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7th International Conference on New Media Studies, CONMEDIA 2023

作者： Fernando, Erick Hidayat, Desman Pengaribuan, Christian Haposan Prabowo, Yulius Denny Universitas Multimedia Nusantara Faculty of Engineering and Informatics Department of Information System Tangerang Indonesia Bina Nusantara University Binus Entrepreneurship Center Management Department Jakarta11480 Indonesia Sampoerna University Management Study Program Faculty of Business Jakarta12780 Indonesia Bina Nusantara University Binus Online Learning Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307504

Along with technological improvements, online shopping is currently developing quickly. Online shops started by selling electronics, clothing, food, and home appliances and continue to evolve, selling various things. Currently, digital marketing has a novel technique, namely live shopping, where sellers can present, promote and offer their products directly through live streaming on social media and e-commerce platforms. This research will focus on gaining insight into the factors influencing customers to watch and purchase through live streaming. This research is an early-stage study of exploring and searching for research models. The study used a literature review approach by reviewing similar previous research articles. Several variable components were used in this study. The findings of the factors include visibility capacity, meta-vocation capacity, purchase orientation capacity, social presence, price, perceived product quality, perceived enjoyment, purchase orientation, perceived usefulness, and intention to buy. These factors were tested and proved to be valid with Cronbach's Alpha value being more than 0.5 and reliable with the value of the loading factor a greater than 0.6. Criteria The factors of the findings for further analysis of the relationship between factors and other variables. © 2023 IEEE.

关键词： Domestic appliances

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Enhancing Performance of 3D Point Completion Network using Consistency Loss

arXiv

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arXiv 2024年

作者： Wijaya, Kevin Tirta Goenawan, Christofel Rio Kong, Seung-Hyun Computer Graphics Department Max Planck Institute for Informatics Saarbrücken66123 Germany Robotics Master Program KAIST Daejeon34051 Korea Republic of CCS Graduate School of Mobility KAIST Daejeon34051 Korea Republic of

Point cloud completion networks are conventionally trained to minimize the disparities between the completed point cloud and the ground-truth counterpart. However, an incomplete object-level point cloud can have multiple valid completion solutions when it is examined in isolation. This one-to-many mapping issue can cause contradictory supervision signals to the network because the loss function may produce different values for identical input-output pairs of the network. In many cases, this issue could adversely affect the network optimization process. In this work, we propose to enhance the conventional learning objective using a novel completion consistency loss to mitigate the one-to-many mapping problem. Specifically, the proposed consistency loss ensure that a point cloud completion network generates a coherent completion solution for incomplete objects originating from the same source point cloud. Experimental results across multiple well-established datasets and benchmarks demonstrated the proposed completion consistency loss have excellent capability to enhance the completion performance of various existing networks without any modification to the design of the networks. The proposed consistency loss enhances the performance of the point completion network without affecting the inference speed, thereby increasing the accuracy of point cloud completion. Notably, a state-of-the-art point completion network trained with the proposed consistency loss can achieve state-of-the-art accuracy on the challenging new MVP dataset. The code and result of experiment various point completion models using proposed consistency loss will be available at: https://***/kaist-avelab/ConsistencyLoss . © 2024, CC BY.

关键词： Cloud platforms

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Student's skills competency test prediction using c4.5 algorithm 7

Student's skills competency test prediction using c4.5 algor...

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7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019

作者： Enri, Ultach Jaman, Jajam Haerul Ananda, Muhammad Rizky Informatics Engineering Program Faculty of Computer Science Universitas Singaperbangsa Karawang Indonesia

ISBN: (纸本)9781631902567

Competency Skills (UKK) is part of government intervention in ensuring the quality of education in the Secondary Vocational School aims to measure the achievement of a certain level of competency in students' appropriate competency skills. The purpose of the research is to find out how competent the students' in their vocation as well as new strategies for educators in providing more effective learning by using C4.5 algorithm combining with feature selection. Overall the results of the validation of the model experiments that have the best influence are supplied with a set of test accuracy values of 96.875%, and 13 optimal attributes are selected. Therefore, in this study, the C4.5 algorithm with feature selection can provide good and effective results. © 2020 EAI.

关键词： Students

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Detect Areas of Upward and Downward Fluctuations in Bitcoin Prices Using Patterned Datasets

Detect Areas of Upward and Downward Fluctuations in Bitcoin ...

