Jurnal SINTA 2
Mendeteksi Jenis Burung Berdasarkan Pola Suaranya
Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 3 No. 2 (2016) · pp. 126–132
- ISSN
- 2528-6579, 2355-7699
- Published
- 2016-06-20
- Publisher
- Fakultas Ilmu Komputer, Universitas Brawijaya
- Language
- en
Abstract
AbstrakIlmuwan biologi terutama di bidang biodifersitas, terus melakukan penelitian tentang spesies hewan yang ada di dunia. salah satu hewan yang spesiesnya memiliki banyak variasi adalah burung. Tiap jenis burung memiliki perbedaan-perbedaan, mulai dari bentuk anggota tubuhnya, prilakunya, makanannya hingga suaranya. Ilmuwan sering juga mengalami kesulitan untuk melakukan pengamatan di alam. Misalnya, untuk mengetahui spesies burung apa saja yang ada di suatu daerah, mereka harus hadir di suatu wilayah, dan menelusuri setiap pelosok. kadang kala kehadiran mereka di tempat tersebut dalam jangka waktu lama, malah mengusik burung yang ada, dan burung-burung malah pergi meninggalkan tempat, sebelum berhasil diamati. Salah satu cara untuk mendeteksi burung apa saja yang ada di suatu wilayah, tanpa harus mengusik keberadaan burung adalah dengan menggunakan alat bantu. Bisa dengan menggunakan kamera video untuk mengambil gambar lingkungan sekitar, atau dengan perekam suara, untuk merekam suara burung yang ada di sana. Untuk itu penelitian ini ditujukan untuk membuat sebuah pengklasifikasi suara burung secara otomatis. Fitur yang digunakan adalah rhythm, pitch, mean, varian, min, max, dan delta dari suara burungnya. dari hasil klasifikasi 4 jenis burung, didapatkan hasil rata-rata akurasi terbaik sebesar 88.82%. Kata Kunci: suara burung, klasifikasi, rhythm, pitchAbstractMany of Biologi scientist, especially in the field of biodiversity, conduct research on the animal species that exist in the world. One of the animal which is largely diverse in species is bird. Each species of birds have differences, from the shape of his body, his behavior, his food to it's voice. Scientists often find it difficult to make observations in nature. For example, to determine which species of birds present in an area, they should be present in an area, and explore every corner. sometimes their presence in that place for a long time, even disturb the bird, and they leaving the place, before been observed. One way to detect any bird that is in an area, without having to disturb the presence of birds is to use the automatic tools. For example to use a video camera to take pictures of the surrounding environment, or with voice recorders to record the sound of the birds that were there. This study is aimed to create a classifier bird sound automatically. Features used are rhythm, pitch, mean, variance, min, max, and delta of the bird sound samples. of the results of the classification of four types of birds, showed the best average of accuracy is 88.82%. Key Word: bird song, classification, rhythm, pitch.
Collaboration network of the authors
40 authors · 108 co-authorship links · 3 across different organisations · showing the 40 most connected
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- University of Brawijaya
- Universitas Amikom Purwokerto
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Arief Andy Soebroto | University of Brawijaya | 3 |
| Daneswara Jauhari | University of Brawijaya | 3 |
| Dhimas Anjar Prabowo | University of Brawijaya | 3 |
| Fitra Abdurrachman Bachtiar | University of Brawijaya | 3 |
| Sutrisno . | Affiliation unknown | 2 |
| Nurul Hidayat | University of Brawijaya | 2 |
| Canny Amerilyse Caesar | University of Brawijaya | 2 |
| Latifah Hanum | University of Brawijaya | 2 |
| Muhammad Fhadli | University of Brawijaya | 2 |
| Anang Hanafi | University of Brawijaya | 2 |
| Listiya Surtiningsih | University of Brawijaya | 2 |
| Ahmad Afif Supianto | University of Brawijaya | 2 |
| Randy Cahya Wihandika | University of Brawijaya | 2 |
| Lailil Muflikhah | University of Brawijaya | 2 |
| Maria Tenika Frestantiya | University of Brawijaya | 1 |
| Ziya El Arief | University of Brawijaya | 1 |
| Candra Dewi | University of Brawijaya | 1 |
| Rina Christanti | University of Brawijaya | 1 |
| Issa Arwani | University of Brawijaya | 1 |
| Rekyan Regasari | University of Brawijaya | 1 |
| Muhammad Syafiq | University of Brawijaya | 1 |
| Achmad Jafar Al Kadafi | University of Brawijaya | 1 |
| Rizka Husnun Zakiyyah | University of Brawijaya | 1 |
| Wanda Athira Luqyana | University of Brawijaya | 1 |
| Uswatun Hasanah | Universitas Amikom Purwokerto | 1 |
| Lintang Resita Mayangsari | University of Brawijaya | 1 |
| Andhica Pratama | University of Brawijaya | 1 |
| Mochammad Ainun Najib | University of Brawijaya | 1 |
| Handika Agus Fauzi | University of Brawijaya | 1 |
| Sutrisno Sutrisno | University of Brawijaya | 1 |
| Aryeswara Sunaryo | University of Brawijaya | 1 |
| Maryamah . | University of Brawijaya | 1 |
| Moh. Fadel Asikin | University of Brawijaya | 1 |
| Daisy Kurniawaty | University of Brawijaya | 1 |
| Selly Kurnia Sari | University of Brawijaya | 1 |
| Putra Pandu Adikara | University of Brawijaya | 1 |
| Muhammad Nugraha Delta Revanza | Affiliation unknown | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.