Pub Date : 2018-10-01DOI: 10.1109/EECSI.2018.8752777
B. N. Cahyadi, W. Khairunizam, M. Muhammad, I. Zunaidi, S. Majid, R. N., S. A. Bakar, Z. Razlan, W. Mustafa
This paper present the studies of analysis arm movement sequence which dedicated for upper limb rehabilitation after stroke. The recovery of the arm could be optimized if the rehabilitation therapy is in a right manner. Upper limb weakness after stroke is prevalent in post-stroke rehabilitation, many factors that can deficit muscle strength there are neural, muscle structure and function change after stroke. Rehabilitation process needs to start as soon as after a stroke attack, repetitive and conceptualized. On the other hand monitoring of muscle activity also need in the rehabilitation process to evaluate muscle strength, motor function and progress in the rehabilitation process. The objective of this research is to analysis arm movement sequence using the feature frequency domain. In this study deltoid, biceps and flexor carpum ulnaris (FCU) muscles will be monitored by surface electromyography (sEMG). Five healthy subjects male and female become participants in data recording. Mean frequency (MNF) and median frequency (MDF) domain are two signals processing technique used for arm movement sequence analyzing. The analysis result showed that MNF is better than MDF where MNF produced higher frequency than MDF from each segment. From the data analysis, this movement sequence design more focuses on deltoid and FCU muscles treatment. This movement sequence has five condition movements. First undemanding, second difficult, third moderate, fourth moderate and the last cool-down movements. The best movement sequence minimum has four condition movements warming up – moderate – difficult – cool-down.
{"title":"Analysis of EMG based Arm Movement Sequence using Mean and Median Frequency","authors":"B. N. Cahyadi, W. Khairunizam, M. Muhammad, I. Zunaidi, S. Majid, R. N., S. A. Bakar, Z. Razlan, W. Mustafa","doi":"10.1109/EECSI.2018.8752777","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752777","url":null,"abstract":"This paper present the studies of analysis arm movement sequence which dedicated for upper limb rehabilitation after stroke. The recovery of the arm could be optimized if the rehabilitation therapy is in a right manner. Upper limb weakness after stroke is prevalent in post-stroke rehabilitation, many factors that can deficit muscle strength there are neural, muscle structure and function change after stroke. Rehabilitation process needs to start as soon as after a stroke attack, repetitive and conceptualized. On the other hand monitoring of muscle activity also need in the rehabilitation process to evaluate muscle strength, motor function and progress in the rehabilitation process. The objective of this research is to analysis arm movement sequence using the feature frequency domain. In this study deltoid, biceps and flexor carpum ulnaris (FCU) muscles will be monitored by surface electromyography (sEMG). Five healthy subjects male and female become participants in data recording. Mean frequency (MNF) and median frequency (MDF) domain are two signals processing technique used for arm movement sequence analyzing. The analysis result showed that MNF is better than MDF where MNF produced higher frequency than MDF from each segment. From the data analysis, this movement sequence design more focuses on deltoid and FCU muscles treatment. This movement sequence has five condition movements. First undemanding, second difficult, third moderate, fourth moderate and the last cool-down movements. The best movement sequence minimum has four condition movements warming up – moderate – difficult – cool-down.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"94 1","pages":"440-444"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83877539","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752876
S. Wibowo, R. Andreswari, M. A. Hasibuan
Information Systems is one of the existing study program at Telkom University that has produced many graduates since it was established in 2008. However, not all graduates produced successfully completed the study period during the four years of normal study. The percentage of graduates on time has some decline between the target and the achievement of the study program. From academic year 2014/2015 to 2016/2017 decrease annually about 1% every year, which is it becomes problems for the credibility and existence of study program and also for academic planners who may have an impact on accreditation assessment process of the study program when it is audited. One of the efforts that can be done by the study program to increase the students on time graduation rate is by making decision support system dashboard that giving early warning to the lecturer or the head of the study program if there are students who are predicted not to graduate on time. By using the C4.5 algorithm to perform the data analysis by looking at the causes of student’s graduation time and pureshare methodology to perform dashboard development method. The result of this study is a prototype of decision support system dashboard, because there are lack of analysis in decision making and the dashboard only showing information and temporary prediction. The data model that used on this research is labeling data that has been processed using C4.5 algorithm and data that has been through data cleansing process using Pentaho Data Integration. This prototype is expected to be used as a reference base to support academic planners in order to make this application run with real time data.
