Jurnal Infotel (Sekolah Tinggi Teknologi Telematika Telkom Purwokerto)
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392 research outputs found
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Doppler Shift Effect at The Communication Systems with 10 GHz around Building
Full text linkThis research described the Doppler shift effect for the communication systems. The mobile station moves with various velocities around the building’s environment. Doppler’s shift influences the communication systems. The frequency communication was used 10 GHz and its influenced by atmospheric attenuation. This research consisted of propagation with LOS and NLOS conditions, mobile station velocity variation, height buildings variation, and transmitter power variation. This research described frequency maximum at Doppler shift, coherence time, and signal to noise ratio. More increase Doppler shift of coherence time caused signal noise ratio to decrease.This research described the Doppler shift effect for the communication systems. The mobile station moves with various velocities around the building’s environment. Doppler’s shift influences the communication systems. The frequency communication was used 10 GHz and its influenced by atmospheric attenuation. This research consisted of propagation with LOS and NLOS conditions, mobile station velocity variation, height buildings variation, and transmitter power variation. This research described frequency maximum at Doppler shift, coherence time, and signal to noise ratio. More increase Doppler shift of coherence time caused signal noise ratio to decrease
Fitur Seleksi pada Data Microarray untuk Deteksi Kanker Berdasarkan Klasifikasi Random Forest
No full textCancer is a disease that can affect all organs of humans. Based on data from the World Health Organization (WHO) fact sheet in 2018, cancer deaths have reached 9.6 million. One known way to detect cancer that is with Microarray Technique, but the microarray data have large dimensions due to the number of features that are very much compared to the number of samples. Therefore, dimension reduction should be made to produce optimum accuracy. In this paper, we compare Minimum Redundancy Maximum Relevance (MRMR) and Least Absolute Shrinkage and Selection Operator (LASSO) to reduce the dimension of microarray data. Moreover, by using Random Forest (RF) Classifier, the performance of classification (cancer detection) is compared. Based on the simulation, it can be concluded that LASSO is better than MRMR because it can produce an evaluation of 100% in lung and ovarian cancer, 92% colon cancer, 93% prostate tumor, and 83% central nervous system.Cancer is a disease that can affect all organs of humans. Based on data from the World Health Organization (WHO) fact sheet in 2018, cancer deaths have reached 9.6 million. One known way to detect cancer that is with Microarray Technique, but the microarray data have large dimensions due to the number of features that are very much compared to the number of samples. Therefore, dimension reduction should be made to produce optimum accuracy. In this paper, we compare Minimum Redundancy Maximum Relevance (MRMR) and Least Absolute Shrinkage and Selection Operator (LASSO) to reduce the dimension of microarray data. Moreover, by using Random Forest (RF) Classifier, the performance of classification (cancer detection) is compared. Based on the simulation, it can be concluded that LASSO is better than MRMR because it can produce an evaluation of 100% in lung and ovarian cancer, 92% colon cancer, 93% prostate tumor, and 83% central nervous system
Navigating Bitcoin Panic-Selling using Linear Approach
Full text linkCOVID-19 affects significant human activity around the globe, including Bitcoin prices. The Bitcoin price is well known for its volatility, so it is not a big shocker when the panic-selling occurs during the pandemic. However, the mechanism to cope with these breakouts, especially the bearish one, is contentious. The experts give numerous pieces of advice with different conclusions in the end. It is also the same with Machine Learning. Various kernels show different results regarding how the price will move. It depends on the window size, how the data is being preprocessed, and the algorithm used. This paper inspects the best combination that various machine learning can offer with a linear approach to navigate the price prediction based on its depth interval, window size until the algorithms themselves. This paper also proposed a new approach to seeing the prediction range called s-steps ahead prediction using a linear model. The result shows that simple machine learning can herd 99.715% profit even during the bearish