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检索条件"机构=Study Program in Information Systems"

共 259 条记录，以下是1-10 订阅

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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...

引用

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

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

引用

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

Digital Transformation in Banking: Behavioral and Technologi...

引用

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

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

引用

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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The Security of Mobile Banking in Industrial Revolution 4.0 2

The Security of Mobile Banking in Industrial Revolution 4.0

引用

2nd International Conference on Emerging Trends in information Technology and Engineering, ic-ETITE 2024

作者： Muzakkir, Andi Alkila Aurellia Firjatullah Gui, Anderes School of Information Systems Bina Nusantara University Information Systems Study Program Jakarta Indonesia

ISBN: (纸本)9798350328202

The phenomenon of globalization has had a significant impact on various sectors of society, such as ideology, politics, economics, socio-culture, defense, and security. This influence is particularly notable in the paradigm shift observed in these areas, with a particular emphasis on the role of a 4.0 society has prompted a profound transition across several industrial sectors, as they integrate digital technology and internet networks. Hence, this study employs a methodology for assessing questionnaire readability that incorporates validity and reliability assessments. The questionnaire consists of 24 items, encompassing nine distinct topics: social influence, reward, effort expentancy, facilitating conditions, security, risk and trust. The respondents were asked to provide their responses using a Likert scale ranging from 1 to 5, where 1 represents severe disagreement and 5 represents strong agreement. The findings of this study consisted of a total of 414 participants, with a significant proportion originating from Greater Jakarta, Java, and North Sumatra. The data will be analyzed with statistical software packages such as SPSS and SMART PLS. The objective of this study is to assess the degree of customer satisfaction in relation to the utilization of the mobile banking application, including service quality, information quality, and system quality. This research has the potential to provide valuable theoretical and technological insights, while also making a significant contribution to the literature in the subject of informatics engineering and information systems. It can serve as a valuable reference for future research endeavors. © 2024 IEEE.

关键词： Customer satisfaction

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Analysis of Factors Affecting Behavioral Intention to Use QRIS 2

Analysis of Factors Affecting Behavioral Intention to Use QR...

引用

2nd International Conference on Emerging Trends in information Technology and Engineering, ic-ETITE 2024

作者： Michael, Gregorius Widjaya, William Gui, Anderes School of Information Systems Bina Nusantara University Information Systems Study Program Jakarta Indonesia

ISBN: (纸本)9798350328202

QRIS strives to provide affordable payment options and promote financial inclusion for small and midsize businesses. Adopting the modified Unified Theory of Acceptance and Use of Technology (UTAUT), this research analyzed the factors influencing customers' behavioral intention to utilize QRIS within financial applications and aim to identify the factors within variable that has influence behavioural intention for adopting the QRIS payment method. Data collected from 491 respondents in Indonesia who have used QRIS was processed using SmartPLS 4 with PLS-SEM to examine the relationships between variables that were used to analyze factors influencing customers' behavioral intention toward QRIS. The findings showed that performance expectancy, effort expectancy, and personal innovativeness positively affect attitude towards QRIS. In addition, behavioral intention is also affected by social influence, habit, personal innovativeness, and attitude. The result of this research also provides better understanding and valuable insights for developing strategies to increase QRIS adoption in promoting the cashless society in Indonesia. © 2024 IEEE.

关键词： Electronic money

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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 ...

引用

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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Harnessing Machine Learning for Sentiment Analysis: A Comparative study of Classification Models on Discord User Reviews

Harnessing Machine Learning for Sentiment Analysis: A Compar...

引用

2024 IEEE International Conference on Internet of Things and Intelligence systems, IoTaIS 2024

作者： Indarto, Joseph William Gusti Ketut Edrick, I. Liu, Felix Antonis Madyatmadja, Evaristus Didik Information Systems Study Program School of Information Systems Bina Nusantara University Jakarta11530 Indonesia

ISBN: (纸本)9798331521219

This research conducts a comparative analysis of machine learning models to gauge user sentiment in Google Play Store reviews of Discord over the past year. As Discord broadens its scope beyond gaming to become a versatile communication tool, understanding user emotions is crucial, particularly in dynamic markets like Indonesia. We evaluated the performance of five classification models-Naive Bayes, Support Vector Machine (SVM), Random Forest, Neural Network, and AdaBoost-using metrics like accuracy, precision, recall, and F1 score. Our findings reveal that SVM and Random Forest lead the pack, offering superior accuracy and robustness in sentiment analysis, while Neural Networks also perform well but fall slightly short. Naive Bayes and AdaBoost deliver reliable results but are less efficient. This study uncovers key sentimental trends: positive reviews often praise features and performance, while negative feedback highlights issues with login and verification. Ultimately, our research underscores the critical role of choosing the right model to enhance user experience and inform strategic improvements on platforms like Discord. Future work should explore real-time sentiment analysis to boost user engagement and satisfaction. ©2024 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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Efficiency Comparison of Employee Management Automation Using Selenium and Playwright: A Case study of Technology Consulting Company

Efficiency Comparison of Employee Management Automation Usin...

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2024 International Conference on information Technology systems and Innovation, ICITSI 2024

作者： Apriansah, Muhammad Rio Desanti, Ririn Ikana Universitas Multimedia Nusantara Information Systems Study Program Tangerang Indonesia

ISBN: (纸本)9798331511470

The research employed a case study methodology to investigate a technology consulting company. The company implements an employee management application to facilitate the approval procedure for granting employee benefits. Before approval, the procedure of gathering and analyzing allowance data is conducted. The current procedure requires manual processing of each task individually, with each permission list taking approximately 3 to 5 minutes. This approach is not only time-consuming but also highly prone to errors, leading to inefficiencies and inconsistent outputs that fail to meet the company's standards. An effective solution to this problem is to develop an automated program using Selenium and Playwright, alongside the Python programming language. The program will be created following the agile software development methodology, and its testing will involve both black box testing and User Acceptance Testing (UAT). After successfully developing both automation programs, a detailed comparison was conducted using data from 10 allowance lists. Testing showed that the Selenium automation program completed all operations in 55.03 and 49.25 seconds, while the Playwright program required only 47.14 and 47.71 seconds. These results indicate that the Playwright automation program demonstrates a higher level of efficiency compared to Selenium. © 2024 IEEE.

关键词： Acceptance tests

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