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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Transmisi: Jurnal Ilmiah Teknik Elektro Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Mahasiswa TEUB Jurnal EECCIS e-Jurnal Arus Elektro Indonesia Journal of Information Systems Engineering and Business Intelligence ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Jurnal Teknologi dan Sistem Komputer Network Engineering Research Operation [NERO] Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Indonesian Journal of Electrical Engineering and Computer Science JAREE (Journal on Advanced Research in Electrical Engineering) International Journal of Engineering, Science and Information Technology Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Rahmadwati Rahmadwati
Unknown Affiliation
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Operasi Morfologi dan Teknik Histogram pada Sistem Deteksi Plat Nomor Kendaraan Bermotor Rahmadwati, Rahmadwati; Razak, Angger Abdul; Huda, Masykur
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 15 No. 3 (2021)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v15i3.1553

Abstract

Setiap kendaraan memiliki identitas berupa nomor kendaraan atau plat yang resmi dari kepolisian. Sistem pengenal/pengidentifikasi mobil otomatis atau Automatic License Plate Recognation (ALPR) telah menjadi salah satu hal yang penting. ALPR dapat diimplementasikan pada berbagai kebutuhan seperti sistem perparkiran, pengawasan jalan tol, pengawasan lalu lintas dan sebagainya. Sistem ini memiliki peranan penting dalam keberhasilan identifikasi karakter/nomor plat kendaraan. Namun, penelitian-penelitian sebelumnya kebanyakan hanya membuat deteksi pada plat kendaraan pribadi atau yang berwarna hitam. Oleh karena itu, pada penelitian ini penulis akan membuat system deteksi area plat yang tidak hanya pada plat kendaraan pribadi (hitam), melainkan pada plat kendaraan umum (kuning) dan juga kendaraan milik pemerintah (merah) menggunakan teknik histogram dan operasi morfologi. Hasil dari penelitian ini dari 40 citra uji didapatkan bahwa teknik histogram dan operasi morfologi citra dapat diterapkan dalam deteksi area plat mobil dengan hasil yang baik, dengan angka akurasi rata-rata 90%.
Deep Learning-Based Worker Posture Classification for Ergonomic Risk Evaluation in Manufacturing Rahmadwati Rahmadwati; Farrel Rafif Ferdian; Yeni Sumantri; Dhaffin Rayhzan Ferdian
International Journal of Engineering, Science and Information Technology Vol 6, No 3 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i3.1878

Abstract

Continuous ergonomic monitoring in manufacturing remains challenging because conventional posture assessment methods rely on manual observation, making evaluations time-consuming, subjective, and unsuitable for continuous industrial applications. This study proposes an automated ergonomic risk assessment framework that integrates Media Pipe Pose with a Convolutional Neural Network (CNN) to classify worker postures into low-, medium-, and high-risk ergonomic categories. The framework extracts 33 anatomical body landmarks from RGB images and video frames to generate marker less posture representations for deep learning-based classification. A dataset consisting of 4,500 posture samples collected from assembly, packaging, and welding workstations was expanded to 12,000 samples through data augmentation techniques, including rotation, scaling, horizontal flipping, and brightness adjustment, to improve model robustness and generalization. The CNN model was trained and evaluated using an independent test dataset, achieving an overall classification accuracy of 94.2%, with precision, recall, and F1-score consistently exceeding 94% across all ergonomic risk categories. Comparative evaluation against a conventional REBA/RULA-based rule-driven assessment demonstrated that the proposed framework improved classification accuracy by 7.5 percentage points while eliminating the need for manual posture scoring and reducing observer subjectivity. Furthermore, computational performance analysis showed that the complete inference pipeline operated at an average of 14 ms per frame (approximately 28.5 FPS) on a standard Intel Core i7 CPU with 16 GB RAM, without requiring GPU acceleration, indicating its suitability for real-time deployment in manufacturing environments. The proposed Media Pipe–CNN framework provides an efficient, accurate, and marker less solution for automated ergonomic risk assessment, supporting intelligent occupational safety management, continuous workplace monitoring, and the implementation of smart manufacturing systems aligned with Industry 4.0 initiatives
Co-Authors Akhmad Sabarudin Akio Kitagawa Alva Kosasih Angger Abdul Razak Angger Abdul Razak Anggraini, Monika Ayu Puji Anindita, Ruth Astari Anisari Mei Prihatini Aziz Muslim Azizurrahman Rafli Boby Yusuf Habibi Dachlan, Hary Soekotjo Danang Aditya Nugraha Deron Liang Dewi, Ajeng Kusuma Dhaffin Rayhzan Ferdian Dharmawan - Eka Maulana Erni Yudaningtyas Erni Yudhaningtyas Fadilla, Rafa Raihan Faiza Alif Fakhrina Farrel Rafif Ferdian Febriantono, M Aldiki FERDIANA, KHAIRUNISA Gigih Gumilar Golshah Naghdy Habibi, Boby Yusuf Hadi Suyono Huda, Masykur Idhil, Andi Nurul Isri Indriany Ika Kusumaning Putri IMRAN, AZZAM ZAHFRAN Luthfiyah Rachmawati M. Aldiki Febriantono M. Aziz Muslim Mahdin Rohmatillah Masykur Huda Moch. Rusli Mudjirahardjo, Panca Muh Wahid Anshori Riza Muhammad Aswin Muhammad Aziz Muslim Muhammad Dzikrullah Suratin, Muhammad Dzikrullah Muhammad Fauzan Edy Purnomo Muhammad Zulfikri Muhammad Zulfikri Nugraha, Danang Aditya Nurrohman, Muhammad Yogi Onny Setyawati Panca Mudjirahardjo Panca Mudjirahardjo Raden Arief Setyawan Raden Arief Setyawan Rakhmad Romadhoni Riza Hasbi Ash Shiddieqy Robintang Sotardodo Situmorang Rudy Yuwono Ruth Astari Anindita Sanjaya, Mochamad Rofi Sari, Sapriesty Nainy Shaskia Vilardl Ri Cahya Sholeh Hadi P. Sholeh Hadi Pramono Sultoni, Sultoni Suyono, Hadi Tanjo Yui Vita Kusumasari Wijono Wijono Wildan Arif Maulana Yeni Sumantri Yuyu Wahyu Zainul Abidin Zulfa Fahrunnisa