信息系统是电信大学现有的研究项目之一，自2008年成立以来，已经培养了许多毕业生。然而，并不是所有的毕业生都能在四年的正常学习中顺利完成学业。毕业生准时毕业的比例在目标和学习计划的实现之间有所下降。从2014/2015学年到2016/2017学年，每年减少约1%，这对学习项目的可信度和存在性造成了问题，也对学术策划者造成了问题，这些问题可能会对学习项目审核时的认证评估过程产生影响。为了提高学生的按时毕业率，学习项目可以做的一项努力是通过制定决策支持系统仪表板，如果有学生预计不能按时毕业，该仪表板会向讲师或学习项目负责人发出预警。通过使用C4.5算法进行数据分析，通过查看学生毕业时间的原因和pureshare方法论来执行仪表板开发方法。本研究的结果是一个决策支持系统仪表板的原型，因为在决策过程中缺乏分析，仪表板只显示信息和临时预测。本研究使用的数据模型是使用C4.5算法对处理过的数据进行标注，使用Pentaho data Integration对数据进行清洗处理的数据进行标注。这个原型有望被用作一个参考基础，以支持学术规划人员，以便使这个应用程序使用实时数据运行。
{"title":"Analysis and Design of Decision Support System Dashboard for Predicting Student Graduation Time","authors":"S. Wibowo, R. Andreswari, M. A. Hasibuan","doi":"10.1109/EECSI.2018.8752876","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752876","url":null,"abstract":"Information Systems is one of the existing study program at Telkom University that has produced many graduates since it was established in 2008. However, not all graduates produced successfully completed the study period during the four years of normal study. The percentage of graduates on time has some decline between the target and the achievement of the study program. From academic year 2014/2015 to 2016/2017 decrease annually about 1% every year, which is it becomes problems for the credibility and existence of study program and also for academic planners who may have an impact on accreditation assessment process of the study program when it is audited. One of the efforts that can be done by the study program to increase the students on time graduation rate is by making decision support system dashboard that giving early warning to the lecturer or the head of the study program if there are students who are predicted not to graduate on time. By using the C4.5 algorithm to perform the data analysis by looking at the causes of student’s graduation time and pureshare methodology to perform dashboard development method. The result of this study is a prototype of decision support system dashboard, because there are lack of analysis in decision making and the dashboard only showing information and temporary prediction. The data model that used on this research is labeling data that has been processed using C4.5 algorithm and data that has been through data cleansing process using Pentaho Data Integration. This prototype is expected to be used as a reference base to support academic planners in order to make this application run with real time data.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"8 1","pages":"684-689"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84234028","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752659
N. Ravichandran, Deokmin Jeon, Junsoo Lee, Jaeseok Park, B. Yun, Sangbong Lee, Pilun Kim, Kwang-Shik Choi, H. Jung, Byeonggyu Jeon, Mansik Jeon, Jeehyun Kim
The Study of mosquitoes and their behavioral analysis are of crucial importance to control the alarmingly increasing mosquito-borne diseases. Conventional imaging techniques use either dissection, exogenous contrast agents. Non-destructive imaging techniques, like x-ray and microcomputed tomography uses ionizing radiations. Hence, a non-destructive and real-time imaging technique which can obtain high resolution images to study the anatomical features of mosquito specimen can greatly aid researchers for mosquito studies. In this study, the three-dimensional imaging capabilities of optical coherence tomography (OCT) for structural analysis of Anopheles sinensis mosquitoes has been demonstrated. The anatomical features of An. sinensis head, thorax, and abdomen regions along with internal morphological structures like foregut, midgut, and hindgut were studied using OCT imaging. Two-dimensional (2D) and three-dimensional (3D) OCT images along with histology images were helpful for the anatomical analysis of the mosquito specimens. From the concurred results and by exhibiting this as an initial study, the applicability of OCT in future entomological researches related to mosquitoes and changes in its anatomical structure is demonstrated.
