Implementasi Algoritma Machine Learning untuk Klasifikasi Suara Lingkungan: Implementation of Machine Learning Algorithm for Environmental Sound Classification

Ari Wibowo; Auliya Rahman Isnain

doi:10.57152/malcom.v5i2.1712

Authors

Ari Wibowo Universitas Teknokrat, Indonesia
Auliya Rahman Isnain Universitas Teknokrat, Indonesia

DOI:

https://doi.org/10.57152/malcom.v5i2.1712

Keywords:

Algoritma, Klasifikasi, Machine Learning, Suara, Suara Lingkungan

Abstract

Suara lingkungan memiliki peran signifikan dalam menentukan kualitas hidup manusia dan keseimbangan ekosistem. Dengan meningkatnya urbanisasi dan perubahan iklim, pemantauan suara lingkungan menjadi krusial. Penelitian ini mengimplementasikan algoritma Machine Learning untuk mengklasifikasikan suara lingkungan menggunakan dataset ESC-50. Fitur-fitur seperti Mel-Frequency Cepstral Coefficients (MFCCs) dan Chroma digunakan untuk ekstraksi ciri. Setelah pra-pemrosesan data, dilakukan pemodelan dengan berbagai algoritma, termasuk KNeighbors Classifier, Random Forest Classifier, dan Extra Tree Classifier, yang kemudian dipilih untuk tuning hyperparameter. Dengan parameter optimal, dilakukan training pada model terpilih dan diuji pada dataset uji. Hasil menunjukkan KNeighbors Classifier memiliki akurasi tertinggi sebesar 63%. Studi ini memberikan kontribusi pada pengembangan teknologi pemantauan suara lingkungan dan membuka prospek penerapan dalam manajemen kota yang lebih efisien. Studi lanjutan disarankan untuk eksplorasi fitur-fitur suara yang lebih spesifik, penggunaan teknik deep learning, dan penggunaan dataset yang lebih luas untuk solusi yang lebih canggih dalam pemahaman dan manajemen suara lingkungan secara global.

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