Jurnal Online Informatika https://join.if.uinsgd.ac.id/index.php/join <p><strong>JOIN (Jurnal Online Informatika) </strong>is an international peer-reviewed journal that publishes original research papers and reviews the field of <strong>informatics</strong>. JOIN is a scientific journal published by the Department of Informatics UIN Sunan Gunung Djati Bandung, Indonesia. The journal is dedicated to promoting the advancement of informatics in the beyond by providing a platform for researchers, scientists, and academics to publish their research findings and share their knowledge with the broader scientific community. JOIN welcomes submissions from researchers, scientists, and academics around the world on topics including:</p> <ul> <li><strong>Computer System and Distributed Computing</strong></li> </ul> <p>Computer Organization &amp; Architecture, Operating System, Computer Networks &amp; Wireless Communication, Embedded System, Pervasive Computing, Network Programming, Internet of Thing (IoT) Technology, Cloud Computing, Software-Defined Networking (SDN), Network function virtualization (NFV), Smart System, Information Technology (IT) Automation, Virtualization, Network Security, Cryptography, Computer Security, Ubiquitous Learning, and Parallel and Distributed Systems</p> <ul> <li><strong>Computer Vision and Artificial Intelligence</strong></li> </ul> <p>Digital Image Processing, Multimedia data processing, Knowledge representation &amp; reasoning, Deep Learning, Natural Language Processing, Prompt Engineering, Data science, Artificial Intelligence driven for IoT, and Artificial Intelligence driven for GameTech.</p> <p><strong>JOIN</strong> <strong>(Jurnal Online Informatika)</strong> has been accredited <strong><em>Sinta 2</em></strong> by Ministry of Research, Technology and Higher Education, Republic of Indonesia as an academic journal (SK Dirjen Dikti No. <a title="SK JOIN Sinta 2" href="https://drive.google.com/file/d/1-L9loUC4BIx7Z1im0f8MTAnSOaYQRJyK/view?usp=sharing" target="_blank" rel="noopener">B/4130/E5/E5.2.1/2019</a>)</p> <p><strong>JOIN (Jurnal Online Informatika)</strong> is published twice a year in <strong>June</strong> and <strong>December</strong>. The paper is an original script and has a research base on Informatics. </p> <p>Thus, we invite Academics, Researchers, and Practitioners to participate in submitting their work to this journal.</p> <p>ISSN : </p> <ul> <li><a title="ISSN Print" href="https://issn.brin.go.id/terbit/detail/1466480524"><strong>2528-1682 (Printed)</strong></a></li> <li><a title="ISSN Online" href="https://issn.brin.go.id/terbit/detail/1464049910"><strong>2527-9165 (Online)</strong></a></li> </ul> Department of Informatics, UIN Sunan Gunung Djati Bandung en-US Jurnal Online Informatika 2528-1682 <div id="deed-rights" class="row" dir="ltr"> <div class="col-sm-offset-2 col-sm-8"> <div id="deed-rights" class="row" dir="ltr"> <div class="col-sm-offset-2 col-sm-8"> <h3>You are free to:</h3> <ul class="license-properties"> <li class="license share show"><strong>Share</strong> — copy and redistribute the material in any medium or format for any purpose, even commercially.</li> <li class="license share show">The licensor cannot revoke these freedoms as long as you follow the license terms.</li> </ul> </div> </div> <div class="row"> </div> <div class="row"> <div class="col-md-offset-1 col-md-10"><hr /></div> </div> <div id="deed-conditions" class="row"> <h3>Under the following terms:</h3> <ul class="license-properties col-md-offset-2 col-md-8" dir="ltr"> <li class="license by show"> <p><strong>Attribution</strong> — You must give <a id="appropriate_credit_popup" class="helpLink" tabindex="0" title="" href="https://creativecommons.org/licenses/by-nd/4.0/" data-original-title="">appropriate credit</a>, provide a link to the license, and <a id="indicate_changes_popup" class="helpLink" tabindex="0" title="" href="https://creativecommons.org/licenses/by-nd/4.0/" data-original-title="">indicate if changes were made</a>. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.</p> </li> <li class="license by show"> <p><span id="by-more-container"></span><strong>NoDerivatives</strong> — If you <a id="some_kinds_of_mods_popup" class="helpLink" tabindex="0" title="" href="https://creativecommons.org/licenses/by-nd/4.0/" data-original-title="">remix, transform, or build upon</a> the material, you may not distribute the modified material.