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2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)最新文献

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Prototype of Automatic Essay Assessment and Plagiarism Detection on Mobile Learning "Molearn" Application Using GLSA Method 基于GLSA方法的移动学习“mollearn”应用论文自动评估与抄袭检测原型
Julianto Lemantara, M. J. Dewiyani Sunarto, B. Hariadi, T. Sagirani, Tania Amelia
In evaluating the student’s learning outcomes, essay exams were commonly used by teachers to measure the level of student’s understanding of the learning material. However assessing essay answers was more difficult in reality because it contained teacher’s subjectivity and required a longer correction time. In addition, detecting similarity in essay answers between students also required more teacher’s efforts. In previous studies, a prototype of essay answer assessment and plagiarism detection had been successfully created. However, the prototype display still needed an improvement based on the evaluation results given by biology teachers in East Java Province as the application users. The previous prototype also still carried the Latent Semantic Analysis (LSA) method which had several weaknesses. Therefore, this study aimed to produce prototypes that had better display and text similarity methods. The Generalized Latent Semantic Analysis (GLSA) method was chosen because it was able to cover the weaknesses of the LSA method. GLSA was able to detect sentences that had syntactic errors or missing common words. Based on the evaluation results, this study succeeded in producing a prototype with a better display value. The level of user satisfaction increased by 6.12%. In addition, the study succeeded in using the GLSA method as a substitute for LSA for creating better prototype essay assessment and automatic plagiarism detection.
在评估学生的学习成果时,论文考试通常被教师用来衡量学生对学习材料的理解程度。然而,在现实中,作文答案的评估难度较大,因为它包含了教师的主观性,并且需要更长的修改时间。此外,发现学生之间作文答案的相似性也需要老师付出更多的努力。在以往的研究中,已经成功创建了一个论文答案评估和抄袭检测的原型。然而,根据东爪哇省生物教师作为应用用户给出的评价结果,原型显示还需要改进。先前的原型仍然采用了潜在语义分析(LSA)方法,该方法有几个缺点。因此,本研究旨在制作具有更好的显示和文本相似方法的原型。选择广义潜在语义分析(GLSA)方法是因为它能够弥补LSA方法的不足。GLSA能够检测出有句法错误或缺少常用词的句子。根据评估结果,本研究成功制作出具有较好显示价值的样机。用户满意度提升6.12%。此外,本研究成功地使用GLSA方法替代LSA方法来创建更好的原型论文评估和自动抄袭检测。
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引用次数: 2
Comparison of Real Time Iterative Deepening Best First Search Algorithm and A* Algorithm on Maze Chase Game NPC 实时迭代深化最优优先搜索算法与A*算法在迷宫追逐游戏NPC中的比较
Husein Nabil, S. M. Nasution, Ratna Astuti Nugrahaeni
Maze Chase is a game that has a maze background. In this game there are players who have the task, which is to take all the points in the labyrinth. In the Maze Chase game there is also an NPC (Non-Playable Character) that aims to chase players so that players cannot take all the points in the labyrinth. Players can be considered to have won the game is that all the points in the labyrinth have been taken by the player. The author implements the A* and RIBS path search algorithms for NPCs so that NPCs can chase players. That way we get the travel time comparison to the players on each path search algorithm. After testing the average travel time to NPC players with the A* algorithm faster 0.116196% than NPC with the RIBS algorithm.
