检索结果-内蒙古大学图书馆

International Conference on ICT For Smart Society (ICISS)

作者： Mutiara Indah Zakiyyah Andi Pramono Rifaldy Galih Santosa Agung Purnomo Fairuz Iqbal Maulana Ira Audia Agustina Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia Interior Design Department School of Design Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

The study examines how young people's health-related behaviors have changed due to access to mobile health (mHealth) technology when looking for health information and services. The authors emphasize that risky health practices among young people, such as a poor diet, lack of activity, and late-night sleeping habits, make them more susceptible to physical and mental problems. This quantitative descriptive study aims to ascertain the opinions and preferences of the Surabaya-area sports community in the Health and Fitness category of the Android OS mobile application. The method employed is a survey utilizing web-based questions for data collection. The questionnaire results were examined by quantitative descriptive analysis techniques and displayed as percentages. The Haters Fat application is a prototype with the primary function as a learning medium to carry out health activities, monitoring, and various health services offered. This prototype starts with making activity diagrams and continues with wireframes for smartphone displays. Furthermore, the prototype was developed considering the user interface (UI) and user experience (UX). It was discovered that most respondents had a favorable opinion of the Android operating system's health and fitness category of smartphone applications. 22.6% of respondents had accurate categorization views based on the investigation. The smartphone applications in the fitness and health category for the Android operating system received only a superficial evaluation from 30.6% and 4.8% of respondents, respectively. Most survey participants are intensely interested in the health-related Android smartphone application. The majority of respondents, in contrast, have limited perceptions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis of User Review on Indonesian Food and Beverage Group using Machine Learning Techniques

Sentiment Analysis of User Review on Indonesian Food and Bev...

引用

Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Yanfi Yanfi Yaya Heryadi Lukas Lukas Wayan Suparta Yulyani Arifin 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

A vast number of technologies based on Artificial Intelligence (AI) have proliferated into various application domains. As part of its objectives to develop agents which can behave and think like humans, some branches of AI have focused on developing various algorithms that can learn from input data without explicitly being programmed. In the food industry, notably in restaurants, smartphone technology is typically used to collect data from customers efficiently such as orders or feedback toward the services provided. The use of smartphones by some restaurants is motivated by their convenience and efficiency. Furthermore, various promotions, discounts, and membership benefits offered by cellular service providers have attracted the use of smartphones as devices for improving restaurant services to their customers. This study aimed to conduct a sentiment analysis related to multi-brand restaurants in Indonesia based on customer feedback. The data retrieved from the Google Play Store consists of 756 reviews from Boga, Champs, Hangry, Ismaya, Kulo, and Union groups. In this study, TF-IDF was used as a vectorizer to represent customer feedback as numeric vectors. The polarity sentiment of customer feedback was recognized using classifier models based on machine learning such as Logistic Regression, Naive Bayes (NB), Random Forest, and Support Vector Machine (SVM) as the classifier. The empirical results showed that SVM has the best accuracy of 93.10 % average accuracy followed by Logistic Regression with 92.41 %, Random Forest with 84.14 % average accuracy, and Naive Bayes with 76.55 % average accuracy.

关键词： Support vector machines Sentiment analysis Analytical models Machine learning algorithms Food industry Companies Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

Mapping the Literature of Artificial Intelligence in Medical Education: A Scientometric Analysis 7th

Mapping the Literature of Artificial Intelligence in Medical...

引用

7th International Conference on Inventive Communication and Computaional Technologies, ICICCT 2023

作者： Maulana, Fairuz Iqbal Zaın, Muhammad Yasır Lestari, Dian Purnomo, Agung Adi, Puput Dani Prasetyo Computer Science Department Bina Nusantara University Jakarta11480 Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Faculty of Medicine Universitas Airlangga Surabaya60132 Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Jakarta11480 Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta11480 Indonesia

ISBN: (纸本)9789819951659

This study aims to investigate the use of artificial intelligence in health education in the last ten years from 2012 to 2022 using the Scopus database. Researchers use bibliometric analysis combined with the quantification method of Vosviewer and Rstudio software used for literature analysis. The results of the article that were flushed showed data such as the year of publication, journal, country, keywords, and authors, to the highest number of citations. The general keywords used by researchers are artificial intelligence, medical, and education. Researchers limit findings through keywords as in the last ten years and English only so that 1681 articles were obtained. According to the study's findings, McGill University affiliation had the greatest number of papers, with 69 pieces, and medicine had a proportion of 39.7% (n = 1067). This bibliometric study will be useful for other researchers to examine the development of research on artificial intelligence in health education in the last ten years. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Medical education

来源：评论

学校读者我要写书评

暂无评论

Effectiveness Analysis of Distributed Scrum Model Compared to Waterfall approach in Third-Party Application Development

