Pengenalan Suara Burung Menggunakan Mel Frequency Cepstrum Coefficient Dan Jaringan Syaraf Tiruan Pada Sistem Pengusir Hama Burung

Nursyeha, Muhammad Agung (2016) Pengenalan Suara Burung Menggunakan Mel Frequency Cepstrum Coefficient Dan Jaringan Syaraf Tiruan Pada Sistem Pengusir Hama Burung. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Indonesia merupakan salah satu negara yang memproduksi hasil pertanian untuk kebutuhan pangan. Indonesia masih mengimpor beras dari negara tetangga. Produksi beras Indonesia menurun akibat serangan hama burung. Ekosistem sawah mengandung berbagai macam spesies burung, baik hama maupun bukan hama. Pada tugas akhir ini telah dirancang perangkat lunak untuk mengenali jenis burung berdasarkan kicau yang dihasilkan. Untuk menangkap suara kicau burung digunakan mikrofon mono. Untuk mendeteksi adanya kicau burung digunakan metode Voice Activity Detection (VAD). Untuk metode ekstraksi ciri suara dari kicau burung digunakan Mel Frequency Cepstrum Coefficient (MFCC) dan Fast Fourier Transform (FFT). Untuk mengenali pola hasil ekstraksi ciri digunakan Jaringan Syaraf Tiruan. Untuk metode pengusiran hama burung digunakan audiosonic birds repeller. Hasil dari pengujian offline pada lokasi indoor dengan menggunakan metode MFCC didaptkan tingkat keberhasilan mencapai 90% untuk variasi kicauan dan jenis burung, Sedangkan dengan metode FFT mencapai 68% untuk variasi kicauan dan jenis burung. Hasil dari pengujian online pada lokasi indoor untuk spesimen burung bondol dengan menggunakan MFCC, didapatkan tingkat keberhasilan 60% hingga 80%, Sedangkan hasil dari pengujian dengan FFT didapatkan tingkat keberhasilan 27% hingga 30%. Metode pengusiran menggunakan suara tembakan menghasilkan tiga kali keberhasilan dari sepuluh percobaan untuk spesimen burung bondol. ============================================================================================================== Indonesia is known as agricultural country. It means that Indonesia produces crops for domestic demand. Nowdays, Indonesia imports rice from other countries. It is caused by rice crops decreasement. A pests is a rice crops decreasement factor. An example of pest in the ricefields is a birds. Indonesian farmers are still using traditional methods to repel bird pest. In the ricefields ecosystem contains variety of bird species. Variety of bird species in the ricefields could be classified as a pest and as not a pest. A kind of birds which is classified as not a pest usually helps farmer to repel insects. In this final project has been designed a software to recognize species of birds. Recognizing system is based on birdsong its generate. For listening an environtment sound is used mono microphone. In this final project is used Voice Activity Detection for birdsong detection methods. Mel Frequency Cepstrum Coefficient and Fast Fourier Transform are used to extract birdsong feature. Artificial Neural Network is used to recognize pattern of birdsong feature. Audiosonic birds repeller is used to repel bird pests. In the offline testing, Success level with MFCC feature extraction is up to 90% for birdsong variation, while success level with Fast Fourier Transform is up to 68% for birdsong variation. In the online tesing, success level with MFCC feature extraction is between 60% and 80% for finch birds, while success level with Fast Fourier Transform is between 27% and 33% for finch birds. Repelling method with shotgun has three times succes of ten trials.

Item Type: Thesis (Undergraduate)
Additional Information: RSE 006.4 Nur p 3100016064935
Uncontrolled Keywords: Hama Burung, Voice Activity Detection, Fast Fourier Trasnform, Mel Frequency Cepstrum Coefficient.
Subjects: Q Science > Q Science (General) > Q337.5 Pattern recognition systems
Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science)
Divisions: Faculty of Industrial Technology > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User: Yeni Anita Gonti
Date Deposited: 16 Sep 2020 04:02
Last Modified: 16 Sep 2020 04:05
URI: https://repository.its.ac.id/id/eprint/81935

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