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Optimization of Resource Allocation and Task Allocation with Project Management Information Systems in Information Technology Companies 利用项目管理信息系统优化信息技术企业的资源配置和任务分配
IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-28 DOI: 10.18421/tem123-65
Ilham Nur Pratama, M. Dachyar, Novandra Rhezza Pratama
This study proposes a novel approach to designing an integrated Resource Allocation and Task Allocation Optimization System (RATAOS) using Enterprise Architecture (EA) to improve project management efficiency. The proposed approach integrates Project Management Information System (PMIS) with an optimization system designed using a random forest model and Natural Language Programming (NLP). The integrated system optimizes resource and task allocation, reducing operational costs by 14% and planning phases by 88.7%. Project completion time increased by 50.80%, demonstrating the effectiveness of the integrated system. The purpose of this study is to find a solution for PMIS to be used as an automatic data-driven Resource and Task Allocation Optimization System. The technique used in this study is service integration between the existing PMIS with the Resource and Task Allocation Optimization System.
本研究提出了一种利用企业体系结构(EA)设计集成资源分配和任务分配优化系统(RATAOS)的新方法,以提高项目管理效率。所提出的方法将项目管理信息系统(PMIS)与使用随机森林模型和自然语言编程(NLP)设计的优化系统相结合。集成系统优化了资源和任务分配,降低了14%的运营成本和88.7%的规划阶段。项目完成时间增加了50.80%,证明了集成系统的有效性。本研究的目的是为PMIS作为一个自动数据驱动的资源和任务分配优化系统找到一种解决方案。本研究中使用的技术是现有PMIS与资源和任务分配优化系统之间的服务集成。
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引用次数: 0
The Role of Cloud Computing on Accounting Information System Quality:A Study in Hotel Industry 云计算对会计信息系统质量的影响——以酒店业为例
IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-28 DOI: 10.18421/tem123-72
D. Syah, I. Muda, Prihatin Lumbanraja, Azizul Kholis
The hotel industry is a significant sector for Indonesian economic growth. Nowadays, cloud computing is bringing much potential for hotels to increase their competitive advantage, specifically in facilitating Information Systems (IS). However, we found still limited study that investigates cloud-based IS in accounting functions. Therefore, this study aims to analyze 1) the impact of the human aspect in determining cloud performance, 2) the impact of cloud performance on the relative advantage and compatibility of cloud-based Accounting Information Systems (AIS) in the hotel industry, and 3) the impact of its relative advantage and compatibility on cloud-based AIS quality. Using purposive sampling, the data was collected from accounting and/or information manager hotels in North Sumatra, Indonesia. The collected data were analyzed using variance-based Structural Equation Modeling (SEM). We found that human, cloud performance, and technology adaptability are the critical antecedents of cloud-based AIS quality in the hotel industry. Hotel leaders should consider user computer-self efficacy and cloud-AIS alignment design while developing and integrating cloud-based AIS into their general system.
酒店业是印尼经济增长的重要部门。如今,云计算为酒店增加竞争优势带来了巨大的潜力,特别是在促进信息系统(is)方面。然而,我们发现在会计职能中调查基于云的信息系统的研究仍然有限。因此,本研究旨在分析1)人为因素在决定云性能方面的影响,2)云性能对酒店行业基于云的会计信息系统(AIS)的相对优势和兼容性的影响,以及3)其相对优势和兼容性对基于云的AIS质量的影响。使用有目的的抽样,从印度尼西亚北苏门答腊岛的会计和/或信息管理酒店收集数据。采用基于方差的结构方程模型(SEM)对收集的数据进行分析。我们发现,人力、云性能和技术适应性是酒店业基于云的AIS质量的关键先决条件。酒店领导在开发和整合基于云的AIS系统到他们的整体系统时,应该考虑用户计算机-自我效能和云-AIS的一致性设计。
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引用次数: 0
Acoustic Vehicle Classification Using Mel-Frequency Features with Long Short-Term Memory Neural Networks 基于Mel频率特征的长短期记忆神经网络声学车辆分类
IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-28 DOI: 10.18421/tem123-29
Ahmad Ihsan Yassin, K. K. Mohd Shariff, Mustapha Awang Kechik, A. Ali, Megat Syahirul Megat Amin
Monitoring vehicle traffic at a large scale is a challenging task for authorities, particularly considering the high cost of traffic sensors such as vision cameras. To meet the growing demand for more accurate traffic monitoring, the use of traffic sounds has become a popular approach, as it provides insight into the types of traffic present. This paper reports on an approach to vehicle classification based on acoustic signals, using the Mel-Frequency Cepstral Coefficients (MFCC) and the Long Short-Term Memory (LSTM) networks. This study exhibited classification accuracy scores of 82-86.2% across four vehicle categories: motorcycle, car, truck, and no traffic. The results demonstrated that large-scale, low-cost acoustic processing can be effectively used for vehicle monitoring.
