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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) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab 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 Jurnal Pengabdian kepada Masyarakat Nusantara 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 Abdi Cendekia: Jurnal Pengabdian Masyarakat Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) 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
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PENERAPAN YOLOv5 UNTUK SISTEM DETEKSI DAN MONITORING LAHAN PARKIR OTOMATIS Putri, Rizka Ferbriliana; Triyanto, Wiwit Agus; Setiaji, Pratomo
JURSIMA Vol 12 No 3 (2025): Volume 12 Nomor 3 2025
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v12i3.1172

Abstract

Pertumbuhan kendaraan di wilayah perkotaan menimbulkan permasalahan keterbatasan lahan parkir dan waktu pencarian tempat parkir yang lama. Penelitian ini bertujuan untuk merancang dan menerapkan sistem yang dapat secara otomatis mendeteksi dan memantau ketersediaan lahan parkir dengan memanfaatkan algoritma YOLOv5 serta citra yang diambil dari kamera drone. Metode yang digunakan mencakup akuisisi data citra melalui rekaman drone dari dua sudut pandang berbeda (atas dan samping), pelabelan data, pelatihan model deteksi objek, serta klasifikasi status slot parkir (kosong atau terisi). Evaluasi sistem dilakukan dengan mengukur precision, recall, accuracy, dan mAP@0.5. Hasil pengujian menunjukkan bahwa sudut pandang memengaruhi akurasi deteksi: pada sudut pandang samping, sistem memperoleh precision 100%, recall 75,86%, dan mAP@0.5 sebesar 75,86%, sedangkan pada sudut atas recall dan mAP@0.5 turun menjadi 35,29% dan 35,00%. Visualisasi Confusion Matrix dan Precision-Recall Curve mendukung hasil ini. Sistem yang dibangun terbukti mampu mendeteksi dan memantau ketersediaan lahan parkir secara real-time dengan visualisasi pada dashboard digital. Pemanfaatan kamera drone memberikan kemampuan untuk menjangkau area yang lebih luas dan fleksibel dibandingkan dengan penggunaan kamera statis. Dengan demikian, sistem ini memiliki potensi untuk menjadi solusi praktis dalam pengembangan smart parking berbasis deep learning di ruang publik. Kata Kunci: YOLOv5, deteksi kendaraan, smart parking, kamera drone, deep learning.
Sistem Klasifikasi Kematangan Apel Fuji berdasarkan Warna menggunakan KNN untuk Sortasi Otomatis Maula, Ahmad Inzul; Triyanto, Wiwit Agus; Setiaji, Pratomo
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 2 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i2.31243

Abstract

Manual fruit sorting typically relies on workers' visual observation to assess ripeness. This assessment is heavily influenced by individual experience and lighting conditions, often leading to inaccuracies. Furthermore, manual methods are time-consuming, increase the risk of misclassification, and reduce operational efficiency. Our research aims to develop a color-based Fuji apple ripeness classification application using the K-Nearest Neighbor algorithm that combines RGB and HSV features. Our research is developmental research using the Waterfall model, consisting of requirements analysis, design, implementation, testing, and maintenance. We used 240 fuji apple images sourced from images taken in the Kudus area. Our findings are an automatic classification application capable of classifying apple images into three ripeness levels: unripe, semi-ripe, and ripe. The evaluation results showed an accuracy of 93.75% with balanced precision, recall, and f1-score across all classes, confirming the system's stable performance without any indication of bias. Testing results using the black-box method in three scenarios opening the application, uploading an image, and reclassifying proved that all features performed as expected. The implication is that this application is ready for use in camera-based sorting in horticultural production lines and can be developed for other fruit classifications, supporting widespread post-harvest digitalization.
SISTEM INFORMASI MANAJEMEN STOK DAN PRODUKSI PAKAIAN ANAK BERBASIS WEB PADA UMKM LINDA COLLECTION MENGGUNAKAN METODE SAFETY STOCK Iskandar, Iskandar; Triyanto, Wiwit Agus; Fithri, Diana Layli; Arifin, Muhammad
Jurnal SITECH : Sistem Informasi dan Teknologi Vol 8, No 1 (2025): JURNAL SITECH VOLUME 8 NO 1 TAHUN 2025
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/sitech.v8i1.15556

