JURNAL INFOTEL 2022-01-21T09:37:34+00:00 Danny Kurnianto Open Journal Systems <h2>About Jurnal INFOTEL</h2> <table border="0"> <tbody> <tr> <td><img src="" alt="telecommunication journal" width="180" height="250"></td> <td align="justify" valign="top"> <div style="background-color: #ebfeec; border: 1px solid #bae481; border-radius: 5px; text-align: justify; padding: 10px; font-family: sans-serif; font-size: 14px; margin-left: 10px;">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 <strong>informatics, telecommunication, and electronics</strong>. 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. <strong>Starting in 2018, Jurnal INFOTEL uses English as the primary language..</strong></div> </td> </tr> </tbody> </table> <h4><strong><span style="text-decoration: underline; color: #ff0000;">Call for Editors and Reviewers</span></strong></h4> <div style="text-align: justify;"> <p>We invite researchers, scientists, and practitioners to become editors or reviewers in Jurnal INFOTEL. If you are interested, please send us information about yourself, such as your full name, education and degree, affiliation, Scopus ID, orcid ID or other researcher ID, and the area of expertise. Send your biodata via the link below.</p> <p><a href=""><strong>Register for Editor and Reviewer</strong></a><br>Thank you.</p> <h4><strong>Important For Authors</strong></h4> <p>Reminder for all the authors, you are expected to submit papers that:<br> 1. are original and have not been submitted to any other publication.<br> 2. have at least 15 references with 80% of scientific Journals.<br> 3. use references published on the last 5 years.<br> 4. structured using IMRaD format.<br> 5. use template specified by Jurnal INFOTEL.<br> 6. use reference manager e.g. Mendeley or others when managing the references.<br>Thank you</p> <p>&nbsp;</p> </div> Optimization of software defects prediction in imbalanced class using a combination of resampling methods with support vector machine and logistic regression 2022-01-21T09:37:34+00:00 Windyaning Ustyannie Emy Setyaningsih Catur Iswahyudi <p>The main problem in producing high accuracy software defect prediction is if the data set has an imbalance class and dichotomous characteristics. The imbalanced class problem can be solved using a data level approach, such as resampling methods. While the problem of software defects predicting if the data set has dichotomous characteristics can be approached using the classification method. This study aimed to analyze the performance of the proposed software defect prediction method to identify the best combination of resampling methods with the appropriate classification method to provide the highest accuracy. The combination of the proposed methods first is the resampling process using oversampling, under-sampling, or hybrid methods. The second process uses the classification method, namely the Support Vector Machine (SVM) algorithm and the Logistic Regression (LR) algorithm. The proposed, tested model uses five NASA MDP data sets with the same number attributes of 37. Based on the t-test, the &nbsp;&lt; &nbsp;= 0.0344 &lt; 0.05 and the &nbsp;&gt; &nbsp;= 3.1524 &gt; 2.7765 which indicates that the combination of the proposed methods is suitable for classifying imbalanced class. The performance of the classification algorithm has also improved with the use of the resampling process. The average increase in AUC values using the resampling in the SVM algorithm is 17.19%, and the LR algorithm is at 7.26% compared to without the resampling process. Combining the three resampling methods with the SVM algorithm and the LR algorithm shows that the best combining method is the oversampling method with the SVM algorithm to software defects prediction in imbalanced class with an average accuracy value of 84.02% and AUC 91.65%.</p> 2021-12-09T00:00:00+00:00 ##submission.copyrightStatement## Breast cancer recurrence prediction system using k-nearest neighbor, naïve-bayes, and support vector machine algorithm 2022-01-17T02:16:54+00:00 I Ketut Agung Enriko Melinda Melinda Agnesia Candra Sulyani I Gusti Bagus Astawa <p class="Abstract"><span lang="EN-US" style="font-weight: normal;">Breast cancer is a serious disease and one of the most fatal diseases in the world. Statistics show that breast cancer is the second common cancer worldwide with around two million new cases per year. Some research has been done related to breast cancer, and with the advancements of technology, breast cancer can be detected earlier by using artificial intelligence or machine learning. There are popular machine learning algorithms that can be used to predict the existence or recurrence of breast disease, for example, k-Nearest Neighbor (kNN), Naïve Bayes, and Support Vector Machine (SVM). This study aims to check the prediction of breast cancer recurrence using those three algorithms using the dataset available at the University of California, Irvine (UCI). The result shows that the kNN algorithm gives the best result in terms of accuracy to predict breast cancer recurrence.