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Concept, Technology, Barriers To Smart Village: A Systematic Literature Review 11

Concept, Technology, Barriers To Smart Village: A Systematic...

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11th International Conference on Cyber and IT Service Management, CITSM 2023

作者： Utamajaya, Joy Nashar Meyliana Prabowo, Harjanto Hidayanto, Achmad Nizar Ramadhan, Arief Bina Nusantara University Computer Science Department Binus Graduate Program - Computer Science Department Jakarta11480 Indonesia Telkom University School of Computing Bandung Indonesia

ISBN: (纸本)9798350305968

Smart villages that utilize digital technology are a solution to assist rural community services in meeting their needs, especially for developing countries. However, financial problems, namely the high cost of infrastructure, the size of the informal economy and governance are challenges in limiting the government's aspirations regarding the smart village concept. The presentation of this article examines the state of smart village development in developing countries, which includes conceptual understanding, motivations, drivers and barriers to smart villages. The purpose of this study is to find answers to research questions by reviewing several selected study articles. The method used was to search for selected studies and there were 60 selected studies identified from a search of five literature databases which initially contained 3394 articles. The results of the data were analyzed using synthetic analysis and thematic analysis. The results of this study found data related to Concept, Technology, Barriers To Smart Village which came from several articles by answering questions from the research, namely RQ1: How many articles from the 10 most populous countries discussed Smart Village, RQ2: What are the basic dimensions of Smart Village, RQ3: What new technologies are discussed in Smart Village digitization, RQ4: What are the Challenges in Smart Village. The results of this SLR can also later be used as a reference for further researchers to find out the background of research related to smart villages. The conclusion obtained in this research is the end of the explanation of this article concludes that there are still many shortcomings in this research and it is hoped that in the future many studies will be able to explore other aspects such as regulations and others that are not discussed in the article so that it is expected to be a reference for further researchers to examine information related to smart villages. in order to find an ideal and up-to-date con

关键词： Developing countries

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IoT-Based portable modules for energy consumption monitoring in smart home system 3

IoT-Based portable modules for energy consumption monitoring...

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3rd International Conference on Vocational Education and Technology, IConVET 2020

作者： Bayu, J.P. Aryanto, K.A.A. Suweken, G. Aryanto, K.Y.E. Study Program of Computer Science Graduate Program Universitas Pendidikan Ganesha Singaraja-Bali Indonesia Department of Computer System Stikom Bali Denpasar-Bali Indonesia

Energy consumption has become one of the major problems in Indonesia. The use of recent technology is highly beneficial since various automation could be done even in simple devices. In this research, portable smart home modules based on the internet of things (IoT) technology to monitor the power consumption in household electrical devices were built. The module consisted of current sensors, voltage sensors, and IoT Wi-Fi Development Board. It communicated with the server, built using the Raspberry Pi, using the MQTT protocol. The server was equipped with web pages that allowed users to monitor the devices' electrical power usage. Therefore, all of the connected modules could be monitored to provide information regarding an electric household device's defect. The results had shown that the prototypes of the modules had been successfully built. It was shown that very slight differences were found between the system measurements compared to the manual one using the 60 seconds interval measurements. The power consumed by the module was very low, where the current sensor uses 0.125 Watt while the voltage sensor uses 0.001 Watt. The portable devices were developed in the shape of small boxes;therefore, it could be easy to move and install. © Published under licence by IOP Publishing Ltd.

关键词： Internet of things

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A Review on Machine Learning Methods for Water Quality Prediction 4

A Review on Machine Learning Methods for Water Quality Predi...

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4th International Conference on Artificial Intelligence and Data sciences, AiDAS 2023

作者： Dharma, Vickenzio Leeputra Nurtanio, Nathanael Kenneth Nugroho, Fakhru Sidik Anggreainy, Maria Susan Kurniawan, Afdhal School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Doctor of Computer Science Computer Science Department Jakarta11530 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350318432

Water is an important substance for the human body. Clean water is important for not just the human body, but also for the environment. In this paper, Prisma is used to filter many of the reference paper where the paper left are used for the research. Machine learning is one of many ways to predict water quality. Using algorithms to process large amounts of data and patterns, water quality can be predicted. Prediction on water temperature, pH, and others can be used to find bad quality water and potentially find the cure for it. There are also different kinds of environment in predicting water quality, where depending on the environment certain machine learning method is better than the others. This paper contains machine learning methods, water parameters, and areas of water for water quality prediction. © 2023 IEEE.

关键词： Forecasting

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Deciding the closure of inconsistent rooted triples is NP-complete 29

Deciding the closure of inconsistent rooted triples is NP-co...

