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2020 International Seminar on Application for Technology of Information and Communication (iSemantic)最新文献

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COBIT 5 for Analysing Information Technology Governance Maturity Level on Masterplan E-Government 总体规划电子政府信息技术治理成熟度水平分析COBIT 5
Rahmat Awaludin Rizal, R. Sarno, Kelly Rossa Sungkono
The information and communication technology development has increased to fulfil processes of an organization. It needs to be structured to create a clean, competent, evident and liable government and a quality and reliable civil service. With the existence of a system of electronic-based government system (SPBE), one of the regional governments that implemented SPBE is East Java Province by generating SPBE index value of 2.92. The SPBE value shows the SPBE implementation quality is still below the expected value, which is 3. By using COBIT 5 Framework, this research obtains levels of selected process capabilities, i.e. EDM05, APO01, APO04, APO06, are below 3rd level (Established). This research also gives recommendations for improving the level of the process capability.
信息和通信技术的发展已经增加,以满足一个组织的过程。它的结构需要建立一个廉洁、能干、明确和负责任的政府,以及一支高质量和可靠的公务员队伍。随着电子政务系统(SPBE)系统的存在,东爪哇省是实施电子政务系统的地区政府之一,产生了2.92的电子政务指数值。SPBE值表明SPBE实现质量仍然低于期望值,即3。通过COBIT 5框架,本研究得出所选择的工艺能力水平,即EDM05、APO01、APO04、APO06,均低于3级(Established)。本研究还对提高工艺能力水平提出了建议。
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引用次数: 9
Checking Wrong Pattern in Process Model Containing Invisible Task by Using Declarative Miner 使用声明式挖掘器检查包含不可见任务的进程模型中的错误模式
Nadia Salsabila, R. A. Palembiya, K. R. Sungkono, R. Sarno
Event log records all events of performed business process on the system. Analysts used the event log to detect occurred anomalies, one of which is wrong pattern, in the process. However, there are conditions, i.e. skip condition, redo condition, and switch condition, which can be misinterpreted as wrong pattern. Uniquely, those conditions cannot be depicted in the reference model without utilizing additional tasks, namely invisible tasks. This research proposes rules which can check the wrong pattern in the process model containing those conditions. This research automatically formed declarative miner rules carrying invisible tasks based on a process model. The form of the used process model in this research is a graph model. Then, the rules are used to checking the wrong pattern. The experiment uses real data, i.e. port-container handling processes, and several simulation data. The analysis explains that declarative miners have 100% accuracy to check the wrong pattern in the process model that contains each invisible task including skip condition, redo condition, and switch condition.
事件日志记录了系统上已执行业务流程的所有事件。分析人员使用事件日志来检测过程中发生的异常,其中一个是错误的模式。然而,有一些条件,如跳过条件、重做条件和切换条件,可能被误解为错误的模式。独特的是,如果不使用额外的任务,即不可见的任务,这些条件就不能在参考模型中描述。本研究提出了一种规则来检查包含这些条件的过程模型中的错误模式。该研究基于流程模型自动形成带有不可见任务的声明性挖掘规则。本研究使用的过程模型形式为图模型。然后,规则被用来检查错误的模式。实验使用了真实数据,即端口-集装箱处理过程,以及多个模拟数据。该分析解释说,声明性挖掘器在包含每个不可见任务(包括跳过条件、重做条件和切换条件)的流程模型中检查错误模式的准确率为100%。
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引用次数: 0
Using Extended UTAUT2 Model to Determine Factors Influencing the Use of Shopee E-commerce 利用扩展UTAUT2模型确定影响Shopee电子商务使用的因素
Prima R. Maulidina, R. Sarno, K. R. Sungkono, Tantya A. Giranita
This study aims to discover the factors that influence users in using Shopee e-commerce. One of the ways to know the contributing factor that influences users is the Unified Theory of Acceptance and Usage of Technology 2 (UTAUT2). UTAUT2 is a known model that could determine the factors thoroughly. However, this study uses seven constructs from UTAUT2 with two additional constructs. For this, the study has targeted 160 Indonesian respondents who have done transactions on Shopee e-commerce in Indonesia. Furthermore, data analysis in this study used Partial Least Squares-Structural Equation Model (PLS-SEM) on SmartPLS software due to its ability to analyze data with a small sample size, even if the model used is complex. The results show that Habit and Trust in Interest are significantly influencing Behavioral Intention. In contrast, other factors such as Hedonic Motivation, Effort Expectancy, Facilitating Conditions, Performance Expectancy, Social Influence, Price Value, and Perceived Transaction Risk do not significantly influence Behavioral Intention in using Shopee. Moderating variables like age, gender, and experience do not significantly influence the relationship between independent variables and Behavioral Intention of users. The extension of the original constructs from UTAUT2 with two additional constructs from two previous studies is the novelty contribution in this study.
