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All Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Journal of The Civil Engineering Student
Muzammil, Rivaul
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Transportation

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Pemenuhan Jaringan Air Minum IPA Glee Dagang Untuk Sistem Air Minum di Kecamatan Muara Batu dan Kecamatan Dewantara Kabupaten Aceh Utara Muzammil, Rivaul; Fauzi, Amir; Ziana, Ziana
Journal of The Civil Engineering Student Vol 3, No 1 (2021): Volume 3, Nomor 1, April 2021
Publisher : Jurusan Teknik Sipil, Fakultas Teknik, Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/journalces.v3i1.12279

Abstract

Air minum merupakan penentu peningkatan kesejahteraan masyarakat, dengan Sistem Penyediaan Air Minum yang sudah beroperasi di Kecamatan Muara Batu dan Kecamatan Dewantara Kabupaten Aceh Utara belum bekerja optimal. Sistem ini diolah oleh IPA Glee yang pada saat ini kapasitas intake yang tersedia 90 l/d namun hanya sekitar 40 liter/detik yang mengalir. Tujuannya untuk mengevaluasi jaringan distribusi dengan memperoleh diameter pipa, debit aliran, kecepatan aliran, dan tekanan aliran yang baru. Data yang digunakan dalam studi ini berupa data pelanggan aktif, data penduduk, serta perhitungan jaringan eksisting. Simulasi pengembangan jaringan baru menggunakan software EPANET 2.0. Untuk masing-masing Kecamatan hasil yang didapatkan adalah jumlah penduduk yang diproyeksikan sampai tahun 2035 dengan diameter pipa sebesar 75 mm sampai 500 mm dengan debit aliran terbesar 47,62 l/d dan 21,23 l/d. Tekanan aliran terbesar 95,92 m dan 87,65 m. Kesimpulanya kebutuhan telah dioptimalkan lebih dari 40 l/d serta kecepatan dan tekanan yang meningkat.
Implementation of Convolutional Recurrent Neural Network for Vehicle Number Plate Identification in Raspberry Pi Based Parking System Muzammil, Rivaul; Oktiana, Maulisa; Roslidar, Roslidar
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 4, November 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i4.2320

Abstract

The rapid growth of vehicles in Indonesia has created significant challenges in managing parking facilities. To address this issue, this study proposes an intelligent parking system based on automatic license plate character recognition. The system employs YOLOv8 (You Only Look Once) for license plate region detection and CRNN (Convolutional Recurrent Neural Network) for alphanumeric character recognition. Its architecture integrates a Raspberry Pi, camera module, and servo motor to enable automated license plate detection and recognition during vehicle entry and exit. YOLOv8 generates bounding boxes to isolate license plate regions, which are then processed as input for CRNN. The CRNN extracts visual features through convolutional layers and captures sequential relationships among characters using recurrent layers. The entire pipeline is deployed on Raspberry Pi with TensorFlow Lite to ensure efficient computation in resource-constrained environments. Experimental results demonstrate that YOLOv8 achieved a detection accuracy of 94.69%, with a precision of 98.32%, recall of 96.25%, and F1-score of 97.27%, while CRNN reached a character recognition accuracy of 93.8% across 30 license plates. Although some recognition errors occurred, such as misclassifying ‘G’ as ‘C’, 'W' as 'H', and 'Q' as 'O', the proposed system proved effective and feasible for embedded smart parking applications.
Co-Authors . Roslidar Amir Fauzi Oktiana, Maulisa Ziana, Ziana