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Intelligent System for Determining Parking Locations in Campus Areas Using Fuzzy Logic Based on Internet of Things 基于物联网模糊逻辑的校园停车场智能定位系统
Pub Date : 2019-04-30 DOI: 10.14710/jtsiskom.7.2.2019.64-70
Dody Ichwana, S. D. Saputra, S. Ekariani
The increasing use of vehicles at campus locations makes it more difficult to find an empty parking lot. This paper develops a system for determining parking locations on campus areas using cloud-based fuzzy logic and Internet of Things (IoT). NFC is used to confirm the order code of the location that has been generated by the system. At the parking location, a sensor is installed to detect parking availability. The concept of IoT has been applied to build this system. Applications on smartphone devices are used for reservations at desired parking locations via the internet. The results show that the system has been able to detect the location of empty parking lots and make reservations in the Andalas University campus environment. The application of fuzzy logic has succeeded in obtaining parking location sequences based on distance and total capacity to find the best parking location.
校园内越来越多的车辆使得找到一个空停车场变得越来越困难。本文利用基于云的模糊逻辑和物联网技术,开发了一个校园停车位置确定系统。NFC用于确认系统生成的位置订单码。在停车位置,安装了一个传感器来检测停车位的可用性。物联网的概念已经被应用于构建这个系统。智能手机上的应用程序可以通过互联网预订所需的停车位。结果表明,该系统在Andalas大学的校园环境中,已经能够检测到空停车场的位置并进行预约。应用模糊逻辑,成功地获得了基于距离和总容量的停车位置序列,从而找到了最佳停车位置。
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引用次数: 1
Manajemen Alokasi Bandwidth Layanan Internet Menggunakan Fractional Knapsack Problem 使用分数背包问题的Internet服务带宽分配管理器
Pub Date : 2019-04-30 DOI: 10.14710/JTSISKOM.7.2.2019.71-76
Ahmad Rizaqu Muttaqi, Sri Wahjuni, Shelvie Nidya Neyman
The technical problems faced in e-government implemented by the Ministry of Religion of Indonesia since 2015 are minimal bandwidth requirements to provide information services and behavior of users who access entertainment sites. When peak hours occur, the congested network often occurs which becomes a significant bottleneck. This study aims to implement bandwidth management using the fractional knapsack problem method by limiting access to entertainment services. The QoS parameters used in this management are throughput, delay, and jitter. The method was tested using a paired t-test using throughput, jitter, and delay test parameters by comparing test parameters before and after bandwidth management applied. The significance value produced is between 75-85%. The method used can control the amount of traffic for each service, but on the other, hand the delay and jitter are still high. It is necessary to add additional free space to each service that can be used when needed to reduce the delay and jitter.
印度尼西亚宗教部自2015年以来实施的电子政务面临的技术问题是提供信息服务的最低带宽要求和访问娱乐网站的用户的行为。当高峰时段出现时,经常会出现网络拥塞,这成为一个重要的瓶颈。本研究旨在通过限制对娱乐服务的访问,使用分数背包问题方法来实现带宽管理。此管理中使用的QoS参数是吞吐量、延迟和抖动。该方法通过比较应用带宽管理前后的测试参数,使用吞吐量、抖动和延迟测试参数进行配对t检验。产生的显著性值在75-85%之间。所使用的方法可以控制每个服务的流量,但另一方面,延迟和抖动仍然很高。有必要为每个服务添加额外的可用空间,以便在需要时使用,以减少延迟和抖动。
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引用次数: 1
Algoritma Genetika untuk Optimasi Komposisi Makanan Bagi Penderita Hipertensi 遗传算法在高血压食品成分优化中的应用
Pub Date : 2019-01-31 DOI: 10.14710/JTSISKOM.7.1.2019.1-6
A. Purnomo, Davia Werdiastu, Talitha Raissa, R. Widodo, Vivi Nur Wijayaningrum
Hypertension can be prevented and handled by eating nutritious foods with the right composition. The genetic algorithm can be used to optimize the food composition for people with hypertension. Data used include sex, age, weight, height, activity type, stress level, and patient hypertension level. This study uses a reproduction method that is good enough to be applied to integer chromosome representations so that the search results provided are not local optimum solutions. The testing results show that the best genetic algorithm parameters are as follows population size is 15 with average fitness 20.97, the generation number is 40 with average fitness 50.10, and combination crossover rate and mutation rate are 0.3 and 0.7 with average fitness 41.67. The solution obtained is the optimal food composition for people with hypertension.
