https://ejournal.st3telkom.ac.id/index.php/infotel/issue/feed JURNAL INFOTEL 2022-08-15T07:08:08+00:00 Eko Fajar Cahyadi ekofajarcahyadi@ittelkom-pwt.ac.id Open Journal Systems <h2>About Jurnal INFOTEL</h2> <table border="0"> <tbody> <tr> <td><img src="http://ejournal.st3telkom.ac.id/public/site/images/journaladmin/cover_infotel.png" alt="telecommunication journal" width="180" height="250"></td> <td valign="top" align="justify"> <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="https://docs.google.com/forms/d/1z8am_OQpUPdDtX93QYcSzv6J5tCd3xoAAN5TWCdNqxU/edit?usp=sharing"><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> https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/717 Peer to peer (P2P) and cloud computing on infrastructure as a service (IaaS) performance analysis 2022-08-05T06:20:39+00:00 Tati Ernawati tatiernawati@poltektedc.ac.id Febi Febiansyah febi.febianyah18@gmail.com <p>The resources of information technology and the availability of services on non-cloud network systems are limited. This constitutes problems for companies, especially in the efficient management of information technology. The high investment in infrastructure procurement is an obstacle in building centralized systems, including the adoption of cloud computing through Infrastructure as a Service (IaaS), as an elective solution. This research aims to analyze the performance of cloud servers on IaaS services using the parameters of cloud service availability, resource utilization, and throughput transfer which were implemented in companies engaged in the toll road concession sector. Furthermore, the results are expected to be a reference in supporting company decisions/policies related to cloud system adoption. The methodology involved the Network Development Life Cycle (NDLC), a system constituted by 6 (six) stages of management, namely user, proxy server, database, web service, monitoring service, and Remote Desktop Protocol (RDP). The results of cloud service availability indicate that the cloud system provides service availability (system interface, broad network access, and resource pooling). Furthermore, cloud systems have a significant performance on resource utilization (CPU) and throughput transfer parameters, while non-cloud systems only excel in response time and resource utilization (Memory) parameters. The overall result analysis based on this research scenario showed that the cloud system provides services according to user needs and has a better speed in data transmission, but has shortcomings in response time.</p> 2022-08-01T00:00:00+00:00 ##submission.copyrightStatement## https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/751 Sensitivity analysis of the SMARTER and MOORA methods in decision making of achieving students 2022-08-15T01:32:39+00:00 Intan Nur Farida in.nfarida@gmail.com Umi Mahdiyah umimahdiyah@gmail.com Akbar Fastio Hari Setiawan akbarfastio@gmail.com <p>Evaluation of student learning in Islamic boarding schools is still limited to the results of exams conducted in writing which can lead to the determination of student achievement using simple criteria, resulting in less than optimal results. In addition, the importance of selecting criteria to suit the learning characteristics of the Islamic boarding school students. The purpose of this study is to assist the process of evaluating student learning based on the value of the criteria, sub-criteria, and priorities. The method used is Rank Order Centroid in assigning weight values ​​to the criteria applied to the Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER) and Multi-Objective Optimization By Ratio Analysis (MOORA) methods. This study produces the same alternative value in the first rank. To calculate the accuracy is done by using sensitivity analysis according to the results of preference values ​​in each method. Based on the sensitivity analysis shows that in the first sensitivity calculation the lowest value is obtained. The sensitivity value of the SMARTER method on the first sensitivity is 0.0714. While the first sensitivity value of the MOORA method is 0.0076. So the best method is owned by the MOORA method because it has the lowest sensitivity value.</p> 2022-08-01T00:00:00+00:00 ##submission.copyrightStatement## https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/764 Time complexity in rejang language stemming 2022-08-05T06:21:41+00:00 Rozali Toyib rozalitoyib@umb.ac.id Sastya Hendri Wib Hendri Wibowo sastiahendriwibowo@gmail.com Muntahanah Muntahanah muntahanah@umb.ac.id Yulia Darnita yuliadarnita@umb.ac.id <p>Stemming is the process of separating the root word from an affixed word in a sentence by separating the base word and affixes which can consist of prefixes (prefixes), insertions (infixes), and suffixes (suffixes). Between one language and another, there are differences in the algorithm, especially the stemming process, in morphology. The time complexity of the Rejang algorithm is determined based on the affix group. To find out the time complexity of the stemming algorithm in the Rejang language using the method of making a digital word dictionary of the Rejang language, studying and analyzing the morphology of the Rejang language, making the Rejang language stemming algorithm based on the results of the Rejang language morphology analysis, analyzing the algorithm's performance and calculating the time complexity of the stemming results. The result of this research is to produce an efficient and effective Rejang Language stemming algorithm, where efficiency is indicated by the algorithm's time complexity of O(log n), and the effectiveness is shown from the results of accuracy of 99% against the test of 9000 affixed words. This accuracy value indicates that the over stemming and under stemming processes are 1%. Test results on 15 text documents with an average stemming failure rate of 1%.