Pub Date : 2022-09-26DOI: 10.17529/jre.v18i3.25903
Ricky Afiful Maula, A. Gunawan, Bima Sena Bayu Dewantara, M. A. Al Rasyid, Setiawardhana Setiawardhana, Ferry Astika Saputra, Junaedi Ispianto
Regression (SVR) 0.739, (KR) Abstract —Shrimp cultivation is strongly influenced by pond water quality conditions. Farmers must know the appropriate action in regulating water quality that is suitable for shrimp survival. The state of water quality can be understood by measuring pond parameters using various sensors. Installing sensors equipped with artificial intelligence modules to inform water quality conditions is the right action. However, the sensor cannot be separated from errors, so it results in not being able to get data or missing data. In this case, the approach of 5 parameters of pond water quality from 13 available parameters is carried out. This paper proposes a technique to obtain lost data caused by sensor error and looks for the best model. A simple approach can be taken, such as the Handling Missing Value (HMV) which is commonly used, namely the mean, with the K-Nearest Neighbors (KNN) classifier optimized using a grid search. However, the accuracy of this technique is still low, reaching 0.739 at 20-fold cross-validation. Calculations were carried out with other methods to further improve the prediction accuracy. It was found that Linear Regression (LR) can increase accuracy up to 0.757, which outperforms different approaches such as the statistical approach to mean 0.739, mode 0.716, median 0.734, and regression approach KNN 0.742, Lasso 0.751, Passive Aggressive Regressor (PAR) 0.737, Support Vector Regression (SVR) 0.739, Kernel Ridge (KR) 0.731, and Stochastic Gradient Descent (SGD) 0.734.
{"title":"Handling Missing Value dengan Pendekatan Regresi pada Dataset Akuakultur Berukuran Kecil","authors":"Ricky Afiful Maula, A. Gunawan, Bima Sena Bayu Dewantara, M. A. Al Rasyid, Setiawardhana Setiawardhana, Ferry Astika Saputra, Junaedi Ispianto","doi":"10.17529/jre.v18i3.25903","DOIUrl":"https://doi.org/10.17529/jre.v18i3.25903","url":null,"abstract":"Regression (SVR) 0.739, (KR) Abstract —Shrimp cultivation is strongly influenced by pond water quality conditions. Farmers must know the appropriate action in regulating water quality that is suitable for shrimp survival. The state of water quality can be understood by measuring pond parameters using various sensors. Installing sensors equipped with artificial intelligence modules to inform water quality conditions is the right action. However, the sensor cannot be separated from errors, so it results in not being able to get data or missing data. In this case, the approach of 5 parameters of pond water quality from 13 available parameters is carried out. This paper proposes a technique to obtain lost data caused by sensor error and looks for the best model. A simple approach can be taken, such as the Handling Missing Value (HMV) which is commonly used, namely the mean, with the K-Nearest Neighbors (KNN) classifier optimized using a grid search. However, the accuracy of this technique is still low, reaching 0.739 at 20-fold cross-validation. Calculations were carried out with other methods to further improve the prediction accuracy. It was found that Linear Regression (LR) can increase accuracy up to 0.757, which outperforms different approaches such as the statistical approach to mean 0.739, mode 0.716, median 0.734, and regression approach KNN 0.742, Lasso 0.751, Passive Aggressive Regressor (PAR) 0.737, Support Vector Regression (SVR) 0.739, Kernel Ridge (KR) 0.731, and Stochastic Gradient Descent (SGD) 0.734.","PeriodicalId":30766,"journal":{"name":"Jurnal Rekayasa Elektrika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45069033","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}
Pub Date : 2022-09-26DOI: 10.17529/jre.v18i3.25923
Nugroho Adi Wicaksono, Arief Goeritno
A compact integrated circuit is an intellectual property core at the heart of the decades of embedded devices on embedded systems. Using a microcontroller-based electronic module manufactured as desired or direct service of the board of Arduino as a control system for many purposes has become a certainty. Defining the problem formulations is related to the manufacture, assembly of the mechanical apparatus, and integrated wiring of several electronic modules. The acquisition of research contributions is expected to get the miniature embodiment of the physical machine equipped with a user program and perform the machine driver. The research methods consist of several steps to carry out each research objective. The miniature embodiment is carried out through (i) manufacturing and assembling to obtain the physical machine, (ii) integrating the electronic modules and all components and support systems by wiring to form an embedded system as a mini-PCB printing machine, and (iii) making a program structure based on Arduino IDE. Performing the machine driving mechanism is operating tests of calibration and moving on the axes of X, Y, and Z. Concluding based on the implementation process, testing, and analysis are carried out that the stages for performing the Mini PCB Printing Machine assisted by Arduino board with driven by GRBL Gru can be realized according to the initial design of hardware and software design.
