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All Journal International Journal of Electrical and Computer Engineering Proceedings of Annual International Conference Syiah Kuala University - Life Sciences & Engineering Chapter Techno.Com: Jurnal Teknologi Informasi Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Kitektro JOURNAL OF INFORMATICS AND COMPUTER SCIENCE JURNAL NASIONAL TEKNIK ELEKTRO Bulletin of Electrical Engineering and Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Syntax Literate: Jurnal Ilmiah Indonesia MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Komputasi dan Teknologi Informasi Journal of Electronics, Electromedical Engineering, and Medical Informatics JOURNAL OF INFORMATICS AND COMPUTER SCIENCE Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Rekayasa elektrika Jurnal Pengabdian Rekayasa dan Wirausaha
Fitri Arnia
Department Of Electrical And Computer Engineering, Universitas Syiah Kuala, Indonesia
Aerospace Engineering Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Neuroscience Social Sciences Transportation Other

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PENGENALAN GERAKAN ISYARAT BAHASA INDONESIA MENGGUNAKAN ALGORITMA SURF DAN K-NEAREST NEIGHBOR Nur Amalia Hasma; Fitri Arnia; Rusdha Muharar
Jurnal Komputer, Informasi Teknologi, dan Elektro Vol 7, No 1 (2022)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/kitektro.v7i1.23262

Abstract

Berkomunikasi adalah kebutuhan dasar setiap manusia untuk berinteraksi satu sama lain. Dalam kehidupan sehari-hari, manusia menggunakan komunikasi verbal untuk berinteraksi. Namun tidak setiap orang mampu menggunakan komunikasi secara verbal, seperti tuna rungu dan tuna wicara. Terdapat keterbatasan ketika melakukan komunikasi antara orang normal dengan tuna rungu dan tuna wicara dikarenakan kurangnya pemahaman mengenai bahasa isyarat. Pada penelitian ini dilakukan pengenalan bahasa isyarat, berupa isyarat huruf dan angka (SIBI) dengan memanfaatkan teknik pengolahan citra. Proses pengenalan dilakukan dengan menggunakan algoritma Speeded Up Robust Features (SURF) sebagai metode ekstraksi fitur dan algoritma K-Nearest Neighbor (K-NN) sebagai metode klasifikasi. Pengujian akurasi digunakan metode k-fold Cross Validation. Uji akurasi menggunakan 10-fold Cross Validation untuk menentukan nilai K. Dengan menggunakan nilai K = 7 didapatkan hasil akurasi tertinggi untuk pengenalan Gerakan Isyarat Bahasa Indonesia dengan persentase 90%.
HISTOGRAM E QUALIZATION SMOOTHING FOR DETERMINING THRESHOLD ACCURACY ON ANCIENT DOCUMENT IMAGE BINARIZATION Mahendar Dwipayana; Fitri Arnia; Zuhar Musliyana
JOURNAL OF INFORMATICS AND COMPUTER SCIENCE Vol 2, No 2 (2016): Oktober 2016
Publisher : Ubudiyah Indonesia University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33143/jics.Vol2.Iss2.733

Abstract

Ancient documents are inheritance that must be preserved. Thedocuments contain historical, scientific, social, religious information, etc.Converting ancient documents into digital image formats is one of ways topreserve the inheritance and can be stored into a computer. However,images of ancientdocuments have many blemishes caused by age,moisture, flood, etc. Therefore, special techniques are needed for thoseimages to be restored and can improve the legibility of the ancientdocuments’ images. In this study, the image restoration process usesseparation of background and foreground/text on histogram equalizationsuch as research conducted by Fitri Arnia in 2008. Through histogramequalizationimages can be seen the distribution of pixels from the intensityof black color "0" to white "1". The distribution of pixels on histogramequalization describes the curves of foreground/text and curves ofbackground. Among the histogram curves, the determination ofthresholdvalues can be done so as to clarify the foreground/text andbackground areas on images of ancient documents. The lowest pointbetween the two curves is the lowest pixel (local minima) which is used asthe threshold value. However, the selection of such threshold values insome cases is very difficult to determine because there are still manyfluctuations in the curve at the lowest curve. Therefore, this studyproposesa histogram smoothing method in the ancient documents’ imagesto minimize curvature fluctuations and to determine more accuratethreshold values. In this research, average filtering method is used forsmoothing the histogram image. This filter successfully refines thehistogram and makes the image of the restoration or binary image displaythe value of the ancient document image readability increases.Keywords: HistogramEqualization, Smoothing Histogram, AverageFiltering, Thresholding
On Reducing ShuffleNets’ Block for Mobile-based Breast Cancer Detection Using Thermogram: Performance Evaluation Rizka Ramadhana; Khairun Saddami; Khairul Munadi; Fitri Arnia
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 4: December 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i4.4062