{"title":"OCT for non-destructive examination of the internal biological structures of mosquito specimen","authors":"N. Ravichandran, Deokmin Jeon, Junsoo Lee, Jaeseok Park, B. Yun, Sangbong Lee, Pilun Kim, Kwang-Shik Choi, H. Jung, Byeonggyu Jeon, Mansik Jeon, Jeehyun Kim","doi":"10.1109/EECSI.2018.8752659","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752659","url":null,"abstract":"The Study of mosquitoes and their behavioral analysis are of crucial importance to control the alarmingly increasing mosquito-borne diseases. Conventional imaging techniques use either dissection, exogenous contrast agents. Non-destructive imaging techniques, like x-ray and microcomputed tomography uses ionizing radiations. Hence, a non-destructive and real-time imaging technique which can obtain high resolution images to study the anatomical features of mosquito specimen can greatly aid researchers for mosquito studies. In this study, the three-dimensional imaging capabilities of optical coherence tomography (OCT) for structural analysis of Anopheles sinensis mosquitoes has been demonstrated. The anatomical features of An. sinensis head, thorax, and abdomen regions along with internal morphological structures like foregut, midgut, and hindgut were studied using OCT imaging. Two-dimensional (2D) and three-dimensional (3D) OCT images along with histology images were helpful for the anatomical analysis of the mosquito specimens. From the concurred results and by exhibiting this as an initial study, the applicability of OCT in future entomological researches related to mosquitoes and changes in its anatomical structure is demonstrated.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"1967 1","pages":"436-439"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91397991","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752649
K. Prilianti, Ivan C. Onggara, M. A. Adhiwibawa, T. H. Brotosudarmo, S. Anam, A. Suryanto
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).
{"title":"Multispectral Imaging and Convolutional Neural Network for Photosynthetic Pigments Prediction","authors":"K. Prilianti, Ivan C. Onggara, M. A. Adhiwibawa, T. H. Brotosudarmo, S. Anam, A. Suryanto","doi":"10.1109/EECSI.2018.8752649","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752649","url":null,"abstract":"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).","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"27 1","pages":"554-559"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85027953","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752769
M. O. Pratama, W. Satyawan, Bagus Fajar, Rusnandi Fikri, Haris Hamzah
Indonesian ID Card can be used to recognize citizen of Indonesia identity in several requirements like for sales and purchasing recording, admission and other transaction processing systems (TPS). Current TPS system used citizen ID Card by entering the data manually that means time consuming, prone to error and not efficient. In this research, we propose a model of citizen id card detection using state-of-the-art Deep Learning models: Convolutional Neural Networks (CNN). The result, we can obtain possitive accuracy citizen id card recognition using deep learning. We also compare the result of CNN with traditional computer vision techniques.
