2020 6th International Conference on Wireless and Telematics (ICWT)最新文献_第3页

TOPSIS Method on Selection of New Employees’ Acceptance 新员工接受度选择的TOPSIS方法

2020 6th International Conference on Wireless and Telematics (ICWT) Pub Date : 2020-09-03 DOI: 10.1109/ICWT50448.2020.9243658

D. R. Ramdania, K. Manaf, Fikri Rahmat Junaedi, A. Fathonih, A. Hadiana

{"title":"TOPSIS Method on Selection of New Employees’ Acceptance","authors":"D. R. Ramdania, K. Manaf, Fikri Rahmat Junaedi, A. Fathonih, A. Hadiana","doi":"10.1109/ICWT50448.2020.9243658","DOIUrl":"https://doi.org/10.1109/ICWT50448.2020.9243658","url":null,"abstract":"A hospital is a labor-intensive organization that requires many personnel and professions from various disciplines. Employees are one of the determinants of the success of a company. One way that agencies use to obtain qualified employees is by making a selection at the time of employee recruitment. The problem that is often encountered is that part-time employee selection is calculated objectively so that it is less efficient and accurate in the selection process. Decision support systems with the TOPSIS method are considered suitable to assist the personnel section of the public Hospital in selecting prospective part-time employees. TOPSIS is a multi-criteria decision-making method based on a concept where the chosen alternative has the closest distance from a positive ideal solution and also has the farthest distance from a negative ideal solution. The completion criteria applied to the selection of employees include the results of written tests, psychological tests, health tests, and interviews. The results of the tests show that the TOPSIS method can be used well in selecting and sorting from the largest to the smallest value with an accuracy rate of 85% in the amount of 20 data.","PeriodicalId":304605,"journal":{"name":"2020 6th International Conference on Wireless and Telematics (ICWT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125358495","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

The Design of Application for Smart Home Base on LoRa 基于LoRa的智能家居应用设计

2020 6th International Conference on Wireless and Telematics (ICWT) Pub Date : 2020-09-03 DOI: 10.1109/ICWT50448.2020.9243648

F.A.R. Mu’amar Wildan, E. A. Z. Hamidi, T. Juhana

{"title":"The Design of Application for Smart Home Base on LoRa","authors":"F.A.R. Mu’amar Wildan, E. A. Z. Hamidi, T. Juhana","doi":"10.1109/ICWT50448.2020.9243648","DOIUrl":"https://doi.org/10.1109/ICWT50448.2020.9243648","url":null,"abstract":"Applicated of LoRa technology itself will not separated from an interface who created to connect between humans and computers in this case a smart home device was made. This study aims to design a GUI interface for LoRa-based smart home and implement a smart home system using applications that can control LoRa-based household electronic devices. The results of this study are devices for applying LoRa-based smart homes and web-based applications as interfaces so that users can use smart home devices. LoRa Dragino is used as a client and server communication tool and the NodeMCU (ESP8266 Module) is used as a liaison between the server and the user through the GUI interface created. This web-based application is compatible with Android 6.0, 7.1.2, 9.0, 10.0, and iOS 9.3.5, and various browsers such as Internet Explorer, Mozilla Firefox, and Google Chrome. The test results of the interface design are made with a 10 times test of each feature that produces 0% error, which means that the features contained in the interface design are made to work according to plan. The average delay when controlling a household electronic device is 3.86 seconds. The furthest communication distance between the LoRa Server and the LoRa Client is 63 meters in blocked space and 183 meters in semi open space.","PeriodicalId":304605,"journal":{"name":"2020 6th International Conference on Wireless and Telematics (ICWT)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127305794","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: 8

A Summarization of the Visual Depression Databases for Depression Detection 抑郁症视觉检测数据库综述

2020 6th International Conference on Wireless and Telematics (ICWT) Pub Date : 2020-09-03 DOI: 10.1109/ICWT50448.2020.9243625

