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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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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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Cross-site Scripting Attack Detection Using Machine Learning with Hybrid Features Dimaz Arno Prasetio; Kusrini Kusrini; M. Rudyanto Arief
JURNAL INFOTEL Vol 13 No 1 (2021): February 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i1.606

Abstract

This study aims to measure the classification accuracy of XSS attacks by using a combination of two methods of determining feature characteristics, namely using linguistic computation and feature selection. XSS attacks have a certain pattern in their character arrangement, this can be studied by learners using n-gram modeling, but in certain cases XSS characteristics can contain a certain meta and synthetic this can be learned using feature selection modeling. From the results of this research, hybrid feature modeling gives good accuracy with an accuracy value of 99.87%, it is better than previous studies which the average is still below 99%, this study also tries to analyze the false positive rate considering that the false positive rate in attack detection is very influential for the convenience of the information security team, with the modeling proposed, the false positive rate is very small, namely 0.039%
A double e-shape microstripe antenna design with proximity coupling techniques Lukman Medriavin Silalahi; Imelda Uli Vistalina Simanjuntak; Agus Dendi Rochendi
JURNAL INFOTEL Vol 13 No 4 (2021): November 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i4.608

Abstract

Wireless technology is currently growing along with the increasing need for communication in society. This of course must be supported by better and more efficient device specifications, one of which is the antenna. Microstrip antenna is currently one type of antenna that is widely carried out by lecturers and students because of its shape that can be arranged in such a way that it is expected to be more efficient and practical. In this research, a Double E-shaped microstrip antenna with proximity coupling technique will be designed which will be applied in S-Band services. The S-Band service itself is in the 2-4 GHz frequency range which can serve broadband services. The initial stage of the design takes into account the dimensions of the antenna using the applicable formula to obtain suitable dimensions, then optimization of the feed slot and position of the letter E on the antenna patch uses Ansoft HFSS simulation to obtain the best optimization results. From the design results, it is expected to obtain a microstrip antenna in the form of Double E-shaped with Proximity Coupling technique with a working frequency of 2.5 GHz, a return loss of -18.573 dB, a bandwidth of 144 MHz, a VSWR of 1.265 and a gain of 5.8 dB with the results of the omnidirectional radiation pattern being met as expected.
A New Method of Artificial to Solve the Optimization Problems without the Violated Constraints Jangkung Raharjo; Hermagasantos Zein; Adi Soeprijanto; Kharisma Bani Adam
JURNAL INFOTEL Vol 13 No 2 (2021): May 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i2.624

Abstract

There are some problems in optimization that cannot be derived mathematically. Various methods have been developed to solve the optimization problem with various functional forms, whether differentiated or not, to overcome the problem, which are known as artificial methods such as artificial neural networks, particle swarm optimization, and genetic algorithms. In the literature, it is said that there is an artificial method that frequently falls to the minimum local solution. The local minimum results are proof that the artificial method is not accurate. This paper proposes the Large to Small Area Technique for power system optimization, which works based on reducing feasible areas. This method can work accurately, which that never violates all constraints in reaching the optimal point. However, to conclude that this method is superior to others, logical arguments and tests with mathematical simulations are needed. This proposed method has been tested with 24 target points using ten functions consisting of a quadratic function and a first-order function. The results showed that this method has an average accuracy of 99.97% and an average computation time of 62 seconds. The proposed technique can be an alternative in solving the economic dispatch problem in the power system.
Analysis the impact of sun outage and satellite orbit at performance of the telkom 3S satellite communication system Vi Bauty Riska Utami; Imam MPB; Shinta Romadhona
JURNAL INFOTEL Vol 13 No 3 (2021): August 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i3.626

