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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknik ITS IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science Semantik JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmiah Kursor EMITTER International Journal of Engineering Technology Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Health Notions Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JAVA Journal of Electrical and Electronics Engineering JAREE (Journal on Advanced Research in Electrical Engineering) International Journal of Robotics and Control Systems Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Sistim Informasi dan Teknologi Sewagati
Tri Arief Sardjono
Departemen Teknik Biomedik Institut Teknologi Sepuluh Nopember Surabaya
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Modifikasi Fitur dengan Differential Asymmetry untuk Meningkatkan Akurasi Klasifikasi EEG Motor Imagery Yulianto Tejo Putranto; Tri Arief Sardjono; Mochamad Hariadi; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 8 No 1: Februari 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 (1090.653 KB)

Abstract

Brain-Computer Interface (BCI) technology has enabled people with motor disabilities to interact with their environment. The electroencephalograph (EEG) signals related to a motor imagery movement were used as a control signal. In this paper, EEG motor imagery signals from the 2-class data have been processed into features and classified. The power and standard deviation of EEG signals, mean of absolute wavelet coefficients, and the average power of the wavelet coefficients were used as features. The purpose of this paper is to apply the differential asymmetry of these features as new features to improve the system accuracy. As a classifier, Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), and Tree were used. The result shows that for dataset I the use of differential asymmetry as feature can increase the system accuracy up to 47.8%, from 52.20% to 100%, with Tree as a classifier. For dataset II, it can increase accuracy by 8.46%, from 54.42% to 62.48%.
Pengenalan Viseme Dinamis Bahasa Indonesia Menggunakan Convolutional Neural Network Aris Nasuha; Tri Arief Sardjono; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

There has been very little researches on automatic lip reading in Indonesian language, especially the ones based on dynamic visemes. To improve the accuracy of a recognition process, for certain problems, choosing suitable classifiers or combining of some methods may be required. This study aims to classify five dynamic visemes of Indonesian language using a CNN (Convolutional Neural Network) and to compare the results with an MLP (Multi Layer Perceptron). Varying some parameters theoretically improving the recognition accuracy was attempted to obtain the best result. The data includes videos on pronunciation of daily words in Indonesian language by 28 subjects recorded in frontal view. The best recognition result gives 96.44% of validation accuracy using the CNN classifier with three convolution layers.
Optimasi Support Vector Machine untuk Memprediksi Adanya Mutasi pada DNA Hepatitis C Virus Berlian Al Kindhi; Tri Arief Sardjono; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Hepatitis C Virus (HCV) is a virus which capable of infecting RNA that can lead to changes in the DNA sequence. This change of DNA arrangement is called genetic mutation. Every mutation occurs in HCV, it will be called a new subtype. Over time, HCV subtypes increase, and will continue to grow as the HCV mutation cycle progresses faster. Therefore, a way to find a mutation in millions of sequences in the gene bank is needed. This study tested six types of Support Vector Machine (SVM) methods to determine the best SVM kernel performance in the application of HCV DNA sequence detection in isolatedDNA. The tested SVM kernel was linear, quadratic, cubic, fine Gaussian, median Gaussian, and coarse Gaussian. The data set is 1000 isolated DNA consisting of 500 isolated Homo Sapiens and 500 isolated HCV. Firstly, the data set will go through the pattern search process using the Edit Levenshtein Distance method, then the result of the processing will be the variable x in SVM. The target or variable y on SVM is the positive or negative value of the isolated against HCV. The results show that among the six types of SVM methods being tested, the method of fine Gaussian SVM has the lowest performance of 77.4%. The SVM method is tested by performing optimizations on the determination of the hyperplane. The test results proved that the SVM method is able to analyze the presence of HCV mutations in isolated DNA with an accuracy of 99.8%.
An Image Processing Framework for Breast Cancer Detection Using Multi-View Mammographic Images Nada Fitrieyatul Hikmah; Tri Arief Sardjono; Windy Deftia Mertiana; Nabila Puspita Firdi; Diana Purwitasari
EMITTER International Journal of Engineering Technology Vol 10 No 1 (2022)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v10i1.695

