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All Journal International Journal of Electrical and Computer Engineering Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Perfecting a Video Game with Game Metrics Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JETT (Jurnal Elektro dan Telekomunikasi Terapan) JOIV : International Journal on Informatics Visualization IT JOURNAL RESEARCH AND DEVELOPMENT TECHNO-SOCIO EKONOMIKA Jurnal Nasional Teknik Elektro dan Teknologi Informasi eProceedings of Applied Science eProceedings of Engineering Jurnal Rekayasa elektrika VCode Jurnal INFOTEL
Suci Aulia
Telkom University
Arts Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Comparison of resting electroencephalogram coherence in patients with mild cognitive impairment and normal elderly subjects Sugondo Hadiyoso; Inung Wijayanto; Suci Aulia
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1558-1564

Abstract

Mild cognitive impairment (MCI) was a condition beginning before more serious deterioration, leading to Alzheimer’s dementia (AD). MCI detection was needed to determine the patient's therapeutic management. Analysis of electroencephalogram (EEG) coherence is one of the modalities for MCI detection. Therefore, this study investigated the inter and intra-hemispheric coherence over 16 EEG channels in the frequency range of 1-30 Hz. The simulation results showed that most of the electrode pair coherence in MCI patients have decreased compared to normal elderly subjects. In inter hemisphere coherence, significant differences (p<0.05) were found in the FP1-FP2 electrode pairs. Meanwhile, significant differences (p<0.05) were found in almost all pre-frontal area connectivity of the intra-hemisphere coherence pairs. The electrode pairs were FP2-F4, FP2-T4, FP1-F3, FP1-F7, FP1-C3, FP1-T3, FP1-P3, FP1-T5, FP1-O1, F3-O1, and T3-T5. The decreased coherence in MCI patients showed the disconnection of cortical connections as a result of the death of the neurons. Furthermore, the coherence value can be used as a multimodal feature in normal elderly subjects and MCI. It is hoped that current studies may be considered for early detection of Alzheimer’s in a larger population.
Geometric and Grayscale Template Matching for Saudi Arabian Riyal Paper Currency Recognition Suci Aulia; Bagus Budhi L.; Angga Rusdinar; Yuyun Siti R.
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v8i6.pp4230-4238

Abstract

Detecting the authenticity of paper currencies using automated based Paper Currency Recognition (PCR) with image processing techniques was still a hot topic of discussion, due to the circulation of counterfeit currency that was still overwhelming in some countries. There was a downside along with this advancement in technology in the field of color printing, duplication, and scanning, because it was became one of the supporting factors of the increasing crime rate in production of counterfeit money. Our system has performed a PCR approach based on image processing techniques. In this study, the SAR banknote was the object to be recognized and detected its authenticity with the development of the previous method, which was incorporating the Geometric Template Matching and Grayscale Template Matching. In addition to the pattern recognition process, the classification process on 1 SAR, 2 SAR, 5 SAR, and 10 SAR was also performed. From PCR test up to 100 sample data, for each tested banknote value obtained the average value of the best accuracy level from incorporating GeoMatchingScore and GrayMatchingScore for the classification process was 95.25%. While the average level of system accuracy in recognizing counterfeit money on each banknote obtained a maximum value of 100%.
Brain Tumor Identification Based on VGG-16 Architecture and CLAHE Method Suci Aulia; Dadi Rahmat
JOIV : International Journal on Informatics Visualization Vol 6, No 1 (2022)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.1.864

Abstract

Magnetic Resonance Imaging (MRI) in diagnosing brain cancers is widespread. Because of the variety of angles and clarity of anatomy, it is commonly employed. If a brain tumor is malignant or secondary, it is a high risk, leading to death. These tumors have an increased predisposition for spreading from one place to another. In detecting brain abnormality form such as a tumor, from a magnetic resonance scan, expertise and human involvement are required. Previous, the image segmentation of brain tumors is widely developed in this field. Suppose we could somehow use an automatic brain tumor detection technology to identify the presence of a tumor in the brain without requiring human intervention. In that case, it will give us a leg up in the treatment process. This research proposed two stages to identify the brain tumor in MRI; the first stage was the image enhancement process using Clip Limit Adaptive Histogram Equalization (CLAHE) to segment the brain MRI. The second one was classifying the brain tumor on MRI using Visual Geometry Group-16 Layer (VGG-16). The CLAHE was used in some instances, there were CLAHE applied in FLAIR image on green color, and CLAHE applied in Red, Green, Blue (RGB) color space. The experimental result showed the highest performance with accuracy, precision, recall, respectively 90.37%, 90.22%, 87.61%. The CLAHE method in RGB Channel and the VGG-16 model have reliably on predicted oligodendroglioma classes in RGB enhancement with precision 91.08% and recall 95.97%.
Hand gesture recognition using discrete wavelet transform and hidden Markov models Erizka Banuwati Candrasari; Ledya Novamizanti; Suci Aulia
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.13725

