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arXiv 2022年

作者： Flyvbjerg, Bent Budzier, Alexander Lee, Jong Seok Keil, Mark Lunn, Daniel Bester, Dirk W. Major Programme Management University of Oxford's Saïd Business School United Kingdom Major Program Management IT University of Copenhagen Denmark The Field of Information Systems Saïd Business School University of Oxford United Kingdom Department of Accounting and Information Management Haslam College of Business University of Tennessee Knoxville United States The University System of Georgia Computer Information Systems J. Mack Robinson College of Business Georgia State University United States Department of Statistics University of Oxford United Kingdom 4 Thornhill Mews Cross Street Kent MaidstoneME14 2SP United Kingdom

If managers assume a normal or near-normal distribution of information Technology (IT) project cost overruns, as is common, and cost overruns can be shown to follow a power-law distribution, managers may be unwittingly exposing their organizations to extreme risk by severely underestimating the probability of large cost overruns. In this research, we collect and analyze a large sample comprised of 5, 392 IT projects to empirically examine the probability distribution of IT project cost overruns. Further, we propose and examine a mechanism that can explain such a distribution. Our results reveal that IT projects are far riskier in terms of cost than normally assumed by decision makers and scholars. Specifically, we found that IT project cost overruns follow a power-law distribution in which there are a large number of projects with relatively small overruns and a fat tail that includes a smaller number of projects with extreme overruns. A possible generative mechanism for the identified power-law distribution is found in interdependencies among technological components in IT systems. We propose and demonstrate, through computer simulation, that a problem in a single technological component can lead to chain reactions in which other interdependent components are affected, causing substantial overruns. What the power law tells us is that extreme IT project cost overruns will occur and that the prevalence of these will be grossly underestimated if managers assume that overruns follow a normal or near-normal distribution. This underscores the importance of realistically assessing and mitigating the cost risk of new IT projects up front. © 2022, CC BY.

关键词： Project management

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Feasibility study of information Technology Investment (a case study of ODOO ERP: Project Management Module Implementation in Indonesia Based Company) 10

Feasibility study of Information Technology Investment (a ca...

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10th International Conference on ICT for Smart Society, ICISS 2019

作者： Jingga, Fredy Kosala, Raymond Supangkat, Suhono Harso Ranti, Benny School of Information Systems Bina Nusantara University Computer Science Department BINUS Graduate Program-Doctor of Computer Science Information Systems Department Jakarta11480 Indonesia Bina Nusantara University Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta11480 Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9781728148809

IT Governance are one of the needs in managing Enterprise Level IT. This study shows part of the decision domain of IT Governance Help, which are IT Investment and Prioritization. The purpose of this study is to determine feasibility of implementation open source ERP system Odoo project management module that replaces current system based on operational, economic, and technical aspects. The method used are Fit/Gap Analysis and Cost Benefit model using economic impact worksheet. The analysis is done by comparing the requirement with features owned by current system and Odoo ERP system. This research resulted that Odoo ERP System is feasible in the 3 aspects, the operational feasibility Odoo reaching 72% Fit, the economic feasibility with ROI of 84%, and technical feasibility indicating the technical requirement can be fulfilled by leasing AWS server. The conclusion is the open source ERP system Odoo project management module is feasible to be applied in terms of 3 aspects that have been studied, those are operational, economic, and technical. © 2019 IEEE.

关键词： Cost benefit analysis

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Accuracy for Sentiment Analysis of Twitter Students on ELearning in Indonesia using Naive Bayes Algorithm Based on Particle Swarm Optimization 1

Accuracy for Sentiment Analysis of Twitter Students on ELear...