{"title":"Designing an Arduino Board-based Electronic Device Driven by GRBL Gru to Operate the Mini PCB Printing Machine","authors":"Nugroho Adi Wicaksono, Arief Goeritno","doi":"10.17529/jre.v18i3.25923","DOIUrl":"https://doi.org/10.17529/jre.v18i3.25923","url":null,"abstract":"A compact integrated circuit is an intellectual property core at the heart of the decades of embedded devices on embedded systems. Using a microcontroller-based electronic module manufactured as desired or direct service of the board of Arduino as a control system for many purposes has become a certainty. Defining the problem formulations is related to the manufacture, assembly of the mechanical apparatus, and integrated wiring of several electronic modules. The acquisition of research contributions is expected to get the miniature embodiment of the physical machine equipped with a user program and perform the machine driver. The research methods consist of several steps to carry out each research objective. The miniature embodiment is carried out through (i) manufacturing and assembling to obtain the physical machine, (ii) integrating the electronic modules and all components and support systems by wiring to form an embedded system as a mini-PCB printing machine, and (iii) making a program structure based on Arduino IDE. Performing the machine driving mechanism is operating tests of calibration and moving on the axes of X, Y, and Z. Concluding based on the implementation process, testing, and analysis are carried out that the stages for performing the Mini PCB Printing Machine assisted by Arduino board with driven by GRBL Gru can be realized according to the initial design of hardware and software design.","PeriodicalId":30766,"journal":{"name":"Jurnal Rekayasa Elektrika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44050125","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}
Pub Date : 2022-09-26DOI: 10.17529/jre.v18i3.27227
Dalila Husna Yunardi, Maya Fitria, Rahmad Dawood, T. Alamsyah
Qurbani is an Islamic ritual animal sacrifice that is carried out during Eid-Adha; one of the two major Muslim holidays. In Indonesia, every village normally has one mosque that takes charge of organizing any related Qurbani activities, from collecting money, creating slaughter schedule, to distributing the meat for the recipients. The current management of these activities is done manually and by hand, which can potentially have errors. Therefore, this research aims to develop and evaluate the usability of a web-based application that will in part take care of Qurbani-related activities. This application is designed and developed using the Scrum methodology. The application as successfully developed and its functionalities are as expected based on design. The application was then evaluated using System Usability Scale (SUS) with 10 respondents. The application obtained the average score of 91.25 which falls into A or excellent category.
