scholarly journals Pengaruh Biaya Operasional Berbanding Pendapatan Operasional (BOPO), Non Performing Loan (NPL), Loan To Deposit Ratio (LDR) Terhadap Kinerja Usaha (ROA)

2020 ◽  
Vol 5 (2) ◽  
pp. 098-108
Author(s):  
Anysa . ◽  
Bambang Rahardjo
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Business Performance ◽  
Multiple Linear Regression Model ◽  
Test Results ◽  
Operational Cost ◽  
Operating Income ◽  
Independent Variables ◽  
Operational Costs ◽  
Observation Period

The study was based on a formulation of problems, namely are Operational Cost versus Operating Income (ROA), Non Performing Loan (NPL), Loan to Deposit Ratio (LDR) on Business Performance (ROA) at PT Bank Rakyat Indonesia (Persero) Tbk., PT Bank Negara Indonesia (Persero) Tbk., and Bank Mandiri (Persero) Tbk. The purpose of this research was to determine the effect of operational cost compared to Operating Income (ROA), Non Performing Loan (NPL), Loan to Deposit Ratio (LDR) on Business performance (ROA) at PT Bank Rakyat Indonesia (Persero) Tbk., PT Bank Negara Indonesia (Persero) Tbk,  and Bank Mandiri (Persero) Tbk.  The method used in this research is quantitative method. This method is used to predict the effect of one variable with another variable. In this study the variable X (Operating Expenses compared to Operating Income (ROA), Non Performing Loan (NPL), Loan to Deposit Ratio (LDR) are independent variables (free) and Y (Return On Asset) is the dependent variable (dependent). The data obtained was secondary, and to analyze the data, multiple regression analysis was used. During the observation period of the study showed that the data were normally distributed. Based on the test multicollinearity, heteroscedasticity test and autocorrelation test found no variable that deviates from the classical assumption tests, this shows that the available data are qualified to use a multiple linear regression model. Based on the results of the study it can be concluded that there is significant influence of operational costs when compared to Operating Income (ROA), Non Performing Loan (NPL), Loan to Deposit Ratio (LDR) PT Bank Rakyat Indonesia (Persero) Tbk., PT Bank Negara Indonesia (Persero ) Tbk, and Bank Mandiri (Persero) Tbk. with test results of multiple linear regression equation

A Mathematical Comparison of the Lachance - Traill Matrix Correction Procedure with Statistical Multiple Linear Regression Analysis in XRF Applications

1992 ◽  
Vol 36 ◽  
pp. 1-10
Author(s):  
Anthony J. Klimasara
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Mathematical Meaning ◽  
Matrix Correction ◽  
Independent Variables ◽  
Xrf Analysis

AbstractIt will be shown that the Lachance-Traill XRF matrix correction equations can be derived from the statistical multiple linear regression model. By selecting and properly transforming the independent variables and then applying the statistical multiple linear regression model, the following form of the matrix correction equation is obtained:Furthermore, it will be shown that the Lachance-Traill influence coefficients have a deeper mathematical meaning. They can be related to the multiple regression coefficients of the transformed system:Finally, it will be proposed that the Lachance-Traill model is equivalent to the statistical multiple linear regression model with the transformed independent variables. Knowing these facts will simplify correction subroutines in Quantitative/Empirical XRF Analysis programs. These mathematical facts have already been implemented and presented in a paper: “Automated Quantitative XRF Analysis Software in Quality Control Applications” (Pacific-International Congress on X-ray Analytical Methods, Hawaii, 1991).This demonstrates that the Lachance-Traill model has a strong mathematical foundation and is naturally justified mathematically.

scholarly journals The Effect of Phase on Paper Thickness Optimization in the Paper Recycling Process Using Recycling Machine

2020 ◽  
Vol 2 (1) ◽  
pp. 19
Author(s):  
Fauzhia Rahmasari
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Multiple Linear Regression Model ◽  
Thickness Optimization ◽  
Recycling Process ◽  
Paper Recycling ◽  
Independent Variables ◽  
The Relationship

