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Eko Fajar Cahyadi
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Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) Institut Teknologi Telkom Purwokerto Jl. D. I. Panjaitan, No. 128, Purwokerto 53147, Indonesia
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INDONESIA
Jurnal INFOTEL
Published by Universitas Telkom
ISSN : 20853688     EISSN : 24600997     DOI : https://doi.org/10.20895/infotel.v15i2
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Jurnal INFOTEL is a scientific journal published by Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) of Institut Teknologi Telkom Purwokerto, Indonesia. Jurnal INFOTEL covers the field of informatics, telecommunication, and electronics. First published in 2009 for a printed version and published online in 2012. The aims of Jurnal INFOTEL are to disseminate research results and to improve the productivity of scientific publications. Jurnal INFOTEL is published quarterly in February, May, August, and November. Starting in 2018, Jurnal INFOTEL uses English as the primary language.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 473 Documents
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Prototype of Long-Range Radio Communication for e-Nelayan Devices using LoRaWAN Febri Dawani; Syifaul Fuada; Sinantya Feranti Anindya; Aditia Rifai; Erick Adinugraha; Irfan Gani Purwanda; Trio Adiono
JURNAL INFOTEL Vol 10 No 4 (2018): November 2018
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v10i4.411

Abstract

In this paper, development progress of a long-range radio communication-based fishing assistant system called e-Nelayan is reported. The purpose of the system is to increase the productivity, safety, and welfare of fishermen using mobile phone and long-range radio based system that enables them to report maritime violations, access and exchange information regarding weather, fishing area, marketplace, and also communication with mainland using Android-based mobile phone within extended range. We used LoRaWAN as a base technology for long-range communication scheme. In this work, the test conducted to obtain an insight to e-Nelayan device (LoRa-based) received RSSI and its packet loss. The received data collected in a server also includes the GPS tracking data. The test results show that our system reached approximately 5 km of distance between end-node to the LoRa Gateway within urban area (LoS configuration) and about 2 km for NLOS configuration.
The Newton’s Polynomials Interpolation Based-Error Correction Method for Low-Cost Dive Altitude Sensor in Remotely Operated Underwater Vehicle (ROV) Gandha, Gutama Indra; Nurcipto, Dedi
JURNAL INFOTEL Vol 11 No 1 (2019): February 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i1.419

Abstract

Indonesia is the one of the countries with the largest of sea area. However, the water surveillance categorized as minimum. The human resource and the low level of infrastructure are the causal of the minimum level of water surveillance. The human involvement of water surveillance has many weaknesses, such as weak against the change of the nature condition, limitation in reaching location, weak against water turbidity levels and water pollution. The utilization of ROV (Remotely Operated Underwater Vehicle) could be a solution in water surveillance problem. The development of ROV still not significant in Indonesia. The development costs are also a problem in development of ROV. Many researcher using USBL (Ultra Short Base Line) sensor to sense the depth of the ROV. However, the cost of this sensor is relatively expensive. The usage of low-cost pressure sensor could be a solution to replace the USBL sensor. The low-cost pressure sensor has a significant deviation. The implementation of Newton’s polynomials interpolation algorithm has been used to decrease the deviation level of the sensors. The result shows the algorithm has succeeded to decrease the deviation level of the pressure sensor significantly. The MSE value of default sensor was 42956.2, which is significantly worst. The Newton interpolation algorithm has been succeeded to reducing the MSE value to 17.82. The result of this research was expected to reduce the cost of the ROVs development especially for sensors cost.
Web of Thing Application for Monitoring Precision Agriculture Using Wireless Sensor Network Nurul Fahmi; Eko Prayitno; Siti Fitriani
JURNAL INFOTEL Vol 11 No 1 (2019): February 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i1.421