《Maze Chase》是一款以迷宫为背景的游戏。在这个游戏中,玩家的任务是在迷宫中获得所有的点数。在《Maze Chase》中,还有一个NPC(非可玩角色)旨在追逐玩家,这样玩家就无法在迷宫中获得所有分数。玩家可以认为自己赢得了游戏是在迷宫中所有的点数都被玩家拿走了。作者为npc执行了A*和rib路径搜索算法,以便npc能够追逐玩家。这样我们就得到了玩家在每个路径搜索算法上的旅行时间对比。经过测试,使用A*算法的NPC玩家的平均旅行时间比使用rib算法的NPC快0.116196%。
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引用次数: 0
Design of Automated Polarization based on EDU-QCRY 1 基于EDU-QCRY的自动偏振设计
Carensy Donabela, M. A. Ulin Nuha, Rini Wisnu Wardhani, Mohamad Syahral, Dion Ogi, Dedy Septono Catur Putranto
Polarization Automation based on EDU-QCRY 1 is a system designed to facilitate the use of EDU-QCRY 1 devices in simulation of sending Quantum Bit (Qubit). Polarization automation utilizes quantum mechanical properties on the EDU QCRY 1 device, which will produce bits through polarization automation on the EDU-QCRY 1 quantum polarizator device. Polarization rotation will be done automatically and randomly using an ultrasonic piezomotor device that receives random voltage input on the Arduino Uno microcontroller. The random voltage input is based on a random source from the accelerometer sensor. The measurement results of the accelerometer sensor will be processed and converted into voltage as input to perform automatic and random polarization rotations on the EDU QCRY polariator device. Furthermore, the automatic polarization results will produce a series of numbers that run on the principle of anti-cloning and quantum mechanical properties.
基于EDU-QCRY 1的极化自动化系统是为了方便使用EDU-QCRY 1器件模拟发送量子比特(Qubit)而设计的。极化自动化利用EDU-QCRY 1器件上的量子力学特性,通过EDU-QCRY 1量子偏振器件上的极化自动化产生比特。在Arduino Uno微控制器上使用一个接收随机电压输入的超声波压电马达装置,自动和随机地完成极化旋转。随机电压输入基于来自加速度计传感器的随机源。将加速度计传感器的测量结果进行处理并转换为电压作为输入,在EDU QCRY极化装置上进行自动和随机极化旋转。此外,自动极化结果将产生一系列基于反克隆原理和量子力学特性的数字。
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引用次数: 1
Simulation of the Influence of environmental factors related to Greenhouses using Augmented Reality 利用增强现实技术模拟温室相关环境因素的影响
Thusitha Shaleendra, Buddhi Tharuka Wishvamali, N. Gunarathne, S. Hareendran, P. Abeygunawardhana
With the vast growth of the population, increased production of agricultural products is necessary. Although the amount of land available for agriculture is limited, the demand for food products based on agriculture is expanding. The Organic food supply is scarce in the current food market; hence, their retail prices are higher than the other agricultural products which were produced with the use of pesticides. In this context, Greenhouse production is widely used all over the world with minimal pesticides and weedicides including Sri Lanka. Automated Greenhouses can be used to increase production with a minimum amount of human labor. With less use of human hours, it will produce more harvest than conventional Greenhouses which need constant human attention and care. The installation of automated Greenhouses is costly although their long-term benefits are higher than a conventional one. For this reason, introducing the concept to cultivators would be difficult, as they are reluctant to invest their money on unfamiliar technology. There is a hesitance to embrace technology since they don’t have the first-hand experience in operating an automated Greenhouse. Therefore, in this paper, we present a simulated model of automated Greenhouse using Augmented reality, through which a client can visually experience the workings of IoT Greenhouse based on theoretical models beforehand to make an informed decision to invest in automated Greenhouses.
