Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) https://journal.lembagakita.org/index.php/jtik <p>Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi), e-ISSN: <a href="https://issn.lipi.go.id/terbit/detail/1487831807" target="_blank" rel="noopener">2580-1643</a> is a free and open-access journal published by the Research Division, KITA Institute, Indonesia. Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) is a scientific journal which is a place for scholars and experts from various countries to publish scientific articles on important aspects in the field of Information and Communication Technology. The journal covers a wide range of disciplines, including Computer Science, Communication Studies, Chemistry, Physics, Biology, Medicine, Geology, Statistics, Accounting, Social Sciences, Mathematics, Management, and Economics. Within this broad scope, the JTIK Journal encourages innovative research that addresses data processing, software development, artificial intelligence, algorithm analysis, as well as information and communication technology applications in various sectors. In the field of Communication Studies, this journal opens space for studies on mass communication, social media, human and technological interactions, and their social implications. The aim of the JTIK Journal is to encourage collaboration between disciplines and to contribute high-quality knowledge for the development of science and technology in the digital era. With high quality articles, this journal is the main reference for academics, researchers and practitioners in understanding the latest developments in the field of information and communication technology. It is hoped that, through the publication of excellent articles, the JTIK Journal can contribute significantly in advancing and increasing understanding of the crucial role of information and communication technology in contemporary society.. All published article URLs will have a digital object identifier (DOI).</p> <p><strong>Publication schedule</strong>: January-March, April-June, July-September, October-December | <a title="Publication frequency and important dates" href="http://journal.lembagakita.org/index.php/jtik/freq">more info</a><br /><strong>Language</strong>: English (<strong>preferable</strong>), Indonesia<br /><strong>APC</strong>: 500K IDR or $40 USD (submission, publishing) | <a title="Article Processing Charge" href="http://journal.lembagakita.org/index.php/jtik/fee">more info</a><br /><strong>Indexing</strong>: SINTA, PKPIndex, EBSCO, Google Scholar, etc | <a title="Jurnal JTIK indexing" href="http://journal.lembagakita.org/index.php/jtik/indexing">more info</a><br /><strong>OAI address</strong>: http://journal.lembagakita.org/index.php/jtik/oai</p> <p>To submit your article to <strong>Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) </strong>;</p> <ul> <li class="show">You have to <a class="label label-info" href="http://journal.lembagakita.org/index.php/jtik/user/register">Register</a> or <a class="label label-success" href="http://journal.lembagakita.org/index.php/jtik/login">Login</a> to submit your or.</li> <li class="show">You can access the manuscript format from the author guidelines.</li> <li class="show">Download <a class="label label-warning" href="https://drive.google.com/file/d/1prtx8_9AkLRGoYNY-30kOPknOYBTqD0u" target="_blank" rel="noopener">Template (Indonesia)</a>, <a class="label label-warning" href="https://drive.google.com/file/d/1mh2ciSGu-E3mED6CV1AICMJGK_0vlo4J/" target="_blank" rel="noopener">Template (English)</a></li> </ul> <p>Currently, <strong>Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) </strong><strong>has been accredited </strong>to the Ministry of Research, Technology and Higher Education of the Republic of Indonesia</p> <div id="additionalHomeContent"> <p>Interested in becoming our reviewer/editor? Please fill [<a title="Jurnal JTIK Reviewer / Editor Aplication Form" href="http://bit.ly/JTIK_Reviewer" target="_blank" rel="noopener"><strong>Reviewer Form</strong></a>].</p> <p><strong>Contact</strong>: <a href="mailto:jtik@lembagakita.org">jtik@lembagakita.org</a> / <a href="mailto:journal@lembagakita.org">journal@lembagakita.org</a></p> </div> <div id="additionalHomeContent"> </div> en-US <p>The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to JTIK journal and Research Division, KITA Institute as the publisher of the journal. Copyright encompasses rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations.</p> <p>JTIK journal and Research Division, KITA Institute and the Editors make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in JTIK journal are the sole and exclusive responsibility of their respective authors and advertisers.