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29th International Symposium on Algorithms and Computation, ISAAC 2018

作者： Johnson, Matthew P. Department of Computer Science Lehman College Ph.D. Program in Computer Science Graduate Center City University of New York United States

ISBN: (纸本)9783959770941

Interpreting three-leaf binary trees or rooted triples as constraints yields an entailment relation, whereby binary trees satisfying some rooted triples must also thus satisfy others, and thence a closure operator, which is known to be polynomial-time computable. This is extended to inconsistent triple sets by defining that a triple is entailed by such a set if it is entailed by any consistent subset of it. Determining whether the closure of an inconsistent rooted triple set can be computed in polynomial time was posed as an open problem in the Isaac Newton Institute's "Phylogenetics" program in 2007. It appears (as NC4) in a collection of such open problems maintained by Mike Steel, and it is the last of that collection's five problems concerning computational complexity to have remained open. We resolve the complexity of computing this closure, proving that its decision version is NP-Complete. In the process, we also prove that detecting the existence of any acyclic B-hyperpath (from specified source to destination) is NP-Complete, in a significantly narrower special case than the version whose minimization problem was recently proven NP-hard by Ritz et al. This implies it is NP-hard to approximate (our special case of) their minimization problem to within any factor. © Matthew P. Johnson

关键词： Computational complexity

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Decision support system using data warehouse for retail system

Decision support system using data warehouse for retail syst...

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International Conference on Engineering, Technology and Innovative Researches 2019, ICETIR 2019

作者： Girsang, Abba Suganda Arisandi, Geri Elysisa, Calista Michelle Saragih, Melva Hermayanty Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Management Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia

CMK company is a retail company that sell and distributes miniature vehicle items to small stores. CMK has several branches in various countries that use for operational and storage warehouse. This company faces the problem for analysing sales to decide the useful strategy since this company only uses Online Transaction Processing (OLTP) database. This study implements Online Analysis Processing (OLAP) database and data warehouse to provide useful information for this company by using the nine-step method designed by Kimball & Ross. The data will be performed into dashboard to make easier for CMK Company to analyze data. Furthermore, many useful information can be provided in short and efficient time. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Data warehouses

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Pain Classification Using Statistical Feature Extraction Using Machine Learning Approach: A Pilot Study 13

Pain Classification Using Statistical Feature Extraction Usi...

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13th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2023

作者： Sudimanto Trisetyarso, Agung Kartowisastro, Iman Herwidiana Budiharto, Widodo Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Mathematics Department Jakarta11480 Indonesia Bina Nusantara University Computer Science Department Binus Graduate Program Computer Science Computer Engineering Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jl. K. H. Syahdan No. 9 Kemanggisan Palmerah Jakarta11480 Indonesia

ISBN: (纸本)9798350323184

Electrodermal activity (EDA) is a general term for all electrical phenomena occurring on the skin, both passive and active. EDA measurements are used by researchers to measure levels of stress, emotion, mental strain, and so on. Measuring human stress levels, emotions, and mental strain are generally associated with the skin conductance response. The function GSR sensor is not only used to read people's psychology but also can be used as a pain sensor used to read the degree of pain in the skin. This pilot study uses sample data from ***. The *** data is galvanic skin response sensor data. The output of this sensor is the conductivity value that occurs in the skin. The data obtained from *** will be extracted using the mean, standard deviation, maximum, minimum, RMS, skewness, and peak-to-peak characteristics. The extracted functions are selected using the forward selection method. The results of the feature selection are three features with an accuracy percentage greater than 50%, namely the mean feature, the RMS feature, and the skewness feature. The machine learning models used are bagged tree, SVM, and K-NN models. Of the three models used, the bagged tree model has the highest accuracy rate, at 98.05%, with an F1 score is 0.9807. The KNN model with k=10 has the lowest level of accuracy compared to other models, at 96.75%. © 2023 IEEE.

关键词： Extraction

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Real Time Chest X-Ray Interpretation Applying Vision Transformer for Tuberculosis Detection

Real Time Chest X-Ray Interpretation Applying Vision Transfo...

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2024 International Conference on computer Engineering, Network and Intelligent Multimedia, CENIM 2024

作者： Irhamsyah, Muhammad Roslidar Yunidar Al Lail Qadrillah, M. Nasaruddin Arnia, Fitri Munadi, Khairul Universitas Syiah Kuala Post Graduate Program in Engineering Banda Aceh2311 Indonesia Faculty of Engineering Department of Electrical and Computer Engineering 2311 Indonesia

ISBN: (纸本)9798350368802

Tuberculosis (TB) is an infectious disease that can attack the lungs and other organs. In the diagnosis of TB, the interpretation of X-ray radiological images requires special skills from medical specialists. However, the lack of experience of medical personnel and focus on X-ray examinations can be a challenge for radiologists because it has the potential to cause diagnostic errors in image interpretation. Therefore, we proposed a web-based application of real-time chest X-ray interpreter by integrating the deep learning model of Vision Transformer (ViT) to interpret chest X-ray images. The inference model was trained and tested on 652 normal and 652 tuberculosis X-ray images. The data preprocessing of Contrast Adaptive Histogram Equalization (CLAHE) was implemented to increase chest X-ray image contrast as well as inference model performance. The proposed real time system can inteprete the tested chest x-ray images with an accuracy of 95% and with simulation duration time of 4.7 seconds. © 2024 IEEE.