</p> </li> <li class="license by show"> <p><span id="nd-more-container"></span><strong>No additional restrictions</strong> — You may not apply legal terms or <a id="technological_measures_popup" class="helpLink" tabindex="0" title="" href="https://creativecommons.org/licenses/by-nd/4.0/" data-original-title="">technological measures</a> that legally restrict others from doing anything the license permits.</p> </li> </ul> </div> <div class="row"> </div> <div class="row"> <div class="col-md-offset-1 col-md-10"><hr /></div> </div> <div id="deed-understanding" class="row"> <h3>Notices:</h3> <ul class="understanding license-properties col-md-offset-2 col-md-8"> <li class="license show">You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable <a id="exception_or_limitation_popup" class="helpLink" tabindex="0" title="" href="https://creativecommons.org/licenses/by-nd/4.0/" data-original-title="">exception or limitation</a>.</li> <li class="license show">No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as <a id="publicity_privacy_or_moral_rights_popup" class="helpLink" tabindex="0" title="" href="https://creativecommons.org/licenses/by-nd/4.0/" data-original-title="">publicity, privacy, or moral rights</a> may limit how you use the material.</li> </ul> </div> </div> </div> <p align="center"><a href="http://creativecommons.org/licenses/by-nd/4.0/" rel="license"><img style="border-width: 0;" src="https://i.creativecommons.org/l/by-nd/4.0/88x31.png" alt="Creative Commons License" /></a><br />This work is licensed under a <a href="http://creativecommons.org/licenses/by-nd/4.0/" rel="license">Creative Commons Attribution-NoDerivatives 4.0 International License</a></p> Improving Indonesian Named Entity Recognition for Domain Zakat Using Conditional Random Fields https://join.if.uinsgd.ac.id/index.php/join/article/view/898 <p><span style="font-weight: 400;">In Indonesia, where the majority of the population is Muslim, one of the obligations of a Muslim is zakat. To reduce illiteracy about zakat among Muslims, they need to have access to basic information about it. In order to facilitate the acquisition of this information, this study utilized named entity recognition (NER) and defined 12 named entity classes for the zakat domain, including the pillars of Islam, various types of zakat, and zakat management institutions. The Conditional Random Fields method was used for testing Indonesian-NER in three scenarios. In the specific context of the Zakat domain, NER can extract information about organizations, individuals, and locations involved in collecting and distributing Zakat funds. This information can improve the Zakat system’s efficiency and transparency and support research and analysis on Zakat-related topics. The average performance evaluation of the Indonesian-NER model showed a precision of 0.902, recall of 0.834, and an F1-score of 0.867.</span></p> Nur Febriana Widiyanti Husni Teja Sukmana Khodijah Hulliyah Dewi Khairani Lee Kyung Oh Copyright (c) 2023 Jurnal Online Informatika https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 131 138 10.15575/join.v8i2.898 User Experience Design and Prototypes of Mobile-based Learning Media for Children with Special Needs in the Dyslexia Category https://join.if.uinsgd.ac.id/index.php/join/article/view/959 <p><span style="font-weight: 400;">Education is the right of all living things regardless of social status, gender, or physical condition. Persons with disabilities have the same rights and obligations as citizens. Based on the 1945 Constitution Article 31 Paragraph 1 and Law Number 20 of 2003 concerning the National Education System, it can be concluded that the state provides full guarantees for children with special needs to obtain quality education services. Children with special needs are divided into several categories, in this study the research team will focus on solving learning problems for children with disabilities in the dyslexia category. Dyslexia also known as reading disorder, is a disorder characterized by reading below the expected level for one's age. This study aims to find learning solutions by developing user experience designs and prototypes of mobile-based learning media for children with special needs in the dyslexia category. This research applies design thinking methodology to understand users, challenge assumptions, redefine problems, and create innovative solutions to prototype and test.