Abstract

Wireless Sensor Network (WSN) is a technology which can help humans solve problems in daily life for monitoring the environment. This can be done to help farmers in monitoring and making decisions for watering plants. In this study, temperature, humidity and soil moisture sensors were used to help farmers monitor web-based precision agriculture, and the system which be built could make a decision to automatically water plants based on soil conditions. The results of measuring precision agriculture from the sensor node will be sent to the gateway using Zigbee 802.15.4. The data will be stored in the MySQL database provided by the gateway. Then it will be synchronized to the cloud using IoT technology, so users can access it in real time by using web-based application. From the system which is developed, it really helps farmers to complete their work and make innovation in the digital era.
Performance Analysis Of Firewall As Virtualized Network Function On VMware ESXi Hypervisor Ahmad Thoriq Azzam; Rendy Munadi; Ratna Mayasari
JURNAL INFOTEL Vol 11 No 1 (2019): February 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i1.425

Abstract

Virtualization technology is slowly being used to build network infrastructure called Network Function Virtualization (NFV). It takes network functions such as firewall, load balancer, IPS out of its hardware then uses its software to be run on high specification server. It helps to reduce vendor lock-in and creates a multiplatform network function environment for telecommunication or Internet Service Provider (ISP) company. It has a lot of benefits compared to a traditional network. One of them is reducing the number of hardware that is used in the telecom industry. This technology runs on the hypervisor that is used for the hardware management. One of the important components from NFV is Virtualized Network Function (VNF). In NFV, network devices are run on a server so that a firewall is needed. If an attack occurs on the network, it will interfere the existing network components. This paper focuses on analyzing the performance of two firewall systems: pfSense, and FortiGate. Both firewalls run on the VMware ESXi hypervisor. It compares the firewall performance in normal conditions without attacks and under SYN DoS attacks. Besides, firewall failover capabilities are evaluated. Based on the overall testing results, FortiGate has better performance than pfSense. It has better ability in handling DoS SYN attack because of lower throughput performance degradation and better FTP performance. It is concluded that FortiGate has best performance if it is compared to pfSense.
Estimation of Atmospheric Water Vapor from ANFIS Technique and Its Validation with GPS Data Wayan Suparta; Kemal Maulana Alhasa
JURNAL INFOTEL Vol 11 No 1 (2019): February 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i1.426

Abstract

Adaptive neuro-fuzzy inference system (ANFIS) is a prospective approach in modeling weather parameters based on learning from historical data used. This study presented the comparison of tropospheric precipitable water vapor (PWV) between ANFIS and Global Positioning System (GPS) for areas in Pekan, Pahang, Malaysia. The PWV value was estimated with the ANFIS model with the surface meteorological data as inputs. The accuracy of PWV from ANFIS has been validated with PWV from GPS measurements for the period of 2010. The result showed that the ANFIS PWV has a similar trend with the GPS PWV (r = 0.999 at the 99% confidence level) and found a difference of 0.024%. The PWV from ANFIS was calculated 0.035% higher compared to GPS PWV and found a similar character in two seasonal monsoons. This indicates that the PWV obtained with ANFIS model agreed very well with GPS measurements and it can be implemented to monitor atmospheric variability as well as climate change studies in the absence of GPS data.
Stateless Authentication with JSON Web Tokens using RSA-512 Algorithm Alam Rahmatullo; Aldy Putra Aldya; Muhammad Nur Arifin
JURNAL INFOTEL Vol 11 No 2 (2019): May 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i2.427

Abstract

Today's technology needs are getting higher, one of the technologies that continues to grow now is Web Service (WS). WS can increase service flexibility on a system. However, security at WS is one of the things that needs attention. One effort to overcome this problem is JWT (JSON Web Token). JWT is one of the authentication mechanisms in WS, with a standard signature algorithm, HMAC SHA256, RSA-256 or ECDSA. In this research we will discuss the performance of JWT RSA-512 which is implemented on SOAP and RESTful. Because based on previous research the speed performance of the 512-bit algorithm is better, but it is not yet known if applied to JWT. The test results show that the speed of the JWT RSA-512 token on the RESTful process is superior to 24.69% compared to SOAP. Then the speed of the authentication of JWT RSA-512 tokens, RESTful is superior to 11.64% compared to SOAP. Whereas in testing the size of JWT RSA-512 generated tokens, RESTful is only 1.25% superior to SOAP.
Maize Leaf Disease Image Classification Using Bag of Features Wahyudi Setiawan; Mohammad Syarief; Novi Prastiti
JURNAL INFOTEL Vol 11 No 2 (2019): May 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i2.428

