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All Journal Brilliance: Research of Artificial Intelligence Informatics and Enginering Dedication
Hendriko, Viky
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Other

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Pelatihan Java Fundamental Kepada Siswa/I SMA Xaverius 3 Palembang ., Vincent; Sinaga, Dep'niel; Hendriko, Viky; Irsansaputra, Vincentius Hansel; Maximilliano, Wesley
FORDICATE Vol 3 No 1 (2023): November 2023
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/fordicate.v3i1.5062

Abstract

Perkembangan teknologi di Dunia semakin berkembang dan maju, mulai dari teknologi yang terkecil hingga terbesar telah mengalami perubahan yang signifikan, Perkembangan teknologi juga didukung oleh Algoritma dari bahasa pemrograman yang dibangun dalam struktur teknologi yang digunakan, misalnya pada perangkat lunak (Software) maupun perangkat keras (Hardware). Bahasa pemrograman menjadi juru kunci utama dalam pembuatan algoritma pada suatu teknologi seperti Cloud Computing, Artificial Intelligence, dan Internet Of Things. Dengan adanya program pelatihan Java Fundamentals ini diharapkan menjadi bekal bagi siswa/i tentang dasar bahasa pemrograman Java, program pelatihan ini ditujukan kepada siswa/i SMA Xaverius 3 Palembang secara langsung/luring dengan mengunjungi sekolah SMA Xaverius 3. Setelah program pelatihan ini dilaksanakan berdasarkan hasil dari Exercise 1 diperoleh nilai dengan rata-rata 90% dari 27 murid. Program pelatihan ini memberikan peluang tinggi bagi siswa/i yang ingin mempelajari serta memahami bahasa pemrograman Java untuk masa depan mereka.
Performance Comparison of YOLOv10, YOLOv11, and YOLOv12 Models on Human Detection Datasets Hendriko, Viky; Hermanto, Dedy
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.6447

Abstract

One popular of object detection model for object detection is You Only Look Once (YOLO) with humans are among the most often utilized for detection objects. Despite the various of human datasets, just a few research that compared the datasets performance against various versions of the YOLO algorithm. This study compares the performance of YOLOv10, YOLOv11, and YOLOv12 on eight different datasets, such as CrowdHuman, CityPersons, Wider Person, Mall Dataset, INRIA, Microsoft Common Object (MS COCO), PASCAL VOC, and MOT17. Precision, recall, mAP@50, and mAP@50-95 are used to measure the YOLO model version's performance on each dataset. The results indicate that each datasets have different perfomance on each version of YOLO, so the performance on model depends on the variation of the dataset. The best results on the MOT17 dataset are obtained by YOLOv12, with 0.909 in precision, 0.775 in recall, 0.88 in mAP@50, and 0.695 in mAP@50-95. On the City Person dataset. However, YOLOv11 performs best result, with 0.782 in precision, 0.529 in recall, 0.694 in mAP@50, and 0.476 in mAP@50-95. Therefore, choosing a YOLO version that is appropriate for the dataset's complexity is essential to creating the best detection model Therefore, selecting the appropriate YOLO version according to the dataset complexity is crucial to obtain the most optimal detection model.
Co-Authors ., Vincent Dedy Hermanto Irsansaputra, Vincentius Hansel Maximilliano, Wesley Sinaga, Dep'niel