随着人口的大量增长,必须增加农产品的产量。虽然可用于农业的土地数量有限,但对以农业为基础的食品的需求正在扩大。目前的食品市场上,有机食品供应稀缺;因此,它们的零售价格高于其他使用农药生产的农产品。在这种情况下,温室生产在世界各地广泛使用,农药和除草剂最少,包括斯里兰卡。自动化温室可以用最少的人力来增加产量。与需要人类持续关注和护理的传统温室相比,它使用的人力时间更少,将产生更多的收获。安装自动化温室的成本很高,尽管它们的长期效益高于传统温室。因此,把这个概念介绍给耕耘者是很困难的,因为他们不愿意把钱投资在不熟悉的技术上。由于他们没有操作自动化温室的第一手经验,因此他们对采用技术犹豫不决。因此,在本文中,我们提出了一个使用增强现实技术的自动化温室模拟模型,通过该模型,客户可以预先根据理论模型直观地体验物联网温室的工作原理,从而做出投资自动化温室的明智决策。
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引用次数: 3
Electronic Loads Control and Management Using Priority Queue Algorithm on Android Based Smartphone 基于Android智能手机优先队列算法的电子负载控制与管理
Shofyan Arsyad Widhiono, Muhammad Ary Murti, C. Setianingsih
In this modern age, electricity has become essential things in every aspect of living. To ensure its proper use, a program created to help regulate electricity usage based on user defined priority. In this study Priority Queue Algorithm is used to measure how long every can stay active so it will not drain user’s monthly electricity target usage. The calculation process is done on android device then the execution order to turn the devices on or off are sent to database MySQL The result obtained from this research that priority queue algorithm is able to regulate electricity usage based on rule testing and fast response time to control and retrieve data from the database, 0.006s average time on manual control system, 0.005s average time on automatic control system, and 0.004s average time on retrieving data.
在这个现代时代,电已经成为生活各个方面必不可少的东西。为了确保其正确使用,根据用户定义的优先级创建了一个程序来帮助调节用电量。在本研究中,使用优先队列算法来衡量每个人可以保持多长时间的活动,以便它不会耗尽用户的每月电力目标使用量。计算过程在android设备上完成,然后将打开或关闭设备的执行命令发送到数据库MySQL。研究结果表明,优先队列算法能够根据规则测试和快速响应时间来调节用电量,控制和检索数据库数据,手动控制系统平均时间为0.006s,自动控制系统平均时间为0.005s,检索数据平均时间为0.004s。
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引用次数: 0
Collaborative Whitelist Packet Filtering Driven by Smart Contract Forum 智能合约论坛驱动的协同白名单包过滤
Fahrudin Mukti Wibowo, M. Sidiq, Imadudin Alif Akbar, A. Basuki, D. Rosiyadi
The massive spread of harmful content on the internet is hard to filter. Meanwhile, blacklist content filtering cannot keep up with the rapid growth of content creations. As a result, an extra protection layer is required to provide a safe internet for children. However, implementing a network or application firewall requires an expert’s knowledge and complicated maintenance. In this paper, we proposed a framework to automate internet protection by using whitelist packet filtering. We use the blockchain smart contract as the secure collaboration media to determine the filtering rules. Meanwhile, the SDN controller automates the packet filtering by installing the determined forwarding rules into the network switches. We evaluate the whitelist packet filtering by using Mininet for the network emulation and Ethereum Rinkeby networks for the smart contract implementation. The result shows that the proposed whitelist system can filter the packet without incurring significant latency. It supports fast content update with a maximum speed of ≈ 1200 valid contents per-minute by using a three-votes verification system.