Abstract

UMKM Linda Collection, yang bergerak di bidang produksi pakaian anak, menghadapi kendala dalam pengelolaan stok dan proses produksi akibat pencatatan manual yang mengakibatkan ketidaksesuaian data dan risiko kekurangan maupun kelebihan stok. Penelitian ini bertujuan untuk mengembangkan sistem informasi manajemen stok dan produksi berbasis web yang dilengkapi dengan metode Safety Stock guna mengoptimalkan pengendalian persediaan. Metode pengembangan sistem menggunakan pendekatan System Development Life Cycle (SDLC) model waterfall, sedangkan perancangan sistem menggunakan Unified Modeling Language (UML). Sistem yang dibangun memungkinkan pengguna untuk memantau stok secara real-time, menghitung persediaan pengaman, mengelola transaksi produksi, dan menyusun laporan berbasis data. Hasil implementasi menunjukkan bahwa sistem ini mampu meningkatkan efisiensi proses bisnis, meminimalkan risiko stock-out maupun overstock, serta mendukung pengambilan keputusan yang lebih akurat di lingkungan UMKM.
KLASIFIKASI EKSPRESI EMOSI WAJAH BAHAGIA DAN TIDAK BAHAGIA MENGGUNAKAN ARSITEKTUR MOBILENETV2 BERBASIS DEEP LEARNING Zahra, Fatimah Az; Setiaji, Pratomo; Triyanto, Wiwit Agus
Jurnal SITECH : Sistem Informasi dan Teknologi Vol 8, No 1 (2025): JURNAL SITECH VOLUME 8 NO 1 TAHUN 2025
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/sitech.v8i1.15546

Abstract

Penelitian ini bertujuan membangun sistem klasifikasi ekspresi wajah dua kelas (happy dan not happy) menggunakan arsitektur Convolutional Neuran Network (CNN) berbasis MobileNetV2 yang ringan dan efisien. Dataset yang digunakan merupakan gabungan dari FER2013, Pinterest, dan Roboflow, yang telah melalui proses augmentasi dan preprocessing. Model dilatih menggunakan metode 5-Fold Cross Validation untuk memperoleh evaluasi yang lebih stabil dan menyeluruh. Hasil penelitian menunjukkan bahwa model mencapai rata-rata akurasi validasi sebesar 81,49%, dengan nilai precision, recall, dan F1-score yang seimbang. Model kemudian diimplementasikan dalam sistem web berbasis Flask, memungkinkan pengguna mengunggah gambar dan memperoleh hasil klasifikasi dalam bentuk label teks. Pengujian menggunakan gambar wajah pribadi menunjukkan bahwa sistem memiliki kemampuan generalisasi yang baik pada data nyata di luar data latih. Penelitian ini menunjukkan bahwa arsitektur MobileNetV2 dapat diandalkan untuk tugas klasifikasi ekspresi wajah dua kelas berbasis gambar statis dan berpotensi dikembangkan lebih lanjut untuk aplikasi praktik di bidang pendidikan, interaksi manusia-komputer, dan layanan publik.
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.
Appropriate Application of Sawob M-Banking Technology To Develop Waste Bank Management in Bae Village Noor Romadlon, Farid; Ratna Wijayani, Dianing; Agus Triyanto, Wiwit
Devotion : Journal of Research and Community Service Vol. 3 No. 4 (2022): Devotion: Journal of Research and Community Service
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/dev.v3i4.129

