This article uses a qualitative descriptive approach, through field visits with observations and in-depth interviews. The research location chosen was a representative village in accordance with the Tourism Village classification of the Gunung Kidul Regency Tourism Office. A tourist village is a form of integration between attractions, accommodation and supporting facilities presented in a structure of community life that is integrated with applicable procedures and traditions. In line with this, the existence of tourist villages can be an alternative strategy for increasing village original income (PADes) to support poverty alleviation. Measuring the impact of tourism village innovation on increasing Village Original Income (PADes) in supporting poverty reduction can provide a complete picture of how the implementation of tourism village innovation has a significant impact on village development through increasing PADes. Gunung Kidul Regency is one of the areas that has succeeded in developing tourist villages, this can be seen from the reduction in poverty rates in the last 10 years.

This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.

This study examined the labor regulations regarding the hours of work and rest for representative fishing countries (Norway) by the International Labor Organization (ILO) Convention C188—Work in Fishing, 2007. A dual comparative analysis with Norway is used to explore policy implications for the representation and protection of fishers’ labor standards in Korea. This study examined the possibility of synchronisation between national and international legislation on the hours of work and rest for fishers, with a particular focus on the Norwegian case. The objective is to identify policy enhancements related to the Korean Seafarers Act. This study looked in depth at the fatigue and well-being problems faced by Korean fishers working long times on various vessels. It is based on the results of a qualitative comparative study. To achieve the objectives, We proposed to ‘the name of the fishing vessel’, which are excluded from the protections afforded by the Seafarers Act and to clarify the regulations regarding the labor standards for them. This proposal will provide compensation and protection for Korean fishers’ labor rights. It aims to enhance labor conditions in line with ILO standards, harmonize national and international agreements to protect small-scale fisheries and contribute to the development of environmentally friendly propulsion technologies, such as hydrogen-fueled electric hybrids and LPG (Liquefied Petroleum Gas).