大规模监控车辆交通对当局来说是一项具有挑战性的任务,特别是考虑到视觉摄像头等交通传感器的高成本。为了满足对更准确的交通监控日益增长的需求,使用交通声音已经成为一种流行的方法,因为它可以深入了解当前的交通类型。本文报告了一种基于声学信号的车辆分类方法,该方法使用梅尔频率倒谱系数(MFCC)和长短期记忆(LSTM)网络。这项研究显示,摩托车、汽车、卡车和无交通四种车辆类别的分类准确率得分为82-86.2%。结果表明,大规模、低成本的声学处理可以有效地用于车辆监测。
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引用次数: 1
Liquid Characterization of 2 GHz Complimentary Split Ring Resonator (CSRR) for Water Quality Applications 用于水质应用的2GHz互补分裂环谐振器(CSRR)的液体特性
IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-28 DOI: 10.18421/tem123-20
M. F. Sapuri, Mohd Khairil Adzhar Mahmood, N. E. Abd Rashid, N. Zakaria, S. A. E. Ab Rahim, Z. I. Khan
This study describes a complementary split-ring resonator (CSRR)-based planar microwave sensor. Its capability in detecting several samples which are based on the usual water contaminant in Malaysia was investigated. The CSRR sensor was designed with an unloaded resonant frequency of 2.0 GHz, and it was fabricated on an FR-4 substrate with a thickness of 1.6 mm and a dielectric constant of 4.3. The S-parameter responses of the sensor were measured under two conditions; i) unloaded and ii) loaded. For the latter, samples of tap water, salt water, isopropyl alcohol, filtered water and cooking oil were used to load the resonant element of the CSRR. The measurement result of unloaded CSRR shows that the designed sensor resonates at 1.99 GHz, which is in line with the simulation. The measurement results also showed that the presence of all samples caused the resonant frequency of the CSRR to shift, with filtered water and cooking oil showing the biggest frequency shifts (0.84 GHz and 0.96 GHz, respectively). A sensitivity analysis of the CSRR was carried out and it shows that it achieves 0.25% sensitivity. The proposed sensor may be a useful substitute for pricey commercial sensors for applications involving water quality because of the inexpensive materials and ease of fabrication.
