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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Teknik ITS Semantik Perfecting a Video Game with Game Metrics JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmiah Kursor SCAN Seminar Nasional Informatika (SEMNASIF) Sewagati
Bilqis Amaliah
Departemen Teknik Informatika, Institut Teknologi Sepuluh Nopember, Kampus ITS, Keputih, Sukolilo, Surabaya 60111
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Education Engineering Library & Information Science Social Sciences Other

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Journal : Jurnal Ilmu Komputer dan Informasi

 1 
ABCD FEATURE EXTRACTION OF IMAGE DERMATOSCOPIC BASED ON MORPHOLOGY ANALYSIS FOR MELANOMA SKIN CANCER DIAGNOSIS Bilqis Amaliah; Chastine Fatichah; M. Rahmat Widyanto
Jurnal Ilmu Komputer dan Informasi Vol 3, No 2 (2010): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1704.294 KB) | DOI: 10.21609/jiki.v3i2.145

Abstract

This research present asymmetry, border irregularity, color variation, and diameter (ABCD) feature extraction of image dermatoscopic for melanoma skin cancer diagnosis. ABCD feature is the important information based on morphology analysis of image dermatoscopic lesion. ABCD feature is used to calculate Total Dermatoscopic Value (TDV) for melanoma skin cancer diagnosis. Asymmetry feature consist information of asymmetry and lengthening index of the lesion. Border irregularity feature consist information of compactness index, fractal dimension, edge abruptness, and pigmentation transition from the lesion. Color homogeneity feature consist information of color homogeneity and the correlation between photometry and geometry of the lesion. Diameter extraction is diameter of the lesion. There are three diagnosis that is used on this research i.e. melanoma, suspicious, and benign skin lesion. The experiment uses 30 samples of image dermatoscopic lesion that is suspicious melanoma skin cancer. Based on the experiment, the accuracy of the system is 85% that there are four false diagnoses of 30 samples. Penelitian ini menyajikan ekstraksi fitur citra dermatoskopik untuk diagnosis kanker kulit melanoma berdasarkan asymmetry, border irregularity, color variation, dan diameter (ABCD). Fitur ABCD adalah informasi yang penting berdasarkan analisis morfologi lesi citra dermatoskopik. Fitur tersebut digunakan dalam perhitungan Total Dermatoscopic Value (TDV) untuk diagnosis kanker kulit melanoma. Fitur asymmetry terdiri dari informasi asimetri dan indeks perpanjangan luka. Fitur border irregularity terdiri dari informasi indeks compactness, dimensi fraktal, edge abruptness, dan transisi pigmentasi dari lesi. Warna fitur homogenitas terdiri dari informasi homogenitas warna dan korelasi antara fotometri dan geometri lesi. Ekstraksi diameter adalah diameter lesi. Ada tiga diagnosa yang digunakan pada penelitian ini yaitu melanoma, diduga melanoma, dan benign skin lesion. Percobaan ini menggunakan 30 sampel dari lesi citra dermatoskopik kanker kulit melanoma yang mencurigakan. Berdasarkan percobaan, akurasi dari sistem ini adalah 85% dan terdapat empat diagnosa palsu dari 30 sampel.
Co-Authors ABDUL MUNIF Achmad Saikhu Adam Mizza Zamani Agus Zainal Arifin Ahmad Mustofa Ahmad Saikhu Aini, Nuru Alvin Lazaro Amethis Oktaorora Andhik Ampuh Yunanto Anindhita Sigit Nugroho Anindita Sigit Nugroho Anny Yuniarti Antonius Malem Barus Arya Yudi Wijaya Arya Yudi Wijaya Aurelius Ratu Bhawika, Gita Widi Buliali, Joko Lianto Chastine Fatichah Darlis Herumurti Dwi Kristianto Edy Subali Fahmi Akbar Saputra Ginardi, R.V. Hari Hadziq Fabroyir Handayani Tjandrasa Hermanto Hermanto Imam Kuswardayan Irina Amalia Nastiti Isye Arieshanti Joko Lianto Joko Lianto Kartika Nuswantara Khakim Ghozali M Rahmat Widyanto M. Rahmat Widyanto Margo Pudjiantara Mohammad Saifullah Ratna Rintaningrum Ridho Rahman Hariadi Riyanarto Sarno Sambodho, Kriyo Siska Arifiani Suarmini, Ni Wayan Suwadi Suwadi Sylvi Novita Dewi Tri Agung Wahyu Handrian Victor Hariadi Yudhi Purwananto