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The effect of visual advanced driver assistance systems on a following human driver in a mixed-traffic condition

Procedia computer science 2023年 216卷 221-229页

作者： Dedy Ariansyah Bens Pardamean Giandomenico Caruso Bioinformatics and Data Science Research Centre Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia Department of Mechanical Engineering Politecnico di Milano Milan 20156 Italy

Rapid development in vehicular technology has caused more automated vehicle control to increase on the roads. Studies showed that driving in mixed traffic with an autonomous vehicle (AV) had a negative impact on the time headway (THW) of conventional vehicles (CVs) (i.e., driven by humans). To address this issue, there is a need to equip CV with visual advanced driver assistance systems (ADASs) that helps the driver maintain safe headway when driving near AVs. This study examines the perception of drivers using visual ADAS and their associated risk while driving behind the AV at constant and varying speeds. The preliminary results showed that while visual ADAS could help drivers keep the safe THW, it could affect drivers’ ability to react to emergencies. This implies that visual modality alone might not be sufficient and therefore requires some other feedback or intelligent transport systems to help drivers maintain safe driving in a mixed-traffic condition.

关键词： sustainable transport management platooning car-following visual advanced driver assistance system virtual realtiy

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Density Based Spatial Clustering of Applications with Noise and Sentence Bert Embedding for Indonesian Utterance Clustering

Density Based Spatial Clustering of Applications with Noise ...

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computer science, Information Technology and Engineering (ICCoSITE), International Conference on

作者： Muhammad Fikri Hasani Yaya Heryadi Yulyani Arifin Lukas Wayan Suparta Computer Science Department BINUS Graduate Program Computer Science School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Task oriented chatbots are a sub-topic related to chatbots, where chatbots will perform certain tasks with specific goals. One part of creating a task-oriented chatbot is doing intent classification. Intent classification is a task of text classification. As in general text classification, the required dataset requires a label to carry out the classification process. To speed up and help the utterance analysis process, there is already a method, namely clustering, and Density-based clustering is a part of clustering that can determine cluster patterns based on arbitrary data, with DBScan as one of its algorithms. This research used 10000 client utterance data of awhatsapp based e-commerce conversation. SentenceBert also used as a state of art sentence embedding. This research yield silhouette score of 0.327 as the best result from eps of 0.1 and MinPts of 95. However, based on the cluster result, sentences labelled as noise can be further clustered. Text Preprocessing, text augmentation and sentence embedding techniques can be explored to increase the cluster performance.

关键词： computer science Art Text categorization Clustering algorithms Oral communication Chatbots Classification algorithms

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Pap Smear Medical Image Classification Using Deep Learning: A Systematic Review

Pap Smear Medical Image Classification Using Deep Learning: ...

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International Conference of computer and Informatics Engineering (IC2IE)

作者： Elvan Selvano Gregorius Natanael Elwirehardja Bens Pardamean Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia

Cervical cancer has been known as one of the most prevalent medical disorders globally and a leading cause of death. Early detection, particularly through Pap tests, plays a vital role in its prevention. Previous studies have leveraged machine learning and deep learning techniques to classify the medical images obtained from Pap tests. In this study, a Systematic Literature Review methodology was used to examine 15 relevant papers that have been filtered from queries to Google Scholar which have gone through 4 stages of filtering that include: identification, screening, eligibility, and inclusion. This study addresses two research questions regarding the datasets and deep learning techniques for classifying pap smear images in recent years. The performance of the models was analyzed and potential areas for improvements are suggested. The findings of this study reveal that the Herlev University Hospital and SIPaKMed datasets are the most used. The methodologies used by researchers range from machine learning techniques, transfer learning using Convolutional Neural Networks, and utilize state-of-the-art models with novel optimizing methodology. While there are exciting opportunities in the field, challenges include model generalization and interpretability.

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E-Government Interoperability: Provincial-Level Architecture Model to Enable Fast Healthcare Interoperability Resources (FHIR)

E-Government Interoperability: Provincial-Level Architecture...

