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检索条件"机构=Postgraduate Program in Computer science"

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Unbalanced Data Clustering with K-Means and Euclidean Distance Algorithm Approach Case Study Population and Refugee Data 2

Unbalanced Data Clustering with K-Means and Euclidean Distan...

引用

2nd International Conference on computer, science, Engineering, and Technology, ICComSET 2019

作者： Faizah, N.M. Surohman Fabrianto, L. Hendra Prasetyo, R. Information Systems Department Tama Jagakarsa University Jakarta Indonesia Master of Computer Science-Postgraduate Program STMIK Nusa Mandiri Jakarta Indonesia

There is a lot of data that does not have a pattern and unbalanced that is difficult to classify, such as the total population of each country in the world is very varied especially when compared with the number of refugees from each of these countries, China and India numbered more than 2 billion people but the number of refugees is only 0, 01%, while Syria around 70% of the 18 million more residents are refugees. By using the K-Means algorithm, we can group countries that have similar characteristics of population and number of refugees, the average percentage of refugees to the population in each cluster is the character of the cluster. The methodology used in this study are: measures the distance of the data using the Euclidean distance formula, runs the K-Means algorithm, calculate the percentage value of each cluster and find conclusions from the characteristics of the clusters formed. We found how machine learning made a pattern of data without political and social issues, the result is K-Means describing machine learning can grouped every country in cluster that make sense. © Published under licence by IOP Publishing Ltd.

关键词： K-means clustering

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Performance analysis of message prioritization in delay tolerant networks

Performance analysis of message prioritization in delay tole...

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2012 IEEE Military Communications Conference, MILCOM 2012

作者： McAtee, Florence Narayanan, Sathya Xie, Geoffrey G. Computer Science and Information Technology Program California State University Monterey Bay Seaside CA 93955 United States Department of Computer Science Naval Postgraduate School Monterey CA 93943 United States

ISBN: (纸本)9781467317290

A variety of network deployments in disaster recovery, fire fighting and military scenarios create networks that do not form a connected network all the time. In such scenarios, paths between a source and destination may be created over time when nodes encounter each other due to node mobility. Many routing algorithms that can route messages in such delay-tolerant networking (DTN) settings have been proposed. Currently, these protocols do not differentiate between the messages that are being routed through the network treating all messages equally. But, there are DTN scenarios, in particular in military situations, where it is critical that messages are differentiated based on their importance to the task being supported. In this paper, we propose extensions to two popular DTN routing protocols, Epidemic and PROPHET, to implement such message prioritization. We implemented the proposed extensions in ONE (Opportunistic Network Emulator) and studied the performance of these extensions. Results from our simulation analysis demonstrate that it is possible to implement message prioritization in non-deterministic delay tolerant networks and provide us with insights into configuring message prioritization in DTN. In particular, the importance of selecting optimal queue lengths at each node to mitigate congestion in such networks. © 2012 IEEE.

关键词： Delay tolerant networks

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Learning multiple description logics concepts 23

Learning multiple description logics concepts

引用

23rd International Conference on Inductive Logic programming, ILP 2013

作者： Melo, Raphael Revoredo, Kate Paes, Aline Postgraduate Information Systems Program UNIRIO Rio de Janeiro Brazil Department of Computer Science Institute of Computing UFF Rio de Janeiro Brazil

Description logics based languages have became the standard representation scheme for ontologies. They formalize the domain knowledge using interrelated concepts, contained in terminologies. The manual definition of terminologies is an expensive and error prone task, therefore automatic learning methods are a necessity. In this paper we lay the foundations of a multiple concept learning method that uses virtual concepts to aid the learning process, yielding more compact and readable terminologies. In this paper, we define virtual concepts and how they can be implemented in the current concept learning methods. We show through experiments how the method stacks up against other multiple concept learning methods.

关键词： Terminology

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A Software Process Simulator Machine for Software Engineering Simulation Games

A Software Process Simulator Machine for Software Engineerin...

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Brazilian Symposium on Games and Digital Entertainment

作者： Rafael O. Chaves Eloi L. Favero Emanuel M. da C. Tavares Sandro R. B. Oliveira Postgraduate Program in Electrical Engineering ITEC - UFPA Postgraduate Program in Computer Science ICEN - UFPA

ISBN: (纸本)9781612843919

Develop new games without having to start from scratch has been made possible by using game engines, since they offer a number of specialized components and optimized functions which are common in games. However, one realizes that process simulation games have not taken advantage of these technologies. This paper aims to demonstrate the results of the development of a software process simulation component called Software Process Simulator Machine (SPSM), which focuses on help and motivate software process educational game development through the addressing of main generic requirements for process simulation software.