Abstract

Garbage is a consequence of human activities. Along with the increasing population and current economic growth, waste management in the community creates uncontrolable problems. Based on this, one of the Community Service Program teams at Universitas Muria Kudus established a partnership with the Tanjung Seto Youth Organization in Bae village to help manage waste in the area. The main and urgent problem from partners that needs to be resolved is the operational activities of the waste bank. These problems include the socialization of waste bank activities, technical transactions, and circulation of waste bank savings money so that it is more efficient, effective, and practical and more citizens participate. The objective of this program is to assist the operational activities of the waste bank by using an android-based application named SAWOB M-Banking to support the process and mechanism of the Waste Bank activities. The method used to implement the solution is mentoring and knowledge transfer. Identifying needs will be accomplished through data collection on waste bank schedules, the number of waste bank clients, waste categories and price values, and customer savings data. Furthermore, processing the obtained data then making the SAWOB M-Banking application. The SAWOB M-Banking application has been socialized to customers gradually and tested for 10 customers in waste bank activities. After being simulated, the SAWOB M-Banking application has been used for all waste bank customers in Bae village.
Development of a Web-Based Information System for Real-Time Fainting Detection Using YOLO in Smart Healthcare Triyanto, Wiwit Agus; Susanti, Nanik
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 4, November 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i4.2407

Abstract

Loss of consciousness (fainting) is a critical condition that requires prompt treatment, especially in the context of elderly health services and independent patient care. This research aims to develop a web-based information system that is able to detect fainting events in real-time using the You Only Look Once (YOLO) algorithm version 11, which is one of the latest approaches in deep learning-based object detection. The system is designed to monitor video from the surveillance camera directly, make visual inferences of the patient's posture, and provide automatic notifications if a loss of consciousness condition is detected. The dataset was obtained from the Roboflow platform and consists of 9,081 annotated images representing the fainting position. The YOLOv11 model was trained and tested using training data sharing, validation, and testing methods. The test results showed that the model achieved mAP, precision, recall and F1-score values of 98.70%, 98.00%, 97.30% and 97.65%, respectively. The developed information system is able to display the detection visually through the bounding box on the dashboard and record the time of the incident. With this performance, this system shows great potential in improving patient safety through intelligent monitoring and automated response in hospital, nursing home, and residential environments. This research also opens up opportunities for the development of more adaptive AI-based health monitoring systems and computer vision in the future.
Pembuatan Perpustakaan Digital Untuk Membangun Desa Cerdas di Era Modern Muzakkiy, Muhammad; Ridwan, Muhammad Eldo; Ilyas, Muhamad Dwi; Triyanto, Wiwit Agus
Muria Jurnal Layanan Masyarakat Vol 7, No 2 (2025): September 2025
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/mjlm.v7i2.15975

Abstract

This community service program aims to support digital transformation in rural areas through the establishment of a digital library as an initial step toward realizing a smart village. The program targets village officials, youth organizations, students, and the general public who have limited access to digital literacy resources. The implementation method adopts a collaborative and participatory approach, consisting of community needs assessment, joint program planning, installation of a web-based library system, content management training, and follow-up mentoring. The results show an increase in the community’s ability to access digital information, the formation of the Nganguk Digital Literacy Community as library managers, and a growing culture of reading among residents. This program demonstrates that the adoption of information technology at the village level can serve as a catalyst for inclusive and sustainable social transformation, driven by collaboration and a shared spirit of learning. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk mendukung transformasi digital desa melalui pembangunan perpustakaan digital sebagai langkah awal menuju desa cerdas (smart village). Sasaran kegiatan mencakup perangkat desa, pemuda Karang Taruna, pelajar, dan masyarakat umum yang masih memiliki keterbatasan dalam literasi digital. Metode pelaksanaan dilakukan dengan pendekatan kolaboratif partisipatif melalui tahapan identifikasi kebutuhan masyarakat, perencanaan program bersama, instalasi sistem perpustakaan berbasis web, pelatihan pengelolaan konten, serta evaluasi dan pendampingan lanjutan. Hasil kegiatan menunjukkan adanya peningkatan kemampuan masyarakat dalam mengakses informasi digital, terbentuknya Komunitas Literasi Digital Nganguk sebagai pengelola perpustakaan digital, serta meningkatnya minat baca dan kolaborasi warga dalam menjaga keberlanjutan layanan literasi desa. Program ini membuktikan bahwa penerapan teknologi informasi di tingkat desa dapat menjadi katalisator perubahan sosial yang inklusif dan berkelanjutan melalui semangat gotong royong dan pemberdayaan masyarakat lokal.
CNN-Based Model for Classifying Regional Types on Shipping Label Images Widodo, Wahyu Kurniawan Ade Nur; Triyanto, Wiwit Agus; Setiaji, Pratomo
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i6.5584

