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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI ULIL ALBAB JURNAL HANDAYANI PGSD FIP UNIMED Jurnal Riset Rumpun Ilmu Pendidikan (JURRIPEN)
Lasker Pangarapan Sinaga
Universitas Negeri Medan
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Journal : Jurnal Riset Rumpun Ilmu Pendidikan (JURRIPEN)

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ANALISIS OPTIMISASI PROGRAM KUADRATIK DENGAN FUNGSI PENALTY Roberto Parujian Sitanggang; Lasker Pangarapan Sinaga
JURNAL RISET RUMPUN ILMU PENDIDIKAN Vol. 2 No. 1 (2023): April : Jurnal Riset Rumpun Ilmu Pendidikan
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurripen.v2i1.812

Abstract

This study aims to analyze the optimality of a quadratic program model using the penalty function. The analysis is carried out in each case that has been made so that in each case optimal results are obtained. There are many methods that can be used to solve the quadratic program problem but in terms of the number of iterations, this research uses the penalty function and then implements it into the Matlab programming language. The results obtained in this study indicate that by using the penalty function as a parameter, the optimal value of a function can be obtained. The results of the analysis will also be more optimal by using the lagrange method depending on the parameter values obtained.
REKONSTRUKSI MODEL PROGRAM NONLINIER DENGAN FUNGSI POLINOMIAL MENJADI BENTUK PROGRAM KUADRATIK Amar Pilenon Sinaga; Lasker Pangarapan Sinaga
JURNAL RISET RUMPUN ILMU PENDIDIKAN Vol. 2 No. 1 (2023): April : Jurnal Riset Rumpun Ilmu Pendidikan
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurripen.v2i1.814

Abstract

The purpose of this research to revisits methods that are more effective in nonlinear Optimization with single variable polynomial functions at high degrees. Models with linear objective functions and constraint functions are Polynomials of third, fourth and fifth degree reconstructed into subproblems that are easier to solve, namely quadratic programs, using bilinear Auxiliary Functions and solved by MATLAB simulations. The method used is the development of Tawarmalani & Sahinidis' research regarding relaxation with Auxiliary Functions. Examples of nonlinear Optimization with polynomial functions are also given to illustrate the implementation of this algorithm. The results of the research show that the application of the development reconstruction method produces a global solution that is no better than the solution to the original problem so that it is not an effective alternative method to use.
Co-Authors Agustin Richardo Josua Nababan Amar Pilenon Sinaga Ceria Clara Simbolon Desrinawati Tindaon Hamidah Nasution July Hartiny Marlina Setia Sinaga Oktariani Purba Roberto Parujian Sitanggang Willyam Daniel Sihotang