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International Conference of Computer Science and Information Technology

作者： Fairuz Iqbal Maulana Agung Purnomo Andi Pramono Mohammad Nazir Arifin Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia Interior Design Department School of Design Bina Nusantara University Jakarta Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia

ISBN: (纸本)9798350399080

Artificial Intelligence (AI) seems to be a disruptive technology that defines and reshapes the economy, more efficient industrial processes, new business models, and the service sector, becoming the development of different practices than before. The literature shows that it will be included in all fields and people's lives, as is the case in the digital economy. Artificial Intelligence for Digital Economy has not been studied significantly. This study uses bibliometric analysis to graphically map scientific publications and research trends in the Artificial Intelligence for Digital Economy sector around the world in the last ten years. The Scopus database was used to collect metadata information for this study, and VOSViewer was used to demonstrate bibliometric network mapping. We use an article selection procedure starting with the searched keywords and year constraints and then exporting the database to a RIS file format. Over the last ten years, we retrieved 540 scientific publications published between 2012 and 2021 from the Scopus database. From the data obtained, researchers at the Russian Federation have the most published papers indexed by Scopus among the most productive countries (N=131), the most productive authors are Petrenko, S.A. (N=4), and the most subject area is Computer Science (N=246). We also use VOSViewer to map the Network Theme. This study recommends incorporating research subjects Artificial Intelligence for Digital Economy: Thing, Education, Platform, Global Economy, abbreviated as TEPGE research theme.

关键词： Computer science Databases Bibliometrics Taxonomy Education Metadata Market research

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Developing art geometric app based on flash player for student in elementary school 6

Developing art geometric app based on flash player for stude...

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6th International Seminar on Mathematics, Science, and Computer Science Education, MSCEIS 2018

作者： Irawan, A. Syamsiah, S. Rangka, I.B. Niswati, Z. Mustika, F.A. Wibawanti, Y. Alamsyah, N. Marlina, D. Rahayu, W. Pinahayu, E.A.R. Informatics Study Program Universitas Indraprasta PGRI DKI Jakarta Indonesia

The purpose of research is developed learning mathematics to the matter wake up Three dimensions-based e-learning use macromedia flash. A method of this research is research and development (RnD). The phase that carried out is to identify matter by means of a analyse needs that is in research locations. Next design products which adjusted with needs of material geometric three dimensions. Math teacher and the design do validation to judge feasibility products have been made, repair based on input from validator and to pilot a small scale/limited products. The research was done at student in Elementary School. The results of the study of applications that can help teachers in conducting the process of learning and the teaching material to receive help student's geometric about three dimensions. Next undergone a try to use the widely, revision of the material further and mass production math as the basis for elementary school. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Optimization of hyper parameter bandwidth on naïve Bayes kernel density estimation for the breast cancer classification 2

Optimization of hyper parameter bandwidth on naïve Bayes ke...

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2nd International Conference on Information and Communications Technology, ICOIACT 2019

作者： Sasongko, Theopilus Bayu Arifin, Oki Al Fatta, Hanif Information Technology Department Faculty of Computer Science Universitas Amikom Yogyakarta Yogyakarta Indonesia Management of Informatics Study Program Economy and Business Departement Politeknik Negeri Lampung Lampung Indonesia

ISBN: (纸本)9781728116556

Cancer is viewed as the most harmful disease in the world. One of the most deadly cancer diseases attacking the women is breast cancer. In this paper, used Naïve Bayes classifier Kernel Density Estimation in breast cancer Wisconsin dataset take from UCI data repository. Naïve Bayes with Kernel Density Estimation was used as it could enable the Naïve Bayes to process the quantitative data. However, the performance of KDE (kernel density estimation) highly depends upon the size of the bandwidth parameter used to control the curve. The problem an accurate choice of parameter bandwidth (h) using trial and error technique requires a long process. A large bandwidth (h) will over-smooth the density and mask the structure in the data, a small bandwidth (h) will yield a density estimate that is spiky and very hard to interpret. The aim of this research is to compare the optimization of grid search parameter with the genetic algorithm to determine the bandwidth parameter (h) on the Naïve Bayes Kernel Density Estimator algorithm. The parameters used to compare the two optimization methods included accuracy, AUC (Area under Curve), and computation time. The experiment results on the test of the significance value on the comparison of grid search and algorithm in determination of the bandwidth parameter (h) naïve Bayes kernel density used Mann-Whitney Test. The result of the significance ranking showed that mean rank of the genetic algorithm accuracy was 489.95 better than the mean value of the rank of grid search accuracy at only 189.05, mean rank of AUC genetic algorithm was 491.82 better than mean rank of AUC grid search only at 187.18. The mean rank of computation time grid search was 243.37 faster than mean rank of computation time genetic algorithm at 435.63. © 2019 IEEE