AbstractEfforts to manage the recycling of paper waste into new paper have been carried out in recent times. It takes a tool or machine that is able to effectively and efficiently recycle used paper into new paper. There are several factors that affect the effectiveness of paper recycling machines, one of which is the paper thickness. One method that can be used to analyze the factors that influence paper thickness in the paper production process using a paper recycling machine is regression analysis. Regression analysis is data analysis techniques in statistics that is used to examine the relationship between several independent variables and dependent variable. However, if we want to examine the relationship or effect of two or more independent variables on a dependent variable, the regression model used is a multiple linear regression model. This study purposes are to analyze the factors that influence paper thickness using a paper recycling machine using multiple linear regression and to inform the modeling about that. The results showed that the factors that affect the paper thickness optimization are destruction and press phase. AbstractUpaya pengelolaan daur ulang sampah kertas menjadi kertas baru telah banyak dilakukan pada jaman sekarang. Dibutuhkan suatu alat atau mesin yang mampu secara efektif dan efisien dalam mendaur ulang kertas bekas menjadi kertas baru. Terdapat beberapa faktor yang mempengaruhi tingkat efektifitas mesin daur ulang kertas diantaranya adalah ketebalan kertas. Salah satu metode yang dapat digunakan untuk menganalisis faktor-faktor yang mempengaruhi ketebalan kertas pada proses produksi kertas menggunakan mesin daur ulang kertas adalah analisis regresi. Analisis regresi merupakan teknik analisis data dalam statistika yang digunakan untuk mengkaji hubungan antara beberapa variabel bebas dengan variabel tidak bebas. Namun, jika ingin mengkaji hubungan atau pengaruh dua atau lebih variabel bebas terhadap satu variabel tidak bebas, maka model regresi yang digunakan adalah model regresi linier berganda. Tujuan dalam penelitian ini yaitu menganalisis faktor-faktor yang mempengaruhi ketebalan kertas menggunakan mesin daur ulang kertas menggunakan regresi linier berganda serta memberikan informasi pemodelan mengenai hal tersebut. Hasil penelitian menunjukkan bahwa faktor yang mempengaruhi keoptimalan ketebalan kertas adalah fase penghancuran dan pemadatan kertas

scholarly journals What Determines Murabahah Margin Income? Evidence from Islamic Commercial Banks in Indonesia

2021 ◽  
Vol 7 (1) ◽  
pp. 22
Author(s):  
Ananda Puteri Wahyuni ◽  
Ratna Mulyany ◽  
Zata Hulwani Zuhri
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Central Bank ◽  
Multiple Linear Regression ◽  
Commercial Banks ◽  
Sampling Method ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Operating Income ◽  
Independent Variables

This study aims to examine factors that influence Murabahah margin income. Spefically it investigates the effect of the Central Bank of Indonesia Rate (BI Rate), Operating Expenses to Operating Income (OEOI), Non-Performing Financing (NPF), and wadiah savings on Murabahah margin income at Islamic Commercial Banks in Indonesia. The method used in this study is quantitative by using the multiple linear regression analysis to test the variables. 12 Islamic Commercial Banks were selected as the sample using a purposive sampling method. With 60 data observations for 5 years, the findings indicate that all the independent variables simultaneously affect the dependent variable. Partially, BI Rate does not affect Murabahah margin income, while in contrast, Operating Expenses to Operating Income (OEOI), Non-Performing Financing (NPF), and wadiah savings affect the Murabahah margin income.

The Impact of Climate Change on Agriculture in Morocco: An Econometric Study

2020 ◽  
Vol 1 (2) ◽  
pp. 19-28
Author(s):  
Faycel Tazigh
Keyword(s):  
Climate Change ◽  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Independent Variables ◽  
Temperature And Precipitation ◽  
The Impact ◽  
The Relationship

This paper aims to analyze the relationship that may exist between climate change and cereal yield in Morocco. In order to study this correlation between variables, we used the most common form of regression model which is the multiple linear regression model. There are two main uses of multiple linear regression model. The first one is to quantify the weight of impact that the independent variables had on the dependent variable. The second use is to predict not only the relationship that may found between variables but also their impacts. In our case, we have chosen temperature and precipitation as an independent variables and cereal yield as dependent variable.

