Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2023/r/adakent/10107
  Adoption of the Green Economy through Branchless Rural Credit Banks during the COVID-19 Pandemic in Indonesia

  Marhaeni, A. A. I. N.; Jermsittiparsert, Kittisak; Sudarmo, Lucia Rita; Indrawati, Lucia Rita; Prasetyo, Andjar; Fuada, Noviati; Rachmadhani, Arnis; Raharjo, Tri Weda; Wahyudianto, Heri; Harwijayanti, Bekti Putri

  A green economy has an impact on improving welfare, but it takes continuous efforts to achieve it from various fields. Contribution in the context of banking on a small scale is one of the initiatives that can show participation in achieving a green economy. This study aims to explore people's behavior in financial transactions and analyze the practice of rural credit banks in encouraging the achievement of a green economy through the National Financial Inclusive Strategy (NFIS) program despite the COVID-19 pandemic. This study used quantitative approaches; observations were conducted at a certain time by collecting data taken directly as a complement to this study, as well as taking questionnaire data involving 363 samples and analyzing them using the structural equation model (SEM). The result is that green economic support is found in using paper for fewer savings transactions compared to branchless banking with conventional savings transactions. The high number of residents exposed to COVID-19 does not affect branchless banking. In addition, the use of branchless banking can show the penetration of financial literacy in the community. The results of the path analysis explain that perceived ease of use (7.468) and perceived usefulness (2.152) have an influence on attitude; intention is greatly influenced by attitude (15.357); and actual usage is influenced by intention (11.682). This research has specific implications for the Magelang City Rural Bank (MCRB), which needs to conduct market research to find out the potential of branchless banking that is specifically needed by the people of Magelang. Branchless banking innovation needs to be strengthened by presenting easy-to-understand and easy-to-use applications to improve the attitude of the Magelang people in adopting branchless banking applications and using them sustainably.

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• MakaleAçık Erişim2023/r/adakent/10099
  An Intelligent Recommendation for Intelligently Accessible Charging Stations: Electronic Vehicle Charging to Support a Sustainable Smart Tourism City

  Suanpang, Pannee; Jamjuntr, Pitchaya; Kaewyong, Phuripoj; Niamsorn, Chawalin; Jermsittiparsert, Kittisak

  The world is entering an era of awareness of the preservation of natural energy sustainability. Therefore, electric vehicles (EVs) have become a popular alternative in today's transportation system as they have zero emissions, save energy, and reduce pollution. One of the most significant problems with EVs is an inadequate charging infrastructure and spatially and temporally uneven charging demands. As such, EV drivers in many large cities frequently struggle to find suitable charging locations. Furthermore, the recent emergence of deep reinforcement learning has shown great promise for improving the charging experience in a variety of ways over the long term. In this paper, a Spatio-Temporal Multi-Agent Reinforcement Learning (STMARL) (Master) framework is proposed for intelligently public-accessible charging stations, taking into account several long-term spatio-temporal parameters. When compared to a random selection recommendation system, the experimental results demonstrate that an STMARL (master) framework has a long-term goal of lowering the overall charging wait time (CWT), average charging price (CP), and charging failure rate (CFR) of EVs.

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• MakaleAçık Erişim2022/r/adakent/10101
  Tourism Service Scheduling in Smart City Based on Hybrid Genetic Algorithm Simulated Annealing Algorithm

  Suanpang, Pannee; Jamjuntr, Pitchaya; Jermsittiparsert, Kittisak; Kaewyong, Phuripoj

  The disruptions in this era have caused a leap forward in information technology being applied in organizations to create a competitive advantage. In particular, we see this in tourism services, as they provide the best solution and prompt responses to create value in experiences and enhance the sustainability of tourism. Since scheduling is required in tourism service applications, it is regarded as a crucial topic in production management and combinatorial optimization. Since workshop scheduling difficulties are regarded as extremely difficult and complex, efforts to discover optimal or near-ideal solutions are vital. The aim of this study was to develop a hybrid genetic algorithm by combining a genetic algorithm and a simulated annealing algorithm with a gradient search method to the optimize complex processes involved in solving tourism service problems, as well as to compare the traditional genetic algorithms employed in smart city case studies in Thailand. A hybrid genetic algorithm was developed, and the results could assist in solving scheduling issues related to the sustainability of the tourism industry with the goal of lowering production requirements. An operation-based representation was employed to create workable schedules that can more effectively handle the given challenge. Additionally, a new knowledge-based operator was created within the context of function evaluation, which focuses on the features of the problem to utilize machine downtime to enhance the quality of the solution. To produce the offspring, a machine-based crossover with order-based precedence preservation was suggested. Additionally, a neighborhood search strategy based on simulated annealing was utilized to enhance the algorithm's capacity for local exploitation, and to broaden its usability. Numerous examples were gathered from the Thailand Tourism Department to demonstrate the effectiveness and efficiency of the proposed approach. The proposed hybrid genetic algorithm's computational results show good performance. We found that the hybrid genetic algorithm can effectively generate a satisfactory tourism service, and its performance is better than that of the genetic algorithm.

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• MakaleAçık Erişim2022/r/adakent/10097
  Extensible Metaverse Implication for a Smart Tourism City

  Suanpang, Pannee; Niamsorn, Chawalin; Pothipassa, Pattanaphong; Chunhapataragul, Thinnagorn; Netwong, Titiya; Jermsittiparsert, Kittisak

  The metaverse is an innovation that has created the recent phenomenon of new tourism experiences from a virtual reality of a smart tourism destination. However, the existing metaverse platform demonstrated that the technology is still difficult to develop, as the service provider did not disclose the internal mechanisms to developers, and it was a closed system, which could not use or share the user's data across platforms. The aim of this paper was to design and develop an open metaverse platform called the extensible metaverse, which would allow new developers to independently develop the capabilities of the metaverse system. The acquisition of this new technology was conducted through requirements analysis, then the analysis and design of the new system architecture, followed by the implementation, and the evaluation of the system by the users. The results found that the extended metaverse was divided into three tiers that created labels, characters, and virtual objects. Furthermore, the linking tier combined the 3D elements, and the deployment tier compiled the results of the link to use all three parts by using the Blender program, Godot Engine, and PHP + WebGL as their respective key mechanisms. This system was tested in Suphan Buri province, Thailand, which was evaluated by 428 users. The results of the metaverse satisfaction, created tourism experience, and overall satisfaction of the variation of the satisfaction of using the metaverse were 86.0%, 79.7%, and 92.9%, respectively. The relative Chi-square (chi(2)/df) of 1.253 indicated that the model was suitable. The comparative fit index (CFI) was 0.984, the goodness-of-fit index (GFI) was 0.998, and the model based on the research hypothesis was consistent with the empirical data. The root mean square error of approximation (RMSEA) was 0.024. In conclusion, the extended metaverse is more flexible than other platforms and also creates the user's satisfaction and tourism experience in the smart destination to support sustainable tourism.

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