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Integrasi Metode Fuzzy Additive SVM (FASVM) Menggunakan Model Warna YUV-CMY-HSV Untuk Klasifikasi Bibit Unggul Sapi Bali Melalui Citra Digital

Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 2 No. 2 (2015) · pp. 110–115

DOI
10.25126/jtiik.201522142
ISSN
2528-6579, 2355-7699
Published
2015-07-22
Publisher
Fakultas Ilmu Komputer, Universitas Brawijaya
Language
en

Abstract

AbstrakBudidaya sapi sangat identik dengan pemilihan bibit unggul, namun permasalahan yang sering muncul adalah cara mengenali bibit unggul tersebut yang relatif tidak mudah, cenderung membutuhkan waktu cukup lama. Peternak masih sering mengamati warna kulit dengan mata secara langsung, yang cenderung kurang teliti. Sehingga dalam penelitian ini, diusulkan metode dengan menggunakan beberapa model warna yang nantinya sebagai rekomendasi untuk fitur yang optimal dalam sistem. Kemudian metode klasifikasi yang digunakan adalah Fuzzy Additive Support Vector Machine (FASVM). Data yang digunakan didapatkan dari Balai Pembibitan Ternak Unggul (BPTU) Sapi Bali. Dari hasil pengujian didapatkan model warna yang paling optimal dan rata-rata akurasi pada Sapi Betina dan Jantan dengan ukuran citra tertentu. Model warna tersebut sangat dipengaruhi oleh kondisi data citra dan juga banyaknya kelas data.Kata kunci: Sapi Bali, Model warna, Intersection kernel, Fuzzy additive SVM, Sequential training SVM AbstractCattle farming is identical with the selection of seeds, but the problems that often arises is how to recognize quality seeds are relatively easy, tend to take a long time. Breeders still often observe skin color with eyes directly, which tend to be less rigorous. Thus, in this study, the proposed method by using several color models that will be voted on features that are optimal in the system. Then the classification method used is Additive Fuzzy Support Vector Machine (FASVM). The data used was obtained from Livestock Breeding Center for Excellence (BPTU) Bali cattle. From the test results obtained the most optimal color models and average accuracy on Cow Females and Males with a particular image size. The color model is highly influenced by the condition of the image data and also the amount of class data. Keywords: Bali cattle, Color model, Intersection kernel, Fuzzy additive SVM, Sequential training SVM

Collaboration network of the authors

40 authors · 109 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-authorOrganisationJoint articles
Daneswara JauhariUniversity of Brawijaya3
Dhimas Anjar PrabowoUniversity of Brawijaya3
Sutrisno .Affiliation unknown3
Canny Amerilyse CaesarUniversity of Brawijaya3
Latifah HanumUniversity of Brawijaya3
Muhammad FhadliUniversity of Brawijaya2
Anang HanafiUniversity of Brawijaya2
Listiya SurtiningsihUniversity of Brawijaya2
Fitra Abdurrachman BachtiarUniversity of Brawijaya2
Randy Cahya WihandikaUniversity of Brawijaya2
Maria Tenika FrestantiyaUniversity of Brawijaya2
Ziya El AriefUniversity of Brawijaya2
Candra DewiUniversity of Brawijaya2
Rina ChristantiUniversity of Brawijaya2
Sutrisno SutrisnoUniversity of Brawijaya2
Ahmad Afif SupiantoUniversity of Brawijaya1
Muh. Arif RahmanUniversity of Brawijaya1
Budi Darma SetiawanUniversity of Brawijaya1
Rekyan Regasari Mardi PutriUniversity of Brawijaya1
Lailil MuflikhahUniversity of Brawijaya1
Muhammad SyafiqUniversity of Brawijaya1
Achmad Jafar Al KadafiUniversity of Brawijaya1
Rizka Husnun ZakiyyahUniversity of Brawijaya1
Wanda Athira LuqyanaUniversity of Brawijaya1
Uswatun HasanahUniversitas Amikom Purwokerto1
Lintang Resita MayangsariUniversity of Brawijaya1
Andhica PratamaUniversity of Brawijaya1
Mochammad Ainun NajibUniversity of Brawijaya1
Handika Agus FauziUniversity of Brawijaya1
Aryeswara SunaryoUniversity of Brawijaya1
Maryamah .University of Brawijaya1
Moh. Fadel AsikinUniversity of Brawijaya1
Daisy KurniawatyUniversity of Brawijaya1
Selly Kurnia SariUniversity of Brawijaya1
Nurulita Purnama PutriAffiliation unknown1
Adhi Harmoko SaputroAffiliation unknown1
Ratih PrasetyaAffiliation unknown1

