Identifikasi Jenis Kucing Berdasarkan Pola Citra Menggunakan Convolutional Neural Network
DOI:
https://doi.org/10.29407/475nw093Keywords:
akurasi klasifikasi, Random Forest Classifier, dataset citra, identifikasi kucing, klasifikasi citraAbstract
Kucing merupakan salah satu hewan peliharaan yang populer di seluruh dunia. Identifikasi jenis kucing secara akurat dapat bermanfaat dalam berbagai aplikasi, seperti perawatan kesehatan hewan, penelitian, dan pengenalan jenis kucing. Penelitian ini bertujuan untuk mengembangkan sebuah sistem identifikasi jenis kucing berdasarkan pola citra menggunakan Random Forest Classifier. Kami mengumpulkan dataset citra kucing dari berbagai jenis dan melatih model Random Forest Classifier untuk mengklasifikasikan jenis kucing. Hasil eksperimen menunjukkan bahwa model Random Forest dapat mencapai akurasi klasifikasi hingga 92% pada set data uji. Sistem ini dapat digunakan untuk mengidentifikasi jenis kucing secara akurat dan efisien, serta memiliki potensi aplikasi yang luas di bidang zoologi, veteriner, dan pengembangan aplikasi berbasis komputer vision
Downloads
References
C. Effendi and N. S. Budiana, Kucing: Complete guide book for your cat. AgriFLo, 2014.
F. Marpaung, F. Aulia, and R. C. Nabila, “Computer Vision Dan Pengolahan Citra Digital,” 2022,
PUSTAKA AKSARA.
G. Pascarella et al., “COVID-19 diagnosis and management: a comprehensive review,” 2020. doi:
1111/joim.13091.
Suci Amaliah, M. Nusrang, and A. Aswi, “Penerapan Metode Random Forest Untuk Klasifikasi Varian
Minuman Kopi di Kedai Kopi Konijiwa Bantaeng,” VARIANSI J. Stat. Its Appl. Teach. Res., vol. 4, no. 3,
pp. 121–127, 2022, doi: 10.35580/variansiunm31.
P. D. Hadi, D. A. Widhining K, and F. A. Fiolana, “Identifikasi Jenis Ras Pada Kucing Menggunakan
Algoritma Support Vector Machine (SVM),” JASIEK (Jurnal Apl. Sains, Informasi, Elektron. dan
Komputer), vol. 6, no. 1, pp. 77–86, 2024, doi: 10.26905/jasiek.v6i1.10989.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Satya Dwi Permana Putra, Fikri Fikri, Oktaviana Tivani Kiki
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Copyright on any article is retained by the author(s).
- The author grants the journal, right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work’s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
- The article and any associated published material is distributed under the Creative Commons Attribution-ShareAlike 4.0 International License