Abstract

The rapid growth of the e-commerce sector has led to a significant surge in shipping volumes in Indonesia. In logistics systems, a shipping receipt serves as a crucial document containing destination information such as address, city/regency, and postal code. Errors or delays in classifying destination regions not only generate additional operational costs (e.g., reshipment fees and service penalties) but may also reduce customer satisfaction and harm the reputation of service providers. This study proposes the implementation of a Convolutional Neural Network (CNN) model to automatically classify region types in shipping receipt images, aiming to minimize manual errors and accelerate processing time. CNN was chosen for its ability to recognize complex visual patterns in digital documents without requiring manual feature extraction. The dataset used in this study consists of 1,540 shipping receipt images from various courier services, labeled as REG_JAWA and REG_LUARJAWA. The research process includes image preprocessing (resizing, normalization, augmentation), CNN architecture design, model training with early stopping, and performance evaluation using accuracy, precision, recall, and F1-score metrics. The results demonstrate that the model achieved a testing accuracy of 99.87%, precision of 99.71%, and recall of 100%, highlighting its strong potential for real-world implementation in logistics systems to improve efficiency and reliability of deliveries.
Co-Authors - Universitas Muria Kudus, Muhammad Arifin - Universitas Muria Kudus, Nanik Susanti A.A. Ketut Agung Cahyawan W Ahmad Adam Farokhi Ahmad Alif Candra Selamet Alif Catur Murti, Alif Catur Anastasya Latubessy Anis Fakhriyyah Arif Setiawan Bachtiar Hanafi Diana Laily Fithri Dimyati Utoyo Erlina Nofianti Faby Melia Shanni Fajar Nugraha Fakhriyyah, Anis Farid Noor Romadlon faridah ayu shefia Fatimah Az Zahra Ferianti, Lydya Ayu Feriyan Agusta Fernando Candra Yulianto Fernando Candra Yulianto Fikri Hamdhan Fithri, Diana Layli H. Himawan Hartiningsih Hartiningsih Hasan Basri Hidayatullah, Muhamad Arzak Hutomo Rusdianto Ilyas, Muhamad Dwi Iskandar Iskandar Jamhari Jamhari Jayanti Putri Purwaningrum Kevin Putra Adama Khoiruz Zahro Khusnul Himam, Muhammad Latifah Nur Ahyani Maula, Ahmad Inzul Mochammad Imron Awalludin Muhamad Dwi Ilyas Muhammad Arifin Muhammad Eldo Ridwan Muhammad Fahrino Haykal Febrian Muhammad Khasan Luthfi Muhammad Muzakkiy Muzakkiy, Muhammad Nanda Aulia Salsa Bila Nandalisa Lisa Fa’ati Rahmawati Nia Zuliyana, Nia Nisa, Nila Akhidatul Noor Latifah Nurhaliza, Aulia Nurhaliza, Maulin Pambudi, Satrio Pramita, Alvina Gusti Pratomo Setiaji Pratomo Setiaji Pratomo Setiaji Pratomo Stiaji Putri, Rizka Ferbriliana R Rhoedy Setiawan Ratna Wijayani, Dianing Rendy Afandy Retno Tri Handayani Riawan Yudi Purwoko Ridwan, Muhammad Eldo Rizal Naufal Farras Arkanda Rosalva Denisia Yulia Yahya Semit, Danial Setiawan, Faris Apri Slamet Kusmanto, Agung Sonia Shekha Anggriani Sri Septiana, Deyana Fitri Suku Rahayu, Sri Intan Supriyono Supriyono Syafiul Muzid Sya’diah, Ary Kania Syifa Amalia Tamami, Ghufron Teguh Prasetyo Vincent Suhartono Wahyu Wibowo, Angga Wardhani, Indah Kusuma Widiya Amelia Putri Widodo, Wahyu Kurniawan Ade Nur Yudie Irawan Yuniarsi Rahayu Yutia Nia Nesicha Zahra, Fatimah Az Zuliyati Zuliyati Zuliyati Zuliyati