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Steven Pragestu
Universitas Tanjungpura
Computer Science & IT

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Pengembangan Sistem Informasi Geografis Penerangan Jalan Umum Kota Pontianak dengan Integrasi Telegram Bot API Steven Pragestu; Juanda Astarani
Jurnal Teknik Informatika dan Teknologi Informasi Vol. 5 No. 3 (2025): Desember: Jurnal Teknik Informatika dan Teknologi Informasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jutiti.v5i3.6068

Abstract

Public Street Lighting (PJU) plays a crucial role in supporting community activities at night while ensuring the safety, comfort, and aesthetics of urban environments. However, in many regions, including Pontianak City, numerous streetlights remain non-functional for extended periods due to delayed damage reporting and the lack of an efficient monitoring system. This research aims to create a Public Street Lighting information system based on Geographic Information System (GIS) technology, integrated with the Telegram Bot API, to enhance the efficiency of damage reporting and response management. The system allows both the public to submit reports of malfunctioning lights through a web-based application, where the backend automatically sends notifications to administrators and technicians via Telegram. Data were collected through spatial data mapping, documentation, and interviews with the Head of the Road Equipment Division at the Pontianak City Transportation Department, followed by system design using the Waterfall model and testing through blackbox testing. The system visualizes the distribution and condition of streetlights on an interactive WebGIS map and records damage reports in real-time. The findings indicate that the integration of WebGIS and Telegram Bot API enhances the responsiveness and transparency of streetlight maintenance management. This innovation contributes to the realization of a smart city ecosystem by promoting community participation, improving infrastructure service efficiency, and supporting data-driven decision-making in local governance.
Co-Authors Juanda Astarani