关键词： Diagnosis

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An Agile Implementation Model for ERP 4

An Agile Implementation Model for ERP

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4th International Conference on Information Management and Technology, ICIMTech 2019

作者： Wijaya, Santo Fernandi Prabowo, Harjanto Kosala, Raymondus Raymond Meyliana Information Systems Department Computer Science Department Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Management Department Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781728133331

The growing impact of industrial dynamics will be a challenge to increase productivity. Productivity is a demand for improving organizational performance. ERP systems are a way to increase productivity. Therefore, ERP implementation is important to ensure that ERP runs well. Critical factors in ERP implementation must get serious attention to project management. Even so, the reality of ERP implementation is slowly, even tends to experience failure, resulting in highly expensive. The previous research that carried out ERP implementation showed that the failure reached 40%, and the achievement of the benefits of ERP implementation in Indonesia is still not optimal. It can be said that ERP implementation is a complexity project. For this reason, it is necessary to consider other implementation methods that can overcome the problem in implementing ERP. An agile method is a proactive and reactive alternative to handle the problem in implementing of ERP. The development of an agile ERP model is one way to achieve success in ERP implementation. This research methodology is a survey approach to the study of literature. This research will propose an agile ERP model which will be used as an effective guide for achieving the success of ERP implementation. © 2019 IEEE.

关键词： Productivity

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Plagiarism detection on electronic text based assignments using vector space model 7

Plagiarism detection on electronic text based assignments us...

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2014 7th International Conference on Information and Automation for Sustainability, ICIAfS 2014

作者： Jiffriya, M.A.C. Jahan, M. A. C. Akmal Ragel, Roshan G. Post Graduate Institute of Science University of Peradeniya Peradeniya Sri Lanka Department of Computer Engineering University of Peradeniya Peradeniya Sri Lanka

ISBN: (纸本)9781479945986

Plagiarism is known as illegal use of others' part of work or whole work as one's own in any field such as art, poetry, literature, cinema, research and other creative forms of study. Plagiarism is one of the important issues in academic and research fields and giving more concern in academic systems. The situation is even worse with the availability of ample resources on the web. This paper focuses on an effective plagiarism detection tool on identifying suitable intra-corpal plagiarism detection for text based assignments by comparing unigram, bigram, trigram of vector space model with cosine similarity measure. Manually evaluated, labelled dataset was tested using unigram, bigram and trigram vector. Even though trigram vector consumes comparatively more time, it shows better results with the labelled data. In addition, the selected trigram vector space model with cosine similarity measure is compared with tri-gram sequence matching technique with Jaccard measure. In the results, cosine similarity score shows slightly higher values than the other. Because, it focuses on giving more weight for terms that do not frequently exist in the dataset and cosine similarity measure using trigram technique is more preferable than the other. Therefore, we present our new tool and it could be used as an effective tool to evaluate text based electronic assignments and minimize the plagiarism among students. © 2014 IEEE.

关键词： Vectors

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Sequence to Sequence Deep Learning Architecture for Forecasting Temperature and Humidity inside Closed Space 10

Sequence to Sequence Deep Learning Architecture for Forecast...

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10th International Conference on Cyber and IT Service Management, CITSM 2022

作者： Setiawan, Karli Eka Elwirehardja, Gregorius Natanael Pardamean, Bens Bina Nusantara University Binus Graduate Program Computer Science Program Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia

ISBN: (数字)9781665460743

ISBN: (纸本)9781665460743

Solar Dryer Dome (SDD), an agricultural facility for drying and preserving agricultural products, needs a smart ability to predict the future indoor climate accurately, including indoor temperature and indoor humidity, in order to optimize electricity usage. To overcome these challenges, deep learning has been a widely adopted method. This research aims to forecast the future indoor climate using time series data by implementing a sequence-to-sequence (seq2seq) architecture, which is mostly used in Natural Language Processing (NLP) tasks. The two proposed seq2seq models, Long Short-Term Memory (LSTM) seq2seq and Gated Recurrent Unit (GRU) seq2seq, have proven to be superior to the adapted LSTM and GRU. The results show that the seq2seq GRU model outperforms the adapted GRU baseline model by an average difference of 0.03013 in MAE and the seq2seq LSTM model outperforms the adapted LSTM baseline model by an average difference of 0.00941 in MAE. To the best of our knowledge, this is the first implementation of seq2seq models for indoor climate forecasting on the Room Climate dataset. © 2022 IEEE.

关键词： Long short-term memory

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