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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Mechatronics, Electrical Power, and Vehicular Technology TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Transportasi Jurnal Teknologi Prosiding SNATIF International Journal of Advances in Intelligent Informatics ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Proceeding of the Electrical Engineering Computer Science and Informatics Techne : Jurnal Ilmiah Elektroteknika Communications in Science and Technology Buletin Ilmiah Sarjana Teknik Elektro IJITEE (International Journal of Information Technology and Electrical Engineering) Indonesian Journal of Electrical Engineering and Computer Science International Journal of Quantitative Research and Modeling Teknika STTKD: : Jurnal Teknik, Elektronik, Engine Automotive Experiences
Oyas Wahyunggoro
Univeristas Gadjah Mada
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Transportation

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A new approach for sensitivity improvement of retinal blood vessel segmentation in high-resolution fundus images based on phase stretch transform Kartika Firdausy; Oyas Wahyunggoro; Hanung Adi Nugroho; Muhammad Bayu Sasongko
International Journal of Advances in Intelligent Informatics Vol 8, No 3 (2022): November 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v8i3.914

Abstract

The eye-fundus photograph is widely used for eye examinations. Accurate identification of retinal blood vessels could reveal information that is helpful for clinical diagnoses of many health disorders. Although several methods have been proposed to segment images of retinal blood vessels, the sensitivity of these methods is plausible to be improved. The algorithm’s sensitivity refers to the algorithm’s ability to identify retinal vessel pixels correctly. Furthermore, the resolution and quality of retinal images are improving rapidly. Consequently, new segmentation methods are in demand to overcome issues from high-resolution images. This study presented improved performance of retinal vessel segmentation using a novel edge detection scheme based on the phase stretch transform (PST) function as its kernel. Before applying the edge detection stage, the input retinal images were pre-processed. During the pre-processing step, non-local means filtering on the green channel image, followed by contrast limited adaptive histogram equalization (CLAHE) and median filtering, were applied to enhance the retinal image. After applying the edge detection stage, the post-processing steps, including the CLAHE, median filtering, thresholding, morphological opening, and closing, were implemented to obtain the segmented image. The proposed method was evaluated using images from the high-resolution fundus (HRF) public database and yielded promising results for sensitivity improvement of retinal blood vessel detection. The proposed approach contributes to a better segmentation performance with an average sensitivity of 0.813, representing a clear improvement over several benchmark techniques
Low Pass Filter as Energy Management for Hybrid Energy Storage of Electric Vehicle: A Survey Maghfiroh, Hari; Wahyunggoro, Oyas; Cahyadi, Adha Imam
Automotive Experiences Vol 6 No 3 (2023)
Publisher : Automotive Laboratory of Universitas Muhammadiyah Magelang in collaboration with Association of Indonesian Vocational Educators (AIVE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.9398

Abstract

The transportation sector contributes up to 35% of carbon dioxide pollution. Electric Vehicles (EVs) offer a pollution-free alternative but face a crucial challenge in their battery-based Energy Storage System (ESS). The solution to the battery issues is combining it with other ESS with high power density called a Hybrid Energy Storage System (HESS). Energy Management Strategy (EMS) is used to distribute the power demand in the HESS. Low Pass Filters (LPFs) are one type of EMS that can be used to ensure the smooth flow of power between different energy storage elements. This article focuses on the pivotal role of Low Pass Filters (LPFs) within HESS for EVs, facilitating seamless power flow. The novelty lies in the comprehensive review of LPFs in this context, shedding light on their impact on energy management. Four LPF architecture classes are discussed: fixed cut-off, optimal cut-off, adaptive cut-off, and combination, referencing prior research. Additionally, a critical examination of challenges and limitations is provided, offering insights for researchers and practitioners.
Inverse kinematic solution and singularity avoidance using a deep deterministic policy gradient approach Surriani, Atikah; Wahyunggoro, Oyas; Imam Cahyadi, Adha
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2999-3009

Abstract

The robotic arm emerges as a subject of paramount significance within the industrial landscape, particularly in addressing the complexities of its kinematics. A significant research challenge lies in resolving the inverse kinematics of multiple degree of freedom (M-DOF) robotic arms. The inverse kinematics of M-DOF robotic arms pose a challenging problem to resolve, thus it involves consideration of singularities which affect the arm robot movement. This study aims a novel approach utilizing deep reinforcement learning (DRL) to tackle the inverse kinematic problem of the 6-DOF PUMA manipulator as a representative case within the M-DOF manipulator. The research employs Jacobian matrix for the kinematics system that can solve the singularity, and deep deterministic policy gradient (DDPG) as the kinematics solver. This chosen technique offers enhancing speed and ensuring stability. The results of inverse kinematic solution using DDPG were experimentally validated on a 6-DOF PUMA arm robot. The DDPG successfully solves inverse kinematic solution and avoids the singularity with 1,000 episodes and yielding a commendable total reward of 1,018.
Interval type-2 fuzzy logic system for diagnosis coronary artery disease Sajiah, Adha Mashur; Setiawan, Noor Akhmad; Wahyunggoro, Oyas
Communications in Science and Technology Vol 1 No 2 (2016)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.1.2.2016.26

