Garuda - Garba Rujukan Digital

p-Index From 2020 - 2025

1.431

P-Index

This Author published in this journals

All Journal E-Jurnal Matematika The Journal of Experimental Life Sciences (JELS) Telematika : Jurnal Informatika dan Teknologi Informasi Journal of Innovation and Applied Technology Natural B Jurnal Berkala Epidemiologi Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Prosiding Seminar Nasional Teknoka Jurnal Irigasi Indonesian Journal of Electrical Engineering and Computer Science COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat

Anam, Syaiful

Brawijaya University

Author-ID : 1175744

Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Mathematics Medicine & Pharmacology Neuroscience Public Health Social Sciences

Published : 23 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3

Backpropagation with BFGS Optimizer for Covid-19 Prediction Cases in Surabaya Zuraidah Fitriah; Mohamad Handri Tuloli; Syaiful Anam; Noor Hidayat; Indah Yanti; Dwi Mifta Mahanani
Telematika Vol 18, No 2 (2021): Edisi Juni 2021
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v18i2.5454

Covid-19 is a new type of corona virus called SARS-CoV-2. One of the cities that has contributed the most to infected Covid-19 cases in Indonesia is Surabaya, East Java. Predicting the Covid-19 is the important thing to do. One of the prediction methods is Artificial Neural Network (ANN). The backpropagation algorithm is one of the ANN methods that has been successfully used in various fields. However, the performance of backpropagation is depended on the architecture and optimization method. The standard backpropagation algorithm is optimized by gradient descent method. The Broyden - Fletcher - Goldfarb - Shanno (BFGS) algorithm works faster then gradient descent. This paper was predicting the Covid-19 cases in Surabaya using backpropagation with BFGS. Several scenarios of backpropagation parameters were also tested to produce optimal performance. The proposed method gives better results with a faster convergence then the standard backpropagation algorithm for predicting the Covid-19 cases in Surabaya.

Peningkatan Kemampuan Perangkat Desa Gondowangi Kecamatan Wagir Kabupaten Malang Dalam Pengelolaan Sistem Informasi Data Kependudukan Terintegrasi Website Zuraidah Fitriah; Noor Hidayat; Trisilowati Trisilowati; Syaiful Anam; Candra Dewi
Journal of Innovation and Applied Technology Vol 7, No 1 (2021)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jiat.2021.007.01.15

Dalam observasi awal diperoleh informasi tentang pengelolaan sistem informasi data kependudukan di desa Gondowangi belum dilakukan secara terintegrasi, dalam hal ini hanya dilakukan secara manual. Desa Gondowangi telah memiliki website, namun pengelolaan dilakukan oleh pihak luar perangkat desa, sehingga penyampaian informasi melalui website tersebut belum optimal. Agar pengelolaan website bisa lebih optimal, maka harus dilakukan peningkatan kemampuan perangkat desa dalam mengelola website (sebagai admin) dan mengintegrasikan hasil pengolahan data kependudukan dengan website. Dalam makalah ini diuraikan tentang upaya meningkatkan kemampuan perangkat desa Gondowangi dalam pengelolaan sistim informasi data kependudukan yang terintegrasi dengan website Desa Gondowangi. Pengelolaan dan pengolahan data dilakukan dengan menggunakan aplikasi yang tersedia pada Google, dalam hal ini Google Application.

Enzymatic Reaction Model Parameter Estimation of Biodiesel Synthesis Using Particle Swarm Optimization Syaiful Anam; Indah Yanti; Wuryansari Muharini K.
Natural B, Journal of Health and Environmental Sciences Vol 1, No 1 (2011)
Publisher : Natural B, Journal of Health and Environmental Sciences

