scholarly journals ANALIZING FACTOR THAT AFFECTING IMPORT OF MAIZE IN INDONESIA ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI IMPOR JAGUNG DI INDONESIA

2019 ◽  
Vol 12 (2) ◽  
Author(s):  
Raditya Audayuda ◽  
Elpawati E ◽  
Iwan Aminudin
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Linear Regression ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Series Data ◽  
F Test ◽  
Maize Production ◽  
Us Dollar

The purpose of The study is to identify the factor that affecting import of maize in Indonesia, Ana to analyze The factor that affecting import of maize in Indonesia. The data used in The Study is Time series data from 1990 to 2014 sourced from BPS(Badan Pusat Statistik) and Kementrian Pertanian. The method used in The Study is linear regression analysis using SPSS 18 software. Statistics Test that used in this Study including R2 , F-test, and T-test.In this Study we can concluded that R2 test value is 0,703 that means 70,3% import of maize explained by variable that used in model, which is: maize production (produksi jagung), maize consumption (konsumsi jagung), maize domestic prize (harga jagung domestik), maize import prize (harga jagung impor), and Rupiah to US Dollar currency (Nilai tukar rupiah terhadap dollar Amerika), and remaining 29,7% remains explained by another variable that exclude by this model. After all The testing, results shows all variable in The model affecting maize import simultaneously, and partial Test shows maize production, maize consumption, maize domestic prize, and Rupiah to US Dollar currency partially affecting import of maize in Indonesia, and maize import prize variable didn’t affect import of maize in Indonesia.

scholarly journals Pengaruh Pertumbuhan Ekonomi, Tingkat Inflasi, dan Pertumbuhan Penduduk terhadap Tingkat Pengangguran Terbuka di Indonesia

2019 ◽  
Vol 18 (1) ◽  
pp. 52
Author(s):  
Irma Yuni Astuti ◽  
Nanik Istiyani ◽  
Lilis Yuliati
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Regression Analysis ◽  
Linear Regression ◽  
Population Growth ◽  
Multiple Linear Regression ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Series Data

This study aims to determine the effect of economic growth, inflation and population growth in open unemployment rate in Indonesia. The type of data used in this study is secondary data in the form of time series data and variable data used are annual data in the period 1986-2017 with the object of research in the country o Indonesia. The data sources used in this study were obtained from the Central Statistics Agency (BPS) Indonesia and World Bank. The analytical method used in this study is multiple linear regression analysis with the Ordinary Least Square (OLS) technique. The estimation of time series data with multiple linear regression analysis shows that the economics growth variable has a positive and not significant effect on the level of open unemployment, the inflation variable has a positive and not significant effect on the level of open unemployment, and the population growth variable has a negative and significant effect on the level of open unemployment in Indonesia. Keywords: Open Unemployment, Economic Growth, Inflation, Population Growth

scholarly journals ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI IMPOR BERAS DI INDONESIA

2019 ◽  
Vol 11 (2) ◽  
pp. 183-201
Author(s):  
Yona Namira ◽  
Iskandar Andi Nuhung ◽  
Mudatsir Najamuddin
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Time Series Data ◽  
Series Data ◽  
Test Results ◽  
The Us ◽  
Rice Prices ◽  
Us Dollar ◽  
Spss Software

This study aims to 1) identify factors that affect the import of rice in Indonesia 2) analyze the influence of these factors on imports of rice in Indonesia. The data used in this research are time series data from 1994 to 2013 from the Central Statistics Agency (BPS), the Ministry of Agriculture, Ministry of Commerce, National Logistics Agency (Bulog), and Bank Indonesia. Multiple linear regression through SPSS software version 21 was employed to analyze the data. The test results together indicated the variables of productions, consumptions, stocks of rice, domestic rice prices, international rice prices and the rupiah against the US dollar affect the imports of rice in Indonesia.

scholarly journals Pengaruh Produk Domestik Regional Bruto (PDRB) terhadap Tingkat Kemiskinan Kota Medan

2022 ◽  
Vol 4 (3) ◽  
pp. 683-693
Author(s):  
Reni Ria Armayani Hasibuan ◽  
Anggi Kartika ◽  
Firdha Aigha Suwito ◽  
Lismaini Agustin
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Domestic Product ◽  
Series Data ◽  
Simple Linear Regression ◽  
Poverty Level ◽  
Simple Linear Regression Analysis ◽  
A Value

