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All Journal International Journal of Electrical and Computer Engineering Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Jurnal Teknik ITS IPTEK The Journal for Technology and Science Semantik TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer agriTECH Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) EMITTER International Journal of Engineering Technology Proceeding of the Electrical Engineering Computer Science and Informatics JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science Jurnal Sains Dan Teknologi (SAINTEKBU) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Inotera Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) CCIT (Creative Communication and Innovative Technology) Journal JAVA Journal of Electrical and Electronics Engineering JAREE (Journal on Advanced Research in Electrical Engineering) Jurnal Impresi Indonesia Jurnal Nasional Teknik Elektro dan Teknologi Informasi Makara Journal of Technology Jurnal Rekayasa elektrika International Journal of Computing Science and Applied Mathematics-IJCSAM
Mauridhi Hery Purnomo
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Journal : EMITTER International Journal of Engineering Technology

 1 
Stable Algorithm Based On Lax-Friedrichs Scheme for Visual Simulation of Shallow Water Bandung Arry Sanjoyo; Mochamad Hariadi; Mauridhi Hery Purnomo
EMITTER International Journal of Engineering Technology Vol 8 No 1 (2020)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v8i1.479

Abstract

Many game applications require fluid flow visualization of shallow water, especially dam-break flow. A Shallow Water Equation (SWE) is a mathematical model of shallow water flow which can be used to compute the flow depth and velocity. We propose a stable algorithm for visualization of dam-break flow on flat and flat with bumps topography. We choose Lax-Friedrichs scheme as the numerical method for solving the SWE. Then, we investigate the consistency, stability, and convergence of the scheme. Finally, we transform the strategy into a visualization algorithm of SWE and analyze the complexity. The results of this paper are: 1) the Lax-Friedrichs scheme that is consistent and conditionally stable; furthermore, if the stability condition is satisfied, the scheme is convergent; 2) an algorithm to visualize flow depth and velocity which has complexity O(N) in each time iteration. We have applied the algorithm to flat and flat with bumps topography. According to visualization results, the numerical solution is very close to analytical solution in the case of flat topography. In the case of flat with bumps topography, the algorithm can visualize the dam-break flow and after a long time the numerical solution is very close to the analytical steady-state solution. Hence the proposed visualization algorithm is suitable for game applications containing flat with bumps environments.
Towards Improvement of LSTM and SVM Approach for Multiclass Fall Detection System Herti Miawarni; Eko Setijadi; Tri Arief Sardjono; Wijayanti; Mauridhi Hery Purnomo
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.v10i1.639

Abstract

Telemonitoring of human physiological data helps detect emergency occurrences for subsequent medical diagnosis in daily living environments. One of the fatal emergencies in falling incidents. The goal of this paper is to detect significant incidents such as falls. The fall detection system is essential for human body movement investigation for medical practitioners, researchers, and healthcare businesses. Accelerometers have been presented as a practical, low-cost, and dependable approach for detecting and predicting outpatient movements in the user. The accurate detection of body movements based on accelerometer data enables the creation of more dependable systems for incorporating long-term development in physiological remarks. This research describes an accelerometer-based platform for detecting users' body movement when they fall. The ADXL345, MMA8451q, and ITG3200 body sensors capture activity data, subsequently classified into 15 fall incident classes based on SisFall dataset. Falling incidents classification is performed using Long Short-Term Memory results in best AUC-ROC value of 97.7% and best calculation time of 6.16 seconds. Meanwhile, Support Vector Machines results in the best AUC-ROC value of 98.5% and best calculation times of 17.05 seconds.
IRAWNET: A Method for Transcribing Indonesian Classical Music Notes Directly from Multichannel Raw Audio Dewi Nurdiyah; Eko Mulyanto Yuniarno; Yoyon Kusnendar Suprapto; Mauridhi Hery Purnomo
EMITTER International Journal of Engineering Technology Vol 11 No 2 (2023)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v11i2.827

Abstract

A challenging task when developing real-time Automatic Music Transcription (AMT) methods is directly leveraging inputs from multichannel raw audio without any handcrafted signal transformation and feature extraction steps. The crucial problems are that raw audio only contains an amplitude in each timestamp, and the signals of the left and right channels have different amplitude intensities and onset times. Thus, this study addressed these issues by proposing the IRawNet method with fused feature layers to merge different amplitude from multichannel raw audio. IRawNet aims to transcribe Indonesian classical music notes. It was validated with the Gamelan music dataset. The Synthetic Minority Oversampling Technique (SMOTE) overcame the class imbalance of the Gamelan music dataset. Under various experimental scenarios, the performance effects of oversampled data, hyperparameters tuning, and fused feature layers are analyzed. Furthermore, the performance of the proposed method was compared with Temporal Convolutional Network (TCN), Deep WaveNet, and the monochannel IRawNet. The results proved that proposed method almost achieves superior results in entire metric performances with 0.871 of accuracy, 0.988 of AUC, 0.927 of precision, 0.896 of recall, and 0.896 of F1 score.
Modified Deep Pattern Classifier on Indonesian Traditional Dance Spatio-Temporal Data Mulyanto, Edy; Yuniarno, Eko Mulyanto; Hafidz, Isa; Budiyanta, Nova Eka; Priyadi, Ardyono; Hery Purnomo, Mauridhi
EMITTER International Journal of Engineering Technology Vol 11 No 2 (2023)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v11i2.832