</span></p> Rian Andrian Aldi Yasin Rizki Hikmawan Ahmad Fauzi Muhamad Irwan Ramadhan Copyright (c) 2023 Jurnal Online Informatika https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 139 146 10.15575/join.v8i2.959 Implementation of Dynamic Topic Modeling to Discover Topic Evolution on Customer Reviews https://join.if.uinsgd.ac.id/index.php/join/article/view/963 <p><span style="font-weight: 400;">Annotation and analysis of online customer reviews were identified as significant problems in various domains, including business intelligence, marketing, and e-governance. In the last decade, various approaches based on topic modeling have been developed to solve this problem. The known solutions, however, often only work well on content with static topics. As a result, it is challenging to analyze customer reviews that include dynamic and constantly expanding collections of short and noisy texts. A method was proposed to handle such dynamic content. The proposed system applied a dynamic topic model using BERTopic to monitor topics and word evolution over time. It would help decide when the topic model needs to be retrained to capture emerging topics. Several experiments were conducted to test the practicality and effectiveness of the proposed framework. It demonstrated how a dynamic topic model could handle the emergence of new and over-time-correlated topics in customer review data. As a result, improved performance was achieved compared to the baseline static topic model, with 25% of new segmented texts discovered using the dynamic topic model. Experimental results have, therefore, convincingly demonstrated that the proposed framework can be used in practice to develop automatic review annotation tools.</span></p> Valentinus Roby Hananto Copyright (c) 2023 Jurnal Online Informatika https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 147 157 10.15575/join.v8i2.963 Artificial Neural Network for Classification Task in Tabular Datasets and Image Processing: A Systematic Literature Review https://join.if.uinsgd.ac.id/index.php/join/article/view/1002 <p><span style="font-weight: 400;">Artificial Neural Network (ANN) is one of the machine learning algorithms that is widely used for classification cases. Some examples of classification cases that can be handled with ANN include classifications in the health sector, banking, and classification in image processing. This study presents a systematic literature review (SLR) of the ANN algorithm to find a research gap that can be used in future research. There are 3 phases used in preparing the SLR. Those are planning, conducting, and reporting. Formulation of research questions and establishing a review protocol is carried out in the planning phase. The second phase is conducted. In this phase, searching for relevant articles is carried out, determining the quality of the literature found and selecting particles according to what has been formulated in the planning phase. The selected literature is then carried out by the process of extracting data and information and then synthesizing the data. Writing SLR articles based on existing findings is carried out in the last phase, namely reporting. The results of data and information extraction from the 13 reviewed articles show that the ANN algorithm is powerful enough with satisfactory results to handle classification cases that use tabular datasets or image datasets. The challenges faced are the need for extensive training data so that ANN performance can be better, the use of appropriate evaluation measures based on the cases studied does not only rely on accuracy scores, and the determination of the correct hyperparameters to get better performance in the case of image processing.</span></p> Adi Zaenul Mustaqim Nurdana Ahmad Fadil Dyah Aruming Tyas Copyright (c) 2023 Jurnal Online Informatika https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 158 168 10.15575/join.v8i2.1002 The Impact of Data Augmentation Techniques on the Recognition of Script Images in Deep Learning Models https://join.if.uinsgd.ac.id/index.php/join/article/view/1073 <p><span style="font-weight: 400;">Deep learning technology is widely used for recognizing character images, including various regional characters and diverse ancient scripts. Deep learning models require large data sets to recognize images accurately. However, creating a dataset has limitations in terms of quantity, including the Komering script dataset used in