2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)最新文献_第7页

Recovery System using SDN Technology for Cyber Attack Solution 基于SDN技术的网络攻击恢复系统解决方案

2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) Pub Date : 2021-10-20 DOI: 10.23919/eecsi53397.2021.9624278

R. Umar, Ridho Surya Kusuma

引用次数: 0

Optimization of Multi-Controller Locations in SDWAN using Various Method 基于多种方法的SDWAN多控制器位置优化

2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) Pub Date : 2021-10-20 DOI: 10.23919/eecsi53397.2021.9624264

Victor Lamboy Sinaga, R. F. Sari

{"title":"Optimization of Multi-Controller Locations in SDWAN using Various Method","authors":"Victor Lamboy Sinaga, R. F. Sari","doi":"10.23919/eecsi53397.2021.9624264","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624264","url":null,"abstract":"Software Define Wide Area Network (SDWAN) is a solution for utilizing technology in sending information. SDWAN is designed by separating the control plane and data plane by applying the Software Define Network (SDN) concept; therefore, it can use physical devices more effectively and efficiently. With many nodes and spread, node grouping is needed to facilitate control and supervision that requires a controller in each cluster. Installing many nodes on SDWAN will require several controllers to make it more effective and efficient placement. Optimal controller placement will improve the performance of the network. In this study, determining the optimal controller location requires various methods that are interconnected with each other. The algorithms used are the Haversine method, Johnson's Algorithm, Partition Around Medoids (PAM), and Silhouette Analysis. The number of nodes and locations obtained from Zootopology in this research using the Indonesia Biznet network, therefore the recommendation for the optimal number of controllers is obtained using the Silhouette, Gap, Calinski-Harabasz, and Davies-Bouldien evaluation methods. The algorithms aim to get the optimal point by determining the number of controllers and recommendations for the optimal number of controllers as an initial recommendation for a company that uses this method. In this study, the most optimal number of controllers on the Biznet network with 29 nodes were two controllers and an average value of Silhouette analysis calculation of 0.51846.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130774364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

n-gram Effect in Malware Detection Using Multilayer Perceptron (MLP) 基于多层感知器(MLP)的n-gram效应恶意软件检测

2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) Pub Date : 2021-10-20 DOI: 10.23919/eecsi53397.2021.9624273

Benni Purnama, D. Stiawan, Darmawijoyo Hanapi, E. Winanto, R. Budiarto, Mohd Yazid Bin Idris

引用次数: 1

Classification of Chili Plant Origin by Using Multilayer Perceptron Neural Network 基于多层感知器神经网络的辣椒植物来源分类

2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) Pub Date : 2021-10-20 DOI: 10.23919/eecsi53397.2021.9624228

D. K. Agustika, N. Ariyanti, I Nyoman Kusuma Wardana, D. Iliescu, M. Leeson

{"title":"Classification of Chili Plant Origin by Using Multilayer Perceptron Neural Network","authors":"D. K. Agustika, N. Ariyanti, I Nyoman Kusuma Wardana, D. Iliescu, M. Leeson","doi":"10.23919/eecsi53397.2021.9624228","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624228","url":null,"abstract":"The geographical origin of the plants can affect the growth and hence the quality of the plants. In this research, the origin of the chili plants has been investigated by using Fourier transform infrared (FTIR) spectroscopy. The spectroscopy generated 3734 data with a wavenumber range from 4000–400 cm−1. The pre-processing of the spectra was done by using baseline correction and vector normalization. The analysis was then taken in the biofingerprint area of 1800–900 cm−1 range which has 934 data points. Feature extraction for dimension reduction was achieved using principal component analysis (PCA). The PC scores from PCA were then fed into a k-means and a multilayer perceptron neural network (MLPNN). The k-means clustering shows that the samples can be distinguished into three different groups. Meanwhile, for the MLPNN, the number of the hidden layer's neurons and the learning rate of the system were optimized to get the best classification result. A hidden layer with twenty neurons had the highest accuracy, while a learning rate of 0.001 had the highest value of 100%.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133885076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of Heater and Mixer Machine With Control System for Biodiesel Production 生物柴油生产用加热混合机及控制系统的研制