Abstract

Satellites of communication are located at altitude of thousands kilometers above the earth's surface, so the signal is transmitted by satellite to earth station is very susceptible to interference. Every March and September equinox or when the sun crosses the Earth's equator for several days, earth station occurs a naturally interference called by sun outage. At this time, satellite and the sun reach the closest distance because satellite's position is same direction with the sun. This interference makes the signal received by earth station weaken and even disappears due to temperature noise which increases drastically. Loss of signal on the downlink side caused by noise greatly affects to the performance of satellite communication system. This study aims to analyze the effect of sun outage and satellite orbit to determine sun outage period on the performance of Telkom 3S satellite communication system. The results obtained that indicate the signal quality is represented by degradation in the Carrier to Noise Ratio (C/N) from 14,777 dB to 6,0 dB, Energy bits per Noise Ratio (Eb/No) from 11,515 dB to 2,738 dB, and increase the Bit Error Rate (BER) from 8,29×10-7 to 11,08×10-3. In addition, sun outage makes lost of satellite communication traffic and affecting link availability to 99,855324%. Meanwhile, the result from satellite orbit calculation for sun outage period based on ITU-R S.1525 standard and based by satellite’s handbook. Keywords – Telkom 3S satellite, sun outage, C/N, Eb/No, BER, link availability, sun outage period.
Classification Based on Configuration Objects by Using Procrustes Analysis Ridho Ananda; Agi Prasetiadi
JURNAL INFOTEL Vol 13 No 2 (2021): May 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i2.637

Abstract

Classification is one of the data mining topics that will predict an object to go into a certain group. The prediction process can be performed by using similarity measures, classification trees, or regression. On the other hand, Procrustes refers to a technique of matching two configurations that have been implemented for outlier detection. Based on the result, Procrustes has a potential to tackle the misclassification problem when the outliers are assumed as the misclassified object. Therefore, the Procrustes classification algorithm (PrCA) and Procrustes nearest neighbor classification algorithm (PNNCA) were proposed in this paper. The results of those algorithms had been compared to the classical classification algorithms, namely k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), AdaBoost (AB), Random Forest (RF), Logistic Regression (LR), and Ridge Regression (RR). The data used were iris, cancer, liver, seeds, and wine dataset. The minimum and maximum accuracy values obtained by the PrCA algorithm were 0.610 and 0.925, while the PNNCA were 0.610 and 0.963. PrCA was generally better than k-NN, SVM, and AB. Meanwhile, PNNCA was generally better than k-NN, SVM, AB, and RF. Based on the results, PrCA and PNNCA certainly deserve to be proposed as a new approach in the classification process.
Early Detection of Deforestation through Satellite Land Geospatial Images based on CNN Architecture Nor Kumalasari Caecar Pratiwi; Yunendah Nur Fu'adah; Edwar Edwar
JURNAL INFOTEL Vol 13 No 2 (2021): May 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i2.642

Abstract

This study has developed a CNN model applied to classify the eight classes of land cover through satellite images. Early detection of deforestation has become one of the study’s objectives. Deforestation is the process of reducing natural forests for logging or converting forest land to non-forest land. The study considered two training models, a simple four hidden layer CNN compare with Alexnet architecture. The training variables such as input size, epoch, batch size, and learning rate were also investigated in this research. The Alexnet architecture produces validation accuracy over 100 epochs of 90.23% with a loss of 0.56. The best performance of the validation process with four hidden layers CNN got 95.2% accuracy and a loss of 0.17. This performance is achieved when the four hidden layer model is designed with an input size of 64 × 64, epoch 100, batch size 32, and learning rate of 0.001. It is expected that this land cover identification system can assist relevant authorities in the early detection of deforestation.
Smart card security mechanism with dynamic key N Noprianto; Vivi Nur Wijayaningrum
JURNAL INFOTEL Vol 13 No 4 (2021): November 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i4.652

Abstract

As a currently popular technology, the use of smart cards continues to increase in various fields and the rapid development of technology. Therefore, data security stored on a smart card needs to focus on avoiding misuse of data by unauthorized parties. However, it is not enough for the security mechanism to be carried out only during the communication process of sending data. Then, the mechanism for securing data on the smart card also needs to be done. In this study, a data security technique using dynamic keys is proposed by changing the key and access conditions on the smart card according to predetermined rules. Dynamic keys are a new mechanism proposed to authenticate smart cards using a different key on each card. This technique ensures that the keys used to access each smart card are different so that the risk of data duplication and modification threats can be minimized. In addition, this mechanism is a low-cost security privacy protection. The test results show that the data security technique using dynamic keys ensures that read and write access to the smart card can only be done if the keys match the rules.
Design and Implementation of Smart Parking System Using Location-Based Service and Gamification Based On Internet Of Things Alam Nasyrah Muharram Nasution; Rendy Munadi; Sussi Sussi
JURNAL INFOTEL Vol 13 No 2 (2021): May 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i2.654

