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Analisa Implementasi Metode Fuzzy Time Series Jasim pada Prediksi Perkembangan COVID-19 di Indonesia 分析Jasim的模糊时间方法系列的实施,以预测COVID-19在印度尼西亚的发展
Pub Date : 2021-09-15 DOI: 10.21456/vol11iss2pp125-130
D. R. Prehanto, Ginanjar Setyo Permadi, Melvin Nurdiansari
The pandemic of COVID-19 that has been going on since March 2020 until now has weakened many sectors in many countries an Indonesia as well. In Indonesia, more than 9,000 people have died because of this pandemic. In the first week, 56 cases of COVID-19 were recorded and the cases continued to increase to more than 2,000 cases per week so that the increasing number of cases could result in a lack of service provision and facilities for medical. This study aims to determine the forecasting scheme and how the development of COVID-19 cases that occur in Indonesia. Fuzzy Time Series Jasim method that is applied to find out how to do forecasts by managing previous data.  This method uses the determination of the width of the interval, the formation of a set from historical data and using of the average based length method. In this method also used grouping and data relations that have been fuzzified. From the method that has been used, it can be seen that the results obtained from the Fuzzy Time Series Jasim method are obtained from the accuracy rate of the accuracy error using MAD of 286. And the error magnitude of the forecasting results with the actual data using MAPE is 2.43%. Where it can be concluded that the use of Fuzzy Time Series Jasim method in this study provides good forecasting results
自2020年3月以来一直持续到现在的新冠肺炎大流行也削弱了包括印度尼西亚在内的许多国家的许多部门。在印度尼西亚,有9000多人死于这场大流行。在第一周,记录了56例COVID-19病例,病例继续增加到每周2000多例,因此病例数量的增加可能导致缺乏服务和医疗设施。本研究旨在确定预测方案以及印度尼西亚发生的COVID-19病例的发展情况。模糊时间序列的Jasim方法,是用来找出如何通过管理以前的数据进行预测。该方法采用确定区间宽度,从历史数据中形成一组,并使用基于平均长度的方法。该方法还采用了分组和模糊化的数据关系。从所采用的方法可以看出,模糊时间序列Jasim方法得到的结果是由286的MAD精度误差的正确率得到的。MAPE预测结果与实际数据的误差幅度为2.43%。在哪里可以得出结论,在本研究中使用模糊时间序列Jasim方法提供了良好的预测效果
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引用次数: 0
Evaluasi Tingkat Penerimaan Sistem Manajemen Aset Menggunakan Metode HOT-FIT 使用热适配方法评估资产管理系统的入学率
Pub Date : 2021-08-25 DOI: 10.21456/VOL11ISS2PP87-96
Muhammad Amiruddien, A. Widodo, R. Isnanto
The development of the institution will be directly proportional to the development of the number and types of assets it owns. The growing number and type of assets owned by an institution will have an impact on increasingly difficult management. In asset management, Diponegoro University has developed an Sistem Informasi Manajemen Aset Terpadu (SIMASET). SIMASET needs to be evaluated to find out its shortcomings and can be input for further development. This study aims to determine the factors that influence the level of acceptance and net benefits received by users from the application of SIMASET using the Human-Organization-Technology (HOT-Fit) method. This study begins with designing hypotheses, determining the sample of respondents, filling out questionnaires, and ending with questionnaire data analysis. There are 20 hypotheses tested regarding the relationship between technology, human and organizational constructs in the HOT-Fit method. The Partial Least Squares-Structural Equation Modeling (PLS-SEM) method in the Smart-PLS 3.0 application is used to analyze the questionnaire data that has been filled out by SIMASET direct users. The results showed that the net benefits of implementing SIMASET were increasing effectiveness, helping decision making, reducing errors and facilitating communication. In addition, it can be seen that SIMASET's shortcomings lie in the quality of information and service quality because they have no significant effect on system use and user satisfaction. SIMASET acceptance rate of 51.6% or moderate taken from the R-square value of net benefits.
