https://e-journals.dinamika.ac.id/joti/issue/feed Journal of Technology and Informatics (JoTI) 2025-08-31T20:58:14+07:00 P3kM p3km@dinamika.ac.id Open Journal Systems <p><img src="https://e-journals.dinamika.ac.id/public/site/images/wawan/joti-vol.-7-no.-2-oktober-2025.jpg" alt="" width="1351" height="1909" /></p> <p>Journal of Technology and Informatics (JoTI) is a Peer-Reviewed Journal published by <a href="https://dinamika.ac.id/">Universitas Dinamika</a> <strong>in collaboration with <a href="https://drive.google.com/file/d/15U0_UmkfQlxMCsZNHiFp5x1C5jgtwjQ0/view?usp=sharing">Asosiasi Pendidikan Tinggi Informatika dan Komputer (APTIKOM) Jawa Timur</a></strong>. This journal is published twice a year in April and October. This journal covers the fields of Information Technology, Communication Systems, Signals, Systems and Electronics.</p> <ol> <li><strong>Journal Title: </strong>Journal of Technology and Informatics (JoTI)</li> <li><strong>Initial:</strong> JoTI</li> <li><strong>Abbreviation:</strong> Technol. Inform.</li> <li><strong>Accreditation Status : </strong><a href="https://sinta.kemdikbud.go.id/journals/profile/9804" target="_blank" rel="noopener">Sinta 3 Accredited Journal</a></li> <li><strong>Publication Frequency: </strong>2 issues per year</li> <li><strong>DOI: </strong><a href="https://doi.org/10.37802/joti">https://doi.org/10.37802/joti</a></li> <li><strong>Online ISSN:</strong> <a href="https://issn.brin.go.id/terbit/detail/1569308412" target="_blank" rel="noopener">2686-6102</a></li> <li><strong>Print ISSN:</strong> <a href="https://issn.brin.go.id/terbit/detail/1577072213" target="_blank" rel="noopener">2721-4842</a></li> <li><strong>Editor in Chief:</strong> <a href="https://scholar.google.co.id/citations?user=GpsCXvwAAAAJ&amp;hl=en" target="_blank" rel="noopener"><strong>Dr. Ira Puspasari, S.Si., M.T.</strong></a></li> <li><strong>Publisher:</strong><a href="https://www.dinamika.ac.id/" target="_blank" rel="noopener">Universitas Dinamika</a></li> <li><strong>Email : </strong><a href="mailto:joti@dinamika.ac.id">joti@dinamika.ac.id</a></li> <li><strong>Indexing:</strong> <a href="https://sinta.kemdikbud.go.id/journals/profile/9804" target="_blank" rel="noopener">SINTA 3</a><strong>|</strong><a href="https://scholar.google.com/citations?user=QdfKQZAAAAAJ&amp;hl=en" target="_blank" rel="noopener">Google Scholar</a><strong>|</strong><a style="background-color: #ffffff; font-size: 0.875rem;" href="https://garuda.kemdikbud.go.id/journal/view/22458" target="_blank" rel="noopener">Garuda</a><strong style="font-size: 0.875rem;">|</strong><a style="background-color: #ffffff; font-size: 0.875rem;" href="https://doaj.org/toc/2686-6102?source=%7B%22query%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22terms%22%3A%7B%22index.issn.exact%22%3A%5B%222721-4842%22%2C%222686-6102%22%5D%7D%7D%5D%7D%7D%2C%22size%22%3A100%2C%22sort%22%3A%5B%7B%22created_date%22%3A%7B%22order%22%3A%22desc%22%7D%7D%5D%2C%22_source%22%3A%7B%7D%2C%22track_total_hits%22%3Atrue%7D" target="_blank" rel="noopener">DOAJ</a><strong style="font-size: 0.875rem;">| </strong><a style="background-color: #ffffff; font-size: 0.875rem;" href="https://app.dimensions.ai/discover/publication?search_mode=content&amp;and_facet_source_title=jour.1424326" target="_blank" rel="noopener">Dimensions</a></li> </ol> https://e-journals.dinamika.ac.id/joti/article/view/1086 Simulated Phishing Attack and Forensic Analysis Using the D4I Framework: A Case Study on Kredivo 2025-06-25T09:07:15+07:00 Muhammad Yusuf Halim myusufhalim26@gmail.com Toto Raharjo etotoraha@gmail.com Rosi Rahmadi Syahputra rosirahmadisyahputra@gmail.com Erika Ramadhani erika@uii.ac.id <p>Phishing is a form of cyberattack where attackers deceive users into revealing sensitive information such as credentials or financial data, often through fake communication channels or websites. This threat is particularly critical in the financial technology (fintech) sector, where services rely heavily on digital transactions and user trust. This study presents a simulated phishing case targeting Kredivo users to evaluate the effectiveness of the Digital Forensics framework for Reviewing and Investigating cyber-attacks (D4I) in digital forensic analysis. The Cyber Kill Chain (CKC) model was employed to trace attacker behavior across seven phases, from weaponization to actions on objectives. Forensic data was acquired using MOBILedit Forensic Express from two smartphones, namely an iPhone 11 (iOS 15.8.1) and a Vivo Y21 (Android 8.1.0), which served as simulated evidence devices. Using the D4I framework, the investigation successfully identified and correlated key digital artifacts such as phishing links, OTP transmissions, and unauthorized access logs. These findings were organized into a visual chain of artifacts to reconstruct the full attack lifecycle. The results demonstrate that the D4I framework is effective in guiding structured forensic investigations and understanding attack patterns, supporting the enhancement of fintech security strategies.