The increasing number of vehicles and industries that emit exhaust gas emissions that cause air pollution close to the threshold of a dangerous man. Oil exploration major cause rapid depletion of petroleum. The discovery of biodiesel provides an alternative solution to the above, because biodiesel can reduce exhaust emissions and is a renewable alternative energy. Synthesis biodiesel can be done through an enzyme reaction that utilizes so-called biodiesel synthesis enzymatic reaction. Valid model enzymatic reaction is the key in the process of biodiesel synthesis reaction. This enzymatic reaction model contains the parameters to be estimated. Therefore, the determination of the parameters (parameter estimation) is an important enzyme kinetic. Parameter estimation can be performed using local optimization algorithms, but this algorithm has the major drawback is the optimal value obtained is a local optimal value. Therefore, in this research have been applied to global optimization algorithm, Particle Swarm Optimization for parameter estimation because it has the ability to find solutions quickly. Based on the simulation results obtained by the best parameter estimates as follows: k1=0.05000000000, k2=0.11000000000, k3=0.215000000000, k4=1.22799999999995, k5=0.24200000000000, k6=0.007000000000 and Sum Square Error is 2.51 x 10-27.

MODIFIED ARMIJO RULE ON GRADIENT DESCENT AND CONJUGATE GRADIENT ZURAIDAH FITRIAH; SYAIFUL ANAM
E-Jurnal Matematika Vol 6 No 3 (2017)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2017.v06.i03.p166

Armijo rule is an inexact line search method to determine step size in some descent method to solve unconstrained local optimization. Modified Armijo was introduced to increase the numerical performance of several descent algorithms that applying this method. The basic difference of Armijo and its modified are in existence of a parameter and estimating the parameter that is updated in every iteration. This article is comparing numerical solution and time of computation of gradient descent and conjugate gradient hybrid Gilbert-Nocedal (CGHGN) that applying modified Armijo rule. From program implementation in Matlab 6, it's known that gradient descent was applying modified Armijo more effectively than CGHGN from one side: iteration needed to reach some norm of the gradient (input by the user). The amount of iteration was representing how long the step size of each algorithm in each iteration. In another side, time of computation has the same conclusion.

Multispectral Imaging and Convolutional Neural Network for Photosynthetic Pigments Prediction Kestrilia Prilianti; Ivan C. Onggara; Marcelinus A.S. Adhiwibawa; Tatas H.P. Brotosudarmo; Syaiful Anam; Agus Suryanto
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

The evaluation of photosynthetic pigments composition is an essential task in agricultural studies. This is due to the fact that pigments composition could well represent the plant characteristics such as age and varieties. It could also describe the plant conditions, for example, nutrient deficiency, senescence, and responses under stress. Pigment role as light absorber makes it visually colorful. This colorful appearance provides benefits to the researcher on conducting a nondestructive analysis through a plant color digital image. In this research, a multispectral digital image was used to analyze three main photosynthetic pigments, i.e., chlorophyll, carotenoid, and anthocyanin in a plant leaf. Moreover, Convolutional Neural Network (CNN) model was developed to deliver a real-time analysis system. Input of the system is a plant leaf multispectral digital image, and the output is a content prediction of the pigments. It is proven that the CNN model could well recognize the relationship pattern between leaf digital image and pigments content. The best CNN architecture was found on ShallowNet model using Adaptive Moment Estimation (Adam) optimizer, batch size 30 and trained with 15 epoch. It performs satisfying prediction with MSE 0.0037 for in sample and 0.0060 for out sample prediction (actual data range -0.1 up to 2.2).

Pemetaan Trase Jaringan Irigasi Melalui Analisis Geospasial (Studi Kasus Daerah Irigasi Cibuluh, Jawa Barat) Abu Bakar Sambah; Dwi Agus Kuncoro; Syaiful Anam
Jurnal Irigasi Vol 12, No 1 (2017): Jurnal Irigasi
Publisher : Balai Teknik Irigasi