FACTORS ASSOCIATED WITH CHILDREN’S HEIGHT AND BODY MASS INDEX IN LITHUANIA, 1990–2008

2015 ◽  
Vol 48 (4) ◽  
pp. 502-529 ◽  
Author(s):  
Andrej Suchomlinov ◽  
Janina Tutkuviene
Keyword(s):  
Body Mass Index ◽  
Linear Regression ◽  
Regression Model ◽  
Socioeconomic Factors ◽  
Multiple Linear Regression ◽  
Birth Order ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Factors Associated ◽  
Independent Variables

SummaryThe aim of the study was to reveal the ethnic and socioeconomic factors associated with height and body mass index (BMI) of children during the period of political and social transition in Lithuania in 1990–2008. Data were derived from the personal health records of 1491 children (762 boys and 729 girls) born in 1990 in Vilnius city and region. Height and BMI from birth up to the age of 18 years were investigated. Children were divided into groups according to their ethnicity, place of residence, father’s and mother’s occupation and birth order. Height and BMI were compared between the groups; a Bonferroni correction was applied. A multiple linear regression model was used to measure the effects of the independent variables on height and BMI. Girls living in Vilnius city were significantly taller in later life at the ages of 8 and 11 years. Sons of mothers employed as office workers appeared to be significantly taller at the ages of 7, 12, 14 and 15 years compared with the sons of labourers. First-born girls were taller at the age of 7 years than later-born girls of the same age (124.48±5.11 cm and 122.92±5.14 cm, respectively,p<0.001). Later-born children of both sexes had higher BMIs at birth compared with first-borns; however, first-born girls had higher BMIs at the age of 11 years compared with their later-born peers (17.78±2.87 kg/m² and 16.79±2.14 kg/m² respectively,p<0.001). In the multiple linear regression model, the five tested independent variables explained only up to 18% of total variability. Boys were more sensitive to ethnic and socioeconomic factors: ethnicity appeared to be a significant predictor of boys’ height at the age of 5 years (p<0.001), while birth order (p<0.001) predicted boys’ BMI at birth. In general, ethnicity, place of residence, father’s and mother’s occupation and birth order were not associated with children’s height and BMI in most age groups.

scholarly journals ANALISIS PENGARUH FUNGSI INTERMEDIASI PERBANKAN TERHADAP PERTUMBUHAN EKONOMI DI INDONESIA TAHUN 2008 - 2011

2013 ◽  
Vol 11 (2) ◽  
pp. 147
Author(s):  
. Anjarwati
Keyword(s):  
Economic Growth ◽  
Interest Rate ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Models ◽  
Coefficient Of Determination ◽  
Test Results ◽  
Linear Regression Models ◽  
Independent Variables ◽  
Multiple Linear Regression Models

This study aims to analyze the development of intermediation to economic growth in Indonesia and a significant test whether or not the effect of intermediation on economic growth. From the test results obtained by the coefficient of determination (R2) for multiple linear regression models for 0.916. It means that the independent variables can explain the variation in the dependent variable 91.6% together, then variable t can be seen that variable Interest Rate Loans and lending have a significant effect on economic growth, It is proved that t-count > t-table. Lending to the variable (X1) 7,944 t > t table 2.026, and for variable Interest Rate Loans (X2) 4.521 t-count > t table 2.026. From the analysis has been conducted simultaneously indicates that those independent variables have a significant effect on economic growth, with simultaneous F test results are calculated F value > F 204.012> 3.25. it means that Ho is rejected.

scholarly journals Bridge Construction Cost Prediction using Multiple Linear Regression

2019 ◽  
Vol 8 (9) ◽  
pp. 3115-3121
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Correlation Method ◽  
Multiple Linear Regression Model ◽  
Percentage Error ◽  
Cost Prediction ◽  
Independent Variables ◽  
Qualitative Variables ◽  
Leave One Out

