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All Journal Jurnal Informatika dan Teknik Elektro Terapan CHAIN: Journal of Computer Technology, Computer Engineering and Informatics
Tiana Ramdani
Universitas Bina Insani
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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PENGUJIAN APLIKASI SAPAWARGA (JABAR SUPER APPS) MENGGUNAKAN METODE BLACK BOX TESTING Sugiarto Catrio Mulyo Rachmanto; Hebert Arya Agatha; Tiana Ramdani; Ade Yusuf Ardiyansyah; Ilham Avin Pratama; Achmad Sholehudin
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.4741

Abstract

Aplikasi Sapa Warga Jawa Barat adalah platform digital yang meningkatkan interaksi dan komunikasi antara pemerintah provinsi Jawa Barat dengan warganya. Aplikasi ini memungkinan warga melaporkan masalah, mengajukan pengaduan, dan mendapatkan informasi publik secara real-time, serta mendukung layanan e-Government untuk akses layanan pemerintahan online. Dirancang dengan antarmuka yang user-friendly, aplikasi ini tersedia untuk Android dan iOS. Melalui berbagai tahap pengujian fungsionalitas, kinerja, dan kompatibilitas, aplikasi ini memastikan kualitas dengan teknologi modern. Integrasi dengan layanan peta juga disertakan.Hasil kuesioner dari tahap uji beta, yang melibatkan 33 responden, menunjukkan bahwa 68,7% responden menilai aplikasi ini layak digunakan. 
Timbangan Digital Berbasis AIOT Dengan Deteksi Otomatis Jenis Buah Menggunakan YOLOv8 Dan Infrastruktur VPS Tiana Ramdani; Rully Pramudita
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 4 No. 3 (2026): Volume 4 Number 3 July 2026
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v4i3.310

Abstract

PT Interskala Mandiri Indonesia relies on manual input of Price Look Up (PLU) codes on the keypad for digital weighing, which results in human errors and lower operational efficiency. This study presents the development of an AIoT-based digital scale that integrates YOLOv8 for automatic fruit classification and leverages a Virtual Private Server (VPS) as a centralized data management infrastructure. The ADDIE model is used as the research and development framework. The hardware is built using an ESP32 NodeMCU-32S microcontroller, an ESP32-S3 CAM for image capture, and a load cell with an HX711 module for precise weight measurement. The YOLOv8n model was trained on five fruit classes (fuji apple, orange, lemon, century pear, and dragon fruit) and deployed on a VPS backend via Flask API. Receipt printing is performed through a Bluetooth T3 thermal printer using RawBT software, while monitoring is conducted through a React.js dashboard. Test results show that YOLOv8n achieved mAP@50 of 99.5%, precision of 99.97%, recall of 100%, and F1-score of 100%. The load cell provided 99.74% accuracy with a 0.26% error tolerance. All 25 Black Box Testing scenarios returned a Successful status. Average end-to-end latency was 7.55 seconds. The system proved capable of eliminating manual PLU input, centralizing transaction management, and providing a digital scale modernization solution for the retail industry.
Co-Authors Achmad Sholehudin Ade Yusuf Ardiyansyah Hebert Arya Agatha Ilham Avin Pratama Rully Pramudita Sugiarto Catrio Mulyo Rachmanto