This study aims to examine the influence of the psychosocial work environment on the proclivity for asset misuse in the context of local government management, with a focus on the perceptions of administrators in Central Sulawesi Province. Employing purposive sampling, a total of 39 government units constituted the study's population, with a final sample size of 114 participants, comprising administrators, officers, and managers. WarpPLS software was employed to analyze the data. The findings reveal a positive relationship between rationalization and the inclination toward asset misuse. Additionally, rationalization exhibits a negative impact on the psychosocial work environment. Finally, the psychosocial work environment demonstrates a negative influence on the propensity for asset abuse. These outcomes suggest that the psychosocial work environment plays a pivotal role in mitigating the inclination for asset misuse within the local government of Central Sulawesi Province. This research sheds light on the significance of fostering a positive psychosocial work environment to enhance decision-making processes and reduce the likelihood of fraudulent activities in the management of government assets. Understanding these dynamics is crucial for the development of strategies to promote ethical and responsible asset management in local government entities.

The dynamics of the conflict in the South China Sea (SCS) have begun to enter a new chapter. Currently, the South China Sea (SCS) is a flashpoint in the Asia Pacific region. This study aims to provide an analysis of the concept of the Revolution in Military Affairs (RMA) strategy by the Indonesian Armed Forces (TNI) toward Competitive Advantage in the South China Sea region. This study employed an analytical approach with a qualitative sequence exploratory method supported by some quantitative data. PEST (Political, Economy, Socio-cultural, Technology) analysis and SWOT analysis methods were used to support the study. Furthermore, this study also utilized an Analytical Hierarchy Process (AHP) method approach to provide strategic value and sensitivity analysis as a strategy scenario analysis toward competitive advantage. Based on the results of the research analysis, a strategy under the development of Indonesian Armed Forces capabilities towards a competitive advantage in the South China Sea was obtained, namely the WO strategy which consists of 6 substrate aspects with eight subfactors, namely the combination of all components and strengths in handling security disturbances in the South China Sea (0.162), increased competence of human resources (0.159); development of integrated defense forces and capabilities (0.147), protection of information systems and state secrets (0.145), development of defense facilities and infrastructure (0.109), increasing the capacity and capability of modernizing intelligence technology (0.093), utilization and capacity building of the national defense industry (0.089), deployment of Indonesian Armed Forces troops in the South China Sea (0.075). This study is expected to contribute to the strategy for handling conflicts in the South China Sea and provide strategic steps in increasing capabilities on competitive advantage.

The complexity of risk management and supply chain optimization in the business context, especially in financial institutions such as banking, highlights several factors that require special attention. In the banking sector, where risk and operational smoothness are crucial, risk management and supply chain optimization play pivotal roles in maintaining stability and competitiveness. The objective of this research is to explore the extent to which the implementation of ERM (Enterprise Risk Management) and SCM (Supply Chain Management) can create a competitive advantage, influence decision-making, and ultimately impact company performance. The research methodology employed is quantitative. Data collection was conducted through the distribution of Likert-scale questionnaires with a score range from 1 to 5. The sample selection process utilized random sampling techniques, involving managers and staff working in State-Owned Enterprises (SOE/BUMN) in Indonesia. The study analyzed 263 samples, with data collected from February 2023 to June 2023. Structural Equation Modeling (SEM) with SmartPLS software facilitated data analysis. The results indicate that ERM significantly influences competitive advantage and decision-making, but it does not directly impact company performance. Similarly, SCM has a significant positive impact on competitive advantage and decision-making but does not directly affect company performance. Competitive advantage, in this study, did not prove to enhance firm performance or act as a mediator connecting ERM and SCM to company performance. However, decision-making significantly influences company performance and serves as a significant mediator in the relationship between ERM and SCM concerning company performance.

This study aims to determine an accurate forecasting model, especially an error rate of around 0, and to examine how the automatic rejection system reacts to stock price as a result of the pandemic. The statistical clustering method is used for the dataset in form of daily observations, while the sample covers the period of cases before and after COVID-19 pandemic from 02 January 2019 to 20 June 2020 at the Trinitan Minerals and Metal Company. Furthermore, the data used in the estimation are the opening and closing price of returns, which are later processed using SAS analysis tools. It is shown that the most appropriate decision-making processes are those proven to be most effective. Therefore, predicting future events based on a suitable time series model will help policymakers and strategists make decisions and develop appropriate strategic plans regarding the stock market. Meanwhile, 98% of the ARIMA (1,1,1) is a forecasting model which can be applied to predict stock prices. The new approach of this study is an integrated autoregressive moving average used as an attempt to accurately predict stock prices during a pandemic.

Vocational education is no longer just an education that prepares its graduates to work or become mediocre workers. Creative thinking skills are the basis of science that is very important for students. This research uses a quantitative approach and the population of this study included 106 Cadets of The School of Aviators in Indonesia. Sampling techniques taken were saturated sampling techniques and the samples were taken as many as 106 cadets. Data analysis techniques used were Structural Equation Model (SEM) with AMOS help (Analysis of Moment Structures) program. The results of this study show that critical thinking has a significant effect on decision making.

