Risk Assessment of Neobank in Indonesia: Case Study of Bank Gembira Indonesia

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This research delves into a comprehensive analysis of the risks encountered by Bank Gembira, a notable neobank in Indonesia. Through combining qualitative and quantitative methodologies, this research study identifies and classifies various types of risk, including credit risk, market risk, liquidity risk, and operational risk. In facilitating the prioritization process, the study makes use of Saaty’s Analytic Hierarchy Process (AHP) as instrument. The study highlights the importance of understanding customer behavior in mitigating risks for neobanks and recommends further research on risk assessment in the neobanking sector. The analysis emphasizes the critical role of credit risk and operational risk for Bank Gembira as a neobank. Through AHP calculations, credit default and cyberattacks are identified as the highest priority risks, underscoring the need for robust risk treatment plans to address these high-level risks effectively. Recommendations are proposed to address these risks, such as enhancing credit scoring for P2P lending partners, improving cybersecurity measures, collaborating with regulators, tracking technology updates, partnering with e-commerce platforms, offering promotional programs, developing digital talent programs, and attracting MSMEs customers. Further research on risk assessment in the neobanking sector is suggested to enhance risk management practices and ensure sustainable growth for neobanks like Bank Gembira.

Discerning Digital from Canvas: Investigating Visual Distinction between AI-Generated Art and Actual Art among Far Eastern University’s Institute of Architecture and Fine Arts (IARFA) and Non-IARFA Students

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Artificial Intelligence is one of the current generation’s inventions that has been widely used. It has helped make lives easier, especially regarding appliances and business, and it has also altered various industries, including the arts. However, this development has sparked different perspectives among artists and non-artists. This study aims to evaluate how students, both artists, and non-artists, perceive the differences between real art and artificial intelligence-generated art. For this study, a total of fifty (50) students will be gathered, consisting of twenty-five (25) non-artist students from different courses and twenty-five (25) artist students from the IARFA Institute of Far Eastern University. The participants will receive the questionnaire via Messenger. The results of this study showed that the participants could differentiate actual art from AI-generated art based on their knowledge when evaluating artworks. Additionally, it demonstrates that artist students showed more confidence in determining actual artworks from AI-generated artworks due to their knowledge. While non-artists remain skeptical in determining artworks as they base their perception on how they see art.

Feasibility Analysis of Beef Cattle Farming Business against Climate Change in Sumenep District Indonesia

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The objective of the study was to analyze the feasibility of beef cattle farming to climate change in Sumenep District, East Java Province, Indonesia. The research was conducted at the beef cattle Farm for one month from December to January 2023. The method used in the research is a survey with a quantitative approach while the sampling method is multistage sampling (multi-stage cluster sampling for data collection from a large group of areas with the largest to smallest population) and the method can be combined with other sampling methods namely purposive sampling (deliberate data collection) and data collection methods are interviews, questionnaires, observation, focus group discussions and documentation. The data used is cost data from beef cattle farming businesses with a sample size of 150 respondents. The data analysis used was feasibility analysis, namely R/C ratio, which collected production cost data consisting of variable costs, fixed costs and total revenue. The results showed that beef cattle farming in Sumenep district obtained an R/C ratio value of 0.99 for a population of 2 heads, an R/C ratio of 1.00 for a population of 3 heads, and an R/C ratio of 1.06 for a population of 4 populations. The conclusion is that climate change affects the R/C ratio value of the 2-tailed population which is declared not feasible to run while the 3-tailed and 4-tailed populations are feasible to run and develop.

Examining the Distributional Characteristics of Daily Returns of Nifty 50: Normality Assessment and Implications

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This paper investigates the distributional characteristics of daily returns of the Nifty 50 index, a benchmark index comprising 50 large-cap stocks traded on the National Stock Exchange of India. Utilizing historical data spanning a specified time period, we conduct normality testing to assess the adequacy of the normal distribution assumption underlying many financial models. Our analysis provides insights into the departure from normality. As a result of departure from Normality, it may affect the tail behaviour, and volatility dynamics of Nifty 50 daily returns, offering implications for risk management, option pricing, portfolio management, and market efficiency. By synthesizing empirical findings with theoretical considerations, this research contributes to a deeper understanding of the statistical properties of Nifty 50 daily returns and informs practitioners in finance about the challenges associated with Modeling and analysing stock market data.

The Effect of Non-Performing Loans and Loan to Deposit Ratio on Profitability with Inflation as a Moderating Variable in Banking Companies Listed on Indonesia Stock Exchange Period 2018-2022

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This study was conducted to test and analyze the effect of Non Performing Loan and Loan to Deposit Ratio as independent variables on Profitability as a dependent variable, as well as the ability of inflation to moderate the relationship between the independent variable and the dependent variable. The research method in this study is quantitative research with regression analysis of panel data using Eviews. The object of research in this study is banking companies listed on the Indonesia Stock Exchange for the 2018-2022 period. The sampling technique used purposive sampling and found 175 observations. The results of this study show that Non-Performing Loans have a negative effect on Profitability and Loan to Deposit Ratio has a positive effect on Profitability. Meanwhile, inflation cannot moderate the relationship between Non-Performing Loans and Loan to Deposit Ratio to Profitability.

