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

作者： Rahutomo, Reza Jariyah, Ainun Trinugroho, Joko Pebrianto Pardamean, Bens School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University 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

This study analyzed interactions between Twitter users in conversations regarding Indonesia's state-owned vaccine manufacturer 'Biofarma' in 2021. The primary objective of this study is to identify Key Opinion Leaders (KOL) due to the need of authentic and trustworthy persona in social media. A technique called network centrality was employed in this research alongside four centrality measurements, namely degree of centrality, eigenvector centrality, betweenness centrality, and closeness centrality. Focused on using a reply network interaction dataset, the research discovered several important usernames with different roles that enlivened the conversation and have a potential for social media marketing optimization. © 2022 IEEE.

关键词： Marketing

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A Design of Childhood Stunting Assessment Feature with Agile UX Approach 8

A Design of Childhood Stunting Assessment Feature with Agile...

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8th International HCI and UX Conference in Indonesia, CHIuXiD 2022

作者： Rahutomo, Reza Perbangsa, Anzaludin Samsinga Asadi, Faisal Nirwantono, Rudi Pardamean, Bens Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program-Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665476645

multidisciplinary collaboration between public health, system engineering, and UX is able to generate a solution in healthcare problem like stunting. The principle of Agile UX gathers requirements to generate an application design. Currently, various website and mobile applications are available to be utilized for stunting research. StuntingDB is one of many web-based applications that specialized in stunting data management. The application required several types of users to operate hierarchically. This research focused on Public Health Officers' workflow that require a solution to in the form of assessment module for stunting DBMS by using Agile UX principle. The method collaborates agile team and UX team to solve Public Health Officer's difficulty in changing stunting status at pre-saved child patient's profile. Collaboration of both agile team and UX team successfully proposed an application design that system design. © 2022 IEEE.

关键词： Websites

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Cloud-Based Mixed Reality System in Machinery Vocational School: ICT Blueprint

Cloud-Based Mixed Reality System in Machinery Vocational Sch...

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2022 International Conference on science and Technology, ICOSTECH 2022

作者： Suryodiningrat, Satrio Pradono Gaol, Ford L. Supangkat, Suhono Harso Ranti, Benny Bina Nusantara University Binus Graduate Program Doctor of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Faculty of Computing and Media Computer Science Department Jakarta Indonesia Bina Nusantara University Jakarta Doctor of Computer Science Graduate Program Jakarta Indonesia Smart City and Community Innovation Center Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9781665479851

Education is always the most important part of our lives. To make education make a significant impact on today's learners, teaching and learning must evolve to match with today's learner's profile. Any education including vocational education has an important role in economic development and one of the ways to maximize the contribution of vocational educations is strengthening the link and match with the world of work [1]. As the technology also keeps evolving and it is getting more and more advanced, one technology that has significant traction lately is the mixed reality system and is often used for education purposes. Most big ICT companies like Microsoft, and HTC are racing to develop mixed reality systems to help the teaching and learning process to be more effective and efficient. Where everything is cloud-based, having a cloud-based mixed reality system is just makes sense but will have a great challenge and considered as a big ICT project. One of the ways to make the ICT project successful is to make a blueprint before it is started. The objective of this paper is how to develop an ICT Blueprint for implementing a cloud-based mixed reality system for machinery vocational schools to make the project have a higher success rate. © 2022 IEEE.

关键词： Blueprints

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

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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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Optimized LightGCN for Music Recommendation Satisfaction

Optimized LightGCN for Music Recommendation Satisfaction

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International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Aaron Christian Hansel Adrianus Lunardi Pradana Abba Suganda Girsang Ariadi Nugroho Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

With the large amount of information available on the internet, recommendation tasks have grown to be more crucial than ever. Businesses that store digital media on the internet such as video streaming and music streaming platforms, benefit a lot from recommendation systems. A simple yet powerful recommendation system that can give better recommendation performance is always being sought after. Light Graph Convolution Network (LightGCN) is a simplified version of Graph Convolution Network (GCN) for collaborative filtering in recommendation systems. LightGCN architecture includes only the most essential part of GCN for collaborative filtering that is the neighborhood aggregation, it removes the feature transformation and nonlinear activation because both of them contribute little to no effect to the recommendations. The focus of this research is to optimize LightGCN by tuning the hyperparameters using exhaustive search (grid search). The optimized LightGCN model is able to out-perform LightGCN by more than 140% in music recommendation

关键词： Machine learning algorithms Convolution Collaborative filtering Machine learning Streaming media Media Task analysis

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Identification of Meteorological Parameters Affecting Dengue Hemorrhagic Fever Incidences 4

Identification of Meteorological Parameters Affecting Dengue...

