scholarly journals PEMODELAN REGRESI ROBUST S-ESTIMATOR UNTUK PENANGANAN PENCILAN MENGGUNAKAN GUI MATLAB (Studi Kasus : Faktor-Faktor yang Mempengaruhi Produksi Ikan Tangkap di Jawa Tengah)

2019 ◽  
Vol 8 (1) ◽  
pp. 81-92
Author(s):  
Dhea Kurnia Mubyarjati ◽  
Abdul Hoyyi ◽  
Hasbi Yasin
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Least Squares ◽  
Robust Regression ◽  
Ordinary Least Squares ◽  
Predictor Variables ◽  
Fish Production ◽  
Significance Level ◽  
Central Java ◽  
Approximate Estimation

Multiple Linear Regression can be solved by using the Ordinary Least Squares (OLS). Some classic assumptions must be fulfilled namely normality, homoskedasticity, non-multicollinearity, and non-autocorrelation. However, violations of assumptions can occur due to outliers so the estimator obtained is biased and inefficient. In statistics, robust regression is one of method can be used to deal with outliers. Robust regression has several estimators, one of them is Scale estimator (S-estimator) used in this research. Case for this reasearch is fish production per district / city in Central Java in 2015-2016 which is influenced by the number of fishermen, number of vessels, number of trips, number of fishing units, and number of households / fishing companies. Approximate estimation with the Ordinary Least Squares occur in violation of the assumptions of normality, autocorrelation and homoskedasticity this occurs because there are outliers. Based on the t- test at 5% significance level can be concluded that several predictor variables there are the number of fishermen, the number of ships, the number of trips and the number of fishing units have a significant effect on the variables of fish production. The influence value of predictor variables to fish production is 88,006% and MSE value is 7109,519. GUI Matlab is program for robust regression for S-estimator to make it easier for users to do calculations. Keywords: Ordinary Least Squares (OLS), Outliers, Robust Regression, Fish Production, GUI Matlab.

scholarly journals PEMODELAN REGRESI RIDGE ROBUST-MM DALAM PENANGANAN MULTIKOLINIERITAS DAN PENCILAN (Studi Kasus : Faktor-Faktor yang Mempengaruhi AKB di Jawa Tengah Tahun 2017)

2019 ◽  
Vol 8 (1) ◽  
pp. 24-34
Author(s):  
Eka Destiyani ◽  
Rita Rahmawati ◽  
Suparti Suparti
Keyword(s):  
Least Squares ◽  
Robust Regression ◽  
Ordinary Least Squares ◽  
Regression Method ◽  
Predictor Variables ◽  
Healthy Life ◽  
Significance Level ◽  
Central Java ◽  
Regression Parameters

The Ordinary Least Squares (OLS) is one of the most commonly used method to estimate linear regression parameters. If multicollinearity is exist within predictor variables especially coupled with the outliers, then regression analysis with OLS is no longer used. One method that can be used to solve a multicollinearity and outliers problems is Ridge Robust-MM Regression. Ridge Robust-MM  Regression is a modification of the Ridge Regression method based on the MM-estimator of Robust Regression. The case study in this research is AKB in Central Java 2017 influenced by population dencity, the precentage of households behaving in a clean and healthy life, the number of low-weighted baby born, the number of babies who are given exclusive breastfeeding, the number of babies that receiving a neonatal visit once, and the number of babies who get health services. The result of estimation using OLS show that there is violation of multicollinearity and also the presence of outliers. Applied ridge robust-MM regression to case study proves ridge robust regression can improve parameter estimation. Based on t test at 5% significance level most of predictor variables have significant effect to variable AKB. The influence value of predictor variables to AKB is 47.68% and MSE value is 0.01538.Keywords:  Ordinary  Least  Squares  (OLS),  Multicollinearity,  Outliers,  RidgeRegression, Robust Regression, AKB.

scholarly journals ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI VOLUME EKSPOR BIJI KAKAO INDONESIA KE MALAYSIA

2019 ◽  
Vol 13 (1) ◽  
pp. 37-58
Author(s):  
Ilma Yuni Rosita ◽  
Lilis Imamah Ichdayati ◽  
Rizki Adi Puspita Sari
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Least Squares ◽  
International Market ◽  
Ordinary Least Squares ◽  
Cocoa Beans ◽  
Significance Level ◽  
The Real ◽  
Analyze Time Series