关键词： Software Process Simulation Engines

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Determination of C4.5 Algorithm Performance Based on Training Data and Testing Data in Determining Diseases in Rice Plants

Determination of C4.5 Algorithm Performance Based on Trainin...

引用

International Conference of computer science and Information Technology

作者： Rahmadani Siregar Hartono Roslina Muhammad Zarlis Wanayumini Computer Science Postgraduate Study Program Universitas Potensi Utama Medan Indonesia Computer Science Postgraduate Study Program Politeknik Negeri Medan Medan Indonesia Computer Science Postgraduate Study Program University of Bina Nusantara Jakarta Indonesia

Disease detection in rice plants at the Padang Lawas District Agriculture Service is carried out every year by collecting data from the Agriculture Service. Therefore, it is necessary to carry out classification to determine the best percentage of training data and test data in determining rice plant diseases and a comparison between testing data and training data for accurate accurate predictions. So data mining algorithms are needed that must be used to classify these diseases. Classification is carried out to group data into categories or groups so that objects from the same data are more similar to data objects from different groups. In this study, disease classification was processed using the C4.5 algorithm using disease data collection on rice plants from 2017 to 2020 which had a total of 248 data. The results of testing data and training data will be compared to see accuracy performance.

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Privacy Preserving Electronic Health Record with Consortium Blockchain 6

Privacy Preserving Electronic Health Record with Consortium ...

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6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022

作者： Gautama, Adri Rochim, Adian Fatchur Bayuaji, Luhur Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Diponegoro University Department of Computer Engineering Semarang Indonesia Computer Science Budi Luhur University Jakarta Indonesia

ISBN: (纸本)9798350399615

Every patient has health record, it was written as statement of patient's conditions, treatments, and medications, and nowadays it is become digitalized, it can be copied and shared easily, but the nature of EHR is private, not for public, private between patients and healthcare provider. Privacy preserving can be done by implementing Blockchain network for storing EHR, only authorized users or nodes can access and write data to the network. New block in blockchain created as per consensus among nodes, every node can join a blockchain network if it is public, to meet a consensus required resources intensive cryptographic challenge, in private blockchain, only selected can join and involved in the network or specific transaction. In healthcare, data privacy is the main concerned, need a secure, scalable, and efficient blockchain hence implementing consortium blockchain is perfect match for EHR where multiple healthcare provider can operate in a single platform to conduct transaction or sharing EHR among members. This study analyzes 15 articles derived from IEEE Explore, science Direct and Scopus by implementing screening with keyword Consortium Blockchain and EHR and proposing new blockchain model accommodating solution for challenges on access, storage, sharing, privacy, and performance. © 2022 IEEE.

关键词： Consortium Blockchain e-health EHR Privacy

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New Student Prediction Using Algorithm Naive Bayes And Regression Analysis In Universitas Potensi Utama

New Student Prediction Using Algorithm Naive Bayes And Regre...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Elsa Aditya Zakarias Situmorang B. Herawan Hayadi Muhammad Zarlis Wanayumini Computer Science Postgraduate Study Program Universitas Potensi Utama Medan Indonesia Computer Science Postgraduate Study Program Saint Thomas Catholic University Medan Indonesia Computer Science Postgraduate Study Program University of Sumatera Utara Medan Indonesia

ISBN: (纸本)9781665453967

Universitas Potensi Utama has various study programs, and also has various facilities to support student learning activities. However, the main obstacle in higher education is the uncertainty of the interest of students who register, so that sometimes the facilities are inadequate. To overcome these problems, there must be activities to predict prospective new student applicants to improve facilities and interest of prospective students to choose to study at the Universitas Potensi Utama. Forecasting is the most important thing that must be applied to a company. With this forecasting, companies can see the opportunities that exist to generate sales predictions in the future based on the results of past sales data. Naive Bayes is a classification using probability and statistical methods, the Naive Bayes algorithm can be used in scientific fields, one of which is predicting future opportunities based on previous experience. Linear regression method can be used for forecasting with the assumption that the correlation between variables will continue in the future. Linear Regression is a Regression Method where the resulting equation is linear. Based on the resulting equation, predictions can be calculated by entering the values of the predictor variables in the equation. Based on this process, the predictive value of the response variable can be generated. In this study, the author explains more about how to determine new student predictions using a combination of the two algorithms where the Naïve Bayes algorithm is used to state which study programs have a lot of interest in the coming year, and the Linear Regression algorithm is used to show which study programs are most in demand based on the number of students who registered in the previous year, In the description that has been stated above, the author makes a paper with the title: “Predictions of New Student Registration Using the Naive Bayes Algorithm and Regression Analysis at the Universitas Potensi Utama”.