Abstract

Gesture recognition based on computer-vision is an important part of human-computer interaction. But it lacks in several points, that was image brightness, recognition time, and accuracy. Because of that goal of this research was to create a hand gesture recognition system that had good performances using discrete wavelet transform and hidden Markov models. The first process was pre-processing, which done by resizing the image to 128x128 pixels and then segmented the skin color. The second process was feature extraction using the discrete wavelet transform. The result was the feature value in the form of a feature vector from the image. The last process was gesture classification using hidden Markov models to calculate the highest probability of feature matrix which had obtained from the feature extraction process. The result of the system had 72% of accuracy using 150 training and 100 test data images that consist five gestures. The newness thing found in this experiment were the effect of acquisition and pre-processing. The accuracy had been escalated by 14% compared to Sebastien’s dataset at 58%. The increment effect propped by brightness and contrast value.
FPGA-based implementation of speech recognition for robocar control using MFCC Bayuaji Kurniadhani; Sugondo Hadiyoso; Suci Aulia; Rita Magdalena
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 4: August 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i4.12615

Abstract

This research proposes a simulation of the logic series of speech recognition on the MFCC (Mel Frequency Spread Spectrum) based FPGA and Euclidean Distance to control the robotic car motion. The speech known would be used as a command to operate the robotic car. MFCC in this study was used in the feature extraction process, while Euclidean distance was applied in the feature classification process of each speech that later would be forwarded to the part of decision to give the control logic in robotic motor. The test that has been conducted showed that the logic series designed was precise here by measuring the Mel Frequency Warping and Power Cepstrum. With the achievement of logic design in this research proven with a comparison between the Matlab computation and Xilinx simulation, it enables to facilitate the researchers to continue its implementation to FPGA hardware.
Automatic face and VLP’s recognition for smart parking system Reivind P. Persada; Suci Aulia; Burhanuddin D.; Sugondo H.
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 4: August 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i4.11746

Abstract

One of the concerning issues regarding smart city is Smart Parking. In Smart Parking, some researchers try to provide solutions and breakthroughs on several research topics among security systems, the availability of single space, an IoT framework, etc. In this study, we proposed a security system on Smart Parking based on face recognition and VLP’s (Vehicle License Plates) identification. In this research, SSIM (Structural Similarity) method as part of IQA has been applied due to its reliability and simple computation for face detection and recognition process. From the test results of 30 data, obtained the highest SSIM value 0.83 with the highest accuracy rate of 76.67%. That level of accuracy still has not reached the implementation standard of 99.9%. So that it still needs to be improved in the future studies, especially in the filtering noise section.
Hand gesture recognition using discrete wavelet transform and convolutional neural network Muhammad Biyan Priatama; Ledya Novamizanti; Suci Aulia; Erizka Banuwati Candrasari
Bulletin of Electrical Engineering and Informatics Vol 9, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (753.476 KB) | DOI: 10.11591/eei.v9i3.1977

Abstract

Public services are available to all communities including people with disabilities. One obstacle that impedes persons with disabilities from participating in various community activities and enjoying the various public services available to the community is information and communication barriers. One way to communicate with people with disabilities is with hand gestures. Therefore, the hand gesture technology is needed, in order to facilitate the public to interact with the disability. This study proposes a reliable hand gesture recognition system using the convolutional neural network method. The first step, carried out pre-processing, to separate the foreground and background. Then the foreground is transformed using the discrete wavelet transform (DWT) to take the most significant subband. The last step is image classification with convolutional neural network. The amount of training and test data used are 400 and 100 images repectively, containing five classes namely class A, B, C, # 5, and pointing. This study engendered a hand gesture recognition system that had an accuracy of 100% for dataset A and 90% for dataset B.
Multipoint to Point EKG Monitoring Berbasis ZigBee Sugondo Hadiyoso; Suci Aulia
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2014
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pada penelitian sebelumnya, telahdirealisasikan perangkat monitoring EKG berbasis Wifidan ZigBee namun masih bersifat point to point sehinggatidak dapat digunakan untuk memonitor banyak pasiendalam satu perangkat display. Sistem point to pointmenjadi tidak efisien ketika digunakan pada beberapapasien yang memerlukan pemantauan secara bersamaan.Oleh karena itu diperlukan konfigurasi multipoint to pointuntuk mengatasi permasalahan tersebut. Pada penelitianini telah direalisasikan suatu sistem monitoring EKG yangmengaplikasikan konfigurasi jaringan multipoint to pointmenggunakan perangkat ZigBee sebagai modultransceiver. Sebagai penelitian awal, direalisasikan sistemmonitoring untuk tiga (3) perangkat EKG pada sisi pasiendan satu perangkat penerima sebagai penampil data sinyalEKG. Sistem ini kita sebut 3 to 1 EKG monitoring system.Perangkat EKG pada proyek ini menggunakan tekniksadapan bipolar lead berbasis segitga Einthoven dengansadapan lead II sebagai standar monitoring EKG.
Pengembangan Perangkat EKG 12 Lead dan Aplikasi Client-Server untuk Distribusi Data SUGONDO HADIYOSO; MUHAMMAD JULIAN; ACHMAD RIZAL; SUCI AULIA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 3, No 2 (2015): ELKOMIKA
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v3i2.91

