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All Journal Journal of Mathematical and Fundamental Sciences Journal of Engineering and Technological Sciences Indonesia Symposium on Computing KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Desimal: Jurnal Matematika Limits: Journal of Mathematics and Its Applications Journal of Research in Mathematics Trends and Technology Jurnal Teknik Informatika (JUTIF) MATHunesa: Jurnal Ilmiah Matematika Jurnal Siger Matematika Jurnal Matematika Integratif
Aang Nuryaman
Universitas Lampung
Astronomy Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Simulasi Numerik Proses Pendinginan pada Media Berpori dengan Memvariasikan Syarat Batas Aang Nuryaman
Indonesia Symposium on Computing Indonesian Symposium on Computing 2014/Seminar Nasional Ilmu Komputasi Teknik Informatika (SNIKTI)
Publisher : Indonesia Symposium on Computing

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Proses pendinginan dalam media berpori dibangun oleh persamaan konvektif-difusi dengan disertasi syarat awal dan syarat batas tertentu. Paper ini menyajikan simulasi numerik dinamika/distribusi suhu pada media berpori yang mengalami pendinginan dengan cara mengalirkan fluida melalui celah kecil. Berbagai variasi laju alir fluida dikombinasikan dengan variasi syarat batas di ujung kanan media berpori akan dikaji pengaruhnya terhadap distribusi suhu.
A Singular Perturbation Problem for Steady State Conversion of Methane Oxidation in a Reverse Flow Reactor Aang Nuryaman; Agus Yodi Gunawan; Kuntjoro Adji Sidarto; Yogi Wibisono Budhi
Journal of Mathematical and Fundamental Sciences Vol. 44 No. 3 (2012)
Publisher : Institute for Research and Community Services (LPPM) ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.sci.2012.44.3.7

Abstract

The governing equations describing methane oxidation in a reverse flow reactor are given by a set of convective-diffusion equations with a nonlinear reaction term, where temperature and methane conversion are dependent variables. In this study, the process is assumed to be a one-dimensional pseudohomogeneous model and takes place with a certain reaction rate in which thewhole process ofthereactor is still workable. Thus, the reaction rate can proceed at a fixed temperature. Under these conditions, we can restrict ourselves to solving the equations for the conversion only. From the available data, it turns out that the ratio of the diffusion term to the reaction term is small. Hence, this ratio is considered as a small parameter in our model and this leads to a singular perturbation problem. Numerical difficulties will be found in the vicinity of a small parameter in front of a higher order term. Here, we present an analytical solutionby means of matched asymptotic expansions. The result shows that, up to and including the first order of approximation, the solution is in agreement with the exact and numerical solutions of the boundary value problem.
Simulasi Jumlah Klaim Agregasi Berdistribusi Poisson Dengan Besar Klaim Berdistribusi Gamma dan Rayleigh Rudi Ruswandi; Aang Nuryaman; Subian Saidi
Limits: Journal of Mathematics and Its Applications Vol 17, No 2 (2020)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v17i2.6642

Abstract

A claim is a transfer of risk from the insured to the guarantor. Claims that occur individually are called individual claims, whereas collections of individual claims are called aggregation claims in a single period of vehicle insurance. Aggregation claims consist of a pattern of the number and amount (nominal value) of individual claims, so that the model of aggregation claims is formed from each distribution of the number and amount of claims. The distribution of claims is based on the probability density function and the cumulative density function. One method that can be used to obtain a claim aggregation model is to use convolution, which is by combining the distribution of the number of claims and the distribution of the amount of claims so that the expected value can be obtained to predict the value of pure premiums. In this paper, aggregation claim modeling will be carried out with the number of claims distributed Poisson and the amount of claims distributed Gamma. As comparison, we compare it with claim amount distributed Rayleigh. By using VaR (value at risk) and MSE (Mean Square Error) indicators, the results of the analysis show that the Rayleigh distribution is better used for distributing data that has extreme values.
Variational homotopy perturbation method for solving systems of homogeneous linear and nonlinear partial differential equations Atika Faradilla; Aang Nuryaman; Asmiati Asmiati; Dewi Rakhmatia Nur
Desimal: Jurnal Matematika Vol 4, No 2 (2021): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (381.991 KB) | DOI: 10.24042/djm.v4i2.7825

Abstract

The variational homotopy perturbation method is developed by combining variational iteration method and homotopy perturbation method. Variational iteration method has an efficient process in solving a wide variety of equations and systems of equations. Meanwhile, homotopy perturbation method yields a very rapid convergence of the solution series in most cases. The developed method, variational homotopy perturbation method, took full advantage of both methods. In this study, we described an application of the variational homotopy perturbation method to solve systems of homogeneous partial differential equations. Here we consider some initial value problems of homogeneous partial differential equation systems with two and three variables. The results show that the obtained solution using this method was in agreement with the solution using the homotopy analysis method and variational iteration method, which prove the validity of the variational homotopy perturbation method when applied to systems of partial differential equations.
An Analytical Solution Of 1-D Pseudo Homoneneous Model For Oxidation Reaction Using Homotopy Perturbation Method Aang Nuryaman
Journal of Research in Mathematics Trends and Technology Vol. 1 No. 1 (2019): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v1i1.751