本研究旨在发现影响用户使用Shopee电子商务的因素。了解影响用户的促成因素的方法之一是技术接受和使用统一理论2 (UTAUT2)。UTAUT2是一个已知的模型,可以彻底确定这些因素。然而,本研究使用了来自UTAUT2的七个构念和两个附加构念。为此,该研究针对160名在印尼进行过Shopee电子商务交易的印尼受访者。此外,本研究中的数据分析在SmartPLS软件上使用了偏最小二乘-结构方程模型(PLS-SEM),因为它能够以小样本量分析数据,即使使用的模型很复杂。结果表明,习惯和兴趣信任对行为意向有显著影响。而享乐动机、努力预期、便利条件、绩效预期、社会影响、价格价值、感知交易风险等因素对Shopee使用行为意向的影响不显著。年龄、性别、经验等调节变量对自变量与用户行为意向的关系影响不显著。本研究的新颖性贡献是将UTAUT2的原始构式扩展为两个先前研究的附加构式。
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引用次数: 9
Implementation of Random Forest Regression for COCOMO II Effort Estimation 随机森林回归在COCOMO II工作量估计中的实现
Ilham Cahya Suherman, R. Sarno, Sholiq
One of Project Manager early activity is to estimate time, and cost based on given scope, which can help project manager to plan schedule and used resources. Estimation is very important in project management because a bad result of estimation will result in bad management of project and may cause failure. There are methods that can be used to estimate software development effort; COCOMO II is one method that commonly used. Many researcher before have been used algorithm, such as Bat, Bee Colony, or MOPSO to increase COCOMO II estimation accuracy. However, as the technology advanced, there are a lot more options that can be used to predict software effort estimation based on COCOMO, such as machine learning. In this paper, we compare machine learning algorithm with tuning parameter method to know whether tuning parameter estimation is better than machine learning estimation or vice versa. In this paper, we use Random Forest Regression as machine learning algorithm to estimate the effort. We also compare it with another machine learning algorithm, Support Vector Regression, and Bee Colony Method as parameter tuning method. The results of experiment is evaluated by their error rate. The results show that Random Forest Regression is better than Support Vector Regression and Bee Colony Method.