{"title":"Indonesian ID Card Recognition using Convolutional Neural Networks","authors":"M. O. Pratama, W. Satyawan, Bagus Fajar, Rusnandi Fikri, Haris Hamzah","doi":"10.1109/EECSI.2018.8752769","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752769","url":null,"abstract":"Indonesian ID Card can be used to recognize citizen of Indonesia identity in several requirements like for sales and purchasing recording, admission and other transaction processing systems (TPS). Current TPS system used citizen ID Card by entering the data manually that means time consuming, prone to error and not efficient. In this research, we propose a model of citizen id card detection using state-of-the-art Deep Learning models: Convolutional Neural Networks (CNN). The result, we can obtain possitive accuracy citizen id card recognition using deep learning. We also compare the result of CNN with traditional computer vision techniques.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"140 1","pages":"178-181"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76693921","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752686
Quota Alief Sias, I. Fadlika, I. Wahyono, Arif Nur Afandi
Z-Source Inverter (ZSI) is famous power converter who has capability to deal with voltage sags, improved power factor and wide voltage range of output. Quasi Z Source Inverter (QZSI) is the modern ZSI who has continuous current of input and can reduce stress of the passive component. This paper proposes simple boost QZSI circuit as Maximum Power Point Tracking (MPPT) using Grey Wolf Optimization (GWO) algorithm in photovoltaic system. Grey Wolf algorithm has been compared with the Perturb and Observed (P&O) technique for gaining the maximum power from the sun. Both techniques can get the optimum power of solar panel not only at constant sun light condition but also under varying irradiance levels. The value of average power obtained from GWO technique is greater than P&O. Although the value of solar radiation changes, the output voltage remains stable and both algorithms carry on obtaining optimal power of the sun.
z源逆变器(Z-Source Inverter, ZSI)是一种具有抗电压跌落、提高功率因数、宽输出电压范围等特点的著名功率变换器。准Z源逆变器(Quasi Z Source Inverter，简称QZSI)是一种具有连续输入电流并能减小无源元件应力的现代Z源逆变器。本文提出了一种简单的升压QZSI电路作为光伏系统中使用灰狼优化算法的最大功率点跟踪(MPPT)。将灰狼算法与扰动观测(P&O)技术进行了比较，以获得太阳的最大功率。这两种技术不仅可以在恒定的光照条件下，而且可以在不同的辐照度下获得最佳的太阳能电池板功率。GWO技术的平均功率值大于P&O技术。虽然太阳辐射值发生变化，但输出电压保持稳定，两种算法都能获得太阳的最优功率。
{"title":"Quasi Z-Source Inverter as MPPT on Renewable Energy using Grey Wolf Technique","authors":"Quota Alief Sias, I. Fadlika, I. Wahyono, Arif Nur Afandi","doi":"10.1109/EECSI.2018.8752686","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752686","url":null,"abstract":"Z-Source Inverter (ZSI) is famous power converter who has capability to deal with voltage sags, improved power factor and wide voltage range of output. Quasi Z Source Inverter (QZSI) is the modern ZSI who has continuous current of input and can reduce stress of the passive component. This paper proposes simple boost QZSI circuit as Maximum Power Point Tracking (MPPT) using Grey Wolf Optimization (GWO) algorithm in photovoltaic system. Grey Wolf algorithm has been compared with the Perturb and Observed (P&O) technique for gaining the maximum power from the sun. Both techniques can get the optimum power of solar panel not only at constant sun light condition but also under varying irradiance levels. The value of average power obtained from GWO technique is greater than P&O. Although the value of solar radiation changes, the output voltage remains stable and both algorithms carry on obtaining optimal power of the sun.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"22 1","pages":"362-366"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80819346","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752874
Mehdi Guessous, L. Zenkouar
Dynamic Radio Resource Management (RRM) is a major building block of Wireless LAN Controllers (WLC) function in WLAN networks. In a dense and frequently changing WLANs, it maximizes Wireless Devices (WD) opportunity to transmit and guarantees conformance to the design Service Level Agreement (SLA). To achieve this performance, a WLC processes and applies a network-wide optimized radio plan based on data from access points (AP) and upper-layer application services. This coverage processing requires a "realistic" modelization approach of the radio environment and a quick adaptation to frequent changes. In this paper, we build on our Beam-based approach to radio coverage modelization. We propose a new Machine Learning Regression (MLR)-based optimization and compare it to our NURBS-based solution performance, as an alternative. We show that both solutions have very comparable processing times. Nevertheless, our MLR-based solution represents a more significant prediction accuracy enhancement than its alternative.