Abstract

Coronary artery disease (CAD) is a disease that has been the deadliest disease in Indonesia. The ratio of cardiologists over potential patients is not appropriate either. Intelligent system which can help doctors or patients for cheap and efficient diagnosing CAD is needed. Medical record data, acquisition of cardiologist knowledge and computing technology can be utilized for developing fuzzy logic based intelligent system. Type-1 fuzzy logic system (T1 FLS) has been widely used in various fields. T1 FS has limitation in representing and modelling uncertainty and minimize the impact. Whereas, type-2 fuzzy set (T2 FS) was also introduced as fuzzy set that can model uncertainty more sophisticated. T2 FLS does have a higher degree of freedom when modeling uncertainty but it is quite difficult to make the membership function. An interval T2 FS is a T2 FS in which the membership grade on third dimension is the same everywhere so it is simpler than T2 FS. This paper aims to clarify the better capability of IT2 FLS over T1 FLS on the development of CAD diagnosis system. Rules and membership function were formulated with the help of fuzzy c-means. This study illustrated the causes of CAD risk factors, fuzzification, type reduction and defuzzification. The resulted system was tested with percentage split method (50%-50%) to produce training data and testing data. This test is performed ten times with random seed to separate the data set. The resulted system generates an average of 73.78% accuracy, 71.94% sensitivity and 76.52% specificity.
A robust automated system for detecting and recognising the digit of electrical energy consumption number of the postpaid kWh-meter Pujiharsono, Herryawan; Nugroho, Hanung Adi; Wahyunggoro, Oyas
Communications in Science and Technology Vol 2 No 2 (2017)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.2.2.2017.61

Abstract

Most of the processes of kilowatt-hour meter (kWh-meter) reading in Indonesia are still in manual process which may lead to some problems, such as time consumption and high possibility of data entry errors.  Therefore, this study proposes an automated system to minimise these problems.  This system is developed for the image with uneven illumination condition and tilted position of stand kWh-meter due to the unavoidable situation while capturing the kWh-meter image.  In this study, the illumination problem is solved by local thresholding and the tilted position of stand kWh-meter is solved by combination of morphology operations and vertical edge detection on the location detection process and vertical-horizontal projections on the segmentation process.  Finally, the numeral recognition is performed by support vector machine (SVM) classifier with zonal density feature as a selected input.  The results show that the accuracy of proposed system is 93.55% on detection location process, 89.38% on segmentation process, and 78.10% on numeral recognition process.
Dynamic path planning using a modified genetic algorithm Pratomo, Awang Hendrianto; Wahyunggoro, Oyas; Triharminto, Hendri Himawan
International Journal of Advances in Intelligent Informatics Vol 10, No 3 (2024): August 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v10i3.699

Abstract

Genetic algorithm (GA) is well-known algorithm to find a feasible path planning which can be defined as global optimum problem. The drawback of GA is the high computation due to random process on each operator.  In this research, the new initial population integrating with new crossover operator strategy was proposed. The parameter is the length of distance travelled of the robot. Before employing the crossover operator, generating a c-obstacle have been done. The c-obstacle is used  as a filter to reduce unnecessary nodes to decrease time computation. After that, the initial population has been determined. The initial population is divided into two parents which parent’s chromosome contains an initial and goal position. The second parents are fulfilled with nodes from each obstacle. The genes of chromosome will add with c-obstacle nodes. Crossover operator is applied after filtering and c-obstacle of possible hopping is determined. Filtering method is used to remove unnecessary nodes that are part of c-obstacle. Fitness function considers the distance from  the last to next position. Optimum value is the shortest distance of path planning which avoids the obstacle in front.  The aim of the proposed method is to reduce the random population and random operating in GA. By using a similar data set of previous researches, the modified GA can reduce the total of generation and yield an adaptive generation number. This means that the modified GA converges faster than the other GA methods.
Broad-Band Noise Reduction using Least Mean Square (LMS)-Adaptive Line Enhancer (ALE) on Doppler Blood Flow Sound Signal SANTOSO, DANIEL; WAHYUNGGORO, OYAS; NUGROHO, PRAPTO
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 10, No 1: Published January 2022
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v10i1.189

