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All Journal JURNAL INTEGRASI Journal of Applied Electrical Engineering Community Development Journal: Jurnal Pengabdian Masyarakat
Dwijotomo, Abdurahman
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Humanities Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Public Health Other

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Smart Rack Inventory Berbasis RFID Untuk Manajerial Gudang Muharramsyah, Iqbal Fadjar; Mu'Arif, Samsul; Dwijotomo, Abdurahman; Kamarudin, Kamarudin; Ridwan, Ridwan
Journal of Applied Electrical Engineering Vol. 8 No. 2 (2024): JAEE, December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaee.v8i2.8562

Abstract

In warehouse management within the industry, there are often condition named stock-opname where physical stock and recorded stock do not match. This discrepancy can be caused by human error, as most of the input process work is still performed manually. To address this issue, this research developed Smart Rack Inventory capable of detecting items stored on the rack based on the RFID codes attached to the stored items. Additionally, an interactive web interface is utilized for managing storage and retrieving information about stored items. From the test results, the tool can easily record and display stored items with RFID tags when the orientation of the RFID sticker on the items aligns with the RFID sensor in the designed rack system. The success rate reached 100% at a distance of 60 cm. However, when the sticker's position is not aligned with the RFID sensor, where the RFID tag faces a direction opposite to the sensor, the smart rack system encounters difficulties in detecting and recording the item.
PELATIHAN PLC SISWA SMK DI KOTA BATAM Diono, Diono; Firdaus, Fadli; Dwijotomo, Abdurahman; Deviana, Yesi; Yangu, Juliansyah; Winandari, Rahmi Agustin
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2024): Volume 5 No. 2 Tahun 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v5i2.27917

Abstract

Perkembangan pendidikan tingkat menengah di Batam berfokus pada peningkatan kuantitas dan kualitas lulusann SMK yang mampu menyerap kebutuhan industri. Salah satu teknologi yang banyak digunakan adalah Programmable Logic Control (PLC). PLC merupakan alat kendali yang berfungsi untuk menerapkan desain kontrol otomatis pada mesin industri sesuai aturan dan langkah langkah kontrolnya. Namun demikin, seringkali kursus dan sertifikasi PLC membutuhkan biaya yang tidak sedikit. Ditambah lagi kebutuhan alat alat hardware dan software penunjang selalu berubah mengikuti perkembangan teknologi. Polibatam selaku gugusan terdepan pendidikan vokasi di kepulauan Riau turut serta ambil bagian dalam mengatasi masalah tersebut. Melalui program pengabdian kepada masyarakat, Polibatam melaksanakan pelatihan PLC untuk melatih peserta didik pendidikan menengah di sekitar Batam. Diharapkan nantinya lulusan siswa SMK dapat memiliki kemampuan untuk memprogram PLC dengan baik.
Project Based Learning: Sistem Otentifikasi melalui Deteksi Wajah untuk Akses Pintu Otomatis Berbasis Raspberry Pi Alifiansyah, Irfan; Akmal, Muhamad Raihan; Febrianto, Wahyu; Dwijotomo, Abdurahman; Fahruzi, Iman
JURNAL INTEGRASI Vol. 16 No. 2 (2024): Jurnal Integrasi - Oktober 2024
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v16i2.7646

Abstract

Security concerns are of utmost importance in our daily lives. Conventional door locking systems that rely on physical keys possess vulnerabilities in terms of security. Physical keys are susceptible to tampering, theft, and effortless replication. Hence, it is imperative to devise a novel approach that may effectively mitigate this issue. An example of technological use for alternative locks involves utilizing face recognition techniques to grant or deny access to doors depending on the data associated with the individual seeking entry. The primary objective of this study is to create a facial identification approach by employing machine learning techniques, namely the histogram of oriented gradients (HOG) method in conjunction with a linear Support Vector Machine (SVM). This technique is designed to be easily implemented on a Raspberry Pi 4-based Single Board Computer (SBC) that features a video sensor for machine learning input and a doorlock solenoid output. Initially, it is important to train the machine learning algorithm to accurately identify and distinguish the individual who is granted access to the door. The facial data is obtained through the capture of photographs that encompass variations in facial expression, positioning, and lighting conditions. The facial data photos are further analyzed using machine learning techniques to generate a dataset algorithm model capable of accurately identifying faces. When the system is operational and identifies a face that closely matches the trained model, the Raspberry Pi will activate the doorlock solenoid to unlock the door, and conversely, to lock the door. This approach offers security benefits as it restricts access to only those individuals whose facial features are registered in the dataset, hence allowing them to unlock the door. The developed face detection system has an accuracy rate of 83% and is compatible with computing devices possessing constrained computational capabilities, such as the SBC Raspberry Pi 4.
Co-Authors Akmal, Muhamad Raihan Alifiansyah, Irfan Deviana, Yesi Diono, Diono Fahruzi, Iman Febrianto, Wahyu Firdaus, Fadli Kamarudin Kamarudin Mu'arif, Samsul Muharramsyah, Iqbal Fadjar Ridwan, Ridwan Winandari, Rahmi Agustin Yangu, Juliansyah