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International Conference on Information Management and Technology (ICIMTech)

作者： Diana Wijayanti Satriawansyah Urbaya Taufiq Sitompul Verry Adrian Department of Information Systems BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Country Health Information Systems and Data Use (CHISU) Program USAID Indonesia Jakarta Indonesia Department of Informatics University of Oslo Oslo Norway Computer Science Department Binus Graduate Program – Doctor Computer Science Bina Nusantara University Jakarta Indonesia Center of Data and Information Technology Jakarta Provincial Health Office Jakarta Indonesia

ISBN: (数字)9798350390025

ISBN: (纸本)9798350390032

The process of using ICT to provide services to the public is known as the Indonesian e-Government system, or Sistem Pemerintahan Berbasis Elektronik (SPBE). The e-Government initiative in Jakarta Provincial Health Office involves enhancing collaboration among public health entities for efficient data exchange and streamlined processes, especially between the Provincial and District Health Offices, public hospitals, government clinics, and primary health care centers (Puskesmas). Achieving interoperability requires standardized protocols and a well-defined architectural model to integrate data seamlessly. This study presents a provincial-level architectural model focused on improving electronic health records interoperability, aiming to promote the adoption of the national Fast Healthcare Interoperability Resources (FHIR) health information exchange platform and enhance the integrity of health data in Jakarta. The study methodology involves conducting literature reviews, observations, and discussions with representatives from healthcare facilities to develop the e-Government architecture model and prototype of the infrastructure layer aiming to facilitate the interoperability of Electronic Health Records (EHRs) across 93 healthcare facilities, all of which are part of the SPBE users.

关键词： Prototypes Medical services Data models Security Public healthcare Electronic medical records Interoperability Information exchange Standards Electronic government

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Service Oriented Fuzzy Decision Model for Road Traffic Engineering

Service Oriented Fuzzy Decision Model for Road Traffic Engin...

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International Conference on Computing, Engineering, and Design (ICCED)

作者： Ditdit Nugeraha Utama Fauzan Affan Zaki Intan Juliani Munjeri Nidya Utami Putri Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department UIN Syarif Hidayatullah Jakarta Indonesia

A number of attempts have already been implemented formally to solve road traffic congestion. However, the objective strategy type of road traffic engineering could not be proven truly. Try and error is one inefficient way in road traffic engineering to degrade the level of congestion. The study was conducted to propose a new service-oriented model (SOM) that combines fuzzy-logic and water flow algorithm methods (called FWFA). The method combination was operated as the main method to construct the decision model for selecting the objective strategy in road traffic engineering. Also, service-oriented architecture (SOA) is realized to implement such a constructed model practically. The Model can suggest the most optimal strategy decision in road traffic engineering. Here, a main traffic road of Juanda in area Ciputat, Tangerang Selatan, province Banten, Indonesia; was selected as a research object in this study. The constructed SOM for road traffic engineering was structurally delivered in this paper.

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Social Media Analysis using Sentiment Analysis on COVID-19 from Twitter 6

Social Media Analysis using Sentiment Analysis on COVID-19 f...

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

作者： Iqbal Maulana, Fairuz Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350399615

The development of the internet is getting faster, participating in encouraging the emergence of new and innovative information. In filtering the various information that appears, we need a recommended system to perform well for users in today's internet era. A well-performing recommendation system in question is a reliable recommendation algorithm. This algorithm is fundamental to analyzing various information, such as responses on social media based on user behavior data related to the topic of COVID. This data is crawled from tweets on social media Twitter. The data analysis algorithm obtained uses Python, which is then visualized in the form of a diagram. The processed data is user comments on Twitter, and the text data is analyzed using Python, using more than 60000 data sets taken to form visualizations and conclusions. From sentiment analysis, polarity and subjectivity data are obtained to be analyzed, which are negative, neutral, or positive. The result is show positive tweets with 29.2%, negative tweets is 13%, and 57.8% neutral tweets. Lastly, sentiment analysis can help people effectively infer vast and complex data from social media like Twitter. © 2022 IEEE.

关键词： COVID-19 python sentiment analysis social media twitter

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Sentiment Analysis of Cooking Oil using Bidirectional Encoder Representations from Transformers 5

Sentiment Analysis of Cooking Oil using Bidirectional Encode...

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

作者： Widianto, Mochammad Haldi Heryadi, Yaya Lukas Suparta, Wayan Wibowo, Antoni Bina Nusantara University Computer Science Department Binus Graduate Program - Doctor of Computer Science Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Departement of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (数字)9781665451406

ISBN: (纸本)9781665451406

Recently, cooking oil has been widely discussed on social media. Many people ask how to analyze this phenomenon, one of which is using a sentiment analysis application on Twitter that performs a scientific analysis of the tweets of this media user. This study aims to test the performance of the sentiment analysis algorithm utilizing the Bidirectional Encoder Representations from Transformers (BERT) algorithm from Twitter, which is used to classify the types of tweets processed in 2000 tweets. The study shows the results of the confusion matrix, accuracy, and precision. The study obtained a fairly good accuracy and precision performance of 84%, which occurred at a learning rate of 1e-6 and epoch 5. The author also discusses the factors that affect the performance of BERT, such as;pre-processing, data quantity, and data variation. © 2022 IEEE.