Abstract

In this paper, we propose an analytical solution of convective-diffusion equation that derived from an oxidation reaction in a chemical reactor. Here, concentration of feed gas as dependent variable. In this study, the reaction are assumed to be a one-dimensional pseudo homogeneous model and it is evaluated at a certain reaction rate. By rescaling process, the nonlinear term of the reaction rate can be approximated by a linear term, resulting a linear convective-diffusion equation with an initial condition and a set of boundary conditions. Here, we present an analytic solution of the initial condition and the boundary conditions using the homotopy perturbation method. The results show that at the end of the reactor, the solution is in agreement with numerical solution of the initial and boundary conditions.
Desain dan Analisis Geometri Propellant Grain Configuration pada Roket Padat Muhammad Ihsan Abyan; Aang Nuryaman; Bagus Hayatul Jihad; Soleh Fajar Junjunan
Jurnal Siger Matematika Vol 1, No 2 (2020)
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (378.087 KB) | DOI: 10.23960/jsm.v1i2.2677

Abstract

This article examine mathematical model of propellant grain configuration to obtain the appropriate burning area in sonda rocket. Sonda roket is experimental rocket that created by Pustekroket LAPAN to support research on space sector with altitude as the target of assessment. Burning area for hollow grain, wagon wheel grain, star grain are analysed analytically through mathematical modelling. Than the results are compared by manual calculation using SolidWork. The results show that burning area of three types of grain did not show a significant difference between these two methods.
Design Optimization of Propellant Grain and Nozzle Contour to Improve Performance of Solid Rocket Propulsion Muhammad Ihsan Abyan; Aang Nuryaman; Bagus Hayatul Jihad; Soleh Fajar Junjunan; Asmiati Asmiati
Journal of Engineering and Technological Sciences Vol. 54 No. 5 (2022)
Publisher : Institute for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2022.54.5.8

Abstract

A rocket is a spacecraft, guided missile, or flying vehicle that boosted by a chemical reaction resulting from the combustion of propellant in the rocket motor. One of the essential parameters in the development of rocket motors is design optimization to improve the propulsion performance of the rocket. Increasing the propulsion performance of the rocket will increase the flight performance of the rocket, in terms of its maximum range or the altitude of the rocket trajectory. This study examined the determination of the design parameter values of a rocket motor by looking at it as an optimization problem with constraints. The problem studied was limited to the case of the second-stage rocket motor. A genetic algorithm was used to solve the resulting optimization problem of propellant grain configuration cases and a characteristic method for designing the bell nozzle. The results obtained indicated an increase in total impulse by 10% compared to the results before optimization.
IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORK (ANN) USING BACKPROPAGATION ALGORITHM BY COMPARING FOUR ACTIVATION FUNCTIONS IN PREDICTING GOLD PRICES Dian Kurniasari; Ranti Vidia Mahyunis; Warsono Warsono; Aang Nuryaman
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 10, No 1 (2023)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v10i1.587

Abstract

The trend in global currency values is speedy and fluctuating due to the recession caused by the Covid-19 pandemic. That causes investors to flock to buy gold assets. Therefore, it is necessary to predict the price of gold from a business and academic perspective to obtain a reasonable gold price prediction model. This study applies the Backpropagation Algorithm by determining the best ANN model structure based on four activation functions: Sigmoid, Tanh, ReLU, and Linear, as well as learning rate values, namely 0.01 and 0.001. The results are the best ANN model structure with four nodes in the input layer, four nodes in the hidden layer and the output layer using the Linear activation function and a learning rate of 0.01. Based on the structure of the model, the MSE value is 0.00051, the MAPE value is 1.9798%, and the accuracy is 98%.Keywords: Artificial Neural Network, Backpropagation, Gold Price Prediction, Activation Function, Model Structure Trend nilai mata uang global sangat cepat dan fluktuatif akibat terjadinya resesi yang disebabkan oleh pandemi Covid-19. Hal ini menyebabkan, para investor berbondong-bondong untuk membeli aset emas. Oleh sebab itu, perlu dilakukan prediksi harga emas, baik dari perspektif bisnis maupun akademis agar memperoleh model prediksi harga emas yang baik. Penelitian ini menerapkan Algoritma Backpropagation dengan menentukan struktur model ANN terbaik berdasarkan empat fungsi aktivasi yaitu, Sigmoid, Tanh, ReLU, dan Linear serta nilai learning rate, yaitu 0,01 dan 0,001. Hasil yang diperoleh berupa struktur model ANN terbaik dengan empat node pada input layer, empat node pada hidden layer dan output layer dengan menggunakan fungsi aktivasi Linear dan learning rate sebesar 0,01. Berdasarkan struktur model tersebut, diperoleh nilai MSE sebesar 0.00051, nilai MAPE sebesar 1,9798% dan akurasi sebesar 98%.Kata Kunci: Artificial Neural Network, Backpropagation, Prediksi Harga Emas, Fungsi Aktivasi, Struktur Model
IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORK WITH BACKPROPAGATION ALGORITHM FOR RATING CLASSIFICATION ON SALES OF BLACKMORES IN TOKOPEDIA Dalfa Habibah Nurul Aini; Dian Kurniasari; Aang Nuryaman; Mustofa Usman
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.2.539