EFL Teachers’ Beliefs and Practice of Code-Switching: A Case Study at Ba Ria – Vungtau University

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This paper presents the practice, including the forms and functions, and beliefs of code-switching practiced by EFL teachers in classroom instruction in the context of a university in Ba Ria – Vung Tau province. Three instruments will be employed in this research including classroom observation, questionnaires, and semi-structured interviews with the participation of 9 EFL teachers and 59 students. The aims of this research are to (1) investigate the functions and forms of code-switching that teachers employed in their classrooms; (2) investigate how teacher’s beliefs and attitudes toward employing code-switching; (3) research for the similarities, and differences between teacher’s opinion and their actual practice of code-switching in 9 EFL classrooms from a case study at Ba Ria – Vung Tau University (BVU).

Bibliometric Analysis: Research Trends in Creative Thinking Behavior in Learning

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The ability to think outside the box, create something that has never existed before, and apply knowledge and skills creatively and inventively. Effective learning activities require a balance between several aspects, namely cognitive, affective, and psychomotor aspects. Creative thinking behavior is a manifestation of creativity, and creativity refers to the ability to generate new, unique ideas. Related to the importance of behavior on creative thinking, it is necessary to analyze the extent of the development of research on creative thinking behavior. Bibliometric analysis using Publish of Perish (PoP) and VOSviewer for the last 10 years (2014-2023) keyword “creative thinking behavior. The analysis took from the google scholar and scopus databases. Bibliometric analysis is a technique that is realized in 2 categories, namely performance analysis and science mapping. The results of the analysis are stored in a small database used in this study. Since this research only uses Google Scholar and Scopus databases, the research methodology of thinking behavior is also limited. The research results can be expanded by using alternative databases and keyword searches. This study may be useful for future researchers who want to investigate creative thinking behavior.

Measuring the Critical Success Factor of Safety Program in Drilling and Well Intervention Operation at PT. MHK, Ltd.

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The drilling and well intervention division implements various safety initiatives to prevent incidents. Despite its multiple activities, an assessment has yet to be conducted to determine the program’s efficacy. This paper aims to determine the elements that impact the effectiveness of safety program execution in drilling and well intervention operations in MHK, Ltd. The Author conducted measurements utilizing variables related to the critical success factor of the safety program, as outlined in the cross-reference research article. Subsequently, the author introduces a system of incentives in variables quantified as a novelty of this research based on input from subject matter experts. By understanding the variables that influence the efficacy of the safety campaign, the safety campaign initiatives will be more focused on mitigating accidents within the drilling and well intervention divisions. The research was conducted utilizing a quantitative approach, where data was gathered through a questionnaire that employed a Likert scale. The population comprises individuals employed in the Drilling and Well Intervention roles at many locations, including the site, field, barge, rig, and town. The data is further analyzed using the Partial Least Squares Structural Equation Modelling (PLS-SEM) technique, employing the smartPLS4 software. The study findings indicated that three out of five variables examined had a favorable and significant impact on the efficacy of the safety program at DWI MHK, Ltd.: management commitment, reward and punishment, and safety arrangement. We propose strengthening identified elements and addressing weaknesses, including utilizing digitalization and artificial intelligence for safety monitoring.

 

Enhancing Customer Service in Banking with AI: Intent Classification Using Distilbert

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With the increasing demand for efficient and responsive customer service in the banking sector, artificial intelligence offers a promising solution. This paper presents a comparative analysis of artificial intelligence methodologies applied to intent classification within the banking sector customer service domain. Utilizing a comprehensive dataset of banking service inquiries, we evaluate several machine learning approaches, including Naive Bayes, Logistic Regression, Support Vector Machine with Linear Kernel, Random Forest, XGBoost, and the transformer-based DistilBERT model. The models are assessed based on their accuracy, precision, recall, and F1 score metrics. Our findings indicate that DistilBERT, with its distilled architecture, not only outstrips traditional models but also demonstrates exceptional performance with an accuracy and F1 score exceeding 92%. The paper delves into the advantages of employing such an efficient and powerful model in real-time customer service settings, suggesting that DistilBERT offers a substantial enhancement over conventional methods. By providing detailed insights into the model’s capabilities, we underscore the transformative impact of employing advanced AI in the financial industry to elevate customer service standards, streamline operational efficiency, and harness the power of state-of-the-art technology for improved client interactions. The results showcased in this study are indicative of the strides being made in AI applications for financial services and set a benchmark for future exploratory and practical endeavors in the field.