PENDAPATAN DAN RISIKO PENDAPATAN USAHA TANI PADI DAERAH IRIGASI DAN NON IRIGASI DI KABUPATEN BANJAR KALIMANTAN SELATAN

This study aims to determine the income and revenue risk from rice farming inirrigated and non irrigated land are also factors that influence it. The hypothesisadvanced is that (1) factors that affect revenue and revenue risk rice farming inpaddy fields are irrigated and non irrigated land area, the price of seed, fertilizerprices, wage labor, the price of seeds, irrigation areas and varieties, (2 ) rice farmincome risk in irrigated land is lower than non-irrigated land. Data obtainedthrough interviews with 80 randomly simple rice farmers. The method used ismultiple linear regression analysis model with Ordinary Least Square (OLS) andthe analytical coefficient of variation (CV). The results showed that the area ofland, the price of urea, ponska price, the price of pesticides, and irrigation areadummy effect on income. While the risk is influenced by the land revenue, theprice of seed, the price of urea fertilizer, fertilizer prices ponska, pesticide pricingand superior varieties of variables. Income risk in the area of irrigated ricefarming was smaller than non-irrigated areas with kofisien variation of 0.83 and0.89.Key words: revenue, risk, rice, irrigated and non irrigated area.

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MEKANISASI USAHATANI PADI DI KECAMATAN SANANWETAN KOTA BLITAR

JURNAL AGRI-TEK Jurnal Penelitian Ilmu-Ilmu Eksakta ◽

10.33319/agtek.v21i1.53 ◽

2020 ◽

Vol 21 (1) ◽

pp. 20-28

Author(s):

Cristina Ratnawati

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

Linear Regression Analysis ◽

Multiple Linear Regression Analysis ◽

Variable Cost ◽

Rice Farming ◽

Land Area ◽

Rice Farmers ◽

Group Members ◽

Labor Requirements

Mechanization is one form of technology adoption to improve yields in rice farming. The aims of the research to determine the use of agricultural mechanization and its impact on rice farming in Sananwetan Sub-District, Blitar City expected to improve the standard of living and welfare of its group members. The number of samples taken was 50 rice farmers in Sananwetan Sub-District, Blitar City, chosen by using proportional random sampling. Data analysis using the Mann-Whitney Test and the Multiple Linear Regression Cobb Douglas Model. From the results of interviews in this study show that the use of the mechanization of rice farming in Sananwetan Sub-District, Blitar City is still not optimal. This was due to farmers' perceptions of the unsatisfactory results of agricultural machinery performance, a sense of humanity to 'farm laborers', narrow land area and insufficient availability of farm machinery. While from the results of Mann Whitney's test show that pesticide use and labor requirements were smaller and differed significantly in the use of full mechanization rather than partial mechanization. Other than that, the variable cost of the harvest is lower in the use of full mechanization and is significantly different compared to using the mechanism partially. Rice productivity in full mechanization was 782.15 kg / 1000m2 while partial mechanization was 682.87 kg / 1000m2. For farmers' income in full mechanization is IDR. 1,153,407, - per 1000 m2, in the partial mechanization of IDR. 1,590,574, - per 1000m2. From Cobb Douglas model multiple linear regression analysis found that land area (m2), seed costs and the use of mechanization had a significant effect on the income of rice farming in Sananwetan District, Blitar City.

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PERBANDINGAN TRANSFORMASI BOX-COX DAN REGRESI KUANTIL MEDIAN DALAM MENGATASI HETEROSKEDASTISITAS

E-Jurnal Matematika ◽

10.24843/mtk.2015.v04.i01.p081 ◽

2015 ◽

Vol 4 (1) ◽

pp. 8

Author(s):

NI WAYAN YUNI CAHYANI ◽

I GUSTI AYU MADE SRINADI ◽

MADE SUSILAWATI

Keyword(s):

Regression Analysis ◽

Linear Regression ◽

Quantile Regression ◽

Linear Regression Analysis ◽

Least Square ◽

Power Transformation ◽

Ordinary Least Square

Ordinary least square (OLS) is a method that can be used to estimate the parameter in linear regression analysis. There are some assumption which should be satisfied on OLS, one of this assumption is homoscedasticity, that is the variance of error is constant. If variance of the error is unequal that so-called heteroscedasticity. The presence heteroscedasticity can cause estimation with OLS becomes inefficient. Therefore, heteroscedasticity shall be overcome. There are some method that can used to overcome heteroscedasticity, two among those are Box-Cox power transformation and median quantile regression. This research compared Box-Cox power transformation and median quantile regression to overcome heteroscedasticity. Applied Box-Cox power transformation on OLS result ????2point are greater, smaller RMSE point and confidencen interval more narrow, therefore can be concluded that applied of Box-Cox power transformation on OLS better of median quantile regression to overcome heteroscedasticity.

