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The availability of groundwater is a crucial solution to ensure the sustainability of water resources, including providing clean water. Therefore, efforts to map groundwater potential are required to enhance the efficiency of groundwater utilization and support achieving one of the Sustainable Development Goals (SDGs), particularly clean water and sanitation. This research aims to identify the distribution of the groundwater potential in Kediri Regency using the random forest (RF) and extreme gradient boosting (XGB) algorithms. This research utilizes 13 parameters, including elevation, slope, aspect, drainage density, river density, distance from rivers, lineament density, Topographic Wetness Index (TWI), Normalized Difference Vegetation Index (NDVI), land cover, soil type, lithology, and band 3 from Sentinel-2A satellite imagery. The coordinates of groundwater wells are used as training and testing data with ratios of 80:20, 70:30, and 60:40. Through the evaluation of each model’s performance using a confusion matrix, it is revealed that the best model is the RF 70:30 ratio model with Accuracy (Acc), Specificity (Spe), Sensitivity (Sen), Positive Predictive Value (PPV) values of 0.978, Cohen’s Kappa (CK) and Matthew’s Correlation Coefficient (MCC) of 0.956, and Area Under Curve (AUC) of 0.994. In this model, the elevation has the highest influence on the model, with a significance level equal to 100.

Floods are a natural hazard that has a major impact on society because of deaths, injuries, property damage, and economic losses. In the context of exposure to flooding, there is a gap between communities or individuals in each region in responding to and dealing with its impacts because of differences in demographic characteristics, regional structure, availability of facilities, and existing disaster prevention and management efforts. In this study, we assessed social vulnerability to flooding in the Samin watershed using the social vulnerability index (SoVI). Social vulnerability index is a quantitative measure that is widely applied to evaluate social vulnerability. This study compiles the stages of indicator selection, data collection, statistical analysis and normalisation, determination of indicator weights and dimensions using principal component analysis, aggregation of indicators, construction of SoVI, and mapping of results. The results show that dimensions related to demographics and exposure are the causes of the majority of social vulnerability variability. Other important dimensions include the socio-economic dimension and growth ratio.ContributionSpatial data-based social vulnerability measurement can be used by the government as a basis for formulating flood disaster management policies in the Samin watershed area.

This study addresses a critical gap in the literature on 21st-century skills by examining how deficiencies in cultural knowledge contribute to communication challenges among senior high school students in Surakarta, Indonesia. While communication is widely recognized as a core competency for students in the digital era, most research has focused on general or higher education contexts, often overlooking the nuanced impact of local cultural knowledge on communication effectiveness at the secondary school level. Drawing on survey data from students, teachers, and parents, and employing qualitative thematic analysis, this research reveals that many communication difficulties experienced by Surakartanese youth-including misunderstandings, perceived disrespect, and inappropriate gestures-are deeply rooted in insufficient mastery of local cultural norms and values. These issues are most apparent in both verbal and nonverbal interactions with elders and authority figures. The findings underscore the urgent need for educational models that integrate local cultural knowledge to foster more effective and respectful communication. By situating cultural knowledge at the heart of communication skill development, this study offers actionable insights for educators seeking to create inclusive learning environments and better prepare students for success in Indonesia's multicultural and rapidly globalizing society. Cultural knowledge deficiency can significantly hinder effective communication among school-aged youths, particularly in diverse environments like Surakarta, Indonesia. This issue is not merely an academic concern; it has real-world implications for social cohesion, educational success, and personal development. Bridging the gap in cultural knowledge is vital for nurturing effective communication among school-aged youths in Surakarta. By prioritizing cultural education, we can empower the next generation to thrive in an increasingly interconnected society, ultimately contributing to a more inclusive and harmonious community.

Gamalama is an active stratovolcano on Ternate, a small volcanic island in Maluku Utara, Indonesia. Since 1510, a total of 77 eruptions have been recorded, with various impacts on the population and environment on the island and its surroundings. In July 2015, Gamalama erupted after < 24 h of precursor signs. The seismic activity continued to increase until September 2015, as marked by three sudden eruptions that were not preceded by significant volcanic and tremor earthquakes. This research was intended to understand the chronology and impact of the 2015 Gamalama eruption, which is categorically unusual, and to learn how the government conducted relevant crisis management and in what manners the community affected by ejected materials reacted to it. The former was achieved by analyzing the data provided by the Gamalama volcano observatory. As for the latter, interviews with key stakeholders in volcanic disaster management and a questionnaire-based survey involving 85 respondents in the most affected areas were conducted. The results showed that despite the relatively small Volcanic Explosivity Index (VEI = 2), the 2015 eruption was rather unexpected to many parties because it began with a short-term precursor sign (less than a day). The impact included tephra deposits as thick as 2–6 mm was in the Loto, Togafo, and Takome Villages. A total of 1791 people was recorded evacuating to several locations, such as Afe Taduma village, the SMKN 2 camp, the SKB camp, and the Naval Base camp. After a rapid impact assessment and coordination with the Center for Volcanology and Geological Hazard Mitigation (CVGHM), the government issued a status of emergency and evacuation orders. In cases when eruptions are initiated with a short-term precursor, the large population size and geographic condition of Ternate Island create a particular challenge in the resultant evacuation. Nevertheless, with prior mitigation measures and evacuation drills in hazard zones, evacuation can be carried out effectively. Even when a large-scale Gamalama eruption requires an evacuation to neighboring islands, a properly implemented mitigation such as the establishment of sister islands can substantially facilitate volcanic crisis management activities on small islands.