Arselan Ashraf, T. Gunawan, Farah Diyana Abdul Rahman, M. Kartiwi, N. Ismail, Ulfiah

引用次数: 11

Prototype Design of Smart Home System Base on LoRa 基于LoRa的智能家居系统原型设计

2020 6th International Conference on Wireless and Telematics (ICWT) Pub Date : 2020-09-03 DOI: 10.1109/ICWT50448.2020.9243643

S. Opipah, H. Qodim, D. Miharja, Sarbini, E. A. Z. Hamidi, T. Juhana

引用次数: 13

Design of Hardware Module of IoT-based Infant Incubator Monitoring System 基于物联网的婴儿培养箱监控系统硬件模块设计

2020 6th International Conference on Wireless and Telematics (ICWT) Pub Date : 2020-09-03 DOI: 10.1109/ICWT50448.2020.9243665

W. Shalannanda, I. Zakia, E. Sutanto, F. Fahmi

引用次数: 5

Error Performance Analysis of IMM-Kalman Filter for Maneuvering Target Tracking Application imm -卡尔曼滤波在机动目标跟踪中的误差性能分析

2020 6th International Conference on Wireless and Telematics (ICWT) Pub Date : 2020-09-03 DOI: 10.1109/ICWT50448.2020.9243662

Meutia Yunita, J. Suryana, A. Izzuddin

{"title":"Error Performance Analysis of IMM-Kalman Filter for Maneuvering Target Tracking Application","authors":"Meutia Yunita, J. Suryana, A. Izzuddin","doi":"10.1109/ICWT50448.2020.9243662","DOIUrl":"https://doi.org/10.1109/ICWT50448.2020.9243662","url":null,"abstract":"Maneuvering target is one of the important issues in the tracking system algorithm development. Various techniques are used to improve algorithm performance in maneuvering target tracking. The most popular technique is the Interacting Multiple Model (IMM) algorithm. IMM algorithm uses a combination of several types of filter models in the tracking process. In this paper, the error performance of three types of IMM algorithms namely IMM - Kalman Filter (KF) constant velocity (CV) and constant acceleration (CA), IMM-KF constant velocity (CV) and constant turn (CT), and IMM - KF CV, CA, and CT will be compared. The three types of algorithm will also be compared with a single filter KF- CV to see an increase in the performance of the Kalman Filter algorithm on target maneuvers after being combined. The four types of algorithm will be tested in 3 types of generated target trajectories. Based on the simulation results, it is concluded that the IMM-KF that uses 2 types of filter models provide the best error performance compared to other algorithms. These four types of algorithms will also be tested on real measurement data, which is Automatic Dependent Surveillance - Broadcast (ADS-B) measurement data commonly used to support secondary surveillance radar (SSR) at the airports. From the results of the implementation (using ADS-B data), the same conclusions are obtained from the simulation results.","PeriodicalId":304605,"journal":{"name":"2020 6th International Conference on Wireless and Telematics (ICWT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128306192","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

Speech Emotion Recognition using Convolution Neural Networks and Deep Stride Convolutional Neural Networks 基于卷积神经网络和深度跨步卷积神经网络的语音情感识别

2020 6th International Conference on Wireless and Telematics (ICWT) Pub Date : 2020-09-03 DOI: 10.1109/ICWT50448.2020.9243622

