SISTEM CERDAS MONITORING KANDANG KENARI BERBASIS IoT DENGAN ALGORITMA C.45 THINGSPEAK

Authors

  • Anderias Eko Wijaya Universitas Mandiri
  • Ade Irfan Universitas Mandiri
https://doi.org/10.47561/a.v15i1.220
This Abstract has been read 15 times

Abstract

Kenari birds are one of the singing birds that have a very beautiful voice, the melody and variety of their crooks are very numerous, from there the opportunity arises to try breeding kenari birds because their price also has a high economic value and can be developed into a business that continues to grow. In the making of cages, the temperature of the environment (temperature of the animal cage environment) must also be studied. In addition, the safety of kenari from insect and rat disturbances must also be considered. The room temperature conducive for kenari livestock is between 23 and 27 C°.

This study aims to maintain the quality of the temperature of the kenari bird cage to remain well preserved, thereby maintaining the health of the livestock birds. The data is calculated and processed using the DHT11 microcontroller sensor to maintain the temperature and humidity of the cage, the distance sensor for bird feed automatically by looking at the distance of the feeding place, the data is sent to thingspeak and then processed using the C4.5 algorithm and produces an accuracy level of 86%.

Keywords: Internet of Things, Kandang Burung Kenari, Algoritma C4.5

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Author Biography

Anderias Eko Wijaya, Universitas Mandiri

Program Studi Teknik Informatika Fakultas Teknik Universitas Mandiri

References

Aryana, I. (2018). Burung Lovebird dan Kebudayaannya. UNIKOM, 6 - 34.

Danukusumo, K. P. (2017). IMPLEMENTASI DEEP LEARNING MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK UNTUK KLASIFIKASI CITRA CANDI BERBASIS GPU. UAJY.

Fajar, R. N. (2016, 11). Pengertian Fungsi dan Jumper.

Han, J., & Kamber, M. (2006). “Data Mining: Concepts and Techniques. Morgan Kaufmann”.

Imam, & Rohima. (2016). Budi Daya Burung Kenari. UNIKOM, 1-28.

Karimireddy, S. P., Satyen , S., Mohri, M., Reddi, S., Stich, S., & Suresh , A. T. (2022). SCAFFOLD: Stochastic Controlled Averaging for Federated Learning. Proceedings of Machine Learning Research, 5132-5143.

Malimba, K., & Purbakawaca, R. (2014). Breadboard si papan projek. ACADEMIA.

moderndevice.com. (2021). Retrieved from https://moderndevice.com/?s=breadboard&post_type=product&dgwt_wcas=1

Mucthar, F. R., Wibowo, S. A., & Ariwibisono, F. X. (2020). PENERAPAN IoT (Internet of Thing) TERHADAP RANCANG BANGUN SANGKAR BURUNG PINTAR UNTUK BURUNG TERIEP. JATI (Jurnal Teknik Informatika), 162 - 170.

Sandi, T. H., & Agung, A. I. (2020). RANCANG BANGUN SISTEM PENGISIAN PAKAN DAN MINUM BURUNG OTOMATIS BERBASIS ARDUINO UNO. Jurnal Teknik Elektro, 799 - 805.

Shaleh, M. (2017). RANCANG BANGUN SISTEM KEAMANAN RUMAH MENGGUNAKAN RELAY. Teknologi Elektro.

Published

2022-12-31

How to Cite

[1]
A. E. Wijaya and A. Irfan, “SISTEM CERDAS MONITORING KANDANG KENARI BERBASIS IoT DENGAN ALGORITMA C.45 THINGSPEAK”, JTIK, vol. 15, no. 1, Dec. 2022.

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Articles