Planning of irrigation canal has always faced the problems due to the overlapping of different land use. Irrigation planning should consider the irrigation canals surrounding different land use. Optimization of the determination of the irrigation network must be applied through the assumption of the physical condition of topographical as well as the proximity between irrigation canal and area of irrigation. The aims of this study were: (1) Mapping existing condition of irrigation canals in DI Cibuluh related to the land use and topography of the study area; (2) Mapping and determining the optimal trace irrigation networks based on spatial analysis of the existing land use and topographical characteristics; (3) Establish a simulation concepts of re-classification related to irrigation services area based on the elevation of the study area using geospatial analysis. The study was conducted through geospatial analysis methods in Geographic Information Systems. Digital Elevation Models (DEM) were the basic data in simulating irrigation services area. The results showed that there were two overlapping land use type (forests and industrial areas) that should be subtracted from the irrigated areas. Alignment of Irrigation network was planned without overlapping forest and industrial area, so that the planning was more focus on simulation based on the control points by processing adjustments as well as high elevation contour and water height.

Leaders and followers algorithm for constrained non-linear optimization Helen Yuliana Angmalisang; Syaiful Anam; Sobri Abusini
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i1.pp162-169

Leaders and Followers algorithm was a novel metaheuristics proposed by Yasser Gonzalez-Fernandez and Stephen Chen. In solving unconstrained optimization, it performed better exploration than other well-known metaheuristics, e.g. Genetic Algorithm, Particle Swarm Optimization and Differential Evolution. Therefore, it performed well in multi-modal problems. In this paper, Leaders and Followers was modified for constrained non-linear optimization. Several well-known benchmark problems for constrained optimization were used to evaluate the proposed algorithm. The result of the evaluation showed that the proposed algorithm consistently and successfully found the optimal solution of low dimensional constrained optimization problems and high dimensional optimization with high number of linear inequality constraint only. Moreover, the proposed algorithm had difficulty in solving high dimensional optimization problem with non-linear constraints and any problem which has more than one equality constraint. In the comparison with other metaheuristics, Leaders and Followers had better performance in overall benchmark problems.

PARAMETER ESTIMATION OF COVID-19 COMPARTMENT MODEL IN INDONESIA USING PARTICLE SWARM OPTIMIZATION Raqqasyi Rahmatullah Musafir; Syaiful Anam
Jurnal Berkala Epidemiologi Vol. 10 No. 3 (2022): Jurnal Berkala Epidemiologi (Periodic Epidemiology Journal)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbe.V10I32022.283-292

Background: The government established a vaccination program to deal with highly reactive COVID-19 cases in Indonesia. In obtaining accurate predictions of the dynamics of the compartment model of COVID-19 spread, a good parameter estimation technique was required.. Purpose: This research aims to apply Particle Swarm Optimization as a parameter estimation method to obtain parameters value from the Susceptible-Vaccinated-Infected-Recovered compartment model of COVID-19 cases. Methods: This research was conducted in April-May 2020 in Indonesia with exploratory design research. The researchers used the data on COVID-19 cases in Indonesia, which was accessed at covid19.go.id. The data set contained the number of reactive cases, vaccinated cases, and recovered cases. The data set was used to estimate the parameters of the COVID-19 compartment model. The results were shown by numerical simulations that apply to the Matlab program. Results: Research shows that the parameters estimated using Particle Swarm Optimization have a fairly good value because the mean square error is relatively small compared to the data size used. Reactive cases of COVID-19 have decreased until August 21, 2021. Next, reactive cases of COVID-19 will increase until the end of 2021. It is because the virus infection rate of the vaccinated population is positive . If occurs before the stationary point, then the reactive cases of COVID-19 will decrease mathematically. Conclusion: Particle Swarm Optimization methods can estimate parameters well based on mean square error and the graphs that can describe the behavior of COVID-19 cases in the future.

