2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE)最新文献_第2页

Simulation of a Solar Power System with Generator Set Backup Source for Hybrid Power System Application 混合动力系统中带发电机组备用电源的太阳能发电系统仿真

2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE) Pub Date : 2019-10-01 DOI: 10.1109/ICEEIE47180.2019.8981414

Y. Rahmawati, S. Sendari, W. Irianto, Toru Matsumoto, David Anggara Putra, D. Arengga

{"title":"Simulation of a Solar Power System with Generator Set Backup Source for Hybrid Power System Application","authors":"Y. Rahmawati, S. Sendari, W. Irianto, Toru Matsumoto, David Anggara Putra, D. Arengga","doi":"10.1109/ICEEIE47180.2019.8981414","DOIUrl":"https://doi.org/10.1109/ICEEIE47180.2019.8981414","url":null,"abstract":"Today the need for electrical energy throughout the world is increasing. This is because the use of electrical energy has penetrated almost all aspects of human life. In general, electrical energy is generated by using oil or gas-fired power plants that are limited and require a long time to be reproduced. And does not rule out the possibility of a system failure that results in the supply of electrical energy not meeting the load requirements, where this will result in a temporary cut off of the electrical energy supply until the system is restored. Therefore, the use of new and renewable energy is considered as an alternative to overcome the bad possibilities that might occur. This paper describes the simulation of backup electrical energy sources using solar cells as the main source and generator sets as additional sources. This system works if the electricity from the network is cut off. The main electrical energy supply from this system is the solar cell, the generator set will be active when the supply of the solar cell cannot meet the load requirements. The process of adding electrical energy by a generator set is controlled by using a microcontroller circuit. Simulation results show that the system can provide electricity more efficiently. The complete simulation has been accomplished using load flow analysis simulation. This simulation is based on the G4 building owned by the Electrical Engineering Department in Universitas Negeri Malang that uses solar panel installation and generator set as the backup source, where the supply of energy is allocated to several priority components.","PeriodicalId":418311,"journal":{"name":"2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127435765","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

Classification of Locally Grown Apple Based On Its Decent Consuming Using Backpropagation Artificial Neural Network 利用反向传播人工神经网络对土产苹果合理消费进行分类

2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE) Pub Date : 2019-10-01 DOI: 10.1109/ICEEIE47180.2019.8981472

M. Muladi, D. Lestari, D. Prasetyo, A. Wibawa, Triyanna Widiyaningtiyas, U. Pujianto

{"title":"Classification of Locally Grown Apple Based On Its Decent Consuming Using Backpropagation Artificial Neural Network","authors":"M. Muladi, D. Lestari, D. Prasetyo, A. Wibawa, Triyanna Widiyaningtiyas, U. Pujianto","doi":"10.1109/ICEEIE47180.2019.8981472","DOIUrl":"https://doi.org/10.1109/ICEEIE47180.2019.8981472","url":null,"abstract":"Fruit is in the highest ranking together with protein as dietary food that containing high energy but low sugar. The risk of some chronic disease may be reduced by consuming fruit. One of the fruits chosen as a diet is apple because it has high phytochemical and anti-oxidant content. As one of the fruits most sought after by the public to maintain diet and competition with imported fruit, handling post-harvest apples is very important. Color is one of the indicators considered when consumers choose fruit. The classification method in sorting fruit automatically is based largely on the color of the fruit because in this method there is no physical contact with the fruit which can cause fruit damage. In this research, the classification system is developed for the Malang's local grown apple Manalagi based on the extraction of the average RGB color feature using the Backpropagation Artificial Neural Network algorithm. The purpose of the developed system is to distinguish the Manalagi, the famous Malang grown apple of worth consumption and not worth the consumption. The fruit classification is based on the average RGB color composition of the fruit skin. The developed system can classify Manalagi in worth consumption and not worth the consumption with an accuracy rate of 90%.","PeriodicalId":418311,"journal":{"name":"2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121792174","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: 3

Implementation of Adaptive Threshold for Peak Detection of Photoplethysmography Applied on Microcontroller 自适应阈值光容积脉搏波峰值检测的单片机实现

2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE) Pub Date : 2019-10-01 DOI: 10.1109/ICEEIE47180.2019.8981423

I. Zaeni, Aripriharta, Mahfud Jiono, D. R. Anzani, Leonel Hernandez

引用次数: 1

Locking Object Position using Camshift Algorithm for Automatic Trolley 基于Camshift算法的自动小车目标位置锁定

2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE) Pub Date : 2019-10-01 DOI: 10.1109/ICEEIE47180.2019.8981447

D. Lestari, S. Sendari, S. Sanjaya, A. N. Handayani, Hsien-I Lin, Ahmad Fahmi

{"title":"Locking Object Position using Camshift Algorithm for Automatic Trolley","authors":"D. Lestari, S. Sendari, S. Sanjaya, A. N. Handayani, Hsien-I Lin, Ahmad Fahmi","doi":"10.1109/ICEEIE47180.2019.8981447","DOIUrl":"https://doi.org/10.1109/ICEEIE47180.2019.8981447","url":null,"abstract":"Today, the development of science and technology produces many innovative devices, that can facilitate people to make their work easier. One of the devices is a trolley, which can help people to bring goods from one place to another place in a modern market. This paper proposed a method to develop an automatic trolley control, which can follow a customer based on the clothes color. The control system is built with Jetson Nano, where a webcam and motors are connected. The webcam has a function as the trolley's eye, which is used to view and retrieve the color data of the customer's clothes. These data are processed by Jetson Nano and the results are sent to the motors for the robot movement. The unique point of this paper is that the trolley has ability to lock the position of a certain customer. To improve the performance of locking object position, the Camshift Algorithm was used. This research conducted three experiments to lock the object position using proposed algorithm. The result of these experiments were: (1) minimum distance between main object and another object to be detected by the camera was 5 cm; (2) the main object was successfully detected by the camera with maximum distance of 360 cm; (3) the camera successfully locked the main object in front of the camera as far as 360 cm while another object stood in front of the camera as far as 20 cm. The advantage of this system is that the trolley can remember the customer that is supposed to be followed even though there are some customer use similar color. This study shows that the trolley can identify the position of customer and follows successfully.","PeriodicalId":418311,"journal":{"name":"2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124902961","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

