In recent years, more and more attention has been paid to the behavior of tourists and their intention to choose a destination based on various factors. The goal of this research was to determine to what extent environmental risks and the attractiveness of the destination influence the choice of destination and the behavior of tourists. Furthermore, the goal was to determine the influence of psychological groups of tourists on their decision to choose a tourist destination using three psychographic techniques: BFI-10 (Big Five Inventories), AIO (Activities, Interests, and Opinions), and VALS 2 (Values and Lifestyle), and a freely determined six-level scale of risk and tourist attractiveness of imagined destinations. Analyzing the results obtained through the structural modeling-path analysis model, it was determined that tourists grouped in almost all psychographic orientations, resulting from lifestyles, negatively perceive destinations with a high degree of risk and attractiveness, while, with the VALS 2 technique, only members of the action orientation tend to accept ecologically risky destinations. Despite the fact that many studies have looked at how tourists perceive various risks and behave, it is still uncommon to use an integrated approach that considers the simultaneous application of several psychological tests and a unique method of gathering responses from travelers by presenting them with descriptively imagined destinations that differ in their levels of environmental risk and tourist appeal. As a result, this study can provide a conceptual framework for theoretical and practical implications for improved risk management strategies in a specific travel destination and in areas vulnerable to environmental hazards, as well as for completing knowledge about traveler behavior in risky destinations.

This article examines recovery strategies in post-COVID-19 tourism villages in Bantul, Yogyakarta, Indonesia, utilising a rural tourism resilience approach involving multi-stakeholder participation. This qualitative study collected data through interviews, literature, social media, and local news online observations. The data obtained were then analysed with the help of a code from NVivo 12 Plus to visualise the multi-stakeholder network in the five tourism village recovery strategies through the sociogram network, group queries, and concept mapping queries. The results of this study reveal the following: First, the five tourist villages have different ways of getting back on their feet and getting more substantial for a massive recovery. Second, all government levels strongly support accelerating the five tourist villages' recovery via various media promotions of the four (Tembi, Kakilangit, Kebonagung, and Kampung Santan), except for Lopati's tourism village destinations. In addition, the two villages, in terms of the resilience of social networks, mostly need support in increasing institutional capacity (Kampung Santan and Lopati), fostering collaboration, and requiring creativity. Therefore, post-COVID, mechanisms for development and new ideas in two tourist villages (Lopati and Kampung Santan) were relatively noticeable. Some tourism villages still need leaders for programmes and activities. Further, the government's persistence in popularising tourist villages requires further improvement through media promotion, tourism awareness groups, and participation in the tertiary sector.

Studies on water-based tourism have recently gained consistent attention from scholars. Its development relies on water segmentation of areas that could potentially become a tourist attraction or even an alternative source of renewable energy. In short, the ideas of water-based tourism, as presented theoretically, conceptually, and practically by scholars, have been widespread; however, studies to map the core issues in the literature have not yet been undertaken. Therefore, this paper aims to analyze the progress of water-based tourism literature around the world. Furthermore, we used the scientometric and literature review approaches, along with the assistance of two qualitative applications, NVivo and VOSViewer, as tools for visualizing the code of 106 documents in Scopus. Our core findings showed that water-based tourism studies have undergone rather substantial developments in the last decade. Moreover, our study also noted that there were eight pivotal issues that had been identified, classified as follows: “areas”, “water”, “economic”, “value”, “tourist”, “quality”, “development”, “management”, and “resources”. We believe that this water-based tourism segmentation provides potential opportunities for regions that have water resources or water utilization as their main developable asset, and that water segmentation provides great potential development for community economic growth, increased tourist visits, and a contribution to local income. Therefore, it is necessary to request that the authorities engage other agencies in order to support the best economic and practical realities associated with procuring resources, directly or indirectly. This paper also introduces insightful future directions for water-based tourism studies.

Nowadays, the presence of Artificial Intelligence (AI) in the government sector has been rapidly experiencing a significant increase in its uses. Therefore, AI technology can attract the attention of several scholars to find out more deeply about the variety of its capacities. In Indonesia, the government uses AI as an instrument in formulating regulation, and focusing on managing complex data as well as its implication for accelerating activity and work. More importantly, it is very useful for decision making. In this context, as one of the adoptions of AI in the government, one of the highlights is Electronic Traffic Law Enforcement (e-TLE). E-TLE intends to handle cases of traffic violations in the Yogyakarta region (“DIY”). The high number of accidents and traffic violations in the DIY jurisdiction are a significant issue that is especially important to discuss when the presence of AI is necessary to manage them. Therefore, this paper aims to examine artificial intelligence in ‘Electronic Traffic Law Enforcement’ that overviews current efforts and future challenges of its implementation. This paper used qualitative research with explorative-oriented; it attempts to explore the meaning of information from sources that are then interpreted to obtain more in-depth insights that are easier to understand. Finally, this paper highlights the current situation and future challenges in providing public convenience in traffic. The police officer can promote the e-TLE system periodically to reduce the number of accidents and traffic violations in the DIY region.