本研究描述了一种基于互补开口环谐振器(CSRR)的平面微波传感器。研究了它在检测基于马来西亚常见水污染物的几个样本方面的能力。CSRR传感器设计为空载谐振频率为2.0GHz,并在厚度为1.6mm、介电常数为4.3的FR-4基板上制造。传感器的S参数响应是在两种条件下测量的;i) 卸载和ii)加载。对于后者,使用自来水、盐水、异丙醇、过滤水和食用油的样品来加载CSRR的谐振元件。空载CSRR的测量结果表明,所设计的传感器在1.99GHz处产生谐振,与仿真结果一致。测量结果还表明,所有样品的存在都导致CSRR的谐振频率发生偏移,过滤水和食用油的频率偏移最大(分别为0.84GHz和0.96GHz)。对CSRR进行了灵敏度分析,结果表明其灵敏度达到0.25%。由于材料便宜且易于制造,所提出的传感器可能是涉及水质的应用中昂贵的商业传感器的有用替代品。
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引用次数: 0
Exploring the Full Potential of Collaborative Learning and E-Learning Environments in Universities: A Systematic Review 探索大学协作学习和电子学习环境的全部潜力:系统综述
IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-28 DOI: 10.18421/tem123-60
Wagino Wagino, H. Maksum, W. Purwanto, K. Krismadinata, S. Suhendar, Rahmat Desman Koto
This systematic review examines the challenges and potential solutions to improve the implementation of collaborative learning and e-learning environments in universities. The article analyzes 200 relevant articles published between 2014-2022 using a qualitative approach to identify themes and sub-themes related to collaborative learning and e-learning environments. The study reveals various learning methods employed, including MOOC (Massive Open Online Course), digital mind maps, and tripartite learning, but also highlights challenges such as lack of digital infrastructure, low-quality internet networks, and inadequate practical tools. The research emphasizes the need for effective leadership and management in vocational institutions and recommends further research on curriculum development, learning evaluation methods, lecturer performance assessment, and improving digital infrastructure and educator training. Collaboration with industry and other training institutions is also suggested to improve students' employability and entrepreneurship skills.
这篇系统的综述探讨了在大学中改进协作学习和电子学习环境的挑战和潜在的解决方案。本文使用定性方法分析了2014-2022年间发表的200篇相关文章,以确定与协作学习和电子学习环境相关的主题和子主题。该研究揭示了所采用的各种学习方法,包括大规模开放在线课程(MOOC)、数字思维导图和三方学习,但也强调了诸如缺乏数字基础设施、低质量互联网网络和缺乏实用工具等挑战。该研究强调了职业院校有效领导和管理的必要性,并建议进一步研究课程开发、学习评估方法、讲师绩效评估以及改进数字基础设施和教育工作者培训。还建议与行业和其他培训机构合作,以提高学生的就业能力和创业技能。
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引用次数: 1
Developing Air Traffic Control Simulator for Laboratory 研制实验室空中交通管制模拟器
IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-28 DOI: 10.18421/tem123-26
Dimas Arya Soeadyfa Fridyatama, S. Suparji, M. Sumbawati
The widely-used ATC simulator laboratory in air traffic control education lacks research on its development. This study aims to develop a computer-based aerodrome control tower simulator for ATC using the research and development method. The simulator offers a realistic training environment, covering simulation, technicalities, facilities, configuration, equipment, specifications, software, operations, and development. It is a crucial facility in ATC courses at Indonesian aviation universities. Findings demonstrate its effectiveness in enhancing student proficiency and reducing reliance on external suppliers. The resulting design concept, developed through research and development, can be utilized by local experts to promote advanced technology mastery and cost efficiency in ATC training systems. It provides opportunities for local experts and serves as a model for other countries, advancing ATC education.
空中交通管制教育中广泛使用的ATC模拟器实验室缺乏对其发展的研究。本研究旨在利用研发方法开发一种用于ATC的基于计算机的机场塔台模拟器。模拟器提供了一个逼真的训练环境,包括模拟、技术、设施、配置、设备、规范、软件、操作和开发。它是印尼航空大学ATC课程中的一个重要设施。研究结果表明,它在提高学生熟练程度和减少对外部供应商的依赖方面是有效的。通过研究和开发得出的设计理念可供当地专家使用,以促进ATC培训系统的先进技术掌握和成本效益。它为当地专家提供了机会,并为其他国家树立了榜样,推动了ATC教育。
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引用次数: 0
ESG Performance and Disclosure: National Composite Indicators for Monitoring Sustainable Growth Conditions in the EU-27 ESG绩效和披露:监测欧盟27国可持续增长状况的国家综合指标
IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-28 DOI: 10.18421/tem123-68
Petra Jílková, Jana Kotěšovcová
Sustainable growth is a major global concern due to environmental challenges, social and corporate governance matters. Identifying and analyzing key indicators can provide valuable insights into the critical factors affecting sustainability in the EU-27 countries. This paper analyzes environmental, social and governance national composite indicators for monitoring sustainable growth conditions in the EU-27. The authors develop a simplified algorithm based on the ESG index methodology and composite indicators theory. The three pillars of the ESG methodology are examined with a focus on the ten most valuable indicators in each pillar. A sub-objective is to verify what percentage of the results are consistent with the original approach. The data were collected for the EU-27 countries for 2020–2021. The study's main outcome is a simplified approach to measuring sustainability that is 81% consistent with previous calculations. In line with previous studies, Norway, Sweden, and Finland rank highest on the ESG index, while Cyprus, Bulgaria, Lithuania, and Greece rank the lowest.