高血压可以通过食用成分正确的营养食品来预防和治疗。遗传算法可用于优化高血压患者的食物成分。使用的数据包括性别、年龄、体重、身高、活动类型、压力水平和患者高血压水平。这项研究使用了一种繁殖方法,该方法足够好,可以应用于整数染色体表示,因此提供的搜索结果不是局部最优解。测试结果表明,最佳遗传算法参数为:群体规模为15,平均适应度为20.97,世代数为40,平均适应力为50.10,组合交叉率和突变率分别为0.3和0.7,平均适应值为41.67。获得的解决方案是高血压患者的最佳食物组成。
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引用次数: 4
Perbandingan Kinerja Block Storage Ceph dan ZFS di Lingkungan Virtual 在虚拟环境中,Ceph和ZFS的性能比较
Pub Date : 2019-01-31 DOI: 10.14710/JTSISKOM.7.1.2019.7-11
Faza Abdani Auni Robbi, Agung Budi Prasetijo, Eko Didik Widianto
The growth of data requires better performance in the storage system. This study aims to analyze the comparison of block storage performance of Ceph and ZFS running in virtual environments. Tests were conducted to measure their performances, including IOPS, CPU usage, throughput, OLTP Database, replication time, and data integrity. Testing was done using 2 node servers with a standard configuration of the storage system. Server virtualization uses Proxmox on each node. ZFS has a higher performance of reading and writing operation than Ceph in IOPS, CPU usage, throughput, OLTP and data replication duration, except the CPU usage in writing operation. The test results are expected to be a reference in the selection of storage systems for data center applications.
随着数据的增长,对存储系统的性能要求越来越高。本研究旨在分析Ceph和ZFS在虚拟环境下运行的块存储性能的比较。进行测试以测量它们的性能,包括IOPS、CPU使用率、吞吐量、OLTP数据库、复制时间和数据完整性。测试使用具有标准存储系统配置的2个节点服务器完成。服务器虚拟化在每个节点上使用Proxmox。ZFS读写性能在IOPS、CPU占用率、吞吐量、OLTP和数据复制持续时间等方面均优于Ceph,但写操作CPU占用率不高。测试结果有望为数据中心应用中存储系统的选择提供参考。
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引用次数: 3
Perbandingan Metode Segmentasi K-Means Clustering dan Segmentasi Region Growing untuk Pengukuran Luas Wilayah Hutan Mangrove K均值聚类分割方法与生长区分割方法在红树林外部测量中的比较
Pub Date : 2019-01-31 DOI: 10.14710/JTSISKOM.7.1.2019.31-37
Tyas Panorama Nan Cerah, Oky Dwi Nurhayati, R. Isnanto
This study aims to examine the k-means clustering and region growing segmentation methods to identify and measure the area of mangrove forests in the Southeast Sulawesi province. The image of the area of this study used Landsat 8 satellite imagery. The area of mangrove forest was carried out by calculating the number of pixels identified as mangrove forests with an area density of 900 m2/pixel. The accuracy of the two segmentation methods in calculating the area was compared based on the same area calculated by LAPAN. The overall accuracy of k-means clustering segmentation method has better accuracy, which is 59.26%, than region growing with 33.33% of accuracy. Both image segmentation methods, k-means clustering and region growing, can be used to calculate the area of mangrove forests in the Southeast Sulawesi region using Landsat 8 satellite imagery.
