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All Journal Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Limits: Journal of Mathematics and Its Applications
Clarine Alfiani
Universitas Diponegoro
Computer Science & IT Decision Sciences, Operations Research & Management Education Mathematics

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PENERAPAN FUZZY GOAL PROGRAMMING DALAM PENGOPTIMALAN PERENCANAAN PRODUKSI Clarine Alfiani; Melyatul Zavina; Uswatun Khasanah; Muhammad Nur Fadli; Annisa Indahsari
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 3 No. 2 (2022): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v3i2.143

Abstract

Production planning is a very important activity for companies in considering production factors ranging from the number of products that must be produced, when the product must be completed, and other things needed. Improper production planning risks causing losses to the company because the use of production costs and profit estimates are not optimized. One method that can be used in optimizing production planning is the fuzzy goal programming method. Fuzzy goal programming is an extension of linear programming that can solve problems of more than one goal in the presence of target constraints. This study aims to examine and apply the fuzzy goal programming method which is solved by the simplex method in Ayune Kitchen production planning by maximizing revenue and minimizing raw material costs. The data used in this study include product data (comb bread, dulce, brulee, mentai, lasagna, and briyani rice), production prices, and raw materials for making products from Ayune Kitchen which will be analyzed using linear programming and fuzzy goal programming methods. simplex. The result of this research is the optimal income that will be obtained by Ayune Kitchen is Rp. 8.830.000 and the optimal expenditure incurred by Ayune Kitchen to purchase raw materials is Rp. 6.687.821
Perbandingan Metode Euler - Estimasi Galat Neural Network dan Metode Runge Kutta Orde 4 dalam Menyelesaikan Persamaan Diferensial Biasa Linear Ratna Herdiana; Clarine Alfiani
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 2 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 2 Edisi Ju
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i2.3467

Abstract

Linear ordinary differential equations are a type of differential equation that is generally easy to solve analytically when the function on a partial integral has a simple form. However, when the function is a difficult function, it requires other methods such as numerical methods and methods adapted from neural networks because analytical methods can only be used when the problem has a simple geometric interpretation. This study involves the Euler method followed by error estimation using neural networks and the Runge-Kutta Orde-4 method as a comparison. The comparison was carried out by solving four equations which were then analyzed for the results and errors in each method based on the graphs generated and the MAPE criteria. The results of the study based on graphs show that the error generated by the method with error estimation using neural networks is more stable than the 4th Order Runge-Kutta method. In addition, based on the results of calculations with the MAPE criteria, the error estimation method using neural networks produces a very high level of accuracy in the category, while the 4th Order Runge-Kutta method produces a level of accuracy in two categories, namely the very high and reasonable categories
Co-Authors Annisa Indahsari Melyatul Zavina Muhammad Nur Fadli Ratna Herdiana Uswatun Khasanah