</p> 2022-08-01T00:00:00+00:00 ##submission.copyrightStatement## https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/779 Development of mobile billing application system for PAMDES water meter data logging 2022-08-05T06:22:06+00:00 Umar Ali Ahmad umarali@telkomuniversity.ac.id Ikbal Ramdani ikbalramdani@telkomuniversity.ac.id Fath Muhammad Isham fath@telkomuniversity.ac.id Reza Rendian Septiawan zaseptiawan@telkomuniversity.ac.id R Rogers Dwiputra Setiady rogers@telkomuniversity.ac.id Angga Rusdinar anggarusdinar@telkomuniversity.ac.id Ashri Dinimaharawati ashri@telkomuniversity.ac.id Yusup Diva Pratama yusupdiva@telkomuniversity.ac.id Fauzi Sofyan fauzisofyan@telkomuniversity.ac.id Rifdo Shah Alam rifdoshah@telkomuniversity.ac.id <p>Along with the growth of Sindangsari's population, the water requirement in this village has increased. So, the drinking water company (PAMDES) in this village must be able to manage the available water to meet the necessities of public life. Now, the water company is still collecting and recording water meters manually. It is very risky to consider the water condition in the village because an officer can make a human error while recording the water meter's value. When the water meter recorder is damaged, the officer estimates the water meter's value. An application is needed to manage bills and record water meters to avoid this in previous studies using the Internet of Things (IoT) or mobile applications that must be sent online to the server in real-time. This solution is not suitable for the internet condition in Indonesia, which is not evenly distributed to remote villages. This study proposes to use a mobile application that can store data on mobile devices. When the internet connection is unavailable, it can be sent later when it is available again. In this study, data obtained that the condition of the meter recorder from 672 customers, 37 water meters recorder is damaged. In addition, water meter data is also obtained for the following month's bill and data on average water usage of 10,661m<sup>3 </sup>per month. With these data, it is found that the minimum water requirement is 10,661 m<sup>3</sup> per month. It is hoped that the application for billing management and recording of PAMDES water meters in Sindangsari village, Cikoneng sub-district, Ciamis district can help increase PAMDES management capacity.</p> 2022-08-01T00:00:00+00:00 ##submission.copyrightStatement## https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/791 Utilization of the COBIT 2019 framework to identify the level of governance in internet services 2022-08-05T06:22:37+00:00 Sandhy Fernandez sandhy.fernandez@gmail.com Muhammad Imanullah muhimanullah@gmail.com M. Yoka Fathoni yoka@ittelkom-pwt.ac.id Pahrizal Pahrizal pahrizal@gmail.com <p>Information and communication technology services at the University of Muhammadiyah Bengkulu are IT services that support IT needs in all sectors. Of all the IT services that have been implemented at this institution, there is one very crucial service, namely the internet connection service, where this internet connection service is needed by all existing information technology access. In managing this internet connection, a standardized feasibility calculation has not been carried out which results in it not being in accordance with the institutional business needs. Information technology governance is a process that is able to manage investment decisions related to Information Technology within the company in order to achieve the company's current and future needs. To achieve standardized governance, this research uses the COBIT 2019 framework which is the latest version of the development results from COBIT 5. The purpose of this study is to identify the extent to which the value of existing processes for internet connection services is currently and the value of the process achievement that refers to the standard. COBIT 2019 by calculating the maturity level value which represents the level of performance on internet connection services. From the results of the 2019 COBIT Design, LTIK Muhammadiyah Bengkulu University, it is known that those who score above 80 or must reach Capability Level 4 are APO13, BAI10, DSS02, DSS03 and DSS04, for a value of 100 there is APO12.