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The Role of Online Media to Improve Student Understanding in the Merdeka Belajar Kampus Merdeka program: (Case study at the information systems study program at Universitas Pembangunan Jaya) 7th

The Role of Online Media to Improve Student Understanding in...

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7th International Conference on Intelligent Technologies, ICIT 2022

作者： Siregar, Johannes Hamonangan Purwanto, Edi Tengkulung, Clarissa Katheline Ananto, Iffat Dwi Alpeus, Richard Erlangga, Daffa Nurhata Information Systems Study Program Universitas Pembangunan Jaya Banten South Tangerang Indonesia Management Study Program Universitas Pembangunan Jaya Banten South Tangerang Indonesia

ISBN: (纸本)9789819919116

The Merdeka Belajar Kampus Merdeka program (MBKM) needs to be clearly understood by students to be able to determine the appropriate program activities from what is offered. The purpose of this study was to determine the role of online media in increasing students’ understanding of the MBKM program. The research method used is a descriptive analysis method using quantitative data collection techniques through questionnaires and interviews in discussion group forums to obtain qualitative data. Analysis of the data to determine the information needs of students in understanding the MBKM program. The subjects of this research are students of the information systems study program at Pembangunan Jaya University (SIF UPJ study program) who are active in the Odd Semester of the Academic Year 2021/2022, a total of 221 students. From the results of the questionnaire, it was found that as many as 4% stated that there was a lack of information about the MBKM program so that they did not participate in the MBKM program activities which can cause these students to be less interested in joining the MBKM program. In order to improve understanding of the MBKM program, an online media application design is proposed in this study. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Students

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Digital Transformation in Banking: Behavioral and Technological Factors in Indonesia 29

Digital Transformation in Banking: Behavioral and Technologi...

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29th International Conference on information Technology, IT 2025

作者： Lycaso, Auryns Gui, Anderes Bina Nusantara University School of Information Systems Information Systems Study Program Indonesia

ISBN: (纸本)9798331517649

This study investigates the behavioral and technological factors influencing non-users' intention to adopt digital banking in Indonesia, utilizing the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT). Key constructs analyzed include Perceived Usefulness (PU), Perceived Ease of Use (PEU), Social Influence (SI), Facilitating Conditions (FC), Perceived Risk (PR), Perceived Trust (PT), and Perceived Security (PS). Despite the widespread use of TAM and UTAUT, this research addresses a significant gap by integrating trust-sensitive factors (PR, PT, and PS), which are crucial for understanding adoption in emerging markets. Data from 277 non-users were collected via a structured survey and analyzed using Structural Equation Modeling (SEM). Results reveal that PU, SI, FC, PR, and PS significantly influence Behavioral Intention (BI), while PEU and PT exhibit non-significant effects. This finding reflects a shift in user priorities from usability and generalized trust to tangible factors like security and infrastructure reliability. By refining these established frameworks, this study provides actionable insights for advancing digital banking adoption, particularly in Indonesia and other trust-sensitive emerging markets. Practical recommendations for policymakers and financial institutions focus on enhancing security, improving digital literacy, and bridging infrastructural gaps. © 2025 IEEE.

关键词： behavioral intention digital banking perceived risk security technology acceptance trust

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A Comparative study of Traditional and Deep Learning Models Using Emotional Customer Data in Automotive Sales Forecasting

A Comparative Study of Traditional and Deep Learning Models ...

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2025 International Conference on Advancement in Data Science, E-learning and information System, ICADEIS 2025

作者： Godata, Gempar Bambang Irmawati Universitas Multimedia Nusantara Information Systems Study Program Banten Indonesia

ISBN: (纸本)9798331513320

This study investigates the effectiveness of traditional and deep learning models in predicting automotive sales outcomes using customer acoustic and emotional parameters extracted from sales call recordings. A primary dataset of sales conversations was processed using an internal tool, which converts audio into numerical data based on 11 acoustic features such as pitch, volume, and speech rate. Traditional machine learning models, including AdaBoost, Support Vector Machine (SVM), and Random Forest, were compared with deep learning models like Dense Neural Networks (DNN) and TabNet. The optimized DNN model achieved the highest performance, with an F1-Score of 0.7298, balancing precision and recall effectively. TabNet provided competitive results with an F1-Score of 0.7237, offering additional benefits of feature interpretability through its attention mechanism. These findings suggest that while traditional models, particularly AdaBoost, perform adequately, deep learning models, especially DNN and TabNet, are better equipped to capture the complex, non-linear relationships in acoustic and emotional data. The results provide actionable insights for optimizing sales strategies through data-driven decision-making. It offers a foundation for future advancements in predictive analytics within automotive industries using voicebased datasets. © 2025 IEEE.

