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Riza Adrian Maulana
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Computer Science & IT Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Pembelajaran dan Pelatihan Penggunaan Ms. Word di SDN Kresek III Muhammad Iqbal A; Riza Adrian Maulana; Rinaldi Prasya; Ocha Alfiano; Ridwan Al-Husyairi; Muhammad Aldi Septian; Febby Diansyah; Fajar Rizkiyan Arief
Abdi Jurnal Publikasi Vol. 1 No. 2 (2022): November
Publisher : Abdi Jurnal Publikasi

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Aplikasi Microsoft Office sangat penting digunakan dalam era digital saat ini, baik untuk anak Sekolah Dasar sampai Perguruan Tinggi bahkan untuk pekerja sekalipun. Dengan penggunaan yang semakin diminati oleh berbagai kalangan baik disektor perkantoran maupun dunia pendidikan. Untuk itu dibuatlah kegiatan pelatihan dalam rangka pengabdian masyarakat, yang bertujuan untuk meningkatkan pengetahuan serta pemahaman siswa/i sekolah dasar (SD) dalam menggunakan Microsoft Word dibuatlah pelatihan di SD NEGERI KRESEK III dengan jumlah siswa/i yang hadir 22 orang. Berdasarkan pelatihan yang diberikan, diperoleh hasil dari para peserta terlihat sangat antusias untuk mengikuti pelatihan ini, disisi lain kurangnya pengetahuan dan pelatihan membuat siswa/i Sekolah Dasar sangat kesulitan dalam mengoperasikannya. Setelah pelatihan dilakukan terdapat 90% siswa/i dapat memahami dan mempraktikkannya, karena metode yang kita pakai dengan cara memandu para siswa/i untuk mempraktikkan materi apa yang kita sampaikan. Pelatihan ini sangat berguna bagi para siswa/i Sekolah Dasar untuk menambah wawasan dan pengetahuan tentang Aplikasi Microsoft Word.
Implementation of Yolo (You Only Look Once) Algorithm for Drowsiness Detection as an Additional Safety Feature in the Operation of Crane Equipment in Real Time Riza Adrian Maulana; Hardiansyah
Jurnal Inotera Vol. 10 No. 1 (2025): January-June 2025
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol10.Iss1.2025.ID458

Abstract

Work accidents, especially in the construction sector, are still a serious problem, with fatigue as one of the main causes. Based on data from satudata.kemnaker, the author realizes the need for early prevention solutions to reduce the risk of accidents due to fatigue. One of the approaches proposed is the development of an automatic detection system to recognize workers' facial expressions, especially in detecting levels of freshness and sleepiness. The obstacles that are often faced are limited time and scale in manual monitoring, especially on large-scale construction projects. To overcome this, the You Only Look Once (YOLO) algorithm is used, which is able to detect objects quickly and accurately, to provide continuous monitoring of workers' conditions. This research focuses on the application of the YOLOv8n model in an automatic freshness and sleepiness facial expression detection system. The model is trained using a dataset that includes a variety of facial expressions in different situations, allowing the system to detect worker conditions in real-time and at scale. The evaluation results in this research show very good performance, with precision reaching 99.9%, recall 100%, mAP50 99.5%, and mAP50-90 97.9%. Although the model sometimes makes mistakes in object class recognition, the overall results still show a very high level of accuracy. With this system, it is hoped that it can improve work safety through early detection of signs of fatigue in workers, so that the potential for work accidents can be significantly minimized.
Co-Authors Fajar Rizkiyan Arief Febby Diansyah Hardiansyah Hardiansyah Muhammad Aldi Septian Muhammad Iqbal A Ocha Alfiano Ridwan Al-Husyairi Rinaldi Prasya