scholarly journals Model Regresi Data Panel Pada Kasus Infeksi Saluran Pernapasan Akut (ISPA) di Provinsi Nusa Tenggara Timur

2021 ◽  
pp. 49-56
Author(s):  
Indah Magfirrah Jamaludin ◽  
Astri Atti ◽  
Maria A. Kleden
Keyword(s):  
Exclusive Breastfeeding ◽  
Random Effect ◽  
Coefficient Of Determination ◽  
Response Variable ◽  
Independent Variables ◽  
Panel Data Regression ◽  
Data Regression ◽  
Number Of Patients ◽  
Outlier Data ◽  
Random Effect Models

Acute respiratory infection (ARI) is an infectious desease cause by bacteria or viruses that attack the respiratory organs. This research aims to determine the best panel data regression model in the case of the factors that influence the number of patients with ARI in East Nusa Tenggara Province from 2014 to 2018. Response variable used is the number of ARI patients. Independent variables were observed among others, low birth weight, malnutrition, immunization, exclusive breastfeeding, and vitamin A in 22 districts or city in East Nusa Tenggara. The results showed that the Random Effect Models eliminate outlier data on response variable is a model that can describe the influence of independent variables on the number of patients with ARI in East Nusa Tenggara Province from 2014 to 2018. Variables that influence of ARI are malnutrition and exclusive breastfeeding with a coefficient of determination (R) of 9,2%.

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 Analysis of the Effect of Unemployment Rate, RMW, and HDI on Poverty Rates in the Special Region of Yogyakarta

2021 ◽  
Vol 5 (2) ◽  
pp. Layouting
Author(s):  
Yolanda Oktaviani ◽  
Indanazulfa Qurrota A'yun
Keyword(s):  
Minimum Wage ◽  
Unemployment Rate ◽  
Random Effect ◽  
Poverty Rate ◽  
Poverty Level ◽  
Panel Data Regression ◽  
Data Regression ◽  
The City ◽  
Random Effect Models ◽  
Special Region

Poverty is one of the most complex problems in a country's economy, including in a region. Therefore, efforts to reduce poverty must be carried out comprehensively. The purpose of this study was to analyze the effect of the unemployment rate, the Regional Minimum Wage (RMW), and the Human Development Index (IPM) on the poverty rate in the districts of Bantul, Sleman, Gunung Kidul, Kulon Progo, and the City of Yogyakarta in 2015-2019. The analytical method used is panel data regression random effect models (REM). This study indicates that the unemployment rate, regional minimum wage, and HDI simultaneously affect the poverty level. Partially, the unemployment rate is positively and not significantly correlated with the poverty rate.

Capital Structure and Earnings per Share: An Empirical Analysis of Indian Corporate Sector

2015 ◽  
Vol 5 (3) ◽  
Author(s):  
Harvinder Singh Mand ◽  
Manjit Singh
Keyword(s):  
Capital Structure ◽  
Empirical Analysis ◽  
Corporate Sector ◽  
Independent Variables ◽  
Earnings Per Share ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Impact ◽  
The Relationship ◽  
The Empirical Analysis

This paper intends to measure the impact of capital structure on EPS (earnings per share) in Indian corporate sector. Fifteen control variables along with capital structure have been selected to know their impact on EPS. Panel data regression has been applied to establish the relationship among dependent and independent variables. It is found from the empirical analysis that the relation of capital structure with EPS has been statistically insignificant in Indian corporate sector among all specific industries except telecommunication industry. The results are consistent with Modigliani-Miller approach.

