Article Per Year (5 Year)
p-Index From 2021 - 2026
7.603
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics CESS (Journal of Computer Engineering, System and Science) Jurnal Teknologi Informasi dan Komunikasi InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Juripol Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Query : Jurnal Sistem Informasi Zero : Jurnal Sains, Matematika, dan Terapan JURIKOM (Jurnal Riset Komputer) Data Science: Journal of Computing and Applied Informatics ComTech: Computer, Mathematics and Engineering Applications Building of Informatics, Technology and Science Jurnal Mantik Indonesian Journal of Education and Mathematical Science International Journal of Advances in Data and Information Systems Randwick International of Social Science Journal Jurnal Scientia Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Journal of Applied Data Sciences TECHSI - Jurnal Teknik Informatika Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) The Indonesian Journal of Computer Science Journal of Digital Market and Digital Currency
Efendi, Syahril
Department Of Computer Science And Information Technology, University Of North Sumatra, Indonesia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

Published : 68 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 68 Documents
Search

 3   4   5   6   7 
Enhance Control Mobile Compiuting Improvement in Quality Data Acquisition in Simulation Efendi, Syahril; Aryza, Solly; Mardiansyah, Heru; Ahmadi, Fauzan Nur; Khowarizmi, Al-
Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 4, No 4 (2021): Budapest International Research and Critics Institute November
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v4i4.3335

Abstract

This research is a research and development (R&D) process with software design and testing using the v-model software development life cycle (SDLC) method, consisting of stages: (1) requirements modeling, (2) architectural design, (3) component design, (4) code generation, (5) unit testing, (6) integration testing, (7) system testing, (8) acceptance testing. Unit testing method using a white-box technique with base-path test, flowgraph, independent path on "DigiChip" software. Testing integration, system, acceptance with black-box techniques. The functional suitability aspect was tested with a feature run test questionnaire and a test case. The maintainability aspect is tested by measuring maintainability index (MI), duplication source code, line of code (LoC), cyclomatic complexity (CC). The portability aspect is tested by installing on various hardware configurations, various versions of the Android OS kernel. The material and media test used a material expert and media expert questionnaire. The usability aspect was tested using the USE Questionnaire and the calculation of Cronbach's Alpha through SPSS. This paper describes the main advantages of this DAS module which is that it can be manufactured at a very affordable price and provides good performance as is commonly used in industrial control systems. In motor control systems, alternative data acquisition system (DAS) modules can use the LabVIEW interface. The DAS module is controlled by the ATmega64 AVR micro controller which will communicate in both directions with LabVIEW using the serial communication method. Which is used to obtain 8-bit digital input, 8-bit digital output, 8 analog input channels, and also 2 analog output channels. Digital inputs can be used for 0-5V and 0-24V voltages. The digital output is made open collector with a "low" voltage of 0.276V. For analog inputs and analog outputs, this system has an average error of 14.47mV for the input range of 1-5V; 72.34mV for the 0-10V input range; 0.037mA for 4-20mA input range, and 16.2mV for 0-10V output range. This system is not designed for use in applications that require real-time accuracy and fast accuracy.
Detection and Tracking Different Type of Cars With YOLO model combination and deep sort algorithm based on computer vision of traffic controlling Hasibuan, Nisma Novita; Zarlis, Muhammad; Efendi, Syahril
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11231

Abstract

The application of CCTV cameras for traffic surveillance and monitoring is one effective solution to address urban traffic problems, as the number of vehicles that continue to increase rapidly but the area of the road remains the same will cause congestion. However, the problem in traffic surveillance and monitoring is not just focusing on vehicle detection based on category inference on video sequence data sourced from CCTV cameras alone, another important, challenging task is to combine calculations, classification and tracking of different vehicle movements in urban traffic control systems. The study expanded on previous research by breaking down the problem into different sub-tasks using the YOLOv4 approach combined with the Deep Sort algorithm for the detection and tracking of objects directly on CCTV footage of vehicle activity on the city's three-stop highway. Based on the results of YOLOv4 testing resulted in a detection accuracy rate with mAP of 87.98% where the combination of YOLOv4 with the Deep Sort algorithm can detect, track and calculate 13 types of vehicles.
Analysis of Dimensional Reduction Effect on K-Nearest Neighbor Classification Method Taufiqurrahman, Taufiqurrahman; Nababan, Erna Budhiarti; Efendi, Syahril
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11234

