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All Journal Proceedings of Annual International Conference Syiah Kuala University - Life Sciences & Engineering Chapter Jurnal Buana Informatika Kitektro Jurnal Ilmu Kebencanaan : Program Pascasarjana Unsyiah JURNAL NASIONAL TEKNIK ELEKTRO Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Rekayasa elektrika
Khairul Munadi
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Other

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Penggunaan Histogram dari Koefisien Aproksimasi Wavelet untuk Deteksi Cacat Tekstil Fitri Arnia; Andika Saputra; Khairul Munadi
JURNAL NASIONAL TEKNIK ELEKTRO Vol 3 No 1: Maret 2014
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1145.802 KB) | DOI: 10.25077/jnte.v3n1.57.2014

Abstract

Generally, textile defect inspection at textile industry is still conducted manually by human. This approach is susceptible to errors and tends to be inconsistent due to fatigue and inattentiveness. To guarantee the consistency and inspection quality, an automatic defect detection system is required. This research proposes the use of histograms generated from two-level wavelet’s approximation coefficients as features to detect textile defects. The Euclidian distance that is calculated between feature of reference textile (non-defective textile) and feature of defective one is used as an evaluation parameter. If the Euclidian distances of the features of textile images are higher than a predetermined threshold, the textiles are determined as defective ones, and vice versa. Simulations are conducted using four groups of textile defects. It turns out that the proposed method can achieve 100% detection rate for textile group with ink-spot and textile group with holes.Keywords : Wavelet coefficient histogram, Euclidean distance, Textile defect, industrial textiles, Image features AbstrakPada industri tekstil, cacat produksi umumnya masih diperiksa secara manual oleh manusia. Pemeriksaan secara manual rentan terhadap kesalahan dan kurang konsisten, karena sifat manusia yang dapat lelah, lupa dan lain sebagainya. Untuk menjamin konsistensi dan kualitas pemeriksaan cacat kain, sebuah sistem deteksi otomatis perlu ada. Penelitian ini mengusulkan penggunaan histogram dari koefisien aproksimasi wavelet dua tingkat sebagai fitur untuk deteksi cacat tekstil. Jarak Euclidian yang dihitung diantara fitur tekstil citra referensi (berasal dari citra tidak cacat) dengan fitur tesktil citra cacat digunakan sebagai parameter evaluasi. Jika jarak Euclidian dari fitur suatu citra tekstil berada di atas nilai ambang yang telah ditentukan sebelumnya, citra tersebut dinyatakan cacat, dan sebaliknya. Penelitian dilaksanakan dengan menjalankan simulasi deteksi cacat tekstil, menggunakan empat kelompok cacat tekstil yang berbeda. Ditemukan bahwa metode usulan mencapai tingkat kebenaran deteksi sebesar 100% untuk citra kelompok cacat tinta dan kelompok cacat lubang.             Kata Kunci : Histogram koefisien wavelet, Jarak  Euclidean, Cacat tekstil, Industri tekstil, Fitur citra  
Aplikasi Histogram Discrete Cosine Transform (DCT) Untuk Sistem Temu Kembali Citra Termal Berbasis Konten Faridah Faridah; Khairul Munadi; Fitri Arnia
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 2, No 1 (2019): APRIL 2019
Publisher : Program Studi Teknik Informatika, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (305.158 KB) | DOI: 10.32672/jnkti.v2i1.1055

Abstract

Content Based Image Retrieval (CBIR) merupakan sistem yang digunakan untuk menemukan kembali gambar dari sebuah arsip gambar yang besar (database) berdasarkan isi (content) query gambar. Salah satu bidang yang telah menerapkan teknologi pencarian citra adalah bidang medis. Pada penelitian ini, CBIR diterapkan untuk menemukan kembali citra termal tangan dan kaki, tangan dan kaki dipilih karena banyaknya pasien yang memiliki masalah kesehatan pada bagian anggota tubuh tersebut, seperti patah tulang dan penyakit kulit. Kinerja CBIR dievaluasi dengan mengukur nilai recall, precision, dan f-measure dari hasil temu kembali citra query tangan dan query kaki. Hasil temu kembali terbaik diperoleh pada citra termal kaki dengan nilai recall mencapai 100% sedangkan citra termal tangan hanya 90%.
Penerapan Deskriptor Warna Dominan untuk Temu Kembali Citra Busana pada Peranti Bergerak Yustina Dhyanti; Khairul Munadi; Fitri Arnia
Jurnal Rekayasa Elektrika Vol 12, No 3 (2016)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1062.094 KB) | DOI: 10.17529/jre.v12i3.5701