This study has the benefit of analyzing the effect of regional gross domestic product on poverty in the city of Medan in 2010-2020. The research method used is a quantitative method with reference to a descriptive approach. The data used is time series data on economic growth and poverty at the Central Statistics Agency (BPS) of Medan City in 2010-2020. Data collection techniques used are journals, book documentation, and previous reports. The technique of analyzing the data uses simple linear regression analysis which is carried out to determine whether the model used is free from deviations from the classical assumption test. The equations obtained from the simple linear regression analysis test Y = 24576.325 – 0.365X and have the understanding that the GRDP variable (X) has a significant effect on Poverty (Y). Obtained a value of R2 (R square) of 0.556 with the understanding that the independent variable, namely GRDP, affects the variable of the poverty level in Medan City by 55.6%. Meanwhile, the remaining 44.4% are influenced by different independent variables and are not included in this study. For this reason, it can be concluded that when GRDP increases, it will have an impact on decreasing the value of Poverty in Medan City, and vice versa. Keywords: Gross Regional Domestic Product; Poverty; Medan city

scholarly journals Pengaruh tingkat inflasi terhadap nilai tukar rupiah (Studi pada Bank Indonesia periode tahun 2011-2015)

2017 ◽  
Vol 5 (1) ◽  
pp. 32
Author(s):  
Yati Wijayanti Sudarmiani
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Exchange Rate ◽  
Inflation Rate ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Secondary Data ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Simple Linear Regression

<p><em>This study aimed to analyze the influence of the inflation rate of the Rupiah. Population and samples used in this study are all monthly time series data rate of inflation and the Rupiah during the period January 2011-December 2015 as many as 60. The data used are secondary data obtained from the official website of Bank Indonesia<a href="http://www.bi.co.id/"> (www.bi.co.id).</a> The analytical method used in this study is a simple linear regression analysis. The result of the coefficient of determination (r2) which shows that the percentage of the effect of the inflation rate to changes in the rupiah exchange rate of 7,9%. From the calculations, the equation Y = 3.941 + 0,073X , it can be concluded that the level of inflation is positive and significant effect on the rupiah.</em></p>

scholarly journals An improved ARIMA model for precipitation simulations

2014 ◽  
Vol 21 (6) ◽  
pp. 1159-1168 ◽  
Author(s):  
H. R. Wang ◽  
C. Wang ◽  
X. Lin ◽  
J. Kang
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Arima Model ◽  
Series Data ◽  
Monthly Precipitation ◽  
Monthly Variation ◽  
Arima Models ◽  
Hydrologic Variable

Abstract. Auto regressive integrated moving average (ARIMA) models have been widely used to calculate monthly time series data formed by interannual variations of monthly data or inter-monthly variation. However, the influence brought about by inter-monthly variations within each year is often ignored. An improved ARIMA model is developed in this study accounting for both the interannual and inter-monthly variation. In the present approach, clustering analysis is performed first to hydrologic variable time series. The characteristics of each class are then extracted and the correlation between the hydrologic variable quantity to be predicted and characteristic quantities constructed by linear regression analysis. ARIMA models are built for predicting these characteristics of each class and the hydrologic variable monthly values of year of interest are finally predicted using the modeled values of corresponding characteristics from ARIMA model and the linear regression model. A case study is conducted to predict the monthly precipitation at the Lanzhou precipitation station in Lanzhou, China, using the model, and the results show that the accuracy of the improved model is significantly higher than the seasonal model, with the mean residual achieving 9.41 mm and the forecast accuracy increasing by 21%.

scholarly journals FAKTOR - FAKTOR YANG MEMPENGARUHI PDRB KABUPATEN / KOTA JAWA TENGAH TAHUN 2008-2012

JEJAK ◽  
2015 ◽  
Vol 8 (1) ◽  
Author(s):  
Yozi Aulia Rahman ◽  
Ayunda Lintang Chamelia
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Series Data ◽  
Main Condition ◽  
Independent Variables ◽  
Central Java ◽  
Central Java Province