OSPF Wireless Mesh with MPLS Traffic Engineering OSPF无线Mesh with MPLS流量工程

2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE) Pub Date : 2019-10-01 DOI: 10.1109/ICEEIE47180.2019.8981478

M. Taruk, E. Budiman, M. Wati, Haviluddin

引用次数: 7

Copyright Page 版权页

2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE) Pub Date : 2019-10-01 DOI: 10.1109/ICEEIE47180.2019.8981463

引用次数: 0

Disease Diagnosis System Using Certainty Factor 基于确定性因子的疾病诊断系统

2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE) Pub Date : 2019-10-01 DOI: 10.1109/ICEEIE47180.2019.8981421

J. A. Widians, N. Puspitasari, Aidil Febriansyah

引用次数: 11

Has the VS Ready for Industry 4.0? 美国准备好迎接工业4.0了吗?

2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE) Pub Date : 2019-10-01 DOI: 10.1109/ICEEIE47180.2019.8981476

H. Suswanto, Juwita Annisa Fauzi, A. Wibawa

引用次数: 1

An Augmented Reality Model Physical Transformation Learning 增强现实模型物理转换学习

2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE) Pub Date : 2019-10-01 DOI: 10.1109/ICEEIE47180.2019.8981444

Nathaniel Dengen, H. S. Pakpahan, Gresiandra Fitrahananda Putra, M. Firdaus, R. Wardhana, Andi Tejawati

{"title":"An Augmented Reality Model Physical Transformation Learning","authors":"Nathaniel Dengen, H. S. Pakpahan, Gresiandra Fitrahananda Putra, M. Firdaus, R. Wardhana, Andi Tejawati","doi":"10.1109/ICEEIE47180.2019.8981444","DOIUrl":"https://doi.org/10.1109/ICEEIE47180.2019.8981444","url":null,"abstract":"Every object is made up of small particles such as atoms, molecules or ions. In other words, each particle attracts other particles on its own. There are three forms of common objects, namely solid, liquid and gas. Objects can change from one form to another when heat energy is absorbed or released. This change is known as the physical transformation of an object. This study aims to create an application that can model the process of physical transformation of an object through 3D shapes and animation. The purpose of this research can be problems in the form of changes in a form that is felt to be less implementative, so that the model of this technology exists to be able to fill that gap. The augmented reality method used is the Tracking Based Marker. The results of testing the device shows that the application is made to run smoothly and is suitable for use on Android versions 6.0 and above with a 16: 9 screen aspect ratio. While the results of the study based on questionnaires distributed to senior high school students and college students show that each question from the questionnaire received agree and strongly agree answers ranging from 68% to 89% which indicates positive results.","PeriodicalId":418311,"journal":{"name":"2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126434384","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: 9

SVM Method for Classification of Primary School Teacher Education Journal Articles 基于SVM的小学教师教育期刊文章分类方法

2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE) Pub Date : 2019-10-01 DOI: 10.1109/ICEEIE47180.2019.8981455

U. Pujianto, I. Zaeni, Ninon Oktaviani Irawan

{"title":"SVM Method for Classification of Primary School Teacher Education Journal Articles","authors":"U. Pujianto, I. Zaeni, Ninon Oktaviani Irawan","doi":"10.1109/ICEEIE47180.2019.8981455","DOIUrl":"https://doi.org/10.1109/ICEEIE47180.2019.8981455","url":null,"abstract":"Increasing search for a journal article should be supported by appropriate journal articles search results. Searching for appropriate journal articles can be done by grouping journal articles or information presented based on certain categories. The categorization problem that is often faced is the unbalanced data categorization. So that the settlement of the problem of categorizing unbalanced journal articles in each group will be solved by over-sampling and text classification methods. The purpose of this study is to compare the text classification for the journal articles of Primary School Teacher Education (PGSD) with the Support Vector Machine (SVM) classification method by conducting over-sampling techniques or methods with Synthetic Minority Over-Sampling Technique (SMOTE) and classification of PGSD journal articles using the SVM method only. This research includes text preprocessing processes such as tokenizing and case folding which produce a set of terms or words. The results of words will be weighted using TFIDF. After obtaining the TFIDF value, SMOTE will be conducted to overcome the data imbalance. The data that has been through SMOTE will be classified by the SVM method. The comparison of performance for each method is measured by 3 test outputs, which are accuracy, recall, and precision. From the test results, it was proved that the SVM using SMOTE after the TFIDF value obtained is better for classifying than using the SVM method only. The test value for the SVM method using SMOTE has a precision value of 97.3%, recall of 97.23% and accuracy of 97.22%, while the SVM method has a precision value of 72.55%, recall of 50.71% and accuracy of 80.56%.","PeriodicalId":418311,"journal":{"name":"2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116681767","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