本研究旨在检验k-means聚类和区域生长分割方法,以识别和测量东南苏拉威西省的红树林面积。本研究区域的图像使用了陆地卫星8号卫星图像。红树林面积是通过计算被确定为面积密度为900平方米/像素的红树林的像素数量来进行的。在LAPAN计算相同面积的基础上,比较了两种分割方法计算面积的准确性。k-means聚类分割方法的整体准确率为59.26%,高于33.33%的区域增长准确率。使用Landsat 8卫星图像,可以使用k-means聚类和区域生长这两种图像分割方法来计算东南苏拉威西地区的红树林面积。
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引用次数: 3
Pengaruh Masukan Kendali Terhadap Hasil Identifikasi Parameter Pesawat Udara Konfigurasi Konvensional Matra Terbang Longitudinal 飞机参数识别的控制器输入面结果纵向约定Matra配置
Pub Date : 2019-01-31 DOI: 10.14710/JTSISKOM.7.1.2019.25-30
Eries Bagita Jayanti, Novita Atmasari, H. Mardikasari, Ardian Rizaldi, Fuad Surastyo Pranoto, S. Wibowo
Parameter identification is a process to get real characteristics of the motion dynamics of an object which can then be used to build the dynamics model of the object, which has a very high level of validity and accuracy. The modeling process is usually carried out using aircraft input data and the results of existing navigation data recording. From the data, the model parameters are estimated using the simple least square method. In this study, the simulation was carried out by varying the deflection input in the control field and simulation time. The input given to the longitudinal dimension is the deflection of the elevator control field. The results of parameter identification in the Corsair A-7A plane in the longitudinal dimension indicate that the input form 3-2-1 has a smaller error value than using doublet and pulse inputs. This shows that the input form 3-2-1 is most suitable for the longitudinal dimension among the given inputs.
参数辨识是一个获取物体运动动力学真实特征并据此建立物体动力学模型的过程,具有很高的有效性和准确性。建模过程通常使用飞机输入数据和现有导航数据记录的结果进行。根据数据,采用简单最小二乘法估计模型参数。在本研究中,通过改变控制场的挠度输入和仿真时间来进行仿真。纵向尺寸的输入是电梯控制场的挠度。在海盗船a - 7a飞机上进行纵向参数辨识的结果表明,3-2-1输入方式的误差值比采用双重输入和脉冲输入方式的误差值要小。这表明在给定的输入中,3-2-1的输入形式最适合纵向尺寸。
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引用次数: 0
Metode SURF dan FLANN untuk Identifikasi Nominal Uang Kertas Rupiah Tahun Emisi 2016 pada Variasi Rotasi SURF和FLANN在旋转变化中确定2016年印尼盾年排放量的面值
Pub Date : 2019-01-31 DOI: 10.14710/jtsiskom.7.1.2019.19-24
Adri Priadana, Ari Murdiyanto
In December 2016, Bank Indonesia (BI) officially launched the 2016 Year Emission Rupiah. With the development of technology, the process of buying and selling are not only possible between humans and humans, but humans with a machine. In addition, the machine must also be able to read and recognize the nominal banknotes in various variations of face and rotation. This is because humans can put money in machines with various variations of face and rotation. This study aims to apply and analyze the level of accuracy of nominal rupiah banknotes identification with the SURF and FLANN methods for rotation variation. Testing for identification of nominal rupiah banknotes is carried out with different rotation variations, namely 0o, 90o, 180o, and 270o. The proposed identification method provides 100% of accuracy.