Abstract

Nowadays, clothes with various designs and color combinations are available for purchasing through an online shop, which is mostly equipped with keyword-based item retrieval. Here, the object in the online database is retrieved based on the keyword inputted by the potential buyers. The keyword-based search may bring potential customers on difficulties to describe the clothes they want to buy. This paper presents a new searching approach, using an image instead of text, as the query into an online shop. This method is known as content-based image retrieval (CBIR).  Particularly, we focused on using color as the feature in our Muslimah clothes image retrieval. The dominant color descriptor (DCD) extracts the wardrobe's color. Then, image matching is accomplished by calculating the Euclidean distance between the query and image in the database, and the last step is to evaluate the performance of the DWD by calculating precision and recall. To determine the performance of the DCD in extracting color features, the DCD is compared with another color descriptor, that is dominant color correlogram descriptor (DCCD). The values of precision and recall of DCD ranged from 0.7 to 0.9 while the precision and recall of DCCD ranged from 0.7 to 0.8. These results showed that the DCD produce a superior performance compared to DCCD in retrieving a set of clothing image, either plain or patterned colored clothes.
Analisa Statistik Pengunjung Situs Resmi Universitas Syiah Kuala (www.unsyiah.ac.id) . Syahrial; Khairul Munadi; Nunung Mardatillah
Jurnal Rekayasa Elektrika Vol 9, No 2 (2010)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (376.977 KB) | DOI: 10.17529/jre.v9i2.165

Abstract

Sebuah situs web umumnya merupakan bagiandari suatu nama domain (domain name) atau sub domain diWorld Web Wide (WWW) di internet. Website berguna untukmempermudah tukar menukar informasi dan memperbaruiinformasi kepada sesama pengguna internet. Bagianterpenting dari web adalah desain dan statistika laporan.Desain web yang indah dapat mencuri perhatian pengunjungsedangkan statistika berguna untuk mengetahui siapa danapa saja yang dicari oleh para pengunjung di website.Banyak tool gratis yang digunakan untuk menganalisastatistik website, salah satunya adalah Google Analytics.Sehingga dengan menggunakan Google Analytics dapat dievaluasi berapa jumlah pengunjung, halaman yang dibuka,waktu kunjungan, pengunjung berdasarkan letak geografis,loyalitas pengunjung dari situs Universitas Syiah Kuala.
Penerapan Deskriptor Warna Dominan untuk Temu Kembali Citra Busana pada Peranti Bergerak Yustina Dhyanti; Khairul Munadi; Fitri Arnia
Jurnal Rekayasa Elektrika Vol 12, No 3 (2016)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v12i3.5701

Abstract

Nowadays, clothes with various designs and color combinations are available for purchasing through an online shop, which is mostly equipped with keyword-based item retrieval. Here, the object in the online database is retrieved based on the keyword inputted by the potential buyers. The keyword-based search may bring potential customers on difficulties to describe the clothes they want to buy. This paper presents a new searching approach, using an image instead of text, as the query into an online shop. This method is known as content-based image retrieval (CBIR).  Particularly, we focused on using color as the feature in our Muslimah clothes image retrieval. The dominant color descriptor (DCD) extracts the wardrobe's color. Then, image matching is accomplished by calculating the Euclidean distance between the query and image in the database, and the last step is to evaluate the performance of the DWD by calculating precision and recall. To determine the performance of the DCD in extracting color features, the DCD is compared with another color descriptor, that is dominant color correlogram descriptor (DCCD). The values of precision and recall of DCD ranged from 0.7 to 0.9 while the precision and recall of DCCD ranged from 0.7 to 0.8. These results showed that the DCD produce a superior performance compared to DCCD in retrieving a set of clothing image, either plain or patterned colored clothes.
Co-Authors . Nasaruddin . Syahrial Andika Saputra Cut Dian Eka Sartika Endang Mutiawati Rahayuningsih* Faridah Faridah Fery Irianda Fitri Arnia Fitri Arnia Fitri Arnia Imran . Lina Marlina M. Dirhamsyah Maya Muthia Nunung Mardatillah Raihan Islamadina Ramzi Adriman Sayed Muchalil Siti Aisyah Tata Arsatria Yudha Nurdin Yustina Dhyanti Yuswardi Yuswardi Zul Syukri