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In the recent years, the number of smartphone users has increased dramatically every year. Smartphones produce a variety of services including indoor navigation and tracking using the Received Signal Strength Indicator (RSSI) value of the Wi-Fi (Wireless Fidelity) routers to estimate user position. In this research, we developed a navigation and tracking system using a Fingerprint map and k-Nearest Neighbor (k-NN) algorithm. In that way, we can help the user to go through the nearest path to user destination by using Dijkstra’s algorithm. These features are displayed in the form of an RSSI-based navigation application on an Android smartphone. At the same time, estimated position of user of this navigation app will be sent to server and viewed in a real time website application. This system helps to assist visitors in finding their way in a complex building and at the same time it allows building owners record and analyze visitor movement. One key benefit of the system is its low initial cost. It only utilizes the existing Wi-Fi infrastructure. Experimental results show that this system can reach an accuracy up to 78% and distance errors less than 3 meters.

A global positioning system (GPS) is often used as a tool for determining direction and positioning. However, GPS is weak in estimating the error, which is quite large at the actual distance, so positioning in a narrow area cannot work well. Therefore, a better method is needed to be used as a narrow-navigation system. This study aimed to determine whether RSSI has a better error than GPS for navigation devices in a narrow space or area. The method used was plotting graphs using Ms. Excel and determining the value of R square. The RSSI value was obtained through the Esp8266 device and then sent to the server via the MQTT protocol and converted using Node-Red on the Raspberry Pi. The comparison results of the Esp8266 device RSSI graph match the Laptop RSSI device as a reference. The match between the relative distance to the RSSI with the actual distance shows a 3.3-33% error. This result is considered much better than the GPS error.

Technology makes it easier for us to communicate over a distance. However, there are still many remote areas that find it difficult to communicate. This is due to the fact that communication infrastructure in some areas is expensive to build while the profit will be low. This paper proposes to combine voice over internet protocol (VoIP) over mesh network implemented on openWRT router. The routers are performing mesh functions. We set up a VoIP server on a router and enabled session initiation protocol (SIP) clients on other routers. Therefore, we only need routers as a means of communication. The experiment showed very good results, in the line-of-sight (LOS) condition, they are limited to reception distances up to 145 meters while in the non-line-of-sight (NLOS) condition, they are limited to reception distances up to 55 meters.

Kelud is one of Indonesian volcano lies between Kediri and Blitar districts of East Java province. This volcano has erupted since 1000 where casualties of 200000 people emerged until the last eruption in 2014. Therefore, it is needed a volcano early warning system to detect the eruption earlier for minimizing the casualties. We have developed an early warning system based on sensor nodes consist of vibration, temperature and gasses (sulfur and carbon dioxide) sensors to monitor the physical parameter of the volcano, drone surveillance, mapping and temperature measurement, and mobile robot consists of the same sensor as in the node for both normal and emergency situations. The system has been tested in Kelud volcano in August 2019. In a normal condition, the system has detected 1 Hz of seismicity, under 1 ppm of sulfur and carbon dioxide, 23-55.3oC of the lake temperature, 32oC of the ground temperature and 23-25oC of the air temperature. The system could be used for 37 hours of full operation for 1 charging cycles of solar cell’s charging process where suitable for dangerous environment application.

Topography of a volcano crater can change due to endogenic processes such as deformation or eruption, or surface processes. Erosion and deposition are surface processes that may occur and gradually change the slope of the inner volcano crater. Here, we investigated erosion and deposition processes that occurred in the Kelud crater after the 2014 plinian eruption. We used high-resolution Digital Elevation Models (DEMs) and orthomosaic images derived by drone photogrammetry that acquired between September 2018 and July 2019. We obtained hundreds of aerial images which were reconstructed to obtain 3D models of Kelud’s crater by using Structure from Motion (SfM) technique. Results show erosions at alluvial fans that dominantly located at the east valleys of Kelud crater. The erosion removed the volcanic materials up to -5 m which transported and deposited close to the vicinity of the Kelud crater. The deposition process causes the increase of the Kelud crater lake up to 3 m. Moreover, we also mapped the thermal distribution of the Kelud crater lake by using low cost thermal camera. Our thermal investigation is able to identify some hotspots at the vicinity of the Kelud crater lake with range temperature of 43.7°C – 55.3°C, while the average apparent temperature of the Kelud crater lake is ~ 29°C. This high temperature area may indicate underwater active fractures that continuously release volcanic gasses which leads to convection heat transfer through Kelud’s water lake.

In this work, ruby (Cr doped Al2O3 bulk crystal) with the size of ∅10×21 mm was grown by the flame fusion technique (FFT). Absorption spectrum was carried out in the range of 300–800 nm by spectrophotometer, It shows 2 absorption peaks of Cr3+ in ruby near 400 nm and 550 nm . The crystal structure and the lattice parameters were estimated using X-Ray diffraction studies. The density, refractive index and hardness of synthesis ruby were measured and shown the values in the range of natural ruby material.

