This study aims to explain the design of policy strengthening in forest and land fire disaster mitigation governance, through the integration of ecotourism development in Siak Regency. Based on the research topic, this study employs a qualitative approach to describe governance conditions and the design of policy strengthening in ecotourism-based disaster mitigation governance. Data analysis is performed using Nvivo 12 Plus software. The results of this study indicate that forest and land fire disaster mitigation governance based on ecotourism development still has shortcomings that need to be addressed in the principles of conservation, economy, and community involvement. Then, the design of a policy to strengthen ecotourism-based disaster mitigation governance includes three crucial policy recommendations, namely: the need for special regulations related to forest and land fire disaster mitigation prevention based on the integration of ecotourism principle development, the need for a balance of roles between actors in determining and implementing ecotourism-based disaster mitigation policies, and the need for effective and efficient implementation of ecotourism-based disaster mitigation policies through increasing the involvement of strategic actors. Substantially, the handling of forest and land fire disasters in Siak Regency can be combined with ecotourism activities, especially in tourist village areas, by developing policies to strengthen the utilization of village-owned disaster mitigation facilities such as reservoirs, lakes, or ponds that are converted into water supplies during the dry season for forest and land fire disaster prevention activities and local economy-based tourist destinations. Our findings are a strategic effort to raise awareness among actors and highlight the need for policy-strengthening design in ecotourism-based disaster mitigation. These findings can also contribute to the literature that will be useful for all stakeholders in developing future long-term disaster mitigation governance policies. This study relies heavily on information from key informants, who represent only the perspectives and expertise of the stakeholders encountered. However, it still refers to important elements based on the informants’ knowledge capabilities in the disaster and tourism sectors. Therefore, we propose to conduct future studies on a comprehensive analysis of sustainable ecotourism-based disaster mitigation governance to promote and accelerate the idea of disaster and tourism in the future.

The problem of stunting is not only related to children’s short height, but also has an impact on high morbidity rates, due to long-term nutritional deficiencies. which hinders motor and mental development in children. The objectives of this research are: 1) to understand household food security, 2) to understand the eating habits of pregnant women and toddlers regarding existing belief systems and traditions, and 3) to understand resilience mechanisms in overcoming food emergencies to prevent stunting. The data collection process uses a mixed methods approach by combining qualitative and quantitative research. The research results show that the determining factor for the incidence of stunting in coastal areas of Indonesia is the lack of household food availability due to subsistence economic life which then has an impact on eating behavior in the household, namely the lack of quality and quantity of the types of food consumed. daily. Apart from that, there is still a lack of understanding by pregnant women regarding the importance of providing complementary breast milk food to toddlers, low literacy of food diversity among toddlers, and low public trust in the importance of immunization. Furthermore, the high rate of early marriage in society and the limited awareness of using clean water is caused by a philosophy that still considers rivers as a source of life, so the water is used for consumption. Apart from that, socio-cultural mechanisms as a strategy to resolve the problem of food shortages have not yet been implemented.

The aim of this paper is to introduce a research project dedicated to identifying gaps in green skills by using the labor market intelligence. Labor Market Intelligence (LMI). The method is primarily descriptive and conceptual, as the authors of this paper intend to develop a theoretical background and justify the planned research using Natural Language Processing (NLP) techniques. This research highlights the role of LMI as a tool for analysis of the green skills gaps and related imbalances. Due to the growing demand for eco-friendly solutions, there arises a need for the identification of green skills. As societies shift towards eco-friendly economic models, changes lead to emerging skill gaps. This study provides an alternative approach for identification of these gaps based on analysis of online job vacancies and online profiles of job seekers. These gaps are contextualized within roles that businesses find difficult to fill due to a lack of requisite green skills. The idea of skill intelligence is to blend various sources of information in order to overcome the information gap related to the identification of supply side factors, demand side factors and their interactions. The outcomes emphasize the urgency of policy interventions, especially in anticipating roles emerging from the green transition, necessitating educational reforms. As the green movement redefines the economy, proactive strategies to bridge green skill gaps are essential. This research offers a blueprint for policymakers and educators to bolster the workforce in readiness for a sustainable future. This article proposes a solution to the quantitative and qualitative mismatches in the green labor market.

This study examined the role of cryptocurrencies in tourism and their acceptance across EU regions, with particular attention to the digital transformation precipitated by the COVID-19 pandemic. The analysis focuses on the relationship between cryptocurrency acceptance points and the intensity of tourism, highlighting that the acceptance of cryptocurrencies is significantly correlated with tourism services. The literature review highlighted that Web 3.0, especially blockchain technology and decentralized applications, opens new possibilities in tourism, including secure and transparent transactions, and more personalized travel experiences. The research investigated cryptocurrency acceptance points and the intensity of tourism within the EU. The study illuminates that the acceptance of cryptocurrencies significantly correlates with tourism services. The data and methodology demonstrated the analysis methods for examining the relationship between cryptocurrency acceptance points and tourism intensity, including the use of clustering neural networks and Eurostat data utilization. The results showed a positive correlation between the number of cryptocurrency acceptance points and tourism intensity in the EU, affirming the research hypothesis. According to the regression analysis results, each additional cryptocurrency acceptance point is associated with an increase in tourism intensity. The significance of the research lies in highlighting the growing role of digital payment solutions, especially cryptocurrencies, in tourism, and their potential impacts on the EU economy. The analysis supports that the intertwining of tourism and digital financial technologies opens new opportunities in the sector for both providers and tourists.

The purpose of Vehicular Ad Hoc Network (VANET) is to provide users with better information services through effective communication. For this purpose, IEEE 802.11p proposes a protocol standard based on enhanced distributed channel access (EDCA) contention. In this standard, the backoff algorithm randomly adopts a lower bound of the contention window (CW) that is always fixed at zero. The problem that arises is that in severe network congestion, the backoff process will choose a smaller value to start backoff, thereby increasing conflicts and congestion. The objective of this paper is to solve this unbalanced backoff interval problem in saturation vehicles and this paper proposes a method that is a deep neural network Q-learning-based channel access algorithm (DQL-CSCA), which adjusts backoff with a deep neural network Q-learning algorithm according to vehicle density. Network simulation is conducted using NS3, the proposed algorithm is compared with the CSCA algorithm. The find is that DQL-CSCA can better reduce EDCA collisions.