Abstract

In this paper, we proposed a reduced-block-Shufflenet (RB-ShuffleNet) for thermal breast cancer detection. RB-ShuffleNet is a modification of Shufflenet obtained by reducing blocks from the original architecture. The images for training and testing were obtained from Database for Mastology Research (DMR). First, we detected and cropped the image based on the region of interest (ROI), in which the ROI is determined by using the red intensity profile. Then, the ROI images were trained using RB-ShuffleNets. In the experiments, we built eight architectures, based on ShuffleNet, each with a different number of reduced blocks. The result showed that RB-Shufflenet with four reduced blocks had fewer than 50% of the learning parameters of the original Shufflenet, without compromising its performance. The RB-ShuffleNet with up to four reduced blocks could achieve 100% testing accuracy. Furthermore, The RB-ShuffleNets performed better than MobileNetV2 and resulted in higher accuracy when fed with ROI images. Due to its light structure and good performance, we recommend RB-ShuffleNet as mobile-based CNN model which is preferable to implement in breast cancer detection.
Improved Classification of Handwritten Jawi Script Based on Main Part of Script Body Safrizal Razali; Fitri Arnia; Rusdha Muharrar; Kahlil Muchtar; Akhyar Bintang
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 1 (2023): February 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i1.4600

Abstract

Since the entry of Islam, many ancient relics in the archipelago were written using Jawi script. Due to human or natural factors, these ancient relics will be damaged or destroyed. To avoid the loss of this ancient heritage data, the data must be stored in digital documents. In order to convert digital documents into machine-readable text format, the use of Optical Character Recognition (OCR) technology is inevitable. In this research, OCR technology is implemented on isolated Jawi scripts. Freeman Chain Code (FCC) is used to extract the isolated Jawi script features. Subsequently, the FCC feature is fed into Support Vector Machine (SVM) in order to classify the character. The decision rule classification is applied to the class of SVM classification in the Jawi script form. The results of the SVM classification into 19 classes reached 81.58%, while the results for merging into 15 classes produced better results with the accuracy 84.21%. Feature extraction of dot location is divided into the top, middle, and bottom. Feature extraction of the number of dotss is done by counting the number of dots, while feature extraction of the presence of holes is carried out by detecting the presence of holes in the characters. These features are applied to the class of results from SVM classification with decision-making rules. The percentage of success in applying the decision rules to the results of the classification of incorporation into 15 classes by SVM reached 92.86%. Further research will be conducted to determine the effect of the feature of the location of the dot and the number of dots on the shape of the main part of the character.
Studi Pencocokan Plat Kendaraan Dengan Metode Phase Only Correlation Listia Sukma Putri; Roslidar Roslidar; Fitri Arnia
Jurnal Rekayasa Elektrika Vol 9, No 4 (2011)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (650.171 KB)