Abstract

ABSTRAKElektrokardiograf adalah perangkat untuk mengukur aktifitas kelistrikan jantung. Sinyal yang ditampilkan oleh perangkat elektrokardiograf adalah sinyal elektrokardiogram (EKG). Untuk monitoring ECG  minimal diperlukan satu lead sementara untuk standar klinis diperlukan 12 lead. Untuk realisasi perangkat EKG 12 lead diperlukan strategi agar jumlah perangkat keras yang dibutuhkan semakin sedikit sehingga dimensi menjadi lebih kecil. Untuk mengatasi permasalahan tersebut, pada penelitian ini dirancang perangkat EKG 12 lead dengan teknik multipleksing. Kombinasi sadapan sinyal EKG 12 lead dikontrol oleh multiplekser 4051 melalui mikrokontroler secara bergantian. Data dijital hasil konversi ADC selanjutnya dikirim secara serial ke komputer server dan dapat dilihat pada komputer client yang terhubung. Hasil yang didapat menunjukkan bahawa perangkat analog telah berhasil mengakuisisi sinyal EKG dengan baik dari Lead I sampai Lead V6. Dengan waktu pensakelaran sebesar 5 ms, sinyal tidak dapat ditampilkan secara simultan 12 lead. Sinyal dapat diakuisisi dengan baik jika waktu pensakelaran sebesar 5 detik namun seluruh sadapan sinyal EKG tidak dapat ditampilkan secara simultan.Kata kunci: Elektrokardiograf, 12 Lead, Multipleksing, Server, Client. ABSTRACTElectrocardiograph is device for measuring electrical activity of heart. Electrocardiograph displays electrocardiogram signal (ECG). For monitoring ECG, at least need one ECG lead meanwhile for standard clinical ECG need 12 lead. For realization of 12 lead ECG devices, it is need strategy to reduce number of hardware to make dimension of ECG device smaller. To solve this problem, we use multiplexing method for ECG device development. Combination of 12 lead ECG signal is controlled by the multiplexer 4051 through microcontroller sequentially. Digital data of ADC is sent serially to the server computer and can be viewed on client computer that connected to the network. From the results obtained indicate that analog devices have been successfully acquired ECG signals Lead I to Lead V6. With 5 ms switching time, the 12 lead ECG signal can not be displayed simultaneously. The signal can be acquired properly with 5 seconds switching time, but the whole of ECG signals can not be displayed simultaneously.Keywords: Electrocardiograph, 12 Lead, Multiplexing, Server, Client.
Deteksi Limfosit Plasma Biru pada Citra Darah untuk Diagnosa Pendukung pada Kasus Demam Berdarah Dengue SUCI AULIA; SUGONDO HADIYOSO
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 9, No 1 (2021): ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektro
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v9i1.150

