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Implementasi Sistem Hybrid Verifikasi Kehadiran Berbasis Embedded untuk Monitoring Distribusi MBG Aan Febriansyah; Lesta Lesta; Astria Jana Azzura; Ilham Faqih
Jurnal Inovasi Teknologi Terapan Vol. 4 No. 2 (2026): Jurnal Inovasi Teknologi Terapan
Publisher : Politeknik Manufaktur Negeri Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33504/jitt.v4i2.465

Abstract

Attendance-data validity was essential to support accurate distribution of the Free Nutritious Meals Program. This study designed and implemented a Raspberry Pi 4-based hybrid attendance-verification system with selectable facial and fingerprint recognition. Experimental engineering was applied through device design, dataset preparation, software integration, and subsystem and integrated-system testing. Facial recognition used YOLOv5n as a trigger, MediaPipe for face detection, MobileFaceNet for embedding extraction, and cosine similarity for identity matching. The dataset produced 1,172 valid embeddings from 30 students. Testing achieved 100% fingerprint success, 100% face-detection success, and 94.7% facial-recognition accuracy. All five storage and web-dashboard functions operated as designed. The system supported local, automatic, and integrated attendance recording; however, facial-recognition performance decreased under low illumination.
PERANCANGAN ALAT STERILISASI AIR KOLAM IKAN MENGGUNAKAN TEKNOLOGI OZONE Fakhrul Hendri; Muhammad Bayu Adjie Dhiastra; Peprizal Peprizal; Lesta Lesta
Prosiding Seminar Nasional Inovasi Teknologi Terapan Vol. 6 No. 1 (2026): Prosiding Seminar Nasional Inovasi Teknologi Terapan
Publisher : Politeknik Manufaktur Negeri Bangka Belitung

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Abstract

Water quality is a crucial factor affecting the growth, health, and survival of koi fish. This study aimed to design and implement a fish pond water sterilization system using ozone technology based on the ESP32 microcontroller and the Internet of Things (IoT) for real-time water quality monitoring. The proposed system consists of an ESP32, DFRobot pH sensor, DFRobot turbidity sensor, ACS712 current sensor, ZMPT101B voltage sensor, ozone generator, two water pumps, aerator, relay module, 16×2 I²C LCD, and Node-RED platform. The Research and Development (R&D) method was employed, including system design, hardware implementation, testing, and data analysis. Experimental results showed that the water pH increased from 6.8 to 7.4, while turbidity decreased from 100% to 0% after 60 minutes of ozone treatment. A four-day observation of four koi fish confirmed normal survival throughout the testing period. The developed system effectively improved water quality and enabled real-time IoT-based monitoring.