Abstract

Salah satu cara pengenalan kendaraan adalah dengan identifikasi plat. Umumnya identifikasi yang dilakukan mengacu pada proses segmentasi tiap karakter dari citra plat. Makalah ini mengajukan suatu metode identifikasi plat yang sederhana tanpa melakukan pengenalan melainkan langsung pada proses pencocokan yang berbasis Phase Only Correlation (POC). POC mencocokkan plat dengan mengorelasikan fasa dari dua  citra plat. Fasa diperoleh dengan mengubah citra dari domain spasial menjadi domain frekuensi menggunakan Transformasi Fourier Waktu Diskrit (TFWD). Nilai puncak POC akan tinggi jika citra plat yang dicocokkan adalah citra yang berasal dari plat yang sama. Sebaliknya akan rendah jika yang dicocokkan berasal dari plat yang berbeda. Hasil simulasi menggunakan 20 citra plat menunjukkan bahwa metode POC dapat digunakan dalam pencocokan citra plat.
Metode Band-Limited Phase Only Correlation (BLPOC) untuk Identifikasi Plat Kendaraan Fitri Arnia; Syahrul Wahyudi; Siti Aisyah
Jurnal Rekayasa Elektrika Vol 10, No 1 (2012)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1193.739 KB) | DOI: 10.17529/jre.v10i1.148

Abstract

Digital image processing and computer vision technologies have developed so rapidly and have numerous applications. Automatic lisence plate recognition systems (ALPRS) based on those technologies are not exceptions. In general, the ALPRSs required several steps including image capturing, plate location searching, character segmentation and character recognition. Successful of the whole systems depended heavily on the used segmentation method. A common drawback of many segmentation techniques is that they are very sensitive to illumination variability. The paper proposed a method for license plate recognition based on correlation of phase componenet with limited bandwidth. The method is widely known as band-limited phase only correlation (BLPOC). The method compared input plate’s image with plate’s images in the database. Based on simulation, detection rate can achieve 90% if an appropriate threshold value was selected.
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.
Simulasi Pelacakan Titik Daya Maksimum Modul Surya dengan Metode Grey Wolf Optimization Rizki Faulianur; Ira Devi Sara; Fitri Arnia
Jurnal Rekayasa Elektrika Vol 14, No 1 (2018)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1561.995 KB) | DOI: 10.17529/jre.v14i1.8973

Abstract

The photovoltaic module has a nonlinear current and voltage characteristic curve where there is a maximum power point to be tracked to avoid wasted energy. Some methods for tracking the maximum power points have been developed such as perturb and observe (P O), Incremental Conductance (IC), and Hill Climbing (HC). However, those methods were not so accurate to find the maximum power point and they were also slow to respond the changes in solar radiation and temperature. To overcome the shortcomings of the method, a new optimization approach was developed. This method is called Gray Wolf Optimization (GWO). It work based on the wolf behavior in capturing the prey. In this study, it will be determined to what extent the GWO method can track the maximum working point of solar modules that undergo changes in radiation and working temperature quickly and accurately. This research was conducted by simulation using Matlab/Simulink by comparing the extract of power GWO method with its power characteristics. The results obtained by the GWO method trace maximum power with an average accuracy rate of 99.14 % with time less than 0.1 second. From this data, it can be concluded that the GWO method successfully responds well and accurately to changes in radiation and temperature.
Substraksi Latar Menggunakan Nilai Mean Untuk Klasifikasi Kendaraan Bergerak Berbasis Deep Learning Ilal Mahdi; Kahlil Muchtar; Fitri Arnia; Tia Ernita
Jurnal Rekayasa Elektrika Vol 18, No 2 (2022)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1626.433 KB) | DOI: 10.17529/jre.v18i2.25224

Abstract

Moving object detection systems have been widely used in everyday life. Currently, research in the field of background subtraction is still being carried out to achieve maximum accuracy results. This study aims to model the background subtraction of an image using the mean value with the concept of non-overlapping block. Furthermore, the background abstraction results will be used in deep learning-based moving object detection. Specifically, the input image will be divided into several blocks, then the mean value of each block will be calculated to later produce a binary block (binary map). The binary blocks that have been generated will be used as input for background modeling. The background model aims to separate moving objects from the background in the input image. The resulting moving object (object localization) will be sent to the object classification stage using deep learning. The dataset used in this study is CDNet 2014. The results of the study were able to produce a more accurate moving object detection system. Quantitative tests carried out resulted in an accuracy of above 90%.
Peningkatan Kualitas Citra Digital Menggunakan Metode Super Resolusi Pada Domain Spasial Nailul Mustaqim Abdi; Siti Aisyah; Fitri Arnia
Jurnal Rekayasa Elektrika Vol 9, No 3 (2011)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (668.299 KB) | DOI: 10.17529/jre.v9i3.163