机构的发展将与其拥有的资产数量和类型的发展成正比。一家机构拥有的资产数量和类型的不断增加,将对日益困难的管理产生影响。在资产管理方面,Diponegoro大学开发了一个信息管理系统(SIMASET)。SIMASET需要进行评估,以找出其不足之处,并可投入进一步发展。本研究旨在利用人类-组织-技术(HOT-Fit)方法确定影响用户从SIMASET应用中接受程度和净效益的因素。本研究从设计假设、确定被调查者样本、填写问卷开始,以问卷数据分析结束。HOT-Fit方法测试了20个关于技术、人力和组织结构之间关系的假设。使用Smart-PLS 3.0应用程序中的偏最小二乘-结构方程建模(PLS-SEM)方法对SIMASET直接用户填写的问卷数据进行分析。结果表明,实施SIMASET的净效益是提高效率、帮助决策、减少错误和促进沟通。此外,可以看出SIMASET的缺点在于信息质量和服务质量,因为它们对系统使用和用户满意度没有显著影响。SIMASET接受率为51.6%或中等,从r平方值取净效益。
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引用次数: 1
Implementasi forecastHybrid Package menggunakan R Studio Cloud untuk Prediksi Pertumbuhan Dana Pihak Ketiga dan Pembiayaan Pada Bank Muamalat Indonesia 实施前泡沫包使用R Studio Cloud来预测第三方资金的增长和印尼Muamalat银行的融资
Pub Date : 2021-08-02 DOI: 10.21456/vol11iss2pp97-104
N. Astuti, Rizal Bakri
This study aims to find out how to forecast the growth performance of third party funds (TPF) and financing which is measured on a quarterly by applied the hybrid method with R Studio Cloud using ‘forecastHybrid’ package. This prediction is expected to provide information and data on the growth of third party fund and financing for Bank Muamalat which is experiencing problems of lack of capital and non-performing funds (NPF). Forecasting with Hybrid methods combines ARIMA auto forecasting methods, exponential smoothing forecasting methods, theta forecasting methods, neural network forecasting methods, seasonal and trend decomposition forecasting methods, and TBATS forecasting methods. The forecast results show that the Hybrid method is able to provide information as a decision-making material for Bank Muamalat
本研究的目的是找出如何预测第三方基金(TPF)和融资的增长表现,这是采用混合方法与R Studio Cloud使用“forecastHybrid”包进行季度测量。这一预测预计将为Muamalat银行提供有关第三方基金和融资增长的信息和数据,该银行正在经历缺乏资本和不良基金(NPF)的问题。混合预测方法结合了ARIMA自动预测方法、指数平滑预测方法、theta预测方法、神经网络预测方法、季节和趋势分解预测方法、TBATS预测方法。预测结果表明,混合方法能够为Muamalat银行提供决策信息
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引用次数: 0
Penentuan Penerimaan Karyawan Menggunakan Metode Simple Additive Weighting dan Weight Product
Pub Date : 2021-08-02 DOI: 10.21456/vol11iss2pp117-124
Ermin Al Munawar, Sunardi Sunardi, Abdul Fadlil
Recruitment errors influence in a decrease of quality, performance, and company revenue. One of the causes is the absence of a method that is applied as a systematically of information system in determining the acceptance of the best prospective employees. This study uses the Simple Additive Weighting (SAW) and Weight Product (WP) methods to build an objective, fast, and accurate of Decision Support System (DSS) in determining employee acceptance. This research case study was applied to the Indonesian Market Traders Cooperative (KOPPI) Sorong City, West Papua Province by involving a number of 10 alternative applicants. This study aims to produce an objective information system and provide convenience in determining the best employees, referring to the determination of 9 criteria obtained from interviews, namely education, work experience, motivation, intrapersonal ability, achievement orientation, sales ability, self-confidence, trustworthy, and work ethic by weighting each. SAW and WP methods are both used to determine the best ranking of all alternative applicants and get the best prospective employees. The information system was built using the Waterfall development method with the PHP programming language and Mysql database. Based on the results of research that has been carried out, it is found that the information system built has 100% conformity of functionality and compatibility between manual and application system. Both methods provide the same highest alternative to be used as the determination of the best employee acceptance, however it is found that the WP method provides better accuracy and validity than SAW.