关键词： Classification (of information)

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STEM-Project based learning integration on bioacoustics worksheet to enhance critical thinking skills 4

STEM-Project based learning integration on bioacoustics work...

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4th International Conference on Learning and Quality Education: "Literacy, Globalization, and Technology of Education Quality for Preparing the Society 5.0", ICLIQE 2020

作者： Widiyawati, Yeni Nurwahidah, Indri Sari, Dwi Septiana Masykuri, Mohammad Budiyanto, Cucuk Wawan Science Education Study Program Universitas Ivet Semarang Indonesia Chemistry Education Department Universitas Sebelas Maret Surakarta Indonesia Informatics Education Department Universitas Sebelas Maret Surakarta Indonesia

ISBN: (纸本)9781450375726

STEM is the interdisciplinary subject's integration which plays a key role in the future career. The integration of STEM education and project-based learning on science worksheets in digital format needs to be explored as the alternative guideline for students to provide higher-order thinking skills. Thus, this research aims to develop bioacoustic student worksheet based on STEM-project to enhance critical thinking skills. Borg & Gall model was used and adopted into five main steps: (1) research and information collecting;(2) planning;(3) develop a form of product;(4) expert judgment;(5) product revision. The preliminary research was conducted through an online questionnaire and interview with 17 science teachers in Central Java to collect information about STEM-project based learning implementation and students' critical thinking. Validation of bioacoustic student worksheet was carried out to science learning experts and two instructional media experts. Data were collected through a media validation questionnaire. Descriptive quantitative technique was used to analyze the quality of developed worksheets by converting the score to a scale of 4 based on Nieveen's criteria. The worksheet has been developed in flipbook digital format with additional animation videos to promotes active learning which is easy to use. Measure the sound wave quantities and design the bioacoustics investigation on plant growth projects give opportunities to the students to ask questions, analyze, and evaluate. Based on the expert judgment using Nieveen criteria, the developed worksheet is feasible to use, and able to enhance critical thinking skill. © 2020 ACM.

关键词： Students

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Energy Preservation in MANET Using Self-Adaptive CH Selection with Advanced Genetic Algorithm 1

Energy Preservation in MANET Using Self-Adaptive CH Selectio...

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1st International Conference on Advanced Engineering and Technologies, ICONNIC 2023

作者： Indriyono, Bonifacius Vicky Pamungkas, Natalinda Abbas, Fatima Hashim Mintorini, Ery Almohamadi, Mohammed Mahmood, Sarmad Nozad Alani, Sameer Alkhayyat, Ahmed H. Rachmawanto, Eko Hari University of Dian Nuswantoro Information System Kediri Indonesia Al-Mustaqbal University College Medical Laboratories Techniques Department Hillah51001 Iraq University of Dian Nuswantoro Visual Communication Design Kediri Indonesia College of Information Technology Imam Ja'afar Al-Sadiq University Al-Muthanna66002 Iraq Computer Technology Engineering College of Engineering Technology Al-Kitab University Iraq University of Mashreq Research Center Medical Laboratories Techniques Baghdad Iraq College of Technical Engineering University of Mashreq the Islamic University Najaf Iraq University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia

