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All Journal JETT (Jurnal Elektro dan Telekomunikasi Terapan) JOIV : International Journal on Informatics Visualization JOURNAL OF ELECTRICAL AND SYSTEM CONTROL ENGINEERING Jurnal Ilmiah FIFO TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika IJAIT (International Journal of Applied Information Technology) Journal of Computer, Electronic, and Telecommunication (COMPLETE) Jurnal Ilmiah Teknik Elektro eProceedings of Engineering Jurnal Ilmiah Agroust
Suryo Adhi Wibowo
Universitas Telkom
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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Pembelajaran Kolaboratif Berdasarkan Two-Branch Neural Network dan YOLOv5 Untuk Deteksi Objek Pada Kendaraan Otonom Agniya Tazkiya Aulia; Suryo Adhi Wibowo; Fityanul Akhyar
eProceedings of Engineering Vol 10, No 3 (2023): Juni 2023
Publisher : eProceedings of Engineering

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Abstrak—Seiring dengan kemajuan teknologi dan otomatisasi, perkembangan pada Autonomous Vehicle (AV) meningkat secara signifikan. Object detection memegang peranan penting pada teknologi AV. Pada penerapannya, kondisi cuaca yang buruk mengakibatkan terjadinya penurunan performa sistem dalam mendeteksi objek terutama ketika cuaca berkabut. Tugas Akhir ini menganalisis konfigurasi dari pembelajaran kolaboratif an- tara algoritma dehazing dan object detection untuk meningkatkan kinerja sistem AV dalam mendeteksi objek di kondisi cuaca berkabut. Algoritma dehazing yang digunakan adalah Two- Branch Neural Network, sedangkan algoritma object detection yang digunakan adalah YOLOv5. Pada YOLOv5 dilakukan optimasi dengan hyperparameter tuning untuk mendapatkan nilai pengukuran terbaik. Hasil penelitian menunjukkan bahwa model pembelajaran kolaboratif memiliki mAP yang lebih tinggi dari model YOLOv5 orisinal, dengan nilai 71,5%. Di sisi lain, konfigurasi hyperparameter terbaik didapatkan pada nilai learn- ing rate 0,00334; batch size 32; dan lainnya didapatkan dari hyperparameter VOC. Hal ini meningkatkan mAP dari 71,5% ke 74,8%.Kata kunci—AV, YOLOv5, two-branch neural network, object detection, image dehazing, hyperparameter
Surveillance System Scheme using Multi-detection Attribute with Optimized Neural Network Algorithm on Intelligent Transportation System Akhmad Yusuf Nasirudin; Koredianto Usman; Suryo Adhi Wibowo
eProceedings of Engineering Vol 10, No 3 (2023): Juni 2023
Publisher : eProceedings of Engineering

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Abstract- Intelligent Transportation System (ITS) combines a transportation system with Information and Communication Technology (ICT) system, where ICT system plays a role in adding functionality in the form of intelligence resembling human intelligence to the transportation system. The combination allows humans to know the real state of the transportation system including transportation components, such as the status of the road, objects around the vehicle, and the state of the vehicle, thus enabling humans to optimize the transportation system. For example, if there is a group of thief that using a van on the road, we can fasten the process to detect where is the route that used by the thief by adding a vehicle detector on the traffic light camera. This detector will be work better if the detector can detect the van in real-time and in a high resolution image. This work will discuss on how to increase the detector system performance on inference time (fps) and accuracy using HRNet and FCOS. HRNet is a high resolution image network architecture that can process image in a multiple resolution (low, medium, high) to maintain the high resolution but still have an enough image feature to process, while FCOS is a one stage anchor-free detector, so it can detect the object faster than the anchor-based detector. The performances was even more better when we add a warm up training before the training process. Our experimental results shows that our system has a better result compared with the reference result using same dataset and hyperparameter. It also has a better result compared with the reference result that using the reference dataset and hyperparameter.Keywords- intelligent transportation system; objet detection; vehicle detection; attribute detection; computer vision; image processing; surveillance system.
Performance Analysis Of Class Rebalancing Self-Training Framework For Imbalanced Semi-Supervised Learning Alvaro Septra Dominggo Nauw; Suryo Adhi Wibowo; Casi Setianingsih
eProceedings of Engineering Vol 10, No 5 (2023): Oktober 2023
Publisher : eProceedings of Engineering

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This research aims to analyze the effectiveness ofthe Class-Rebalancing Self-Training (CReST) method in semisupervisedlearning (SSL) on class-imbalanced data. The studyuses the CIFAR 10 long-tailed dataset to test the performance ofSSL with CReST using Python programming language on theGoogle Colab platform. The results showed that CReSTeffectively reduces pseudo-labels in the majority class andincreases recall in the minority class, with the best performanceachieved at Generation 16. However, there was a decrease inAverage Accuracy Recall per Class after Generation 16. Thestudy suggests addressing the over-sampling issue and exploringthe application of the CReST framework in other areas ofmachine learning and AI.Kata kunci— CReST, Semi-Supervised Learning, imbalancedata, pseudo label, Semi-Supervised Learning Generation
Co-Authors Agniya Tazkiya Aulia Agus Pratondo Akhmad Yusuf Nasirudin Aldo Tripolyta Alvaro Septra Dominggo Nauw Angga Rusdinar Anky Aditya P Annisa Istiqomah Atina Nur Azizah Bambang Hidayat Bambang Hidayat Bambang Setia Nugroho Casi Setianingsih Dany Eka Saputra Devita Rahma Apriliani Dini Himmah Al Aliyyah Al Aliyyah Djoko Heru Pamungkas Dwiki Kurniawan Dyah Avita Sari Fahmi Oscandar Fahmi Oscandar Faiz Nashrullah Farah Hana Kusumaputri Felix Corputty Fiky Yosef Suratman Fityanul Akhyar Gelar Budiman Hanaluthfina Nurhadiati Hashfi Fadhillah Iwan Iwut Tritoasmoro JANGKUNG RAHARJO Koredianto Usman Kusuma Nindia Rizki Ledya Novamizanti Liyana Faiza Lulud Annisa Ainun Mahmuddah Lyra Vega Ugi Muhammad Alief Hidayah Baso Muthia Saada Nadya Sindi Safitri Oriza Intani Prasaja Wibawa Utama Putri Utami Hafgianti Raditiana Patmasari Ricky Hilmi Sudrajad Rissa Rahmania Rissa Rahmania Rissa Rahmania Rissa Rahmania Rita Purnamasari Tembang Florian Falah Viky Premeita Mitayani Vivian Alfionita Sutama Wiwit Ratri Wulandari Yacobus Sunaryo Yurika Ambar Lita Yuti Malinda