Abstract

The rating assessment classification contains feedback from consumers, which is given in the form of stars which aims to assess a product. However, the amount of data in the classification process often have differences in each class or is called an imbalanced dataset. These problems can affect the classification results. An imbalanced dataset can be overcome by applying random oversampling. To classify the rating assessment, this study proposes the Neural network method, which has a good accuracy level with the backpropagation algorithm and applies random oversampling to overcome the unbalanced amount of data. The results indicate that the neural network method with the backpropagation algorithm can classify the available data with an accuracy level of 85%. The application of resampling data using random oversampling and determining the amount of distribution of training data, testing data, number of epochs and the correct number of batch sizes affect the results obtained.
IMPLEMENTASI METODE BACKPROPAGATION NEURAL NETWORK DALAM MERAMALKAN TINGKAT INFLASI DI INDONESIA Ahmad Rizki Wiranto; Eri Setiawan; Aang Nuryaman; Mustofa Usman
MATHunesa: Jurnal Ilmiah Matematika Vol 11 No 1 (2023)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v11n1.p8-16

Abstract

Peramalan merupakan upaya dalam memperkirakan sesuatu di masa depan berdasarkan pada pola data atau informasi di masa lalu. Autoregressive Integrated Moving Average (ARIMA), Exponential Smoothing, dan Seasonal Autoregressive Integrated Moving Average (SARIMA) merupakan beberapa metode yang sering digunakan dalam peramalan data deret waktu. Namun, metode tersebut memiliki kelemahan yaitu data yang digunakan harus stasioner serta akurasi yang dihasilkan kurang baik. Untuk mengatasi kelemahan tersebut, peneliti banyak yang menerapkan metode Jaringan Syaraf Tiruan salah satunya Backpropagation Neural Network. Metode Backpropagation Neural Network sangat baik digunakan dalam peramalan bidang ekonomi. Masalah ekonomi di Indonesia yang sampai saat ini masih menjadi permasalahan besar adalah inflasi. Dalam kajian ini, dilakukan peramalan inflasi di Indonesia menggunakan data inflasi periode Januari 2000 hingga Oktober 2022. Hasil yang diperoleh menunjukan pembagian data terbaik yaitu 50% training dan 50% testing dengan menggunakan fungsi aktivasi sigmoid biner didapatkan arsitektur terbaik yaitu 12-21-1 dengan nilai Mean Square Error (MSE) pada tahapan training sebesar 0,00067535 dan pada tahapan testing yaitu 0,0767. Setelah dilakukan peramalan, diperoleh bahwa inflasi tertinggi terjadi pada bulan Oktober 2023 sebesar 0,5579 serta peramalan inflasi terkecil terjadi pada Februari 2023 sebesar 0,203.
Co-Authors . Wamiliana Agus Yodi Gunawan Ahmad Faisol Ahmad Faisol Ahmad Rizki Wiranto Asmiati Asmiati Asmiati Asmiati Atika Faradilla Bagus Hayatul Jihad Bagus Hayatul Jihad Citra Puspa Tria Dalfa Habibah Nurul Aini Dewi Rakhmatia Nur Dian Kurniasari Dina Eka Nurvazly Eri Setiawan Eri Setiawan Fathudin Fathudin Ismawati Ismawati Kuntjoro Adji Sidarto La Zakaria La Zakaria Mega Putri Muhammad Ihsan Abyan Muhammad Ihsan Abyan Mustofa Usman Mustofa Usman Nabilla Yolanda Paramitha Notiragayu Notiragayu Ranti Vidia Mahyunis Raratia ulsa Alfian Rudi Ruswandi Saidi, Subian Saiful Rohman Soleh Fajar Junjunan Soleh Fajar Junjunan Warsono Warsono Warsono Warsono Widiarti Widiarti Yogi Wibisono Budhi