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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Akuntansi Indonesia Jurnal Simetris Prosiding SNATIF Jurnal Pseudocode E-Dimas: Jurnal Pengabdian kepada Masyarakat Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal SOLMA Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal DISPROTEK International Journal of Elementary Education EDUMATIC: Jurnal Pendidikan Informatika Jurnal SITECH : Sistem Informasi dan Teknologi Abdimas Toddopuli: Jurnal Pengabdian Pada Masyarakat Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Journal of Information Technology Ampera Indonesian Journal of Technology, Informatics and Science (IJTIS) Journal of Software Engineering Ampera Jurnal UNITEK Devotion: Journal of Research and Community Service Jurnal Pengabdian Masyarakat (ABDIRA) Indonesian Journal of Networking and Security - IJNS SPEED - Sentra Penelitian Engineering dan Edukasi Muria Jurnal Layanan Masyarakat Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Locus Penelitian dan Pengabdian Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer IC Tech: Majalah Ilmiah Jurnal Sistem Informasi dan Manajemen Sasambo: Jurnal Abdimas (Journal of Community Service) International Journal of Artificial Intelligence and Science IC Tech: Majalah Ilmiah
Wiwit Agus Triyanto
Universitas Muria Kudus
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

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Journal : Jurnal Teknik Informatika (JUTIF)

 1 
Real-Time Traffic Density and Anomaly Monitoring Using YOLOv8, OpenCV and Pattern Recognition for Smart City Applications in Demak Setiaji, Pratomo; Triyanto, Wiwit Agus; Nurhaliza, Maulin
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4867

Abstract

Urban traffic congestion is a persistent issue in medium-sized cities like Demak, leading to delays and potential accidents. This study presents the development of a real-time vehicle density and anomaly detection system using YOLOv8, combined with OpenCV for video analysis, to monitor traffic flow at strategic entry points of Demak City. The system classifies vehicles into four categories (cars, motorcycles, trucks, buses) and determines their direction by detecting crossing lines. A key feature is the recognition of vehicle patterns, particularly the detection of stopped vehicles, flagging anomalies after 30 seconds of stoppage, with tolerance for temporary detection losses. Traffic data is stored in CSV format, enabling periodic analysis and visualization via an interactive graphical user interface (GUI). Evaluation results show the YOLOv8n model achieves 92.5% precision, 88.3% recall, and 89.7% mean average precision (mAP@0.5), demonstrating improved accuracy and speed over previous YOLO versions. Additionally, the vehicle counting accuracy reaches 94.2% when compared with manual annotations. The proposed system provides a reliable solution for real-time traffic monitoring and early anomaly detection, supporting intelligent transportation systems (ITS) and enabling data-driven traffic management decisions. This research contributes to the advancement of real-time video analytics and pattern recognition for urban traffic control and serves as a scientific reference for the development of smart city infrastructures. Furthermore, this study strengthens the application of pattern recognition in intelligent anomaly detection, providing new insights for researchers in the fields of computer science and informatics.
Sentiment Analysis of Fizzo Novel Application Using Support Vector Machine and Naïve Bayes Algorithm with SEMMA Framework Pambudi, Satrio; Setiaji, Pratomo; Triyanto, Wiwit Agus
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4875

Abstract

The increasing popularity of digital reading platforms in Indonesia, such as Fizzo Novel, has generated many user reviews that can be analyzed to understand their satisfaction. This study analyzes user sentiment toward Fizzo Novel using the SEMMA (Sample, Explore, Modify, Model, Assess) framework, and compares the performance of the Support Vector Machine (SVM) and Naïve Bayes algorithms. A total of 139,759 reviews were collected from the Google Play Store through web scraping. The data was then processed through normalization, tokenization, lexicon-based sentiment labeling, and feature extraction using TF-IDF. To address class imbalance, the SMOTE technique was applied. The results showed that SVM achieved the highest accuracy, exceeding 96%, with a consistent F1-score across all sentiment classes. In contrast, Naïve Bayes recorded lower accuracy (75.82% before SMOTE and 73.63% after SMOTE), along with a decline in performance for the neutral class. SVM proved more reliable in handling large and imbalanced text data. Practically, the results of this study can help application developers such as Fizzo Novel in automatically understanding user opinions. With an accurate sentiment classification model, developers can monitor reviews in real-time, identify issues such as excessive advertising or an unpopular chapter division system, and design feature improvements based on real user needs. This research also provides a foundation for algorithm selection in future large-scale sentiment analysis projects and recommends SVM as the more appropriate choice in this context.
Co-Authors - Universitas Muria Kudus, Muhammad Arifin - Universitas Muria Kudus, Nanik Susanti A.A. Ketut Agung Cahyawan W Agusta, Feriyan Alif Catur Murti, Alif Catur Amalia, Syifa Anastasya Latubessy Arif Setiawan Diana Laily Fithri Dimyati Utoyo Erlina Nofianti Fajar Nugraha Fakhriyyah, Anis Farid Noor Romadlon Ferianti, Lydya Ayu Fernando Candra Yulianto Fikri Hamdhan Fithri, Diana Layli H. Himawan Hanafi, Bachtiar Hartiningsih Hartiningsih Hasan Basri Hidayatullah, Muhamad Arzak Hutomo Rusdianto Ilyas, Muhamad Dwi Iskandar Iskandar Jamhari Jamhari Jayanti Putri Purwaningrum Kevin Putra Adama Khoiruz Zahro Latifah Nur Ahyani Maula, Ahmad Inzul Mochammad Imron Awalludin Muhammad Arifin Muzakkiy, Muhammad Nandalisa Lisa Fa’ati Rahmawati Nanik Susanti Nia Zuliyana, Nia Nisa, Nila Akhidatul Noor Latifah Nurhaliza, Aulia Nurhaliza, Maulin Pambudi, Satrio Pramita, Alvina Gusti Pratomo Setiaji Pratomo Setiaji Pratomo Setiaji Putri, Rizka Ferbriliana R Rhoedy Setiawan Ramandani, Fitri Ratna Wijayani, Dianing Retno Tri Handayani Riawan Yudi Purwoko Ridwan, Muhammad Eldo Rizal Naufal Farras Arkanda Selamet , Ahmad Alif Candra Semit, Danial Setiawan, Faris Apri Slamet Kusmanto, Agung Sonia Shekha Anggriani Sri Septiana, Deyana Fitri Stiaji, Pratomo Suku Rahayu, Sri Intan Supriyono Supriyono Syafiul Muzid Sya’diah, Ary Kania Tamami, Ghufron Teguh Prasetyo Vincent Suhartono Wahyu Wibowo, Angga Wardhani, Indah Kusuma Widodo, Wahyu Kurniawan Ade Nur Yudie Irawan Yuniarsi Rahayu Zahra, Fatimah Az Zuliyati Zuliyati Zuliyati Zuliyati