{"title":"A Usability Analysis of QODE: Qurbani Web Application System","authors":"Dalila Husna Yunardi, Maya Fitria, Rahmad Dawood, T. Alamsyah","doi":"10.17529/jre.v18i3.27227","DOIUrl":"https://doi.org/10.17529/jre.v18i3.27227","url":null,"abstract":"Qurbani is an Islamic ritual animal sacrifice that is carried out during Eid-Adha; one of the two major Muslim holidays. In Indonesia, every village normally has one mosque that takes charge of organizing any related Qurbani activities, from collecting money, creating slaughter schedule, to distributing the meat for the recipients. The current management of these activities is done manually and by hand, which can potentially have errors. Therefore, this research aims to develop and evaluate the usability of a web-based application that will in part take care of Qurbani-related activities. This application is designed and developed using the Scrum methodology. The application as successfully developed and its functionalities are as expected based on design. The application was then evaluated using System Usability Scale (SUS) with 10 respondents. The application obtained the average score of 91.25 which falls into A or excellent category.","PeriodicalId":30766,"journal":{"name":"Jurnal Rekayasa Elektrika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45874920","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}
Roslidar Roslidar, M. Syahputra, Rusdha Muharar, Fitri Arnia
The model development for breast thermal image classification can be done using deep learning methods, especially the convolutional neural network (CNN) architecture. This article focuses on adapting a trained CNN (trained model) on a mobile application for binary classification of breast thermal images into normal and abnormal classes. The CNN model applied in this study was based on ShuffleNet, called BreaCNet, with a learning weight of 1028 filters generated from training on images downloaded from the Database for Mastology Research (DMR) and a model size of 22 MB. The model must be converted into a mobile application to enable a trained model to be adapted into a mobile platform. The BreaCNet model was built using MatLab; thus, the stages in the adaptation process consisted of converting the model into ONNX file format, converting ONNX files into Tensorflow files, and Tensorflow files into Tensorflow Lite format. However, not all nodes are fully supported by MATLAB. The shuffle node on ShuffleNet cannot be fully exported using ExportToOnnx, so it needs to be re-defined with a placeholder named “MATLAB PLACEHOLDER”. In addition to the model conversion process, this article describes the user interaction process with the application using UML diagrams and application feature menu designs. The application was also tested on 20 thermal images of the breast. The testing results show that the application can perform the image classification process on mobile devices in less than 1 second with an accuracy rate of 85%. Finally, the breast thermal image screening application has been successfully built by directly interpreting the thermal image of the breast on a mobile device to keep the user data private.
乳房热图像分类的模型开发可以使用深度学习方法，特别是卷积神经网络(CNN)架构来完成。本文的重点是在移动应用程序上使用训练好的CNN(训练模型)对乳房热图像进行正常和异常分类。本研究中应用的CNN模型基于ShuffleNet，称为BreaCNet，其学习权重为1028个过滤器，这些过滤器是对从数据库Mastology Research (DMR)下载的图像进行训练产生的，模型大小为22 MB。该模型必须转换为移动应用程序，才能使训练好的模型适应移动平台。利用MatLab建立了BreaCNet模型;因此，适应过程的阶段包括将模型转换为ONNX文件格式，将ONNX文件转换为Tensorflow文件，将Tensorflow文件转换为Tensorflow Lite格式。然而，MATLAB并不是完全支持所有的节点。ShuffleNet上的shuffle节点不能使用ExportToOnnx完全导出，因此需要使用名为“MATLAB placeholder”的占位符重新定义。除了模型转换过程之外，本文还描述了使用UML图和应用程序功能菜单设计的用户与应用程序的交互过程。该应用程序还在20张乳房热图像上进行了测试。测试结果表明，该应用程序可以在不到1秒的时间内完成移动设备上的图像分类过程，准确率达到85%。最后，通过在移动设备上直接解读乳房热图像，成功构建了乳房热图像筛选应用，保证了用户数据的私密性。
{"title":"Adaptasi Model CNN Terlatih pada Aplikasi Bergerak untuk Klasifikasi Citra Termal Payudara","authors":"Roslidar Roslidar, M. Syahputra, Rusdha Muharar, Fitri Arnia","doi":"10.17529/jre.v18i3.8754","DOIUrl":"https://doi.org/10.17529/jre.v18i3.8754","url":null,"abstract":"The model development for breast thermal image classification can be done using deep learning methods, especially the convolutional neural network (CNN) architecture. This article focuses on adapting a trained CNN (trained model) on a mobile application for binary classification of breast thermal images into normal and abnormal classes. The CNN model applied in this study was based on ShuffleNet, called BreaCNet, with a learning weight of 1028 filters generated from training on images downloaded from the Database for Mastology Research (DMR) and a model size of 22 MB. The model must be converted into a mobile application to enable a trained model to be adapted into a