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All Journal International Journal of Electrical and Computer Engineering Jurnal Gamma TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi CommIT (Communication & Information Technology) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research IJCIT (Indonesian Journal on Computer and Information Technology) Indonesian Journal of Artificial Intelligence and Data Mining Jiko (Jurnal Informatika dan komputer) Technologia: Jurnal Ilmiah Jurnal Abdimas Madani dan Lestari (JAMALI) ILKOMNIKA: Journal of Computer Science and Applied Informatics Automata TIN: TERAPAN INFORMATIKA NUSANTARA JURNAL PENDIDIKAN, SAINS DAN TEKNOLOGI Jurnal Informatika: Jurnal Pengembangan IT
Arrie Kurniawardhani
Universitas Islam Indonesia
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Journal : International Journal of Electrical and Computer Engineering

 1 
CBIR of Batik Images using Micro Structure Descriptor on Android Agus Eko Minarno; Yuda Munarko; Arrie Kurniawardhani
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (499.175 KB) | DOI: 10.11591/ijece.v8i5.pp3778-3783

Abstract

Batik is part of a culture that has long developed and known by the people of Indonesia and the world. However, the knowledge is only on the name of batik, not at a more detailed level, such as image characteristic and batik motifs. Batik motif is very diverse, different areas have their own motifs and patterns related to local customs and values. Therefore, it is important to introduce knowledge about batik motifs and patterns effectively and efficiently. So, we build CBIR batik using Micro-Structure Descriptor (MSD) method on Android platform. The data used consisted of 300 images with 50 classes with each class consists of six images. Performance test is held in three scenarios, which the data is divided as test data and data train, with the ratio of scenario 1 is 50%: 50%, scenario 2 is 70%, 30%, and scenario 3 is 80%: 20%. The best results are generated by scenario 3 with precision valur 65.67% and recall value 65.80%, which indicates that the use of MSD on the android platform for CBIR batik performs well.
Co-Authors Abidatul Izzah Afdhari, Fahrezi Bintang Agus Eko Minarno Agus Zainal Arifin Ahmad Faris Akbar Alamsyah, Juan Parez Mangku Alfaz, Revansha Zulfikar Alhanafi, Ahmad Azzam Andaru, Gabriel Imam Avilba, Pandu Ayu Septya Maulani Aziz, Achmad Noer Catur Singgih Daniel Swanjaya Dhomas Hatta Fudholi Diana Purwitasari Dimas Setyawan Ramadhansyah Fathurrahman, Ihya Fayruz Rahma Ferdian Nursulistio Fitri Bimantoro Fudholi, Dhomas Hatta Huda, Sheila Nurul Ihya Fathurrahman Fathurrahman Indra Lukmana Indrayanti, Indrayanti Indrayanti, Indrayanti Irving V. Paputungan Isye Arieshanti Izzati Muhimmah Khoirunnisa Shofwatul Laili Mufti Leriansyah Muhammad Rizqi Az Zayyad Muhimmah, Izzati mukhamad masrur Najmudin, Nabil Nanik Suciati Nur Jati Lantang Marfu'ah Rahadian Kurniawan Rasyadi, M Javier Rio Galang Jati Respati Salsabila Zahirah Pranida Santoso, Muhammad Lucky Lazuardi Setya Winarno Siti Mutrofin Sri Kusumadewi Yuda Munarko