Pelatihan Pembelajaran Matematika Menggunakan Perangkat Lunak Matematika bagi Guru–Guru Matematika SMA/MA di Kabupaten Pasuruan Syaiful Anam; Agus Widodo; Indah Yanti; Corina Karim; Fery Widhiatmoko; Mochamad Hakim Akbar Assidiq Maulana
COMSERVA : Jurnal Penelitian dan Pengabdian Masyarakat Vol. 2 No. 7 (2022): COMSERVA : Jurnal Penelitian dan Pengabdian Masyarakat
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/comserva.v2i7.422

Pasuruan Regency has natural resources that have the potential to be developed, especially in the fields of agriculture, plantations and tourism. In an effort to improve the quality of human resources, improving the level of education is an important thing to do. One way to increase the number of people's participation in education is to improve the quality of learning so that people are interested in taking higher education levels. Learning media with mathematics software is expected to be able to visualize abstract mathematical objects so that it can improve students' understanding and encourage student learning motivation. GeoGebra is a mathematical software to visualize abstract mathematical objects quickly and accurately and can be used as a tool to construct mathematical concepts. One of the objectives of this activity is to improve the ability and skills of mathematics teachers in SMA/MA in Pasuruan Regency in developing mathematics learning media with GeoGebra software to visualize abstract mathematical objects (geometry objects). In addition, to improve the ability and skills of mathematics teachers in SMA/MA in Pasuruan Regency in explaining mathematical material containing geometric objects by utilizing Geogebra. The results of the training showed that the ability and skills of SMA/MA teachers in Pasuruan Regency increased significantly in the development of teaching media and in explaining geometric objects by using Geogebra.

Prediksi Jumlah Penderita COVID-19 di Kota Malang Menggunakan Jaringan Syaraf Tiruan Backpropagation dan Metode Conjugate Gradient Syaiful Anam; Mochamad Hakim Akbar Assidiq Maulana; Noor Hidayat; Indah Yanti; Zuraidah Fitriah; Dwi Mifta Mahanani
Prosiding Seminar Nasional Teknoka Vol 5 (2020): Prosiding Seminar Nasional Teknoka ke - 5
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

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

COVID-19 is an infectious disease caused by infection with a new type of corona virus. This disease is very dangerous and causes death, especially for sufferers who have congenital diseases or who have low immunity. The disease is spread through droplets from the nose or mouth that come out when a person infected with COVID-19 coughs, sneezes or talks. The prediction of the number of COVID-19 sufferers is very important to prevent and combat the spread of this disease. The backpropagation neural network is a method that can be used to solve predictive problems with good results, but its performance is influenced by the optimization method used during training. In general, the optimization method used is the gradient descent method, but this method has slow convergence. The Conjugate Gradient method has very good convergence when compared to the gradient descent method. In this paper, we will discuss how to make a prediction model for the number of COVID-19 sufferers in Malang using the backpropagation neural network and the conjugate gradient method. The experimental results show that the prediction model gets good results when compared to artificial neural networks that are optimized by the gradient descent method.

Co-Authors A.S. Adhiwibawa, Marcelinus Abu Bakar Sambah Agus Suryanto Agus Suryanto Agus Widodo Ahmad Afif Supianto Candra Dewi Corina Karim, Ari Andari Dian Eka Ratnawati Dwi Agus Kuncoro Dwi Febry Indarwati Dwi Mifta Mahanani Faiz Anggiananta Winantoro Fery Widhiatmoko Helen Yuliana Angmalisang Hidayat, Noor Indah Yanti Isti Marlisa Fitriani Ivan C. Onggara Kestrilia Rega Prilianti Marcelinus A.S. Adhiwibawa Mochamad Hakim Akbar Assidiq Maulana Mochamad Hakim Akbar Assidiq Maulana Mochammad Iskandar Ardiyansyah Rochman Mohamad Handri Tuloli Musafir, Raqqasyi Rahmatullah Nur Khilmiyatul Ilmiyah Nyimas Ayu Widi Indriana Onggara, Ivan C. Onky Prasetyo Raden Rizky Widdie Tigusti Revi Anistia Masykuroh Ririn Nirmalasari Sherly Witanto Sobri Abusini Suhhy Ramzini Suryanto, Agus Tatas H.P. Brotosudarmo Trisilowati, Trisilowati Wuryansari Muharini K. Yunita Dwi Alfiyanti Zuraidah Fitriah ZURAIDAH FITRIAH

Title

Found 23 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 23 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 23 Documents
Search