Abstract

Breast cancer is the leading cause of cancer death in women. The early phase of breast cancer is asymptomatic, without any signs or symptoms. The earlier breast cancer can be detected, the greater chance of cure. Early detection using screening mammography is a common step for detecting the presence of breast cancer. Many studies of computer-based using breast cancer detection have been done previously. However, the detection process for craniocaudal (CC) view and mediolateral oblique (MLO) view angles were done separately. This study aims to improve the detection performance for breast cancer diagnosis with CC and MLO view analysis. An image processing framework for multi-view screening was used to improve the diagnostic results rather than single-view. Image enhancement, segmentation, and feature extraction are all part of the framework provided in this study. The stages of image quality improvement are very important because the contrast of mammographic images is relatively low, so it often overlaps between cancer tissue and normal tissue. Texture-based segmentation utilizing the first-order local entropy approach was used to segment the images. The value of the radius and the region of probable cancer were calculated using the findings of feature extraction. The results of this study show the accuracy of breast cancer detection using CC and MLO views were 88.0% and 80.5% respectively. The proposed framework was useful in the diagnosis of breast cancer, that the detection results and features help clinicians in making treatment.
Comparative SNR Analysis Between Instrument ADAS1000 and AD620 Tri Arief Sardjono; Hendra Kusuma; Tasripan; Kharis Sugiarto
Jurnal Sistim Informasi dan Teknologi 2022, Vol. 4, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (514.934 KB) | DOI: 10.37034/jsisfotek.v4i3.145

Abstract

The semiconductor technology for a certain function, such as instrumentation amplifier ICs is currently developing very fast, commercially available and can be obtained easily on the market. An instrumentation amplifier is a very important part in the process of data acquisition, especially for biopotential signals from the human body because its amplitude is very small and susceptible to noise interference. The selection of the proper amplifier instrumentation will produce an accurate biopotential signal reading. This paper explains the use of 2 types of instrumentation amplifiers, namely AD620 and ADAS1000, which are used in the design and realization of 12-channel ECG (Electrocardiograph). The performance and noise resistance of the two instrumentation amplifiers are compared and analyzed so that an appropriate instrumentation amplifier can be determined especially in the case of 12-channel ECG applications. 12-channel ECG was chosen because of the complexity of the design and can provide more detailed information as well as to detect the abnormalities heart’s functions. The results shows that 12-channel ECG using AD620 instrumentation amplifier has an SNR value below 12.04 dB, while using the ADAS1000 instrumentation amplifier has an SNR value below 35.5 dB and it is more resistant to noise interference.
Comparison of Amplifiers Utilization in Instrumentation to Record Muscle Signals in the Neck for Electrolarynx Applications Muhammad Hilman Fatoni; Nabilah Ashriyah; Tri Arief Sardjono; Mohammad Nuh
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 6, No 2 (2022): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v6i2.329

Abstract

Electrolarynx is an assistive technology commonly used by speech impaired people to speak. The speech impaired people who have lost their larynx (laryngectomee) or have damaged larynx use an electrolarynx device to be able to speak again. The use of the electrolarynx is generally equipped with a button to turn on and start the generation of sound from the electrolarynx. Several studies have tried to use other control methods by using the muscles in the neck, namely the sternohyoid muscle. Activation of the sternohyoid muscle has an influence on sound formation. The sternohyoid muscle is a small and long muscle so recording EMG (electromyograph) signals from this muscle is quite difficult. If the recording process of this signal can be carried out properly, then the electrolarynx control by empowering this muscle will be another solution in using the electrolarynx. In this study, instrumentation amplifier which is an important stage of recording EMG signals of neck muscle was tested and compared. There are two types of instrumentation amplifier tested. The first instrumentation amplifier uses a single IC from IC AD620 while the other is a combination circuit of IC OP07. The EMG signal in the subject's neck muscles was then recorded using the instrumentation amplifiers. The subject will sit down and pronounce the vowels "a", and "i". From the testing process, it was found that the average gain on IC AD620 (minimum 1.74362 volts and maximum 3.70538 volts) was greater than the gain on IC OP07 (minimum 0.57779 volts and maximum 1.71190 volts). IC AD620 also has an overall use area of 5.61 cm2 with the use of 4 external components. Thus, it can be concluded that the best instrumentation amplifier for recording EMG neck muscle for electrolarynx application is by using IC AD620.
Pemanfaatan Kursi Roda Elektrik dengan Kendali Joystick Guna Meningkatkan Kemandirian Siswa Berkebutuhan Khusus di Sekolah Luar Biasa D Yayasan Pembinaan Anak Cacat Surabaya Muhammad Hilman Fatoni; Eko Agus Suprayitno; Achmad Arifin; Nada Fitrieyatul Hikmah; Tri Arief Sardjono; Mohammad Nuh
Sewagati Vol 7 No 2 (2023)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (5909.514 KB) | DOI: 10.12962/j26139960.v7i2.446