mobile platform. The BreaCNet model was built using MatLab; thus, the stages in the adaptation process consisted of converting the model into ONNX file format, converting ONNX files into Tensorflow files, and Tensorflow files into Tensorflow Lite format. However, not all nodes are fully supported by MATLAB. The shuffle node on ShuffleNet cannot be fully exported using ExportToOnnx, so it needs to be re-defined with a placeholder named “MATLAB PLACEHOLDER”. In addition to the model conversion process, this article describes the user interaction process with the application using UML diagrams and application feature menu designs. The application was also tested on 20 thermal images of the breast. The testing results show that the application can perform the image classification process on mobile devices in less than 1 second with an accuracy rate of 85%. Finally, the breast thermal image screening application has been successfully built by directly interpreting the thermal image of the breast on a mobile device to keep the user data private.","PeriodicalId":30766,"journal":{"name":"Jurnal Rekayasa Elektrika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46018277","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}
Pub Date : 2022-09-26DOI: 10.17529/jre.v18i3.26363
G. Maulana, Ridwan Mada, Regim Ramaya Purba
The warehousing system is a means of supporting production activities and industrial operations that function to store goods to be distributed, which are still using a manual system and must adapt to technological developments. The problem that often arises in the warehousing system that is still done manually is that the flow of goods into the warehouse is not well organized, and this makes it difficult when the goods are about to be removed, so it requires a longer search time. Previous research has shown actual data on storage racks that use Arduino Mega as a controller and VB as an interface, but there is no actual data on the state of the lifter or the selection of lifter movement speed modes to facilitate operators in monitoring and operating goods storage. Control systems with industry standards greatly affect the effectiveness and optimization of the production process. Based on these problems, this research aims to simplify the managerial and monitoring process in the warehouse with a prototype of automatic multilevel storage using PLC CP1H and CP1L as system control and Wonderware Intouch as an interface with the SCADA system. The prototype has 12 cells, and each cell can accommodate 2 boxes; each cell is distinguished by the height and color of the box. In testing this research, the SCADA system can work optimally. The interface is capable of displaying the actual data of the rack with a success rate of 100%, the hardware error rate is less than 1%, and the interface can display the actual data on the state of the lifter.
{"title":"Automation Storage System Based On SCADA Using PLC CP1H and CP1L","authors":"G. Maulana, Ridwan Mada, Regim Ramaya Purba","doi":"10.17529/jre.v18i3.26363","DOIUrl":"https://doi.org/10.17529/jre.v18i3.26363","url":null,"abstract":"The warehousing system is a means of supporting production activities and industrial operations that function to store goods to be distributed, which are still using a manual system and must adapt to technological developments. The problem that often arises in the warehousing system that is still done manually is that the flow of goods into the warehouse is not well organized, and this makes it difficult when the goods are about to be removed, so it requires a longer search time. Previous research has shown actual data on storage racks that use Arduino Mega as a controller and VB as an interface, but there is no actual data on the state of the lifter or the selection of lifter movement speed modes to facilitate operators in monitoring and operating goods storage. Control systems with industry standards greatly affect the effectiveness and optimization of the production process. Based on these problems, this research aims to simplify the managerial and monitoring process in the warehouse with a prototype of automatic multilevel storage using PLC CP1H and CP1L as system control and Wonderware Intouch as an interface with the SCADA system. The prototype has 12 cells, and each cell can accommodate 2 boxes; each cell is distinguished by the height and color of the box. In testing this research, the SCADA system can work optimally. The interface is capable of displaying the actual data of the rack with a success rate of 100%, the hardware error rate is less than 1%, and the interface can display the actual data on the state of the lifter.","PeriodicalId":30766,"journal":{"name":"Jurnal Rekayasa Elektrika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48163373","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}