In this investigation, a chitosan-Papia Undulata shell composite film was obtained by casting evaporation method. The physical properties and the influence of chitosan-Papia Undulata shell composite films on the antibacterial were investigated. The effects of Papia Undulata shell on the chitosan film are determined with Fourier Transform Infrared Spectroscopy (FTIR), Energy Dispersive X-Ray Fluorescence (EDXRF) and X-Ray Diffraction (XRD), respectively. On the other hand for evaluated the antibacterial activity, the chitosan-Papia Undulata shell composite films investigate against Gram-negative (E.coli) bacterial. The results revealed that the chitosan-Papia Undulata shell composite films can be inhibiting target microorganisms. Another that, the chitosan-Papia Undulata shell composite films has particles of Papia Undulata shell distribution in the chitosan film which corresponding with the result of XRD pattern, while the results of FTIR suggest that the chitosan-Papia Undulata shell composite films can be modified by the addition of Papia Undulata shell.

Recently, forest fire cases have often occurred in Indonesia. Besides efforts to prevent the forest fires, there is also a need for a good mitigation system. Mitigation is an effort made so that the impact of disasters can be minimized. In this research, a prototype of forest fire alert system will be built. This system will be based on IoT and focus on prediction of forest fire positioning. Temperature data as a basis prediction data obtained from the DHT11 temperature sensor which is transmitted by NodeMCU v3 towards Raspberry Pi 3B utilizes the Message Queuing protocol Telemetry Transport (MQTT) will be displayed on a webpage provided by Node-Red Dashboard. The webpage accessible to authorities to take actions needed to deal with forest fires.

The volcanic warning system in Indonesia is divided into four levels namely normal, waspada, siaga and awas. Based on the setting above, a study is needed to design a volcanic activity forecast system using temperature sensors, SO2, CO2 concentration, as well as vibration. The formulation of determining the conditions of volcanic activity is carried out by using fuzzy logic. Volcanic activity measurements are carried out in real time and continuously. Fuzzy logic has been used in the process of determining alert level of volcanic activity based on measured parameters. There are 53 fuzzy rules to determine volcano activity. Best predictions come from the combination of all sensors into a volcano monitoring and forecast system.

Peatland fires in Indonesia have become a serious problem because they cause huge losses. Geographical factors of peatlands in the Kalimantan contribute to the difficullty of conventional fire fighting. The current solution is water bombing using a helicopter. Water bombing is expensive and has a high risk for the safety of fire fighters/helicopter crew so must be done with the correct calculation to fire position so that firefighting can work effectively and efficiently. Therefore, mathematical calculation of the fire position is very important. The position of the fire can be determined by knowing the rate of spread of the fire (Rate of Spread / ROS). In this study aims to calculate the rate of fire in peatlands along the Trans Kalimantan road between Palangka Raya and Pulang Pisau, Central Kalimantan using the simard’s model. Land surface temperature (LST) data were obtained from the TERRA MODIS satellite which was downloaded from the website https://modis.gsfc.nasa.gov/data/dataprod/index.php. The results of the calculations for the five triangles obtained that the ROS are 0.03m/s, 0.04m/s, 0.04m/s, 0.04m/s and 0.03m/s for R1, R2, R3, R4 and R5 respectively. The average of ROS is 0.037m/s with a direction of 32.57 degrees.

Indonesia has the highest number of active volcano all over the world. There were 63 eruptions with more than 70000 casualties from last year eruptions. To minimize the effect of this disaster, we have developed a volcano early warning system for Indonesian volcano. The main part of the system is volcano monitoring system. A system based on Internet of Things (IoT) has been developed to monitor some activities of a volcano. The physical parameters of these activities are indicated by the changing of temperature, gases (sulphur dioxide and carbon dioxide) concentration, vibration and landslides. The system consists of these parameter sensors, a microcontroller, a solar cell and a Long Range Radio (LoRa) for data transmission to the base station. The system has been tested in laboratory environment for the solar cell, sensors and radio communication. The solar cell could generate 18.81 Volt voltage and 0.23 Ampere current. The temperature sensor has been calibrated for until 51°C measurement (volcano normal condition), while the gas sensor could properly detect the gas until 8 ppm according to the calibration result. After Fast Fourier Transform (FFT) analysis the vibration sensor detected almost zero frequency with 0.168 m/s2, 0.0168 m/s2 and 1.125 m/s2 X, Y and Z axis zero offset respectively. In addition, the landslide had maximum about 4° degraded land slope error. Moreover, only 4% (maximum) percentage error rate (PER) shown by the radio for about 400 m data communication. Furthermore, the physical parameter data acquired then be real-time displayed using Node-red dashboard which can be accessed by the user or other parties who need the information.

A finite-element method based on the vector H-field formulation in conjunction with perturbation techniques is used to study metal-clad microwire waveguides for bio-sensing applications. Sensors are designed to detect DNA hybridization through the change of the effective index and attenuation constant of the waveguide structure. The key parameters, such as effective index, loss coefficient, and spot sizes, are presented and potential sensor applications are discussed.

