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This study aimed to isolate lactic acid bacteria from Halloumi cheese produced by Mazaarat Artisan cheese Indonesia, to evaluate its potential as a probiotics, and to identify it based on molecular characteristics. The lactic acid bacteria were isolated from fresh milk, curd, and the Halloumi cheese and their morphology and physiology were identified. Screening of the lactic acid bacteria isolates for probiotics candidates was mainly based on the resistance of simulated gastric juice, bile salts, antibacterial activities against pathogens, and the adhesion properties by hydrophobicity test. The selected lactic acid bacteria strains as probiotics candidates were then identified molecularly using 16S ribosomal RNA. From this study, 13 lactic acid bacteria isolates were obtained. Among the 13 isolates, K3 isolate was the most potent as a probiotics candidate. This isolate had high tolerance for simulated gastric juice and bile salts, good ability to protect the gut against pathogenic bacteria since it has antibacterial activities and had ability to adhere to human epithelial cells. Based on molecular identification, this probiotics candidate was identified as Lactobacillus plantarum.

Monitoring volcanic activity this is indispensable for both research and disaster mitigation strategies. Therefore, the presence of volcano monitoring allows the monitoring, data recording and early warning system of volcanic activity from a distance that is real time. Volcanic monitoring system aims to detect any changes in volcanic status. Temperature and humidity become parameters of increased magma activity. Concentration of gasses includes SO2 and CO2, indicates of the depth of magma in volcanic conduit. Magma movement also triggers the earthquake. The instrument that used in this research are temperature and humidity sensor DHT11, SO2 sensor TGS2602, CO2 sensor MG811, and vibration sensor ADXL345. Temperature and humidity sensors used DHT11 sensors that serve to detect temperature and humidity in the air. DHT11 sensors can detect temperature between 0-50°C and humidity between 20-90% RH. SO2 emissions were detected using TGS 2602 sensors that detects SO2 gas between 0-100 ppm. While CO2 gas emissions used MG811 sensors that detect the presence of CO2 gas between 350-10000 ppm. Furthermore, the vibrations were detected using a digital accelerometer ADXL345 that detects vibrations between 0.1-3200 Hz. Data from all sensors processed using arduino promini microcontroller and then sent to ESP8266. ESP8266 is a wifi module that serves as a microcontroller enhancement to connect to wifi and create TCP / IP protocol. This module is also used to create an IoT project so that it can be accessed at any time on the web service page. This system will be assembled solar cells as a source of power supply.

Abstract. Volcano monitoring requires the system which has high-fidelity operation and real-time acquisition. MONICA (Mobile Monitoring System for Indonesian Volcano), a system based on Wireless Sensor Network, mobile robot and satellite technology has been proposed to fulfill this requirement for volcano monitoring system in Indonesia. This system consists of fixed-mode for normal condition and mobile mode for emergency situation. The first and second modes have been simulated in slow motion earthquake cases of Merapi Volcano, Indonesia. In this research, we have investigated the application of our bandwidth management for high-fidelity operation and real time acquisition in mobile mode of a strong motion earthquake from this volcano. The simulation result showed that our system still could manage the bandwidth even when there were 2 died fixed node after had stroked by the lightning. This result (64% to 83% throughput in average) was still better than the bandwidth utilized by the existing equipment (0% throughput because of the broken seismometer).