The purpose of this study is to address the issue of low local participation in ecotourism management in Indonesia, specifically at the Malela Waterfall ecotourism site in Cicadas Village, Rongga District, West Bandung Regency, West Java, Indonesia. The research method is action research, which includes observation data gathering, in-depth interviews, and Focus Group Discussions. The findings of the study show that by carrying out the process of developing social infrastructure, namely development that prioritizes strengthening human resources in carrying out social service functions in ecotourism activities such as skill training of residents in the field of ecotourism, massive ecotourism outreach, and strengthening social communities—Non-Governmental Organizations (NGOs) and youth organizations as ecotourism actors. This type of development serves to raise awareness and participation among local inhabitants in Malela Waterfall ecotourism in West Bandung Regency. This promotes harmony and mutually beneficial partnerships among all Malela Waterfall ecotourism stakeholders. Furthermore, increasing community participation benefits the well-being of residents in the tourist region.

The idea of emotions that is concealed in human language gives rise to metaphor. It is challenging to compute and develop a framework for emotions in people because of its detachment and diversity. Nonetheless, machine translation heavily relies on the modeling and computation of emotions. When emotion metaphors are calculated into machine translation, the language is significantly more colorful and satisfies translating criteria such as truthfulness, creativity and beauty. Emotional metaphor computation often uses artificial intelligence (AI) and the detection of patterns and it needs massive, superior samples in the emotion metaphor collection. To facilitate data-driven emotion metaphor processing through machine translation, the study constructs a bi-lingual database in both Chinese and English that contains extensive emotion metaphors. The fundamental steps involved in generating the emotion metaphor collection are demonstrated, comprising the basis of theory, design concepts, acquiring data, annotating information and index management. This study examines how well the emotion metaphor corpus functions in machine translation by proposing and testing a novel earthworm swarm-tunsed recurrent network (ES-RN) architecture in a Python tool. Additionally, the comparison study is carried out using machine translation datasets that already exist. The findings of this study demonstrated that emotion metaphors might be expressed in machine translation using the emotion metaphor database developed in this research.

The digital era has ushered in significant advancements in Generative Artificial Intelligence (GAI), particularly through Generative Models and Large Language Models (LLMs) like ChatGPT, revolutionizing educational paradigms. This research, set against the backdrop of Society 5.0 and aimed at sustainable educational practices, utilizes qualitative analysis to explore the impact of Generative AI in various learning environments. It highlights the potential of LLMs to offer personalized learning experiences, democratize education, and enhance global educational outcomes. The study finds that Generative AI revitalizes learning methodologies and supports educational systems’ sustainability by catering to diverse learning needs and breaking down access barriers. In conclusion, the paper discusses the future educational strategies influenced by Generative AI, emphasizing the need for alignment with Society 5.0’s principles to foster adaptable and sustainable educational inclusion.

Global trade is based on coordinated factors, that means labor and products are moved from their point of origin to the point of use. Strategies have a significant impact on global trade because they enable the effective development of goods across international borders. The decision making is an important task for the development of Logistics Supply Chain (LSC) infrastructure and process. Decisions on supplier selection, production schedule, transportation routes, inventory levels, pricing strategies, and other issues need to be made. These decisions may have a big influence on customer service, profitability, operational efficiency, and overall competitiveness. The Artificial Intelligence (AI) approach of Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (Fuzzy-Promethee-2) is used to assess the priority selection of the factors associated with the LSC and evaluate the importance in global trade. The role of AI is very useful compare to statistical analysis in terms of decision making. The computational analysis placed promotion of exports as the most important priority out of five selected attributes in LSC, with infrastructure development. The result suggests that LSC depends heavily on export promotion as the most significant attribute. Infrastructural development also appeared another factor influencing LSC. The foreign investment was ranked the lowest. The evaluated results are useful for the policy makers, supply chain managers and the logistics professionals associated with the supply chain management.

The objective of this study is to examine the impact of decentralization on disaster management in North Sumatra Province. Specifically, it will analyze the intergovernmental networks, local government resilience, leadership, and communication within disaster management agencies. The study used a hybrid research approach, integrating qualitative and quantitative methodologies to investigate the connections between these factors and their influence on disaster response and mitigation. The study encompassed 144 personnel from diverse government tiers in North Sumatra and performed a meta-analysis on the implementation of disaster management. Intergovernmental networks were discovered to enhance collaboration in disaster management by eliminating regulatory gaps and efficiently allocating logistics. Nevertheless, local governments have obstacles as a result of limited resources and inadequate expertise, notwithstanding the progress made in infrastructure technology. The F test results reveal that leadership and communication have a substantial impact on the performance of BPBD personnel. The meta-assessment classifies its impact as extraordinarily high, suggesting comprehensive evaluation and successful achievement of goals in disaster management planning. Efficient cooperation among relevant parties is essential in handling calamities in North Sumatra. The government, commercial sector, NGOs, universities, and society have unique responsibilities. To improve effectiveness, governments should encourage private sector involvement, while institutions can increase their research contributions.

This study was designed to study the push and pull motivational factors affecting the foreign backpackers travel behavior towards Full Moon Party in Koh Phangan District, Surat Thani Province. In the sample 300 foreign backpackers aged 18 or older were included, who came to attend the Full Moon Party solely for vacation purposes and not for any work or income generating activities. The study was executed using a structured questionnaire. The statistical tools for the analysis of the data included, but were not limited to, frequency counts, computed percentages, means, standard deviations, chi-square analysis, one- way ANOVA, and Pearson correlation at the 0.05 level of significance. The research demonstrated that with respect to the first-time foreign visitors in Thailand to attend the Full Moon Party, then, they have habitually stayed at the resorts and the bungalows. It was a general observation that such visitors preferred to seek out information on the Internet, social websites as well as tourism websites. Their activities included horse riding, general activities, seeing natural sights including waterfalls and mountains, going for mountain hikes, participating in physically hard and risky outdoors activities, and nighttime activities. Tourists are sufficiently motivated to visit Thailand for its various appealing attributes, as revealed by the analysis. Furthermore, 10 motivational components were identified with 24 variables; Push Motivation Components: (1) Escape and Novelty Seeking, (2) Feel Free, (3) Open the World, and (4) Social Need. Pull Motivation Components: (1) Party, (2) Unique, (3) Only for Myself, (4) Sea Lover, (5) Diversity, and (6) Loner. Demographic characteristics for example gender, age, marital status, education level, occupation, and place of residence were also studied. The push factors, as well as the pull factors of travel, were found to co-relate with the behavior of female foreign backpackers on the other hand where both were significant.