this study. Data augmentation techniques can be applied to expand the dataset by modifying existing images to increase data diversity. This study aims to investigate the impact of augmentation techniques on the performance of deep learning models in the case of Komering script recognition. The dataset consists of 500 images for five classes of Komering script characters. Three augmentation techniques, namely random rotation, height shift, and width shift, were applied to the five characters, which were then used to test the model trained to recognize characters in the Komering dataset. This research contributes to providing insights into the effect of augmentation techniques on robust confidence prediction of deep learning models for recognizing newly augmented data. The results demonstrate that the deep learning model can recognize modified data using augmentation techniques with an average accuracy of 80.05%.</span></p> Wulan Sapitri Yesi Novaria Kunang Ilman Zuhri Yadi Mahmud Mahmud Copyright (c) 2023 Wulan Sapitri, Yesi Novaria Kunang, Ilman Zuhri Yadi, Mahmud https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 169 176 10.15575/join.v8i2.1073 Development of Augmented Reality Programming Language using Agile Scrum Methodology https://join.if.uinsgd.ac.id/index.php/join/article/view/1133 <p><span style="font-weight: 400;">The agile scrum methodology for augmented reality development increases project team efficiency. Private campus are frequently confronted with the dilemma of new students with various backgrounds that come not only from vocational high schools but also from high schools. First year students in the informatics study programme come not only from vocational informatics high schools, but also from high schools that specialize in social studies and languages. This is a difficult task in terms of imparting a comprehension of the fundamentals of programming. This study develops augmented reality in order to teach HTML and Javascript. By combining basic principles with gaming, the proposed augmented reality (AR) makes programming interesting. Players must comprehend their programming logic in order to be immersed in a virtual environment by answering coding bug questions. During usability testing, the System Usability Scale (SUS) assesses user happiness and AR knowledge. Participants from various programming backgrounds were tested on their knowledge of programming languages. According to usability research, 59% of people found AR programming languages useful for learning and understanding basic programming languages. AR and Agile Scrum make programming more enjoyable. This study demonstrates how augmented reality can be used to teach programming languages. These findings imply that Agile Scrum and AR methods can improve learning and programming foundations. More research and development could lead to more complete and complicated AR learning environments for programming instruction. </span></p> Ade Bastian Sarmidi Dadan Zaliluddin Mochammad Bagasnanda Firmansyah Copyright (c) 2023 Ade Bastian, Sarmidi, Dadan Zaliluddin, Mochammad Bagasnanda Firmansyah https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 177 185 10.15575/join.v8i2.1133 Designing a Virtual Campus Tour using Image Stitching Techniques to Provide Information on College Entrance Test https://join.if.uinsgd.ac.id/index.php/join/article/view/1030 <p><span style="font-weight: 400;">The University of Bengkulu administers college entrance exams, however some test takers still require assistance in locating the correct room, despite the building being marked. It is crucial to avoid errors in finding the right test room, as it can cause potential students to waste valuable time. Therefore, a more precise and practical solution is necessary to provide information on test locations. This study designs a location-based virtual tour that offers a 360-degree view, providing information on the location of each building and the conditions inside and outside each test room. The virtual tour encompasses 81 buildings, including test rooms, with 28 to 32 images captured at each location, then stitched together using image stitching techniques. The goal of the virtual tour is to create a comprehensive view of the test location and provide more detailed information on the room's condition. Furthermore, the usability of this virtual tour was tested on 140 high school students as potential test participants, utilizing the System Usability Scale (SUS) to evaluate its effectiveness, resulting in a score of 72.19. In other words, the virtual tour was found to be an effective tool in helping users understand the test location.