Abstract

Sekolah Luar Biasa Yayasan Pembinaan Anak Cacat (SLB YPAC) Surabaya merupakan yayasan pendidikan yang dirintis dan ditujukan untuk anak-anak yang mengalami cacat atau berkebutuhan khusus. SLB YPAC Surabaya berdiri dikhususkan untuk anak-anak penyandang disabilitas fisik atau tunadaksa. Anak Tunadaksa (ATD) mengalami hambatan dalam hal mobilitas dan gerak, baik pada bagian tangan, kaki, atau anggota tubuh lain yang berkaitan dengan motorik. Oleh karena itu mereka membutuhkan alat bantu seperti kursi roda, tongkat, brace, dan teknologi asistif lain untuk menggantikan fungsi anggota tubuh yang hilang. Meski dengan bantuan alat, kenyataannya mereka masih membutuhkan bantuan orang lain misalnya bagi pengguna kursi roda. Dengan kursi roda konvensional, setiap siswa akan membutuhkan pendampingan secara khusus untuk bergerak dan berpindah. Terlebih lagi, ketika siswa melewati permukaan miring atau medan yang sulit maka guru harus berperan secara langsung. Harga kursi roda elektrik yang mahal juga menjadi alasan kursi roda konvensional masih digunakan. Dengan masalah ini, tim telah mengembangkan kursi roda elektrik dengan kendali berupa joystick. Pada bulan Agustus 2021 telah dilaksanakan sosialisasi penggunaan kursi roda elektrik dengan joystick di SLB YPAC. Dan pada awal bulan November 2021 tim telah melakukan serah terima kursi roda elektrik kepada SLB YPAC. Dengan produk kursi roda elektrik yang dikendalikan menggunakan joystick, dapat dilipat, memiliki fitur sabuk dan meja diharapkan dapat meningkatkan kemandirian siswa SLB YPAC Surabaya dalam melakukan aktivitas mobilisasi.
Metode Kalibrasi Probe Ultrasonik dari Phantom Kawat Tunggal Menggunakan Algoritma Levenberg-Marquardt Tri Arief Sardjono; Eko Mulyanto Yuniarno; I Made Gede Sunarya; I Ketut Eddy Purnama; Mauridhi Hery Purnomo; Norma Hermawan
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 3: Agustus 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i3.6282

Abstract

A freehand three-dimensional (3D) ultrasound system is a method of acquiring images using a 3D ultrasound probe or conventional two-dimensional (2D) ultrasound probe to give a 3D visualization of an object inside the body. Ultrasounds are used extensively in clinical applications since they are advantageous in that they do not bring dangerous radiation effects and have a low cost. However, a probe calibration method is needed to transform the coordinate position into a 3D visualization display, especially for image-guided intervention. The current ultrasound probe calibration system usually uses the numerical regression method for the N-wire phantom, which has problems in accuracy and reliability due to nonlinear point scattered ultrasound image data. Hence, a method for ultrasound probe positional calibration of single-wire phantom using the Levenberg-Marquardt algorithm (LMA) was proposed to overcome this weakness. This experiment consisted of an optical tracking system setup, a 2D ultrasound probe with marker, an ultrasound machine, and a single-wire object in a water container equipped with a marker. The position and orientation of the marker in a 2D ultrasound probe and the marker in the water container were tracked using the optical tracking system. A 2D ultrasound probe was equipped with a marker connected wirelessly using an optical tracking system to capture the single-wire object. The resulting sequences of 2D ultrasound images were reconstructed and visualized into 3D ultrasound images using three transformations, ultrasound beam to ultrasound probe’s marker, single-wire phantom position to container’s marker, and the 3D visualization transformation. The LMA was used to determine the best optimization parameters for determining the exact position and representing that 3D visualization. The experiment result showed that the lowest mean square error (MSE), rotation error, and translation error were 0.45 mm, 0.25°, and 0.3828 mm, respectively.
Peningkatan Akurasi Adaptive Monte Carlo Localization Menggunakan Convolutional Neural Network Riza Agung Firmansyah; Tri Arief Sardjono; Ronny Mardiyanto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 3: Agustus 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i3.7432

Abstract

This paper explains the increase in localization system accuracy of the adaptive Monte Carlo localization (AMCL) in robots utilizing a convolutional neural network (CNN). The localization system in robots is defined as the position recognition process of robots within their working environment. This system is essential as it allows robots to navigate and map efficiently and accurately. Without appropriate localization, robots cannot operate effectively and can encounter troubles such as losing direction or bumping into objects. AMCL is a popular localization system and is widely applied in robots. This method utilizes the changes in the robots’ position and light detection and ranging (LiDAR) sensor reading as input. Reading of robot position changes is susceptible to error due to slips or wheel deformations. The inaccuracy of reading the robots’ position change results in the inaccuracy of the robots’ position prediction by AMCL, so improvements are required. Novelty in this paper includes providing compensation values from AMCL results for the error to be small. These compensation values were obtained from the CNN training results; hence, the proposed method was dubbed AMCL+CNN. Inputs given to the CNN were the changes in wheel odometry values and distance reading by the LiDAR sensor. CNN outputs were compared to the target data in the form of the robots’ actual position from observation results. Network training was conducted for as many as 200 epochs to achieve the lowest validation loss. Testing was done on a robot installed with a robot operating system (ROS). Training and testing datasets were obtained from rosbag data when the robot traversed the testing area. In straight and turn scenarios, obtained AMCL+CNN algorithms had fewer errors than the regular AMCL and Monte Carlo localization (MCL). Results obtained are also superior in terms of positional error metrics when compared to several other comparison methods.
Perbaikan Mesin Cetak Braille dan Pelatihan Bagi Operator dan Guru di SLB N Muara Bulian, Batanghari, Jambi Hendra Kusuma; Tasripan; Tri Arief Sardjono; Rudy Dikairono; Totok Mujiono
Sewagati Vol 7 No 6 (2023)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v7i6.696