Pub Date : 2022-09-26DOI: 10.17529/jre.v18i3.26017
I. D. Irawati, D. N. Ramadan, S. Hadiyoso
The hydroponic planting method is one solution for supplying vegetable needs where agricultural land is limited. Hydroponics allows the growing of vegetables in stages in a limited area by utilizing water as a growing medium. Water quality greatly determines plant fertility, so monitoring must be carried out regularly. Currently, the agricultural sector in Sukabumi has a large potential for the economy of the community. Farmers develop hydroponic farming but monitoring of water quality is still done traditionally. Therefore, in this study, a water quality monitoring system is proposed including pH, turbidity, and temperature. Another parameter that is observed is the water level in the reservoir which is useful for maintaining water circulation. This system works online through the internet network, both the sensing process, data transmission, and data display using the Internet of Things (IoT) platform. The measured parameters can be observed via a web application. Performance evaluation of sensor devices is carried out by comparing the measurement values of standard devices. The test results on the system that has been implemented show that the system has high accuracy, and all parameters are successfully displayed on the web page. The applied systems can increase the fertility of vegetables on hydroponic land so that it can improve the quality of production.
{"title":"Web-based Water Quality Parameter Monitoring for Packcoy Hydroponics using Multi Sensors","authors":"I. D. Irawati, D. N. Ramadan, S. Hadiyoso","doi":"10.17529/jre.v18i3.26017","DOIUrl":"https://doi.org/10.17529/jre.v18i3.26017","url":null,"abstract":"The hydroponic planting method is one solution for supplying vegetable needs where agricultural land is limited. Hydroponics allows the growing of vegetables in stages in a limited area by utilizing water as a growing medium. Water quality greatly determines plant fertility, so monitoring must be carried out regularly. Currently, the agricultural sector in Sukabumi has a large potential for the economy of the community. Farmers develop hydroponic farming but monitoring of water quality is still done traditionally. Therefore, in this study, a water quality monitoring system is proposed including pH, turbidity, and temperature. Another parameter that is observed is the water level in the reservoir which is useful for maintaining water circulation. This system works online through the internet network, both the sensing process, data transmission, and data display using the Internet of Things (IoT) platform. The measured parameters can be observed via a web application. Performance evaluation of sensor devices is carried out by comparing the measurement values of standard devices. The test results on the system that has been implemented show that the system has high accuracy, and all parameters are successfully displayed on the web page. The applied systems can increase the fertility of vegetables on hydroponic land so that it can improve the quality of production.","PeriodicalId":30766,"journal":{"name":"Jurnal Rekayasa Elektrika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48118614","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}
Pub Date : 2022-09-26DOI: 10.17529/jre.v18i3.25816
Sholahuddin Muhammad Irsyad, A. Basuki, Bima Sena Bayu Dewantara
—Digital interaction are still commonly using indirect media such as mouse and keyboard to provide user input in the form of two-dimensional data. Therefore, to provide intuition in virtual interactions, it is possible to add media that can draw directly in the air or a flat surface that will track hand movements and overall finger position. In this research, we try to track hand movements in real time by capturing the position of the hand and finger curvature using a wearable sensor equipped with an Inertial Measurement Unit (IMU) sensor and a flex sensor installed by the user. Then the system will identify the position of the user's finger bending. and the location indicated by the sensors installed to move the cursor on the screen and simulate left-click and right-click hand movements as with a traditional mouse. By using this system, users can interact with the computer more naturally and get the accuracy of cursor movement with the accuracy of finger movement translation reaching more than 85% and the translation of hand movements to mouse cursor movements is on average 73% for shapes that use straight lines. and 23.4% on curved lines such as circles and other shapes.
