Investigating El Nino Southern Oscillation as the main driver of forest fire in Kalimantan

Strong El Nino events have been identified as major factors contributing to the forest fire in Indonesia. This is due to El Nino Southern Oscillation (ENSO) variability has a distinct connection with tropical precipitation, mainly in Indonesia. El Nino years are typically drier, while La Nina events generally increase precipitation in Indonesia. Although very strong El Nino events have been connected with massive forest fires, fire continue to occur during the other phases of ENSO: La Nina and normal. Here, the research reports a time series of monthly counted fires in Kalimantan between the period 2001-2020 from MODIS fire hotspot and MODIS Burned Area products. The region is divided into three categories, Primary Intact Forest, Primary Degraded Forest and Outside Forest/ Deforested area. This categorization validates the location of the fire. Our results show that in general wildfires in Kalimantan follow a similar temporal pattern with Oceanic Nino Index (ONI), with several anomalies. If ONI is high, wildfires are more intense and vice versa. The wildfire appears almost every month and increases drastically in June-October of El Nino years. However, the proportion of wildfires in Primary Intact Forest are tiny and insignificant. The primary intact forest fire only appears in July-October and have a different pattern with wildfires in general. In conclusion, wildfires are highly correlated with El Nino but limited in primary intact forests. The fires dominantly appear in the deforested area, about 80%. The rest 20% are in degraded forest and only less than 1% in primary intact forest

RANCANG BANGUN KLINOSTAT 2-D DENGAN PEROTASI MOTOR DC D06D401E

It has successfully developed a 2-D clinostat using a DC motor rotation D06D401E. The tool has angular velocity (?') of 1.67 to 93.53 rpm with changes intervals of 1.67 rpm. The reading of angular velocity is performed by DI-REV#1 module, the reading of data by the ATmega16 microcontroller on timer/counter T1 PortB.1 and 2x16 LCD as a data display. The accuracy of the angular velocity which compared by a digital tachometer DT-2234C + (?'ref) is 99.91%. The input voltage to a DC motor supplied by a variable power supply with range of 0-5 VDC, with the linearity between power and angular velocity of 99.13%. At the smallest value of the angular speed of 1.67 rpm obtained a Relative Centrifugal Force (RCF) of 4.68´10-5 g

Development of IoT-Based Real-Time Monitoring System and LFA to Improve the Efficiency and Performance of Wastewater Treatment Plant in Udayana University Hospital

Indonesia is one of the countries infected by the Coronavirus Disease 2019 (COVID-19) pandemic, which is caused by acute respiratory syndrome virus 2 (SARS-CoV-2). At the end of March 2020, the provincial government of Bali appointed Udayana University Hospital to handle COVID-19 patients because the province has experienced an increase in the number of positive cases. In September 2020, COVID-19 cases in Bali increased by more than 100%, resulting in a higher volume and content of hazardous liquid waste. Furthermore, hazardous liquid waste is the residue of activities that contain substances that can pollute and damage the environment and health, necessitating more efforts in managing the processing of hazardous wastewater produced by the hospital. Based on the background above, this study developed and applied an Internet of Things (IoT) based monitoring system to the Wastewater Treatment Plant (WWTP) in Udayana University Hospital. In principle, the IoT system can be used as a real-time monitoring tool and minimizes direct contact activities of officers’ WWTP sites. Moreover, the Liquid Film Aerator (LFA) was applied to improve the efficiency of WWTP. The developed IoT system successfully monitors pH, DO, and real-time temperature, and the monitoring results were presented in a web-based user interface. The result shows better power usage efficiency than conventional aeration. Furthermore, conventional aeration with a root blower requires 619.8 watts to produce 1 mg/L of DO, while LFA only requires 273.2 watts. The developed systems can be applied to other hospitals or similar wastewater plants that handle COVID-19 cases

Sea Level Rise, Land Subsidence, and Flood Disaster Vulnerability Assessment: A Case Study in Medan City, Indonesia

Global sea level rise (SLR) has emerged as a pressing concern because of its impacts, especially increased vulnerability of coastal urban areas flooding. This study addresses the pressing concern of SLR and flood vulnerability in the East Coast of North Sumatra (ECNS) and Medan City. We employ a data-driven approach integrating multicriteria analysis, analytical hierarchy process (AHP)-based weighting, and spatial modeling within a geographic information system framework. The analysis considers crucial factors such as slope, land use, soil type, SLR, and land deformation. The study expands the existing framework by incorporating SLR and land subsidence, acknowledging their significant roles in exacerbating flood vulnerability. Future flood-intensity scenarios are simulated based on SLR projections. Data for spatial analysis primarily originated from multisensor satellite imagery, secondary sources from published literature, and field surveys. We validated the consistency of the variable weightings assigned for vulnerability analysis using a consistency ratio threshold (<0.1). Finally, the established flood vulnerability model was validated by comparing its predictions with recorded flood events in the ECNS and Medan City. The ECNS and Medan City areas were classified as very high and highly vulnerable to flooding, respectively