Abstract

Traditional dances, like those of Indonesia, have complex and unique patterns requiring accurate cultural preservation and documentation classification. However, traditional dance classification methods often rely on manual analysis and subjective judgment, which leads to inconsistencies and limitations. This research explores a modified deep pattern classifier of traditional dance movements in videos, including Gambyong, Remo, and Topeng, using a Convolutional Neural Network (CNN). Evaluation model's performance using a testing spatio-temporal dataset in Indonesian traditional dance videos is performed. The videos are processed through frame-level segmentation, enabling the CNN to capture nuances in posture, footwork, and facial expressions exhibited by dancers. Then, the obtained confusion matrix enables the calculation of performance metrics such as accuracy, precision, sensitivity, and F1-score. The results showcase a high accuracy of 97.5%, indicating the reliable classification of the dataset. Furthermore, future research directions are suggested, including investigating advanced CNN architectures, incorporating temporal information through recurrent neural networks, exploring transfer learning techniques, and integrating user feedback for iterative refinement of the model. The proposed method has the potential to advance dance analysis and find applications in dance education, choreography, and cultural preservation.
Improving 3D Human Pose Orientation Recognition Through Weight-Voxel Features And 3D CNNs Riansyah, Moch. Iskandar; Putra, Oddy Virgantara; Rahmanti, Farah Zakiyah; Priyadi, Ardyono; Wulandari, Diah Puspito; Sardjono, Tri Arief; Yuniarno, Eko Mulyanto; Hery Purnomo, Mauridhi
EMITTER International Journal of Engineering Technology Vol 13 No 1 (2025)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v13i1.847