</p> 2022-08-01T00:00:00+00:00 ##submission.copyrightStatement## https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/796 Classification of diabetic foot ulcer using convolutional neural network (CNN) in diabetic patients 2022-08-05T06:22:57+00:00 Mawaddah Harahap mawaddah@unprimdn.ac.id Sai Kumarani Anjelli officialanjelli@gmail.com Widy Anggun M. Sinaga anggunwidy2109@gmail.com Ryan Alward ryanalwardofficial@gmail.com Junio Fegri Wira Manawan juniofegriwiramanawan@gmail.com Amir Mahmud Husein amirmahmud@unprimdn.ac.id <p>The image of chronic wounds on human skin tissue has the similar look in shape, color and size to each other even though they are caused by different diseases. Diabetic ulcer is a condition where peripheral arterial blood vessels are disrupted due to hyperglycemia in people with diabetes mellitus. This research was aimed to analyze the accuracy of the Convolutional Neural Network algorithm in classifying diabetic ulcer disease with a transfer learning approach based on the appearance of the image of the wound on the sole in people with diabetes mellitus. By applying the transfer learning approach, the results showed that the Resnet152V2 model achieved the best accuracy value of 0.993 (99%), precision of 1.00, recall of 0.986, F1-Score of 0.993 and Support of 72. Therefore, the ResNet152V2 model was highly considered for classifying diabetic ulcer in patients with diabetes melitus.</p> 2022-08-01T00:00:00+00:00 ##submission.copyrightStatement## https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/793 A deep learning model to detect the brain tumor based on magnetic resonance images 2022-08-15T07:05:27+00:00 Kelvin Leonardi Kohsasih ceokelvin12@gmail.com Muhammad Dipo Agung Rizky dipoagung@gmail.com Rika Rosnelly rikarosnelly@gmail.com Willy Wira Widjaja willywira@gmail.com <p>Deep learning techniques have been widely used in everything from analyzing medical information to tools for making medical diagnoses. One of the most feared diseases in modern medicine is a brain tumor. MRI is a radiological method that can be used to identify brain tumors. However, manual segmentation and analysis of MRI images is time-consuming and can only be performed by a professional neuroradiologist. Therefore automatic recognition is required. This study propose a deep learning method based on a hybrid multi-layer perceptron model with Inception-v3 to predict brain tumors using MRI images. The research was conducted by building the Inception-v3 and multilayer perceptron model, and comparing it with the proposed model. The results showed that the hybrid multilayer perceptron model with inception-v3 achieved accuracy, recall, precision, and fi-score of 92%. While the inception-v3 and multilayer perceptron models only obtained 66% and 56% accuracy, respectively. This research shows that the proposed model successfully predicts brain tumors and improves performance</p> 2022-08-01T00:00:00+00:00 ##submission.copyrightStatement## https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/788 Detection of learning styles with prior knowledge data using the SVM, K-NN and Naïve Bayes algorithms 2022-08-15T07:06:37+00:00 Muhammad Said Hasibuan msaid@darmajaya.ac.id RZ Abdul Aziz rz_aziz@darmajaya.ac.id <p>The two types of automatic learning style detection approaches are data driven (DD) and literature based (LB). Both methods of automatic learning style detection have advantages over traditional learning style detection methods because they use external data sources, such as forums, quizzes and views of teaching materials, that are more accurate than the questionnaires used in traditional styles of detection. The results of automatic detection, on the other hand, do not always reflect learning styles. This paper presents a learning style recognition method that uses data from the learner’s internal source, namely prior knowledge, to overcome these challenges. Prior knowledge is proposed because it is based on the learner’s knowledge or skills, which better reflect the learner’s characteristics, rather than on the learner’s behaviour, which tends to be dynamic. By using past knowledge, this paper presents a method for detecting automatic learning patterns. The learning style detection framework is unique in that it consists of three stages: prior knowledge question development, prior knowledge measurement and learning style detection using the Support Vector Machine (SVM), Naïve Bayes and K-Nearest Neighbour (K-NN) classification methods. The accuracy of learning style detection using prior knowledge data was higher than detection results using behavioural data or hybrid data (prior knowledge + behaviour) in this study</p> 2022-08-05T00:00:00+00:00 ##submission.copyrightStatement## https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/758 Software-based simulation to analyze the variation of digital modulation and atmospheric condition on the free space optic (FSO) link performance 2022-08-15T07:07:22+00:00 Fauza Khair fauza.khair@ittelkom-pwt.ac.id Dodi Zulherman zulherman.dodi@ittelkom-pwt.ac.id Rifani Auliana r.auliana1@gmail.com <p>Free Space Optic (FSO) is the solution for telecommunications technology that offers high data rates, wide bandwidth, and low power consumption. However, to maximize the performance of the FSO system, the modulation used should be considered in environmental conditions. This study aims to compare the performance of the FSO communication link based on digital modulation variations used in various weather conditions, including sunny, rainy, and foggy weather. This study uses two attenuation models, namely the Kim and Kruse