ISBN: (纸本)9798350306484

Mobile Adhoc Networks (MANETs) is an emerging technology in both the industrial and academic research. The major drawback in MANETs is improving the battery capacity. MANETs are dynamic in nature therefore during communication it consumes more energy that reduces the overall energy efficiency of the network. Many past and present researches are concern about this problem. In this paper, Energy Preservation in MANETs using Self-Adaptive Cluster Head Selection with Advanced Genetic Algorithm (EPMSA-CHAG) approach is proposed where the CH selection is performed using two segments;they are initial parameter based on CH selection and Advanced Genetic Algorithm (AGA) based CH selection. At the initial stage the parameters which are considered for the CH selection are node degree, node stability, distance, residual energy, and speed and delivery rate. Using these parameters are the best fit for CH selection is chosen then in order to find the optimal best fit from the best fit calculation, Advanced Genetic Algorithm (AGA). The proposed EPMSA-CHAG approach is simulated using NS2 and the parameters which are considered for the performance analysis are packet delivery rate, energy efficiency, end to end delay, routing overhead and throughput. The methods that are taken for the comparative analysis are HLSPM-CHSR and HAMBO-CHLD. From the results calculated it is proven that the proposed EPMSA-CHAG approach achieved high packet delivery rate, energy efficiency and throughput as well as lower end to end delay and routing overhead when compared with the earlier methods HLSPM-CHSR and HAMBO-CHLD. © 2023 IEEE.

关键词： Energy efficiency

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The Combination of Foot Switch and Low-Cost IMU for a Wearable Mouse in Human-computer Interaction

The Combination of Foot Switch and Low-Cost IMU for a Wearab...

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International Conference on Information Technology and Electrical Engineering (ICITEE)

作者： Romy Budhi Widodo Evans Jahja Yusuf Giovanno Ma Chung Human-Machine Interaction Research Center Informatics Engineering Study Program Ma Chung University Malang Indonesia Informatics Engineering Study Program Ma Chung University Malang Indonesia

The following topics are dealt with: learning (artificial intelligence); feature extraction; mean square error methods; image classification; image segmentation; human computer interaction; invertors; diseases; Intern... 详细信息

ISBN: (数字)9781728110974

ISBN: (纸本)9781728110981

关键词： Mice Fatigue Sensors Switches Throughput Standards Foot

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Determination location of disturbance the electricity distribution network for efficiency SOP repair of distribution networks based on Google Maps

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AIP Conference Proceedings 2022年第1期2499卷

作者： Yessy Asri Dwina Kuswardani Widya Nita Suliyanti M. Faiz Arnovie 1Informatics Engineering Study Program PLN Institute of Technology Jakarta Indonesia

The Electric Power Distribution Network, which in this case is also called Feeder, UP3 Manokwari has 6 (six) feeders that are used in the distribution of electricity. Feeders include Elang feeders, Kasuari feeders, Nuri feeders, Mambruk feeders, Maleo feeders, and Merpati feeders. Each feeder has a distribution transformer to distribute the electrical network to customers. Facing the feeder distribution network disruption, PLN Company UP3 Manokwari had a hard time knowing the feeder location and the faulty feeder distribution transformer location, so field officers (Yantek) had a hard time finding the location. and sub-location of each feeder disturbance. This study aims to create a system containing location and sub-location information using Google Maps as a map display. This study uses the A * (A-Star) algorithm. The A-Star algorithm uses the closest approximate distance to reach the destination and has a heuristic value. The path search process is done by first determining the nodes and assigning a graph value for each node, then calculating the graph value that brings up the latitude and longitude values. The chart values are stored in the database and then calculated using the A-Star method. The result of this system is that yantek officers can view the information directly in the form of a map showing the location points and distribution transformers of the feeder that is experiencing disturbances, the system will check the user’s position, and then the system will display the fastest route. from the officer’s location to the location of the feeder experiencing disturbances.