项目经理的早期活动之一是根据给定的范围估计时间和成本,这可以帮助项目经理计划进度和使用的资源。评估在项目管理中是非常重要的,因为一个糟糕的评估结果将导致项目管理不善,甚至可能导致失败。有一些方法可以用来评估软件开发工作;COCOMO II是常用的一种方法。在此之前,许多研究者已经使用了蝙蝠、蜂群或MOPSO等算法来提高COCOMO II的估计精度。然而,随着技术的进步,有更多的选择可以用来预测基于COCOMO的软件工作量估计,比如机器学习。在本文中,我们将机器学习算法与调优参数方法进行比较,以了解调优参数估计是否优于机器学习估计,反之亦然。在本文中,我们使用随机森林回归作为机器学习算法来估计工作量。我们还将其与另一种机器学习算法,支持向量回归和蜂群方法作为参数调整方法进行了比较。用它们的错误率来评价实验结果。结果表明,随机森林回归方法优于支持向量回归和蜂群回归方法。
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引用次数: 2
Hemorrhage Diabetic Retinopathy Detection based on Fundus Image using Neural Network and FCM Segmentation 基于神经网络和FCM分割眼底图像的出血糖尿病视网膜病变检测
Hadapininglaksmi Astri Purwanithami, Christy Atika Sari, E. H. Rachmawanto, De Rosal Ignatius Moses Setiadi
Hemorrhage Diabetic Retinopathy is a type of diabetes that attacks the blood vessels of the retina. This disease can cause blindness, but early treatment can minimize this. This research proposes a method of detecting blood vessels in the retina caused by Hemorrhage Diabetic Retinopathy. Detection is based on the Fundus image based on several stages of preprocessing, segmentation, and detection. At the preprocessing stage, the fundus image with the RGB image format is taken the green channel to do a contrast enhancement operation with CLAHE and segmentation with FCM. Then the detection is done using the Neural Network method. At the experimental stage, 100 testing images are used which are divided into two classes, namely Hemorrhage and Non-Hemorrhage. Detection results showed from 100 images, only one image was detected incorrectly, so it can be concluded that the detection accuracy reached 99%.
出血糖尿病视网膜病变是一种攻击视网膜血管的糖尿病。这种疾病可导致失明,但早期治疗可将其减少到最低程度。本研究提出了一种检测出血型糖尿病视网膜病变视网膜血管的方法。检测是基于眼底图像的预处理、分割和检测几个阶段。在预处理阶段,将RGB图像格式的眼底图像取绿色通道,用CLAHE进行对比度增强操作,并用FCM进行分割。然后利用神经网络方法进行检测。实验阶段使用100张检测图像,分为出血和非出血两类。检测结果显示,在100幅图像中,只有1幅图像检测不正确,因此可以得出检测准确率达到99%的结论。
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引用次数: 2
Design Flyback Converter For Charging Battery using Fuzzy Logic Controller 用模糊控制器设计电池充电反激变换器
Renny Rakhmawati, S. Suhariningsih, Silvia Husniatuzzahro’
Motorcycle is one of the many private transportation facilities that currently. Unfortunately motorcycles still use energy from fossil fuels which are increasingly rare and not environmentally friendly. So now many developed environmentally friendly electric vehicles from renewable sources. But the battery charging process is needed as energy storage. So this paper offers a flyback converter method that is controlled by fuzzy logic controller. In the battery charging process, the values of Vin, Iin, Vout, and Iout are monitored with an output voltage target of 14.4 V. The fuzzy logic controller can control the output voltage is 14.37 Vdc with error voltage 0.208%.
摩托车是目前众多的私人交通工具之一。不幸的是,摩托车仍然使用化石燃料的能源,这种燃料越来越稀有,而且不环保。所以现在很多人开发了环保的可再生能源电动汽车。但是电池的充电过程是需要作为能量储存的。为此,本文提出了一种由模糊控制器控制的反激变换器方法。在电池充电过程中,监测Vin、Iin、Vout、Iout的值,输出电压目标为14.4 V。模糊控制器可以控制输出电压为14.37 Vdc,误差电压为0.208%。
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引用次数: 2
Impact of Blade Length on the Horizontal Wind Turbine Output Power and Torque 叶片长度对水平风力机输出功率和转矩的影响
L. Gumilar, Mokhammad Sholeh
Power plants using fossil fuel are always used to meet the needs of the load at any time. However fossil fuels can cause air pollution. An alternative that can be used to reduce fossil energy is renewable energy source type of wind power plant (WPP). Currently WPP is only limited to reducing the use of fossil fuels and it has not been able to replace fossil energy sources. Because the power generated by WPP is still small capacity. For this reason, it is necessary to carry out continuous research on WPP to increase output power. This paper aims to determine the impact of the horizontal wind turbine blade length to output power and torque. In the method, the length of the turbine blade is varied, so there is also a change in the sweep area value. The effect of swept area, wind speed, turbine rotation speed, and Cp on the output power and torque is presented in curve. The results of the simulation are the highest power and torque at the blade length of 5 m. The highest power obtained is 69.74 kW, and the highest turbine torque is 66.9 kN.m. The longer the turbine blade, the higher the wind turbine power and torque.