<p>Pertumbuhan ekonomi yang tinggi merupakan kondisi utama bagi kelangsungan pembangunan ekonomi daerah. Untuk mengukur kemajuan perekonomian daerah dengan mengamati seberapa besar laju pertumbuhan ekonomi yang dicapai daerah tersebut yang tercermin dari kenaikan Produk Domestik Regional Bruto (PDRB). PDRBKabupaten/Kota di Jawa Tengah selama tahun 2008- 2012 mengalami pertumbuhan karena banyak yang mempengaruhinya, seperti: Tabungan, Kredit, PAD dan Belanja Daerah. Penelitian ini bertujuan untuk menganalisis seberapa besar faktor-faktor tersebut mempengaruhi tingkat PDRB kabupaten/Kota di Jawa Tengah selama tahun 2008-2012. Variabel dependen yang digunakan dalam penelitian ini adalah PDRB, sedangkan variabel-variabel independen yaitu Tabungan, Kredit, Pendapatan Asli Daerah (PAD) dan Belanja Daerah. Penelitian ini menggunakan analisis regresi linear berganda melalui metode OLS dengan menggunakan data    time series 2008  –2012 dan data crosssection 35 kabupaten/kota di Provinsi Jawa Tengah atau yang dimaksud dengan data panel. Pengujian model dalam penelitian ini menggunakan metode FixedEffect. Hasil estimasi menunjukkan bahwa hasil analisis regresi pada α=5%menunjukkan bahwa secara parsial  variabel tabungan   dan kredit berpengaruh signifikan, sedangkan variabel PAD, dan Belanja Daerah tidak signifikan terhadap PDRB kabupaten/kota di Provinsi Jawa Tengah tahun 2008–2012. </p><p>High economic growth is the main condition for the continuation of regional economic development. To measure the progress of the regional economy, observation on the economyc growth rate in each area can be conducted. It is reflected in the increase of Gross Regional Domestic Product (GDP). The increase of GDP of regency/city in Central Java during the year of 2008- 2012 was influenced by several factors such as savings, credit, local generated revenue (PAD), and Expenditure. This study intends to analyze the affect of these factors to the level of GDP on districts / cities in Central Java during the years 2008-2012. The dependent variable used in this study is GDP. Meanwhile, the independent variables are savings, credit, revenue (PAD) and expenditure. This study uses multiple linear regression analysis by the OLS method using time series data in 2008 -2012 and data crosssection of 35 districts / cities in Central Java province which are often called as the data panel. The model is tested by using Fixed Effect. The result indicates that the results of the regression analysis on the α = 5% shows that in partial,  saving and loan have significant effect on GDP.  Meanwhile,  PAD variable and expenditurehave no significant effect on GDP districts / cities in Central Java province in 2008-2012.</p>

scholarly journals Regression Factors of Rainfall, Humidity, and Rainy Day on Pepper Yield and Policy Alternatives in North Sumatra

2020 ◽  
Vol 3 (2) ◽  
pp. 25-35
Author(s):  
Fransisca Natalia Sihombing ◽  
Koko Tampubolon ◽  
Triara Juniarsih
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Data Analysis ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Series Data ◽  
Policy Alternatives ◽  
The Relationship ◽  
North Sumatra

Introduction: This research was aimed to determine the relationship pattern of rainfall, humidity, and rainy day on the increase in pepper yield in North Sumatra. Materials and Methods: This research used the time-series data on factors of rainfall, humidity, rainy day, and yield of pepper for 14 years (2005 until 2018). Data analysis used the multiple linear regression analysis with the Eviews 10 software. Results: The rainfall, humidity, and rainy day simultaneous significantly increased the pepper yield of 55.767% in North Sumatra. A 1% increase in humidity can increase the pepper yield by 0.455 ton, but a 1 mm.year-1 increase in rainfall and a 1 rainy day can decrease the pepper yield in North Sumatra by 0.503 and 1.866 ton, respectively. The humidity had the value positive, meanwhile rainfall and rainy day had the value negative in pepper yield.