关键词： Contrastive Learning

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Detection of Watermarks in Digital Images Using Filter Techniques and Convolutional Neural Networks

Detection of Watermarks in Digital Images Using Filter Techn...

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International IoT, Electronics and Mechatronics Conference, IEMTRONICS 2024

作者： Angelica, Vanessa Irmawati Information Systems Study Program Universitas Multimedia Nusantara Banten Tangerang Indonesia

ISBN: (纸本)9789819747832

The forgery of watermark images poses a significant threat to digital works’ visual integrity and authenticity. This research focuses on developing a method for detecting forged watermark images by comparing the performance of two conventional approaches: the Gabor and the Prewitt filters. In addition, a Convolutional Neural Network (CNN) is employed as a classifier to model complex features that may be challenging to identify using traditional detection methods. The Gabor and Prewitt filters extract texture and edge features from the images. Experiments were conducted on a dataset containing various forged watermark images with different levels of complexity. Performance evaluation results were measured by assessing accuracy during validation and testing, True Positive Rate (TPR), False Negative Rate (FNR), and the ROC–AUC curve. The research findings indicate that the Prewitt filter outperforms the Gabor filter, achieving a testing accuracy of 88.32%, a TPR of 82.94%, an FNR of 17.05%, and an ROC–AUC value of 0.884 for validation accuracy. These results demonstrate the potential of the Prewitt filter and CNN as a practical approach to addressing the challenges of detecting increasingly complex watermark image forgeries. This study contributes to developing watermark image authenticity detection methods by combining conventional approaches with deep learning technology. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Digital Transformation in Banking: Behavioral and Technological Factors in Indonesia

Digital Transformation in Banking: Behavioral and Technologi...

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International Scientific-Professional Conference on information Technology (IT)

作者： Auryns Lycaso Anderes Gui Information Systems Study Program School of Information Systems Bina Nusantara University Indonesia Lecturer Specialist-S3 from Information Systems Study Program School of Information Systems Bina Nusantara University

ISBN: (数字)9798331517649

ISBN: (纸本)9798331517656

This study investigates the behavioral and technological factors influencing non-users’ intention to adopt digital banking in Indonesia, utilizing the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT). Key constructs analyzed include Perceived Usefulness (PU), Perceived Ease of Use (PEU), Social Influence (SI), Facilitating Conditions (FC), Perceived Risk (PR), Perceived Trust (PT), and Perceived Security (PS). Despite the widespread use of TAM and UTAUT, this research addresses a significant gap by integrating trust-sensitive factors (PR, PT, and PS), which are crucial for understanding adoption in emerging markets. Data from 277 non-users were collected via a structured survey and analyzed using Structural Equation Modeling (SEM). Results reveal that PU, SI, FC, PR, and PS significantly influence Behavioral Intention (BI), while PEU and PT exhibit non-significant effects. This finding reflects a shift in user priorities from usability and generalized trust to tangible factors like security and infrastructure reliability. By refining these established frameworks, this study provides actionable insights for advancing digital banking adoption, particularly in Indonesia and other trust-sensitive emerging markets. Practical recommendations for policymakers and financial institutions focus on enhancing security, improving digital literacy, and bridging infrastructural gaps.

关键词： Surveys Technology acceptance model Numerical analysis Refining Banking Mathematical models Security Reliability Usability information technology

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A Comparative study of Traditional and Deep Learning Models Using Emotional Customer Data in Automotive Sales Forecasting

A Comparative Study of Traditional and Deep Learning Models ...

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Advancement in Data Science, E-learning and information systems (ICADEIS), International Conference on

作者： Gempar Bambang Godata Irmawati Information Systems Study Program Universitas Multimedia Nusantara Banten Indonesia

ISBN: (数字)9798331513320

ISBN: (纸本)9798331513337

关键词： Deep learning Support vector machines Neural networks Predictive models Feature extraction Data models Acoustics Numerical models Recording Automotive engineering

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The Effect of E-Commerce Factors on Consumer Purchasing Behavior 28

The Effect of E-Commerce Factors on Consumer Purchasing Beha...

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2024 28th International Conference on information Technology, IT 2024

作者： William Gui, A. Bina Nusantara University Information Systems Study Program School of Information Systems Indonesia Bina Nusantara University Information Systems Study Program School of Information Systems Indonesia

ISBN: (纸本)9798350369618

As the digital landscape evolves, consumer confidence within social environments increasingly shapes their purchasing choices. This shift presents new opportunities for entrepreneurs leveraging social commerce to enhance sales. While previous research focused largely on digital trust elements, like the reliability of user reviews, exploring consumer behavior requires considering various influencing factors. This study seeks to create a dependable structure for internet-based enterprises. Through a Google form circulated across platforms like Telegram, Twitter, Instagram, WhatsApp, and Line between January 1st and January 8th, 2024, a group of 277 participants was collected. Among them, 256 met the eligibility criteria, while 21 did not, and the data collected was later analyzed using SmartPLS 4. The study's outcomes were not quite satisfactory, as 2 hypotheses were rejected on which social support and customers satisfaction have not had a positive impact towards purchasing behavior, while the other 5 have been accepted. Essentially, this study underscores the substantial influence of customer trust in e-commerce reviews and the significance of s-commerce in shaping customer satisfaction and loyalty within marketplaces. © 2024 IEEE.

