SISTEM IDENTIFIKASI CITRA JENIS CABAI (Capsicum Annum L.) MENGGUNAKAN METODE KLASIFIKASI CITY BLOCK DISTANCE

Authors

  • Nur Tyas Anggraeni Universitas Ahmad Dahlan
  • Abdul Fadlil

DOI:

https://doi.org/10.12928/jstie.v1i2.2265

Abstract

Sistem pengenalan untuk identifikasi cabai berbasis komputer merupakan proses memasukkan informasi berupa citra cabai ke dalam komputer. Selanjutnya komputer menterjemahkan serta mengidentifikasi jenis cabai tersebut. Pada penelitian ini telah dilakukan perancangan sistem identifikasi cabai yang memanfaatkan kamera digital untuk akuisisi data citra cabai. Selanjutnya dilakukan pemrosesan awal, ekstraksi ciri dan pengklasifikasian. Pada pengembangan sistem ini terdiri dari 2 tahap yaitu penentuan pola standar referensi dan pengujian. Data yang digunakan sebagai standar referensi sebanyak 5 sampel untuk masing-masing jenis cabai yaitu cabai besar, cabai rawit, cabai keriting, dan paprika. Sedangkan untuk pengujian unjuk kerja sistem menggunakan 15 sampel untuk masing-masing jenis cabai.   Pengujian unjuk kerja sistem dilakukan dengan melakukan variasi ukuran citra dan metode matrik jarak. Hasil pengujian sistem identifikasi citra cabai menunjukkan tigkat akurasi yang tinggi sebesar 93 % pada ukuran citra cabai 10x10 dengan menggunakan metode klasifikasi lorentzian distance dan paling rendah tingkat akurasinya adalah 57% pada ukuran citra citra cabai 20x15 dengan menggunakan metode klasifikasi gower distance. Dengan metode ekstraksi Ciri citra cabai diekstrasi dalam bentuk vektor ciri yang diperoleh dari citra cropping dan teknik klasifikasi metrik jarak city block distance.

Kata kunci : Identifikasi cabai, Metrik Jarak, City Block Distance.

References

Munir, Rinaldi. 2004. Pengolahan Citra Digital dengan Pendekatan Algoritmik. Informatika. Bandung

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S.Alex, Usaha Tani Cabai Kiat Jitu Bertanam Cabai di Segala Musim. Pustaka Baru Press.Yogyakarta

Fadlil, A. 2012. Sistem Pengenalan Citra Jenis-Jenis Tekstil. Spektrum Industri,Vol. 10, No1, pp 1-107.

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Published

01-10-2013

Issue

Vol. 1 No. 2 (2013): Oktober

Section

Articles

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