引用

Procedia computer science 2021年 179卷 103-111页

作者： Kresna Dwi Prasetya Suharjito Devriady Pratama Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480

Scrum is widely used to manage application development, including third-party vendors. There are some problems when third-party vendor using scrum such as communication challenges, lack of control, and lack of trust. Therefore, we proposed new model of distributed scrum using Scrum of Scrum and Holonic view to manage an application development project in third party vendors. In this study we created 3 model, Scrum Team Model, Meeting Coordination Model, and Product Backlog Model. In this study it has been shown that the Distributed scrum method is better than waterfall method as a result of the project’s success based on scope, time, and cost aspects. Based on the comparison result, it is found that the Cost Performance Index (CPI) and the Schedule Performance Index (SPI) value of the waterfall approach project is smaller than the Distributed scrum approach project as well as the change request issued by the Distributed scrum project resulting is less than the waterfall project.

关键词： Distributed Scrum Third party vendor Scrum of Scrum Holonic View

来源：评论

学校读者我要写书评

暂无评论

The Transfer Learning Influence on YOLO v8 Performance For Motorbike Detection

The Transfer Learning Influence on YOLO v8 Performance For M...

引用

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

作者： Gusti Pangestu Baskoro Aziz Febby Candra Pratama Agung Pumomo Chasandra Puspitasari Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Interior Design Department School of Design Bina Nusantara University Jakarta Indonesia Enterpreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia

The number of motorbike theft case in Indonesia has increasing rapidly. This phenomenon led to the increasing of the criminal number especially motorbike theft case. Nowadays, the use of CCTV (Closed Circuit Television) camera has been widely applied. Nevertheless, CCTV does not has the ability to prevent criminal acts such motorbike theft case. Therefore, there is a need of a technology based to prevent motorbike theft acts. This research proposed an initial research of motorbike theft detection system that focused on the process of motorbike detection using Deep Learning approach. In this research, the YOLO architecture was utilized to detect the motorbike object inside an image frame. There are two testing scenarios for motorbike detection process, using trained model, and using pre-trained model. The trained model obtain better result rather than using pre-trained model by achieving 0.93 of its accuracy that proven the YOLO v8 model are working well especially when it is applied with transfer learning process for its based model.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Monitoring Applications for Vehicle based on Internet of Things (IoT) using the MQTT Protocol

引用

Procedia computer science 2023年 227卷 73-82页

作者： Nurudin Arief Agus Sukmandhani Muhammad Zarlis Computer Science Department BinusOnline Learning Bina Nusantara University Jakarta Indonesia 11480 Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480

Monitoring of vehicle conditions is needed as one of the securities in driving because one of the accident rates is negligence in checking the condition of the vehicle. This study aims to help reduce the level of accidents and increase human awareness for vehicle conditions, especially minibus type vehicles. The system works to provide information on the condition of vehicles sourced from the Engine Control Unit (ECU). ECU data cars are obtained by SNIP traffic broadcast message and ask for data directly at the ECU. The car can provide vehicle information using a Canbus communication protocol through the OBD-II socket. Vehicle information can be seen by users through the website in real time. Based on the evaluation from the user side, this system provides ease of monitoring vehicle conditions because it can be accessed via the internet using various kinds of devices.

关键词： OBD-II Blackbox Sstem Logging ECU

来源：评论

学校读者我要写书评

暂无评论

SIBI Sign Language Recognition Using Convolutional Neural Network Combined with Transfer Learning and non-trainable Parameters

引用

Procedia computer science 2021年 179卷 72-80页

作者： Suharjito Narada Thiracitta Herman Gunawan Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480

Sign Language Recognition (SLR) is a complex classification problem to be solved. Every language has their own syntax and grammar. New model combination and dataset is required to developed new SLR system for different syntax and grammar. In this study, we implemented a Convolutional Neural Network (CNN) model which is Inflated 3D model combined with transfer learning method from ImageNet and Kinectic dataset to overcome small dataset problems. There is no public dataset available for SIBI Dataset. Therefore, we collected the dataset by our-self using a mobile phone camera with the following specification. Samsung Galaxy S6 Camera, 16-megapixel Sony Exmore RS IMX240 sensor. The camera is in static position. We used 200 videos as our dataset with 10 words (classes) and 2 signers. We split the dataset into 3 parts (training, validation, testing). After several training and testing with 5 different froze layer combination. The highest validation accuracy was 100% and the highest testing accuracy is 97.50%. The best result was obtained by using a model with the most froze inception module.

关键词： Sign Language Convolutional Neural Network Transfer Learning Inflated 3D Model

来源：评论

学校读者我要写书评

暂无评论

Drone Application Model for Image Acquisition of Plantation Areas and Oil Palm Trees Counting 7

Drone Application Model for Image Acquisition of Plantation ...