{"title":"ML-Optimized Beam-based Radio Coverage Processing in IEEE 802.11 WLAN Networks","authors":"Mehdi Guessous, L. Zenkouar","doi":"10.1109/EECSI.2018.8752874","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752874","url":null,"abstract":"Dynamic Radio Resource Management (RRM) is a major building block of Wireless LAN Controllers (WLC) function in WLAN networks. In a dense and frequently changing WLANs, it maximizes Wireless Devices (WD) opportunity to transmit and guarantees conformance to the design Service Level Agreement (SLA). To achieve this performance, a WLC processes and applies a network-wide optimized radio plan based on data from access points (AP) and upper-layer application services. This coverage processing requires a \"realistic\" modelization approach of the radio environment and a quick adaptation to frequent changes. In this paper, we build on our Beam-based approach to radio coverage modelization. We propose a new Machine Learning Regression (MLR)-based optimization and compare it to our NURBS-based solution performance, as an alternative. We show that both solutions have very comparable processing times. Nevertheless, our MLR-based solution represents a more significant prediction accuracy enhancement than its alternative.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"36 1","pages":"564-570"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90908464","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752726
Ahmad Zoebad Foeady, D. C. R. Novitasari, Ahmad Hanif Asyhar, Muhammad Firmansjah
Diabetic Retinopathy (DR) is the cause of blindness. Early identification needed for prevent the DR. However, High hospital cost for eye examination makes many patients allow the DR to spread and lead to blindness. This study identifies DR patients by using color fundus image with SVM classification method. The purpose of this study is to minimize the funds spent or can also be a breakthrough for people with DR who lack the funds for diagnosis in the hospital. Pre-processing process have a several steps such as green channel extraction, histogram equalization, filtering, optic disk removal with structuring elements on morphological operation, and contrast enhancement. Feature extraction of preprocessing result using GLCM and the data taken consists of contrast, correlation, energy, and homogeneity. The detected components in this study are blood vessels, microaneurysms, and hemorrhages. This study results what the accuracy of classification using SVM and feature from GLCM method is 82.35% for normal eye and DR, 100% for NPDR and PDR. So, this program can be used for diagnosing DR accurately.
{"title":"Automated Diagnosis System of Diabetic Retinopathy Using GLCM Method and SVM Classifier","authors":"Ahmad Zoebad Foeady, D. C. R. Novitasari, Ahmad Hanif Asyhar, Muhammad Firmansjah","doi":"10.1109/EECSI.2018.8752726","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752726","url":null,"abstract":"Diabetic Retinopathy (DR) is the cause of blindness. Early identification needed for prevent the DR. However, High hospital cost for eye examination makes many patients allow the DR to spread and lead to blindness. This study identifies DR patients by using color fundus image with SVM classification method. The purpose of this study is to minimize the funds spent or can also be a breakthrough for people with DR who lack the funds for diagnosis in the hospital. Pre-processing process have a several steps such as green channel extraction, histogram equalization, filtering, optic disk removal with structuring elements on morphological operation, and contrast enhancement. Feature extraction of preprocessing result using GLCM and the data taken consists of contrast, correlation, energy, and homogeneity. The detected components in this study are blood vessels, microaneurysms, and hemorrhages. This study results what the accuracy of classification using SVM and feature from GLCM method is 82.35% for normal eye and DR, 100% for NPDR and PDR. So, this program can be used for diagnosing DR accurately.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"12 1","pages":"154-160"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74366186","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752953
Wiwin Agus Kristiana, Mochamad Mizanul Achlaq, Benediktus Anindito, Aryo Nugroho, Cahyo Darujati, Moh Noor Al Azam
Smartphone users are increasingly diverse in using their phones. Some tasks that monitored through the bulletin boards or computer screens, lately it can be done anywhere with a mobile phone while on the move. Similarly, the features in smartphones are increasingly following the development of communication technology. One of them is Bluetooth version 4, which currently can always be available on all types of smartphones. Even for entry-level phones that commonly used by students, nowadays are equipped with the new version of Bluetooth. In this paper discussed the application of BLE or Bluetooth Low Energy, which is part of Bluetooth version 4, to provide the information about availability, lecture schedule, and lecture room at the University Narotama. By using this BLE communication technology all smartphones equipped with BLE, enabling the NARO-MOBILE application and residing in the campus environment, will receive all the latest information provided by SIMNARO - Narotama University Management Information System, in a real-time.