招聘失误会导致质量、绩效和公司收入的下降。其中一个原因是缺乏一种方法,作为一种系统的信息系统,在确定接受最好的潜在员工。本研究采用简单加性加权法(SAW)和权重积法(WP)建立了一个客观、快速、准确的决策支持系统(DSS)来确定员工接受度。这一研究案例研究应用于西巴布亚省索龙市印度尼西亚市场贸易商合作社,涉及10个备选申请人。本研究的目的是建立一个客观的信息系统,为确定最优秀的员工提供方便,通过面试获得的9个标准的确定,即教育程度、工作经验、动机、人际关系能力、成就取向、销售能力、自信、值得信赖、职业道德。SAW和WP方法都用于确定所有备选申请人的最佳排名,并获得最佳的潜在员工。信息系统采用瀑布式开发方法,以PHP为编程语言,Mysql为数据库。研究结果表明,所构建的信息系统具有100%的功能符合性和手工系统与应用系统的兼容性。两种方法都提供了相同的最高替代方案,用于确定最佳员工接受度,但是发现WP方法比SAW方法提供了更好的准确性和有效性。
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引用次数: 1
Evaluasi Kebergunaan (Usability) dan Rekomendasi Penggunaan Google Classroom untuk Blended Learning di Perguruan Tinggi 兼容性评估和谷歌课堂使用在大学混合学习的建议
Pub Date : 2021-06-29 DOI: 10.21456/vol11iss2pp105-116
A. Priyadi, Eko Sediyono, H. Purnomo
The google classroom application is a virtual classroom mixed with real classes in education where the distribution of material and lecture assignments can be done by teachers and students without using paper or paperless. Interaction between teachers and students is done interactively online. The use of the google classroom application as a teaching tool has only been implemented at XYZ college, so usability testing is needed in the use of google classroom. Testing the usability level of Google Classroom is really needed to evaluate and get recommendations about using the Google Classroom application. The method used in this study is the USE (Usefullness, Satisfaction and Ease of Use) Questionnaire and Cognitive Walkthrough (CW) used in the google classroom usability test. USE stands for Usefulness, Satisfaction, and Ease of Use. Ease of use factors can be divided into two, namely Ease of Learning and Ease of Use. The USE test involved all XYZ college students, totaling 213 respondents. Ten respondents within certain criteria were selected by purposive sampling technique to test the usefulness of using the cognitive walkthrough (CW) method. The overall assessment of the usefulness factor with a mean value of 3.95 is included in the "Good" rating range. Overall, the satisfaction factor value of 4.01 is included in the "Good" rating range. Overall, the assessment of the Ease of use indicator with a mean of 4.22 is included in the "Good" rating range. The cognitive walkthrough (CW) method produces several recommendations that can be utilized by XYZ universities in implementing blended learning using google classroom. The usability factor with various features offered by Google Classroom is quite high because it can provide convenience in its use to support lecture activities at XYZ College
谷歌课堂应用程序是一个虚拟教室,混合了真实的教育课堂,教师和学生可以在不使用纸张或无纸化的情况下分发材料和课堂作业。师生之间的互动是在网上进行的。google课堂应用程序作为教学工具的使用只在XYZ学院实现,因此在使用google课堂时需要进行可用性测试。测试Google教室的可用性水平对于评估和获得使用Google教室应用程序的建议是非常必要的。本研究使用的方法是在谷歌教室可用性测试中使用的USE(有用性,满意度和易用性)问卷和认知演练(CW)。USE代表有用性、满意度和易用性。易用性因素可以分为两个,即易学性和易用性。USE测试涉及所有XYZ大学生,总共213名被调查者。通过有目的的抽样技术,在一定的标准内选择了10名受访者,以测试使用认知演练(CW)方法的有效性。有用性因子的整体评估平均值为3.95,包括在“好”评级范围内。总体而言,满意度因子值为4.01,属于“良好”评级范围。总体而言,易用性指标的评估平均值为4.22,属于“良好”评级范围。认知演练(CW)方法产生了一些建议,XYZ大学可以利用这些建议来实现使用google教室的混合学习。谷歌课堂提供的各种功能的可用性因素是相当高的,因为它可以为支持XYZ学院的讲座活动提供便利
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引用次数: 1
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