This study aims to analyze the traffic noise levels at three locations in Makassar City and to compare them with the established noise quality standards. Measurements were conducted over a one-week period at specific times using a sound level meter, a vehicle speed measurement device, and a counting application to classify vehicle types into heavy vehicles (HV), light vehicles (LV), and motorcycles (MC). The observation sites included an educational area, a hospital area, and a residential area. Correlation analysis using Statistical Package for the Social Sciences (SPSS) was employed to examine the relationships between HV, LV, MC, and vehicle speed with the equivalent continuous sound level (Leq). The results indicated that noise levels at all three locations exceeded the standard threshold of 55 decibels (dB). The correlation analysis showed significant relationships between Leq and HV (0.834), LV (0.782), MC (0.787), and vehicle speed (-0.680). The effective contribution to noise was highest for HV (40.44%), followed by MC (13.35%), LV (12.68%), vehicle speed (10.38%), and other factors (23.15%), including human activity, construction noise, road surface type, road gradient, and surrounding environmental conditions. Recommended mitigation measures include restricting the operating hours and rerouting of HV in sensitive areas, as well as enforcing noise emission testing and regulations on illegal exhaust modifications.

Tourism provides considerable economic advantages; however, it also imposes environmental challenges, especially in coastal regions where unmanaged waste poses a threat to long-term sustainability. This research seeks to examine the behavioral and spatial elements that affect tourists’ willingness to pay (WTP) for circular waste management in eight coastal destinations in Southern Yogyakarta, Indonesia. Employing the Contingent Valuation Method (CVM), primary survey data were gathered from 984 visitors and analyzed using Ordinary Least Squares (OLS) regression, K-Means clustering, and spatial mapping techniques with geomap orange data mining. The analysis investigates how socio-economic factors such as age, income, gender, education level, and travel costs influence WTP, with behavioral theory serving as the interpretive framework. The findings indicate that younger and more educated tourists demonstrate a higher WTP, while age and travel costs negatively and significantly impact their WTP. The estimated average WTP of IDR 13,840 surpasses the official waste retribution fee, reflecting a considerable level of environmental concern among visitors. Additionally, spatial and cluster analyses uncover diversity in visitor segments across coastal areas, implying that standardized waste management policies may not be effective. In summary, the results underscore the necessity of merging economic valuation with spatially informed and behaviorally conscious policy tools, illustrating the potential of WTP as a funding mechanism for sustainable and circular waste management in coastal tourism regions.

Sawahlunto City is highly vulnerable to landslides due to steep topography, unstable soil conditions, and the legacy of former mining activities. These conditions pose risks not only to settlements and infrastructure but also to environmental sustainability. This study aims to analyze local government strategies in landslide disaster mitigation using James Brian Quinn’s strategic framework, focusing on goals, policies, and programs. This research employs a qualitative approach with data collected through interviews, observation, and document analysis. This study involved 15 key informants selected through purposive sampling, consisting of Regional Disaster Management Agency (Badan Penanggulangan Bencana Daerah, BPBD) officials, regional apparatus organizations, and local government representatives. Additional triangulation was conducted with community-based and external actors such as Disaster Resilient Village (Desa Tangguh Bencana, Destana), Disaster Preparedness Cadets (Taruna Siaga Bencana, Tagana), Tsunami Alert Community (Komunitas Siaga Tsunami, KOGAMI), Jemari Sakato, and BPBD of West Sumatra Province. Data were collected between December 2024 and January 2025 through interviews, field observations, and document analysis, and analyzed using data reduction, categorization, and thematic interpretation based on strategic dimensions. The findings indicate that although BPBD Sawahlunto has established strategic planning documents such as Disaster Risk Assessment (Kajian Risiko Bencana, KRB), Disaster Management Plan (Rencana Penanggulangan Bencana, RPB), and Contingency Plans (Rencana Kontinjensi, Rekon), their implementation remains constrained by limited budget and human resources. Programs such as Destana and Disaster Safe Education Unit (Satuan Pendidikan Aman Bencana, SPAB) contribute positively to community preparedness, although their coverage is still limited. The study concludes that strengthening inter-agency coordination, optimizing resources, and enhancing community participation are essential to improve the effectiveness and sustainability of landslide mitigation strategies in Sawahlunto City.