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1st International Conference on computer, Science, Engineering and Technology, ICComSET 2018

作者： Kartiko, Mohamad Sfenrianto Master of Computer Science Postgraduate Programs STMIK Nusa Mandiri Jakarta Indonesia Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Universitas Bina Nusantara Jakarta Indonesia

Students can use social media such as Twitter for online learning (E-Learning). This study aims to analyse an accuracy for the sentiments of students about E-Learning who use Indonesian on Twitter social media both positive and negative opinions. The algorithms used are Naive Bayes (NB). Then to optimize the accuracy of the calculation results, the Particle Swarm Optimization (NB-PSO) approach is used. In order to optimize accurate results, this study uses three experimental sequences (scenario 1, scenario 2, and scenario 2) for both NB and NB-PSO algorithms. Each scenario uses different positive and negative comments. The results of the experiment show that in scenario 1 an increase in accuracy is 10.00% for NB-PSO. Scenario 2 there is an increase in accuracy of 13.33% on NB-PSO. Meanwhile, in scenario 3 an increase in accuracy is 27.22% for NB-PSO. These results prove that the accuracy of NB-PSO is better than NB for all scenarios. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Students

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Application for Easy Organizing of Event Organizer

Application for Easy Organizing of Event Organizer

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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Nizirwan Anwar Wesley Rico Darmawan Gian Wellrich Nathaniel Pranata Sutajaya Muhamad Ali Furqon Harco Leslie Hendric Spits Warnars Faculty of Computer Science Esaunggul University Jakarta Indonesia School of Information Systems Bina Nusantara University Jakarta Indonesia Civil Service Police Unit Tangerang Indonesia KelurahanCimone Jaya Kota Tangerang Tangerang Indonesia BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728185194

ISBN: (纸本)9781728185200

These days, Indonesia has entered the era of Industry 4.0 which is marked by the development of all-digital technology and automation. With the increasing rate of technology development that changes people's lives, people are becoming fond of anything fast and instant. With the help of these technological advancements, we create an application that makes it easier for users that are willing to hold events. This application connects 2 entities, which are users and an event organizer. The event organizer can easily find their market and other hands easy as well for the user for finding the market for event organization activities. The business processes in this application were designed with a use case diagram, and the tables in the database were designed with the class diagram and the menu of the application with User Interface (UI). However, this proposed application just only an introduction and needs to be explored for those who are interested to explore entrepreneurship in these areas.

关键词： Organizations User interfaces Mobile applications Reliability Artificial intelligence Informatics Recommender systems

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K-Means Clustering Model to Discriminate Copper-Resistant Bacteria as Bioremediation Agents

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Procedia computer Science 2021年 179卷 804-812页

作者： Ika Nurlaila Wahyu Irawati Kartika Purwandari Bens Pardamean Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Department of Biology Education Faculty of Education Pelita Harapan University Tangerang Indonesia 15811 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Copper (Cu) has been excessively used for some valuable commodities and this creates environmental problems. The inorganic element becomes toxic when presents beyond the recommended tolerated concentration. Bacterial-based remediation is seen to be an excellent tool to overcome it as it reduces the copper contamination without yielding any other forms of contamination. There are some pivotal properties in the bacteria render them being considered as bioremediation agents against coppers contamination, namely bioaccumulation and biosorption. In the present study, we question if these bacteria could be clustered into a strong and representative proximity according to their functional properties. Mostly, bacteria are grouped based on their genetic profiles derived from the 16S rRNA sequencing. We propose that our K-Means clustering model can be employed to identify genetically-unlabelled bacteria. But first, a prominent reference should be developed and we are in this phase. We figured out the K-Means clustering model do not pull the same-genus bacteria into the same cluster. Instead, the model gathers into a proximity those isolates with similarity on a functional characteristic termed minimum inhibitory concentration (MIC), regardless their origins and their hierarchy in taxonomy.

关键词： Copper-Resistant Bacteria K-Means Minimum Inhibitory Concentration

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information system model for maize research to anticipate the impact of climate change on Indonesian food security

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AIP Conference Proceedings 2023年第1期2594卷

作者： A. S. Perbangsa F. A. Munawwar M. B. Pabendon B. Pardamean Information Systems Department School of Information Systems Bina Nusantara University Jakarta 11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Indonesia Cereals Research Institute Maros South Sulawesi 90514 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

As a rich country in genetic resources, Indonesia has the potential for strengthening food security. Maize is one of the commodities that greatly affect food security in Indonesia. Maize is also widely used as animal feed. The high demand for maize requires efforts to increase the productivity of sustainable cultivation. Various research efforts that have been carried out require the support of a comprehensive information system. This study aimed to build a research model for maize genetic resource information systems that can help search for superior varieties. The data collection method used was collecting genotype, phenotype, climate data and interviewing the maize breeders or researchers. As for the design of the model, this study used the Object-Oriented Analysis & Design (OOAD) method with notation from Unified Modelling Language (UML). The result of this research was a web-based model of information systems for maize research.