引用

7th International Conference on Information Management and Technology, ICIMTech 2022

作者： Sastrohartono, Hermantoro Suryotomo, Andiko Putro Saifullah, Shoffan Suparyanto, Teddy Perbangsa, Anzaludin Samsinga Pardamean, Bens Instiper Yogyakarta Faculty of Agricultural Technology Department of Agricultural Engineering Yogyakarta55281 Indonesia Universitas Pembangunan Nasional Veteran Yogyakarta Department of Informatics Yogyakarta55283 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

The area of oil palm plantations in Indonesia increased by 7% from 14 million ha in 2017 to 15 million ha in 2021. The vast land requires the support of effective and efficient management techniques to maintain sustainable productivity. The high-performance computing technologies, Internet of Things (IoT), Big Data, Artificial Intelligence, spatial modeling, and drones are the answers to these needs. This study aims to design an application that can obtain plantation image data and analyze the calculation of the number of oil palm trees. The image of oil palm plantations is obtained from processing photo data from drones through a mosaic and composite process. This study also employed Scrum and UML as a system model development method. The image of the oil palm plantation area is used to build a tree counting model using the Viola-Jones algorithm. The oil palm tree count information generated by this system can then be used by management for fertilizing, harvesting, and monitoring the condition of oil palm trees. © 2022 IEEE.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

BERT-based Topic Modeling Approach for Malaria Research Publication

BERT-based Topic Modeling Approach for Malaria Research Publ...

引用

International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Alam Ahmad Hidayat Rudi Nirwantono Arif Budiarto Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665473286

Malaria is a communicable disease with half of the global population at risk due to its high morbidity and mortality rates. A massive number of studies are dedicated to malaria research, so it plays a key role in formulating the proper prevention strategy and effective malaria treatment. With the overwhelming number of updated publications in the field, an unsupervised text mining approach such as topic modeling may provide an alternative method for the malaria researcher to keep pace with new insights. In this work, we collect metadata of malaria publications from the PubMed database to perform BERT-based topic modeling to find well-defined topics regarding malaria research. The method is largely based on the popular BERTopic pipeline. We compare the performance of three different language models to generate document embeddings from the data. The dimension reduction and the density-based clustering algorithm are used to cluster the embeddings. The topic representation is computed based on the semantic similarity of the class TF-IDF representation. The substance of the resulting topics is then manually annotated based on the top words of each topic. We demonstrate that by merging initial topics into larger topics using hierarchical clustering and manual content-based examination, the evaluated coherence measure can be further improved, thus enhancing the topic's interpretability. Our modeling result is able to extract ten major topics recurring in the malaria research publication published from 2017–2022. The result provides preliminary insight to understand the dynamics and patterns of malaria research over the years

关键词： Text mining Heuristic algorithms Multimedia systems Time series analysis Sociology Semantics Pipelines

来源：评论

学校读者我要写书评

暂无评论

Trends in Research Publication Topics Related to Artificial Intelligence for Medicine in Medical Education: A Bibliometric Analysis

Trends in Research Publication Topics Related to Artificial ...

引用

International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Fairuz Iqbal Maulana Dian Lestari Puput Dani Prasetyo Adi Agung Purnomo Mufidah Nur Amalia Miftahul Hamim Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Medicine Airlangga University Surabaya 60132 Indonesia Surabaya Indonesia Research Center for Telecommunication National Research and Innovation Agency (BRIN) Bandung Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia Digital Language Learning Center Computer Science Department Faculty of Humanities Bina Nusantara University Jakarta Indonesia Entrepreneurship Business Creation BINUS Business School Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350378573

ISBN: (纸本)9798350378580

This bibliometric analysis aims to explore the trends in research publication topics related to Artificial Intelligence (AI) for medicine in medical education over the last five years (2019-2023). By synthesizing data from a variety of scholarly articles, this study seeks to identify key themes, emerging areas of interest, and research trends within this specific domain. The research question focuses on understanding the evolution of research topics in AI for medicine in medical education, while the objective is to conduct a comprehensive analysis using bibliometric techniques. Data selection from the Scopus database yielded a total of 389 documents from 290 sources. There are 1889 Authors, with author collaboration points on Co-Authors per Doc of 5.11. Regarding the quantity of published documents, the USA, China, and Canada have the highest documents. The software employed for bibliometric analysis were R and VOSviewer. By leveraging bibliometric analysis, this research aims to address the existing gap in the literature and provide valuable insights for researchers, educators, and practitioners interested in AI applications in medical education. The present solution exploration will offer recommendations for future research directions and priorities within the field, contributing to the advancement of knowledge and practice in the integration of AI technologies in medical education.

关键词： Seminars Industries Databases Education Bibliometrics Medical services Market research

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：