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All Journal TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Teknik: Jurnal Ilmu Teknik dan Informatika
Pandiangan, Daniel
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Analisis dan Implementasi Sistem Antrian Digital Berbasis Web untuk Optimalisasi Layanan Perbankan Modern Alifya Aisya, Alifya Aisya; Bastio, Aldrik; Pandiangan, Daniel; Niska, Debi Yandra
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8705

Abstract

This study aims to analyze and develop a web-based digital queuing system designed to significantly enhance the efficiency of banking services in the digital age. The urgent problem identified is the suboptimal management of customer queues, which frequently leads to prolonged waiting times and ultimately diminishes customer satisfaction with the bank's services. We constructed this system using the foundational web technologies of HTML, CSS, and JavaScript, primarily targeting the creation of an interface that is user-friendly, visually comfortable, and accessible from any gadget. The research was conducted at Bank Nusantara Branch in Medan. The methodology involved direct observation of the current manual queuing process, coupled with brief discussions (interviews) with several customers and staff to accurately grasp the specific needs. The key contribution of this study is the successful creation of a comprehensive draft design for a digital queuing system, which can serve as a concrete guideline for other banks. This initial result presents a system draft enabling customers to take and monitor their queue position from anywhere. The expectation is that this solution will significantly cut waiting times and elevate the overall customer experience. As a concluding step, the system will undergo thorough testing and user satisfaction evaluation to ensure its readiness for actual implementation in the banking sector.
Perancangan Sistem Pemesanan Online E-Kopma Mahasiswa Berbasis Web Widjayani, Alifya Aisya; Bastio, Aldrik; Pandiangan, Daniel; Niska, Debi Yandra
JURNAL FASILKOM Vol. 16 No. 1 (2026): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v16i1.11338

Abstract

The development of information technology is now increasingly driving digital transformation in various fields, except for student cooperatives. Currently, KOPMA FMIPA Universitas Negeri Medan still relies on traditional ordering methods that often result in long queues, slow service, plus suboptimal data management. Therefore, this research focuses on creating and developing an online ordering system via the web (E-KOPMA) to overcome these problems. The way it works uses the Waterfall model to create the software, starting from analyzing what is needed, system design, coding, to testing. The system is built with PHP and MySQL, plus the illustration uses UML. For testing, Black Box Testing is used so that all features work as expected. From the results, this system really helps ease the process of ordering goods, reduce the number of queues, and make service smoother. Key features such as login, managing product stock, shopping carts, and payment processes, all work well and pass the test. So, E-KOPMA can be the right answer to improve service quality plus manage buying and selling data faster and more precisely
Perancangan Sistem Penerjemah Bahasa Isyarat bagi Tunarungu dan Tunawicara Berbasis Pengolahan Citra Digital dan Text-to-Speech Trianto, Nafil Rizq; Wijaya, Alfarizi; Pardede, Arion; Pandiangan, Daniel; Syahputra, Hermawan
Teknik: Jurnal Ilmu Teknik dan Informatika Vol. 6 No. 1 (2026): Mei : Teknik: Jurnal Ilmu Teknik dan Informatika
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/teknik.v6i1.1156

Abstract

Communication is an essential human right, yet a significant communication gap persists between individuals with sensory disabilities, specifically the deaf and speech-impaired, and the general public. While many technological solutions have been proposed to translate sign language, existing models primarily rely on heavy deep learning architectures such as Convolutional Neural Networks (CNN) or Recurrent Neural Networks (RNN/LSTM). These models often demand high computational power, leading to latency and limiting real-time application on standard devices. This study proposes a lightweight, fast, and highly responsive sign language translation system specifically designed to recognize static alphabets (A-Z) and single-character air writing. The system utilizes MediaPipe for hand tracking, where feature extraction is intelligently processed by calculating the relative spatial coordinates of fingertips to the wrist, reducing dependency on raw camera coordinates. Classification is performed using a Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel, prioritizing computational efficiency without sacrificing accuracy. To enhance user experience, the system introduces three key novelties: smart relative feature extraction, an anti-duplication hold system with a 1-second timer to prevent input spamming, and a non-blocking multithreaded audio execution (Daemon Thread) utilizing Google Text-to-Speech (gTTS), ensuring the webcam feed remains fluid during audio playback. Additionally, an alternative air-writing mode is integrated, utilizing geometric heuristics and PyTesseract OCR to read single drawn letters in the air. The results indicate that the proposed system operates swiftly and efficiently, bridging the communication barrier with a hardware-friendly approach.
Co-Authors Alifya Aisya, Alifya Aisya Bastio, Aldrik Hermawan Syahputra Niska, Debi Yandra Pardede, Arion Trianto, Nafil Rizq Widjayani, Alifya Aisya Wijaya, Alfarizi