Pengenalan Suara Burung Menggunakan Mel Frequency Cepstrum Coefficient dan Jaringan Syaraf Tiruan pada Sistem Pengusir Hama Burung

Fajar Budiman, Muhammad Agung Nursyeha, Muhammad Rivai, Suwito .

Abstract


Indonesia is one of the agricultural country that produces crops. Nevertheless, Indonesia still imports rice from other countries because of crop decreasement. One of its factors is caused by bird pests. In the ricefields ecosystem, the variety of bird species can be classified as a pest and as a non-pest. Non-pest birds usually help farmer against insects. Farmers are using traditional methods to repel bird pests. In this research, a software to recognize species of birds has been designed. The system is based on birdchirp types. A mono-microphone is used to capture the sound. Voice Activity Detection (VAD) method is used for birdchirp detection. Mel Frequency Cepstrum Coefficient (MFCC) and Fast Fourier Transform (FFT) are used to extract birdchirp feature. Artificial Neural Network is utilized to recognize the pattern of  birdchirp feature. Furthermore, audiosonic bird repeller is used to repel bird pests. In the offline mode testing, success level using MFCC feature extraction is up to 90% for birdchirp variation, while up to 68% using FFT. In the online mode, the average success level using MFCC feature extraction is 70% for finch birds, while 30% using FFT. In addition, a gunshot is a best sound to repel bird pests. The success rate of bird voice recognitions using MFCC feature extraction is higher than that using FFT. 

Keywords : Bird pests, Voice Activity Detection, Fast Fourier Transform, Mel Frequency Cepstrum Coefficient.


Abstrak—Indonesia merupakan salah satu negara agraris yang memproduksi hasil pertanian. Namun, Indonesia masih mengimpor beras dari negara lain dikarenakan penurunan hasil panen. Salah satu faktor menurunnya produksi beras Indonesia adalah akibat serangan hama burung. Ekosistem sawah mengandung berbagai macam spesies burung, baik hama maupun non-hama. Burung non-hama menolong petani melawan hama serangga. Petani menggunakan metode tradisional untuk mengusir hama burung. Pada penelitian ini telah dirancang perangkat lunak untuk mengenali jenis burung berdasarkan kicauannya. Voice Activity Detection (VAD) digunakan untuk mendeteksi adanya kicau burung. Metode ekstraksi ciri suara dari kicau burung menggunakan Mel Frequency Cepstrum Coefficient (MFCC) dan Fast Fourier Transform (FFT). Jaringan Syaraf Tiruan digunakan untuk mengenali pola hasil ekstraksi. Selanjutnya, audiosonic bird repeller digunakan sebagai metode pengusiran hama burung. Hasil identifikasi offline dengan menggunakan MFCC didapatkan tingkat keberhasilan mencapai 90% untuk variasi kicauan dan jenis burung, sedangkan dengan FFT mencapai 68%. Hasil identifikasi online untuk spesimen burung bondol didapatkan tingkat keberhasilan 70% dengan menggunakan MFCC, dan 30% dengan FFT. Selain itu, suara tembakan merupakan suara yang paling baik digunakan untuk mengusir hama burung. Tingkat keberhasilan pengenalan suara burung menggunakan ekstraksi ciri MFCC lebih tinggi jika dibandingkan dengan ekstraksi ciri dengan menggunakan FFT.

Kata Kunci : Hama Burung, Voice Activity Detection, Fast Fourier Trasnform, dan Mel Frequency Cepstrum Coefficient.



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DOI: https://doi.org/10.25077/jnte.v5n1.191.2016

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