PENGARUH LEVERAGE, LIKUIDITAS, DAN UKURAN PERUSAHAAN TERHADAP PROFITABILITAS (STUDI KASUS PADA PERUSAHAAN SUB SECTOR REAL ESTATE AND PROPERTY DI BURSA EFEK INDONESIA PERIODE 2015-2018)

2020 ◽  
Vol 4 (02) ◽  
Author(s):  
Pingkan Saraswati
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Real Estate ◽  
Linear Regression Analysis ◽  
T Test ◽  
Company Size ◽  
Return On Assets ◽  
F Test ◽  
Sample Technique ◽  
A Company

Profitabilitya has significance for theecompany because it is one of the bases for evaluating the condition of a company. The level off profitability describes the ecompany's performance as seen from the company's ability to generate profits. Profitability in this study is calculated by return on assets (ROA) because it can show how the company's performance is nseenn from the overall use of assets owned by the company in generating profits. Thissstudyyaims to examine the leverage, liquidity, and size off thee company yaffect the eprofitability. The ssampling ttechniqueu used in this study wass purposivee samplingg, which issaa sample technique ethat uses certain ncriteria.. There earee16 companies ethat are sampled in this sstudy.mThe nanalysiss techniquee usedd is multiplee linearr regressionn using SPSS version 22. Multiplee linear regression analysis susess the eclassicc assumption ntest, nincluding mthe nnormality ntest, multicollonityy test,,heteroscedasticityytest,, and dautocorrelationn test.m Tootestttheevariablessused theecoefficient of determination test, t-test, f-test. The results of this study indicate that there is no significant effect on the variable leverage on profitability. Liquidity hass a positivee effectt onn profitability. There eis snoo significantt effectt off thee Company Size variablee on nthee profitability variable..

scholarly journals Pengaruh Industri Sedang dan Besar Terhadap Tingkat Kemiskinan di Kabupaten Gresik Tahun 2002-2016

2021 ◽  
Vol 4 (1) ◽  
pp. 25-31
Author(s):  
Rohmatul Janah ◽  
Ida Nuraini
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Time Series Data ◽  
Industrial Sector ◽  
Poverty Rate ◽  
Domestic Product ◽  
Series Data ◽  
Insignificant Effect ◽  
Poverty Levels

This research is aimed at studying the influence of medium and large industries on poverty levels in Gresik on 2002-2016. The variables used in this study is medium and large industries, a labour of medium and large industries, gross regional domestic product (GRDP) of industrial sector and poverty rate. The method used in this study used multiple linear regression and used time-series data. The results of this study simultaneously are the variables of the amount of medium and large industries, the labour medium and large industries, and the gross regional domestic product (GRDP) of the industrial sector to poverty rate is significant. While medium and large industries to poverty rate have negative and insignificant effect with a coefficient value of -0,208905. The labour of medium and large industries to poverty rate has a positive and significant effect with a coefficient value of 0,130822,  the gross regional domestic product (GRDP) of industrial to poverty rate has a negative and significant effect with a coefficient value of -0,169431.

scholarly journals Peran Grup Afiliasi dalam Memoderasi Pengaruh Hutang terhadap Nilai Perusahaan pada Perusahaan Property & Real Estate yang terdaftar di Bursa Efek Indonesia

FORUM EKONOMI ◽  
2017 ◽  
Vol 19 (1) ◽  
pp. 58
Author(s):  
Fina Maulidyani ◽  
Set Asmapane ◽  
Ledy Setiawati
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Time Series Data ◽  
Stock Exchange ◽  
Debt Financing ◽  
Series Data ◽  
Simple Linear Regression ◽  
Group Affiliation ◽  
A Company ◽  
Positive Effect

The objective of this research is to examine empirically the effect of Debt on Firm’s Value and the ability of Group Affiliation to moderate the effect of Debt toward Firm’s Value by using an approach simple linear regression and Moderated Regression Analysis (MRA). This research uses time series data in 2011 – 2015 for company's finance data that got from Indonesia Stock Exchange. Election Procedure sample uses purposive sampling and the result are existed 35 companies that fulfill criterion. The results show that Debt has positive effect on Firm’s Value, while Group Affiliation act as a moderating variable can reduce the effect of Debt toward Firm’s Value. The higher capability of group affiliation to take control of a company, the lower debt financing that company has.Keywords:     Debt Financing, Firm’s Value, Group Affiliation

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