</span></p> Ferzha Putra Utama Andang Wijanarko Jemmi Alfarobi Copyright (c) 2023 Ferzha Putra Utama, Andang Wijanarko, Jemmi Alfarobi https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 186 193 10.15575/join.v8i2.1030 XGBoost and Convolutional Neural Network Classification Models on Pronunciation of Hijaiyah Letters According to Sanad https://join.if.uinsgd.ac.id/index.php/join/article/view/1081 <p><span style="font-weight: 400;">According to Sanad, the pronunciation of </span><em><span style="font-weight: 400;">Hijaiyah</span></em><span style="font-weight: 400;"> letters can serve as a benchmark for correct or valid reading based on the </span><em><span style="font-weight: 400;">makhraj</span></em><span style="font-weight: 400;"> and properties of the letters. However, the limited number of Qur'anic Sanad teachers remains one of the obstacles to learning the Qur'an. This study aims to identify the most practical combination of classification models in constructing a voice recognition system that facilitates learning without requiring direct interaction with a teacher. The methods employed include the XGBoost algorithm and CNN. As a result, out of the 12 letter trait labels, the CNN model was utilized for 10 of them, specifically for traits S1, S2, S4, S5, T1, T2, T3, T4, T5, and T6, on trait labels S3 and T7 applying the XGBoost model. Furthermore, the inclusion of additional data yielded performance results for each property, with an average accuracy of 78.14% for property S (letters with opposing properties), 70.69% for property T (letters without opposing properties), and an overall average of 73.79% per letter.</span></p> Aaz Muhammad Hafidz Azis Dessi Puji Lestari Copyright (c) 2023 Aaz Muhammad Hafidz Azis, Dessi Puji Lestari https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 194 203 10.15575/join.v8i2.1081 Analysis of Electrocardiogram Dynamic Features for Arrhythmia Classification https://join.if.uinsgd.ac.id/index.php/join/article/view/1106 <p><span style="font-weight: 400;">Arrhythmia is a deviation from the normal heart rate pattern. Arrhythmias are usually harmless, but they can cause heart problems. Some types of arrhythmias include Atrial Fibrillation (AF), Premature Atrial Contractions (PAC), and Premature Ventricular Contractions (PVC). Many studies have been conducted to identify the dynamic characteristics of electrocardiogram (ECG) irregular waves in the detection of arrhythmias. However, the accuracy obtained in these studies is less than optimal. This study aims to solve the problem by evaluating three main features of arrhythmias using ECG signals: RR interval, PR interval, and QRS complex. Experiments were conducted rigorously on these three features. The accuracy achieved was 98.21%, with a specificity of 98.65% and a sensitivity of 97.37%.</span></p> Yusril Ramadhan Satria Mandala Copyright (c) 2023 Yusril Ramadhan, Satria Mandala https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 204 212 10.15575/join.v8i2.1106 Implementation of Recurrent Neural Network (RNN) for Question Similarity Identification in Indonesian Language https://join.if.uinsgd.ac.id/index.php/join/article/view/1138 <p><span style="font-weight: 400;">In a question-and-answer forum, the identification of question similarity is used to determine how similar two questions are. This procedure makes sure that user-submitted questions are compared to the questions in a database for matches to improve system performance on the online Q&amp;A platform. Currently, question similarity is mostly done in foreign languages. The purpose of this research is to identify question similarities and evaluate the effectiveness of the methods used in Indonesian language questions. The data used is a public dataset with labeled pairs of questions as 0 and 1 where label 0 for different pairs of questions and label 1 for the same pairs of questions. The method used is a Recurrent Neural Network (RNN) with the Manhattan Distance approach to calculate the similarity distance between two questions. The question pairs are taken as two inputs with a reference label to identify the similarity distance between the two question inputs. We evaluated the model using three different optimizers namely RMSprop, Adam, and Adagrad. The best results were obtained using the Adam optimizer with 80:20 ratio split-data and overall accuracy is 76%, precision is 74%, recall is 98.8%, and F1-score is 85.1%.