| dc.contributor.advisor | Neyman, Shelvie Nidya | |
| dc.contributor.author | Putra, Zidan Febrian Indra | |
| dc.date.accessioned | 2025-08-13T06:40:07Z | |
| dc.date.available | 2025-08-13T06:40:07Z | |
| dc.date.issued | 2025 | |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/168964 | |
| dc.description.abstract | Pemanfaatan teknologi komunikasi radio masih banyak digunakan meskipun di tengah era modern, tetapi dalam penggunaannya masih banyak disalahgunakan sehingga menyebabkan gangguan terhadap pengguna frekuensi Radio Frequency Modulation (FM) karena tidak sesuai aturan. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem pemantauan frekuensi radio FM berbasis Internet of Things di Wilayah Bogor menggunakan HackRF(Radio Frequency)-SDR (Software Defined Radio) dan Raspberry Pi untuk pengolahan data guna memastikan tidak adanya pengguna frekuensi radio FM ilegal yang dapat mengganggu pengguna frekuensi radio FM legal. Prosedur kerja sistem yang dibuat yaitu memantau sinyal frekuensi radio FM, mengklasifikasi legaltias sinyal yang terdeteksi, dan menampilkan hasil secara otomatis di website berbasis Python dan Firebase, kemudian hasil pemantauan akan dianalisis menggunakan analisis statistik deskriptif untuk memastikan sistem pemantauan dan klasifikasi berfungsi dengan baik. Metode pengumpulan data meliputi observasi langsung, diskusi, dan studi pustaka. | |
| dc.description.abstract | The use of radio communication technology remains widespread despite the modern era, but its misuse often causes interference with legal Frequency Modulation (FM) radio frequency users due to non-compliance with regulations. This research aims to design and implement an FM radio frequency monitoring system based on the Internet of Things in the Bogor region using HackRF (Radio Frequency)-SDR (Software Defined Radio) and Raspberry Pi for data processing to ensure no illegal FM radio frequency usage disrupts legal FM radio frequency users. The system’s workflow involves monitoring FM radio frequency signals, classifying the legality of detected signals, and automatically displaying the results on a Python and Firebase-based website. The monitoring results will then be analyzed using descriptive statistical analysis to ensure the monitoring and classification system functions effectively. Data collection methods include direct observation, discussions, and literature studies. | |
| dc.description.sponsorship | | |
| dc.language.iso | id | |
| dc.publisher | IPB University | id |
| dc.title | Implementasi HackRF-SDR untuk Pemantauan Frekuensi Radio FM di Wilayah Bogor Berbasis IoT | id |
| dc.title.alternative | Implementation of HackRF-SDR for FM Radio Frequency Monitoring in the Bogor Area Based on IoT | |
| dc.type | Tugas Akhir | |
| dc.subject.keyword | SDR | id |
| dc.subject.keyword | Internet of Things (IoT) | id |
| dc.subject.keyword | Raspberry Pi 4 | id |
| dc.subject.keyword | Descriptive Statistical Analysis | id |
| dc.subject.keyword | Firebase | id |
| dc.subject.keyword | FM radio frequency | id |
| dc.subject.keyword | HackRFSDR | id |