使用化石燃料的发电厂总是为了随时满足负荷的需要而使用。然而,化石燃料会造成空气污染。一种可以用来减少化石能源的替代方案是可再生能源型风力发电厂(WPP)。目前,WPP仅局限于减少化石燃料的使用,并没有能够替代化石能源。因为WPP发电的容量还很小。因此,有必要对WPP进行持续的研究,以提高输出功率。本文旨在确定水平风力机叶片长度对输出功率和扭矩的影响。在该方法中,涡轮叶片的长度是变化的,因此扫掠面积值也有变化。以曲线形式给出了扫掠面积、风速、涡轮转速和Cp对输出功率和转矩的影响。仿真结果表明,在叶片长度为5 m时,功率和扭矩最大。获得的最高功率为69.74 kW,涡轮最大转矩为66.9 kN.m。涡轮机叶片越长,风力涡轮机的功率和扭矩就越高。
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引用次数: 0
Silhouette Analysis of Hand Gesture Dataset Using Histogram Profile Feature Extraction 基于直方图轮廓特征提取的手势数据集轮廓分析
Agustinus Rudatyo Himamunanto, Supriadi Rustad, M. Arief Soeleman, Guruh Fajar Sidhik
Hand gesture dataset is a collection of hand gesture images. Several hand gesture datasets are freely available and can be used for various purposes, such as comparison or method testing. Processing the distribution of hand gesture image quality in the dataset has the opportunity to find potential models of hand gesture image quality for further research. This study tries to provide answers by exploring the quality of hand gesture images based on various datasets of public hand gestures. Then perform feature extraction based on the image histogram profile to get an overview of the range of color intensity values from the hand gesture image. The Herarchical Clustering method is used to build clusters based on histogram characteristics. The feasibility of the relationship between clusters was tested based on the silhouette index clustering method. The total number of hand gesture test images is 16 thousand data taken from 6 dataset sources that have been used in hand gesture recognition research. Based on the results of the processing, it is shown that the three clusters have no relationship feasibility or in other words the image clusters are independent.
手势数据集是手势图像的集合。一些手势数据集是免费提供的,可以用于各种目的,如比较或方法测试。处理数据集中手势图像质量的分布,有机会找到潜在的手势图像质量模型,供进一步研究。本研究试图通过探索基于各种公共手势数据集的手势图像的质量来提供答案。然后基于图像直方图配置文件进行特征提取,得到手势图像颜色强度值的总体范围。基于直方图特征,采用分层聚类方法构建聚类。基于剪影指数聚类方法,对聚类间关系的可行性进行了检验。手势测试图像的总数是来自6个数据集来源的1.6万个数据,这些数据集已经用于手势识别研究。处理结果表明,三个聚类之间没有关系可行性,即图像聚类是独立的。
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引用次数: 0
Case-Based Reasoning Modifications for Intelligent Systems in Handling In Vitro Fertilization (IVF) Patients Post Embryo Transfer 胚胎移植后处理体外受精(IVF)患者的智能系统基于案例的推理修正
Paminto Agung Christianto, E. Sediyono, I. Sembiring
The successful rate of In Vitro Fertilization (IVF) in Indonesia is around 29%, which is considered low. One of the factors causing the IVF failure is anxiety. About 77.7% of IVF patients have a high anxiety, and 83.3% of IVF patients experienced an IVF failure. The long duration of waiting the answer from the fertility doctors become one cause of the anxiety in IVF patients. On the other hand, the fertility doctors themselves have other responsibilities that cause IVF patients questions are not able to be given immediately. The study focused on the problems of the IVF patients and the fertility doctors.This research uses triangulation to obtain valid data and include challenges in developing health sector systems. To test the effect of IVF patients on the proposed intelligent system, Anova testing has been carried out resulting in a value of F = 9,902 and a Coefficient test that produces a value of t = 3,147, so the test results provide evidence that IVF patient feedback has an effect on improving the quality of the intelligent system handling IVF patients post embryo transfer. The final results of the research have provided a case-based reasoning (CBR) modification recommendation for an intelligent system for handling IVF patients after embryo transfer.
