Rancang Bangun Sistem Informasi Keamanan Sepeda Motor Berbasis Internet Of Thinks (IoT) Fingerprint Scanner dan Dashboard

Dannie, Faruqi Aldi (2025) Rancang Bangun Sistem Informasi Keamanan Sepeda Motor Berbasis Internet Of Thinks (IoT) Fingerprint Scanner dan Dashboard. Diploma thesis, UIN Raden Intan Lampung.

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Abstract

ABSTRAK Sepeda motor merupakan transportasi utama masyarakat Indonesia karena terjangkau dan praktis, namun rawan pencurian. Data BPS RI (2024) mencatat 20.978 kasus pencurian kendaraan bermotor, termasuk 648 kasus di Provinsi Lampung pada 2023, dengan Lampung Timur sebagai salah satu wilayah tertinggi. Penelitian ini mengembangkan sistem keamanan sepeda motor berbasis Internet of Things (IoT) dengan autentikasi sidik jari, pelacakan GPS, dan kontrol melalui dashboard. Sistem memanfaatkan sensor R503, GPS Neo M8N, mikrokontroler ESP32, dan GSM SIM900A sebagai media komunikasi. Metode yang digunakan adalah Research and Development (R&D) dengan enam tahap. Pengujian menunjukkan sensor sidik jari berhasil 100% pada kondisi normal (810–1220 ms), GPS akurat di area terbuka, dan kontrol mesin serta notifikasi memiliki rata-rata delay 1270 ms. Sistem berfungsi baik dan terintegrasi, memungkinkan pengguna mengendalikan mesin, memantau lokasi, dan menerima notifikasi real time, sehingga menjadi solusi praktis untuk meningkatkan keamanan kendaraan di wilayah rawan pencurian.ABSTRAK Motorcycles are the primary mode of transportation in Indonesia due to their affordability and practicality, yet they are vulnerable to theft. According to Statistics Indonesia (BPS RI, 2024), there were 20,978 motorcycle theft cases nationwide, including 648 cases in Lampung Province in 2023, with East Lampung being among the highest. This study develops an Internet of Things (IoT)-based motorcycle security system featuring fingerprint authentication, GPS tracking, and dashboard control. The system utilizes an R503 fingerprint sensor, Neo M8N GPS module, ESP32 microcontroller, and SIM900A GSM module for communication. The research method applied is Research and Development (R&D) with six main stages. Testing results show a 100% fingerprint authentication success rate under normal conditions (810–1220 ms), accurate GPS positioning in open areas, and an average delay of 1270 ms for engine control and security notifications. The system functions effectively and is well-integrated, enabling users to control the engine, monitor location, and receive real-time notifications, providing a practical solution to improve vehicle security in theft-prone areas.

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