This study investigates the influence of three distinct water sources on the physical and chemical properties of soil in the Al-Hammar Marsh of southern Iraq. Fifteen geo-referenced soil samples were collected from zones affected by (i) Euphrates River freshwater, (ii) saline agricultural drainage from the Al-Khamisiya canal, and (iii) brackish water intrusion from the Aramco feeder channel. Samples were tested for gypsum content, pH, electrical conductivity (EC), organic matter (OM) content, bulk density, porosity, texture, and the concentration of basic ions. Spatial variability was evaluated utilizing geographic information system (GIS)-based interpolation methods. The highest salinity levels (mean EC, (EC) = 2,292 µS/cm) were found in regions influenced by the main outfall drain (MOD), marked by high concentrations of chloride and sulfate, reduced porosity, and heightened soil alkalinity. Conversely, Umm Al-Wudaa, affected by Euphrates freshwater, exhibited superior soil structure, elevated levels of OM (7.86%), and reduced salinity (EC = 1,960 $\mu$S/cm), signifying efficient natural leaching. Areas supplied by Aramco exhibited the presence of gypsum and marine ions, along with an intermediate salinity (EC = 2265 $\mu$S/cm). The places with the highest salinity were detected, and the dilution of salt downstream was confirmed via GIS analysis. The findings highlight the need for integrated salinity management in Al-Hammar Marsh through controlled freshwater releases, targeted soil amendments, wetland-based pretreatment of drainage inflows, and continuous GIS-supported monitoring.

Environmental noise generated by motorcycle traffic constitutes a critical challenge for intermediate cities of the Global South, where high motorization rates intensify exposure to stressful acoustic environments. In Florencia (Caquetá, Colombia)—a city in which motorcycles represent 96.6% of the vehicle fleet—noise functions not only as an environmental pollutant but also as a psychosocial trigger associated with irritability, stress, and aggressive driving behaviors among young riders. This study evaluates urban motorcyclists’ perceived effectiveness of regulatory measures aimed at noise and traffic control, considering how education level and driving experience shape normative perceptions. Using a non-experimental, cross-sectional design, data were collected from 502 motorcyclists. Kruskal–Wallis tests and Spearman correlations revealed a significant positive association between higher education and favorable perceptions of regulatory effectiveness, while no association was observed for driving experience. An exploratory factor analysis (EFA) confirmed a two-factor structure (54.3% variance), differentiating structural/collective measures from individual/educational ones. Overall, structural and educational interventions were perceived as more effective than coercive approaches. These findings highlight the need for context-sensitive regulatory frameworks that integrate social legitimacy, cultural adaptation, and psychological determinants of behavior. The study contributes empirical evidence for designing participatory and education-centered strategies for noise management and mobility governance in structurally informal urban contexts such as Florencia.

Water scarcity is a major challenge in agriculture, where nearly 70% to 80% of freshwater is used for irrigation. This study reviews clay pot irrigation and its integration with drip irrigation and Internet of Things (IoT)-based monitoring for improving water use efficiency. Previous studies have reported substantial irrigation water savings under clay pot irrigation systems up to 80% compared to conventional methods by supplying water slowly near to the root zone and reducing losses. It also provides good water use efficiency and maintains acceptable crop yield under limited water conditions. Previous studies have shown that the performance of the clay pot irrigation depends on pot design, including size and shape. A few studies suggested that storing water in clay pots and the water passing through the pot walls may lead to some improvement in water quality, although detailed data is still limited. However, the integration with drip irrigation and IoT-based control can further improve water distribution and reduce manual effort.

This study aims to develop a model for predicting daily sea wave heights in the Makassar Strait to support shipping safety in tropical waters. Observation data were obtained from the Makassar station of the Meteorology, Climatology, and Geophysical Agency (Badan Meteorologi, Klimatologi, dan Geofisika, BMKG) (January 2018–December 2023), covering wind speed, wind direction, sea surface temperature, and rainfall. Feature selection was performed using Frequent Pattern Growth (FP-Growth), which was chosen because it efficiently finds association patterns between variables with only two database scans, making it more economical than other techniques such as Recursive Feature Elimination or Principal Component Analysis. The selected features were used to build a Support Vector Regression (SVR) model optimised with the Fruit Fly Optimisation Algorithm (FOA). The evaluation was conducted with zonal validation in three sub-regions of the Makassar Strait (north, central, south) using a lead time of one day ahead. The results show that the SVR-FOA model produces an average root mean square error (RMSE) of 0.4938 m (95% confidence interval (CI): 0.472–0.516), mean absolute percentage error (MAPE) of 0.00208 (95% CI: 0.00195–0.00221), and a correlation of 0.935. SVR-FOA reduced the RMSE by 16.8% compared to the default SVR, while compared to the grid search SVR, there was a 6.7% reduction. The model’s performance is comparable to similar studies in the literature, although the RMSE is still higher than Long-Short Term Memory (LSTM) and XGBoost; however, SVR-FOA excels in stability between zones. In conclusion, SVR-FOA with FP-Growth feature selection effectively predicts daily sea wave height in the Makassar Strait. Further research is needed to test shorter time scale predictions, real-time data integration, and field validation with stakeholders.