互联网上大量传播的有害内容很难过滤。同时,黑名单内容过滤也跟不上内容创作的快速增长。因此,需要一个额外的保护层来为儿童提供一个安全的互联网。然而,实现网络或应用程序防火墙需要专家的知识和复杂的维护。本文提出了一种利用白名单包过滤实现网络防护自动化的框架。我们使用区块链智能合约作为安全协作媒介来确定过滤规则。同时,SDN控制器通过在网络交换机中安装确定的转发规则,实现包过滤的自动化。我们通过使用Mininet进行网络仿真和使用Ethereum Rinkeby网络进行智能合约实现来评估白名单包过滤。结果表明,所提出的白名单系统可以在不产生明显延迟的情况下过滤数据包。它支持快速的内容更新,最大速度为每分钟≈1200个有效内容,使用三票验证系统。
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引用次数: 3
Selection of Tourism Destinations Priority using 6AsTD Framework and TOPSIS 基于6AsTD框架和TOPSIS的旅游目的地优先选择
Yunifa Miftachul Arif, S. M. S. Nugroho, M. Hariadi
Many tourist cities in developing countries, especially in Indonesia, have exciting tourism destinations. However, some of them do not use a good management concept, for example, to develop tourism destinations. Early process in the development of the destination is making priority selection appropriately. They should consider the success level of tourism destinations. This paper discusses implementations of the 6AsTD framework and TOPSIS method as a combination concept to select destinations priority that recommended to do development. 6AsTD has six components that reflect successful tourism destinations. All components used in the process of the TOPSIS method as input criteria. This research used 11 tourism destinations data bundles in Batu City. The result is a tourism destination with the highest priority has a score of 0.88, and the lowest priority has a score of 0.19.
发展中国家的许多旅游城市,特别是印度尼西亚的旅游城市,都有令人兴奋的旅游目的地。然而,有些企业并没有运用良好的管理理念,例如开发旅游目的地。在目的地开发的早期过程中,适当地进行优先选择。他们应该考虑旅游目的地的成功程度。本文讨论了6AsTD框架和TOPSIS方法的实现,作为一个组合概念来选择推荐做开发的目的地优先级。6AsTD有六个组成部分,反映了成功的旅游目的地。所有组件在TOPSIS过程中使用的方法作为输入标准。本研究使用了拔都市11个旅游目的地的数据包。结果表明,优先级最高的旅游目的地得分为0.88,优先级最低的旅游目的地得分为0.19。
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引用次数: 8
Converging Security Threats and Attacks Insinuation in Multidisciplinary Machine Learning Applications: A Survey 多学科机器学习应用中的融合安全威胁和攻击暗示:调查
S. Madhusudhanan, Renjith R. Nair
Security threats and attacks are increasing day by day with an inclination that insinuates most of the multidisciplinary Machine Learning (ML) applications. Artificial Intelligence (AI) is playing a major role in most of these multidisciplinary ML applications which help applications to sample, learn and decide to act wisely depending on the situation. The intelligence required for processing the data and take decisions opens the door towards vulnerabilities. This will take place when it converges with the world of Internet. Design of a secure realm that mitigates the attacks against privacy preservation in multidisciplinary ML applications is of paramount concern. Thus, it is a must to have an understanding of the security threats and attacks that can affect the ML applications or ML models. In this work we have listed various research work that has developed security models to defend the attacks on multidisciplinary ML applications including the traditional or existing ML and deep learning solutions. Then, we have categorized various security threats and attacks against some of the existing multidisciplinary ML applications. Finally, we have listed some defensive strategies that can enrich and complement to build a secure and efficient multidisciplinary ML model or application.