breakout.COVID-19 affects significant human activity around the globe, including Bitcoin prices. The Bitcoin price is well known for its volatility, so it is not a big shocker when the panic-selling occurs during the pandemic. However, the mechanism to cope with these breakouts, especially the bearish one, is contentious. The experts give numerous pieces of advice with different conclusions in the end. It is also the same with Machine Learning. Various kernels show different results regarding how the price will move. It depends on the window size, how the data is being preprocessed, and the algorithm used. This paper inspects the best combination that various machine learning can offer with a linear approach to navigate the price prediction based on its depth interval, window size until the algorithms themselves. This paper also proposed a new approach to seeing the prediction range called s-steps ahead prediction using a linear model. The result shows that simple machine learning can herd 99.715% profit even during the bearish breakout
Performance Analysis of FBMC O-QAM System Using Varied Modulation Level
Full text linkCommunication channels that are affected by various disturbances will cause a high Bit Error Rate (BER). To maximize the performance of the channel in the future, Filter Bank Multicarrier (FBMC) technique is used as a renewal of Orthogonal Frequency Division Multiplexing (OFDM). FBMC has better spectrum efficiency properties due to the nature of orthogonality which only divides bandwidth for sub-channels. The purpose of the research was to knowing the performance of FBMC Offset QAM (FBMC O-QAM) which has a variation of modulation levels of 4-QAM, 16-QAM, and 64-QAM. The Zero Forcing (ZF) method is used to detect the original signal sent by the transmitting antenna. System performance in this study was measured by parameter Bit Error Rate (BER) and channel capacity. The results showed that the FBMC O-QAM system with ZF has decreased BER value on each modulation. At the time of modulation 4 QAM has a BER value of 0.0008945 with an SNR value of 20 dB. Modulation 16 QAM also experienced the same thing when the SNR value of 20 dB has BER value of 0.001856, and at modulation 64 QAM has BER value of 0.01766 at a SNR of 20 dB. Besides decreasing the BER parameters, the FBMC O-QAM ZF system has own characterize in channel capacity. For the 4-QAM has 4.808 b/s/Hz, 16-QAM has 4.627 b/s/Hz, and 64-QAM has 3.903 b/s/Hz at SNR 20 dB. It conclude that 4-QAM has a best channel capacity enhancement. The value of channel capacity generated based on simulations using Zero Forcing shows an increase in value along with an increase in SNR, but has a smaller value compared to channel capacity in theory
The Newton’s Polynomial Based - Automatic Model Generation (AMG) for Sensor Calibration to Improve the Performance of the Low-Cost Ultrasonic Range Finder (HC-SR04)
Full text linkThe ultrasonic range finder sensors is a general-purpose sensor to measure the distance contactless. This sensor is categorized as a low-cost sensor that is widely used in various applications. This sensor has a significant deviation that leads to significant errors in the measurement result. The error produced by this sensor tends to increase proportionally to the measured distance. The implementation of a particular algorithm is required to reduce the error value. The model-based calibration is a solution to increase accuracy. The model-based solutions are no longer feasible if the states of the model have changed. The length of the usage of the sensor leads to sensor fatigue. Sensor fatigue is one of the causes of model state changes. If the drift is still within the tolerance limit, the sensor performance can still be restored using the calibration method. The model-based calibration calibrates the sensor by using the model. The update of the model must be made whenever the changing of the model state occurred. Since the manual model-making process is not an easy task, time, and cost required, then the Newton polynomial-based (Automatic Model Generation (AMG) has been implemented in this research. The AMG algorithm generates the new sensor model automatically based on the most updated states. This automatic model generation is implemented in the calibration process of the ultrasonic sensor. The implementation of a polynomial-based AMG algorithm for sensor calibration has been succeeded in improving the calibrated sensor’s accuracy by 96.4% and reducing the MSE level from 25.6 to 0.914The ultrasonic range finder sensors is a general-purpose sensor to measure the distance contactless. This sensor is categorized as a low-cost sensor that is widely used in various applications. This