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Journal : Knowledge Engineering and Data Science

Human Intestinal Condition Identification based-on Blended Spatial and Morphological Feature using Artificial Neural Network Classifier Ummi Athiyah; Arif Wirawan Muhammad; Ahmad Azhari
Knowledge Engineering and Data Science Vol 3, No 1 (2020)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v3i12020p19-27

Abstract

Colon cancer is a type of disease that attacks the intestinal walls cell of humans. Colorectal endoscopic screening technique is a common step carried out by the health expert/gynecologist to determine the condition of the human intestine. Manual interpretation requires quite a long time to reach a result. Along with the development of increasingly advanced digital computing techniques, then some of the weaknesses of the manually endoscopic image interpretation analysis model can be corrected by automating the detection process of the presence or absence of cancerous cells in the gut. Identification of human intestinal conditions using an artificial neural network method with the blended input feature produces a higher accuracy value compared to the artificial neural network with the non-blended input feature. The difference in classifier performance produced between the two is quite significant, that is equal to 0.065 (6.5%) for accuracy; 0.074 (7.4%) for recall; 0.05 (5.0%) for precision; and 0.063 (6.3%) for f-measure.
Co-Authors Adam Ikbal Perdana Adela Putri Handayani Aditya Dwi Putro Aditya Dwi Putro Wicaksono Adytia Abi Restianto Agus Priyanto Agustyawan, Arif Ahmad Muslih Syafi'i Al Fachri, Moh. Aminullah Alam Patria Utama Alameka, Faza Alifta Salma Shafira Alika, Shintia Dwi Amalia, Hasna Shafa Andreas Rony Wijaya Arif Wirawan Muhammad Arif Wirawan Muhammad Arnelka Hananta Atika Ratna Dewi Azhari, Ahmad Dwi Setiawan, Brandon Elisabeth Angeline Wilhelmina Bakowatun Erlina Marfianti, Erlina Faisal Dharma Adhinata Faiz Rizky Fahlevi Felia Citra Dwiyani Putri Rosyadi Firda Millennianita Firda Millennianita Habiburrahman, Muhammad Quthb Hafidz Daffa Hekmatyar Hasan Nizar Hikmah Quddustiani Hulqi, Filfimo Yulfiz Ahsanul Irmayatul Hikmah Ismail , Moh Izzati Muhimmah Jannah , Uzlifatul Juvandio Aufaresa Kholidiyah Masykuroh Luthfi Rakan Nabila Made Riza Kartika Maya Nurachmawati Adiningtias Moh. Aminullah Al Fachri Muhammad Alvi Awliya Muhammad Nur Faiz Muhammad Nur Faiz Muhammad Quthb Habiburrahman Muhammad Yusril Aldean Naden, Yoga Nikmatul Khayati Novanda Alim Setya Nugraha Novantri Prasetya Putra Novian Adi Prasetyo Oktavia Jazilatus Sa’adah Pangestu, Happy Gery Puguh Ika Listyorini Rafian Ramadhani Rara Nur Salsabila Rayhan Hidayat Regina Putri Wanda Zahirah Reno Agil Saputra Rheni Aprilia Ningrum Ridha Berlianny Sulistiaputri Sa’adah, Oktavia Jazilatus Saputro, Satria Nur Sausan Sinaga, Rifaldo Yohannes Siti Khomsah, Siti Sudianto Suryani, Ajeng Ayu Taufik Maulidi Theo Felix Harianto Purba Tri Ginanjar Laksana Trihastuti Yuniati Tufail Akhmad Satrio Ulya, Fadilla Zundina Vico Meylana Eka Putra Warto Yehezekiel Ramasyah Putra Haloho Yohani Setiya Rafika Nur Yunita Wisda Tumarta Arif