2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) Pub Date : 2021-10-20 DOI: 10.23919/eecsi53397.2021.9624315

M. Rahmawaty, H. Hendriko, Engla Puspita Haryanisa

{"title":"Development of Heater and Mixer Machine With Control System for Biodiesel Production","authors":"M. Rahmawaty, H. Hendriko, Engla Puspita Haryanisa","doi":"10.23919/eecsi53397.2021.9624315","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624315","url":null,"abstract":"Biodiesel is one of the renewable energies that is environmentally friendly. Generally, it is made from renewable materials that consisting of fatty acids. Biodiesel can also be made from vegetable oil, animal oil and waste cooking oil. Producing biodiesel is divided into three stages: heating and stirring process, cooling and washing process, and drying and filtration process. In this study, a machine for the first stage processing of biodiesel-based waste cooking oil was made. The machine is used for heating and mixing waste cooking oil and catalyst materials. The developed machine is equipped with a control system that is aimed for detecting the temperature of mixture materials. The data obtained by the sensor is then used to regulate the flow rate of the gas. The flow of the gas is controlled by a valve that is actuated by a servo motor. Several tests have been carried out. The tests were aimed to determine several control parameters that is used in programming. Moreover, the objective of the tests is also to determine the effectiveness of the machine in producing fatty acid methyl ester (FAME). The test results show that the gas flow rate should be reduced when the temperature of mixture material reaches 55 Celsius. The gas flow rate was reduced by changing the gas valve angle from 90 to 13. The machine's ability in producing FAME has been tested using three different volumes of waste cooking oil. The results showed that the amount of FAME produced is quite large.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"64 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131471555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Artificial Intelligence IoT based EEG Application using Deep Learning for Movement Classification 基于人工智能物联网的脑电应用，使用深度学习进行运动分类

2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) Pub Date : 2021-10-20 DOI: 10.23919/eecsi53397.2021.9624269

Widhi Winata Sakti, K. Anam, Satryo B Utomo, B. Marhaenanto, Safri Nahela

引用次数: 3

Comparative Study of CNN and YOLOv3 in Public Health Face Mask Detection CNN与YOLOv3在公共卫生口罩检测中的比较研究

2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) Pub Date : 2021-10-20 DOI: 10.23919/eecsi53397.2021.9624247

N. Setyawan, Tri Septiana Nadia Puspita Putri, Mohamad Al Fikih, N. Kasan

{"title":"Comparative Study of CNN and YOLOv3 in Public Health Face Mask Detection","authors":"N. Setyawan, Tri Septiana Nadia Puspita Putri, Mohamad Al Fikih, N. Kasan","doi":"10.23919/eecsi53397.2021.9624247","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624247","url":null,"abstract":"Coronavirus Disease (COVID-19) is gaining special concern from entire world population. The transmission of the COVID-19 virus is spreading almost in whole the world, including Indonesia which undergoing a crisis, especially in the health and economic sector. In prevention, the government is implementing Large-Scale Social Restrictions which public services or public places require people to wear masks. During this time, the detection of masks is done manually with observations from security personnel, which is time consuming. This study will apply a mask detection system (Face Mask Detection) using deep learning image processing. This study apply the most popular deep learning model which consist Convolutional Neural Networks (CNN) and You Only Look Once (YOLOv3) method. In training step, the datasets taken vary with images of faces that using head attribute such as hijabs, hats, and not using attributes. In addition, the images were taken from various countries such as Asia including Indonesia mostly, Europe, and the Americas. The system used a combination of object detection classification, image, and object tracking to develop a system that detects using a mask or not using a mask faces in images or camera videos. From the comparative analysis which developed in training and deploying step with image and camera video stream, YOLOv3 can detect accurately and faster with 4.8 FPS than CNN.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125368680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Strawberry Fruit Quality Assessment for Harvesting Robot using SSD Convolutional Neural Network 基于SSD卷积神经网络的草莓果实采摘机器人品质评价