Bengawan Solo River water is a source of drinking water and raw materials for the government of Surakarta city, but the water has been mixed with domestic, industrial, and agricultural wastes. The waste contains estradiol-17 derived from urine and feces, both from livestock and humans as well as industries around the sub-watershed Bengawan Solo River. The content of estradiol-17 in the Bengawan Solo sub-watershed is quite high. This study is the first conducted in Bengawan Solo River to look at natural estrogens that are very rarely studied in the environment, which are likely could cause several health effects in humans and wildlife due to their relatively strong estrogenic potential and high levels in wastewater and river water. Therefore, research on the elimination of these compounds using effective, energy-efficient, and low-maintenance technologies for water treatment such as phytoremediation is highly expected. The purposes of this study were to identify estradiol, to measure the estradiol levels through HPLC tests as well as to test the effectiveness of phytoremediation with Portulaca plant as biological agents. The results show that the water of Bengawan Solo River contained estradiol substances ranging from 3.88 ppm to 5.76 ppm. The Portulaca plant species was effective at eliminating estrogenic waste up to 99.89%.

Optimal production planning is a problem that causes product stock buildup at PT Marina. Factors that affect production planning in the company are the conditions of Demand, Safety Stock, and Production Costs. The results of the demand forecasting method chosen are the Moving Average with N = 3 and the Mean Absolute Percentage Error (MAPE) = 0.05 is 68,084 boxes/period with a production cost of IDR 544,672.00/period. The Safety Stock of bottle products in the ninth forecasting period is 8076 Boxes. Based on the three factors above, an intelligent production planning model was developed using a fuzzy logic approach. The result of defuzzification of demand planning for bottle products for the ninth or three months using the Center of Area (COA) method was 59,917 Boxes. Based on the defuzzification of production planning, the total cost of aggregate production planning for the next three months using the chase strategy method is 617,235,300. 1500 ml = 17,105 boxes. Based on the aggregate planning model above, the company can schedule production and raw materials so that the warehouse’s product stock management is maintained optimally.

The massive influx of Rohingya refugees to Bangladesh from Myanmar in August 2017, impelled the government of Bangladesh to clear thousands of acres of forestland in Ukhia and Teknaf sub-districts to allow their accommodation. Subsequently, the refugees also cut down trees thus resulting in rapid deforestation in that region. Recently, however, the Rohingya refugees in collaboration with UNHCR, have undertaken a massive tree plantation project. In this study, we calculated a Normalized Difference Vegetation Index (NDVI) using remote sensing data in the Ukhia sub-district to analyze changes that occurred in the years following the 2017 influx and evaluated the effectiveness of the reforestation effort. After calculating the NDVI, we found that there was an implication of a slight increase in vegetation. The results show that the total area of vegetation coverage in February, 2017 was 215 square kilometers and in 2019 it had gone down to 197.92 and by 2023 it had recovered to 235 square kilometers. Thus, we can conclude that the reforestation process should be continued as the changes will become more visible. As Bangladesh is highly vulnerable to climate change, continued deforestation will only aggravate the situation and thus this raises the importance of reforestation.

The complexity of managing the supply and demand for egg agents causes conditions for egg agents to experience difficulties in determining the ideal number of eggs available in the warehouse and establishing the right strategy for controlling the supply from breeders. This research aims to assist egg agents in supporting the right strategic decisions in managing chicken eggs so that the supply and demand for chicken eggs are maintained through the development of the SAFCES application so that it is not done manually. The Fuzzy Analytical Hierarchy Process (AHP) model is used through the development of an application called SAFCES. The results showed that the main priority in managing chicken eggs was focusing on selling prices (0.63) and an alternative strategy that could be used as increasing agent area (0.78) to manage demand which was always maintained.

Ecosystems play a crucial role in carbon storage, with each ecosystem type having a different storage capacity. Baluran National Park comprises several ecosystems, including savannas, coastal, mountainous, mangrove, and evergreen forests invaded by Acacia nilotica, all of which impact carbon storage. This study aims to quantify and map the distribution of carbon storage across various land-cover classes in Baluran National Park. The analysis uses a 2024 land-cover map, biogeophysical data (aboveground and belowground biomass, soil organic carbon, deadwood) derived following IPCC and FREL guidelines, and is conducted using the InVEST Carbon Storage and Sequestration model. The results show that secondary forests have the highest carbon storage of 8,86 x 10 5 tC, primarily in aboveground biomass due to tall stands and dense canopies. Among non-forest classes, A.nilotica stands have the highest carbon storage at 1,28 x 10 5 tC dominated by belowground biomass because this leguminous species develops a large root system. Despite its contribution to carbon stocks, A. nilotica litter contains allelopathic compounds that suppress understorey vegetation and disrupt savanna dynamics. These findings highlight a trade-off between maximizing carbon storage and conserving native savanna ecosystems, underscoring the importance of integrating invasive species control into carbon-oriented conservation planning in Baluran National Park.

Numerous studies reported that infrared thermography and vibration are condition monitoring technology that is important and effective for doing a condition diagnostic of bearing centrifugal pump health without destructing or disturbing machine operational. This paper focuses on thermography image processing based on K-Mean color segmentation which will produce normal and abnormal condition features. Health diagnostic of bearing by processing of digital image, image clustering, segmentation and extraction. Extraction of image pattern is done by calculating the area of heat point and color feature bearing condition of RGB colour space and active contour segmentation in order to process and differentiate between normal and abnormal bearing image by statistical technique. The parameters that can be used as reference to classifying conditions are standard deviation, Mean, Variance, Skewness, Kurtosis, Vibration (RMS) and Shape features (area). Final step is determining the boundary condition between normal and abnormal using statistical logic method.