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Risk Management of Bank and FinTech Collaboration: A Phenomenological Research 6

Risk Management of Bank and FinTech Collaboration: A Phenome...

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6th International Conference on Computer and Informatics Engineering, IC2IE 2023

作者： Legowo, Mercurius Broto Sorongan, Fangky Antoneus Subanidja, Steph Institute of Perbanas Study Program of Information System Faculty of Information Technology Jakarta Indonesia Institute of Perbanas Study Program of Accounting Faculty of Economic and Business Jakarta Indonesia Post Graduate School Institute of Perbanas Program of Master of Management Jakarta Indonesia

ISBN: (纸本)9798350345162

Banking and Fintech are encouraged to collaborate to fill each other's deficiencies and further grow the digital economy. This collaboration will create benefits for both banks, Fintech, and customers. However, this collaboration also comes with risks. The Financial Services Authority has stated that several risk phenomena can occur in the collaboration of banks and Fintech. First, no law guarantees the protection and exchange of customer personal data. Second, the risk of customer data leakage. Third, the risk of cyberattacks. The fourth is the risk of outsourcing. This research aims to analyze the risk phenomenon of bank and fintech collaboration through the Enterprise Risk Management Framework approach. This study uses a phenomenological research approach, which is a study to study how individuals subjectively experience and give meaning to the phenomenon. Data analysis based on this phenomenon data uses qualitative methods involving banking and fintech practitioners. The results of this study describe the phenomenon of risks that occur in banking-fintech collaboration, as approached by the Enterprise Risk Management framework. Proper risk management will minimize risks when the Bank collaborates with FinTech. This study hopefully contributes to making brief policy recommendations on bank and fintech collaboration risk management for Indonesian financial regulators. © 2023 IEEE.

关键词： bank collaboration ERM framework fintech risk management

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The Evaluations of Cross-Cultural User Experience for Indonesian E-Marketplace: Facilitating MSME (Micro, Small, and Medium Enterprises) Export to MERCOSUR

The Evaluations of Cross-Cultural User Experience for Indone...

引用

International Conference on information Technology systems and Innovation (ICITSI)

作者： Rizaldi Pratama Tanty Oktavia Information System Management Bina Nusantara Graduate Program Jakarta Indonesia

ISBN: (数字)9798331511470

ISBN: (纸本)9798331511487

This research aims to investigate the cross- cultural impact of User Experience (UX) perceptions between Indonesian users and users from MERCOSUR countries (Argentina, Brazil, Paraguay, and Uruguay) on the Indonesian e-marketplace accessible to Micro, Small, and Medium Enterprises (MSMEs). With the rapid growth of the digital economy and the launch of the Indonesia Mercosur Comprehensive Economic Partnership Agreement (IM-CEPA), this study is relevant to comprehend the potential assistance for Indonesian MSMEs in enhancing the value of exports. The research employs the User Experience Questionnaire Plus (UEQ+) method to assess whether the current UX of the Indonesian e-marketplace is acceptable to users with significantly different cultural backgrounds from Indonesia. Additionally, SmartPLS structural equation modeling is utilized to test hypotheses and examine relationships between UX dimensions and user behaviors. The tool is designed to accommodate cultural differences among users, enabling in- depth cross-cultural research. By exploring perceptions, preferences, and reactions of MERCOSUR users to the Indonesian e-marketplace, this research aims to identify factors influencing user acceptance and satisfaction in a cross-cultural context. The findings of this study are expected to provide strategic insights for designers, e-marketplace developers, and other stakeholders. The research can also contribute to optimizing IM-CEPA by aligning the Indonesian e-marketplace platform with the preferences and expectations of MERCOSUR users, strengthening the competitiveness of Indonesian MSMEs in the international market. By understanding the cross-cultural impact on UX, this research lays the foundation for more effective design improvements and marketing strategies, fostering economic growth and the competitiveness of Indonesian MSMEs on the global stage.

关键词： Technological innovation User experience Mathematical models Cultural differences Stakeholders information technology

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach 7

Minimizing the Number of Stunting Prevalence Using the Eucli...

