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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Evaluation and Research in Education (IJERE) Proceedings of Annual International Conference Syiah Kuala University - Life Sciences & Engineering Chapter Jurnal Pendidikan Teknologi dan Kejuruan Jurnal Didaktik Matematika Journal of Aceh Physics Society Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika Jurnal Inotera MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Ilmiah Pendidikan Matematika Al Qalasadi Journal of Mathematics Technology and Education Jurnal Natural Jurnal Rekayasa elektrika Journal of Educational Management and Learning Journal on Mathematics Education
Marwan Ramli
Program Studi Matematika FMIPA Universitas Syiah Kuala, Banda Aceh
Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Social Sciences Transportation Other

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SHALLOW WATER EQUATION SOLUTION IN 2D USING FINITE DIFFERENCE METHOD WITH EXPLICIT SCHEME Nuraini Nuraini; Syamsul Rizal; Marwan Ramli
Jurnal Natural Volume 17, Number 2, September 2017
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v17i2.7997

Abstract

Abstract. Modeling the dynamics of seawater typically uses a shallow water model. The shallow water model is derived from the mass conservation equation and the momentum set into shallow water equations. A two-dimensional shallow water equation alongside the model that is integrated with depth is described in numerical form. This equation can be solved by finite different methods either explicitly or implicitly. In this modeling, the two dimensional shallow water equations are described in discrete form using explicit schemes.Keyword: shallow water equation, finite difference and schema explisit.REFERENSI 1. Bunya, S., Westerink, J. J. dan Yoshimura. 2005. Discontinuous Boundary Implementation for the Shallow Water Equations. Int. J. Numer. Meth. Fluids. 47: 1451-1468.2. Kampf Jochen. 2009. Ocean Modelling For Beginners. Springer Heidelberg Dordrecht. London New York.3. Rezolla, L 2011. Numerical Methods for the Solution of Partial Diferential Equations. Trieste. International Schoolfor Advanced Studies.4. Natakussumah, K. D., Kusuma, S. B. M., Darmawan, H., Adityawan, B. M. Dan  Farid, M. 2007. Pemodelan Hubungan Hujan dan Aliran Permukaan pada Suatu DAS  dengan Metode Beda Hingga. ITB Sain dan Tek. 39: 97-123.5. Casulli, V. dan Walters, A. R. 2000. An unstructured grid, three-dimensional model based on the shallow water equations. Int. J. Numer. Meth. Fluids. 32: 331-348.6. Triatmodjo, B. 2002. Metode Numerik  Beta Offset. Yogyakarta.
Non-perfect maze generation using Kruskal algorithm MAHYUS IHSAN; DEDI SUHAIMI; MARWAN RAMLI; SYARIFAH MEURAH YUNI; IKHSAN MAULIDI
Jurnal Natural Volume 21 Number 1, February 2021
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v21i1.18840

Abstract

A non-perfect maze is a maze that contains loop or cycle and has no isolated cell. A non-perfect maze is an alternative to obtain a maze that cannot be satisfied by perfect maze. This paper discusses non-perfect maze generation with two kind of biases, that is, horizontal and vertical wall bias and cycle bias. In this research, a maze is modeled as a graph in order to generate non-perfect maze using Kruskal algorithm modifications. The modified Kruskal algorithm used Fisher Yates algorithm to obtain a random edge sequence and disjoint set data structure to reduce process time of the algorithm. The modification mentioned above are adding edges randomly while taking account of the edge’s orientation, and by adding additional edges after spanning tree is formed. The algorithm designed in this research constructs an  non-perfect maze with complexity of  where  and  denote vertex and edge set of an  grid graph, respectively. Several biased non-perfect mazes were shown in this research by varying its dimension, wall bias and cycle bias.
DESIGNING APPLICATION OF ANT COLONY SYSTEM ALGORITHM FOR THE SHORTEST ROUTE OF BANDA ACEH CITY AND ACEH BESAR REGENCY TOURISM BY USING GRAPHICAL USER INTERFACE MATLAB Durisman Durisman; Marwan Ramli; Siti Rusdiana
Jurnal Natural Volume 17, Number 2, September 2017
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v17i2.7920

Abstract

Banda Aceh city and Aceh Besar Regency are two of the leading tourism areas located in the province of Aceh. For travelling, there are some important things to be considered, such as determining schedule and distance of tourism. Every tourist certainly chooses the shortest route to reach the destination since it can save time, energy, and money. The purpose of this reserach is to develop a method that can be used in calculating the shortest route and applied to the tourism of Banda Aceh city and Aceh Besar regency. In this reserach, Ant Colony Optimization algorithm is used to determine the shortest route to tourism of Banda Aceh city and Aceh Besar regency. From the analysis made by using both manual calculation and  GUI MATLAB program application test, the shortest route can be obtained with a minimum distance of 120.85 km in one travel. Based on the test result, the application for tourism (in Banda Aceh city and Aceh Besar regency) shortest route searching built by utilizing the Ant Colony Optimization algorithm can find optimal route. Keyword: tourism, the shortest route, Ant Colony Optimization
Quadratic Programming Approach in the Non-Negatif Matrix Factorization Simbolon, Heri Yusus; Sawaluddin; Ramli, Marwan
Journal of Mathematics Technology and Education Vol. 2 No. 2 (2023): Journal of Mathematics Technology and Education
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jomte.v2i2.15670