This study aims to analyze the factors that affect the volume of Indonesian cocoa exports to Malaysia. Multiple linear regression and ordinary least squares (OLS) were employed to analyze time series of data from 2005 until 2013. Based on the analysis, it is obtained that factors that significantly effect the volume of Indonesian cocoa exports to Malaysia with a significance level (α) five percent are the real prices of Indonesian cocoa exports to Malaysia and the real prices of cocoa beans the international market.

scholarly journals ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI VOLUME EKSPOR BIJI KAKAO INDONESIA KE MALAYSIA

2019 ◽  
Vol 11 (2) ◽  
pp. 161-182
Author(s):  
Ilma Yuni Rosita ◽  
Lilis Imamah Ichdayati ◽  
Rizki Adi Puspita Sari
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Least Squares ◽  
International Market ◽  
Ordinary Least Squares ◽  
Cocoa Beans ◽  
Significance Level ◽  
The Real ◽  
Analyze Time Series

This study aims to analyze the factors that affect the volume of Indonesian cocoa exports to Malaysia. Multiple linear regression and ordinary least squares (OLS) were employed to analyze time series of data from 2005 until 2013. Based on the analysis, it is obtained that factors that significantly effect the volume of Indonesian cocoa exports to Malaysia with a significance level (α) five percent are the real prices of Indonesian cocoa exports to Malaysia and the real prices of cocoa beans the international market.

Robust Weighted Least Squares Estimation of Regression Parameter in the Presence of Outliers and Heteroscedastic Errors

2014 ◽  
Vol 71 (1) ◽  
Author(s):  
Bello Abdulkadir Rasheed ◽  
Robiah Adnan ◽  
Seyed Ehsan Saffari ◽  
Kafi Dano Pati
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Robust Regression ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Least Square ◽  
Model Parameters ◽  
Constant Variance ◽  
Regression Parameters ◽  
M Estimation

In a linear regression model, the ordinary least squares (OLS) method is considered the best method to estimate the regression parameters if the assumptions are met. However, if the data does not satisfy the underlying assumptions, the results will be misleading. The violation for the assumption of constant variance in the least squares regression is caused by the presence of outliers and heteroscedasticity in the data. This assumption of constant variance (homoscedasticity) is very important in linear regression in which the least squares estimators enjoy the property of minimum variance. Therefor e robust regression method is required to handle the problem of outlier in the data. However, this research will use the weighted least square techniques to estimate the parameter of regression coefficients when the assumption of error variance is violated in the data. Estimation of WLS is the same as carrying out the OLS in a transformed variables procedure. The WLS can easily be affected by outliers. To remedy this, We have suggested a strong technique for the estimation of regression parameters in the existence of heteroscedasticity and outliers. Here we apply the robust regression of M-estimation using iterative reweighted least squares (IRWLS) of Huber and Tukey Bisquare function and resistance regression estimator of least trimmed squares to estimating the model parameters of state-wide crime of united states in 1993. The outcomes from the study indicate the estimators obtained from the M-estimation techniques and the least trimmed method are more effective compared with those obtained from the OLS.

scholarly journals Investigation on Quantitative Structure-Activity Relationships of 1,3,4-Oxadiazole Derivatives as Potential Telomerase Inhibitors

2020 ◽  
Vol 17 (1) ◽  
pp. 79-86 ◽  
Author(s):  
Marco Tutone ◽  
Beatrice Pecoraro ◽  
Anna M. Almerico
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Least Squares ◽  
Ordinary Least Squares ◽  
Chemical Information ◽  
Telomerase Inhibition ◽  
Telomerase Inhibitors ◽  
Potential Marker ◽  
Ic50 Values ◽  
Oxadiazole Derivatives

