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Sistem Deteksi Plat Nomor Kendaraan Pada Aplikasi Mobile Tiket Pariwisata Ilham Albana; Ecky Efansyah Sukoco; Akbar Fitrian; Anugerah Bagus Wijaya; Aulia Hamdi; Fiby Nur Afiana; Zanuar Rifai
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 8 No. 1 (2025): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v8i1.39259

Abstract

Vehicle license plate recognition plays a vital role in intelligent transportation systems, parking management, and digital ticketing. However, conventional license plate recognition systems often face challenges related to lighting variations, viewing angles, and character distortions, which can decrease accuracy and efficiency, especially on mobile devices. This study aims to implement an Optical Character Recognition (OCR) framework, specifically EasyOCR, in a mobile application designed to read vehicle license plates in real time. The system was developed using the Software Development Life Cycle (SDLC) methodology, which includes the stages of planning, analysis, design, implementation, and testing. The mobile application was built using Flutter, integrated with a smartphone camera for data input and EasyOCR for text extraction. The testing results demonstrate that the proposed system can accurately detect and recognize license plate characters with an average accuracy rate of 100%. The contribution of this study lies in the application of EasyOCR on mobile platforms through a structured SDLC approach, enhancing the practicality of OCR-based vehicle identification systems for real-world transportation and parking management applications.
Analisis Pola Konsumsi Air Menggunakan Algoritma Random Forest Classifier Pada Distribusi Air Bersih Desa Rempoah Baturraden Ngarifatul Khofiyah, Salma; Hamdi, Aulia; Nur Isnaini, Khairunnisak
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.3001

Abstract

Clean water is a basic necessity for communities that must be managed efficiently to ensure its distribution remains equitable and sustainable. In Rempoah Village, water usage is still recorded manually, making it difficult to analyze consumption patterns and detect irregular usage. This study aims to analyze water consumption patterns using the Random Forest Classifier algorithm as an effort to support clean water distribution management by the Berkah Maju Bersama Village-Owned Enterprise (BUMDes). The research data was obtained through observation and interviews with the management, followed by a data preprocessing stage that included data cleaning, missing value handling, data exploration, label encoding, and data division into training and test data. The Random Forest model was used to classify water consumption patterns into three categories, namely economical, normal, and wasteful. The results showed that the model was able to classify the data with an accuracy rate of 100%, where all test data was correctly identified. Based on the analysis results, most customers were in the wasteful category at 56.2%, indicating the need for an evaluation of the efficiency of household water use. These findings prove that the application of machine learning methods can be an effective solution in supporting decision-making and clean water management at the village level in a sustainable manner.
Dynamic IoT–PID Control for Energy-Efficient Water Distribution: EPANET-Based Digital Twin Validation in Varied Geographical Terrains Kusuma, Bagus Adhi; Isnaini, Khairunnisak Nur; Hamdi, Aulia
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1188

Abstract

Topographical heterogeneity in water distribution networks frequently causes pressure imbalance, hydraulic inefficiency, and elevated energy consumption, particularly in regions with significant elevation gradients. This study aims to develop and validate a dynamic Internet of Things (IoT)-based pressure control model within a cyber–physical system framework for energy-efficient water distribution under varied geographical conditions. The primary contribution of this work lies in the separation of strategic and tactical control layers, where a Digital Twin based on EPANET dynamically generates optimal pressure setpoints, while distributed proportional–integral–derivative controllers execute real-time valve regulation at the network edge. The research adopts a Design Science Research methodology to design, implement, and evaluate a four-layer architecture consisting of physical sensing and actuation, long-range communication, tactical control, and strategic simulation layers. Validation is conducted using EPANET-based simulations across three control scenarios: a baseline condition without dynamic control, a static rule-based valve control scenario, and the proposed dynamic IoT–PID control scenario. The experimental procedure involves comparative analysis using control performance metrics including overshoot, settling time, steady-state error, and root mean square error. Simulation results demonstrate that the baseline configuration suffers from severe pressure imbalance and hydraulic backflow, while static rule-based control partially mitigates inefficiencies but fails to adapt to demand variability. In contrast, the proposed dynamic IoT–PID approach achieves precise pressure regulation with overshoot below 2% and tracking error maintained under 0.5 meters across all evaluated scenarios. These findings confirm that integrating a Digital Twin with real-time PID control significantly improves pressure stability and operational efficiency. The proposed architecture offers practical implications for smart water infrastructure in geographically diverse regions, providing a scalable foundation for adaptive pressure management, energy optimization, and future digital-twin-driven water distribution systems.
Peningkatan Efisiensi Distribusi Air Bersih melalui TirtaDesa: Digitalisasi PAMSIMAS untuk Desa Berkelanjutan Pramono, Agus; Hamdi, Aulia; Supriyana, Nana; Shafa Salsabila, Lulu; Fatnurivan, Ardika
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 10 No 1 (2026): Februari
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/aks.v10i1.28355

Abstract

Tata kelola air bersih di BUMDes Berkah Maju Bersama Desa Rempoah menghadapi kendala inefisiensi operasional akibat sistem administrasi manual yang menyebabkan lambatnya proses penagihan dan kerentanan data. Kegiatan pengabdian kepada masyarakat ini bertujuan mengimplementasikan transformasi digital melalui penerapan sistem Tirta Desa guna meningkatkan akurasi data, efisiensi waktu, dan kompetensi pengelola. Metode pelaksanaan dilakukan selama empat bulan dengan pendekatan partisipatif yang mencakup tahapan sosialisasi, konfigurasi perangkat lunak, migrasi data pelanggan, pelatihan intensif bagi petugas, serta pendampingan teknis berkelanjutan. Hasil kegiatan menunjukkan keberhasilan migrasi 542 data pelanggan ke dalam sistem digital tanpa kehilangan informasi. Secara kuantitatif, implementasi sistem terbukti memangkas waktu pemrosesan tagihan bulanan secara signifikan dari sembilan jam menjadi 1,5 jam, serta meningkatkan kompetensi enam petugas operasional dengan kenaikan skor evaluasi dari 57,4 menjadi 82,1. Selain itu, tersedianya dashboard berbasis web dan integrasi kode QRCode telah mempermudah pemantauan transaksi secara transparan. Dapat disimpulkan bahwa digitalisasi tata kelola air merupakan solusi efektif untuk optimalisasi layanan BUMDes, di mana keberlanjutan program didukung oleh penyusunan standar operasional prosedur dan rencana pengembangan fitur sinkronisasi data luring.