引用

7th IEEE International Conference of Computer Science and information Technology, ICOSNIKOM 2023

作者： Zarlis, Muhammad Oktavia, Tanty Buaton, Relita Ernawan, Ferda Andrian, Kevin Bina Nusantara University Information System Management Department BINUS Graduate Program - Master of Information System Management Jakarta11480 Indonesia STMIK Kaputama Informatics Engineering Binjai20714 Indonesia Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan26600 Malaysia BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Department of Information Systems Management Jakarta Indonesia

ISBN: (纸本)9798350360752

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city. © 2023 IEEE.

关键词： Classification (of information)

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Examining the impact of attitude, availability, price, and quality of service on broadband Internet customer satisfaction 9

Examining the impact of attitude, availability, price, and q...

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9th IEEE International Conference on Computing, Engineering and Design, ICCED 2023

作者： Arin, Ikrar Adinata Murad, Dina Fitria Warnars, Harco Leslie Hendric Spits Meyliana Bina Nusantara University Information System Department School of Information Systems Computer Science Department BINUS Graduate Program Computer Science Jakarta Indonesia Bina Nusantara University Information Systems Department BINUS Online Learning Jakarta Indonesia Bina Nusantara University Computer Science Department BINUS Graduate Program Computer Science Jakarta Indonesia Bina Nusantara University Information System Department School of Information Systems Jakarta Indonesia

ISBN: (纸本)9798350370126

After the COVID-19 pandemic, broadband internet utilization is predicted to continue to grow and experience a significant increase. The pandemic has changed how people work, study, communicate, shop, and carry out many aspects of daily life. Research reported that since 2018, research on broadband internet has continued to increase until now. This quantitative study examines the impact of the four critical variables on the link between attitude, availability, pricing, and quality of service (QoS) on broadband internet customer satisfaction using the Structural Equation Model approach and the Partial Lease Square technique. Three hundred and sixty-one citizen respondents in DKI Jakarta Province were collected using the snowball sampling method facilitated by Google Forms. At the same time, the COVID-19 post-pandemic was still ongoing in Indonesia. Through rigorous statistical analysis, the results show that customer satisfaction with broadband internet services is influenced by all factors, from attitude towards broadband Internet, broadband Internet availability, broadband Internet price, and service quality. The implications of this research are significant for service providers. They provide actionable insights for developing effective strategies to improve customer satisfaction and increase broadband internet subscriptions. © 2023 IEEE.

关键词： Quality of service

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Assessing the Potential of Robo-Advisors in Transforming Indonesia’s Insurance Sector

Assessing the Potential of Robo-Advisors in Transforming Ind...

引用

International Scientific-Professional Conference on information Technology (IT)

作者： Daniel Yosia Arbi Anderes Gui Information Systems Management Department BINUS Graduate Program-Master of Information System Management Jakarta Indonesia

ISBN: (数字)9798331517649

ISBN: (纸本)9798331517656

This study aims to investigate the adoption of robo-advisors in the Indonesian insurance sector, focusing on key factors influencing their acceptance, such as trust, anxiety, performance expectancy, preference for human advisors, attitude, and perceived privacy. The research employed a quantitative approach using a structural equation modeling (SEM) technique through Partial Least Squares (PLS). Data were collected via a Google Forms survey distributed to 442 valid respondents using purposive sampling, with the study conducted in Jakarta, Indonesia. The findings revealed that performance expectancy, anxiety, preference for human advisors, and perceived privacy significantly impact the intention to use robo-advisors, whereas trust and attitude showed limited influence. The study concludes that while robo-advisors hold potential in enhancing efficiency and personalization, concerns such as user privacy and the need for human interaction remain critical. Insurance companies should prioritize robust data privacy measures and consider hybrid models combining robo-advisors with human advisors to enhance user trust and satisfaction. Implications for practice include fostering user trust through transparent data handling policies and providing educational resources to mitigate technology-related anxiety. Limitations of this research include its focus on respondents in a single geographic region and its reliance on self-reported data, which may introduce biases. Future research should explore the application of robo-advisors in broader insurance markets and examine their long-term impact on user behavior and financial decision-making.

