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All Journal Kitektro JURNAL NASIONAL TEKNIK ELEKTRO Jurnal Serambi Engineering Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Rusdha Muharar
Universitas Syiah Kuala
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Environmental Science

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Pengenalan Aksara Jawi Tulisan Tangan Menggunakan Freemen Chain Code (FCC), Support Vector Machine (SVM) dan Aturan Pengambilan Keputusan Safrizal .; Fitri Arnia; Rusdha Muharar
JURNAL NASIONAL TEKNIK ELEKTRO Vol 5 No 1: Maret 2016
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (548.515 KB) | DOI: 10.25077/jnte.v5n1.185.2016

Abstract

Jawi is one variant of Arabic script consists of 35 characters. Some of Jawi characters have the same main shape, but different number of dots in different location. Thus, recognition process of Jawi characters can be done by performing a classification based on the main shape. In recognition process, feature extraction plays an important role. In this research, Freeman Chain Code (FCC) was used as feature extraction and Support Vector Machine (SVM) as classifier. Then we apply the decision rules to classifySVMresult into Jawi characters. FCC is used to represent the boundary of Jawi characters into a chain code. Then the chain code is used bySVMto classify the characters into 19 groups. Feature of location and the number of dots are used by decision rules to classify the groups into Jawi characters. The Jawi characters are handwritten and generated by 10 writers from different backgrounds and ages. The recognition rate of this research was 80.00%.Keywords : Jawi script, handwriting, FCC, SVM, decision rules.Abstrak—Aksara Jawi merupakan salah satu varian dari aksara Arab yang terdiri dari 35 aksara. Dari 35 aksara Jawi  tersebut terdapat beberapa aksara dengan bentuk bagian utama yang sama namun memiliki letak dan jumlah titik yang berbeda. Karena perbedaan tersebut maka proses pengenalan aksara Jawi dapat dilakukan dengan melakukan klasifikasi berdasarkan perbedaan bentuk bagian utama. Pada penelitian ini Freeman Chain Code (FCC) digunakan sebagai ekstraksi fitur dan Support Vector Machine (SVM). FCC digunakan untuk merepresentasikan garis batas (boundary) aksara Jawi kedalam kode rantai. Kode rantai tersebut diklasifikasi dengan menggunakan SVM kedalam 19 kelompok. Fitur letak titik dan jumlah titik digunakan sebagai aturan pengambilan keputusan terhadap 19 kelompok hasil klasifikasi SVM kedalam aksara Jawi. Aksara Jawi yang digunakan merupakan tulisan tangan dari 10 orang penulis dari berbagai latar belakang dan umur. Tingkat keberhasilan klasifikasi penelitian ini mencapai 80,00%.Kata Kunci : aksara Jawi, tulisan tangan, FCC, SVM, aturan pengambilan keputusan
Analisis Kinerja MIMO Masif dengan Teknik Precoding Maximum Ratio Transmission Rusdha Muharar
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 8 No 3: Agustus 2019
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1096.419 KB)

Abstract

Channel State Information (CSI) at the base stations obtained via the uplink trainingis an important factor in cellular and multiuser Multi-Input Multi-Output (MIMO) communi-cation networks. In massive MIMO cellular networks with pilot-based training, the most adopted approach is to employ the sameset of orthogonal training symbols in each cell. This is called the full-pilot reuse (FPR) scheme. In this paper, we consider the less-common but a more practical approach where each cell uses different sets of orthogonal training symbols and call this scheme as the Different Orthogonal Pilot (DOP) sequences. In particular, we focus on the downlink performance of massive MIMO networks with the Maximum Ratio Transmission (MRT) precoder at the base stations. The analysis is performed in the large system regime where the number of antennas at each base station and the number of users at each cell tend to infinity with a fixed ratio. We obtain a new expression for the Signal to Interference plus Noise Ratio (SINR) in that regime, called the limiting SINR. Numerical simulations show that it can approximate the finite-size systems accurately. Furthermore, the simulations also indicate that the DOP scheme can give a better SINR and a higher user capacity compared to those of the FPR scheme.
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%.
Dataset Kata Jawi untuk Sistem Pengenalan Tulisan Tangan Jawi Kuno Baihaqi Baihaqi; Fitri Arnia; Rusdha Muharar
Jurnal Serambi Engineering Vol 7, No 3 (2022): Juli 2022
Publisher : Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jse.v7i3.4611