Abstract

Non-negative Matrix Factorization is an iteration optimization algorithm. ie to decipher one matrix into several non-negative component matrices. Non-negative Matrix Factorization (FMN) serves to obtain a picture of non-negative data. There is a problem in the Non-negative Matrix Factorization that is optimization at the constraint boundary, where in the optimization solution on the constraint boundary it is necessary to do long iteration and of course very difficult and conquers a long time. Quadratic Programing is an approach to solving linear optimization problems where the constraint is linear function and its purpose function is the square of the decision variable or multiplication of the two decision variables. This method is considered to be an effective method to overcome the optimization in the Non-negative Matrix Factorization.
Key Influences on Students' Academic Success: Insights from Scholarly Research Vitoria, Linda; Ramli, Marwan; Johar, Rahmah; Mawarpury, Marty
Journal of Educational Management and Learning Vol. 2 No. 1 (2024): May 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v2i1.164

Abstract

Literature reveals that there are numerous factors that affect students' academic achievement. These factors range from internal factors with varying degrees of influence. Determining the dominant factors is highly useful as part of the effort and the planning of potential actions regarding what can be done to improve students’ academic achievement. The present study employed a systematic literature review method to identify the dominant factors. Results show that there are four dominant factors that affect students’ academic achievement. They are academic motivation, emotional intelligence, teachers, and peers. This finding confirms the complex nature of the factors that affect students’ academic achievement, which involve internal and external factors. Without disregarding the other factors, these findings suggest that schools and parents should pay close attention to the dominant factors in order to improve students’ achievement.
Study of mathematical models of type 2 diabetes mellitus and its complications MAGHFIRAH, AFIATUN; GANI, BASRI A.; RAMLI, MARWAN; IKHWAN, MUHAMMAD
Jurnal Natural Volume 24 Number 3, October 2024
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v24i3.33482

Abstract

The rapid increase in type 2 diabetes mellitus (DM) cases in Indonesia, driven by hereditary factors and unhealthy lifestyles, poses significant health challenges. This study develops a compartmental model to analyze the progression of type 2 DM and the onset of complications, classifying individuals into susceptible, patients without complications, patients with complications, and those disabled due to complications. The model examines the influence of two key factors on the recovery from complications: habitual factors, including medication adherence, physical activity, dietary habits, smoking history, and environmental factors, such as stress levels, environmental support, patient trust, and compliance. The results indicate that habitual factors have a more substantial impact on mitigating complications compared to environmental factors, suggesting that lifestyle interventions are crucial in improving patient outcomes. The model also shows that an increase in behavioral interactions leading to disease progression results in instability, emphasizing the need for early and consistent behavioral interventions. This research offers valuable insights for healthcare providers and policymakers. By identifying the most influential factors in managing complications, the model can guide the development of targeted interventions that prioritize habitual changes, such as medication adherence and physical activity. Public health strategies can be tailored to emphasize the importance of these habitual factors, potentially reducing the burden of type 2 DM complications. Overall, this study highlights the critical role of personalized, behavior-focused interventions in the management and prevention of complications in patients with type 2 DM, offering a practical framework for improving patient care.
ConciseCarNet: convolutional neural network for parking space classification Ramli, Marwan; Rahman, Sayuti; Bayu Syah, Rahmad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i4.pp4158-4168

Abstract

The car is a mode of transportation that brings numerous benefits to the community. As a result, the growth of vehicles is increasing, which has a negative impact. Some of the negative impacts include noise, air pollution, traffic congestion, and the need for parking spaces. Drivers that drive around looking for parking places increase the negative impact as well as boredom and even worry for the driver. Therefore, the driver needs this information on the availability of parking spaces. A convolutional neural network (CNN) using a camera is one of the best methods that can be used to solve this problem. We built a more efficient CNN architecture for classifying parking spaces, which was named ConciseCarNet. ConciseCarNet uses 33 and 11 convolution filters, which cause fewer parameters than previous architectures. ConciseCarNet has two branches, each with a different branch structure. This branch is designed to generate additional feature variations, which will help improve the accuracy. Based on testing, the accuracy of ConciseCarNet2x outperforms the accuracy of mAlexnet, Carnet, EfficientParkingNet, and you look once (YOLO)+MobilNet architectures, which is 99.37%. ConciseCarNet has fewer parameters, file sizes, and floating point operations (FLOPs) compared to other architectures.
Mathematical model of student learning behavior with the effect of learning motivation and student social interaction Mutiawati; Johar, Rahmah; Ramli, Marwan; Mailizar
Journal on Mathematics Education Vol. 13 No. 3 (2022): Journal on Mathematics Education
Publisher : Universitas Sriwijaya in collaboration with Indonesian Mathematical Society (IndoMS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22342/jme.v13i3.pp415-436