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Empowering Biomedical Discovery with AI Agents

arXiv

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arXiv 2024年

作者： Gao, Shanghua Fang, Ada Huang, Yepeng Giunchiglia, Valentina Noori, Ayush Schwarz, Jonathan Richard Ektefaie, Yasha Kondic, Jovana Zitnik, Marinka Department of Biomedical Informatics Harvard Medical School BostonMA United States Department of Chemistry and Chemical Biology Harvard University CambridgeMA United States Program in Biological and Biomedical Sciences Harvard Medical School BostonMA United States Department of Brain Sciences Imperial College London London United Kingdom Harvard College CambridgeMA United States Program in Biomedical Informatics Harvard Medical School BostonMA United States Department of Electrical Engineering and Computer Science MIT CambridgeMA United States Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University MA United States Broad Institute of MIT and Harvard CambridgeMA United States Harvard Data Science Initiative CambridgeMA United States

We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms. Rather than taking humans out of the discovery process, biomedical AI agents combine human creativity and expertise with AI’s ability to analyze large datasets, navigate hypothesis spaces, and execute repetitive tasks. AI agents are poised to be proficient in various tasks, planning discovery workflows and performing self-assessment to identify and mitigate gaps in their knowledge. These agents use large language models and generative models to feature structured memory for continual learning and use machine learning tools to incorporate scientific knowledge, biological principles, and theories. AI agents can impact areas ranging from virtual cell simulation, programmable control of phenotypes, and the design of cellular circuits to developing new therapies. © 2024, CC BY.

关键词： Adversarial machine learning

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Content design: E-learning module for study on cultural tourism information systems based on local wisdom 2

Content design: E-learning module for study on cultural tour...

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2nd International Conference on Vocational Education and Technology, IConVET 2019

作者： Pageh, I.M. Permana, A.A.J. Historical Education Faculty of Law and Social Sciences Ganesha University of Education Singaraja Indonesia Information Technology Department Informatics Management Study Program Faculty of Engineering and Vocational Ganesha University of Education Singaraja Indonesia

Facing the 4.0 industrial revolution, it is necessary to carry out reforms and innovations related to national education. Reforms and innovations in the implementation of components of the education system involve changes in curriculum, graduate competencies and assessments, teacher qualifications, funding, facilities and infrastructure, decentralization and educational autonomy. Bali as a world tourist destination must be maintained and passed on to the younger generation. The younger generation can use information technology to help promote Balinese culture. Bali has a lot of local wisdom that can be implemented in the tourism sector. Therefore to promote those local wisdoms, a module that can be accessed through e-learning is developed to help students develop a cultural tourism package based on local wisdom to be promoted online. The modules developed have been tested by content and media experts, which can be used independently by students. Modules can be accessed online at e-learning and they are ready to use instructions for students so they can work on assignments and projects independently. Modules containing this theory and practice are for making brochures, tour packages, videos, and websites, all of which are connected to promote tourism based on local Balinese wisdom. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Students

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Face Identification System Using Convolutional Neural Network for Low Resolution Image

Face Identification System Using Convolutional Neural Networ...

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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Muhammad Arafah Andani Achmad Indrabayu Intan Sari Areni Universitas Hasanuddin Makassar Indonesia Study Program Informatics STMIK AKBA Makassar Indonesia

ISBN: (数字)9780738125176

ISBN: (纸本)9781665418614

This research aims to determine the performance of face identification on closed circuit television (CCTV) cameras. There are two data classifications used, namely training data and testing data. The training data use the CASIA-Webface dataset. Meanwhile, the testing data consists of two data, namely the source data and the target data. The source data are form of photos taken using a Digital Single Lens Reflex (DSLR) camera, while the target data use video data taken with CCTV. The source data consists of 10 IDs, each of them has 1 image for each size, so the total images used in the source data are 50 IDs. While the target data are 20 IDs, each of them has 20 face images with low resolution characteristics, less light and face capture not parallel to CCTV. This research uses Convolutional Neural Network (CNN) method with ResNet50 architecture, ArcFace as a loss function in the training process and Cosine Similarity for the face identification process. ResNet50 and ArcFace use an embedding size of 512 and in the training process, ArcFace's scale and margin parameters are 64 and 0.5. The results indicate differences in accuracy, True Positive Rate (TPR) and False Positive Rate (FPR) from the face identification process between the image sizes used and the respective IDs in the source data. The method used had the highest performance for face image identification scenarios of 128 × 128 pixels with accuracy and FPR reached 99.30% and 0.02%. From the TPR, the method used had high performance at size of 512 × 512 pixels namely 91.50%.

关键词： Face recognition Training Faces Cameras Testing Image resolution Conferences

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