Background:Telomerase, a reverse transcriptase, maintains telomere and chromosomes integrity of dividing cells, while it is inactivated in most somatic cells. In tumor cells, telomerase is highly activated, and works in order to maintain the length of telomeres causing immortality, hence it could be considered as a potential marker to tumorigenesis.A series of 1,3,4-oxadiazole derivatives showed significant broad-spectrum anticancer activity against different cell lines, and demonstrated telomerase inhibition.Methods:This series of 24 N-benzylidene-2-((5-(pyridine-4-yl)-1,3,4-oxadiazol-2yl)thio)acetohydrazide derivatives as telomerase inhibitors has been considered to carry out QSAR studies. The endpoint to build QSAR models is determined by the IC50 values for telomerase inhibition, i.e., the concentration (μM) of inhibitor that produces 50% inhibition. These values were converted to pIC50 (- log IC50) values. We used the most common and transparent method, where models are described by clearly expressed mathematical equations: Multiple Linear Regression (MLR) by Ordinary Least Squares (OLS).Results:Validated models with high correlation coefficients were developed. The Multiple Linear Regression (MLR) models, by Ordinary Least Squares (OLS), showed good robustness and predictive capability, according to the Multi-Criteria Decision Making (MCDM = 0.8352), a technique that simultaneously enhances the performances of a certain number of criteria. The descriptors selected for the models, such as electrotopological state (E-state) descriptors, and extended topochemical atom (ETA) descriptors, showed the relevant chemical information contributing to the activity of these compounds.Conclusion:The results obtained in this study make sure about the identification of potential hits as prospective telomerase inhibitors.

THE PERFORMANCE OF LEVERAGE BASED NEAR NEIGHBOUR-ROBUST WEIGHT LEAST SQUARES IN MULTIPLE LINEAR REGRESSION IN THE PRESENCE OF HETEROSCEDASTIC ERRORS AND OUTLIER

2015 ◽  
Vol 76 (13) ◽  
Author(s):  
Khoo Li Peng ◽  
Robiah Adnan ◽  
Maizah Hura Ahmad
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Least Squares ◽  
Standard Error ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Standard Errors ◽  
Data Sets ◽  
Near Neighbour ◽  
Heteroscedastic Errors

In this study, Leverage Based Near Neighbour–Robust Weighted Least Squares (LBNN-RWLS) method is proposed in order to estimate the standard error accurately in the presence of heteroscedastic errors and outliers in multiple linear regression. The data sets used in this study are simulated through monte carlo simulation. The data sets contain heteroscedastic errors and different percentages of outliers with different sample sizes.  The study discovered that LBNN-RWLS is able to produce smaller standard errors compared to Ordinary Least Squares (OLS), Least Trimmed of Squares (LTS) and Weighted Least Squares (WLS). This shows that LBNN-RWLS can estimate the standard error accurately even when heteroscedastic errors and outliers are present in the data sets.

scholarly journals Determinant of Cocoa Export in Indonesia

2018 ◽  
Vol 7 (3) ◽  
pp. 286-293
Author(s):  
Medha Wardhany ◽  
Fauzul Adzim
Keyword(s):  
International Trade ◽  
Exchange Rate ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Least Squares ◽  
Analytical Method ◽  
Ordinary Least Squares ◽  
Cocoa Beans ◽  
Export Volume ◽  
Us Dollar

International Trade is one of the activities that plays an important role for the economy. Indonesia is one of the countries whose depends on exports. One of the agricultural commodities that become the leading commodity is cocoa. Although it is a main flag export commodity, cocoa farming still has many challenges. The export volume of cocoa beans in the period 1987-2016 increase slightly, but in the last six years the export tend to decrease. The purpose of this study is to analyze the factors that affect the export of cocoa beans. The analytical method used is Multiple Linear Regression with the ordinary least squares rank method (OLS). The results showed that the variables of production have a positive and significant effect with coefficient value of 0.642607. Domestic cocoa price does not affect the export volume of cocoa beans. The international cocoa price variable has a negative and significant effect on export volume of Indonesian cocoa beans with coefficient value of -7,073793. The rupiah exchange rate variable to US Dollar has a positive and significant effect on the export volume of Indonesian cocoa beans with coefficient value of 15.22362. While simultaneously, production variables, domestic cocoa prices, international cocoa prices, and Rupiah exchange rate against US Dollar together affect the export volume of Indonesian cocoa beans.

PENGARUH HARGA DAN BRAND TRUST TERHADAP KEPUTUSAN PEMBELIAN OPPO SMARTPHONE (Studi kasus pada OPPO Store, Sinergy Celular Medan)

2019 ◽  
Vol 14 (1) ◽  
pp. 17
Author(s):  
Andi S Tarigan ◽  
Zulkarnaian Siregar
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Coefficient Of Determination ◽  
Purchase Decision ◽  
Brand Trust ◽  
Significance Level ◽  
Research Hypothesis ◽  
Analysis Technique ◽  
The Relationship