</span></p> Muhammad Iqbal Hasmawati Ade Romadhony Copyright (c) 2023 Muhammad Iqbal, Hasmawati, Ade Romadhony https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 213 221 10.15575/join.v8i2.1138 Automate IGP and EGP Routing Protocol Configuration using a Network Automation Library https://join.if.uinsgd.ac.id/index.php/join/article/view/1157 <p><span style="font-weight: 400;">Data communication is sending data from client to client through a computer network. The increasing use of data communication makes computer networks more complex. Complex computer networks make it difficult for network administrators to configure them, especially routing protocol configuration. Network administrators are in charge of configuring routing protocols and managing networks. In addition, the more devices on the network, the greater the chance of human error from the administrator. Therefore, network automation is one solution that helps network administrators overcome this. This study focuses on analyzing the performance of network automation using the Paramiko and Telnetlib libraries. The routing protocol used by OSPF for IGP and BGP for EGP. The scenario in this study involves configuring IP addresses and configuring OSPF and BGP routing. Based on the test results, the Telnetlib library is better than the Paramiko library in terms of script delivery time, convergence time, and delay by 19.237% when applied to the IGP and EGP routing protocols.</span></p> Yuansa Alfaresa Bongga Arifwidodo Fauza Khair Copyright (c) 2023 Yuansa Alfaresa, Bongga Arifwidodo, Fauza Khair https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 222 231 10.15575/join.v8i2.1157 YOLOv5 and U-Net-based Character Detection for Nusantara Script https://join.if.uinsgd.ac.id/index.php/join/article/view/1180 <p class="a_ tm5"><span style="font-weight: 400;">Indonesia boasts a diverse range of indigenous scripts, called Nusantara scripts, which encompass Bali, Batak, Bugis, Javanese, Kawi, Kerinci, Lampung, Pallava, Rejang, and Sundanese scripts. However, prevailing character detection techniques predominantly cater to Latin or Chinese scripts. In an extension of our prior work, which concentrated on the classification of script types and character recognition within Nusantara script systems, this study advances our research by integrating object detection techniques, employing the YOLOv5 model, and enhancing performance through the incorporation of the U-Net model to facilitate the pinpointing of fundamental Nusantara script's character locations within input document images. Subsequently, our investigation delves into rearranging these character positions in alignment with the distinctive styles of Nusantara scripts. Experimental results reveal YOLOv5's performance, yielding a loss rate of approximately 0.05 in character location detection. Concurrently, the U-Net model exhibits an accuracy ranging from 75% to 90% for predicting character regions. While YOLOv5 may not achieve flawless detection of all Nusantara scripts, integrating the U-Net model significantly enhances the detection rate by 1.2%.</span></p> Agi Prasetiadi Julian Saputra Iqsyahiro Kresna Imada Ramadhanti Copyright (c) 2023 Agi Prasetiadi, Julian Saputra, Iqsyahiro Kresna, Imada Ramadhanti https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 232 241 10.15575/join.v8i2.1180 Classification of Bulughul Maraam Categories: Prohibitions, Recommendations, and Information Using Extreme Learning Machine and Fasttext https://join.if.uinsgd.ac.id/index.php/join/article/view/1205 <p><span style="font-weight: 400;">Hadith is the second source of Islamic law after the Quran. After the hadiths were compiled, Imam of Hadith created collections of hadiths, one of which is Imam Bukhari who compiled the book Bulughul Maraam, which is considered to have the highest level of authenticity. Digital collections of hadiths can now be found in the form of e-books and web pages, which help in the search for hadiths. The classification of hadiths is necessary to organize them by category, making it easier to search for hadiths based on their categories. Text mining is needed to classify hadiths because it can identify patterns in unstructured