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Improving Rice Productivity in Indonesia with Artificial Intelligence 7

Improving Rice Productivity in Indonesia with Artificial Int...

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7th International Conference on Cyber and IT Service Management, CITSM 2019

作者： Liundi, Nicholas Darma, Aditya Wirya Gunarso, Rivaldi Warnars, Harco Leslie Hendric Spits School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728129099

Indonesia is one of the biggest agriculture countries in the world with one of its major commodities, rice. Despite its vast paddy field and tropical resources, Indonesia still has not achieved food security. This paper explores ideas about how to present artificial intelligence that may increase rice productivity in Indonesia. Current situations of rice cultivation are mentioned start from existing technologies and systems used in Indonesia. Some artificial intelligence concepts are also introduced. Artificial Intelligence use in rice farming is then analyzed which ideas may be applicable to increase efficiency further. Those that are already implemented in rice farming include diseases and pest detection, prediction and estimation, and automated intelligent systems. In the proposed idea section, ideas to increase production are explored. Using advanced technologies may not be suitable for Indonesia's rice farmers. One argument is to minimize the differences in rice yield in different areas or so what we called yield gap. Factors such as weather, water, and harvest date are those with most impacts on the yield gap. It is beneficial to have a model that can predict the optimal planting date of rice since that will maximize the factors before. Among those implemented, a planting calendar prediction on rice-based on rainfall is already developed. However, rainfall is not the only factor. El-Nino occurrences and temperature changes also have a role in deciding when best to plant rice. The author suggests adding those two new variables, making three in total to the earlier neural network model may improve the overall result. © 2019 IEEE.

关键词： Productivity

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Mobile Patient Application for Outpatient 4

Mobile Patient Application for Outpatient

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4th International Conference on Informatics and Computing, ICIC 2019

作者： Kristiadi, Dedy Prasetya Hasanudin, Muhaimin Sutrisno Salim, Jennifer Gunawan, Michael Glenn Laurence, Angeline Chandra, Antoni Hendric Spits Warnars, Harco Leslie Mantoro, Teddy Computer Systems Department Raharja University Tangerang15117 Indonesia Information Systems Department Raharja University Tangerang15117 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia Department of Computer Science Faculty of Science and Technology Sampoerna University Jakarta12780 Indonesia

ISBN: (纸本)9781728122076

We as a human can not avoid the disease, and when we are sick, we need to see a practical doctor. However, in term of location and patient's right for changing the practical doctor, then the patient when moving from one practical doctor to others will have similar and repeated questions such as medicine allergy, history of diseases and so on. Moreover, become a problem for a vulnerable patient such as unconscious patient, disabled or elderly when seeing a new practical doctor and at the end of the day, it will become malpractice. Few of the causes of the problem above are the lack of health education, delay in diagnosing/misdiagnosis, and inaccessible healthcare facilities and with the increasing popularity of telemedicine and IoT across the world, then we need to apply IoT in order to help the patient. In this paper, a framework is created and designed for an IoT-integrated mobile application for the patient where this mobile application is expected to be implemented. © 2019 IEEE.

关键词： Internet of things

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Precision Rehabilitation for Patients Post-Stroke based on Electronic Health Records and Machine Learning

arXiv

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arXiv 2024年

作者： Gao, Fengyi Zhang, Xingyu Sivarajkumar, Sonish Denny, Parker E. Aldhahwani, Bayan M. Visweswaran, Shyam Shi, Ryan Hogan, William Bove, Allyn Wang, Yanshan Department of Health Information Management University of Pittsburgh PittsburghPA United States Department of Communication Science and Disorders University of Pittsburgh PittsburghPA United States Intelligent Systems Program School of Computing and Information University of Pittsburgh PittsburghPA United States Department of Physical Therapy University of Pittsburgh PittsburghPA United States Department of Medical Rehabilitation Sciences Umm Al-Qura University Makkah Saudi Arabia Department of Biomedical Informatics University of Pittsburgh PittsburghPA United States Department of Computer Science University of Pittsburgh Medical Center PittsburghPA United States Data Science Institute Medical College of Wisconsin MilwaukeeWI United States Hillman Cancer Center University of Pittsburgh Medical Center PittsburghPA United States