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ANALISIS DETERMINAN PENDAPATAN PEDAGANG PASAR BANJARSARI KOTA PEKALONGAN PASCA KEBAKARAN

ECONBANK: Journal of Economics and Banking ◽

10.35829/econbank.v2i1.77 ◽

2020 ◽

Vol 2 (1) ◽

pp. 1-8

Author(s):

Nur Elitami Insan ◽

Arif Pujiyono

Keyword(s):

Regression Analysis ◽

Linear Regression ◽

Multiple Linear Regression ◽

Linear Regression Analysis ◽

Working Hours ◽

Multiple Linear Regression Analysis ◽

Least Square ◽

Ordinary Least Square ◽

Business Location ◽

Dominant Influence

The income of traders in the Banjarsari Emergency Market Pekalongan is influenced by various factors, one of which is the trader resources (capital, working hours, business length, education, and business location). This study aims to determine the effect of capital, working hours, business length, education, and business location on the income of traders in the Banjarsari Emergency Market in Pekalongan. There as 95 traders of Banjarsari Emergency Market in Pekalongan were taken as samples with purposive sampling and accidental sampling. This study uses multiple linear regression analysis tools with the Ordinary Least Square (OLS) method. The results showed that capital, length of business, and location of business affect the income of traders. While working hours and education have not affected the income of the trader. Capital provides the most dominant influence on income trader

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Earmarking Tax Optimization to Support The Effective and Sustainable Infrastructure

Jurnal Ekonomi Pembangunan Kajian Masalah Ekonomi dan Pembangunan ◽

10.23917/jep.v18i2.4168 ◽

2017 ◽

Vol 18 (2) ◽

pp. 194

Author(s):

Hadi Sasana

Keyword(s):

Regression Analysis ◽

Linear Regression Analysis ◽

Secondary Data ◽

Least Square ◽

Road Maintenance ◽

Sustainable Infrastructure ◽

Fuel Tax ◽

Ordinary Least Square ◽

Revenue Sources ◽

Transportation Sector

The majority of road infrastructure condition is far from excellent. The implementation of 10% minimum compulsory allocation of vehicle tax to be returned for road and transportation sector is potential to increase road maintenance fund.The research purpose is to raise regional revenue sources of Semarang City which is worth to be earmarked and to be alocated for road maintenance. This research is using secondary data of 2008-2015 period and linear regression analysis with Ordinary Least Square (OLS) method. The result of research concludes that : 1) the sources of earmarking consist of : vehicle tax (PKB), fee of vehicle title transfer (BBNKB), and fuel tax (PPBKB). 2) the allocation proportion of each earmarking source for Semarang City road maintenancefor next five years are : 25% (PKB), 15% (BBKNB), and 15% (PBBKB). 3) the allocation proportion of each earmarking source for Semarang City roadconstruction for next five years are: 50% (PKB), 45% (BBNKB), and 45% (PBBKB).

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ANALISIS FAKTOR YANG MEMPENGARUHI ALIH FUNGSI LAHAN SAWAH KE NON SAWAH DI KABUPATEN SLEMAN DAERAH ISTIMEWA YOGYAKARTA

SEPA Jurnal Sosial Ekonomi Pertanian dan Agribisnis ◽

10.20961/sepa.v13i1.14232 ◽

2017 ◽

Vol 13 (1) ◽

pp. 22

Author(s):

Annisa Titias Habibatussolikhah ◽

Darsono Darsono ◽

Susi Wuri Ani

Keyword(s):

Linear Regression ◽

Agricultural Sector ◽

Agricultural Land ◽

Linear Regression Analysis ◽

Secondary Data ◽

Least Square ◽

Land Area ◽

Ordinary Least Square ◽

Trust Level

The development of non-agricultural sector are increasingly in need of land. The land needs met by conversion of agricultural land to non-agricultural land. This research was aimed to examine the rate of the agriculture land (wet land) conversion and factors that determine the conversion in Sleman Regency. The basic method which used was descriptive analytic. Determination of the research location was using purposive method in Sleman regency. Method to analyze the data was double linear regression (Ordinary Least Square). The data which used in this research was secondary data in 1984-2013 from BPS, BPN, Bappeda, and DPUP of sleman regency.The result of this research shows that the conversion of wet land in Sleman regency happened in 1984-2013. Since 30 years, wet land area which convert to nonagricultural area was 4.496 Ha or 150 Ha. Wet land area had decreased with the growth rate 0,608% per year. Based on the double linear regression analysis (Ordinary Least Square) with 95% of trust level, it could be known the significance relation between wet land area and the number of population, industry, residential, road length, PDRB, and government policy. Individually, the area of agricultural land in sleman regency was influenced by the number of population, industry, residential, and PDRB.