This study analyzed the influence of project planning on the business growth of 313 SMEs in the Central Region of Peru (Tarma), evaluating the mediating effect of decision-making. Using a quantitative approach, a hypothetical-deductive method, and a non-experimental, cross-sectional, and explanatory design, data were collected using a Likert-scale questionnaire and processed with SmartPLS 4.0. The measurement model demonstrated optimal internal consistency and psychometric validity, with Cronbach's alpha and composite reliability values greater than 0.90, and a mean variance extracted (AVE) greater than 0.50. Structural equation modeling (PLS-SEM) validated all hypotheses (p ≤ 0.001; t ≥ 1.96). It was demonstrated that strategic planning (β = 0.412), resource and budget management (β = 0.356), and scope and quality (β = 0.438) have a direct and positive impact on decision-making. This, in turn, has a strong influence on business growth (β = 0.621), confirming a significant mediating effect of decision-making. The overall model fit was satisfactory (SRMR = 0.045; R² = 0.385), leading to the conclusion that the analytical professionalization of decision-making flows is a critical factor for the scalability of SMEs.

Forecasting is an integral approach due to its ability to make informed act decisions and develop data-driven strategies. It's also used to make decisions related to current circumstances and predictions on future conditions. An integral part has been developed using visibility analysis for COVID-19 Outbreak, a lesson from Indonesia. The author identified that its topic has limited attention, especially in assessing the forecasting models. The issue comes from predicted results that are questionable or cannot be trusted without applying the visibility analysis in the forecasting model. The visibility analysis is required to assess the model's ability to forecast future events. In conjunction with the issue, this paper introduces the analysis of visibility error with the different concepts during model development for the transmission prevention measures in making the decision. This study applied a statistical approach to assess the visibility error of forecasting performance in determining how long periods of forecasting and deciding for transmission prevention measures COVID-19 pandemics. Also, we developed the visibility error of time-variant using inductive logic. The result indicated that the number of data required to perform forecasting work on the basis of forecasting model specifications. In conclusion, this study has been completed to develop the statistical formula for identifying the largest time horizon in forecasting model N = V + 2. Also, this developed model can assist the stakeholder in forecasting the number of transmission prevention and making the decision in case of COVID-19 pandemic.

The objective of this work was to study the influence of Managerial Empowerment on the enforcement of problem solving and decision-making skills. To test a pertinent set of proposed hypotheses, empirical data were collected from 82 individuals among the administrative employees at Abu Dhabi University via a questionnaire survey. The results assure that the level of administrative empowerment implementation at Abu Dhabi University was average while the elements and dimensions of problem solving and decision-making skills studied were relatively high. At the same time, there was globally a moderate impact of the dimensions of administrative empowerment on enhancing problem solving and decision-making skills among employees of Abu Dhabi University. Taking these results into consideration can be crucial to better understanding the use of empowerment strategy to enhance employees’ managerial skills.

The growing adoption of artificial intelligence (AI) in production systems has revolutionized quality assurance processes. Fault detection capability is a critical enabler of production performance and process variability reduction. This study explores the relationship between AI integration, represented by AI-supported decision-making, real-time processing, fault anticipation, and data integration, and production quality assurance. It also assesses the mediating role of fault detection capability in industrial production environments. A quantitative approach was used to gather data from staff in production, quality assurance, process monitoring, maintenance, and operational control units of industrial companies. Participants included production managers, quality assurance managers, process engineers, maintenance supervisors, data analysts, and operational specialists with experience in production process management and digital technologies. The results show that enhancing AI integration across the four dimensions positively impacts production quality assurance by increasing process visibility, facilitating real-time decisions, anticipating faults, and integrating production data across functional activities. The research also reveals that fault detection capability acts as a key mediator, allowing production units to detect anomalies early, prevent quality issues, and boost the stability of production outcomes. It concludes that AI integration positively impacts production quality assurance both directly and indirectly through fault detection capability, helping industrial organizations achieve higher quality standards, process reliability, and production control.

The objective of this research is to determine the location for the dock and office of naval bases in Padang city of Indonesia. Following this objective, the Regional Government of Padang Mentawai Islands District provides 3 (three) alternative places namely in Semabuk Bay, Siuban Bay, and Semebai Bay for the location of dock and office of Naval Base. For the selection of Mentawai base, the method uses BORDA and PROMETHEE, since the methods can consider alternative evaluation based on factors that are both qualitative and quantitative. Based on the research of BORDA method calculation on 16 naval base selection criteria, it is found that criterion of Sailing Flow maintains the highest weight value that is equal to 10.9% and the lowest criterion weighted value belongs to criterion Political Condition for about 2%. For the results of ranking against the alternative using the Promethee method, the study obtains Semebai Bay as the best location to serve for the location of the base of the Mentawai Naval Base.