Abstract

Classification algorithms mostly become problematic on data with high dimensions, resulting in a decrease in classification accuracy. One method that allows classification algorithms to work faster and more effectively and improve the accuracy and performance of a classification algorithm is by dimensional reduction. In the process of classifying data with the K-Nearest Neighbor algorithm, it is possible to have features that do not have a matching value in classifying, so dimension reduction is required. In this study, the dimension reduction method used is Linear Discriminant Analysis and Principal Component Analysis and classification process using KNN, then analyzed its performance using Matrix Confusion. The datasets used in this study are Arrhythmia, ISOLET, and CNAE-9 obtained from UCI Machine Learning Repository. Based on the results, the performance of classifiers with LDA is better than with PCA on datasets with more than 100 attributes. Arrhythmia datasets can improve performance on K-NN K=3 and K=5. The best performance is obtained by LDA+K-NN K=3 which produces an accuracy value of 98.53%, the lowest performance found in K-NN without reduction with K=3. ISOLET datasets, the best performance results are also obtained by data that has been reduced with LDA, but the best performance is obtained when the classification of K-NN with K=5 and the lowest performance is found in PCA+ K-NN with a value of K=3. As for the best performance, dataset CNAE-9 is also achieved by LDA+K-NN, while the lowest performance is PCA+K-NN with the value of K=3.
A Decision Model For Tackling Logistic Optimization Problem in Online Business Environment Syahraini, Syahraini; Efendi, Syahril; Sitorus, Syahriol
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11593

Abstract

Online business has increased during the COVID-19 pandemic, but the emergence of a number of problems, namely reduced material supply, price fluctuations because an item is difficult to distribute and slow delivery due to transportation of goods based on the type of transportation used (Trucks, Trains, Airplanes and Ships). a number of declines due to the COVID-19 virus pandemic, resulting in longer order waiting times. Pick-up and Delivery Issues are variations of Vehicle Routing Issues that appear in many real-world transportation scenarios, such as product delivery and courier services. This work studies the Pickup and Delivery Problem with Time Windows, where goods must be transported from one location to another, with taking into account certain time limits and vehicle capacity. This aims to minimize the number of vehicles used, as well as operational costs for all routes. To solve this problem, a mathematical model in the form of is used Mixed Integer Linear Programming (MILP) from Pickup and Delivery Problems with Time Windows
Optimization Model of Location Routing Problem for Disaster Relief Distribution Hamzani, Fitri Rezky; Sitorus, Syahriol; Efendi, Syahril
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11604

Abstract

Disaster relief distribution is a very important component in the overall disaster response process. Consideration of limited funds, time pressure and surge of demand that come together increase to the complexity of the distribution process that must be done in a short time. Meanwhile, delays in the delivery of relief can lead to a decrease in the level of safety and welfare of disaster-affected victims. This paper proposes a location routing problem optimization model for disaster relief distribution with a multi-objective approach that minimizes waiting time and total costs. This model can help decision makers to determine the number and location of distribution centers which are opened and optimal vehicle routes.
Analysis of Data classification accuracy using ANFIS algorithm modification with K-Medoids clustering Br Bangun, Desy Milbina; Efendi, Syahril; Sembiring, Rahmat W
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11610

Abstract

The ANFIS algorithm is a technique in data mining that can be used for the data classification process. The ANFIS algorithm still has weaknesses, especially in determining the initial parameters for the network training process. Thus, an additional algorithm or modification is needed for the determination of these parameters. In this study, a clustering method will be proposed, namely K-Medoids Clustering as an additional method to the ANFIS algorithm. Basically, the ANFIS algorithm uses the FCM (Fuzzy C-Means Clustering) algorithm for the initial initialization of network parameters. The use of this method can cause local minima problems, where the clustering results obtained are not optimal because the pseudo-partition matrix generation process is carried out randomly. The matrix value will determine the initial parameter value in the ANFIS algorithm used in the first layer. Based on the research that has been done, it can be concluded that the accuracy of data classification using the ANFIS algorithm which has been modified with the proposed method provides a fairly good influence in conducting training and classification testing. The increase that occurs in the proposed method is 0.73% for the average training accuracy and an increase of 0.66% for the average testing accuracy.
ANALISIS PERBANDINGAN PEMBOBOTAN ROC DAN FULL CONSISTENCY METHOD (FUCOM) PADA MOORA DALAM PENGAMBILAN KEPUTUSAN Prayoga, Nanda Dimas; Zarlis, Muhammad; Efendi, Syahril
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11643