</span></p> 2021-12-09T00:00:00+00:00 ##submission.copyrightStatement## Automatic detection of covid-19 based on CT Scan images using the convolution neural network 2021-12-29T05:53:29+00:00 Mawaddah Harahap Masdiana Damanik Linda Wati Wahyudi Valentino Simamora Isnaeni Khairani Sipahutar Amir Mahmud Husein <p>The 2019 coronavirus pandemic (Covid-19) has been declared a health emergency by WHO with the death rate steadily increasing worldwide, various efforts have been made to deal with this pandemic, from prediction to receiving medical imaging. CT Scan and chest X-Ray images have been proven to be accurate to help medical personnel diagnose COVID, in this paper, we propose a convolutional neural network (CNN) approach and the DenseNet transfer learning model series which aims to understand and find the best classification for COVID or Non-COVID detection. On CT scan chest images, we made two special models in the Descent series, then compared the CNNs in both models by calculating the Accuracy, Precision, Recall, and F1-Score values and presented the results in the confusion matrix. The testing framework is carried out on CNN and the first model of the DenseNet series uses adam optimization, the input function is 244x244x3, the soft-max function is applied as an activity with losses across entropy categories, epoch 50, and batch size for training and testing 16 while validation uses batch size 8, the EarlyStopping function also determined, From the test results, the CNN model is superior to the Densenet series of the first model with an accuracy of about 0.76 (76%), when testing the second model, we carried out the shifting, zooming process and changed the input function to 64x64x3, epoch 30 by adding 4 layers. The second model approach produces better accuracy than CNN and the first DenseNet series, but not as good as expected, based on the test results on the second model produces an accuracy of 0.90 (90%) on Densenet169, Densenet121 around 0.88 (88%) and last Densenet201 is about 0.83 83%), so it is superior to simple CNN models</p> 2021-12-09T13:11:38+00:00 ##submission.copyrightStatement## Smart card security mechanism with dynamic key 2021-12-29T06:16:56+00:00 N Noprianto Vivi Nur Wijayaningrum <p>As a technology that is currently popular, the use of smart cards continues to increase in various fields along with the rapid development of technology. Data security stored on a smart card needs to be a focus of attention to avoid misuse of data by unauthorized parties. It is not enough for the security mechanism to be carried out only during the communication process of sending data, but 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. 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 read and write access to the smart card can only be done if the keys used match the rules.</p> 2021-12-09T13:12:20+00:00 ##submission.copyrightStatement## Designing a Microcontroller-based Half-duplex Interface Device Drove by the Touch-tone Signal 2021-12-09T13:10:09+00:00 Arief Goeritno Ika Setyawibawa Dwi Suhartono <p><strong>The two Arduino boards (UNO R3 and MEGA2560 R3) have been constructed as the electronic modules of the gateway are become a haft-duplex adapter or can be referred to as the interface device for communicating (IDC). The IDC system drove by the touch-tone signal. The</strong><strong>&nbsp;research objectives, i.e. assembly some of the hardware for the embodiment of the half-duplex interface adapter system, make a program structure, and perform a test of verification used in the modules of the gateway. The embodiment has been carried out by integrating all of the components by wiring to form an embedded system. Programming of the Arduino system is carried out by six stages of the algorithm, namely pins configuration, declaration of variables and constants, initialization, the main program, retrieve and send data, and output. The programming syntax structure is based on the Arduino software. The test of verification is carried out in the form of a simulation. The simulation results are obtained for six conditions, namely (i) simulation of the circuit of ring detection, (ii) simulation of the circuit of voice-operated transmit, (iii) simulation of the circuit off/on the hook of the telephone module, (iv) simulation of the circuit of tone decoder, (v) simulation of dial-up telephone numbers via touch-tone push buttons and switching IC circuits, and (vi) simulation of circuits of voice recorder and storage in the form of voice recording and playback. The success of the verification test with six conditions has been an indication that the Arduino-based IDC system is functioning as expected.</strong></p> 2021-12-09T12:59:20+00:00 ##submission.copyrightStatement## All-In-One Computation vs Computational-Offloading Approaches: A Performance Evaluation of Object Detection Strategies on Android Mobile Devices 2022-01-08T10:27:45+00:00 Muhammad Abdullah Rasyad Favian Dewanta Sri Astuti <p>Object detection gives a computer ability to classify certain objects in an image or video. However, to get good performance speed, the device’s specifications running object detection should be appropriately high. To enable device with low specification perform better, one way is offloading the computation process from a device with a low specification to another device with better specifications. This paper investigates the performance of object detection strategies on all-in-one Android mobile phone computation versus Android mobile phone computation with computational offloading on Nvidia Jetson Nano.&nbsp; The experiment carries out the video surveillance from the Android mobile phone with two scenarios, which are all-in-one object detection computation in a single Android device and decoupled object detection computation between an Android device and an Nvidia Jetson Nano. The video is sent by the Android application as an input for object detection using RTSP/RTMP streaming protocol and received by Nvidia Jetson Nano which acts as an RTSP/RTMP server. Then, the output of object detection is sent back to the Android device for being displayed to the user. The results show that the android devices Huawei Y7 Pro who has an average FPS performance of 1.98 and an average computing speed of 180 ms improves significantly when working with the Nvidia Jetson Nano, the average FPS become 10 and average computing speed become 95 ms. It means decoupling object detection computation between an Android device and an Nvidia Jetson Nano using the system provided in this paper successfully improve the detection speed performance.