2016年12月,印尼银行(BI)正式推出2016年度排放印尼盾。随着科技的发展,买卖的过程不仅可以在人与人之间进行,而且可以在人与机器之间进行。此外,机器还必须能够读取和识别各种变型和旋转的标称钞票。这是因为人们可以把钱投到不同形状和旋转的机器里。本研究旨在应用和分析面额印尼盾纸币识别与SURF和FLANN方法的旋转变化的准确性水平。印尼盾纸币的识别测试以不同的旋转变化进行,即0、90、180和2700。所提出的识别方法具有100%的准确率。
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引用次数: 7
Prediction of Call Drops in GSM Network using Artificial Neural Network 基于人工神经网络的GSM网络掉线预测
Pub Date : 2019-01-31 DOI: 10.14710/JTSISKOM.7.1.2019.38-46
Olaonipekun Oluwafemi Erunkulu, E. N. Onwuka, O. Ugweje, Lukman Adewale Ajao
Global System for Mobile communication is a digital mobile system that is widely used in the world. Over the years, the number of subscribers has tremendously increased, the quality of service (Call Drop Rate) became an issue to consider as many subscribers were not satisfied with the services rendered. In this paper, we present the Artificial Neural Network approach to predict call drop during an initiated call. GSM parameters data for the prediction were acquired using TEMS Investigations software. The measurements were carried out over a period of three months. Post analysis and training of the parameters was done using the Artificial Neural Network to have an output of “0” for no-drop calls and “1” for drop calls. The developed model has an accuracy of 87.5% prediction of drop call. The developed model is both useful to operators and end users for optimizing the network.
全球移动通信系统是一种在世界范围内广泛使用的数字移动系统。多年来,用户数量急剧增加,服务质量(掉线率)成为一个需要考虑的问题,因为许多用户对所提供的服务不满意。在本文中,我们提出了一种人工神经网络方法来预测发起呼叫期间的呼叫丢失。使用TEMS Investigations软件获取用于预测的GSM参数数据。测量历时三个月。使用人工神经网络对参数进行后分析和训练,使无掉线呼叫的输出为“0”,掉线呼叫输出为“1”。所开发的模型对掉线呼叫的预测准确率为87.5%。所开发的模型对运营商和最终用户优化网络都很有用。
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引用次数: 6
Sistem Kendali Agitator Dryer Biji Kakao Berbasis Android 可可基种子Dryer控制系统
Pub Date : 2019-01-18 DOI: 10.14710/jtsiskom.0.0.0.%p
Widya Cahyadi, Devri Agus Hidayat, Bambang Sujanarko
Abstract -  This paper proposes a new novelty on telemetry-based cocoa bean circular dryer control system using android applications. There are four new additions compares to the previous one. Its communication is duplex communication which is better than the simplex communication in the previous research, and it also decreases delay due to pushing push button on 2x16LCD. It also lengthens the coverage by adding internet connection via access point. It is easier to use for operator in controlling machine continuously because the number of machine available and no more record for agitator activation and turning-off. There are several tests, namely the telemetry test which checks on the distance covered using bluetooth, wifi esp8266, and accuracy test which checks the accuracy of agitator control of cocoa bean dryers using application in android. The testing process is carried out under N-LOS conditions and LOS conditions. From the test with these two conditions result in range coverage and the accuracy of Agitator Dryer control of cocoa beans using an android based telemetry system, and apply the concept of Internet of Things. Abstrak - Penelitian ini memutakhirkan sistem kendali agitator circular dryer biji kakao berbasis telemetri dengan aplikasi android, penyempurnaan dari penelitian sebelumnya yang hanya menggunakan komunikasi telemetri satu arah, perbaikan pada LCD 2x16 yang menimbulkan delay pada saat menekan push button, menambahkan koneksi internet melalui wifi Access point untuk memperjauh jarak jangkauan. Memudahkan pengoperasian agitator bagi operator dalam mengontrol mesin secara kontinyu sebab mesin lebih dari satu serta tidak adanya catatan agitator saat diaktifkan dan harus dimatikan. Pengujian yang dilakukan, menguji kinerja sistem telemetri yang digunakan yaitu jarak maksimal yang dapat di jangkau oleh piranti nirkabel bluetooth, serta wifi esp8266, dan untuk mengetahui keakurasian pengendalian agitator Dryer biji kakao menggunakan aplikasi di android. Proses pengujian ini dilakukan pada kondisi N-LOS dan kondisi LOS. Dari pengujian dengan dua kondisi tersebut menghasilkan jarak jangkauan dan juga keakurasian pengendalian Agitator Dryer biji kakao menggunakan sistem telemetri berbasis android, serta menerapkan konsep Internet of Things.