Abstract

Citra merupakan salah satu komponen dari multimedia yang memegang peranan penting karena mengandung informasi dalam bentuk visual. Tetapi tidak semua citra dapat menampilkan informasi secara jelas dan detail seperti halnya citra resolusi rendah. Citra resolusi rendah memiliki kepadatan piksel yang rendah. Untuk itudiperlukan peningkatan kualitas citra menggunakan metode super resolusi agar dihasilkan citra resolusi tinggi dari citra resolusi rendah. Penelitian ini menggunakan teknik super resolusi yang melalui tiga tahapan umum yaitu registrasi, interpolasi (bilinear dan bikubik), dan rekonstruksi (smoothing dan denoising). Teknik ini diterapkan pada domain spasial menggunakan citra grayscale resolusi rendah. Teknik super resolusi ini diaplikasikan pada citra satu framedan citra multiframe. Hasil Mean Opinion Score (MOS)menunjukkan bahwa citra multiframe yang melalui prosesregistrasi menghasilkan citra resolusi tinggi yang lebih baikdibandingkan dengan citra satu frame tanpa proses registrasi.
Co-Authors . Melinda . Roslidar ., Safrizal ., Zulfan Abbas Adam AzZuhri Akhyar Bintang Andika Saputra Arsy Febrina Dewi Aulia Syarif Aziz Bahri, Syamsul Cut Mutia Cut Mutia Devi Sara, Ira Dwipayana, Mahendar Elizar Elizar Fardian Fardian Fardian Fardian Faridah Faridah Fathurrahman Fathurrahman Fery Irianda Fikri, Rizal Hardian Saputra Hayatun Maghfirah Hendra Hidayat Hendri Syahputra Hendrik Leo Hubbul Walidainy Ilal Mahdi Iqbal, TWK Muhammad Kahlil Muchtar Khairul Fajri Khairul Munadi Khairul Munadi Khairul Munadi Khairul Munadi Khairul Munadi Khairul Munadi Khairun Saddami Khairun Saddami Khairun Saddami Khusnul Azima Laila Nujmi Burhan Lina Marlina Listia Sukma Putri Maghfirah, Hayatun Maulisa Oktiana Maya Fitria Maya Muthia Muchtar, Kahlil Muhammad Haries Muhammad Irhmasyah Muhammad Irwandi Muhammad Rizky Syahputra Muharar, Rusdha Muharar, Rusdha Munadi, Khairul Nailul Mustaqim Abdi Nargaza, Juanda Nasaruddin Nasaruddin Novandri, Andri Nur Amalia Hasma Nuriza Pramita Nuriza Pramita Nuriza Pramita Oktiana, Maulisa Oktiana, Maulisa Putri Rizkiah Rahmatika, Nisa Adilla Raihan Islamadina Raihan Islamadina Raihan Islamadina Ramadhani Ramadhani Ramiady, Luthfiar Ramzi Adriman Risnaty Utami Marsal Rizal Fikri Rizka Ramadhana Rizki Faulianur Roslidar Roslidar Rusdha Muharar Rusdha Muharar Rusdha Muharar Rusdha Muharar Rusdha Muharar Rusdha Muharar Rusdha Muharar, Rusdha Rusdha Muharrar Saddami, Khairun Safrizal Razali Saputra, Andika Siti Aisyah Siti Aisyah Syahputra, Hendri Syahrul Wahyudi Syamsul Bahri Tata Arsatria Taufik Fuadi Abidin Taufik Fuadi Abidin Taufik Fuadi Abidin Tia Ernita TWK Muhammad Iqbal Yunida, Yunida Yunidar Yusni, Y Yustina Dhyanti Yuwaldi Away Zakiah Zakiah Zharifah Muthiah Zuhar Musliyana Zuhar Musliyana, Zuhar Zul Syukri Zulfan .