Abstract

Indonesia has many historical and cultural heritages in the form of ancient documents written in Arabic, Malay, or Jawi. There are six additional letters in Jawi, namely ca, nya, nga, pa, ga, and va to form Jawi’s vocabulary. This ancient Jawi document has suffered many quality degradations such as uneven lighting, varying contrast, blurred ink and writing, black spots, smudges, and several other glitches. Research on handwritten word recognition systems has been done extensively for Arabic scripts and various other writings. Most of the previous research focused on character level, word level, and document level. However, it still uses publicly available datasets such as IFN/ENIT, CVL dataset, IAM, and several other datasets with similar characteristics. Meanwhile, the Jawi dataset at the word level is still not available at this time. Therefore, this study examines the handwriting recognition system at the word level. The purpose of this study is to propose a new dataset (word Jawi dataset). It is hoped that this new dataset can become a more representative dataset. The process of creating a new dataset is carried out using a manual and semi�automatic approach. Furthermore, the document said Jawi will determine the Ground Truth (GT). This research produces a special dataset of words Jawi as many as 2,310 words.
Penghematan Daya pada Sistem Komunikasi Kooperatif Two-Way dengan Pengaturan Rasio Data Rate Nasaruddin Nasaruddin; Didi Rahmadi; Rusdha Muharar
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 2: Mei 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1105.825 KB)

Abstract

Currently, many communication technologies use wireless media because it can provide seamless connectivity and mobile access. In the implementation, wireless communication system faces many challenges, one of them is fading. The effect of fading on a wireless channel will also add power consumption on mobile devices and can reduce the information signal power. However, fading can be overcome by using a cooperative communication system which is a method that utilizes antenna from other users (relays) with the principle of diversity, so the performance of wireless communication system can be improved. This paper proposes power saving on two-way cooperative communication system based on data rate ratio. The method of setting the value of this data rate ratio aims to minimize power consumption in a two-way cooperative communication system, i.e., a full-duplex communication system with quantized and forward (QF) relay protocol. To obtain a minimum power consumption, the ratio of the data rate must be set on the assumption that the value of the transmit power of each source and the relay is equal. The result shows that the system performance is improved, the system SNR value becomes lower, and the power is more efficient by adjusting the ratio of data rate compared to the conventional system without power control.
Efisiensi Energi Sistem Komunikasi Kooperatif Multi-relay Quantize and Forward Berdasarkan Pemilihan Relay Fityanul Akhyar; Nasaruddin; Rusdha Muharar
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1262.974 KB)

Abstract

Currently, the increasing energy consumption is a global issue. Information technology and telecommunication industry is one of the areas with the largest energy consumption. The growth of mobile data users is an issue and the biggest challenge for the future. The cooperative wireless communication system has been the focus of research as one of the information delivery strategy with more efficient energy consumption. Energy efficiency in the cooperative wireless communication system can be improved by using a relay between base station and user device, where the distance between base station and user can be shortened, thus, the energy transmission can be minimized. Relay mechanism can be built by utilizing the protocol in the cooperative communication system, such as amplify and forward (AF), decode and forward (DF), and quantize and forward (QF). Relay-selection is an important issue in a cooperative wireless communication system that can reduce energy consumption at the system level. This study analyzes energy efficiency of multi-relay QF cooperative communication for line-of-sight (LOS) and non-line-of-sight (NLOS) environment based on relay selection strategies: reactive and proactive relay selection. A computer simulation is conducted based on a system model and mathematical analysis. Energy efficiency is calculated based on power consumption of signal transmission and observed in the distance between the source, relay, and destination. Simulation result shows that multi-relay QF networks with relay selection consume lower energy than without relay selection, hence, the energy usage in the relay selection networks is more efficient. Moreover, the strategy of proactive relay selection provides low energy consumption and high energy efficiency compared to the reactive relay selection strategy.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1237.171 KB)

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 Baihaqi Baihaqi Didi Rahmadi Fitri Arnia Fitri Arnia Fityanul Akhyar Nasaruddin Nasaruddin Nasaruddin Nur Amalia Hasma Rizal Fikri Safrizal Razali