{"title":"Rancang Bangun AirMouse Menggunakan Sarung Tangan Bersensor Berbasis ESP32","authors":"Sholahuddin Muhammad Irsyad, A. Basuki, Bima Sena Bayu Dewantara","doi":"10.17529/jre.v18i3.25816","DOIUrl":"https://doi.org/10.17529/jre.v18i3.25816","url":null,"abstract":"—Digital interaction are still commonly using indirect media such as mouse and keyboard to provide user input in the form of two-dimensional data. Therefore, to provide intuition in virtual interactions, it is possible to add media that can draw directly in the air or a flat surface that will track hand movements and overall finger position. In this research, we try to track hand movements in real time by capturing the position of the hand and finger curvature using a wearable sensor equipped with an Inertial Measurement Unit (IMU) sensor and a flex sensor installed by the user. Then the system will identify the position of the user's finger bending. and the location indicated by the sensors installed to move the cursor on the screen and simulate left-click and right-click hand movements as with a traditional mouse. By using this system, users can interact with the computer more naturally and get the accuracy of cursor movement with the accuracy of finger movement translation reaching more than 85% and the translation of hand movements to mouse cursor movements is on average 73% for shapes that use straight lines. and 23.4% on curved lines such as circles and other shapes.","PeriodicalId":30766,"journal":{"name":"Jurnal Rekayasa Elektrika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43168559","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}
Pub Date : 2022-07-30DOI: 10.17529/jre.v18i2.25147
Abdullah Sani, Suci Rahmadinni
—Hand sign language is a medium of communication for people with disabilities (deaf and speech impaired). However, in social practice, persons with disabilities may have to communicate with non-disable persons who do not understand sign language. These problems can be overcome with the help of translators or normal people learning sign language through existing media such as videos. Unfortunately, this method will probably cost a lot of money and time. In respons to this issue, the present study designed a sistem to detect hand gestures based on image processing. The method used is the You Only Look Once (YOLO) algorithm. The YOLO algorithm can detect and classify objects at once without being influenced by the light intensity and background of the object. This algorithm is a deep learning method that is more accurate than other deep learning methods. From this research, the system can detect and classify hand gestures with different backgrounds, light intensity, and distances with an accuracy rate above 90%.
-手语是残疾人(聋人和语言障碍者)的交流媒介。然而，在社会实践中，残疾人可能不得不与不懂手语的非残疾人进行交流。这些问题可以在翻译人员的帮助下或通过视频等现有媒体学习手语的普通人的帮助下克服。不幸的是，这种方法可能会花费大量的金钱和时间。针对这一问题，本研究设计了一个基于图像处理的手势检测系统。使用的方法是You Only Look Once (YOLO)算法。YOLO算法可以在不受物体光强和背景影响的情况下对物体进行一次性检测和分类。该算法是一种深度学习方法，比其他深度学习方法更准确。通过本研究，该系统可以对不同背景、光照强度和距离的手势进行检测和分类，准确率在90%以上。
{"title":"Deteksi Gestur Tangan Berbasis Pengolahan Citra","authors":"Abdullah Sani, Suci Rahmadinni","doi":"10.17529/jre.v18i2.25147","DOIUrl":"https://doi.org/10.17529/jre.v18i2.25147","url":null,"abstract":"—Hand sign language is a medium of communication for people with disabilities (deaf and speech impaired). However, in social practice, persons with disabilities may have to communicate with non-disable persons who do not understand sign language. These problems can be overcome with the help of translators or normal people learning sign language through existing media such as videos. Unfortunately, this method will probably cost a lot of money and time. In respons to this issue, the present study designed a sistem to detect hand gestures based on image processing. The method used is the You Only Look Once (YOLO) algorithm. The YOLO algorithm can detect and classify objects at once without being influenced by the light intensity and background of the object. This algorithm is a deep learning method that is more accurate than other deep learning methods. From this research, the system can detect and classify hand gestures with different backgrounds, light intensity, and distances with an accuracy rate above 90%.","PeriodicalId":30766,"journal":{"name":"Jurnal Rekayasa Elektrika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45619994","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}
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