Abstract

ABSTRAKDemam Berdarah Dengue (DBD) adalah salah satu penyakit mematikan yang disebabkan oleh virus dengue sehingga diagnosis dini DBD sangat penting dilakukan. Secara umum, diagnosis dini DBD dilakukan melalui pemeriksaan trombosit namun pemeriksaan ini tidak spesifik. Salah satu uji klinis lainnya yang dapat dilakukan untuk diagnosis dini DBD adalah deteksi limfosit plasma biru (LPB) melalui pencitraan sel darah. Oleh karena itu, pada studi ini diusulkan metode deteksi LBP secara otomatis pada citra mikroskopis darah. Data dikumpulkan dari pasien dengue dan subjek normal. Pada studi ini digunakan 20 gambar dataset yang terdiri dari 10 gambar terinfeksi dengue dan 10 gambar limfosit biasa sebagai kondisi normal. Ekstraksi ciri dilakukan dengan filter Gabor dan kemudian validasi dilakukan dengan K-Nearest Neigbor (K-NN) dan 5-fold cross validation. Dari pengujian yang dilakukan diperoleh akurasi deteksi tertinggi sebesar 90%, dimana dicapai menggunakan metode Cosine K-NN. Hasil studi ini diharapkan dapat digunakan dalam menunjang penegakan diagnosa penyakit dengue.Kata kunci: demam berdarah dengue, deteksi, limfosit, K-NN ABSTRACTDengue Hemorrhagic Fever (DHF) is a deadly disease caused by the dengue virus, so early diagnosis of DHF is very important. Commonly, early diagnosis of dengue fever is done through a platelet examination, but this examination is not specific. One of the other clinical tests that can be done for early diagnosis of DHF is detection of blue plasma lymphocytes (LBP) through blood cell imaging. Therefore, this study proposes an automatic LBP detection method on microscopic blood images. Data were collected from dengue patients and normal subjects. A total of 20 images were analyzed in this study consisting of 10 images infected with dengue and 10 images of normal lymphocytes as normal conditions. Feature extraction was carried out with the Gabor filter and then the validation was carried out with K-Nearest Neigbor (K-NN) and 5-fold cross validation. From the tests conducted, the highest detection accuracy is 90%, which is achieved using the Cosine K-NN method. The results of this study are expected to be used in supporting the diagnosis of dengue disease.Keywords: Dengue hemorrhagic fever, detection, lymphocytes, K-NN
Co-Authors Aaron Abel Abid Ghufran Ramadhan Abraham Caesar Yanuar Putra Achmad Rizal Adri Achmad Farhan Agus Gunarso Aldy Andreansyah Himawan Alvinas Deva Sih Illahi Amri Khurniawan Ananda Ayu Chellsya Anatasya Bella Andik Wijanarko Angga Rusdinar Ardyandrea Erstya Surya Arif Setiawan Arif Setiawan ARIS HARTAMAN Asep Mulyana ATIK NOVIANTI Aulya Ellanda Bagas Ruli Pandapotan Bagus Budhi L. Bambang Hidayat Bayuaji Kurniadhani Burhanuddin Burhanuddin Burhanuddin D. Cendra Roganda Sangap Manurung Dadan Nur Ramadan Dadan Nur Ramadhan Dadi Rahmat Della Oktriani Denny Darlis Dery Rimasa Didin Yulian Dimitri Mahayana Diovani Estidia Akbar Efri Suhartono Erizka Banuwati Candrasari Erty Kasdiantika ERVIN MASITA DEWI Fiona Okki Rahmalisty Fony Ferliana Widianingrum Galuh Laksmita Ranggi Gelar Budiman Grislend Gloria Natalies Hafiddudin Hafiddudin Hafiidh As Syahidulhaq Hafiz Adriansyah Handoko Supeno Hengki Setiadi I NYOMAN APRAZ RAMATRYANA Ilham Kurniawan Indrarini Dyah Irawati Inung Wijayanto Jean Pierre Uwiringiyimana Khairunnisa Alfiyanti Suharja Kusumawardhani, Eka Ledya Novamizanti M. Dyovan Uidy Okta Meidi Mahendra Rahmatullah Melina Melina Mohammad Zhillan Al Rashif Muhammad Arly Gunawan Muhammad Biyan Priatama Muhammad Iqbal MUHAMMAD JULIAN Muhammad Katamin Muhammad Obi Nugraha Muhammad Obi Nugraha Muhammad Panji Kusuma Praja Muhammad Rafki Nur Ramadhani Olvyandra Oriesta Raditiana Patmasari Rahmat Sopian Rajali Ginting Randany Maulana Randany Maulana Ratri Dwi Atmaja Raymond Y. Purba Reivind P. Persada Restu Wardani Rita Magdalena Rita Purnamasari Rizky Edi Saputra Rudy Gunawan Ryan Bagus Wicaksana Ryan Bagus Wicaksono Sri Dewi Sartika Sugondo H. Sugondo Hadiyoso Suliyono Suliyono Susi Susanti Syahban Rangkuti Thoriq Dharmawan Viona Apryaleva Yafis Sukma Kurniawan Yoni Sudiani YULI SUN HARIYANI Yusuf Prabowo Yuyun Siti R. YUYUN SITI ROHMAH