The presence of a Kiyai in political contestation in Indonesia has its own challenges because it is motivated by a religious figure who believes that voters can support themselves, especially Muslim voters. Furthermore, the Kiyai carried out various strategies to lure voters effectively on social media, referred Twitter accounts a strategic platform to lure voters in a political context. This article aims to identify political branding using social media Twitter by KH. Ma’ruf Amin as a vice-presidential candidate in the 2019 presidential election contest. Furthermore, qualitative methods are used for this research. Then, the analyzer uses NVivo 12 plus software to see the coding intensity of the KH Twitter account. KH Ma’ruf Amin namely @Kiyai_Marufamin, this tool can provide capture code of capture from a tweet that displays the intensity level. The results of this study indicate that KH. Ma’ruf Amin uses social media Twitter as a tool to find support, especially for Muslim voters. Social media activities in the period February 2019 - April 2019 were considered to have high intensity of coverage, this identified that the distribution of tweets by KH. Ma’ruf Amin is more about spreading tweets along with pictures, formal language and visual style against the background of a Kiyai. Thus, Twitter @Kiyai_Marufamin can provide a good political brand for KH. Ma’ruf Amin as a vice presidential candidate to participate in the 2019 presidential election in Indonesia.Keywords: Twitter, political branding, KH. Ma’ruf Amin, 2019 presidential election campaign ABSTRAKKehadiran dari seorang Kiyai dalam kontestasi politik di Indonesia memiliki tantangan tersendiri karena dilatarbelakangi seorang agamawan yang meyakini bahwa pemilih dapat mendukung dirinya, terutama pemilih Muslim. Selanjutnya seorang Kiyai melakukan berbagai strategi untuk memancing pemilih secara efektif di media sosial, dimana akun Twitter sebagai platform strategis untuk memikat para pemilih dalam kontekstasi politik. Artikel ini bertujuan untuk mengidentifi-kasi branding politik menggunakan media sosial Twitter oleh KH. Ma’ruf Amin sebagai kandidat wakil presiden dalam kontes pemilihan presiden 2019. Selanjutnya, metode kualitatif digunakan untuk penelitian ini. Kemudian, alat analisa menggunakan perangkat lunak NVivo 12 plus untuk melihat intensitas pengkodean dari akun Twitter KH. Ma’ruf Amin yaitu @Kiyai_Marufamin, alat ini mampu memberikan laju koding tangkapan dari tweet yang menampilkan tingkat intensitas. Hasil penelitian ini menunjukkan bahwa KH. Ma’ruf Amin menggunakan media sosial Twitter sebagai alat untuk mencari dukungan, terutama bagi pemilih Muslim. Kegiatan media sosial pada periode Februari 2019 - April 2019 dianggap memiliki intensitas liputan yang tinggi, hal ini mengidentifikasikan bahwa distribusi tweet oleh KH. Ma’ruf Amin lebih tentang menyebarkan tweet bersama dengan gambar, bahasa formal dan gaya visual dengan latar belakang seorang Kiyai. Dengan demikian, Twitter @Kiyai_Marufamin dianggap dapat memberikan merek politik yang bagus untuk KH. Ma’ruf Amin sebagai kandidat wakil presiden untuk berpartisipasi dalam pemilihan presiden 2019 di Indonesia.Kata kunci: Twitter, merek politik, KH. Ma’ruf Amin, kampanye pemilihan presiden 2019

The research aimed to describe the trend issues, identify the key features, and propose a theoretical model of digital government. A comprehensive search was used to find eligible articles in the Academic Scopus Database. Further, the quality of the study was assessed during the screening phase, where it met 115 journal-related articles on digital government within the social sciences discipline. Further, this literature was analyzed by NVivo 12 Plus via a hierarchy diagram, cluster analysis, word frequency analysis, and the VOSViwer tool to visualize the data via a network, overlay, and density analysis. The findings revealed a term network formed by digital government and trend issues, resulting in several growing concerns, such as e-government, open government, and technology adoption. Furthermore, key features were reported following proportional analysis, such as systems, development, services, models, information, public, policy, management, and networks. Another point is that a proposed theoretical model has been constructed and selected for future research.