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Faktor-Faktor Mempengaruhi Ketimpangan Wilayah di Provinsi Jawa Timur, Indonesia

Media Ekonomi dan Manajemen ◽

10.24856/mem.v33i1.564 ◽

2018 ◽

Vol 33 (1) ◽

Cited By ~ 1

Author(s):

Fitrah Sari Islami ◽

Nugroho SBM

Keyword(s):

Regression Analysis ◽

Linear Regression ◽

Multiple Linear Regression ◽

Linear Regression Analysis ◽

Government Expenditure ◽

Multiple Linear Regression Analysis ◽

Least Square ◽

Ordinary Least Square ◽

Regional Inequalities ◽

Index Value

AbstrakKetimpangan wilayah merupakan salah satu masalah yang umum terjadi di Negara sedang berkembang termasuk di Indonesia. Jawa Timur merupakan provinsi yang nilai ketimpangannya cukup tinggi jika dibandingkan dengan provinsi lain yang berada di Pulau Jawa. Penelitian ini bertujuan untuk 1) mengetahui keadaan ketimpangan di Provinsi Jawa Timur 2) mengetahui faktor-faktor yang mempengaruhi ketimpangan wilayah di Provinsi Jawa Timur.Penelitian ini menggunakan 1) Indeks Williamson untuk mengukur ketimpangan wilayah, 2) Analisis regresi linear berganda (Ordinary Least Square) dengan waktu penelitian tahun 2001-2015. Penelitian ini menggunakan software Eviews 9.Hasil Penelitian menunjukkan bahwa tingkat ketimpangan wilayah di Provinsi Jawa Timur cenderung meningkat dengan nilai indeks Williamson lebih dari 1. Hasil analisis regresi linear berganda dalam penelitian ini ada tiga variabel yang hasilnya signifikan (α=5%) dan berpengaruh terhadap ketimpangan wilayah yaitu variabel investasi, angkatan kerja dan IPM serta dua variabel yang tidak signifikan yaitu variabel pertumbuhan ekonomi, pengeluaran pemerintah. Kata Kunci: Ketimpangan Wilayah, Indeks Williamson, Jawa Timur AbstractRegional inequalities are one of the most common issues in developing countries including in Indonesia. East Java is the pro vince with the quiet high inequalities value compared to the other provinces in Java Island. This study aims to: 1) to calculate the inequality value in East Java Province, 2) to classify the regions in East Java Province using Klassen Typology, 3) to determine factors that affect inequalities value in East Java Province.The methods used in this study were 1) Williamson Index to calculate the inequalities values, 2) Multiple linear regression analysis (Ordinary Least Square) during 2001 – 2015 using Eviews 9 software.The result of the study showed that the level of regional inequalities in East Java Province tends to increase with the Williamson index value more than 1. The result of multiple linear regression analysis, the variable of investment, labor forced and HDI were resulted to significant and it affect to the regional inequalities, meanwhile the variable of economic growth, and government expenditure were insignificant.Keyword: inequalities, Williamson Index, Klassen Typology, East Java

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Pengaruh Belanja Daerah dan Tenaga Kerja terhadap Output Sektor Swasta di Sumatera Selatan

MBIA ◽

10.33557/mbia.v19i2.1018 ◽

2020 ◽

Vol 19 (2) ◽

pp. 237-242

Author(s):

Muhammad Bahrul Ulum

Keyword(s):

Time Series ◽

Regression Analysis ◽

Private Sector ◽

Linear Regression Analysis ◽

Secondary Data ◽

Multiple Linear Regression Analysis ◽

Least Square ◽

Ordinary Least Square ◽

Independent Variables ◽

Ministry Of Finance

The purpose of this study was to determine the effect of regional spending namely direct and indirect spending, labor on the private sector in South Sumatra. The data used are secondary data in the form of time series 2006-2017 sourced from the DGT Ministry of Finance and the Central Statistics Agency (BPS) which have been processed. This research uses the Multiple Linear Regression analysis methods with Ordinary Least Square (OLS) method. The results of this study indicate that during 2006-2017 the expenditure variable directly had a positive and significant effect on private-sector output in South Sumatra. The indirect expenditure variable has a positive and significant effect on private-sector output in South Sumatra. Labor variables have a positive and significant effect on private-sector output in South Sumatra. Overall independent variables have a significant effect on the output of the private sector in South Sumatra. Abstrak Tujuan penelitian ini untuk mengetahui pengaruh belnja daerah yakni belanja langsung dan belanja tidak langsung, tenaga kerja terhadap sektor swasta di Sumatera Selatan. Data yang digunakan adalah data sekunder dalam bentuk time series tahun 2006-2017 yang bersumber dari DJPK Kementerian Keuangan dan Badan Pusat Statistik (BPS) yang telah diolah. Penelitian ini menggunakan metode analisis Regresi Linier Berganda dengan metode Ordinary Least Square (OLS). Hasil penelitian ini menunjukan hasil bahwa selama tahun 2006-2017 variabel belanja langsung berpengaruh positif dan signifikan terhadap output sektor swasta di Sumatera Selatan. Variabel belanja tidak langsung berpengaruh positif dan signifikan terhadap output sektor swasta di Sumatera Selatan. Variabel tenaga kerja berpengaruh positif dan signifikan terhadap output sektor swasta di Sumatera Selatan. Secara keseluruhan variabel bebas berpengaruh signifikan terhadap output sektor swasta di Sumatera Selatan. Kata kunci: Belanja Langsung, Belanja Tidak Langsung, Tenaga Kerja, Output Sektor Swasta