Abstract

Preprocessing is a widely used process in deep learning applications, and it has been applied in both 2D and 3D computer vision applications. In this research, we propose a preprocessing technique involving weighting to enhance classification performance, incorporated with a 3D CNN architecture. Unlike regular voxel preprocessing, which uses a zero-one (binary) approach, adding weighting incorporates stronger structural information into the voxels. This method is tested with 3D data represented in the form of voxels, followed by weighting preprocessing before entering the core 3D CNN architecture. We evaluate our approach using both public datasets, such as the KITTI dataset, and self-collected 3D human orientation data with four classes. Subsequently, we tested it with five 3D CNN architectures, including VGG16, ResNet50, ResNet50v2, DenseNet121, and VoxNet. Based on experiments conducted with this data, preprocessing with the 3D VGG16 architecture, among the five architectures tested, demonstrates an improvement in accuracy and a reduction in errors in 3D human orientation classification compared to using no preprocessing or other preprocessing methods on the 3D voxel data. The results show that the accuracy and loss in 3D object classification exhibit superior performance compared to specific preprocessing methods, such as binary processing within each voxel.
Co-Authors Abdillah, Abid Famasya Adhi Dharma Wibawa Adhi Dharma Wibawa Adhi Dharma Wibawa, Adhi Dharma Adhi Kusmantoro Adi Soeprijanto Adi Soeprijanto Adi Soepriyanto Adi Sutanto Adri Gabriel Sooai Adriel Ferdianto Afandi, Acxel Derian Affan, Lazuardi Yaqub Agung Dewa Bagus Soetiono Agung Mega Iswara Agung Wicaksono Agus Dharma Agustinus Bimo Gumelar Ahmad Muslich Al Kindhi, Berlian Alamsyah Alamsyah - Alfiyan Alfiyan, Alfiyan Ali Sofyan Kholimi Amirullah Amirullah Amrul Faruq Ananto Mukti Wibowo Andi Setiawan Andreas Agung Kristanto, Andreas Agung Ardyono Pribadi Ardyono Priyadi Ardyono Priyadi Arham Arham, Arham Arif Muntasa Arifin Arifin Arik Kurniawati Aris Nasuha Aris Widayati Arman Jaya Arraziqi, Dwi Artwodini Muqtadiroh, Feby Aryo Nugroho Atris Suyantohadi Atris Suyantohadi Atyanta Nika Rumaksari Atyanta. N. Rumaksari Bambang Purwahyudi Bambang Sujanarko Bambang Suprianto . Bandung Arry Sanjoyo Basuki, Setio Berlian Al Kindhi Bernaridho Hutabarat, Bernaridho Budi Setiyono Budiarti, Rizqi Putri Nourma Cahyadi, Billy Kelvianto Chastine Fatichah Choirina, Priska Darma Setiawan Putra Dedid Cahya Happyanto Dewi Nurdiyah Diah Puspito Wulandari Diana Purwitasari Djoko Purwanto Dwi F. Suyatno Eddy Satriyanto Effendy Hadi Sutanto Eka Dwi Nurcahya Eko M. Yuniarno Eko Mulyanto Eko Mulyanto Yuniarno Eko Mulyanto Yuniarno Elly Purwanti Endang Setyati Endang Sri Rahayu Endi Permata Era Purwanto Esther Irawati Setiawan Evi Septiana Pane Evi Septiana Pane, Evi Septiana F.X. Ferdinandus Fahmi Amiq Fanani, Nurul Zainal Farah Zakiyah Rahmanti Fath, Nifty Feby Artwodini Muqtadiroh Fendik Eko P Fujisawa, Kimiya Gigih Prabowo Glanny M.Christiaan Mangindaan Gregorius Satio Budhi Gunawan Gunawan Gunawan Gunawan H. Hammad, Jehad A. Hans Juwiantho Hardianto Wibowo Hasti Afianti Hendra Kusuma Hermawan, Norma Herti Miawarni Hidayatillah, Rumaisah Hindarto Husna, Farida Amila Hutama Harsono, Nathanael I Ketut Eddy Purnama I Ketut Edy Purnama I Made Gede Sunarya I Made Ginarsa I Nyoman Budiastra Ima Kurniastuti Imam Robandi Iman Fahruzi Indah Agustien Sirajudin Indar Sugiarto Ingrid Nurtanio Isa Hafidz Iwan Setiawan Jehad A. H. Hammad Joan Santoso Joko Pitono Joko Priambodo Juanita, Safitri Ketut Eddy Purnama Khairuddin Karim Khamid Khamid Khamid Khamid Kristian, Yosi Lailatul Husniah Laksana, Eka Purwa Lie Jasa Lilik Anifah Lukman Zaman Lystianingrum, Vita Makoto Chiba Margareta Rinastiti Margo Pujiantara Marselin Jamlaay Marsetio Pramono Meidhy Panginda Saputra Moch Hariadi Moch. Hariadi Moch. Iskandar Riansyah Mochamad Ashari Mochamad Hariadi Mochammad Facta Mochammad Hariadi Moh. Aries Syufagi Mohammad Arie Reza Muhamad Ashari Muhamad Haddin Muhammad Nur Alamsyah Muhammad Reza Pahlawan Muhammad Rivai Muhtadin Mukhammad Aris Muldi Yuhendri Mulyanto, Edy Nazarrudin, Ahmad Ricky Nova Eka Budiyanta Nova Rijati Nugroho, Supeno Nugroho, Supeno Mardi S. Nur Kasan, Nur Nurul Fadillah Nurul Zainal Fanani Oddy Virgantara Putra Ontoseno Penangsang Pratama, Afis Asryullah Priambodo, Joko Prima Kristalina Purnawan, I Ketut Adi Purwadi Agus Darwito Putra Wisnu AS R Dimas Adityo Rachmad Setiawan Radi Radi Rafly Azmi Ulya, Amik Rahmat Rahmat Rahmat Syam Raihan, Muhammad Ratna Ika Putri Rika Rokhana Rima Tri Wahyuningrum Rima Tri Wahyuningrum Riris Diana Rachmayanti Rohmat rohmat Rokhana, Rika Rumaisah Hidayatillah Ruri Suko Basuki Rusmono Yulianto Saidah Saidah Saputra, Daniel Gamaliel Sartana, Bruri Trya SATO Yukihiko Setiawan, Esther Setijadi, Eko Shanti Wulansari Sidharta, Bayu Adjie Sihombing, Drigo Alexander Sirait, Rummi Santi Rama Siti Rochimah Soebagio Soebagio Soebagio Soebagio Soebagio Soebagio Soebagio Soebagio Soetiono, Agung Dewa Bagus Subagio subagio Subuh Isnur Haryudo Sugiyanto - Sujono Sujono Sujono Sulistyono, Marcelinus Yosep Teguh Sumadi, Fauzi Dwi Setiawan Supeno M. S. Nugroho Supeno Mardi Supeno Mardi S. Nugroho Supeno Mardi Susiki Nugroho, Supeno Mardi Surya Sumpeno Sutedjo Sutedjo Syafaah, Lailis Syaiful Imron Tita Karlita Tita Karlita Tri Arief Sardjono Tsuyoshi Usagawa, Tsuyoshi Ulla Delfana Rosiani Umar Umar Vita Lystianingrum Widodo Budiharto Wijayanti . Wiratmoko Yuwono Wiwik Anggraeni Wridhasari Hayuningtyas Yani Prabowo Yodik Iwan Herlambang Yosi Kristian Yoyon Kusnendar Suprapto Yuhana, Umi Laili Yulianto Tejo Putranto Yuni Yamasari Yuniarno, Eko M. Yusron rijal Zaimah Permatasari Zaman, Lukman