关键词： Surveys Privacy Numerical analysis Anxiety disorders Insurance Focusing Distributed databases Mathematical models Internet information technology

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Evaluation User Experience of Interest in Using Digital Insurance Platforms in Indonesia

Evaluation User Experience of Interest in Using Digital Insu...

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International Conference on Ubiquitous information Management and Communication (IMCOM)

作者： Jessicania Windari Tanty Oktavia Information Systems Management Department BINUS Graduate Program-Master of Information System Management Jakarta Indonesia

ISBN: (数字)9798331507817

ISBN: (纸本)9798331507824

This study looks on the factors that influence 452 Indonesian customers' adoption of digital insurance. The study investigates the impact of psychological, social, and technical aspects on adoption intentions using a modified UTAUT2 model. The results highlight the importance of psychological and social factors over technical ones in influencing the adoption of digital insurance. These factors include perceived benefits, perceived risk, price value, social influence, facilitating conditions, trust, behavioral intention, effort expectancy, and performance expectancy. These findings offer the insurance sector invaluable direction for creating digital products that suit consumer preferences and efficient marketing plans. Purposive sampling was used in the data gathering procedure, and Smart PLS 4 was the statistical tool of choice for structural equation modeling, which was used for hypothesis testing. The results indicate that attitude has a major influence on behavioral intention.

关键词： Insurance Psychology Mathematical models User experience Social factors Data models information management Testing

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Product Backlog Recommendations Using Sentiment Analysis with Topic Modelling and Text Summarization in the XYZ E-Wallet Application

Product Backlog Recommendations Using Sentiment Analysis wit...

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International Scientific-Professional Conference on information Technology (IT)

作者： Giovan Meidy Susanto Tuga Mauritsius Information Systems Management Department BINUS Graduate Program-Master of Information System Management Jakarta Indonesia

ISBN: (数字)9798331517649

ISBN: (纸本)9798331517656

This research investigates sentiment analysis of user reviews for the XYZ e-wallet application on the Google Play Store, which currently holds a low rating of 2.7 out of 5. A preliminary study, including a focus group discussion with key stakeholders, revealed that this rating is primarily due to insufficient consideration of user feedback during the Software Development Life Cycle (SDLC). This study employs word2vec and Long Short-Term Memory (LSTM) models to analyze user sentiments, using a dataset comprising reviews collected between July 1, 2023, and June 30, 2024. The developed sentiment analysis model achieved an accuracy of 91.40%. Subsequently, the model was applied to predict sentiments from new review data spanning July 1, 2024, to July 31, 2024. The results were visualized using BERTopic for topic modeling and BART for text summarization. Insights from these visualizations informed recommendations for application improvement, particularly addressing frequent issues with balance top-ups that fail to update, which were incorporated into the product backlog to enhance user satisfaction. This study is limited to a single sentiment analysis model, topic modeling technique, and summarization method. Future research should explore applying the proposed model to other applications and evaluating alternative algorithms for improved performance.

关键词： Analytical models Sentiment analysis Reviews Online banking Text summarization Data visualization Predictive models Stakeholders Long short term memory Software development management

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Analyzing Twitter Sentiment on Stock Using the Bidirectional Encoder Representations (BERT) Based on the Transformer Model

Analyzing Twitter Sentiment on Stock Using the Bidirectional...

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International Scientific-Professional Conference on information Technology (IT)

作者： Rhisa Adika Putri Tanty Oktavia Information Systems Management Department BINUS Graduate Program-Master of Information System Management Jakarta Indonesia

ISBN: (数字)9798331517649

ISBN: (纸本)9798331517656

This study explores sentiment analysis on Indonesian social media data related to stock investments, focused on GOTO stocks. Using the Knowledge Discovery in Database (KDD) methodology, data was collected from the social media platform X (formerly Twitter) during the period from January 2023 to December 2024, preprocessed, and manually labeled into positive, neutral, and negative categories. A deep learning model, Bidirectional Encoder Representations from Transformers (BERT), was employed to analyze the data. The model demonstrated strong performance, achieving a weighted average precision, recall, and F1-score of 0.95 on the test set, with precision scores of 0.99 for positive sentiments and recall scores of 0.97 for neutral sentiments. However, the F1-score for negative sentiments was comparatively lower at 0.87, indicating an area for improvement. These results highlight the effectiveness of sentiment analysis for monitoring stock market trends and public opinion. However, the study is limited by its reliance on data from a single platform (Twitter) and the relatively small dataset size. Future research should incorporate data from multiple platforms, such as Instagram and Facebook, and explore alternative models alongside BERT to enhance performance and generalizability.