models, with variations in transmission distance from 500 meters to 10 kilometers. Modulation variations used include QPSK, 8-PSK, 16-PSK, and 16-QAM at 10 Gbps bitrate. The simulation is accomplished using OptiSystem 17.0 software. The study results show that sunny weather (very clear) has the best visibility compared to rain and fog conditions with an attenuation value of 0.46 dB/km on the Kim and Kruse models. QPSK modulation has the best performance with a BER value of less than 1x10<sup>-12</sup> up to a transmission distance of 8 km in sunny weather, 3 km in rainy weather &nbsp;(medium rain), and 800 m in foggy (moderate fog) weather. The 8-PSK modulation has a BER value of less than 1x10<sup>-12</sup> with a range of 2000 m in sunny weather and 1500 m in rainy weather but does not meet the standards in foggy weather conditions. 16-PSK and 16-QAM modulation have above baseline BER values ​​during rainy and foggy conditions, but 16-QAM modulation still has a BER value of less than 1x10<sup>-3</sup> during foggy conditions at a distance of 500 m.</p> 2022-08-01T00:00:00+00:00 ##submission.copyrightStatement## https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/759 Power control scheme using particle swarm optimization method in resource allocation process on D2D underlaying communication 2022-08-15T07:07:47+00:00 Vinsensius Sigit Widhi Widhi Prabowo vinsensiusvsw@telkomuniversity.ac.id Linda Meylani lindameylani@telkomuniversity.ac.id Ersa Rahma Aqila Majid ersarahma.student@telkomuniversity.ac.id Achmad Ali Muayyadi alimuayyadi@telkomuniversity.ac.id <p>Fast growing number of cellular telecommunication technology resulting on the increasing number of the user equipment. This condition increased the eNodeB load. To overcome this problem, the device-to-device (D2D) underlaying communication is introduced. In underlaying scheme, the D2D user equipment (DUE) will do the communication process using the same radio resources with the conventional cellular user equipment (CUE). To avoid a severe interference between these two types of user in the system, a good resource allocation is needed. In this work, a power control scheme using particle swarm optimization (PSO) is proposed, to manage the transmit power on each user on the system. The power control scheme take place after the greedy scheduling algorithm, after all user is given a resource block (RB) to do the communication process. The power transmit for each user is managed to reach a better system capacity, and to reduce the power consumed in one communication process. From the simulation, the PSO power control can improve the sumrate and spectral efficiency up to 12.97% and 3.38% respectively. The PSO power control also can reduce the power consumed by the system up to 8.84%. The fairness happens among the CUEs also can be maintained, despite of the decreasing fairness among DUEs.</p> 2022-08-01T00:00:00+00:00 ##submission.copyrightStatement## https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/777 The reduction of polynomial degrees using moving average filter and derivative approach to decrease the computational load in polynomial classifiers 2022-08-15T07:08:08+00:00 Dewi Agustini Santoso dewi@dsn.dinus.ac.id Gutama Indra Gandha gutama.indra@dsn.dinus.ac.id <p>Carbon monoxide is a type of pollutant that is harmful to human health and the environment. On the other hand, carbon monoxide also has benefits for industrial matter. Since the benefits and disadvantages of carbon monoxide, the measurement of carbon monoxide concentration is required. The measurement of carbon monoxide level is not easy moreover with low-cost sensors. The usage of 4 sensors namely TGS2611, TGS2612, TGS2610 and TGS2602 has been used along with feature extractor. The polynomial classifier is required to interpret the feature vector into the amount of substance concentration. The common classifier methods suffer fatal limitations. The polynomial classifiers method offers lower complexity in solution and lower computational effort. Since the involvement of a huge number of data points in the modelling process leads to high degree in the polynomial model. The occurrence of Runge's phenomenon is highly possible in this condition. This phenomenon affects the accuracy level of the generated model. The degree reduction algorithm is required to prevent the occurrence of Runge’s phenomenon. The combination of MAF (Mean Average Filter) and derivative approach as degree reductor algorithm has succeeded in reducing the polynomial model degree. The greater the number degree in the model means the greater the computational load. The model degree reductor algorithm has been succeeded to reduce computational load by 96.6%.</p> 2022-08-01T00:00:00+00:00 ##submission.copyrightStatement## https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/818 Front Matter 2022-08-05T06:44:33+00:00 Nur Ghaniaviyanto Ramadhan ghani@ittelkom-pwt.ac.id <p>Front Matter August 2022</p> 2022-08-05T06:44:33+00:00 ##submission.copyrightStatement## https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/819 Back Matter 2022-08-05T06:47:00+00:00 Nur Ghaniaviyanto Ramadhan ghani@ittelkom-pwt.ac.id <p>Back Matter August 2022</p> 2022-08-05T06:47:00+00:00 ##submission.copyrightStatement##