The Agriculture Trading Platform (ATP) represents a significant innovation in the realm of agricultural trade in Malaysia. This web-based platform is designed to address the prevalent inefficiencies and lack of transparency in the current agricultural trading environment. By centralizing real-time data on agricultural production, consumption, and pricing, ATP provides a comprehensive dashboard that facilitates data-driven decision-making for all stakeholders in the agricultural supply chain. The platform employs advanced deep learning algorithms, including Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), to forecast market trends and consumption patterns. These predictive capabilities enable producers to optimize their market strategies, negotiate better prices, and access broader markets, thereby enhancing the overall efficiency and transparency of agricultural trading in Malaysia. The ATP’s user-friendly interface and robust analytical tools have the potential to revolutionize the agricultural sector by empowering farmers, reducing reliance on intermediaries, and fostering a more equitable trading environment.

This study aims to identify key strategies and tactics necessary to effectively implement national social security in a democratic Indonesia. Indonesia established the Law on the National Social Security System in 2004. However, the national social security programs did not commence until 2014. The national social security implementation has faced significant obstacles. These challenges include recurring delays, legal disputes, appeals, judicial reviews, and deviations from the original policy objectives, all threatening the long-term viability of the national social security programs. This article applies a qualitative approach by critically analyzing regulations, government reports, and publicly available data and observing open public meetings and hearings concerning implementing national social security programs. Our findings indicate that implementing national social security policies in a democratic Indonesia depends on effectively managing the dynamic processes involved in policy formulation and adoption. We propose a risk-based decision-making model to assist policymakers in mitigating policy-related risks and enhance the effectiveness of future policy agendas in social security.

Ancestral knowledge is essential in the construction of learning to preserve the sense of relevance, transmit and share knowledge according to its cultural context, and maintain a harmonious relationship with nature and sustainability. The objective of this research is to study and analyze the management of ancestral knowledge in the production of the Raicilla to provide elements to rural communities, producers, and facilitators in decision-making to be able to innovate and be more productive, competitive, sustainable, and improve people’s quality of life. The methodological strategy was carried out through Bayesian networks and Fuzzy Logic. To this end, a model was developed to identify and quantify the critical factors that impact optimally managed technology to generate value that translates into innovation and competitive advantages. The evidence shows that the optimal and non-optimal management of knowledge, technology, and innovation management and its factors, through the causality of the variables, permits us to capture the interrelationship more adequately and manage them. The results show that the most relevant factors for adequate management of ancestral knowledge in the Raicilla sector are facilitators, denomination of origin, extraction and fermentation, and government. The proposed model will support these small producers and help them preserve their identity, culture, and customs, contributing greatly to environmental sustainability.

Background: People who are financially literate are able to make sound decisions regarding their money since they have a firm grasp of the fundamentals of money and financial products. The significance of financial literacy has been acknowledged by numerous nations, prompting the formation of task teams to assess their populations and develop educational and outreach programs. The requirement to make educated decisions about ever-increasing financial goods necessitates a higher level of financial literacy. Aim: Being able to make sense of one’s personal financial situation is becoming an increasingly valuable skill in today’s world. One of the most essential components for making sure and successful decisions is having a good grip on one’s financial status. By contrast, financial literacy refers to an individual’s level of knowledge and awareness regarding financial matters, whereas investors’ decision-making is characterised by their understanding, prediction, investigation, and assessment of the various stages and transactions involved in making an investment decision. Risk, a decision-making framework and process, and investing itself are all components of investing. Method: Researchers will conduct a cross-sectional survey of Saudi Arabian investors. We used a structured questionnaire to gather data. Using “Cronbach’s a and confirmatory factors” analysis, we checked whether the data is reliable. The links between financial literacy and investment decisions was demonstrated using structural equation modeling (SEM) in IBM-SPSS and SmartPLS. Purpose: The purpose of this research is to look at how the investment choices of Saudi Arabians are correlated with their degree of financial literacy. Consequently, research on the connection between financial literacy, knowledge, behaviour, and investment choices is lacking. Researchers on this subject have already acknowledged the problem’s importance and intended to devote substantial time and energy to solving it. Findings: The study concluded that there was a significant relationship between financial literacy and financial knowledge with respect of investment decision of investors. Similarly, there was a significant relationship between financial behaviour and financial knowledge with respect of investment decision of investors. The discovery of the outcomes will enable regulatory authorities to aid investors in preventing financial losses by furnishing them with sufficient financial information.

Providing and using energy efficiently is hampered by concerns about the environment and the unpredictability of fossil fuel prices and quantities. To address these issues, energy planning is a crucial tool. The aim of the study was to prioritize renewable energy options for use in Mae Sariang’s microgrid using an analytical hierarchy process (AHP) to produce electricity. A prioritization exercise involved the use of questionnaire surveys to involve five expert groups with varying backgrounds in Thailand’s renewable energy sector. We looked at five primary criteria. The following four combinations were suggested: (1) Grid + Battery Energy Storage System (BESS); (2) Grid + BESS + Solar Photovoltaic (PV); (3) Grid + Diesel Generator (DG) + PV; and (4) Grid + DG + Hydro + PV. To meet demand for electricity, each option has the capacity to produce at least 6 MW of power. The findings indicated that production (24.7%) is the most significant criterion, closely followed by economics (24.2%), technology (18.5%), social and environmental (18.1%), and structure (14.5%). Option II is strongly advised in terms of economic and structural criteria, while option I has a considerable advantage in terms of production criteria and the impact on society and the environment. The preferences of options I, IV, and III were ranked, with option II being the most preferred choice out of the four.