由于环境挑战、社会和公司治理问题,可持续增长是全球关注的一个主要问题。识别和分析关键指标可以对影响欧盟27国可持续性的关键因素提供有价值的见解。本文分析了用于监测欧盟27国可持续增长状况的环境、社会和治理国家综合指标。作者基于ESG指数方法和综合指标理论,开发了一种简化算法。对ESG方法的三个支柱进行了审查,重点是每个支柱中最有价值的十个指标。一个次要目标是验证结果的百分比与原始方法一致。这些数据是为欧盟27国收集的2020-2021年的数据。该研究的主要结果是一种衡量可持续性的简化方法,与之前的计算结果一致81%。与之前的研究一致,挪威、瑞典和芬兰在ESG指数中排名最高,而塞浦路斯、保加利亚、立陶宛和希腊排名最低。
{"title":"ESG Performance and Disclosure: National Composite Indicators for Monitoring Sustainable Growth Conditions in the EU-27","authors":"Petra Jílková, Jana Kotěšovcová","doi":"10.18421/tem123-68","DOIUrl":"https://doi.org/10.18421/tem123-68","url":null,"abstract":"Sustainable growth is a major global concern due to environmental challenges, social and corporate governance matters. Identifying and analyzing key indicators can provide valuable insights into the critical factors affecting sustainability in the EU-27 countries. This paper analyzes environmental, social and governance national composite indicators for monitoring sustainable growth conditions in the EU-27. The authors develop a simplified algorithm based on the ESG index methodology and composite indicators theory. The three pillars of the ESG methodology are examined with a focus on the ten most valuable indicators in each pillar. A sub-objective is to verify what percentage of the results are consistent with the original approach. The data were collected for the EU-27 countries for 2020–2021. The study's main outcome is a simplified approach to measuring sustainability that is 81% consistent with previous calculations. In line with previous studies, Norway, Sweden, and Finland rank highest on the ESG index, while Cyprus, Bulgaria, Lithuania, and Greece rank the lowest.","PeriodicalId":45439,"journal":{"name":"TEM Journal-Technology Education Management Informatics","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47176486","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
Using a Convolutional Neural Network for Machine Written Character Recognition 使用卷积神经网络进行机器文字识别
IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-28 DOI: 10.18421/tem123-03
Ladislav Karrach, E. Pivarčiová
Convolutional neural networks are special types of artificial neural networks that can solve various tasks in computer vision, such as image classification, object detection, and general recognition. The paper presents the basic building blocks of convolutional neural networks and their architecture, and compares their recognition accuracy with other character recognition techniques using the example of character recognition from vehicle registration plates. The purpose of the experiments was to determine the optimal configuration of the convolutional neural network and the influence of the size and design method of the training set on the recognition rate. The study shows that although convolutional neural networks have recently gained attention, traditional recognition methods are still relevant, and the choice of the right classifier and its configuration depends on the type of recognition task.