AbstrakPenelitian ini bertujuan untuk mengetahui Pengaruh Harga dan Brand Trust Terhadap Keputusan Pembelian pada Sinergy Celular Medan.Sampel dalam penelitian ini adalah seluruh pengunjung Sinergy Celular Medan sebanyak 77 orang.Teknik pengumpulan data yang digunakan adalah melalui kuesioner (angket) yaitu dengan cara menyebarkan kuesioner kepada sampel (responden) dan mengumpulkannya kembali. Teknik analisis data yang digunakan adalah Regresi Linear Berganda.Sebelum data diregresikan maka terlebih dahulu di uji keterkaitannya antara variabel, datanya diuji menggunakan uji normalitas data, multikolinearitas, dan heterokedastisitas.Serta untuk mengetahui kontribusi faktor Harga dan Brand TrustTerhadap Keputusan Pembelian digunakan rumus Koefisien Determinasi (R2). Hipotesis penelitian diterima apabila t hitung >  t tabel dengan tingkat signifikansi 0,1. Nilai t tabel dalam penelitian ini 1,993. Nilai t hitung variabel X1 sebesar 2,107 t hitung lebih besar dari t tabel maka hipotesis di terima, nilai t hitung variabel X2   sebesar 3,405 t hitung lebih besar dari t tabel maka hipotesis di terima. Kata kunci: Harga, Brand Trust, Keputusan Pembelian AbstractThis study aims to determine the Influence of Price and Brand Trust on Purchasing Decision at Sinergy Celular Medan. The sample in this study is all visitors Sinergy Celular Medan as many as 77 people.Data collection technique used is through questionnaire (questionnaire) that is by distributing questionnaires to the sample (respondent) and collect it back. Data analysis technique used is Multiple Linear Regression. Before the data is diregresikan then first in the test the relationship between variables, the data tested using the test of data normality, multicollinearity, and heterokedastisitas. And to know the contribution of price factors and Brand Trust Against Purchase Decision is used the formula Coefficient of Determination (R2). Research hypothesis accepted if t arithmetic> t table with significance level 0,1. The value of t table in this study is 1,993. Value t arithmetic variable X1 of 2.107 t arithmetic greater than t table then the hypothesis received, the value of t arithmetic variable X2 of 3.405 t arithmetic greater than t table then the hypothesis received. Keywords: Price, Brand Trust, Purchase Decision

PENGARUH PROFITABILITAS, LEVERAGE DAN UKURAN PERUSAHAAN TERHADAP LAMA WAKTU LAPORAN AUDIT

Equity ◽  
2016 ◽  
Vol 19 (1) ◽  
pp. 68
Author(s):  
Syifa Tamara Putri ◽  
Samin Samin
Keyword(s):  
Linear Regression ◽  
Real Estate ◽  
Multiple Linear Regression ◽  
Firm Size ◽  
Sampling Method ◽  
Stock Exchange ◽  
Z Score ◽  
Audit Report ◽  
Significance Level ◽  
Outlier Test

This study aims to test and provide empirical the effect of profitability, leverage and firm size of the audit report lag. The population in this study is a sub company property and real estate sectors listed on the Indonesia Stock Exchange 2012-2014. Sample of 34 companies was selected by purposive sampling method. The data used in this study as much as 102 samples. This study uses several stage of calculation, using outlier test that is by converting the data into a standardized score or so-called z-score. After going through the process of outlier samples were chosen in this study to 93 samples. Analysis of the data using multiple linear regression with a significance level of 5% and determine the hypothesis used t test and f test. The results test showing that profitability, leverage and firm size are simultaneous positive and significant effect on audit report lag. The results test this study indicate that profitability has significance on audit report lag are partial. Meanwhile leverage and firm size has no significance on audit report lag

PENGARUH KUALITAS LAYANAN DAN NILAI PELANGGAN TERHADAP KEPUASAN PELANGGAN

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Ismail Razak, SE., MS. ◽  
Silviana Fadilla Prasevie
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Service Quality ◽  
Multiple Linear Regression ◽  
Customer Value ◽  
Sampling Method ◽  
Analysis Method ◽  
Simple Linear Regression ◽  
Central Java ◽  
Data Analysis Method

The purpose of this study was to analize the impacts of service quality and customer value on the satisfaction of customers. Questionnaires are used to collect data from Boks Café customer in Bumiayu, Kabupaten Brebes, Central java by using scale of Likert. In this study, accident sampling method was used and data analysis method was simple linear regression and multiple linear regression. The results of this study indicated that service quality and customer value positively and significant influenced the satisfaction of customers. The conclution of this study is that customer value was dominant than service quality in influencing the satisfaction of customers

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