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All Journal Jurnal Pekommas Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi dan Sistem Komputer Compiler IJID (International Journal on Informatics for Development) Jurnal Penelitian Pers dan Komunikasi Pembangunan JISKa (Jurnal Informatika Sunan Kalijaga) Indonesian Journal on Data Science Teknomatika: Jurnal Informatika dan Komputer International Journal of Artificial Intelligence in Medical Issues
Aris Wahyu Murdiyanto
Universitas Jenderal Achmad Yani Yogyakarta
Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Electrical & Electronics Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Public Health

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Journal : Jurnal Teknologi dan Sistem Komputer

 1 
Klasterisasi udang berdasarkan ukuran berbasis pemrosesan citra digital menggunakan metode CCA dan DBSCAN Adri Priadana; Aris Wahyu Murdiyanto
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 2, Year 2020 (April 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.8.2.2020.106-112

Abstract

The quality of farmed shrimps has several criteria, one of which is shrimp size. The shrimp selection was carried out by the contractor at the harvest time by grouping the shrimp based on their size. This study aims to apply digital image processing for shrimp clustering based on size using the connected component analysis (CCA) and density-based spatial clustering of applications with noise (DBSCAN) methods. Shrimp group images were taken with a digital camera at a light intensity of 1200-3200 lux. The clustering results were compared with clustering from direct observation by two experts, each of which obtained an accuracy of 79.81 % and 72.99 % so that the average accuracy of the method was 76.4 %.
Metode SURF dan FLANN untuk Identifikasi Nominal Uang Kertas Rupiah Tahun Emisi 2016 pada Variasi Rotasi Aris Wahyu Murdiyanto; Adri Priadana; Aris Wahyu Murdiyanto
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 1, Year 2019 (January 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (570.665 KB) | DOI: 10.14710/jtsiskom.7.1.2019.19-24

Abstract

In December 2016, Bank Indonesia (BI) officially launched the 2016 Year Emission Rupiah. With the development of technology, the process of buying and selling are not only possible between humans and humans, but humans with a machine. In addition, the machine must also be able to read and recognize the nominal banknotes in various variations of face and rotation. This is because humans can put money in machines with various variations of face and rotation. This study aims to apply and analyze the level of accuracy of nominal rupiah banknotes identification with the SURF and FLANN methods for rotation variation. Testing for identification of nominal rupiah banknotes is carried out with different rotation variations, namely 0o, 90o, 180o, and 270o. The proposed identification method provides 100% of accuracy.
Co-Authors Adri Priadana Adri Priadana Agung Purwanto Soedarbe Ahmad Adita Shiddiq Alfun Roehatul Jannah Andi Maulidinnawati Abdul Kadir Parewe Arif Himawan Arif Himawan Dimas Pratama Jati Fajar Syahruddin Fajri Profesio Putra Iqbal Hadi Subekti Kharisma Latipah, Asslia Johar M. Abu Amar Al Badawi Muhamad Arabi Rizki Angkotasan Muhammad Habibi Muhammad Rifqi Ma'arif Nafisa Alfi Sa'diya Nufia Alfi Rohyana Nur Rochmah Dyah Pujiastuti Nurul Fatimah Risky Setyadi Putra Setiawan, Rudi