Abstract

This study aims to determine the mathematical model of student learning behavior. The model is built by analogizing the spread of learning behavior with infectious diseases, which is called the SEIR model. The survey was conducted through filling out a questionnaire on the learning behavior of junior high school students with a population of 1,143 students. The results of the simulation model show that the peak of students' vulnerability to changes in learning behavior increases rapidly in the first two days and will be stable when passing the 150th day. The results of the simulation of the SEIR mathematical model with an incubation period of 365 days found that student learning behavior in Non-Boarding Schools will be stable in on day 198, while in Boarding Schools it will be stable on day 201. Infection cases in Boarding Schools fell to 0 on day 25 while in Non-Boarding Schools decreased on day 21, meaning that infections occurring in Boarding Schools were slower and more resistant long, meaning that the influence of the social environment is very significant on student learning behavior. This study also serves as material for policy formulation for the Aceh Provincial Government regarding the junior high school curriculum.
MobileChiliNet: convolutional neural network for chili leaves classification Rahman, Sayuti; Elveny, Marischa; Ramli, Marwan; Manurung, Dionikxon
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp3757-3770

Abstract

Chili pepper (Capsicum annuum) is an important crop in many countries, including Indonesia, which plays an important role in local economy and food production. To meet the high demand, effective agricultural management, especially the diagnosis and treatment of plant diseases, is essential. This study aims to improve the accuracy of chili leaf disease classification while reducing the computational cost so that it can be applied to low-cost smart farming systems. Through the development of the MobileChiliNet architecture, which is the result of pruning and fine-tuning of MobileNetV2, this model achieves the best accuracy, better than other CNNs such as ResNet50 and VGG16. Testing with various optimizers and learning rate schedulers shows that AdamW with PolynomialDecay provides the best performance by increasing the validation accuracy to 96.48%. This approach successfully reduces the computational complexity while maintaining high accuracy, so that it can be implemented in smart farming systems at a lower cost.
Normalization Layer Enhancement in Convolutional Neural Network for Parking Space Classification rahman, sayuti; Ramli, Marwan; Sembiring, Arnes; Zen, Muhammad; Syah, Rahmad B.Y
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 3 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.3871

Abstract

The research problem of this study is the urgent need for real-time parking availability information to assist drivers in quickly and accurately locating available parking spaces, aiming to improve upon the accuracy not achieved by previous studies. The objective of this research is to enhance the classification accuracy of parking spaces using a Convolutional Neural Network (CNN) model, specifically by integrating an effective normalizing function into the CNN architecture. The research method employed involves the application of four distinct normalizing functions to the EfficientParkingNet, a tailored CNN architecture designed for the precise classification of parking spaces. The results indicate that the EfficientParkingNet model, when equipped with the Group Normalization function, outperforms other models using Batch Normalization, Inter-Channel Local Response Normalization, and Intra-Channel Local Response Normalization in terms of classification accuracy. Furthermore, it surpasses other similar CNN models such as mAlexnet, you only look once (Yolo)+mobilenet, and CarNet in the same classification task. This demonstrates that EfficientParkingNet with Group Normalization significantly enhances parking space classification, thus providing drivers with more reliable and accurate parking availability information.
Co-Authors Anugreni, Fera Baafai, Usman Bansu Irianto Ansari Basri A. Gani, Basri A. Bayu Syah, Rahmad CUT D. SYAHRANI DEDI SUHAIMI Durisman Durisman Hafnani Hafnani Herman Mawengkang IKHSAN MAULIDI Irfandi Nu’man Dani Linda Vitoria, Linda M Ikhsan MAGHFIRAH, AFIATUN Mahyus Ihsan Mailizar Mailizar Mailizar Manurung, Dionikxon Mardlijah - Marischa Elveny, Marischa Marty Mawarpury Mohd Iqbal Muttaqin Muhammad Amin Muhammad Ikhwan Muhammad Ikhwan Muhammad Zen, Muhammad Mulkan Iskandar Nasution Mustamam, Mr Muthmainnah Muthmainnah Mutiawati Mutiawati Mutiawati Nuraini Nuraini Nurliadi Nurliadi Poltak Sihombing Rahmah Johar Rahman, Sayuti Reza Wafdan Rhilmanidar Rhilmanidar Rizki Kurniawan Rangkuti Said Munzir Said Munzir Sawaluddin Sembiring, Arnes Simbolon, Heri Yusus Siti Rusdiana Syah, Rahmad B.Y Syamsul Rizal SYARIFAH MEURAH YUNI T. KHAIRUMAN3 Tulus Tulus Usman Ba’afai Usman Usman Zia Anjelina