T. Wani, T. Gunawan, Syed Asif Ahmad Qadri, H. Mansor, M. Kartiwi, N. Ismail

{"title":"Speech Emotion Recognition using Convolution Neural Networks and Deep Stride Convolutional Neural Networks","authors":"T. Wani, T. Gunawan, Syed Asif Ahmad Qadri, H. Mansor, M. Kartiwi, N. Ismail","doi":"10.1109/ICWT50448.2020.9243622","DOIUrl":"https://doi.org/10.1109/ICWT50448.2020.9243622","url":null,"abstract":"An assortment of techniques has been presented in the area of Speech Emotion Recognition (SER), where the main focus is to recognize the silent discriminants and useful features of speech signals. These features undergo the process of classification to recognize the specific emotion of a speaker. In recent times, deep learning techniques have emerged as a breakthrough in speech emotion recognition to detect and classify emotions. In this paper, we have modified a recently developed different network architecture of convolutional neural networks, i.e., Deep Stride Convolutional Neural Networks (DSCNN), by taking a smaller number of convolutional layers to increase the computational speed while still maintaining accuracy. Besides, we trained the state-of-art model of CNN and proposed DSCNN on spectrograms generated from the SAVEE speech emotion dataset. For the evaluation process, four emotions angry, happy, neutral, and sad, were considered. Evaluation results show that the proposed architecture DSCNN, with the prediction accuracy of 87.8%, outperforms CNN with 79.4% accuracy.","PeriodicalId":304605,"journal":{"name":"2020 6th International Conference on Wireless and Telematics (ICWT)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133907005","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: 16

Block Up Converter Design for Ku Band Ku波段分块转换器设计

2020 6th International Conference on Wireless and Telematics (ICWT) Pub Date : 2020-09-03 DOI: 10.1109/ICWT50448.2020.9243641

P. Herdian, I.Y.M. Edward, Iskandar

引用次数: 0

Research Development and Landscape Artificial Intelligence in Indonesia 印度尼西亚人工智能的研究发展和景观

2020 6th International Conference on Wireless and Telematics (ICWT) Pub Date : 2020-09-03 DOI: 10.1109/ICWT50448.2020.9243659

Muhammad Alvin Noor Reza, E. A. Z. Hamidi, Ririn Herawati, E. Mulyana

{"title":"Research Development and Landscape Artificial Intelligence in Indonesia","authors":"Muhammad Alvin Noor Reza, E. A. Z. Hamidi, Ririn Herawati, E. Mulyana","doi":"10.1109/ICWT50448.2020.9243659","DOIUrl":"https://doi.org/10.1109/ICWT50448.2020.9243659","url":null,"abstract":"This study aims to find out the map of the development of Artificial Intelligence Research in Indonesia. The development of a study will be interrelated with research that has been done before. The existence of methods, infrastructure, data and others become a consideration when conducting research. The success of a study is supported by the existence of these things. The method used is to browse through the Lens.org website with keywords Artificial Intelligence, Machine Learning, Deep Learning, Artificial Neural Network, Convolution Neural Network, Natural Language Processing, Computer Vision, Backpropagation, and Support Vector Machine. Data sources were also taken from surveys conducted using the Google form platform, where the data from the survey results are still in the form of preliminary results. Data from these two sources are exported and processed into several parts, namely the number of publications, the type of publication, the most active institutions, open access publications, the most publications cited and the application of artificial intelligence technology in life aspects. The most published category is Support Vector Machine. The types of publications that are widely publicized are journal articles and conference proceedings. Institutions that have the most publications in each field are generally Telkom University, University of Indonesia, Bandung Institute of Technology and Sepuluh November Institute of Technology. The most cited paper is in the support vector machine category. Based on these data, Artificial Intelligence Research in Indonesia can be said to have developed rapidly.","PeriodicalId":304605,"journal":{"name":"2020 6th International Conference on Wireless and Telematics (ICWT)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134438862","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

Decision Support System For Determining Inventory And Sales Of Goods Using Economic Order Quantity Methods And Linear Regression 基于经济订货量法和线性回归的存货与销售决策支持系统

2020 6th International Conference on Wireless and Telematics (ICWT) Pub Date : 2020-09-03 DOI: 10.1109/ICWT50448.2020.9243619

M. Khaerul, Alam Nurul Cecep, Subaeki Beki, M. F. Kaffah, Ira Rupaida, Aedah Abd Rahman

引用次数: 1