kadang
Keyword(s):  
Panel Data ◽  
Credit Risk ◽  
Fixed Effect Model ◽  
Operational Efficiency ◽  
Factors Affecting ◽  
Effect Model ◽  
Panel Data Regression ◽  
Analysis Technique ◽  
Data Regression ◽  
Model Approach

This study aims to analize the factors that affect the profitability of banks at state-owned banks and private foreign exchange banks listed on the IDX in 2015-2019. The factors used are liquidity, capital, credit risk, and operational efficiency. The analysis technique used is panel data regression with the Fixed Effect Model approach. The results showed that simultaneously liquidity, capital, credit risk and operational efficiency had a significant effect on profitability. then partially liquidity and capital do not have a significant effect on profitability, while credit risk and operational efficiency have a significant effect on profitability.

scholarly journals Implementasi Surat Keterangan Tidak Dipungut Atas Impor Kapal (Implementation of Certificate Not Collected on Ship Import)

2021 ◽  
Vol 28 (2) ◽  
pp. 11
Author(s):  
Rodo Gokmatua Sidabalok ◽  
Suparna Wijaya
Keyword(s):  
Panel Data ◽  
Credit Risk ◽  
Foreign Exchange ◽  
Fixed Effect Model ◽  
Operational Efficiency ◽  
Effect Model ◽  
Panel Data Regression ◽  
Analysis Technique ◽  
Data Regression ◽  
Model Approach

This study aims to analize the factors that affect the profitability of banks at state-owned banks and private foreign exchange banks listed on the IDX in 2015-2019. The factors used are liquidity, capital, credit risk, and operational efficiency. The analysis technique used is panel data regression with the Fixed Effect Model approach. The results showed that simultaneously liquidity, capital, credit risk and operational efficiency had a significant effect on profitability. then partially liquidity and capital do not have a significant effect on profitability, while credit risk and operational efficiency have a significant effect on profitability.

scholarly journals Analisis Faktor-Faktor yang Mempengaruhi Jumlah Penduduk di Kota Semarang Menggunakan Metode Regresi Data Panel

2019 ◽  
Vol 12 (2) ◽  
pp. 36-41
Author(s):  
Prizka rismawati Arum
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Geographical Area ◽  
Random Effect Model ◽  
Factors Affecting ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Relationship ◽  
Number Of Births

Residents are all people who live in the geographical area of Indonesia for six months or more and or those who have been domiciled for less than six months but aim to settle. Population growth is caused by two components, namely: fertility and mortality. To find out how big the relationship between the  population and the number of births and deaths in each sub-district of Semarang, must observed in several specific time periods and places at once. So in this study, the panel data regression method was used. In panel data regression testing, the results show that the panel data regression model formed to determine the factors that influence the level of population is the random effect model. In this model all assumptions are fulfilled. Significant factors affecting population are number of births. Births and deaths affect the population of 99.95% and the remaining 0.05% is influenced by other factors not examined Penduduk adalah semua orang yang berdomisili di wilayah geografis Indonesia selama enam bulan atau lebih dan atau mereka yang berdomisili kurang dari enam bulan tetapi bertujuan menetap. Pertumbuhan penduduk diakibatkan oleh dua komponen yaitu: fertilitas dan mortalitas. Untuk mengetahui seberapa besar keterkaitan antara jumlah penduduk dengan jumlah kelahiran dan kematian di setiap kecamataan Kota Semarang, harus diamati dalam beberapa periode waktu tertentu dan beberapa tempat secara bersamaan. Sehingga dalam penelitian ini digunakan metode regresi data panel. Dalam pengujian regresi data panel, didapatkan hasil bahwa Model regresi data panel yang terbentuk untuk mengetahui faktor-faktor yang mempengaruhi tingkat jumlah penduduk adalah model random Effect. Pada model tersebut semua asumsi terpenuhi. Faktor yang signifikan mempengaruhi jumlah penduduk adalah jumlah kelahiran. Kelahiran dan kematian mempengaruhi jumlah penduduk sebesar 99.95% dan sisanya sebesar 0.05% dipengaruhi oleh faktor- faktor lain yang tidak di teliti.    