Tingkat Kemiskinan di Sumatra Selatan dan Analisisnya

2020 ◽  
Vol 8 (2) ◽  
pp. 127-133
Author(s):  
Doni Putra ◽  
Rifki Khoirudin
Keyword(s):  
Research Method ◽  
Random Effect ◽  
Random Effect Model ◽  
Poverty Rate ◽  
Variable Number ◽  
Regression Method ◽  
Poverty Level ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

This study aims to determine the factors that affect the poverty rate of regencies / cities in South Sumatra Province in 2011 to 2017. In this study the factors that affect poverty rates are related to unemployment, HDI, MSE, and population. The research method used is the panel data regression method using the help of Eviews software. The final thanks is the Random Effect Model. The results of this study are the variable Number of Population has a significant effect on the level of poverty in the District / City in South Sumatra Province. However, the Unemployment Rate Variable, HDI, and UMK were not significant to the poverty level in the regencies / cities in South Sumatra Province.

scholarly journals ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PERTUMBUHAN EKONOMI DI OKI

2020 ◽  
Vol 7 (6) ◽  
pp. 1128
Author(s):  
Wheni Yeisa ◽  
Lina Nugraha Rani
Keyword(s):  
Economic Growth ◽  
Regression Analysis ◽  
International Trade ◽  
Panel Data ◽  
Labour Force ◽  
Estimation Model ◽  
Independent Variables ◽  
Panel Data Regression ◽  
Data Regression ◽  
Effect Estimation

Economic growth is an indicator that plays an important role in determining the prosperity of a country. This study aims to analyze the effect of labour force, international trade, and inflation towards economic growth in OIC countries over the period 2007 to 2018. Panel data regression analysis approach was adopted to analyze the effect of independent variables on the dependent variable. The results of the fixed effect estimation model found that all variables simultaneously had a significant effect on economic growth. Partially, labour force and internasional trade have a significant effect, while inflation has no significant effect on economic growth. The results of this study can be used as a reference and evaluation materials for policy makers.Keywords: Labour Force, International Trade, Inflation, Economic Growth, Organizations of Islamic Cooperation

scholarly journals DIVERSIFIKASI EKSPOR NON MIGAS INDONESIA KE PASAR NON TRADISIONAL

2020 ◽  
Vol 14 (2) ◽  
pp. 215-238
Author(s):  
Hotsawadi Harahap ◽  
Widyastutik
Keyword(s):  
United Arab Emirates ◽  
Oil And Gas ◽  
Random Effect ◽  
Random Effect Model ◽  
Structural Match ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Oil Exports

Abstrak Penelitian ini bertujuan untuk menganalisis diversifikasi ekspor non migas Indonesia ke pasar non tradisional. Metode penelitian yang digunakan adalah analisis statistik deskriptif dengan pendekatan pengelompokan (clustering), Structural Match Index dan Demand Index, serta regresi data panel. Hasil penelitian menunjukkan bahwa negara yang diidentifikasikan sebagai negara non tradisional potensial adalah Brazil, Pantai Gading, Mesir, Georgia, Jamaica, Kazakhstan, Kuwait, Myanmar, Nigeria, Norway, Oman, Pakistan, Russian Federation, Trinidad and Tobago, Turkey, United Arab Emirates, dan Uruguay. Hasil regresi data panel menunjukkan bahwa Random Effect Model merupakan model yang terbaik untuk menjelaskan faktor-faktor yang memengaruhi ekspor non migas Indonesia ke negara non tradisional. Hasil regresi menunjukkan bahwa GDP riil negara tujuan, populasi negara tujuan, nilai tukar riil, FDI dan kualitas pelabuhan Indonesia berpengaruh signifikan secara statistik terhadap ekspor non migas Indonesia ke negara non tradisional potensial tersebut. Beberapa rekomendasi kebijakan yang perlu dilakukan untuk meningkatkan ekspor non migas ke negara tujuan non tradisional diantaranya perlu dilakukan intelejen pasar mengenai kebutuhan dan selera dari masing-masing negara non tradisional atas produk Indonesia, peningkatan kualitas pelabuhan Indonesia dan kebijakan tambahan yang memberikan insentif untuk menarik Foreign Direct Investment ke Indonesia. Kata Kunci: Diversifikasi Ekspor, Demand Index, Non traditional, Random Effect Model, Structural Match Index   Abstract This study aims to analyze the diversification of Indonesia's non-oil and gas exports to non-traditional markets. The research method used is descriptive statistical analysis with a clustering approach, Structural Match Index and demand index, and panel data regression. The results showed that countries identified as potential non-traditional countries were Brazil, Ivory Coast, Egypt, Georgia, Jamaica, Kazakhstan, Kuwait, Myanmar, Nigeria, Norway, Oman, Pakistan, Russian Federation, Trinidad and Tobago, Turkey, United Arab Emirates, and Uruguay. The panel data regression results show that the random effect model is the best model to explain the factors that influence Indonesia's non-oil exports to non-traditional countries. The results show that the real GDP of the destination country, the population of the destination country, the real exchange rate, FDI and the quality of Indonesia's ports have a statistically significant effect on Indonesia's non-oil exports to these potential non-traditional countries. Then, in this study there are several policy recommendations that need to be done to increase non-oil and gas exports to non-traditional destination countries including market intelligence regarding the needs and tastes of each non-traditional country for Indonesian products, improving the quality of Indonesian ports and additional policies that provide incentives to attract Foreign Direct Investment to Indonesia. Keywords:  Export Diversification, Demand Index, Non-traditional, Random Effect Model, Structural Match Index JEL Classifications: F13, F15, F18