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4th International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2022

作者： Asadi, Faisal Trinugroho, Joko Pebrianto Hidayat, Alam Ahmad Rahutomo, Reza Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information System Department Jakarta11480 Indonesia Binus Graduate Program Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665473279

Tropical disease is one of the infectious diseases that affect Indonesia. Many people die because of tropical diseases, such as dengue hemorrhagic fever (DHF), chikungunya, leprosy, lymphatic, and filariasis. The Indonesian government's lack of public policy is the main problem in treating and preventing tropical diseases. The paper aims to describe the analysis results of the incidence of DHF in Jakarta, Indonesia. The analysis used the DHF incidences data from the Jakarta Health service surveillance office representative and combined it with the meteorological parameters data. The meteorological parameters were collected from the Bureau of Meteorological Climatology and Geophysics (BMKG). The statistical analysis of this research used Pearson's correlation. The results show that the meteorological parameters affecting DHF incidences are temperature, humidity, and wind speed. © 2022 IEEE.

关键词： Correlation methods

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Machine Learning Methods for Predicting the Necessity of Caesareans Section of Childbirth 5

Machine Learning Methods for Predicting the Necessity of Cae...

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5th IEEE International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2021

作者： Sunge, Aswan Supriyadi Heryadi, Yaya Abdurachman, Edi Kartowisatro, Iman H. Bina Nusantara University BINUS Graduate Program- Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Faculty Of Engineering Computer Science Departement - BINUS Graduate Program Computer Science Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9781665401968

In the process of delivery usually the baby comes out of the vagina but under some circumstances a cesarean section is performed. Caesarean section, on the one hand can have short-term and long-term effects for the mother but on the other hand it is a life-saving procedure for both mother and child. The purpose of this study is to predict whether or not a caesarean section is necessary for a pregnant mother using a machine learning classifier model and some features from medical records as input data. In this study, some machine models were explored including Logistic Regression, K-Nearest Neighbor, Random Forest, Decision Tree, Gradient Boosting and Support Vector Machine. The experiment found that Logistic Regression model achieved the highest performance as measured by average accuracy 95%, average precision 86%, average recall 95%, and average F1 86%. © 2021 IEEE.

关键词： Forecasting

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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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Implementation Graph Database Framework for Credit Card Fraud Detection

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Procedia computer science 2023年 227卷 326-335页

作者： Nurrahmi Mauliddiah Suharjito Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480

Credit card use is becoming more and more commonplace every day. Financial organizations and credit card customers lose a lot of money because of complicated illegal transactions. Fraudsters constantly stay on top of new technology to quickly perpetrate fraud against customer transaction patterns. We analyze credit card transaction networks and identify suspicious patterns, such as transactions connected to multiple accounts or unusual transaction patterns, transactions made at unusual times, and to monitor credit card transactions in real-time and quickly identify suspicious transactions. TigerGraph is used to analyze data, display results on a dashboard, and send notifications via email. One meth’\ Vc 1``13-od commonly used in anomaly detection is to compare data values against the standard deviation. In this research, we explain the use of TigerGraph as a platform for anomaly detection above the standard deviation, as well as the use of the Louvain algorithm in finding merchant communities used by fraudsters. The data used in this study comes from Sparkov simulation data obtained from Kaggle. Our results show that by using TigerGraph, we managed to achieve a very high accuracy rate of 99.77%, precision 82.84%, recall 72.38%, and f1-score 77,26% in predicting transaction fraud on Sparkov simulation data. This is much better than the results reported in a paper that uses the supervised machine learning method with the AdaBoost algorithm which achieves the highest accuracy of 77%.

关键词： Credit card fraud detection TigerGraph Dashboard Alert

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UML Design for Decision Support Model in Determining the Sustainability of Online Course Materials

UML Design for Decision Support Model in Determining the Sus...

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International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Erna Fransisca Angela Sihotang Afdhal Kurniawan Ditdit Nugeraha Utama Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

The scenario of online learning is a very urgent need in the world of future knowledge. Since the Corona Virus Disease-19 pandemic, the world economy has started to plummet and caused many adults to lose their jobs. The advantage is the flexibility and rapid development of the internet. In 2020, the number of unemployed increased significantly. This reason makes people strive to improve their ability to meet job requirements by taking online courses. Online courses are a way that people can choose to improve their skills anywhere and anytime. The sustainability of online course material that is offered to the course user and issued by the company will be discussed in this study. The novelty of this research is to obtain a decision support model based on fuzzy logic for determining online courses. The method used is decision-making based on UML and fuzzy logic for the final decision. The fuzzy inference model process begins by determining the decision parameters then using fuzzification with absolute input then refracted with fuzzy criteria, and ends with defuzzification with absolute output. There are two groups of parameters in this study, company profits which consist of 5 parameters and user benefits, which consist of 9 parameters. Once the model is verified and valid, the final decision is useful for users looking for online course and also useful for the decision unit of online course companies in determining the sustainability of online course materials.

关键词： Fuzzy logic Electrical engineering Pandemics Unified modeling language Decision making Companies Sustainable development

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