关键词： Sentiment analysis

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Tree Counting with Deep Forest Algorithm for Kulon Progo District in Yogyakarta, Indonesia Using Pleiades Satellite Imagery

Tree Counting with Deep Forest Algorithm for Kulon Progo Dis...

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ICT Conference (AICTC), Arab

作者： David Wijaya Ibrahim Seto Aditama Stanley Armando Austen Calvin Surya Widjaja Bakti Amirul Jabar Edy Irwansyah Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Tangerang Selatan Indonesia Computer Science Department School of Computer Science Bina Nusantara University Bandung Indonesia BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350342086

ISBN: (纸本)9798350342093

Trees are one of the most important living things on the planet. Trees help by being one of the largest producers' oxygens on planet, by absorbing groundwater and by maintaining soil fertility. Trees can also be one of the keys to reducing existing air pollution. Therefore, the number of existing trees must be maintained. The first step in maintaining the number of existing trees is to count or map them. One of the easiest ways is to do this use an algorithm. This study uses a tree-counting algorithm called Deep Forest. Deep Forest is a Python package that can detect trees through RGB satellite imagery. This study used satellite imagery from Pleiades on an area in Kulon Progo district, Yogyakarta, Indonesia for the image-one of the four regencies within Yogyakarta Province in Indonesia. In addition to the Deep Forest algorithm, this research also used an application provided by Esri called ArcGIS Pro. With this application, data preprocessing such as labeling the data and creating the deep learning dataset for research is much easier, while ArcGIS Pro provides tools for labeling and exporting the data to jupyter notebook. The result obtained using the Deep Forest algorithm is the F1 score with an accuracy of 0.76 for the first experiment, 0.774 for the second experiment, and 0.779 for the final experiment.

关键词： Deep learning Training Codes Planets Vegetation Soil Regression analysis Satellite images Labeling Random forests

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Prediction of DHF (Dengue Hemorrhagic Fever) Severity Using Random Forest, KNN, Decision Tree and Naïve Bayes 7

Prediction of DHF (Dengue Hemorrhagic Fever) Severity Using ...

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7th IEEE International Conference on Information Technology and Digital Applications, ICITDA 2022

作者： Pohan, Husni Iskandar Suparta, Wayan Heryadi, Yaya Wibowo, Antoni Lukas Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Institut Teknologi Nasional Yogyakarta Department of Electrical Engineering Yogyakarta55281 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

ISBN: (数字)9781665461368

ISBN: (纸本)9781665461368

Dengue Hemorrhagic Fever is an acute viral infectious disease caused by the dengue virus. Transmitted through the bite of Aedes Mosquitoes and divided into 4 severity. Severity 1 and 2 are characterized by a decrease in platelet levels below normal and there is a change in hemoconcentration, while Severity 3 and 4 are included in Dengue Shock Syndrome (DSS). The purpose of the study was to classify the severity of dengue, based on age, gender, platelets, body temperature, bleeding, and also doctor's recommendation. The advancement of information technology is the reason for the development of medical science, especially with artificial intelligence. Abundant medical data becomes a source that can be processed in improving the quality of medical information. The method chosen is Random Forest, kNN, Decision Tree and Naïve Bayes. The dataset used is the medical records of all DHF patients for 30 months in the period Jan 2019 to June 2021, at the Nadhifa Al Ghiffari Clinic in Bojongsoang District, Bandung Regency. © 2022 IEEE.

关键词： Decision trees

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Snake and digital ladder applications involving the behavior of children applying the health protocols 2

Snake and digital ladder applications involving the behavior...

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2nd Annual Conference of science and Technology, ANCOSET 2020

作者： Ariessanti, H.D. Gaol, F.L. Supangkat, S.H. Ranti, B. Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Esa Unggul University Jakarta11510 Indonesia

This study defines the problem of how understanding health protocols during a pandemic is correctly conveyed according to age levels. This problem for the Government to implement gamification by modifying game media through snake and ladder game that can socialize health protocols for pre-school. Measuring the acceptance of a snake and ladder game media can be considered as a learning medium from the Government which will refer to four components (game content, ease of play, appearance, and active player involvement). The purpose of this study was to modify online-based games as a learning media and to measure children's active interaction with parents in practicing health protocols during game play. This study will use a quantitative approach with data techniques through playing together experiments and filling in online research questionnaires from 115 samples as participants (7 Kindergartens). The results show that the snake and ladder digital game can have a significant effect on changes behavior in implementing health protocols. This research can provide a contribution that can be used as a reference for the Government to design a strategy for socialization through gamification. © Published under licence by IOP Publishing Ltd.

关键词： Health

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