sensor has a significant deviation that leads to significant errors in the measurement result. The error produced by this sensor tends to increase proportionally to the measured distance. The implementation of a particular algorithm is required to reduce the error value. The model-based calibration is a solution to increase accuracy. The model-based solutions are no longer feasible if the states of the model have changed. The length of the usage of the sensor leads to sensor fatigue. Sensor fatigue is one of the causes of model state changes. If the drift is still within the tolerance limit, the sensor performance can still be restored using the calibration method. The model-based calibration calibrates the sensor by using the model. The update of the model must be made whenever the changing of the model state occurred. Since the manual model-making process is not an easy task, time, and cost required, then the Newton polynomial-based (Automatic Model Generation (AMG) has been implemented in this research. The AMG algorithm generates the new sensor model automatically based on the most updated states. This automatic model generation is implemented in the calibration process of the ultrasonic sensor. The implementation of a polynomial-based AMG algorithm for sensor calibration has been succeeded in improving the calibrated sensor’s accuracy by 96.4% and reducing the MSE level from 25.6 to 0.91
A Development of Low Cost Wi-Fi Robot for Teaching Aid
Full text linkA low-cost Wi-Fi robot as a teaching equipment is developed. The robot can be used to teach students in the subjects related to robotics system and internet of things (IoT). A Wi-Fi robot is a robot equipped with a Wi-Fi communication system for connecting to the internet. Integrating the robot with an IoT platform makes the robot able to communicate with other devices. The developed Wi-Fi robot in this study is a three-wheeled robot type. A NodeMCU ESP-12, which is a microcontroller equipped with Wi-Fi module, is applied in the robot. The robot is connected to the Blynk IoT platform and paired to a smartphone. It results in communication between the robot and the smartphone through the internet. The communication is demonstrated by remotely operating the robot using the smartphone. Mechanical structure and electronic wiring of the robot are simple such that the robot is easily built. Moreover, the cost of required components for building the robot is quite cheap as less than USD 20.A low-cost Wi-Fi robot as a teaching equipment is developed. The robot can be used to teach students in the subjects related to robotics system and internet of things (IoT). A Wi-Fi robot is a robot equipped with a Wi-Fi communication system for connecting to the internet. Integrating the robot with an IoT platform makes the robot able to communicate with other devices. The developed Wi-Fi robot in this study is a three-wheeled robot type. A NodeMCU ESP-12, which is a microcontroller equipped with Wi-Fi module, is applied in the robot. The robot is connected to the Blynk IoT platform and paired to a smartphone. It results in communication between the robot and the smartphone through the internet. The communication is demonstrated by remotely operating the robot using the smartphone. Mechanical structure and electronic wiring of the robot are simple such that the robot is easily built. Moreover, the cost of required components for building the robot is quite cheap as less than USD 20
Simulasi Efek Jumlah Event Terhadap Respon Energi TLD LiF: Mg, Cu, P
No full textThe effect of different number of events on the bare thermoluminescent dosimeter (TLD) LiF:Mg,Cu,P chip energy response has been simulated using Geant4. This simulation aims to determine the optimum number of events with a minimum computational time. 14 photon energies in a range of 16–1250 keV with a range number of events 2×107 – 2×1012 were applied. A LiF: Mg, Cu, P chip with 4.5 mm diameter and 0.9 mm thick on the surface of 30×30 cm2 water phantom and a thin 10 µm slice of water (at 10 mm deep in the phantom) were considered as the sensitive volumes to calculate the respective absorbed dose DTLD and DW. The relative energy response R was calculated from the ratio of DTLD and DW for each energy normalised to DTLD and DW ratio of energy 662 keV. 2×109 number of events were found to be the optimum number of events with a minimum computational time.The simulation results were validated to the measurement results and the mean deviation of 0,59% was yielded. As the deviation are within the acceptable limit of ±25%, it was concluded that the results were considered satisfactory and the materials and physics processes applied in the code were correct