Abstract

Image classification is an image grouping based on similarities features. The features extraction stage is a crucial factor for classifying an image. In the conventional image classification, the features commonly used are morphology, color, and texture with various derivative features. The type and number of appropriate features will affect the classification results. In this study, image classification by using the Bag of Features (BOF) method which can generate features automatically. It consists of 4 stages: feature point location by using grid method, feature extraction by using Speed Up Robust Feature (SURF), clustering word-visual vocabularies by using k-means, and classification by using Support Vector Machine (SVM). The classification data are maize leaf images from the PlantVillage-Dataset. The data consists of 3 types of images: RGB, grayscale, and segmentation images. Each type includes four classes: healthy, Cercospora, common rust, and northern leaf blight. There are 50 images for each class. We used two scenarios of testing for each type of data: training and validation, 70% and 80% images for training, and the rest for validation. Experimental results showed that the validation accuracies of RGB, grayscale, and segmentation images were 82%, 77%, and 85%.
Optimal Control Design of Active Suspension System Based on Quarter Car Model Nur Uddin
JURNAL INFOTEL Vol 11 No 2 (2019): May 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i2.429

Abstract

The optimal control design of the ground-vehicle active suspension system is presented. The active suspension system is to improve the vehicle ride comfort by isolating vibrations induced by the road profile and vehicle velocity. The vehicle suspension system is approached by a quarter car model. Dynamic equations of the system are derived by applying Newton’s second law. The control law of the active suspension system is designed using linear quadratic regulator (LQR) method. Performance evaluation is done by benchmarking the active suspension system to a passive suspension system. Both suspension systems are simulated in computer. The simulation results show that the active suspension system significantly improves the vehicle ride comfort of the passive suspension system by reducing 50.37% RMS of vertical displacement, 45.29% RMS of vertical velocity, and 1.77% RMS of vertical acceleration.
Breast Cancer Detection using Residual Convolutional Neural Network and Weighted Loss Samuel Aji Sena; Panca Mudjirahardjo; Sholeh Hadi Pramono
JURNAL INFOTEL Vol 11 No 2 (2019): May 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i2.430

Abstract

This research presents a breast cancer detection system using deep learning method. Breast cancer detection in a large slide of biopsy image is a hard task because it needs manual observation by a pathologist to find the malignant region. The deep learning model used in this research is made up of multiple layers of the residual convolutional neural network, and instead of using another type of classifier, a multilayer neural network was used as the classifier and stacked together and trained using end-to-end training approach. The system is trained using invasive ductal carcinoma dataset from the Hospital of the University of Pennsylvania and The Cancer Institute of New Jersey. From this dataset, 80% and 20% were randomly sampled and used as training and testing data respectively. Training a neural network on an imbalanced dataset is quite challenging. Weighted loss function was used as the objective function to tackle this problem. We achieve 78.26% and 78.03% for Recall and F1-Score metrics, respectively which are an improvement compared to the previous approach.
Investigation of Human Emotion Pattern Based on EEG Signal Using Wavelet Families and Correlation Feature Selection Dwi Utari Surya; Ponco Siwindarto; Erni Yudaningtyas
JURNAL INFOTEL Vol 11 No 2 (2019): May 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i2.431

Abstract

Emotions is one of the advantages given by God to human beings compared to other living creatures. Emotions have an important role in human life. Many studies have been conducted to recognize human emotions using physiological measurements, one of which is Electroencephalograph (EEG). However, the previous researches have not discussed the types of wavelet families that have the best performance and canals that are optimal in the introduction of human emotions. In this paper, the power features of several types of wavelet families, namely Daubechies, symlets, and coiflets with the Correlation Feature Selection (CFS) method to select the best features of alpha, beta, gamma and theta frequencies. According to the results, coiflet is a method of the wavelet family that has the best accuracy value in emotional recognition. The use of the CFS feature selection can improve the accuracy of the results from 81% to 93%, and the five most dominant channels in the power features of alpha and gamma band on T8, T7, C5, CP5, and TP7. Hence, it can be concluded that the temporal of the left brain is more dominant in recognition of human emotions.

Page 22 of 48 | Total Record : 473

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