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FAKTOR – FAKTOR YANG MEMPENGARUHI TINGKAT PENGGANGGURANDI PROVINSI SULAWESI UTARA

AGRI-SOSIOEKONOMI ◽

10.35791/agrsosek.13.1a.2017.14953 ◽

2017 ◽

Vol 13 (1A) ◽

pp. 55

Author(s):

Arfan ., Poyoh ◽

Gene H. M. Kapantow ◽

Juliana R. Mandei

Keyword(s):

Regression Analysis ◽

Linear Regression ◽

Linear Regression Analysis ◽

Least Square Method ◽

Least Square ◽

Gdp Growth ◽

Affecting Factors ◽

Factors Affecting ◽

Ordinary Least Square ◽

North Sulawesi

The study aims to analyze the factors - factors affecting the level of unemployment in theprovince of North Sulawesi. These factors include wages, inflation and GDP growth. This study usesmultiple linear regression analysis with Ordinary Least Square method (OLS) was performed using14 years data from 2001 to 2014. The results showed wage variables significantly influence theunemployment rate in North Sulawesi province with probability 0.0104, while inflation and levels ofGDP growth does not significantly influence the unemployment rate with respective probabilities0.5619 for Inflation and 0.3791 for GDP growth.Keywords: affecting factors, wages, inflation, GDP growth, unemployment, North Sulawesi Province

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PENGARUH PENANAMAN MODAL ASING, PERDAGANGAN INTERNASIONAL, GDP PER KAPITA, SEKTOR PERTANIAN, DAN URBANISASI TERHADAP PENDUDUK BEKERJA DI INDONESIA

Jurnal Ekonomi dan Bisnis ◽

10.24123/jeb.v21i2.1640 ◽

2017 ◽

Vol 21 (2) ◽

pp. 85-95

Author(s):

John Marcell Rumondor

Keyword(s):

International Trade ◽

Gross Domestic Product ◽

Foreign Investment ◽

Linear Regression Analysis ◽

Multiple Linear Regression Analysis ◽

Least Square ◽

Domestic Product ◽

Working Population ◽

Ordinary Least Square ◽

Per Capita

This research aims to understand the influenceof foreign investment, international trade, Gross Domestic Product per capita, agriculture and urbanization of the working population. Country used as an object in this research is Indonesia. This research uses the method of analysis Ordinary Least Square (OLS) and the multiple linear regression analysis method. Research period are from 1997 – 2012. The results showed that the international trade, Gross Domestic Product per capita, agriculture and urbanization have significantpositive influenceon the population work in Indonesia, but foreign investment has no significanteffect on the working population in Indonesia.

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PENERAPAN METODE BOOTSTRAP RESIDUAL DALAM MENGATASI BIAS PADA PENDUGA PARAMETER ANALISIS REGRESI

E-Jurnal Matematika ◽

10.24843/mtk.2014.v03.i04.p075 ◽

2014 ◽

Vol 3 (4) ◽

pp. 130

Author(s):

NI MADE METTA ASTARI ◽

NI LUH PUTU SUCIPTAWATI ◽

I KOMANG GDE SUKARSA

Keyword(s):

Regression Analysis ◽

Statistical Analysis ◽

Confidence Intervals ◽

Bootstrap Method ◽

Least Square ◽

Prediction Tool ◽

Analysis Method ◽

Ordinary Least Square ◽

Independent Variable ◽

Parameter Estimators

Statistical analysis which aims to analyze a linear relationship between the independent variable and the dependent variable is known as regression analysis. To estimate parameters in a regression analysis method commonly used is the Ordinary Least Square (OLS). But the assumption is often violated in the OLS, the assumption of normality due to one outlier. As a result of the presence of outliers is parameter estimators produced by the OLS will be biased. Bootstrap Residual is a bootstrap method that is applied to the residual resampling process. The results showed that the residual bootstrap method is only able to overcome the bias on the number of outliers 5% with 99% confidence intervals. The resulting parameters estimators approach the residual bootstrap values ??OLS initial allegations were also able to show that the bootstrap is an accurate prediction tool.

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