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%.

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 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 Pengaruh Pendidikan, Pengangguran, dan Kemiskinan terhadap Ketimpangan Pendapatan di Indonesia

2019 ◽  
Vol 8 (3) ◽  
pp. 250
Author(s):  
Hindun Hindun ◽  
Ady Soejoto ◽  
Hariyati Hariyati
Keyword(s):  
Data Analysis ◽  
Income Inequality ◽  
Random Effect ◽  
Random Effect Model ◽  
Secondary Data ◽  
Ministry Of Education ◽  
Effect Model ◽  
Panel Data Regression ◽  
Analysis Technique ◽  
Data Regression

This research aims to analyze the effect of education, unemployment, and poverty on income inequality in Indonesia, both partially and simultaneously. This research uses secondary data with a quantitative approach. The type of research used is the type of associative research. The variables in this study are education, unemployment, poverty, and income inequality — data source from BPS and the Ministry of Education and Culture. The data analysis technique used is panel data regression analysis with cross-section 34 provinces and time series for 2015-2018. The results of the research obtained the random effect model, the best models. The results of data analysis show that education and poverty had a partial effect on income inequality in Indonesia, while unemployment had not to affect income inequality. Simultaneously, education, unemployment, and poverty affect income inequality in Indonesia. However, education, unemployment, and poverty can only explain 22.37% of the effect on income inequality in Indonesia. The rest is influenced by factors outside the model.

scholarly journals PENGARUH KEPEMILIKAN INSTITUSIONAL, INTELLECTUAL CAPITAL, DAN LEVERAGE TERHADAP FINANCIAL DISTRESS

2019 ◽  
Vol 2 (2) ◽  
pp. 27
Author(s):  
Saskhia Irving Maest Purba
Keyword(s):  
Intellectual Capital ◽  
Financial Distress ◽  
Stock Exchange ◽  
Random Effect ◽  
Random Effect Model ◽  
Sampling Technique ◽  
Institutional Ownership ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

The purpose of this study is to determine the influence of institutional ownership (KI), intellectual capital (IC) and Leverage (DER) to financial distress (Springate) financial distress condition. Independent variables in this study are institutional ownership (KI), intellectual capital (IC) and Leverage (DER) and financial distress (Springate) partially or simultaneously. Population in this study is Manufacture companies’s sector listed on Indonesia Stock Exchange in 2014-2017. The sampling technique was using purposive sampling, obtained 128 sample data and use Panel data regression analysis using software Eviews 10. Random effect model was chosen after 3 regression panel test. Simultaneously, all the independet variables have significant effect to dependent variable (financial distress). Partially intellectual capital (IC) have negative significant effect with to financial distress. Leverage (DER) have positive significant effect to financial distress. But institutional ownership (KI) have no significant effect to financial distress. Keyword: Financial distress, Institutional Ownership, Intellectual Capital, Leverage

scholarly journals PENGARUH CURRENT RATIO, DEBT TO EQUITY RATIO, DAN EARNING PER-SHARE TERHADAP HARGA SAHAM

2017 ◽  
Vol 11 (1) ◽  
Author(s):  
Arry Widodo ◽  
Renda Puspita Dewi
Keyword(s):  
Stock Prices ◽  
Random Effect ◽  
Random Effect Model ◽  
Secondary Data ◽  
Share Price ◽  
Current Ratio ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Equity Ratio

This study also aimed to determine the effect of Current Ratio (CR), Debt to Equity Ratio (DER), and Earning per Share (EPS) to the Price Stock either partially or simultaneously. Secondary data collected based on time series and cross section from the 2008-2012 from 26 companies Costumer Goods sector. By using panel data regression analysis techniques and the Chow test and Hausman test shows that the model used in the estimation of the data is the Random Effect Model. The results showed that the independent variables, EPS significant effect on stock prices. While CR and partially DER no significant effect on stock prices. Simultaneously, CR, DER, and EPS significant effect on stock prices. Keywords: Current Ratio, Debt to Equity Ratio, Earnings per Share, Price Stock

Corporate Diversification and Firm Value in Financial Crisis in Vietnam

2017 ◽  
Vol 33 (4) ◽  
Author(s):  
Nguyen Kim Duc ◽  
Nguyen Thi Hong Nhung ◽  
Tran Vu Quynh Nhu
Keyword(s):  
Financial Crisis ◽  
Firm Value ◽  
Random Effect ◽  
Random Effect Model ◽  
Corporate Diversification ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Industrial Level ◽  
Diversified Firms

This research aims at assessing the relationship between corporate diversification and firm value ​​in the time of financial crisis in Vietnam. The research sample consists of 42 Vietnamese non-financial enterprises listed on HoSE from the first quarter of 2008 to the fourth quarter of 2011. We used two methods to estimate panel data regression: (1) Regression Method Pooled OLS and (2) Random Effect Model (REM). The results show that: (1) There is relationship between corporate diversification and firm value, however, corporate diversification should be implemented at either national or industrial level; (2) The financial crisis doesn’t dominanate this relationship and the implementation of diversification will contribute to improving the relative valuation of diversified firms in Vietnam regardless of financial crisis. This empirical result will help Vietnamese enterprises have a reference for considering and making decision related to corporate diversification.

scholarly journals THE EFFECT OF SPIN-OFF POLICY AND MACROECONOMIC FUNDAMENTAL FACTORS ON THIRD PARTY FUNDS AT SHARIA GENERAL BANKS

2021 ◽  
Vol 5 (1) ◽  
pp. 08-22
Author(s):  
Fatima Tuzzahara Alkaf ◽  
Nana Nawasiah
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Random Effect Model ◽  
Third Party ◽  
Financial Report ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
Report Data ◽  
The Government

In enhancing the development of Islamic banking, the government issued Law No. 21 of 2008 concerning spin-off. With this policy, it is expected that Islamic Commercial Banks will develop. This study aims to implement panel data regression to examine in depth the influence of spin-off policy and macroeconomic fundamental factors on third party funds of Sharia General Banks. Sampling by purposive sampling, six (6) Sharia General Banks that have conducted spin-offs and financial report data from 2014-2018. The Chow Test and the Hausman Test show that the panel data regression model that matches the variable data used in 2014-2018 is the Random Effect Model (REM). Empirical results show that during the 2014-2018 period, the spin-off policy and macroeconomic fundamental factors had a significant effect on the bank's third-party funds simultaneously. Partially, only the spin-off policy has a significant effect on third party funds.

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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