Implementing green retrofitting can save 50–90% of energy use in buildings built worldwide. Government policies in several developed countries have begun to increase the implementation of green retrofitting buildings in those countries, which must rise by up to 2.5% of the lifespan of buildings by 2030. By 2050, it is hoped that more than 85% of all buildings will have been retrofitted. The high costs of implementing green retrofitting amounting to 20% of the total initial construction costs, as well as the uncertainty of costs due to cost overruns are one of the main problems in achieving the implementation target in 2050. Therefore, increasing the accuracy of the costs of implementing green retrofitting is the best solution to overcome this. This research is limited to analyzing the factors that influence increasing the accuracy of green retrofitting costs based on WBS, BIM, and Information Systems. The results show that there are 10 factors affecting the cost accuracy of retrofitting or customizing high-rise office buildings, namely Energy Use Efficiency, Water Use Efficiency, Use of Environmentally Friendly Materials, Maintenance of Green Building Performance during the Use Period, Initial Survey, Project Information Documents, Cost Estimation Process, Resources, Legal, and Quantity Extraction applied. These factors are shown to increase the accuracy of green retrofitting costs.

Indonesia has ratified United Nations Convention on the Law of the Sea 1982 (UNCLOS 1982) through Law No. 17 of 1985 concerning the ratification of the 1982 Law of the Sea Convention, thus binding Indonesia to the rights and obligations to implement the provisions of the 1982 convention, including the establishment of the three Northern-Southern Indonesia’s Archipelagic Sea Lane (ALKI). The existence of the three ALKI routes, including ALKI II, has led to various potential threats. These violations not only cause material losses but, if left unchecked and unresolved, can also affect maritime security stability, both nationally and regionally. The maritime security and resilience challenges in ALKI II have increased with the relocation of the capital, which has become the center of gravity, to East Kalimantan. The research in this article aims to identify and analyze the factors influencing the success of maritime security and resilience strategies in ALKI II. The factors used in this research include conceptual components, physical components, moral components, command and control center capabilities, operational effectiveness, command and control effectiveness, and the moderating variables of resource multiplier management and risk management to achieve maritime security and resilience. This study employed a mixed-method research approach. The factors are modeled using Structural Equation Modeling (SEM) with WarpPLS 8.0 software. Qualitative data analysis used the Soft System Methodology (SSM). The results of the study indicate that the aforementioned factors significantly influence the success of achieving maritime security and resilience in ALKI II.

This research explores the relationship between the independent variables (need for achievement, risk-taking, family support, economic factors, and the dependent variable of women’s enterprises’ success) and examines the moderating influence of socio-cultural factors. A survey-based methodology was adopted. One hundred sixty-nine small and medium-sized enterprises (SMEs) in the Palestinian West Bank were surveyed using structured questionnaires. Structural equation modeling (SEM) was conducted by using the Smart-PLS program. The results indicate that women entrepreneurs’ success in SMEs is positively and significantly impacted by the need for achievement as an internal factor and economic factors and family support as external factors. Furthermore, sociocultural factors did not show any significant moderating influence. By gaining knowledge about the relationship between internal and external factors and the success of women-owned SMEs, this study adds to the body of literature already in existence. These factors can be considered in the success of these enterprises, particularly in an environment full of political and economic fluctuations. Furthermore, the research is said to be the first of its type in Palestine, particularly concerning SMEs run by women. It also supports entrepreneurs by providing them with resources that might aid in the growth and success of their businesses.

This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.

This research presents a novel approach utilizing a self-enhanced chimp optimization algorithm (COA) for feature selection in crowdfunding success prediction models, which offers significant improvements over existing methods. By focusing on reducing feature redundancy and improving prediction accuracy, this study introduces an innovative technique that enhances the efficiency of machine learning models used in crowdfunding. The results from this study could have a meaningful impact on how crowdfunding campaigns are designed and evaluated, offering new strategies for creators and investors to increase the likelihood of campaign success in a rapidly evolving digital funding landscape.