关键词： Sentiment analysis Social networking (online) Databases Blogs Bidirectional control Transformers Knowledge discovery Encoding Data models Investment

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Analysis of Factors Affecting the Adoption of Digital Insurance in Jakarta

Analysis of Factors Affecting the Adoption of Digital Insura...

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International Scientific-Professional Conference on information Technology (IT)

作者： Jessicania Windari Tanty Oktavia Information Systems Management Department BINUS Graduate Program-Master of Information System Management Jakarta Indonesia

ISBN: (数字)9798331517649

ISBN: (纸本)9798331517656

This study related phenomena to the adoption of digital insurance services in Jakarta. Analysis of 403 respondents reveals that several factors have no significant impact on individual behavioral intention to use digital insurance, although facilitating conditions and performance expectations do not have a significant effect on behavioral intention. This research suggests a unique behavior among digital insurance consumers in Jakarta that requires further understanding. Utilizing SmartPLS 4.0 software for Structural Equation Modeling (SEM-PLS) analysis, the study delves beyond the technical aspects of using digital insurance applications. It needs to highlight to consider psychological and social factors such as perceived benefit, perceived risk, and trust when designing the method. This research makes a significant contribution to identifying the factors influencing digital insurance adoption in Jakarta. By using the UTAUT2 model with modification, the study successfully identifies a gap between theoretical expectations and the market in Jakarta. These results open avenues for further research to delve deeper into context-specific factors in different Indonesian big cities. Future study suggests that need for developing more comprehensive models to predict consumer behavior in the context of financial technology adoption. Insurance industry can design more targeted strategies to enhance the penetration of digital insurance service in Indonesia.

关键词： Industries Urban areas Insurance Psychology Predictive models Mathematical models User experience Software Social factors information technology

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Model Predicting Airline Passengers Purchasing Seat Upgrade Ancillaries Products on Indonesian Domestic Routes with Random Forest Machine Learning

Model Predicting Airline Passengers Purchasing Seat Upgrade ...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Anggara Mahardika Ahmad Nurul Fajar Information System Management Department Binus Graduate Program - Master of Information System Management Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

To increase profitability, airlines are starting to focus on generating revenue not only from ticket sales, but also from the sale of ancillary products. The research focuses only on ancillary seat upgrade products and aims to create a Machine Learning (ML) model to predict economy class passengers who are likely to accept a seat upgrade offer to business class based on historical data on seat upgrade offers received by airline passengers in the 2023 period. The challenge faced in developing a Machine Learning Prediction model is that the number of passengers who take the upgrade offer and those who do not take it is very unbalanced. In previous literature, most investigations covered European, United Kingdom, China routes, most of which use hub and spoke route networks, while in this research try to fill this gap, especially for airlines operating in Indonesia that have domestic routes and use a point to point route network model. The background of domestic routes is the object of research because 80% of the routes flown are domestic routes between cities in Indonesia, and the top 10 routes that contribute the most to ancillary seat upgrade sales are also domestic routes. To build the model, the author uses machine learning for classification, which is combined with Feature Engineering, Data Balancing and Data Dimension Reduction Techniques. Based on an empirical analysis of a historical dataset of passengers who upgraded their seats, it was found that the best combination was provided by Random Forest, PCA, and Stratified Sampling to predict Indonesian passengers who would receive a seat upgrade with 95.6% accuracy.

关键词： Dimensionality reduction Atmospheric modeling Urban areas Companies Predictive models Data models Random forests Airline industry Principal component analysis Business

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