Abstract

ABSTRAKHaemorrhoidal artery ligation (HAL) adalah metode operasi wasir yang memiliki keunggulan rasa sakit minimal dan waktu pemulihan cepat. Prosedur HAL bergantung pada bunyi Doppler untuk menentukan letak arteri dalam liang anus. Derau yang tercampur dalam sinyal membuat dokter kesulitan mendengarkan bunyi Doppler yang menandakan letak arteri wasir. Adaptive line enhancer (ALE) dengan algoritma least mean square (LMS) digunakan dalam penelitian ini untuk mengurangi aras derau yang terkandung dalam sinyal bunyi Doppler aliran darah. Hasil simulasi menunjukkan parameter mean square error (MSE), signal to noise ratio (SNR), dan waktu eksekusi untuk berbagai orde tapis. Nilai maksimum power spectral density (PSD) sinyal yang masuk ke tapis -86 dB/Hz, kemudian turun menjadi -101 dB/Hz setelah lewat tapis. SNR tertinggi 40,03 dB didapat ketika orde tapis 16. Waktu eksekusi hampir tidak berubah meskipun orde filter dinaikkan.Kata kunci: pengurangan derau, bunyi Doppler, ALE, LMS, HAL ABSTRACTHemorrhoidal artery ligation (HAL) is one of surgical methods in treating hemorrhoids disease known for less pain and fast recovery. HAL procedure relies on the Doppler audible sound to locate arteries within rectal column. Noise interfering the signal of interest makes arteries detection becomes difficult task for the surgeon since signal and noise spectral overlaps. Adaptive line enhancer (ALE) with least mean square (LMS) algorithm is used in this study to reduce noise level contained in Doppler blood flow sound signal. The simulation results show the mean square error (MSE), signal to noise ratio (SNR), and execution time for different filter order. The maximum power spectral density (PSD) value of the noisy signal and filtered signal are -86 dB/Hz and -101 dB/Hz. respectively. The highest SNR of 40.03 dB is obtained when filter tap order is set to 16. However signal processing time remains almost unchanged as the filter tap order increased.Keywords: noise reduction, Doppler sound, ALE, LMS, HAL
Discount Factor Parametrization for Deep Reinforcement Learning for Inverted Pendulum Swing-up Control Surriani, Atikah; Maghfiroh, Hari; Wahyunggoro, Oyas; Cahyadi, Adha Imam; Fajrin, Hanifah Rahmi
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 1 (2025): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i1.10268

Abstract

This study explores the application of deep reinforcement learning (DRL) to solve the control problem of a single swing-up inverted pendulum. The primary focus is on investigating the impact of discount factor parameterization within the DRL framework. Specifically, the Deep Deterministic Policy Gradient (DDPG) algorithm is employed due to its effectiveness in handling continuous action spaces. A range of discount factor values is tested to evaluate their influence on training performance and stability. The results indicate that a discount factor of 0.99 yields the best overall performance, enabling the DDPG agent to successfully learn a stable swing-up strategy and maximize cumulative rewards. These findings highlight the critical role of the discount factor in DRL-based control systems and offer insights for optimizing learning performance in similar nonlinear control problems.
Co-Authors ., Priyatmadi Adha Cahyadi Adha Cahyadi, Adha Adha Imam Cahyadi Adha Iman Cahyadi Adha Iman Cahyadi Adhi Susanto Agus Sujono Agus Sujono Awang Hendrianto Pratomo Bhisma Adji Pramana Bhisma Adji Pramana, Bhisma Adji Bobby Rian Dewangga Bwo Ren Ke Dani Prasetyo Daniel Santoso Edy Raharjo, R Suryoto Eka Firmansyah Eka Firmansyah Erwan Eko Prasetiyo Ginting, Almido Almido Haryanto Hanifah Rahmi Fajrin, Hanifah Rahmi Hanung Adi Nugroho Hari Maghfiroh Hari Wibawa Harmoko Harmoko Ibrahim Kamaruddin Ibrahim Kamaruddin Indah Soesanti Irwan Novianto Iswanto Iswanto Kartika Firdausy Kuo Lung Lian Kusban, Muhammad Lora Khaula Amifia Lukito Edi Nugroho M. Nisvo Ramadan M. Nisvo Ramadan, M. Nisvo Madzlan Napiah Madzlan Napiah Maghfiroh, Hari Muhammad Bayu Sasongko Muhammad Fikri Ardiansyah Noor Akhmad Setiawan Nugroho, Anan Nurman Setiawan Prapto Nugroho Prapto Nugroho Prayadi Sulistyanto Priyatmadi . R Suryoto Edy Raharjo R. Soekrisno Risanuri Hidayat Risky Via Yuliantari Roedy Kristiyono Rudi Uswarman Sajiah, Adha Mashur Seta Yuliawan Sigit Agung Widayat Sigit Agung Widayat, Sigit Agung Soekrisno, R. Sujono, Agus Surriani, Atikah Suwardo Suwardo Suwardo Suwardo Syifaun Nafisah Triharminto, Hendri Himawan Widyawati Prima, Widyawati