Activity Monitoring and Detection of Rabbit Livestock Using Internet of Things (IoT) with Classification Tree (CT) Method - Dalam bentuk pengganti sidang - Artikel Jurnal
SEBASTIANUS EAGAN LILO
Informasi Umum
Kode
25.04.1317
Klasifikasi
000 - General Works
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Iot
Dilihat
84 kali
Informasi Lainnya
Abstraksi
Abstract— This research addresses the challenges of real time rabbit activity monitoring in farm management by implementing an IoT-based system with a Classification Tree (CT) method. The system uses an MPU6050 motion sensor integrated with a NodeMCU ESP32 microcontroller to collect acceleration and gyroscope data, which is transmitted to a MySQL database for analysis. The CT algorithm classifies rabbit activities into three categories: sleeping, eating, and moving. A balanced dataset of 1,768 samples ensured unbiased training, with the model achieving an accuracy of 72.13%. While effective, the complexity of the decision tree suggests a risk of overfitting, highlighting the need for optimization through additional features or alternative methods. This research demonstrates the potential of CT in IoT-based livestock monitoring, offering a practical approach to improve rabbit farm management. Future work could enhance accuracy and scalability for broader agricultural applications.
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Koleksi & Sirkulasi
Tersedia 1 dari total 1 Koleksi
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Pengarang
| Nama | SEBASTIANUS EAGAN LILO |
| Jenis | Perorangan |
| Penyunting | Muhammad Al Makky, Hilal Hudan Nuha |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S1 Teknologi Informasi |
| Kota | Bandung |
| Tahun | 2025 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
