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All Journal Techno.Com: Jurnal Teknologi Informasi Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Kitektro JURNAL NASIONAL TEKNIK ELEKTRO Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Rekayasa elektrika
Fitri Arnia
Universitas Syiah Kuala
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Journal : Jurnal Nasional Teknik Elektro dan Teknologi Informasi

 1 
Pengukuran Badan Ikan Berupa Estimasi Panjang, Lebar, dan Tinggi Berdasarkan Visual Capture Raihan Islamadina; Nuriza Pramita; Fitri Arnia; Khairul Munadi; TWK Muhammad Iqbal
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 1: Februari 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Currently, fish measurement process is done manually using the gauge which can cause inappropriate, ineffective result, and requires long time to finish, especially for a great amount of fish. Therefore, an automatic fish body measurement technique in the form of estimation of length, width, and height of fish based on visual capture is needed to facilitate fish body measurement to become more effective and efficient. This research uses five samples of fish in measuring length, width, and height manually to obtain the average data/value as the calibration of reference value for calculation process in the system and to be stored in the database. The stages begin with capturing fish image using a digital camera. Then, preprocessing stage was carried out to get the grayscale image of the fish. The object of the grayscale image was then segmented to separate the important and unimportant part of the object. Lastly, feature extraction process of the fish body from the calibration average value was carried out, and the estimated value of length, width, and height of fish are obtained automatically. The results show that the automatic measurement technique of fish body based on visual capture was able to produce the truth degree of accuracy of 80% to 95%.
Temu Kembali Citra Busana Muslimah Berdasarkan Bentuk Menggunakan Curvature Scale Space (CSS) Hayatun Maghfirah; Fitri Arnia; Khairul Munadi
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 1: Februari 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Nowadays in Indonesia, Islamic woman's clothing has been popular and follows the latest trend. Clothing with various color, texture, and shape are available. Furthermore, the online clothing trading system is becoming more attractive, which facilitates the users the apparel images through the websites. These images can be retrieved by querying a text to the retrieval system. However, the users face difficulties in describing the clothes precisely. Thus, a retrieval method based on content, which is known as content-based image retrieval (CBIR), is developed. Here, the content is represented by color, texture, and shape. This paper aims to present and discuss an application of Curvature Scale Space (CSS) as a shape feature for Islamic woman's clothing retrieval system. The performance of retrieval results of three clothing categories is analyzed: blouse-pant, long dress, and tunic, and used different feature length. The simulations run with as many as 300 images from the three categories, 100 images from each. Performance is measured in recall and precision. The results are compared by applying another shape feature; that is the histogram of gradient (HOG). The blouse-pant group achieves the highest performance, followed by tunic and long dress categories. The different feature length affects the retrieval performance; the longer the features, the lower recall and precision values. The feature of length 4 achieves the highest performance. The CSS is applied as the feature in CBIR of Islamic clothing, results in higher performance than the HOG.
Pengenalan Karakter Tulisan Tangan Jawi Menggunakan Metode New Relative Context dan SVM Rizal Fikri; Fitri Arnia; Rusdha Muharar
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 5 No 3: Agustus 2016
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Dot is an important attribute in character recognition. Similarly in Jawi characters, a dot becomes a special characteristic that distinguish different characters with the same basic shape. Most of feature extraction methods only recognize the characters based on their basic shape and ignore the dots, such as Relative Context (RC). RC classifies characters with the same basic shape into a group. Therefore, the result recognition of RC is not individual characters, but the name of group character. To identify individual character, a new method for RC enhancement is introduced. The method is called New Relative Context (NRC). NRC works by separating characters into some areas. The wider area is defined as the basic shape, while other areas are defined as dot attribute. In this paper Support Vector Machine (SVM) is used to classify eleven sets of isolated Jawi characters. Eight sets of character images are used in the training phase, while in the testing phase three sets of images are used. The recognition rate of this method achieves 80%.
Co-Authors Akhyar Bintang Hayatun Maghfirah Hendrik Leo Ilal Mahdi Kahlil Muchtar Khairul Munadi Khairul Munadi Khusnul Azima Muhammad Haries Novandri, Andri Nur Amalia Hasma Nuriza Pramita Oktiana, Maulisa Raihan Islamadina Rizal Fikri Rizka Ramadhana Rusdha Muharar Rusdha Muharrar Saddami, Khairun Safrizal Razali Syamsul Bahri Tia Ernita TWK Muhammad Iqbal Yustina Dhyanti Yuwaldi Away Zakiah Zakiah