Abstract

Decision support system is a system that can assist companies in making policy. There are several methods in a decision support system, one of which is the MOORA method. The MOORA method does not have a systematic weight determination. In several studies, the determination of the weight value is determined by experts in their field so that the value is less objective. So in this study, the Rank Order Centroid (ROC) and Full Consistency Method (FUCOM) weighting methods will be used systematically and objectively which will be applied to the MOORA method and a comparison of the results of these methods will be carried out with the calculation of the accuracy of the confusion matrix. The purpose of this study was to analyze the results of the weighting comparison using Rank Order Centroid (ROC) and Full Consistency Method (FUCOM) on the MOORA method so as to produce good accuracy. Based on the results of the study, testing with ROC weights on MOORA obtained results of 77.78% accuracy, 84% precision and 84% recall. While testing with ROC weights on MOORA obtained results of 77.78% accuracy, 84% precision and 84% recall. And testing with ROC+FUCOM weights on MOORA obtained 91.67% accuracy, 94% precision and 94% recall. So it can be concluded that the ROC+FUCOM weighting on MOORA produces good accuracy.
The role of Louvain-coloring clustering in the detection of fraud transactions Mardiansyah, Heru; Suwilo, Saib; Nababan, Erna Budhiarti; Efendi, Syahril
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp608-616

Abstract

Clustering is a technique in data mining capable of grouping very large amounts of data to gain new knowledge based on unsupervised learning. Clustering is capable of grouping various types of data and fields. The process that requires this technique is in the business sector, especially banking. In the transaction business process in banking, fraud is often encountered in transactions. This raises interest in clustering data fraud in transactions. An algorithm is needed in the cluster, namely Louvain’s algorithm. Louvain’s algorithm is capable of clustering in large numbers, which represent them in a graph. So, the Louvain algorithm is optimized with colored graphs to facilitate research continuity in labeling. In this study, 33,491 non-fraud data were grouped, and 241 fraud transaction data were carried out. However, Louvain’s algorithm shows that clustering increases the amount of data fraud of 90% by accurate.
Ubiquitous-cloud-inspired deterministic and stochastic service provider models with mixed-integer-programming Sumarlin, Sumarlin; Zarlis, Muhammad; Suherman, Suherman; Efendi, Syahril
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1304-1311

Abstract

The ubiquitous computing system is a paradigm shift from personal computing to physical integration. This study focuses on the deterministic and stochastic service provider model to provide sub-services to computing nodes to minimize rejection values. This deterministic service provider model aims to reduce the cost of sending data from one place to another by considering the processing capacity at each node and the demand for each sub-service. At the same time, stochastic service provider aims to optimize service provision in a stochastic environment where parameters such as demand and capacity may change randomly. The novelties of this research are the deterministic and stochastic service provider models and algorithms with mixed integer programming (MIP). The test results show that the solution found meets all the constraints and the smallest objective function value. Stochastic modeling minimizes denial of service problems during wireless sensor network (WSN) distribution. The model resented is the ability of wireless sensors to establish connections between distributed computing nodes. Stochastic modeling minimizes denial of service problems during WSN distribution.
Financial technology forecasting using an evolving connectionist system for lenders and borrowers: ecosystem behavior Al-Khowarizmi, Al-Khowarizmi; Watts, Michael J.; Efendi, Syahril; Abdulbasah Kamil, Anton
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp2386-2394

