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All Journal TEKNIK Jurnal Transformatika Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Dinamisia: Jurnal Pengabdian Kepada Masyarakat SINTECH (Science and Information Technology) Journal Jurnal Sisfokom (Sistem Informasi dan Komputer) Technomedia Journal Building of Informatics, Technology and Science JUTIS : Jurnal Teknik Informatika Jurnal ABDINUS : Jurnal Pengabdian Nusantara Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat DECODE: Jurnal Pendidikan Teknologi Informasi The Indonesian Journal of Computer Science
Rochadiani, Theresia Herlina
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Journal : Building of Informatics, Technology and Science

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Klasifikasi Suara Anjing Menggunakan Pretrained Model Yet Another Mobile Network Berbasis Convolutional Neural Network Djuardi, Rich Deshan; Rochadiani, Theresia Herlina
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5165

Abstract

In everyday life, pets such as dogs often become an inseparable part of human life. Motivations for keeping a pet can vary from individual to individual, ranging from the need for a loyal companion to the responsibility of caring for another living creature. Among the various choices of pets, dogs are often considered the most loyal and loyal friends towards humans. This uniqueness makes many people choose to keep dogs as part of their family. Often, dog owners may not understand the message that the sounds produced by their beloved pets are trying to convey. These dog sounds have a special purpose that can reflect various emotions, such as joy, sadness, or anger. A dog's voice can also be an indicator of their health that owners need to pay attention to. The main focus of this research is to develop dog voice classification technology to help owners understand and communicate with their pet dogs. In this research, a pre-trained YAMNet model is used as a basis for classifying various audio events. The model training process uses the CNN algorithm contained in the YAMNet architecture. The total data used was 373 data which were classified into 4 classes, namely, bark, howling, growling, whimper. The results of this research model achieved 97.8% accuracy with precision, recall and f1-scores for each class >= 95%.
Co-Authors Anggraini, Astria Febrian Aprilia, Novia Pramesti Cahyadi, Marcelinus Fajar Canady, Richwen Chitiawan, Tommy Danendra, Danica Recca Djuardi, Rich Deshan Fernando, Felix Gabrielle Sheila Sylvagno Hadibrata, Lymanto Indrawan, Vincenzo Matalino Ito Wasito Jaklin, Vanessa Jericho, Vito Jiustian, Danny Karyadi, Phance Laurenso, Justin Mandasari, Rhea Mayatopani, Hendra Muhammad Muhammad Novia Pramesti Aprilia Panna, Ariya Purnomo, Bryan Elmer Santoso, Handri Sofian, Thamrin steven willian Sucipto, Nadya Rudie Suhandi, Vartin Tanaka, Steven Tanuwijaya, Yefta Thamrin Sofian Thendiwijaya, Alfred Gerald Tua, Jonathan Erik Maruli Wulandari , Islamiati