Cost of construction of bridges is predicted using multiple linear regression model, based on data of bridges from Maharashtra state in India. Cost per unit area is taken as an appropriate dependent variable. Using both conventional and double log regression techniques, models for cost/m2 and log of cost/m2 are developed. Total 6 independent variables, which include both qualitative and quantitative variables, are used to develop the model. Height of bridge, average span length and depth of foundation are used as quantitative variables. Zone of construction, deck type and foundation type are used as qualitative variables in developing model. Strength of these independent variables with dependent variable is found out using pearson’s correlation method. Model is then verified using Leave One Out Cross Validation (LOOCV) technique. The most suited regression model obtained from the data experiment is double log regression with R2 of 0.850 and a Mean Absolute Percentage Error (MAPE) of 17.74%, as compared to 25% MAPE observed in past for studies related to traditional cost prediction.

scholarly journals Pengaruh Ukuran Perusahaan, ROA, DAR, Dan Reputasi Auditor terhadap Audit Delay

2017 ◽  
Vol 1 (1) ◽  
pp. 23-34
Author(s):  
Mimelientesa Irman
Keyword(s):  
Linear Regression ◽  
Linear Regression Model ◽  
Stock Exchange ◽  
Manufacturing Sector ◽  
Multiple Linear Regression Model ◽  
Company Size ◽  
Manufacturing Companies ◽  
Independent Variables ◽  
Model Sample ◽  
Observation Period

   This study aims to analyze the factors that affect audit delay on manufacturing companies listed in Indonesia Stock Exchange. This test uses multiple linear regression model. Sample of this study are 20 companies in manufacturing sector. Observation period is 6 years from 2010 to 2015. Independent variables in this study consisted of company size, profitability, solvency, and auditors reputation which tested its influence on audit delay as dependent variable. The results showed that company size, profitability, solvency, and auditors reputation significantly influence on audit delay of manufacturing companies listed in Indonesia Stock Exchange period 2010 until 2015  Keywords: Firm size, ROA, DAR, Reputation Auditor and Audit Delay

scholarly journals PENGARUH MOTIVASI, KOMUNIKASI DAN DISIPLIN TERHADAP KEPUASAN KERJA PT PLN (Persero) P3B SUMBAGUT

2018 ◽  
Author(s):  
Ahmad Saputra
Keyword(s):  
Job Satisfaction ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Positive Influence ◽  
Test Results ◽  
Analysis Model ◽  
Independent Variables ◽  
Positive Effect

This study aims to determine the effect of motivation, communication and discipline of work on job satisfaction of employees at PT PLN (Persero) P3B Sumatera UPB Sumbagut. The analysis model used is multiple linear regression. The conclusion that can be drawn from the test results, which is in partial motivation has a positive influence on job satisfaction, communication has a positive effect on job satisfaction while working discipline variable has a positive effect on job satisfaction. Simultaneously, all the independent variables affect the dependent variable

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUTUSAN PEMBELIAN PROLL TAPE PADA UD. PRIMADONA JEMBER

2016 ◽  
Vol 15 (2) ◽  
Author(s):  
Shanti Maulina Ningrum ◽  
Ratih Puspitorini Y. A. ◽  
Wenny Dhamayanthi
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Multiple Linear Regression Model ◽  
Regression Testing ◽  
Purchase Decision ◽  
Purchasing Decisions ◽  
Validity And Reliability ◽  
Statistical Software ◽  
Factors Affecting ◽  
Independent Variables

This research title is Factors - Factors Affecting Purchase Decision  Proll Tape in UD. Primadona Jember .The purpose of this research is to analyze and test the effect of independent variables simultaneously, partially and the variables that affect the dominant on purchasing decisions proll tape. This study took a sample of 40 respondents. Data were analyzed using statistical software SPSS version 16 with multiple linear regression model. Before analyzing the multiple linear regression to tested the validity and reliability. The results of the research conducted showed that regression testing F test showed that all independent variables have a significant effect on purchasing decisions. Regression testing test showed that the independent variables that affect the purchasing decisions of the variable packaging. While independent variables were not significant effect of variable price and taste. Dominant variable in affecting purchasing decisions in UD. Primadona is variable packaging.

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