Abstract

Information on the number of available parking slot capacity and trip routes to the destination parking area, and motivation in choosing a parking area location are parameters that can help two-wheeled vehicle users choose the right parking area location. The three parameters that determine the accuracy of selecting a parking area location are implemented in an Internet of Things (IoT) based smart parking system. This system can provide information about the maximum number of slot capacities and the number of available slot capacities at the parking area. Two-wheeled riders are given information about which route to take to the destination parking area by utilizing the Location-Based Service (LBS). These two features are then supported by applying the gamification method to motivate two-wheeled riders to choose the right parking area. The smart parking system is tested with considered Quality of Service (QoS) parameter and black box testing. The results of testing the smart parking system produce QoS performance on the Line of Sight (LOS) test, with an average delay is 71.66 ms, average jitter is 107.59 ms, and throughput is 23 kbps. Meanwhile, in the non-LOS test, the average delay is 132.88 ms, the average jitter is 200.84 ms, and the throughput is 12 kbps. Overall system performance obtained the percentage of reliability is 99.65 %, and availability is 99.65 %. In black-box testing, LBS and gamification methods can implement according to application requirements specifications.
Design and Implementation of Robotank for Room Monitoring and Exploration M. Nur Imam DJ; Dadan Nur Ramadhan; Sugondo Hadiyoso
JURNAL INFOTEL Vol 13 No 3 (2021): August 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i3.655

Abstract

A robot is a mechanical device that can perform physical tasks, either autonomously or with human control. Robots began to be used for monitoring in areas that have narrow spaces and/or dangerous areas. So that this robot must be able to carry out monitoring with a remote control system. Therefore, in this study, a robotank is designed that can perform space exploration with remote control. Robotank is designed to use a track and wheel that can pass through various terrains and it has dimensions of 11.8 x 10.8 x 9.1 cm. Robotank is equipped with a camera to monitor in real-time. Robotank can move from one point to another by controlling using a remote control system with a maximum distance of 20 meters in line of sight terrain and 16 meters in non-line of site fields, with an average speed of 0.84 m/s. Robotank can work for 1 hour 52 minutes. With this robotank, it is hoped that it can be used for exploration of areas or rooms that have small spaces and dangerous.
An Evaluation of SVM in Hand Gesture Detection Using IMU-Based Smartwatches for Smart Lighting Control Maya Ameliasari; Aji Gautama Putrada; Rizka Reza Pahlevi
JURNAL INFOTEL Vol 13 No 2 (2021): May 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i2.656

Abstract

Hand gesture detection with a smartwatch can be used as a smart lighting control on the internet of things (IoT) environment using machine learning techniques such as support vector machine (SVM). However, several parameters affect the SVM model's performance and need to be evaluated. This study evaluates the parameters in building an SVM model for hand gesture detection in intelligent lighting control. In this study, eight gestures were defined to turn on and off four different lights, and then the data were collected through a smartwatch with an Inertial Measurement Unit (IMU) sensor. Feature selection using Pearson Correlation is then carried out on 36 features extracted from each gesture data. Finally, two sets of gestures were compared to evaluate the effect of gesture selection on model performance. The first set of gestures show that the accuracy of 10 features compared to the accuracy of 36 features is 94% compared to 71%, respectively. Furthermore, the second set of gestures has an accuracy lower than the first set of gestures, which is 64%. Results show that the lower the number of features, the better the accuracy. Then, the set of gestures that are not too distinctive show lower accuracy than the highly distinctive gesture sets. The conclusion is, in implementing gesture detection with SVM, low data dimensions need to be maintained through feature selection methods, and a distinctive set of gesture selection is required for a model with good performance.

Page 27 of 48 | Total Record : 473

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