关键词： Uncertainty Linear regression Companies Prediction algorithms Mathematical models Classification algorithms Naive Bayes methods

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Spatial Hotspot Data and Weather for Forest Fire Data Clustering 5

Spatial Hotspot Data and Weather for Forest Fire Data Cluste...

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5th International Conference on Information and Communications Technology, ICOIACT 2022

作者： Mimboro, Prasetyo Kusrini, Kusrini Laksito, Arif Dwi Postgraduate Program Universitas Amikom Yogyakarta Yogyakarta Informatics Engineering Departement Amikom Yogyakarta Indonesia Universitas Amikom Yogyakarta Faculty of Computer Science Amikom Yogyakarta Indonesia

ISBN: (数字)9781665451406

ISBN: (纸本)9781665451406

Prediction of fire forest will be needing several parameters that located on the same location and on the same time frame. This is important to have data on the same location and same time periods, since forest fire mostly triggered by weather or temperature condition on certain area on the certain time. Since there are many parameters involved, the preprocessing will need to made the data have standard structure. The clustering process needed to give a label to the data with five class label, very low risk, low risk, medium risk, high risk, very high risk. Based on the data set, we measurement the best cluster number related with DB index, the results shows that 8 cluster is the best number of the data with DB Index score are 0.8856. © 2022 IEEE.

关键词： Fires

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Quality of service for ad hoc wireless network 22

Quality of service for ad hoc wireless network

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22nd International Conference of the Chilean computer science Society, SCCC 2002

作者： Roche, A. Westphall, C.B. Graf Von Mecklenburg, P.A.C.K.-S. Network and Management Laboratory Postgraduate Program in Computer Science Technological Center Federal University of Santa Catarina Brazil Faculty of Social Sciences University of Edinburgh United Kingdom

ISBN: (纸本)0769518672

Wireless networks represent the new computer paradigm. They have as main function to provide users with permanent access, independently of their physical location. With the decrease in the costs of portable devices and the increase in their capacity, a new concept called ad hoc network appeared. Through this technology, communication is made directly between mobile computers. In this paper, the proposal and validation of a mechanism based on the bandwidth management principle are done to guarantee QoS (Quality of Service) in ad hoc wireless networks. Therefore, a software is developed to simulate ad hoc environments, making connections following the approach of the already proposed mechanism. Several experiences demonstrating the advantages of this method were carried out. They proved that this method guarantees a better use of the transmission channel and, at the same time, accepts more connections. © 2002 IEEE.

关键词： Quality of service

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Analyzing User Comments on Fintech E-wallet Applications in Indonesia Using the LDA Algorithm 7

Analyzing User Comments on Fintech E-wallet Applications in ...

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7th International Conference on Information Technology, InCIT 2023

作者： Widiantoro, Albertus Dwiyoga Mustafid, Mustafid Sanjaya, Ridwan Diponegoro University Doctoral Program of Information System School of Postgraduate Studies Semarang Indonesia Soegijapranata Catholic University Information System Computer Science Fakulcty Semarang Indonesia

ISBN: (纸本)9798350358698

The main objective of this article is to compare user comments from 4 Fintech applications in Indonesia using the Latent Dirichlet Allocation (LDA) algorithm. This research is word processing research carried out using text mining. The statistical population is comments from Fintech users Ovo, Dana, LinkAja, and Doku, with data taken from May 2022-May 2023. LDA and the Python programming language are applied to analyze the data and implement text mining algorithms from topic modeling. Each application group has different topic coherence, each application group is analyzed and 4 large categories are found, namely system convenience, system problems, customer service (CS) problems, and service ease. The results of text mining and processing using Coherence and Latent Dirichlet allocation can be used to identify hidden topics and be used as input for system improvements © 2023 IEEE.

关键词： Population statistics

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