摘要:本文提出了一种基于遥测技术的基于android应用的可可豆圆形干燥机控制系统。与前一个相比,新增了四个。其通信方式为双工通信,优于以往研究的单工通信,并且减少了在2x16LCD上按下按钮所造成的延时。它还通过接入点增加了互联网连接,从而扩大了覆盖范围。由于可用机器数量多,无需再记录搅拌器的启动和关闭,因此操作人员更容易连续控制机器。有几个测试,即遥测测试使用蓝牙,wifi esp8266检查覆盖的距离,准确性测试使用android应用程序检查可可豆烘干机的搅拌器控制的准确性。测试过程在N-LOS条件和LOS条件下进行。从这两种条件下的测试结果来看,搅拌器烘干机控制可可豆的范围覆盖和精度采用了基于机器人的遥测系统,并应用了物联网的概念。Abstrak——Penelitian ini memutakhirkan sistem kendali搅拌器《循环干燥机kakao berbasis telemetri dengan aplikasi android, penyempurnaan达里语Penelitian sebelumnya杨hanya menggunakan komunikasi telemetri研究亚拉,perbaikan篇液晶2 x16杨menimbulkan延迟篇种子menekan按钮,menambahkan koneksi互联网melalui无线访问点为她memperjauh jarak jangkauan。东南亚搅拌器bagi操作员dalam mengcontrol mesin secara kontinu sebab mesin lebih dari satu serta tiak adanya catata搅拌器saat diaktifkan dan harus diatikan。企鹅,企鹅,企鹅,企鹅,企鹅,企鹅,企鹅,企鹅,企鹅,企鹅,企鹅,企鹅,企鹅,企鹅,企鹅Proses penguin ini dilakukan padadkondisi N-LOS dankondisi LOS。大企鹅dengan dua kondisi tersebut menghasilkan jarak jangkauan dan juga keakurasian pengen大连搅拌器干燥器biji kakao menggunakan系统远程测量基础机器人,serta menerapkan konsep物联网。
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引用次数: 0
Yoruba Handwritten Character Recognition using Freeman Chain Code and K-Nearest Neighbor Classifier 基于Freeman链码和k近邻分类器的约鲁巴手写字符识别
Pub Date : 2018-10-31 DOI: 10.14710/JTSISKOM.6.4.2018.129-134
J. Ajao, David Olufemi Olawuyi, Odetunji Ode Odejobi
This work presents a recognition system for Offline Yoruba characters recognition using Freeman chain code and K-Nearest Neighbor (KNN). Most of the Latin word recognition and character recognition have used k-nearest neighbor classifier and other classification algorithms. Research tends to explore the same recognition capability on Yoruba characters recognition. Data were collected from adult indigenous writers and the scanned images were subjected to some level of preprocessing to enhance the quality of the digitized images. Freeman chain code was used to extract the features of THE digitized images and KNN was used to classify the characters based on feature space. The performance of the KNN was compared with other classification algorithms that used Support Vector Machine (SVM) and Bayes classifier for recognition of Yoruba characters. It was observed that the recognition accuracy of the KNN classification algorithm and the Freeman chain code is 87.7%, which outperformed other classifiers used on Yoruba characters.
本文提出了一个使用弗里曼链码和K-近邻(KNN)的脱机约鲁巴字符识别系统。大多数拉丁语单词识别和字符识别都使用了k近邻分类器和其他分类算法。研究倾向于探索约鲁巴语字符识别的相同识别能力。数据是从成年土著作家那里收集的,扫描的图像经过一定程度的预处理,以提高数字化图像的质量。利用Freeman链编码提取数字化图像的特征,利用KNN基于特征空间对特征进行分类。将KNN的性能与其他使用支持向量机(SVM)和贝叶斯分类器识别约鲁巴文字的分类算法进行了比较。结果表明,KNN分类算法和Freeman链码的识别准确率为87.7%,优于其他用于约鲁巴语字符的分类器。
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引用次数: 14
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Jurnal Teknologi dan Sistem Komputer
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