Objective In this study, we utilized statistical analysis and machine learning methods to examine whether rehabilitation exercises can improve patients post-stroke functional abilities, as well as forecast the improvement in functional abilities. Our dataset is patients’ rehabilitation exercises and demographic information recorded in the unstructured electronic health records (EHRs) data and free-text rehabilitation procedure notes. Through this study, our ultimate goal is to pinpoint the specific rehabilitation exercises that can effectively aid post-stroke patients in improving their functional outcomes in basic mobility (BM) and applied cognitive (AC) domains. Data sources We collected data for 265 stroke patients from the University of Pittsburgh Medical Center, accessed through the Rehabilitation Datamart With Informatics iNfrastructure for Research (ReDWINE). Methods We employed a pre-existing natural language processing (NLP) algorithm to extract data on rehabilitation exercises and developed a rule-based NLP algorithm to extract Activity Measure for Post-Acute Care (AM-PAC) scores, covering basic mobility (BM) and applied cognitive (AC) domains, from procedure notes. AM-PAC scores were collected at the initial rehabilitation visit and followed up at one and two months—key recovery periods. Changes in AM-PAC scores were classified based on the minimal clinically important difference (MCID), and significance was assessed using Friedman and Wilcoxon tests. To identify impactful exercises, we used Chi-square tests, Fisher's exact tests, and logistic regression for odds ratios. Additionally, we developed five machine learning models—logistic regression (LR), Adaboost (ADB), support vector machine (SVM), gradient boosting (GB), and random forest (RF)—to predict outcomes in functional ability. Results Statistical analyses revealed significant associations between functional improvements and specific exercises. In the AC domain, the BALANCE exercise showed substant

关键词： Statistical tests

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Photonic Terahertz Phased Array

arXiv

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arXiv 2024年

作者： Niu, Li Feng, Xi Zhang, Xueqian Lu, Yongchang Wang, Qingwei Xu, Quan Chen, Xieyu Ma, Jiajun Qiu, Haidi Sha, Wei E.I. Zhang, Shuang Alù, Andrea Zhang, Weili Han, Jiaguang Center for Terahertz Waves College of Precision Instrument and Optoelectronics Engineering The Key Laboratory of Optoelectronics Information and Technology Tianjin University Tianjin300072 China Key Laboratory of Micro-nano Electronic Devices and Smart Systems of Zhejiang Province College of Information Science & Electronic Engineering Zhejiang University Hangzhou310027 China Department of Electrical & Electronic Engineering University of Hong Kong 999077 Hong Kong Photonics Initiative Advanced Science Research Center City University of New York New York10031 United States Physics Program Graduate Center City University of New York New York10016 United States School of Electrical and Computer Engineering Oklahoma State University StillwaterOK74078 United States Guangxi Key Laboratory of Optoelectronic Information Processing School of Optoelectronic Engineering Guilin University of Electronic Technology Guilin541004 China

Phased arrays are crucial in various technologies, such as radar and wireless communications, due to their ability to precisely control and steer electromagnetic waves. This precise control improves signal processing and enhances imaging performance. However, extending phased arrays to the terahertz (THz) frequency range has proven challenging, especially for high-frequency operation, broadband performance, two-dimensional (2D) phase control with large antenna arrays, and strong phase modulation. Here, we introduce a photonic platform to realize a THz phased array that bypasses the above challenges. Our method employs 2D phase coding with 2-bit across a broad THz frequency range from 0.8 to 1.4 THz. The core of our design is a pixelated nonlinear Pancharatnam-Berry metasurface driven by a spatially modulated femtosecond laser, allowing precise phase control of THz signals. We showcase the effectiveness of our method through four proof-of-concept applications: single beamforming, dual beamforming, imaging and vortex beam generation. The realized photonic platform provides a promising pathway for developing broadband phased arrays in the THz regime. Copyright © 2024, The Authors. All rights reserved.

关键词： Terahertz waves

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