Abstract

Program pengembangan sekolah luar biasa untuk tunanetra, yaitu dalam bentuk pengembangan bahan ajar Braille sudah dilakukan Pemerintah sejak awal 1998, yaitu dengan dibentuknya sekolah luar biasa (SLB) yang berperan sebagai pusat sumber Resource Center penyelenggaraan pendidikan yang salah satu fungsinya adalah pengembangan media pembelajaran dalam huruf Braille. SLBN Muara Bulian, Batang Hari, Jambi merupakan salah satu SLB pusat sumber yang dimaksud. Mesin Braille SLB Muara Bulian sudah lama rusak dan tidak ada pihak yang mampu memperbaikinya sehingga kegiatan pengadaan dan pengembangan bahan ajar Braille menjadi terputus. Untuk itu pihak SLB Muara Bulian mengharapkan bantuan tim ahli Departemen Teknik Elektro ITS agar memperbaiki mesin Braille dan sekaligus memberi pelatihan teknis tentang pemeliharaan dan operasional bagi operator mesin Braille dan guru SLB. Hasil diagnosa, dan perbaikan yang dilakukan oleh tim DTE ITS menghasilkan mesin Braille SLB Muara Bulian kembali beroperasi sempurna seperti kondisi baru. Adapun perbaikan mesin Braille yang rusak tersebut dilakukan pada bagian mekanis, dan elektronik serta pada penyempurnaan software, sehingga mesin Braille SLB dapat beroperasi sempurna dengan kemampuan cetak 400 karakter per detik dan konsumsi daya listrik yang lebih rendah 40\% dari konsumsi semula. Disamping itu juga diberikan pelatihan teknis dasar yang berkaitan dengan pemeliharaan mesin bagi operator serta operasional mesin Braille bagi para guru SLB.
Co-Authors A. Surbakti, Armand Faris Ainani Shabrina Febrianti Al Kindhi, Berlian Alan Novi Tompunu Ardyono Priyadi Arifin, Achmad Aris Nasuha Arraziqi, Dwi Asmaria, Talitha Atar Fuady Babgei Berlian Al Kindhi Budiman, Fajar Cahya Perbawa Aji Dewi Mayangsari Dewi Mayangsari Diah Puspito Wulandari Diana Purwitasari Dimas Herjuno Djoko Purwanto Durrotun Munafiah Eko Agus Suprayitno Eko Mulyanto Yuniarno Farah Zakiyah Rahmanti Fatchul Arifin Firmansyah, Riza Agung Gde Bayu Adityaputra Hajjanto, Ariq Dreiki Harris Pirngadi Helmy Widyantara Hendra Kusuma Hendra Kusuma Hermawan, Norma Herti Miawarni Hikmah, Nada Fitrieyatul I Ketut Eddy Purnama I Made Gede Sunarya Ismoyo Sunu Jaenal Arifin Joko Priambodo Joko Subur Kharis Sugiarto Kusuma, Hendra Siswanto Lilik Subiyanto Mauridhi Hery Purnomo Mauridhy Hery Purnomo Melyana Nurul Widyawati Moch. Iskandar Riansyah Mochamad Hariadi Moh. Yani Mohammad Nuh Muhammad Hilman Fatoni Muhammad Rivai Munafiah, Durrotun Nabila Puspita Firdi Nabilah Ashriyah Nabilah Ashriyah Nada Fitrieyatul Hikmah Oddy Virgantara Putra Paskalis Kurniaji Prakosa, Nadhira Anindyafitri RD Kusumanto Retno Tri Wahyuni Rika Rokhana Ronny Mardiyanto, Ronny Rudy Dikairono Setiawardhana Setiawardhana Setiawardhana Setijadi, Eko Tita Karlita Totok Mujiono, Totok Ubaidillah Umar, Ubaidillah Wijayanti . Windy Deftia Mertiana Windy Deftia Mertiana Yulianto Tejo Putranto Yulianto, Lucas Yunardi, Riky Tri