Improvement of tapered fiber sensor by introducing gold thin layer for facilitating surface plasmon resonance (SPR) generation has been studied. The design of structure has been investigated to generate SPR effectively by a finite element method. The particular interest in this problem is the conditions that determine the formation of evanescent field and the interrogation of the transmission intensity change due to the evanescent field absorption. The fabrication of the tapered fiber was conducted by a technique based on flame brushing. The gold nanolayer was then deposited onto the surface of tapered fiber by sputtering technique. Qualitative agreement between the modeling and experiment results found. The results suggest that a compact sensor based on this structure may be useful for biochemical sensors.

We have developed a new volcano early warning system based on sensor node, internet of things (IoT) and UAV to overcome some problems in Indonesian volcano monitoring system. Data (monitored by sensor node) transmission and communication is managed by the IoT while UAV is used for remote sensing data to complete the system to predict the geological status of the volcano. An intelligent-battery UAV is needed for this purpose which manage the power utilization for field application. First stage of the remote sensing process is volcano region mapping for constructing an orthophoto before it is combined with field sensor data. Therefore, we have conducted a laboratory experiment to map some region in ITB, Bandung in different weather as real volcano condition. We have constructed day, night, sunny and cloudy maps of ITB after some data collected through flight and control plan as real volcano environment. Some grid flight plans were chosen for expected result as well as battery saving for each 5 meters data collection. A 3D software has been used for modelling of the orthophoto construction and resulted in 0 – 8 meters error of 20000 – 24000 m2monitored area. Therefore, this method could be used in real volcano application.

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.

The improvement of an external fiber optic sensor both in design and in operational was conducted based on displacement measurement. The purpose of the investigation is to measure the frequency and the amplitude of seismograph signal using the fiber-optic displacement sensor. This sensor setup consists of an optical fiber transmitter, an optical fiber bundle probe, photodiode detector and a seismograph stimulator. The use of stimulator is as a volcano signal model for the testing process. The sensor has the capability to measure the seismograph signal from 0.5 to 1.5 Hz and the linearity is more than 99 %. The proposed sensor is simple, sensitive, provides high dynamic range, and offers lower cost of the fabrication and thus it is suitable to be applied in real field. Furthermore, this sensor generates more excellent result in accuracy and reliability.

Surface enhanced Raman scattering substrate was an alternative analytical tool with ultrahigh sensitivity and rapid response for chemistry, medicine and forensics science. In this work, the surface enhanced Raman scattering (SERS) substrate based on PDMS grating structure created by laser interference lithography using excimer laser modification and further 80 nm-thick Au thin film deposition by dc magnetron sputtering was proposed. We investigated the effect of the grating depth on SERS performance. The methylene blue solution of different concentration was employed to test the SERS performance using the portable Raman spectrometer. The optimal SERS performance can be optimized by fabricating the PDMS grating structure with 850 nm-period, 310 nm-depth and 0.5-filling factor.

Here, we report an efficient approach to optimize the performance of surface enhanced Raman scattering (SERS) substrate. The geometry of the SERS substrate consists of the Au film deposited on polymer grating. The SERS substrate were fabricated by the laser interference lithography (LIL) and magnetron sputtering of Au thin films. The effect of the Au thin film prepared by magnetron sputtering at different deposition time (5-180 s) and operated pressure (3-5 mTorr). The morphology of the obtained samples was observed by field-emission scanning electron microscopy (FE-SEM). The results indicated that optimal SERS substrate with deposition time of 180 s and 3 mTorr-operated pressure was obtained. The limit of detection for methylene blue (MB) and methyl parathion were evaluated at 10-4 M and 10-2 M, respectively. Moreover, our SERS substrate shows the application of a portable Raman spectrophotometer which also promising for on-site pesticide substance detection.

This study develops an ultrasonic sensor system that can be used to determine the number, type, and speed of car vehicles passing a point over some specified time period. The proposed system consists of two ultrasonic sensors and a microcontroller equipped with data logging shield. The data were recorded and then analyzed using a computer program written in Java. Actual experiments that have been conducted indicates that this system can give a correct number of vehicles in a given interval of time.

Simulation, Device exciter, Software LabVIEW It has been made exciter of devices jamming, by using component voltage controled oscilator (vco). It has been done measurements: signal noise,signal sawtooth and level DC voltage at those signals. Being wanted those devices jamming could be raised it’s performance. With helping software LabVIEW being made exciter. Result Simulation are graphic and table relation between input exciter and it’s output. Input exciter are: signal sawtooth, signal noise and level DC voltage that could be changing it’s amplitude. Output exciter are frequency RF, sweeping from frequency f1 to f2 with frequency medium f0. Result simulation could be used for development device jamming

This paper presents the fabrication and simulation of tapered optical fiber. To characterize the properties of these tapered optical fiber sensors, sugar solutions ranging from 0 to 20 in weight percent were utilized. The measured reflection spectra obtained from this SPR sensor shows the observation of a dip originated from the light absorption by the generated surface plasmon wave. The dip reflectance shifts with the increase in the refractive index. A simulation of the experiment was made using OptiFDTD. The simulation and the experiment showed a similar result. The result suggests that a compact sensor based on this structure may be useful for refractive index sensors.