</p> 2021-12-09T13:10:55+00:00 ##submission.copyrightStatement## Simple Methods for Coverage Prediction of the Digital Trunking Radio Communication System 2021-12-29T06:11:51+00:00 Arief Goeritno Ika Setyawibawa Dwi Suhartono <p>This paper describes a radio communication infrastructure based on digital trunking radio communication system for coverage prediction for independent/private use. The objectives of this study include (1) connectivity between the repeater and radio devices and (2) simulation of radio signal coverage prediction and observation of communication performance. The connection method between the repeater device and the radio is in the form of tuning five main parameters, namely -transmitter (Tx) and receiver (Rx) frequencies, -user ID, -IP address for each site, -channel trunking mode, and –talk group ID. Simulation-based is used for predicting radio signal coverage area for repeater system based on Digital Radio Mobile (DMR) application and observation of the communication performance. Tuning on the repeater system, namely -Tx and Rx frequencies, -user ID, -talk group ID, -power on the Simoco SDB680XD repeater, and -sys code; while on radio equipment, namely, -Tx and Rx frequencies, -use of sys code, -talk up ID, and -radio ID. Prediction and observation of the coverage area based on several parameters as input, namely -type of area for radio system operation, -the type and specifications of the antenna used, -losses arising from the presence of cables and cable connector connections, -the coordinates of the installation of the transmitter station or the placement of the repeater, longitude, and latitude, -the height of the transmitting station or repeater antenna in meters, -radio receiver sensitivity in dB, and -the power used in the repeater and radio receiver in watts. The simulation results are in the form of a screenshot with a area coverage of ​​140,938 kilometers. Based on observations of communication performance on radio communication systems through the use of dummy loads, namely group calls, individual calls, and emergency calls. The observations-based results, the system is well connected.</p> 2021-12-09T13:11:59+00:00 ##submission.copyrightStatement## A double e-shape microstripe antenna design with proximity coupling techniques 2021-12-26T23:08:27+00:00 Lukman Medriavin Silalahi Imelda Uli Vistalina Simanjuntak, IUVS Agus Dendi Rochendi, ADR <p>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.</p> 2021-12-09T13:12:40+00:00 ##submission.copyrightStatement## Evaluation of MVNO model implementation in remote and border areas using the consistent fuzzy preference relations method 2022-01-08T10:30:02+00:00 Anggun Fitrian Isnawati Ridwan Pandiya Ade Wahyudin <p>Law No. 36 of 1999 concerning Telecommunication has brought many changes, especially in the development of telecommunications infrastructure in Indonesia. However, the penetration of telecommunications services in the forefront, outermost, and backward regions is still relatively low. The government has made various efforts in terms of minimizing the gap in telecommunication services between urban and rural areas through various programs. However, an acceleration is needed so that the service disparity can be immediately overcome. One of the telecommunications products that can be applied to overcome these barriers is the Mobile Virtual Network Operator (MVNO). This study evaluates the most appropriate type of MVNO model to be applied in Indonesia by implementing the Consistent Fuzzy Preference Relations (CFPR) method. This method is able to accommodate expert opinion through a series of scientific steps so as to produce weights for each alternative type of MVNO model. The results obtained are that the most appropriate model to be applied in Indonesia by taking into account the criteria given. The implementation of this model is expected to be able to encourage the optimization of BTS USO that has been declared by the government.</p> 2021-12-09T13:13:07+00:00 ##submission.copyrightStatement## Fuzzy based sensorless tracking controller on the dual-axis PV panel for optimizing the power production 2021-12-29T06:23:13+00:00 Bandiyah Sri Aprilia Muhammad Zakiyullah Romdlony Jangkung Raharjo Yogi Ghifari Sidik <p class="Abstract">In general active sun trackers move because they respond to light sensors that measure the intensity of sunlight. However, sensor based trackers are usually more expensive than sensor less trackers. In addition, based on several studies, a comparison between sensor and sensorless based tracker only reports lower tracking error and higher power generation for sensor based than sensorless tracker but does not include an analysis of energy use on the sensor. Therefore, this study aims to design a sensorless closed loop tracking system for solar panels with two degrees of freedom. The tracking controller in this study is based on the Fuzzy Logic Controller (FLC) method. In this study, a dual-axis PV can increase power output by 20.2% compared to a fixed PV (0 ° axis position). This is because, in comparison to a fixed PV, dual axis PV adjusts the solar panel perpendicular to the sun's position to optimize electrical conversion.</p> 2021-12-09T12:58:21+00:00 ##submission.copyrightStatement##