卷积神经网络是一种特殊类型的人工神经网络,可以解决计算机视觉中的各种任务,如图像分类、对象检测和一般识别。本文介绍了卷积神经网络的基本组成部分及其体系结构,并以车牌字符识别为例,将其识别精度与其他字符识别技术进行了比较。实验的目的是确定卷积神经网络的最佳配置,以及训练集的大小和设计方法对识别率的影响。研究表明,尽管卷积神经网络最近受到了关注,但传统的识别方法仍然相关,正确分类器及其配置的选择取决于识别任务的类型。
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引用次数: 0
Android-Based Application for Real-Time Indonesian Sign Language Recognition Using Convolutional Neural Network 基于Android的卷积神经网络印尼手语实时识别应用
IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-28 DOI: 10.18421/tem123-35
Raymond Sutjiadi
Individuals with hearing or speech impairments face challenges in communicating with others, requiring special techniques to express their thoughts and feelings. Sign language is an alternative way to communicate using a specific pattern of hand gestures to deliver messages instead of verbal speaking (oral communication). Unfortunately, most people do not know how to use and read sign language. Because of its complexity and many types of sign language worldwide, only well-trained personnel could use it as a communication medium. This research provides a solution in the form of a machine-learning Android-based application designed to recognize sign language captured by a smartphone camera and translate it into Latin characters. The recognition accommodates Convolutional Neural Network (CNN), one of the popular deep learning algorithms. This application recognizes 26 characters of Indonesian Sign Language (Bahasa Isyarat Indonesia/BISINDO) alphabets using MobileNetV3 architecture. To build the data model, dataset images were collected from 5 different models demonstrating 26 BISINDO characters in various lighting, background, and hand gesture position. These dataset images were also generated using image augmentation process to achieve the randomness by adjusting the image rotation, noise, and brightness. Based on the testing result using 6,240 dataset images, the application has 75.38% accuracy in recognizing Indonesian Sign Language alphabets.
有听力或言语障碍的人在与他人沟通时面临挑战,需要特殊的技巧来表达他们的想法和感受。手语是一种使用特定手势传递信息的替代沟通方式,而不是口头交流。不幸的是,大多数人不知道如何使用和阅读手语。由于其复杂性和世界范围内多种手语,只有训练有素的人员才能将其用作交流媒介。这项研究以基于Android的机器学习应用程序的形式提供了一个解决方案,该应用程序旨在识别智能手机摄像头捕捉到的手语,并将其翻译成拉丁字符。该识别包含卷积神经网络(CNN),这是一种流行的深度学习算法。此应用程序使用MobileNetV3架构识别26个印度尼西亚手语(Bahasa Isyarat Indonesia/BISINDO)字母表字符。为了建立数据模型,从5个不同的模型中收集了数据集图像,展示了不同照明、背景和手势位置下的26个BISINDO角色。这些数据集图像也是使用图像增强过程生成的,通过调整图像旋转、噪声和亮度来实现随机性。基于使用6240个数据集图像的测试结果,该应用程序识别印尼手语字母的准确率为75.38%。
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引用次数: 0
Application of Lexicographic Goal Programming Method on Stock Portfolio Optimization With Expected Shortfall Approach 字典目标规划方法在期望缺口法股票投资组合优化中的应用
IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-28 DOI: 10.18421/tem123-19
I. Syahrini, Ariefia Sardini, Nurmaulidar Nurmaulidar, M. Ikhwan
The purpose of this study is to form several optimal portfolios based on the proportion of funds invested in stocks, then the most optimal portfolio will be selected among the optimal portfolios that have been formed. The method used in this study is the lexicographic goal programming method, which is to determine the optimal portfolio based on the proportion of invested funds, then the selection of the most optimal portfolio is determined using the expected shortfall method. This study used data from 5 companies contained in Indonesia Stock Exchange (IDX). The results showed that from the proportion of invested funds, 11 optimal portfolios were obtained. Using the expected shortfall method, the most optimal portfolio of 11 portfolios was obtained, namely type 5 portfolio.
本研究的目的是根据投资于股票的资金比例形成几个最优投资组合,然后在已经形成的最优投资组合中选择最最优的投资组合。本研究中使用的方法是字典目标规划方法,即根据投资资金的比例确定最优投资组合,然后使用预期缺口方法确定最最优投资组合的选择。本研究使用了印度尼西亚证券交易所(IDX)5家公司的数据。结果表明,从投资基金的比例来看,得到了11个最优投资组合。利用期望缺口法,得到了11个投资组合中最优的投资组合,即5型投资组合。
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引用次数: 0
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TEM Journal-Technology Education Management Informatics
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