</p> 2025-09-25T00:00:00+07:00 Copyright (c) 2025 Journal of Technology and Informatics (JoTI) https://e-journals.dinamika.ac.id/joti/article/view/1087 Analisis Sentimen Pengguna X terhadap Perempuan di Lingkungan Kerja Menggunakan Algoritma Machine Learning 2025-07-09T10:05:57+07:00 Muhammad Davit Hilal Fahri l200210146@student.ums.ac.id Dedi Gunawan dg163@ums.ac.id <p><em>Gender bias against women in the workplace persists, including within digital interactions on social media. This study analyzes user sentiment on Platform X regarding women in professional contexts using three machine learning algorithms: Naïve Bayes, Support Vector Machine (SVM), and Random Forest. A total of 2,336 tweets were collected using 14 gender-related keywords and labeled both automatically using the DistilBERT model and manually through contextual interpretation. The automatic dataset was imbalanced (1,823 negative, 479 positive), while the manual dataset was more balanced (1,196 negative, 1,106 positive). After preprocessing and TF-IDF feature extraction, the data were split using the train_test_split method. Evaluation metrics included accuracy, precision, recall, and F1-score. Random Forest achieved the highest accuracy (79%) on automatic labels but showed class imbalance (F1-score: 0.88 for negative, 0.08 for positive). Meanwhile, models trained on manual labels showed more balanced performance with accuracy between 57% and 59%. A web application prototype was developed using Flask to predict sentiment related to workplace gender issues. The findings highlight the importance of balanced labeling and appropriate algorithm selection to build fair and reliable sentiment analysis models, contributing to more inclusive digital discourse on gender equality.</em></p> 2025-09-25T00:00:00+07:00 Copyright (c) 2025 Journal of Technology and Informatics (JoTI) https://e-journals.dinamika.ac.id/joti/article/view/1063 Sistem Pengenalan Wajah Real-Time Menggunakan YOLOv7 untuk Akses Gedung TVRI Palembang Berbasis Web 2025-05-26T08:06:17+07:00 Fatia Salsabilla Kyara kyarasakamaru17@gmail.com Aryanti Aryanti aryanti@polsri.ac.id R.A. Halimatussa'diyah ra_halimatussadiah@polsri.ac.id <p><em>The development of information and communication technology today has had a significant impact on various aspects of life, including in the field of security. The use of face recognition is one of the facial recognition techniques, where the results of the camera capture will be matched with photos or facial curve textures that already exist in the database. The system is widely applied using various methods and artificial intelligence, one of which is YOLO (You Only Look Once). The purpose of this study is to design, develop, and identify challenges in implementing a real-time facial recognition system using web-based YOLOv7 that can detect the faces of people entering the TVRI Palembang building, then photos and times when a person's face is not detected will be stored in the database. The data used comes from literature studies, data collection obtained from photos of TVRI television station employees' faces, software design with technology selection, user interface design, and algorithm structures that will be used. After going through these stages, a system implementation was carried out for the application of the system and analysis of the data results obtained. The results showed that the face detection system using YOLOv7 showed very good performance. In 100 training epochs, the system achieved 96,6% face detection accuracy and 90% face recognition accuracy, successfully identifying almost all registered faces and detecting faces in real time. This system produces high accuracy in detecting faces and almost all faces that should be recognized are successfully detected.</em></p> 2025-09-29T00:00:00+07:00 Copyright (c) 2025 Journal of Technology and Informatics (JoTI) https://e-journals.dinamika.ac.id/joti/article/view/1072 Implementasi Sistem Keamanan Brankas Berbasis Face Recognition Menggunakan Algoritma YOLO dengan Verifikasi Fingerprint 2025-06-10T10:33:53+07:00 Amanda Tsabita Putri Tata amanda.tsabita2303@gmail.com Irma Salamah irma_salamah@polsri.ac.id Martinus Mujur Rose mujur@polsri.ac.id <p><em>Current technological developments make security crucial in protecting important documents. Safes are commonly used for storage but remain vulnerable to burglary despite conventional locks. Based on data from the Central Bureau of Statistics (BPS) in 2023, aggravated theft was the most frequent crime with 62,872 reported cases. This highlights the need to improve safe security by adding biometric techniques such as face recognition and fingerprint verification. This study proposes a layered security system combining face recognition using the YOLO algorithm and fingerprint sensors. The system uses an ESP32-CAM to capture facial images and an ESP32 microcontroller to control a solenoid lock, fingerprint sensor and buzzer alarm. Face recognition testing on two users showed, the trained YOLO model achieved an accuracy of 83.33%, precision of 83,33% and recall of 100%. from 12 trials, with two failures due to poor lighting conditions. Fingerprint testing on 10 samples, five fingers from each of two users, showed successful recognition of all fingerprints with an average response time of 1.41 seconds. The integration of face and fingerprint biometrics significantly enhances safe security and minimizes unauthorized access risks.</em></p> 2025-09-29T00:00:00+07:00 Copyright (c) 2025 Journal of Technology and Informatics (JoTI)