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

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

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.

scholarly journals PENGARUH TINDAK KORUPSI TERHADAP KEMISKINAN DI NEGARA-NEGARA ASIA TENGGARA DENGAN MODEL PANEL DATA

2020 ◽  
Vol 4 (2) ◽  
pp. 311-320
Author(s):  
Aditya Firman Baktiar ◽  
Herpanindra Fadhilah ◽  
Margareth Dwiyanti Simatupang ◽  
Mula Warman ◽  
Salsa Vira ◽  
...  
Keyword(s):  
Panel Data ◽  
Southeast Asia ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
The World ◽  
Data Source ◽  
High Level

Poverty is still being an issue all over the world. It also happens in Southeast Asia that mostly consists of developing countries that identic with high poverty rates. Countries in the world have tried to eradicate the problem of poverty, it's just that it can be hampered due to the high level of corruption. This study aims to look at suitable models and the relationship between corruption and poverty. The data source in this study is secondary data from ten countries in Southeast Asia from 2015 to 2018. Analysis of the data used in this study is panel data. The result obtained is a panel data regression model that is more suitable for modeling the effect of corruption on poverty in Southeast Asian countries is a fixed effect model. Based on the model, the corruption represented by Corruption Perception Index (CPI) and the poverty represented by Human Development Index (HDI) is directly proportional which means every increase in one unit of CPI will also increase the HDI score by 0.001443 unit.

scholarly journals PERTUMBUHAN EKONOMI, DISPARITAS PENDAPATAN DAN KESEJAHTERAAN KABUPATEN/KOTA DI PROVINSI NUSA TENGGARA BARAT

GANEC SWARA ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 59
Author(s):  
BAIQ HIPZIWATY ◽  
PUTU KARISMAWAN ◽  
BAIQ ISMIWATY
Keyword(s):  
Economic Growth ◽  
Regression Analysis ◽  
Panel Data ◽  
Secondary Data ◽  
Fixed Effect Model ◽  
Income Disparity ◽  
The People ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

This study aims to analyze economic growth, income disparity and community welfare in the West Nusa Tenggara Province.     This research is a descriptive study using secondary data obtained from relevant agencies in the form of GRDP data, population, economic growth, HDI and per capita income between regencies / cities in NTB Province and data collection using the case method. With analytical procedures using Williamson index and panel data regression analysis.     The results showed that during the period of 2010-2016 the average economic growth of West Nusa Tenggara Province was 6.0%. The income disparity seen from the Williamson index in the 2010-2016 period is classified as a medium inequality criterion. The estimation results of the relationship between the variables of economic growth, income disparity and the welfare of the people of West Nusa Tenggara Province measured using HDI in 2010-2016 using panel data regression analysis with the Fixed Effect model (FEM), found that economic growth variables were positively related, but not significant to welfare society. The variable income disparity is significantly related to the welfare of the people of NTB Province.

scholarly journals Profitability Condition With Stylized Fact of Banking Industries in Indonesia, Malaysia and Thailand

2020 ◽  
Vol 5 (2) ◽  
pp. 15
Author(s):  
Helma Malini
Keyword(s):  
Exchange Rates ◽  
Interest Rates ◽  
Fixed Effect Model ◽  
Capital Adequacy ◽  
Return On Assets ◽  
Factors Affecting ◽  
Independent Variables ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

<p><em>The survival of banking industries are determined by many factor including profitability earn during the years. Therefore, this study investigates factors affecting profitability of banks in ASEAN. This study uses 10 banks with the largest assets in Indonesia, Malaysia and Thailand with sample studies of 30 banks in ASEAN with 10 years of operationalization duration. Return on assets (ROA) is the dependent variable and the independent variables used are non-performing loans (NPL), capital adequacy ratios (CAR), total assets (Size), loan-to-deposit ratio (LDR), domestic product growth gross (GDP growth), inflation, interest rates and exchange rates. </em></p><em>Data is processed using panel data regression with the Cochrance Orcutt method on the basis of the Common and Fixed Effect Model with the combination of stylized facts among each countries. The final results of this study are varied among countries. In Indonesia only NPLs have a significant significance of ROA, which is a significant negative. In Malaysia, only the exchange rate is significant to ROA, which is a significant negative. In Thailand, only NPI has a significant effect on ROA, which is a significant negative. Overall in Southeast Asia, only NPLs, interest rates and exchange rates significantly affect ROA, which is a significant negative. In other independent variables, it does not have a significant effect on ROA.</em>

scholarly journals APLIKASI REGRESI DATA PANEL DENGAN PENDEKATAN FIXED EFFECT MODEL (STUDI KASUS: PT PLN GIANYAR)

2014 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
NI PUTU ANIK MAS RATNASARI ◽  
I PUTU EKA NILA KENCANA ◽  
G.K. GANDHIADI
Keyword(s):  
Panel Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Dummy Variable ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Panel data regression has three approaches. One of these approaches is Fixed Effect Model (FEM). FEM is common estimated using Least Square Dummy Variable. The use of dummy variable in FEM is based on assumption that slope coefficients are constant but intercept varies over individuals. One of application of FEM is to find out motivation of employees at PT PLN Gianyar for non-outsourcing and outsourcing employees based on existence, relatedness, and growth. This research yields the following two models:with 67% motivation non-outsourcing employees represented by existenceand73% motivation non-outsourcing employees represented by existence and growth.

Sign in / Sign up

Export Citation Format

Share Document