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Information Technology International Seminar (ITIS)

作者： Rizky Parlika Mustafid Basuki Rahmat Department of Doctoral Program of Information System Pascasarjana School Diponegoro University Semarang Indonesia Department of Informatics Faculty of Computer Science University of Pembangunan Nasional “Veteran” JawaTimur Surabaya Indonesia

Many researchers have proposed various theories and techniques to estimate the value of Bitcoin. However, there is still a great opportunity to suggest a new approach to Bitcoin forecasting. This research will examine the concept of forming a patterned dataset to prove the hypothesis regarding the start of a bitcoin price fluctuation until the end of the fluctuation using patterned dataset pairs in conditions of price decline (moon) and in conditions of price decline (crash). Patterned datasets were initially built from data on the movement of all cryptocurrency assets on a digital cryptocurrency trading market. The Patterned Dataset is programmed based on the response of all crypto assets to changes in the price of bitcoin over time. Patterned datasets are better able to describe the conditions of the digital cryptocurrency market, along with patterns of potential increases and decreases in Bitcoin prices in particular and cryptocurrencies in general. To deepen the observations, resampling of the patterned dataset was carried out with a 4-hour timeframe using the mean, median, min, max, and sum filter functions on pairs of crash and moon conditions per month. The results show that filter functions other than sum, namely mean, median, min, and max, provide markings of fluctuation area patterns that are easier to recognize. Two hypotheses related to fluctuations were also successfully proven in this research.

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Truth or Fiction: Multimodal Learning Applied to Earnings Calls

Truth or Fiction: Multimodal Learning Applied to Earnings Ca...

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IEEE International Conference on Big Data

作者： Jamshed Kaikaus Jessen L. Hobson Robert J. Brunner Informatics Program University of Illinois Urbana-Champaign Urbana Illinois Department of Accountancy University of Illinois Urbana-Champaign Urbana Illinois

ISBN: (纸本)9781665480468

A significant amount of resources have been used in both academia and industry to study the impact of financial text on company perception and performance. In order to mitigate potential adverse outcomes, companies have begun to regulate word usage based on perceived sentiment, making conventional text-based analysis less reliable. To address this, we present a multimodal bidirectional Long Short-Term Memory (LSTM) framework augmented with a cross-attention fusion mechanism trained on audio and text data obtained from quarterly earnings conferences calls. The framework is applied to two tasks: financial restatement prediction and market movement prediction. We compare the proposed model against several baseline methods and find that while it does not achieve superior performance, our results show that utilizing multimodal data leads to a substantial increase in model accuracy for restatement prediction. Furthermore, we gain insight on the effectiveness of semantic-and emotion-related features towards these tasks.

关键词： Industries Semantics Companies Predictive models Big Data Feature extraction Data models

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Assessing AI Explainability: A Usability Study Using a Novel Framework Involving Clinicians

arXiv

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arXiv 2025年

作者： Kibria, Mohammad Golam Kucirka, Lauren Mostafa, Javed Carolina Health Informatics Program University of North Carolina Chapel HillNC United States UNC Maternal Fetal Medicine University of North Carolina Chapel HillNC United States Faculty of Information University of Toronto Toronto Canada

An AI design framework was developed based on three core principles, namely understandability, trust, and usability. The framework was conceptualized by synthesizing evidence from the literature and by consulting with experts. The initial version of the AI Explainability Framework was then validated based on an in-depth expert engagement and review process. For evaluation purposes, an AI-anchored prototype, incorporating novel explainability features, was built and deployed online via Google Cloud Platform. The primary function of the prototype was to predict the postpartum depression risk using analytics models. The development of the prototype was carried out in an iterative fashion, based on a pilot-level formative evaluation, followed by a round of refinement and summative evaluation. In the formative stage, the prototype was evaluated based on an internal pilot usability test involving a small number of clinicians (n=3). The prototype was updated based on the user’s feedback in the formative stage. The System Explainability Scale (SES) metric was developed to measure the individual and interacting influence of the three dimensions of the AI Explainability Framework. For the summative stage, a comprehensive usability test was conducted involving 20 clinicians and the SES metric was used to assess clinicians’ satisfaction with the tool. On a 5-point rating system, the tool received high scores for usability dimension followed by trust and understandability. The average explainability score was 4.56. In terms of understandability, trust and usability, the average score was 4.51, 4.53 and 4.71 respectively. Overall, the 13-item SES metric showed strong internal consistency with Cronbach’s alpha of 0.84 and a positive correlation coefficient (Spearman's rho = 0.81, p © 2025, CC BY-NC-ND.

关键词： Usability engineering

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Scholarship Recipients Prediction Model using k-Nearest Neighbor Algorithm and Synthetic Minority Over-sampling Technique

Scholarship Recipients Prediction Model using k-Nearest Neig...