安全威胁和攻击日益增加,并倾向于暗示大多数多学科机器学习(ML)应用程序。人工智能(AI)在大多数这些多学科机器学习应用中发挥着重要作用,它帮助应用程序根据情况进行采样,学习并决定明智地采取行动。处理数据和做出决策所需的智能为漏洞打开了大门。这将在它与互联网世界融合时发生。在多学科机器学习应用程序中,设计一个安全领域以减轻对隐私保护的攻击是最重要的问题。因此,必须了解可能影响ML应用程序或ML模型的安全威胁和攻击。在这项工作中,我们列出了各种研究工作,这些研究工作开发了安全模型,以防御对多学科机器学习应用程序的攻击,包括传统或现有的机器学习和深度学习解决方案。然后,我们对针对一些现有多学科ML应用程序的各种安全威胁和攻击进行了分类。最后,我们列出了一些防御策略,这些策略可以丰富和补充构建安全高效的多学科机器学习模型或应用程序。
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引用次数: 1
The combination of the MOORA method and the Copeland Score method as a Group Decision Support System (GDSS) Vendor Selection 结合MOORA方法和Copeland评分方法作为群体决策支持系统(GDSS)供应商选择
Aulia Pasca Sahida, B. Surarso, R. Gernowo
The selection of the right vendor is crucial for the success and competitiveness of manufacturing organizations. Vendor selection decision making has a wide scope and a high level of complexity, which is due to the involvement of various decision makers who have their own preferences. The involvement of various decision makers with their respective preferences, also causes differences in priority over the criteria used. In this paper, it is proposed to use the concept of Group Decision Support System (GDSS) to determine the best vendor based on the aggregation of the preferences of each decision maker. The proposed GDSS concept is to combine the Multi-Objective Optimization method on the basis of Ratio Analysis (MOORA) with the Copeland Score method. The MOORA method is used as a ranking method based on the criteria and weight ratio of each decision maker. The results of ranking using the MOORA method each decision maker is then aggregated using the Copeland Score method, to get the final vendor ranking. The results show that Alternative 5 (Yogatama) has the highest score, so it is ranked first and shows as the best alternative. Sensitivity analysis showed that the proposed GDSS concept was solid, with a low percentage of change.
选择合适的供应商对制造企业的成功和竞争力至关重要。供应商选择决策具有广泛的范围和高度的复杂性,这是由于各种决策者的参与,他们有自己的偏好。不同的决策者以他们各自的偏好参与其中,也造成了对所使用标准的优先次序的差异。本文提出了利用群体决策支持系统(Group Decision Support System, GDSS)的概念,通过汇总各决策者的偏好来确定最佳供应商。本文提出的GDSS概念是将基于Ratio Analysis (MOORA)的多目标优化方法与Copeland Score方法相结合。采用MOORA法根据各决策者的标准和权重比进行排序。使用MOORA方法进行排名的结果,然后使用Copeland Score方法对每个决策者进行汇总,以获得最终的供应商排名。结果显示,选择5 (Yogatama)得分最高,因此排名第一,显示为最佳选择。敏感性分析表明,提出的GDSS概念是可靠的,具有低百分比的变化。
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引用次数: 9
Indonesian Twitter Data Pre-processing for the Emotion Recognition 面向情感识别的印尼推特数据预处理
Ekasari Nugraheni
The 2019 Presidential Election in Indonesia causes sharp political polarization. The battle of discourse between two massive camps took place on social media. Various aspects of public opinion showing how people think and act can be found easily. Twitter as the most popular microblogging platform, offers a place to express a variety of thoughts and opinions. This makes Twitter as a source of opinion mining that can be used to detect people's emotional feelings about an event. This paper explores the pre-processing stages of text classification for the emotion recognition based on Twitter conversations that correlate with the debate of Indonesian presidential candidates. Data pre-processing is an important step in sentiment analysis because the results of the analysis are strongly affected by the quality of the data provided. A combination of data processing has been carried out using Indonesian Twitter datasets. The accuracy of the analysis was tested using a deep learning model MLP and LSTM. The results show that the use of appropriate pre-processing techniques can improve accuracy.
2019年印尼总统大选引发了尖锐的政治两极分化。两大阵营之间的争论在社交媒体上展开。可以很容易地找到显示人们如何思考和行动的公众舆论的各个方面。Twitter作为最受欢迎的微博平台,提供了一个表达各种想法和观点的场所。这使得Twitter成为一个意见挖掘的来源,可以用来检测人们对事件的情感感受。本文探讨了基于与印尼总统候选人辩论相关的Twitter对话的情感识别文本分类的预处理阶段。数据预处理是情感分析的一个重要步骤,因为分析结果受到所提供数据质量的强烈影响。使用印度尼西亚Twitter数据集进行了综合数据处理。使用深度学习模型MLP和LSTM来测试分析的准确性。结果表明,采用适当的预处理技术可以提高精度。
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引用次数: 8
期刊
2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)
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