</p> <p>TheƂ Copyright Transfer Form can be downloaded here: [<a title="JTIK Copyright Transfer Agreement" href="http://bit.ly/CTA_ENG_JTIK_2020" target="_blank" rel="noopener">Copyright Transfer Form JTIK</a>]. The copyright form should be signed originally and send to the Editorial Office in the form of original mail, scanned document or fax :</p> <p><strong>Muhammad Wali (Editor-in-Chief)</strong><br />Editorial Office of Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) <br />Research Division, KITA Institute<br />Teuku Nyak Arief Street Nomor : 7b, Lamnyong, Lamgugop, Kota Banda Aceh<br />Telp./Fax: 0651-8070141<br />Email: jtik@lembagakita.org - journal@lembagakita.org</p> muhammadwali@lembagakita.org (Muhammad Wali) jtik@lembagakita.org (Cut Nelly) Mon, 01 Jan 2024 00:00:00 +0700 OJS http://blogs.law.harvard.edu/tech/rss 60 Perbandingan Algoritma Support Vector Machine dan Random Forest untuk Analisis Sentimen Terhadap Kebijakan Pemerintah Indonesia Terkait Kenaikan Harga BBM Tahun 2022 https://journal.lembagakita.org/index.php/jtik/article/view/1202 <p>The commodity of fuel oil (BBM) is the main commodity and the driving force of business. The increase in world oil prices is a threat to countries around the world, one of which is Indonesia. With the turbulent conditions in several countries, the Indonesian government decided to cut fuel subsidies which had an impact on price increases. The policy invited all Indonesian people and criticized it on various social media. The purpose of this research is to find out which algorithm has a better accuracy rate and to provide input to the government about public opinion regarding the increase in fuel prices in Indonesia. From the test results both work well, this is evidenced by the accuracy value obtained, where the support vector machine algorithm produces an accuracy value of 77%, while the Random Forest algorithm produces an accuracy value of 76%. So it can be concluded that the support vector machine algorithm has a fairly good accuracy rate compared to the Random Forest algorithm.</p> Muhamad Samantri, Afiyati Copyright (c) 2024 Muhamad Samantri, Afiyati https://creativecommons.org/licenses/by-nc/4.0 https://journal.lembagakita.org/index.php/jtik/article/view/1202 Mon, 01 Jan 2024 00:00:00 +0700 Optimalisasi Dua Layanan Jaringan Internet Menggunakan Teknik Load Balancing dengan Metode Peer Connection Classifier (PCC) (Studi Kasus: Jaringan Internet Desa Banyuanyar Boyolali) https://journal.lembagakita.org/index.php/jtik/article/view/1257 <p>Load Balancing is a technique for distributing data traffic so that the workload is distributed evenly on 2 or more networks to maximize resource usage and improve performance. There are two ISPs for internet access services to the Banyuanyar Village Office, Boyolali, both of which have different bandwidths, namely from PT. Telkom has 100Mbps bandwidth and Kominfo has 50Mbps bandwidth. So here there will be dense network traffic if the internet network is not optimized.. In this case, it can be optimized using load balancing techniques on both ISPs by using the Peer Connection Classifier technique to group traffic and divide the load on both internet connection lines so as not to overload. So it can be concluded that by adding a proxy router device, configuring load balancing, and applying a hierarchical network-based network topology, it will optimize two internet network services at Banyuanyar Village Hall, Boyolali.</p> Afrianton Noor Hafizh, Wiwin Sulistyo Copyright (c) 2024 Afrianton Noor Hafizh, Wiwin Sulistyo https://creativecommons.org/licenses/by-nc/4.0 https://journal.lembagakita.org/index.php/jtik/article/view/1257 Mon, 01 Jan 2024 00:00:00 +0700 Analisis Performa Protokol Routing Proaktif dan Reaktif pada MANET dengan Menggunakan OMNeT++ https://journal.lembagakita.org/index.php/jtik/article/view/1256 <p>Mobile Ad-hoc Network (MANET) technology is a wireless network consisting of a random and dynamic set of nodes. Free flow and ever-changing nodes lead to unpredictable routes throughout the network, so a routing protocol is required to determine the path of each node. Therefore, a study was conducted to analyze the performance of routing protocols based on their characteristics, namely proactive and reactive. The proactive routing protocol tested is DSDV and the reactive routing protocol uses AODV. Based on the research conducted, it can be concluded that the reactive routing protocol, AODV, has better performance than the proactive routing protocol, DSDV, measured by three Quality of Service (QoS) parameters, namely Packet Delivery Ratio (PDR), throughput, and average delay.</p> Zefanya Loudewieq Gabriel Lala, Indrastanti R. Widiasari Copyright (c) 2024 Zefanya Loudewieq Gabriel Lala, Indrastanti R. Widiasari https://creativecommons.org/licenses/by-nc/4.0 https://journal.lembagakita.org/index.php/jtik/article/view/1256 Mon, 01 Jan 2024 00:00:00 +0700 Penerapan Metode Extreme Learning Machine (ELM) untuk Memprediksi Hasil Sensor EWS Trafo https://journal.lembagakita.org/index.php/jtik/article/view/1243 <p>The Early Warning System (EWS) Trafo is a continuous monitoring tool for transformers that provides warnings when anomalies are detected, aiming to prevent explosions. This device applies artificial intelligence and machine learning technologies to monitor and predict the real-time condition of transformers using sensor data collected by the tool. This research aims to predict the condition of transformers based on the EWS Trafo sensor results using the Extreme Learning Machine (ELM) method. The study investigates the effectiveness of the ELM method in predicting transformer conditions. Based on the research results obtained from several combinations of data training: testing with different numbers of hidden layers, the lowest Mean Absolute Percentage Error (MAPE) value was found in the combination of 40% training data and 60% testing data, out of a total of 470 data points, with 20 hidden layers, at 23.1125%. Thus, it can be concluded that the Extreme Learning Machine (ELM) method is effective in predicting the condition of transformers.</p> Rolisa Apalem Copyright (c) 2024 Rolisa Apalem https://creativecommons.org/licenses/by-nc/4.0 https://journal.lembagakita.org/index.php/jtik/article/view/1243 Mon, 01 Jan 2024 00:00:00 +0700