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IEEE International Conference on System Engineering and Technology

作者： Dede Kurniadi Fitri Nuraeni Nia Abania Leni Fitriani Asri Mulyani Yoga Handoko Agustin Department of Computer Science Institut Teknologi Garut Garut Indonesia Study Program of Informatics Institut Teknologi Garut Garut Indonesia

ISBN: (纸本)9798350319842

This research aims to develop a prediction model for scholarship recipients using the k-Nearest Neighbor (KNN) and Synthetic Minority Over Sampling Technique (SMOTE) algorithms. The method in model development uses the Cross-Industry Standard Process for Data Mining (CRISP-DM) which consists of phases of business understanding, data understanding, data processing, modeling, evaluation, and deployment. The dataset used is the Indonesian Smart College Card (KIP-K) Scholarship data in the real world obtained at one of the universities in Indonesia. The evaluation of the model uses a confusion matrix to calculate the values of accuracy, recall, precision, F1-Score, and AUC. The research results show seven attributes that influence the selection process for prospective scholarship recipients, namely non-academic achievement scores, selection test scores, survey scores, interview scores, economic condition scores, academic achievement, and choice of study programs. While the results of model testing produce the best model performance at a value of k=3 with 90.12% accuracy, 85.57% precision, 96.51% recall, 90.71% F1-score, and 0.957 AUC, which are included in the Excellent Classification category. Based on the test results, the model can be applied to a prediction system for prospective scholarship recipients at higher education institutions to make it more targeted.

关键词： Economics Scholarships Education Predictive models Prediction algorithms Systems engineering and theory Data models

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Performance Comparison of Rabin-Karp Algorithm and Winnowing Algorithm for Document Abstraction Similarity Detection

Performance Comparison of Rabin-Karp Algorithm and Winnowing...

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

作者： Anggit Dwi Hartanto Yoga Pristyanto Andy Saputra Eli Pujastuti Atik Nurmasani Ika Asti Astuti Department of Information System Universitas Amikom Yogyakarta Yogyakarta Indonesia Master Program of Informatics Universitas Amikom Yogyakarta Yogyakarta Country

ISBN: (纸本)9781665473286

Plagiarism is one of the actions that have the potential to occur in the academic environment. A real example is the plagiarism of assignments during the lecture process. One of the efforts to prevent plagiarism is to use a system that has been developed in recent years. However, the price of subscribing to the system for a period is quite high. Therefore, we need a plagiarism detection system that everyone can access for free. In developing the system, of course, modeling must be done. Two popular algorithms are often used to detect word similarity: Rabin-Karp and Winnowing. In this study, a performance comparison was made between Rabin-Karp and Winnowing. Comparisons were made using the same dataset of 30 abstraction data from scientific publications. Based on the research, the performance of the Rabin-Karp algorithm and the Winnowing algorithm is almost as good. However, based on the two evaluation parameters used by the Winnowing algorithm, it produces more similarity scores than Rabin-Karp. The same thing also applies to the evaluation of processing time. Winnowing is slightly longer than Rabin-Karp. With the results of this comparison, it can be concluded that if you want a model sensitive to similarity, then Winnowing is recommended. However, if processing time is the target, it is recommended to use Rabin-Karp. In future research, tuning the parameter values of k or n in the Rabin-Karp and Winnowing algorithms is recommended. In addition, it is also recommended to experiment with another distance scoring.

关键词： Plagiarism Multimedia systems informatics Tuning Testing

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

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

引用

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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Exploring Security Threats by Hardware-Faults in Approximate Arithmetic Computing

Exploring Security Threats by Hardware-Faults in Approximate...

引用

Annual IEEE Northeast Workshop on Circuits and Systems (NEWCAS)

作者： Morgana M. A. Da Rosa Eduardo A. C. Da Costa Rafael I. Soares Sergio Bampi Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil PPGC & PGMICRO - Informatics Institute Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil

Approximate computing (AxC) emerged as a design alternative to boost design efficiency by leveraging the inherent error resiliency of many applications. Recent literature shows attackers could exploit some AxC mechanisms to create new attack surfaces. This work proposes integrity checking and exclusive logic-based methods detect attacks by hardware faults on AxC systems. During ASIC-based synthesis, we investigate the security vulnerabilities of the Approximate Parallel Prefix Adder (AxPPA). We compare the expected output of the designer with the output netlists of ASIC-based synthesis. We propose a verification methodology consisting of a golden model (GM) described in a Simulink model and the DUT represented at the netlist level in a standard cell library after logic synthesis. Experimental results show that the AxPPA has an error range of 1.263 × 10 −5 to 0.0098 concerning the designer’s expected output under ASIC-based synthesis attacks.

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