This study thoroughly examined the use of different machine learning models to predict financial distress in Indonesian companies by utilizing the Financial Ratio dataset collected from the Indonesia Stock Exchange (IDX), which includes financial indicators from various companies across multiple industries spanning a decade. By partitioning the data into training and test sets and utilizing SMOTE and RUS approaches, the issue of class imbalances was effectively managed, guaranteeing the dependability and impartiality of the model’s training and assessment. Creating first models was crucial in establishing a benchmark for performance measurements. Various models, including Decision Trees, XGBoost, Random Forest, LSTM, and Support Vector Machine (SVM) were assessed. The ensemble models, including XGBoost and Random Forest, showed better performance when combined with SMOTE. The findings of this research validate the efficacy of ensemble methods in forecasting financial distress. Specifically, the XGBClassifier and Random Forest Classifier demonstrate dependable and resilient performance. The feature importance analysis revealed the significance of financial indicators. Interest_coverage and operating_margin, for instance, were crucial for the predictive capabilities of the models. Both companies and regulators can utilize the findings of this investigation. To forecast financial distress, the XGB classifier and the Random Forest classifier could be employed. In addition, it is important for them to take into account the interest coverage ratio and operating margin ratio, as these finansial ratios play a critical role in assessing their performance. The findings of this research confirm the effectiveness of ensemble methods in financial distress prediction. The XGBClassifier and RandomForestClassifier demonstrate reliable and robust performance. Feature importance analysis highlights the significance of financial indicators, such as interest coverage ratio and operating margin ratio, which are crucial to the predictive ability of the models. These findings can be utilized by companies and regulators to predict financial distress.

In developing countries, urban mobility is a significant challenge due to convergence of population growth and the economic attraction of urban centers. This convergence of factors has resulted in an increase in the demand for transport services, affecting existing infrastructure and requiring the development of sustainable mobility solutions. In order to tackle this challenge, it is necessary to create optimal services that promote sustainable urban mobility. The main objective of this research is to develop and validate a comprehensive methodology framework for assessing and selecting the most sustainable and environmentally responsible urban mobility services for decision makers in developing countries. By integrating fuzzy multi-criteria decision-making techniques, the study aims to address the inherent complexity and uncertainty of urban mobility planning and provide a robust tool for optimizing transportation solutions for rapid urbanization. The proposed methodology combines three-dimensional fuzzy methods of type-1, including AHP, TOPSIS and PROMETHEE, using the Borda method to adapt subjectivity, uncertainty, and incomplete judgments. The results show the advantages of using integrated methods in the sustainable selection of urban mobility systems. A sensitivity analysis is also performed to validate the robustness of the model and to provide insights into the reliability and stability of the evaluation model. This study contributes to inform decision-making, improves policies and urban mobility infrastructure, promotes sustainable decisions, and meets the specific needs of developing countries.

Adopting electric vehicles (E.V.) is crucial for promoting sustainable mobility in metropolitan areas such as Medan, Indonesia. To achieve this, it is essential to comprehend the factors that influence E.V. adoption, with a particular focus on the impact of media. This study examines the adoption of electric vehicles in Medan and evaluates the influence of the media on the public’s perception and policy decisions. Opinions, concerns, and recommendations surrounding electric vehicles were examined through surveys and interviews with 35 stakeholders, including students, lawmakers, industry experts, business owners, and media professionals. The findings indicate a strong knowledge and favorable perception of electric vehicles in Medan. However, there are worries regarding the expenses associated with E.V.s and the availability of charging infrastructure. Notably, 60% of the respondents identified media as their primary source of information, highlighting its significant influence. Encouraging cooperation between media, professionals, and stakeholders is advisable to achieve accurate and balanced reporting. This can be done by employing techniques like showcasing success stories and emphasizing the environmental advantages to encourage acceptance and implementation. This study provides valuable insights into improving the adoption of electric vehicles in Medan. It emphasizes the significance of implementing effective media strategies and supportive policies to achieve sustainable transportation solutions.

The consumption of dietary supplements among the elderly is on the rise. Despite the potential benefits, a comprehensive understanding of the decision-making processes leading to the consumption is lacking. This study explores the conditions influencing the decision-making and behavioral patterns of older adults related to dietary supplement consumption. Using a qualitative approach, in-depth interviews were conducted with 21 elderly participants from a seniors’ club in Bangkok, Thailand, who had consistently consumed dietary supplements for at least one year. The behavior was classified into five primary categories: enduring use of identical dietary supplements, insufficient regard for health compatibility, replacing medications with supplements, not verifying before consumption, and opting for supplements over medical treatments. These patterns are aligned with the core constructs of the Theory of Planned Behavior (attitude, subjective norm, and perceived behavioral control). Many individuals perceive supplements as pivotal health investments, while others view them as a direct route to robust health. Trusted advice from friends and television significantly influence their choices, with a prevailing sentiment that dietary supplements are generally safe. The high price tag on supplements is often associated with superior quality. The findings highlight the multifaceted nature of dietary supplement consumption decisions among the Thai elderly, suggesting the need for interventions to promote safer and more informed choices.