This research aims to build an appropriate leadership model for regional heads in mitigating disasters due to climate change that is occurring in Papua. Papua Island is one of the islands that is included in disaster-prone areas, namely earthquakes, flash floods, tidal floods and landslides. This disaster occurred due to Papua’s geological conditions in the form of activity on the Indo-Australian plate (southern part) and the Pacific plate (north-eastern part). Exploitation of nature carried out by companies and communities themselves in a particular area has an impact on the balance of the natural ecosystem. So far, disaster management has only focused on emergency response. Aid movements coordinated by ordinary people also focus more on raising aid for emergency situations. In fact, comprehensive disaster management includes before, during and after a disaster occurs. So a combination of leadership styles is needed that must be carried out at each phase of a disaster so that the right model can be produced. The results of this research found that the leadership model of regional heads in mitigating climate change in Papua is in accordance with the disaster management cycle with leadership styles, and traditional Papuan leadership styles. This combination is called a collaborative leadership model for disaster management in Papua. It is hoped that by implementing this model, climate change disaster mitigation can be effective.

The financial services industry is experiencing a swift adoption of artificial intelligence (AI) and machine learning for a variety of applications. These technologies can be employed by both public and private sector entities to ensure adherence to regulatory requirements, monitor activities, evaluate data accuracy, and identify instances of fraudulent behavior. The utilization of artificial intelligence (AI) and machine learning (ML) has the potential to provide novel and unforeseen manifestations of interconnectivity within financial markets and institutions. This can be represented by the adoption of previously disparate data sources by diverse institutions. The researchers employed convenience sampling as the sampling method. The form was filled out over the period spanning from July 2023 to February 2024, and it was designed to be both anonymous and accessible through online and offline platforms. To assess the reliability and validity of the measurement scales and evaluate the structural model, we employed Partial Least Squares (PLS) for model validation. Specifically, we have used the software package Smart-PLS 3 with a bootstrapping of 5000 samples to estimate the significance of the parameters. The results indicate a positive and direct connection between artificial intelligence (AI) and either financial services or financial institutions. On the contrary, machine learning (ML) exhibits a strong and positive association among financial services and financial institutions. Similarly, there exists a positive and direct connection between AI and investors, as well as between ML and investors.

Electrical energy is known as an essential part of our day-to-day lives. Renewable energy resources can be regenerated through the natural method within a reasonably short time and can be used to bridge the gap in extended power outages. Achieving more renewable energy (RE) than the low levels typically found in today’s energy supply network will entail continuous additional integration efforts into the future. This study examined the impacts of integrating renewable energy on the power quality of transmission networks. This work considered majorly two prominent renewable technologies (solar photovoltaic and wind energy). To examine the effects, IEEE 9-bus (a transmission network) was used. The transmission network and renewable sources (solar photovoltaic and wind energy technologies) were modelled with MATLAB/SIMULINK^®. The Newton-Raphson iteration method of solution was employed for the solution of the load flow owing to its fast convergence and simplicity. The effects of its integration on the quality of the power supply, especially the voltage profile and harmonic content, were determined. It was discovered that the optimal location, where the voltage profile is improved and harmonic distortion is minimal, was at Bus 8 for the wind energy and then Bus 5 for the solar photovoltaic source.

As a key factor in the macroeconomic process, the interaction between public confidence and the commodity market, especially its impact on commodity facilitation returns and macroeconomic linkages, is worth exploring in depth. This study adopts the TVP-SV-VAR model to analyze the causal linkages, dynamic characteristics, and mechanisms of the interaction, and reveals the following core findings: (1) The economic background and information shocks contribute to the variations in the effects and orientations of the economic variables, which highlight the time-varying nature of the economic interactions. (2) Consumer and investor confidence exert heterogeneous influence on the macroeconomy, and their different responses to the negative effect of interest rates and convenience gains are particularly significant in the post-crisis recovery period. (3) In the short-term perspective, the influence of public confidence on monetary policy and inflation exceeds that in the medium and long term, highlighting the immediate sensitivity of individual economic behavior. (4) Since 2015, accommodative monetary policy has accelerated market capital flows, delaying the interaction between confidence indices and inflation, revealing policy time lag effects. (5) Convenience gains exhibit complex time-varying interactions with key economic parameters (interest rates, commodity prices, and inflation), with 2011 and 2014 displaying particular patterns, mapping differences between short- and long-term mechanisms, respectively. The study highlights the central role of consumer and investor confidence in the precise tailoring of macroeconomic policies, providing a scientific basis for policy forecasting and economic regulation, and contributing to economic stability. Meanwhile, the dynamic evolution of consumer confidence deepens market trend foresight, enhances the precision of market participants’ decision-making, and reinforces the resilience and predictability of economic operations.

This study investigated the use of digital story strategy in teaching Islamic education on achievement and how it affects the development of moral thinking. The quasi-experimental design was implemented as a methodology and the sample included of (60) students from the fourth grade from Abdul Rahman bin Awf School in Abha. The results showed that there are statistically significant differences at the significance level (α ≤ 0.05) between the average responses of students in the two groups in the test. The experimental group performed better than the control group. The findings also showed that there are statistically significant differences at the significance level (α ≤ 0.05) between the average responses of students in the two groups (experimental and control) in the moral thinking scale and favour of the experimental group.

The increasing use of social media has played a prominent role in shaping opinions and forming attitudes, especially among university students. They use them increasingly to transfer information, exchange data, and disseminate topics among students and all members of society. Therefore, this study aims to examine these networks and their role in public life, especially in shaping public opinion among university students. The study adopted a descriptive survey approach to achieve its objectives. The study was conducted on a sample of undergraduate students from four Jordanian universities, totaling 832 participants selected through purposive sampling and using the equal distribution method according to variables (gender, university, specialization). The study relied on a questionnaire as a method of data collection and filling out the data from the respondents in the questionnaire. The study found that social media plays a significant role in shaping opinions, beliefs, and ideas, and that its role is unparalleled. Also, the study showed that social media had a significant impact on shaping public opinion in Jordan among university students who use social media extensively and exchange opinions, ideas, and information, contributing to shaping a series of opinions among young people and contributing to their adoption of new ideas or changing their old ones through the dialogue facilitated by these networks, as users exchange and adopt ideas, contributing to shaping a public opinion on an issue. These findings underscore the importance of understanding and leveraging social media and online platforms to effectively communicate with and engage students.