2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) Pub Date : 2021-10-20 DOI: 10.23919/eecsi53397.2021.9624311

Muhammad Fauzan Ridho, Irwan

引用次数: 1

Denial of Service Attacks Detection on SCADA Network IEC 60870-5-104 using Machine Learning 基于机器学习的SCADA网络拒绝服务攻击检测

2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) Pub Date : 2021-10-20 DOI: 10.23919/eecsi53397.2021.9624255

M. M. Arifin, D. Stiawan, Susanto, J. Rejito, Mohd Yazid Bin Idris, R. Budiarto

{"title":"Denial of Service Attacks Detection on SCADA Network IEC 60870-5-104 using Machine Learning","authors":"M. M. Arifin, D. Stiawan, Susanto, J. Rejito, Mohd Yazid Bin Idris, R. Budiarto","doi":"10.23919/eecsi53397.2021.9624255","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624255","url":null,"abstract":"SCADA was designed to be used in an isolated area however, in modern SCADA, its connection to the Internet has become essential due to performance and commercial needs. This extended SCADA interconnection creates new vulnerabilities in the SCADA network. One of the attacks that may occur caused by the extended interconnection of SCADA networks to heterogeneous networks is Denial of Service attacks (DoS). DoS attack is launched by sending many messages from nodes. The development of easily accessible and simple DoS tools has increased the frequency of attacks. Ease of access and use of DoS tools made reduced the level of expertise needed to launch an attack. This study uses a SCADA dataset containing DoS attacks and running IEC 60870-5-104 protocol where this protocol will be encapsulated into TCP/IP protocol before being transmitted so that the treatment in detecting DoS attack in SCADA networks using the IEC 104 protocol is not much different from a traditional computer network. This study implements three machine learning approaches, i.e.: Decision Tree, Support Vector Machine, and Gaussian Naïve Bayes in creating an Intrusion Detection System (IDS) model to recognize DoS attack on the SCADA Network. Experimental results show that the performance of the Decision Tree approach has the best performance detection on the Testing dataset and Training dataset with an accuracy of 99.99% in all experiments.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133251875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Suitability of FPS and DPS in NOMA for Real-Time and Non-Real Time Applications NOMA中FPS和DPS在实时和非实时应用中的适用性

2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) Pub Date : 2021-08-23 DOI: 10.23919/eecsi53397.2021.9624291

Moontasir Rafique, Abdullah Alavi, Aadnan Farhad, M. T. Kawser

{"title":"Suitability of FPS and DPS in NOMA for Real-Time and Non-Real Time Applications","authors":"Moontasir Rafique, Abdullah Alavi, Aadnan Farhad, M. T. Kawser","doi":"10.23919/eecsi53397.2021.9624291","DOIUrl":"https://doi.org/10.23919/eecsi53397.2021.9624291","url":null,"abstract":"Non-Orthogonal Multiple Access (NOMA) is a popular solution for supporting a high number of users and along with significant bandwidth in 5G cellular communication. By using a technique called cooperative relaying, the same data is sent to all the users, and one user can relay data to the other. In order to provide enough power for the users, energy harvesting techniques have been introduced with Simultaneous Wireless Information and Power Transfer (SWIPT) coming to prominence in recent times. In this paper, analysis has been made comparing two different power allocation schemes in NOMA, Fixed Power allocation Scheme (FPS) and Dynamic Power allocation Scheme (DPS). The comparisons were made in terms of their performance and characteristics while undergoing SWIPT. It has been found that by using DPS, an almost 25% increase in peak spectral efficiency can be obtained compared to FPS. However, DPS suffers from a higher outage probability as the increase of power causes the signal bandwidth to drop below the target rate a significant number of times. Based on the detailed results, conclusions were drawn as to which power allocation coefficient scheme would be used in real-time and non-real time communication standards, respectively. The results suggest that for real-time communication, FPS is more suitable while for non-real time communication, DPS appears to work better than FPS.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134521770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1