Abstract

Financial technology (FinTech) which is included in the development of digitalization in the financial sector in the industrial era 4.0. FinTech can make any transactions anywhere with the pillars of peer-to-peer (P2P) lending, merchants, and crowdfunding. In the P2P lending pillar, there are borrowers and lenders who are digitized in FinTech devices. FinTech in Indonesia is controlled by a state agency called the financial services authority or otoritas jasa keuangan (OJK). In the movement of P2P lending, there are borrowers and lenders who can be said to be investors where these activities are reported to the OJK. This data can be forecasted using a neural network approach such as evolving connectionist system (ECoS), which is a method capable of forecasting with learning that develops in the hidden layer. In this research article, we present results on forecasting borrowers with a mean absolute percentage error (MAPE) of 0.148% and forecasting lenders with an accuracy measurement with MAPE of 0.209% with a learning rate 1=0.6 and a learning rate 2=0.3. So, this forecasting model can be said as an optimization in FinTech activities on the behavior of borrowers and lenders.
Co-Authors Abdulbasah Kamil, Anton Abi Rafdi Ahmad Rozy Ahmadi, Fauzan Nur Al Khowarizmi Aminuyati Andysah Putera Utama Siahaan Arjon Turnip Asrizal Asrizal Badawi, Afif Br Bangun, Desy Milbina Br Ginting, Dewi Sartika Budi K. Hutasuhut Chairil Umri Dadang Priyanto Devi Maiya Sari Nasution Erna Budhiarti Erna Budhiarti Nababan Erna Budhiarti Nababan Fahmi Fahmi Fajar Muhajir Fatma Sari Hutagalung Fauzan Nurahmadi Fauzi Amri Fuzy Yustika Manik, Fuzy Yustika Ginting, Dewi Sartika Br Halim Maulana Hamzani, Fitri Rezky Harahap, Lailan Hariyati Lubis, Hariyati Harumy, T. Henny Febriana Hasibuan, Nisma Novita Hasugian , Paska Marto Hengki Tamando Sihotang Hengki Tamando Sihotang Herianto, Tulus Joseph Herimanto Herimanto herman mawengkang Herman Mawengkang Hotmaida Lestari Siregar Ichsanuddin Hakim Ignazio Ahmad Pasadana Iin Parlina Imanuel Zega Indah Purnama Sari Indra Edy Syahputra Irzal Sofyan Jaya, Ivan Khowarizmi, Al- Lailan Harahap Lidya Rosnita lili Tanti Lubis, Fahrurrozi M Safii M. Isa Indrawan Mahyuddin K. M Nasution Manurung, Rodiyah Aini Mardiansyah, Heru Marischa Elveny, Marischa Maya Silvi Lydia Mesran, Mesran Mochamad Wahyudi Mohammad Andri Budiman Muhammad Iqbal Muhammad Iqbal Muhammad Riki Atsauri Muhammad Rusdi dan Afritha Amelia - Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis Muhammad Zarlis, Muhammad Muliawan Firdaus Mulkan Azhari Naemah Mubarakah Nainggolan, Pauzi Ibrahim Nugroho Syahputra Oktaviana Bangun Pahala Sirait Poltak Sihombing Poltak Sihombing Poltak Sihombing Poltak Sihombing Poltak Sihombing Poltak Sihombing Prayoga, Nanda Dimas Purwanto Purwanto Rahmad Syah Riah Ukur Ginting Rika Permata Sari Siregar Rizki Suwanda Saib Suwilo Santoso, Zikri Akmal Saraswati Yoga Andriyani Sarif, Muhammad Irfan Sawaluddin Sawaluddin Sembiring, Rahmat W Seniman Seniman Seniman Seniman, Seniman Siagian, Deliyana Simamora, Windi Saputri Solly Aryza Sri Dwi Hastuti Sri Melvani Hardi Suherman Suherman Suherman, Suherman Sutarman Sutarman Sutarman Sutarman Syah, Rahmad B. Y. Syahputra, Indra Edy Syahputra, Muhammad Romi Syahraini, Syahraini Syahriol Sitorus Taufiqurrahman Taufiqurrahman Tulus Tulus Tulus Tulus Vinsensia, Desi Watts, Michael J. Weber, Gerhard Wilhelm yeni absah Yudhistira Yudhistira Yudhistira Zakarias Situmorang Zuhri Ramadhan Zulkarnain Lubis