印度尼西亚体外受精(IVF)的成功率约为29%,被认为很低。导致试管婴儿失败的因素之一是焦虑。约77.7%的试管婴儿患者有高度焦虑,83.3%的试管婴儿患者经历过试管婴儿失败。等待生育医生答复的时间过长成为试管婴儿患者焦虑的原因之一。另一方面,生育医生本身也有其他责任,导致试管婴儿患者的问题不能立即给出。研究的重点是试管婴儿患者和生育医生的问题。这项研究使用三角测量法获得有效数据,并包括发展卫生部门系统所面临的挑战。为了检验试管婴儿患者对所提出的智能系统的影响,我们进行了方差分析(Anova)检验,结果为F = 9902,系数检验结果为t = 3147,因此测试结果证明试管婴儿患者反馈对提高处理试管婴儿患者胚胎移植后智能系统的质量有作用。研究的最终结果为胚胎移植后处理IVF患者的智能系统提供了基于案例推理(CBR)的修改建议。
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引用次数: 2
Android Application for Presence Recognition based on Face and Geofencing 基于人脸和地理围栏的存在识别Android应用
A. S. Shahab, R. Sarno
The Attendance system, especially in companies is needed to help assess the attendance and discipline of employees. Some attendance systems that have been made based on the detection of biometrics, barcodes, and QR Codes have not been able to simplify the attendance process where employees still have to queue in front of the attendance machine. This paper aims to design an attendance system that flexible which can simplify and speed up the process by using a mobile application based on geofencing and face recognition so the company does not need to expend the extra cost to buy dedicated machine. The system is using a mobile application as a device to presence. Each of the employees has their own geofencing area which worked as a location virtual boundary. The employee face images are sent to the server from mobile application for the attendance process which includes a recognition process using k-Nearest Neighbours (k-NN) and Principal Component Analysis (PCA). The results obtained are using face recognition k-NN and PCA obtained a 90% accuracy rate with a processing time of 1.5 seconds. The fastest time to do a complete presence is 3.4s which include a geofencing authentication and face recognition process.
考勤制度,特别是在公司,是需要帮助评估出勤和纪律的员工。一些基于生物识别、条形码和QR码检测的考勤系统无法简化考勤流程,员工仍然需要在考勤机前排队。本文旨在设计一个灵活的考勤系统,通过基于地理围栏和人脸识别的移动应用程序简化和加快流程,使公司不需要额外购买专用机器的成本。该系统使用移动应用程序作为设备来呈现。每个员工都有自己的地理围栏区域,作为位置虚拟边界。员工面部图像从移动应用程序发送到服务器,用于考勤过程,其中包括使用k-最近邻(k-NN)和主成分分析(PCA)的识别过程。结果表明,使用人脸识别k-NN和PCA,处理时间为1.5秒,准确率达到90%。完成完整存在的最快时间是3.4秒,其中包括地理围栏认证和面部识别过程。
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引用次数: 5
期刊
2020 International Seminar on Application for Technology of Information and Communication (iSemantic)
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