Mathematicshttps://repository.unri.ac.id/handle/123456789/942019-11-21T17:29:05Z2019-11-21T17:29:05ZMETODE ITERASI BERORDE EMPAT UNTUK MENEMUKAN AKAR GANDA PERSAMAAN NONLINEARHasibuan, Risda Wardanihttps://repository.unri.ac.id/handle/123456789/98112019-08-15T03:30:57Z2019-08-15T00:00:00ZMETODE ITERASI BERORDE EMPAT UNTUK MENEMUKAN AKAR GANDA PERSAMAAN NONLINEAR
Hasibuan, Risda Wardani
This article discusses a new iterative method for finding multiple roots of nonlinear
equations with known multiplicity. This method is obtained by combining the
modified Newton’s method and the weighted Newton’s method for multiple roots.
Analytically it is showed using the Taylor’s expansion, the geometric series, and
the binomial series that the iterative method has a fourth order of convergence.
A special case of the proposed method is also considered. Numerical comparisons
shows that the proposed method can be used as an alternative method in obtaining
multiple roots of nonlinear equations.
2019-08-15T00:00:00ZMODEL REGRESI ADJACENT CATEGORIES DAN PROPORTIONAL ODDS MENGGUNAKAN RESPON ORDINALNurmaida, Nurmaidahttps://repository.unri.ac.id/handle/123456789/97522019-07-22T08:42:13Z2019-07-22T00:00:00ZMODEL REGRESI ADJACENT CATEGORIES DAN PROPORTIONAL ODDS MENGGUNAKAN RESPON ORDINAL
Nurmaida, Nurmaida
This article discusses the regression models with ordinal respon that are adjacent
categories (AC) model and proportional odds (PO) model. The estimated regression
coefficient is obtained through maximum likelihood which is used to calculate the
relative risk for each model. Futhermore, the likelihood ratio test is used to check
the significance of explanatory variable in the model.
Data analysis and simulation have been conducted using R version 3.4.3. We use
a small cell lung cancer data to check the relative risk of tumour respon to patients
receiving one of two therapy strategies and sex of patients. Simulation shows that
AC model is slightly bettter to reject null hipothesis when p-value < 0.05 for larger
sample size than PO model while in contrary for a smaller sample size.
2019-07-22T00:00:00ZKOMBINASI METODE ABABNEH DAN METODE NEWTON DENGAN ORDE KONVERGENSI OPTIMAL UNTUK MENYELESAIKAN PERSAMAAN NONLINEARKaini, Iska Lailatulhttps://repository.unri.ac.id/handle/123456789/97502019-07-22T08:31:48Z2019-07-22T00:00:00ZKOMBINASI METODE ABABNEH DAN METODE NEWTON DENGAN ORDE KONVERGENSI OPTIMAL UNTUK MENYELESAIKAN PERSAMAAN NONLINEAR
Kaini, Iska Lailatul
This article discusses an iterative method for solving nonlinear equations, by com-
bining Ababneh's iterative method of order four with Newton's iterative method.
The method has eight order of convergence with three function evaluations and one
rst derivative function evaluation so that based on Traub's conjecture the method
is optimal. Numerical comparisons show that this method is comparable to the
other eighth methods.
2019-07-22T00:00:00ZMETODE BERTIPE NEWTON DENGAN ORDE KONVERGENSI (k+2) UNTUK MENYELESAIKAN PERSAMAAN NONLINEAR BERTIPE f (0)=0Pratama, Ilham Mulyahttps://repository.unri.ac.id/handle/123456789/97492019-07-22T08:29:06Z2019-07-22T00:00:00ZMETODE BERTIPE NEWTON DENGAN ORDE KONVERGENSI (k+2) UNTUK MENYELESAIKAN PERSAMAAN NONLINEAR BERTIPE f (0)=0
Pratama, Ilham Mulya
This article discusses Newton-type methods with (k + 2) order of convergence for
solving a nonlinear equation of type f(0) = 0, where k is the number of terms in the
generating series. The Newton-type methods require two function evaluations per
iteration. From some computational tests carried out it can be concluded that the
Newton-type method has a high order of convergence and a high index of efficiency.
2019-07-22T00:00:00Z