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 PENGARUH BI RATE DAN KINERJA KEUANGAN BANK TERHADAP PEMBIAYAAN BANK SYARIAH DI INDONESIA (2010 - 2017)

2019 ◽  
Vol 3 (3) ◽  
pp. 376-385
Author(s):  
Didit Suprayitno ◽  
Idah Zuhroh ◽  
M.Faisal Abdullah
Keyword(s):  
Secondary Data ◽  
Capital Adequacy ◽  
Third Party ◽  
Coefficient Of Determination ◽  
Analysis Techniques ◽  
Independent Variables ◽  
Significant Negative Effect ◽  
Panel Data Regression ◽  
Capital Adequacy Ratio ◽  
Negative Effect

This study aims to analyze the influence of the independent variables, namely the BI Rate, Third Party Funds (DPK), Capitalization of Adequacy Ratio (CAR) and Operational Income Costs (BOPO) on Islamic bank financing in Indonesia 2010 - 2017. This type of research is Quantitative Inferential . The required data is secondary data from the financial statements of five Islamic banks in Indonesia 2010-2017.4. Data analysis techniques are panel data regression analysis techniques. The results of the study show that the BI Rate variable has a significant negative effect on financing, Third Party Funds (TPF) have a significant positive relationship to financing, while for the variable Capital Adequacy Ratio (CAR) has a significant positive effect on financing and for Operational Income Operating Costs (BOPO) no significant negative effect on financing. The coefficient of determination (R ^ 2) is 0.938581 or 93.85%. This shows that the ability of the independent variables namely BI Rate, DPK, CAR and BOPO explain the dependent variable of Financing at 93.85% and the remaining 6.15% can be explained by other variables.

scholarly journals Bank Specific and Macroeconomic Determinants of Bank Profitability

2016 ◽  
Vol 3 (2) ◽  
pp. 14-18
Author(s):  
Muhammad Ehsan Javaid
Keyword(s):  
Panel Data ◽  
Significant Relationship ◽  
Commercial Banks ◽  
Banking Sector ◽  
Random Effect ◽  
Macroeconomic Factors ◽  
Customer Base ◽  
Panel Data Regression ◽  
Data Regression ◽  
Macroeconomic Determinants

This study investigated the profitability of the banking sector in Pakistan. It evaluated the effects of both internal (bank-specific) and external (macroeconomic) factors on bank’s profitability from 2006 to 2013 period. The data of 34 commercial banks operating in Pakistan has collected. The data was balanced panel data and analyzed by random effect panel data regression analysis. Results confirmed that bank size and non-interest income had positive significant relationship on banking profitability. Deposit had negative significant relationship with banking profitability because of maintaining high liquidity, which increased cost of holding asset that ultimately, decrease profitability. As major participant, banks of Pakistan banking sector were small size banks so most important factor out of significant factors were income from non-interest facilities provided by these commercial banks. By increasing such facilities increased the bank’s customer base, which ultimately increased bank’s profitability. Macro-economic factors showed no significant effect on bank’s profitability.

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