{"title":"UUID Beacon Advertisements For Lecture Schedule Information","authors":"Wiwin Agus Kristiana, Mochamad Mizanul Achlaq, Benediktus Anindito, Aryo Nugroho, Cahyo Darujati, Moh Noor Al Azam","doi":"10.1109/EECSI.2018.8752953","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752953","url":null,"abstract":"Smartphone users are increasingly diverse in using their phones. Some tasks that monitored through the bulletin boards or computer screens, lately it can be done anywhere with a mobile phone while on the move. Similarly, the features in smartphones are increasingly following the development of communication technology. One of them is Bluetooth version 4, which currently can always be available on all types of smartphones. Even for entry-level phones that commonly used by students, nowadays are equipped with the new version of Bluetooth. In this paper discussed the application of BLE or Bluetooth Low Energy, which is part of Bluetooth version 4, to provide the information about availability, lecture schedule, and lecture room at the University Narotama. By using this BLE communication technology all smartphones equipped with BLE, enabling the NARO-MOBILE application and residing in the campus environment, will receive all the latest information provided by SIMNARO - Narotama University Management Information System, in a real-time.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"44 1","pages":"270-276"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90574306","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 : 2018-10-01DOI: 10.1109/EECSI.2018.8752889
Radinal Setyadinsa, M. R. Shihab, Y. G. Sucahyo
The aim of this research was to discover the stances of individual elements as antecedents of mobile payment usage. Data was gathered by distributing a questionnaire, which in latter steps was analyzed quantitatively. This research collected 90 samples, of whom represented users of a mobile payment service in Indonesia. The collected dataset was statistically analyzed, by employing partial least square structural equational modelling (PLS-SEM), aided with SmartPLS3.0. The results showed that two types of individual factors, namely individual difference and behavioral belief played significant roles in shaping users’ intention to use mobile payments. Individual differences, consisting of mobile payment knowledge and compatibility significantly influenced perceived ease of use. Behavioral belief, such as trust, was shown to significantly influenced perceived usefulness. Finally, perceived ease of use and perceived usefulness concertedly affected mobile payment users’ intention to use.
{"title":"Individual Factors As Antecedents of Mobile Payment Usage","authors":"Radinal Setyadinsa, M. R. Shihab, Y. G. Sucahyo","doi":"10.1109/EECSI.2018.8752889","DOIUrl":"https://doi.org/10.1109/EECSI.2018.8752889","url":null,"abstract":"The aim of this research was to discover the stances of individual elements as antecedents of mobile payment usage. Data was gathered by distributing a questionnaire, which in latter steps was analyzed quantitatively. This research collected 90 samples, of whom represented users of a mobile payment service in Indonesia. The collected dataset was statistically analyzed, by employing partial least square structural equational modelling (PLS-SEM), aided with SmartPLS3.0. The results showed that two types of individual factors, namely individual difference and behavioral belief played significant roles in shaping users’ intention to use mobile payments. Individual differences, consisting of mobile payment knowledge and compatibility significantly influenced perceived ease of use. Behavioral belief, such as trust, was shown to significantly influenced perceived usefulness. Finally, perceived ease of use and perceived usefulness concertedly affected mobile payment users’ intention to use.","PeriodicalId":6543,"journal":{"name":"2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"136 1","pages":"514-518"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76385808","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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