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.

Metadata source: OAI-PMH (metadata jurnal) https://jtiik.ub.ac.id/index.php/jtiik/en/oai, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="id">Integrasi Metode Fuzzy Additive SVM (FASVM) Menggunakan Model Warna YUV-CMY-HSV Untuk Klasifikasi Bibit Unggul Sapi Bali Melalui Citra Digital</dc:title>
	<dc:creator xml:lang="en">Cholissodin, Imam</dc:creator>
	<dc:creator xml:lang="en">Soebroto, Arief Andy</dc:creator>
	<dc:creator xml:lang="en">Hidayat, Nurul</dc:creator>
	<dc:description xml:lang="id">AbstrakBudidaya sapi sangat identik dengan pemilihan bibit unggul, namun permasalahan yang sering muncul adalah cara mengenali bibit unggul tersebut yang relatif tidak mudah, cenderung membutuhkan waktu cukup lama. Peternak masih sering mengamati warna kulit dengan mata secara langsung, yang cenderung kurang teliti. Sehingga dalam penelitian ini, diusulkan metode dengan menggunakan beberapa model warna yang nantinya sebagai rekomendasi untuk fitur yang optimal dalam sistem. Kemudian metode klasifikasi yang digunakan adalah Fuzzy Additive Support Vector Machine (FASVM). Data yang digunakan didapatkan dari Balai Pembibitan Ternak Unggul (BPTU) Sapi Bali. Dari hasil pengujian didapatkan model warna yang paling optimal dan rata-rata akurasi pada Sapi Betina dan Jantan dengan ukuran citra tertentu. Model warna tersebut sangat dipengaruhi oleh kondisi data citra dan juga banyaknya kelas data.Kata kunci: Sapi Bali, Model warna , Intersection kernel, Fuzzy additive SVM, Sequential training SVM  AbstractCattle farming is identical with the selection of seeds, but the problems that often arises is how to recognize quality seeds are relatively easy, tend to take a long time. Breeders still often observe skin color with eyes directly, which tend to be less rigorous. Thus, in this study, the proposed method by using several color models that will be voted on features that are optimal in the system. Then the classification method used is Additive Fuzzy Support Vector Machine (FASVM). The data used was obtained from Livestock Breeding Center for Excellence (BPTU) Bali cattle. From the test results obtained the most optimal color models and average accuracy on Cow Females and Males with a particular image size. The color model is highly influenced by the condition of the image data and also the amount of class data. Keywords: Bali cattle, Color model , Intersection kernel, Fuzzy additive SVM, Sequential training SVM</dc:description>
	<dc:publisher xml:lang="en">Fakultas Ilmu Komputer, Universitas Brawijaya</dc:publisher>
	<dc:date>2015-07-22</dc:date>
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	<dc:source xml:lang="id">Jurnal Teknologi Informasi dan Ilmu Komputer; Vol 2 No 2: Oktober 2015; 110-115</dc:source>
	<dc:source xml:lang="en">Jurnal Teknologi Informasi dan Ilmu Komputer; Vol. 2 No. 2: Oktober 2015; 110-115</dc:source>
	<dc:source>2528-6579</dc:source>
	<dc:source>2355-7699</dc:source>
	<dc:source>10.25126/jtiik.201522</dc:source>
	<dc:language>en</dc:language>
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	<dc:rights xml:lang="en">Copyright (c) 2016 Jurnal Teknologi Informasi dan Ilmu Komputer</dc:rights>
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