text. This research aims to improve the accuracy of classifying recommended, prohibited, and informational hadiths using a dataset of 7008 hadiths, which consists of primary data taken from the book Bulughul Maraam in the Indonesian language. Previously, similar research was conducted in 2017 that classified recommended, prohibited, and obligatory hadiths with an accuracy of 85%, but only for Sahih Bukhari hadiths. In this research, the same classification categories will be examined, proposing a different method, namely the Extreme Learning Machine method and Word2vec Fasttext for text representation with a larger dataset. The results of this research show a model accuracy of 86.31%, 86% precision, and 87% recall, indicating that the proposed model performs well in classifying hadiths.</span></p> Rissa Handayani Ina Najiyah Dirga Wisnuwardana Copyright (c) 2023 Rissa Handayani, Ina Najiyah, Dirga Wisnuwardana https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 242 251 10.15575/join.v8i2.1205 Retweet Prediction Using Multi-Layer Perceptron Optimized by The Swarm Intelligence Algorithm https://join.if.uinsgd.ac.id/index.php/join/article/view/1193 <p><span style="font-weight: 400;">Retweets are a way to spread information on Twitter. A tweet is affected by several features which determine whether a tweet will be retweeted or not. In this research, we discuss the features that influence the spread of a tweet. These features are user-based, time-based and content-based. User-based features are related to the user who tweeted, time-based features are related to when the tweet was uploaded, while content-based features are features related to the content of the tweet. The classifier used to predict whether a tweet will be retweeted is Multi Layer Perceptron (MLP) and MLP which is optimized by the swarm intelligence algorithm. In this research, data from Indonesian Twitter users with the hashtag FIFA U-20 was used. The results of this research show that the most influential feature in determining whether a tweet will be retweeted or not is the content-based feature. Furthermore, it was found that the MLP optimized with the swarm intelligence algorithm had better performance compared to the MLP. </span></p> Jondri Jondri Indwiarti Indwiarti Dyas Puspandari Copyright (c) 2023 Jondri Jondri, Indwiarti Indwiarti, Dyas Puspandari https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 252 260 10.15575/join.v8i2.1193 Optimizing YOLOv8 for Real-Time CCTV Surveillance: A Trade-off Between Speed and Accuracy https://join.if.uinsgd.ac.id/index.php/join/article/view/1196 <p><span style="font-weight: 400;">Real-time video surveillance, especially CCTV systems, requires fast and accurate face detection. Object detection models with slow inference times are ineffective in real-time. This study addresses this challenge by improving the inference speed of the YOLOv8 model, a leading object detection framework known for its accuracy and speed. We focus on pruning the model's architecture, particularly the P5 head section, which detects larger objects. According to Bochkovskiy's 2020 research, this modification enhances the model's performance specifically for medium and small objects in CCTV footage. The standard YOLOv8 model and its modified version were compared for inference time, mean Average Precision (mAP), and model weight. The pruned YOLOv8 model cuts inference time by 15.56%, from 4.5 ms to 3.8 ms, and reduces model weight. The advantages mentioned above are offset by a 1.6% decrease in mean average precision. This research advances object detection technology by demonstrating architectural modifications' efficacy. These changes make the model faster and lighter, making it suitable for real-time surveillance. The accuracy trade-off is slight. The implications of these findings are crucial for implementing efficient object detection systems in CCTV surveillance. These findings also lay the groundwork for future research to improve such systems' speed-accuracy trade-off.</span></p> Muhammad Rizqi Sholahuddin Maisevli Harika Iwan Awaludin Yunita Citra Dewi Fachri Dhia Fauzan Bima Putra Sudimulya Vandha Pradiyasma Widarta Copyright (c) 2023 Muhammad Rizqi Sholahuddin, Maisevli Harika, Iwan Awaludin, Yunita Citra Dewi, Fachri Dhia Fauzan, Bima Putra Sudimulya, Vandha Pradiyasma Widarta https://creativecommons.org/licenses/by-nd/4.0 2023-12-28 2023-12-28 8 2 261 270 10.15575/join.v8i2.1196