关键词： Electronic commerce

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Design of Dual Space Inquiry framework for facilitating flexible learning in digital technology era

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International Journal of Educational Research Open 2025年 8卷

作者： Novitra, Fuja Abdullah, Mohd Nor Syahrir Özdemir, Erdogan Riyasni, Selma Emiliannur Festiyed Metra, Pol Department of Physics Faculty of Mathematics and Natural Science Universitas Negeri Padang Indonesia Department of Mathematics and Science Education Faculty of Education University of Malaya Malaysia Vocational School of Health Services Sivas Cumhuriyet University Turkey Information Systems Study Program Faculty of Science and Technology UIN Sulthan Thaha Saifuddin Jambi Indonesia

Mixed learning that offers flexibility is a current requirement. However, the challenge lies in ensuring that these approaches effectively accommodate interactive and practical elements, especially in physics education. This research aims to design a conceptual framework of the Dual Space Inquiry for facilitating flexible learning in basic physics course. An educational design research (EDR) approach was used to develop and validate the Dual Space Inquiry framework comprising three phases: analysis and exploration;design and construction;and evaluation and reflection. This research involved 253 students and 20 experts and practitioners. The findings highlighted the urgency of implementing a mixed learning framework that combines face-to-face and online learning methods in physics education contexts to optimize learning outcomes. These results became the basis for the design of the Dual Space Inquiry Framework which emphasizes flexibility, humanism, and student-centered. Furthermore, the results of expert and practitioner judgment showed that the framework's validity is in the high category (v-values=0.770). Based on the results, it is concluded that an approach that combines online and offline learning with inquiry activities integration in a balanced manner is recommended for optimal learning outcomes for physics education. The Dual Space Inquiry Framework, with its high validity, is a valuable framework for lecturers in physics and other science fields to enhance learning quality and adapt to the digital technology era. © 2024 The Author(s)

关键词： Digital pedagogy Framework ICT Inquiry Teaching strategies

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Factors that Influence College Students in the use of ChatGPT in Indonesia 28

Factors that Influence College Students in the use of ChatGP...

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2024 28th International Conference on information Technology, IT 2024

作者： Silvano, R. Gui, A. Bina Nusantara University Information Systems Study Program School of Information Systems Indonesia

ISBN: (纸本)9798350369618

This research investigates the characteristics that influence Indonesian college students' use of ChatGPT, an AI-powered chatbot. Understanding students' opinions and usage patterns is critical as AI becomes more prevalent in education. This questionnaire data collection was distributed using Google form and filled in by college students who were undergoing their studies. It focuses on three essential factors: trust (TRU), performance (PE), and effort (EE). The students' trust in ChatGPT's data security, credibility, and information correctness is critical. Performance Expectancy assesses how ChatGPT helps with job completion and information quality. The ease of use and user-friendliness of ChatGPT are factors in Effort Expectancy. This questionnaire data processing was processed using the SmartPLS 4 application. The data show that trust has a considerable positive influence on ChatGPT usage, implying that higher trust levels correlate with increasing utilization. Students recognize ChatGPT's usefulness in academic settings, which has a positive impact on usage. The platform's intuitive design and user-friendly interface are crucial reasons in its acceptance, according to Effort Expectancy. The study sheds light on AI adoption in educational settings, emphasizing the importance of trust, performance, and effort anticipation in changing student views toward technology. These findings can be used to influence the development of AI tools in education, emphasizing the importance of safe, efficient, and accessible designs to improve the learning experience. © 2024 IEEE.

关键词： Students

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Mobile Payment Continuance Usage Intention in Indonesia 25

Mobile Payment Continuance Usage Intention in Indonesia

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25th International Conference on information Technology, IT 2021

作者： Seannery, G. Gui, A. Bina Nusantara University Accounting Information Systems Program Indonesia Bina Nusantara University Information Systems Study Program School of Information Systems Indonesia

ISBN: (纸本)9781728191034

Due to the increase in mobile payment user, this study explores the factors influencing continuance usage intention mobile payment in Indonesia. A total of 506 respondents are collected and analyzed using SmartPLS 3. The result revealed that additional values, perceived transaction convenience, and perceived risk are significant factor that positively affect continuance usage intention. However perceived security and trust surprisingly do not affect continuance usage intention of mobile payment in Indonesia. © 2021 IEEE.

关键词： Electronic money

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