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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Journal of Data Science and Its Applications
Adhi Dharma Wibawa
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Computer Science & IT Decision Sciences, Operations Research & Management

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Aplikasi Metode Backpropagation untuk Pengenalan Perubahan Abnormal Organ Pankreas Melalui Iris Mata Marsetio Pramono; Gregorius Satio Budhi; Adhi Dharma Wibawa; Mauridhi Hery Purnomo
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2006
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Abstract

Pemeriksaan kesehatan tubuh manusia pada umumnya melalui pemeriksaan tekanan darah, pemeriksaan pernafasan dengan stetoscop dan dengan cara pemeriksaan lainnya seperti uji klinis. Pada saat ini telah ada teori baru dalam mendiagnosa penyakit yaitu melalui iris mata. Iris mata dapat merefleksikan kondisi dari berbagai organ tubuh dan sistem yang ada di dalam tubuh. Pada tahap preprocessing, dilakukan image processing seperti image enhancement, serta pada proses pengenalan dengan menggunakan metode Backpropagation yang merupakan salah satu artificial intelligence system. Untuk pembuktiannya akan dilakukan tes insulin.Kata kunci: backpropagation, iridologi, image processing
Soccer Players Detection Using GDLS Optimization and Spatial Bitwise Operation Filter Adhi Dharma Wibawa; Atyanta Nika Rumaksari
Journal of Data Science and Its Applications Vol 2 No 1 (2019): Journal of Data Science and Its Applications
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/jdsa.2019.2.18

Abstract

Advancement computer vision technology in order to help coach creates strategy has been affecting the sport industry evolving very fast. Players movement patterns and other important behavioral activities regarding the tactics during playing the game are the most important data obtained in applying computer vision in Sport Industry. The basic technique for extracting those information during the game is player detection. Three fundamental challenges of computer vision in detecting objects are random object’s movement, noise and shadow. Background subtraction is an object’s detection method that used widely for separating moving object as foreground and non moving object as background. This paper proposed a method for removing shadow and unwanted noise by improving traditional background subtraction technique. First, we employed GDLS algorithm to optimize background-foreground separation. Then, we did filter shadows and crumbs-like object pixels by applying digital spatial filter which is created from implementation of digital arithmetic algorithm (bitwise operation). Finally, our experimental result demonstrated that our algorithm outperform conventional background subtraction algorithms. The experiments result proposed method has obtained 80.5% of F1-score with average 20 objects were detected out of 24 objects.
Co-Authors Atyanta Nika Rumaksari Gregorius Satio Budhi Marsetio Pramono Mauridhi Hery Purnomo