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All Journal International Journal of Electrical and Computer Engineering Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Majalah Ilmiah Teknologi Elektro 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 Nasional Teknik Elektro dan Teknologi Informasi Makara Journal of Technology Jurnal Rekayasa elektrika Majalah Ilmiah Teknologi Elektro
Mauridhi Hery Purnomo
EEPIS
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Other

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Self-Training Naive Bayes Berbasis Word2Vec untuk Kategorisasi Berita Bahasa Indonesia Joan Santoso; Agung Dewa Bagus Soetiono; Gunawan; Endang Setyati; Eko Mulyanto Yuniarno; Mochamad Hariadi; Mauridhi Hery Purnomo
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 (1455.318 KB)

Abstract

News as one kind of information that is needed in daily life has been available on the internet. News website often categorizes their articles to each topic to help users access the news more easily. Document classification has widely used to do this automatically. The current availability of labeled training data is insufficient for the machine to create a good model. The problem in data annotation is that it requires a considerable cost and time to get sufficient quantity of labeled training data. A semi-supervised algorithm is proposed to solve this problem by using labeled and unlabeled data to create classification model. This paper proposes semi-supervised learning news classification system using Self-Training Naive Bayes algorithm. The feature that is used in text classification is Word2Vec Skip-Gram Model. This model is widely used in computational linguistics or text mining research as one of the methods in word representation. Word2Vec is used as a feature because it can bring the semantic meaning of the word in this classification task. The data used in this paper consists of 29,587 news documents from Indonesian online news websites. The Self-Training Naive Bayes algorithm achieved the highest F1-Score of 94.17%.
Menuju Pengenalan Ekspresi Mikro: Pendeteksian Komponen Wajah Menggunakan Discriminative Response Map Fitting Ulla Delfana Rosiani; Priska Choirina; Surya Sumpeno; Mauridhi Hery Purnomo
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

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Abstract

The observations made in the study of micro-expression are to recognize and track the very subtle movements of certain facial areas and in a short time. In this study, the observation of movement is held in some areas of the face component. The facial and facial components detection is the pre-process stage on micro-expression recognition system. The goal at this stage is to get face and face components accurately and quickly on every movement of the video sequence or image sequence. The face landmark point of the Discriminative Response Map Fitting (DRMF) method can be used to get face components area accurately and quickly. This can be done because the facial landmark points used in this model-based method do not change when objects are moved, rotated, or scaled. The results obtained by using this method are accurate with a 100% accuracy value compared to the Haar Cascade Classifier method with an average accuracy of 44%. In addition, the average time required in the formation of facial component boxes for each frame is 0.08 seconds, faster than the Haar Cascade Classifier method of 0.32 seconds. With the results obtained, then the detection of facial components can be obtained accurately and quickly. Furthermore, the boxes of face components obtained are expected to display the appropriate data to be processed correctly and accurately in the next stage, feature extraction and the classification of micro-expression motion stage.
Penggalian Pola Kemampuan Peserta Ujian Berbasis Klaster untuk Penentuan Aturan Sistem Penilaian Umi Laili Yuhana; Eko M. Yuniarno; Supeno Mardi S. Nugroho; Siti Rochimah; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 4: November 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Determination of initial ability of examinees is one of the important stages in the adaptive assessment system. The accuracy of the examinee's ability level prediction will influence the appropriateness of choosen item difficulty level for each examinee. This paper discusses the patterns mining of cognitive ability based on cluster using K-Means. The K-means method is utilized to mine the examinees’ ability pattern from examinees’ pretest answers. The patterns are used for developing rules to determine examinee’s ability level in the adaptive assessment system. The addition of this method is proposed to improve the performance of the prediction methods to predict the examinees’ ability level. Extraction of graduation value at each level is done before the pattern excavation process. Patterns found become the basis of making the rules as well as replace the rules from the experts in previous studies. The prediction of participants' ability is done by implementing rule based method classifier. A total of 140 data were used for the experiment. Based on the results of the experiment, it can be concluded that the cluster-based pattern mining using K-means can be utilized to determine the cognitive ability level of examinee. The application of this method to student pretest data shows the performance improvement of all the prediction methods used in this paper, i.e. Naive Bayes, MLP, SMO, Decision Table, JRIP, and J48. This method is suitable for adaptive assessment system where the rules can be adjusted along with the addition of the number of the data as well as the addition of the number of variations in the ability pattern of examinees.
Meta-Algoritme Adaptive Boosting untuk Meningkatkan Kinerja Metode Klasifikasi pada Prestasi Belajar Mahasiswa Yuni Yamasari; Supeno M. S. Nugroho; Dwi F. Suyatno; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 3: Agustus 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Determining the right class on student achievement is important in an evaluation process, because placing students in the right class helps lecturer in reflecting the successfullness of learning process. This problem relates to the performance of classification method which is measured by the classifier metrics. High performance is indicated by the optimality of these classifier's metrics. Besides, meta-algorithm adaptive boosting has been proven to be able to improve the performance of classifier in various fields. Therefore, this paper employs adaptive boosting to reduce the number of incorrect student placement in a class. The experimental results of implementing adaptive boosting in classifying student achievement shows that there is an increase of performance of all classification metrics, i.e., Kappa, Precision, Recall, F-Measure, ROC, and MAE. In terms of accuracy, J-48 is able to rise about 3.09%, which means this method reduces three misclassified students. Additionally, decisionStump increases 12.37% of accuracy. This also means this method is able to decrease 12 misclassified students. Finally, Simple Cart reaches the highest accuracy of about 23.71%, while the number of misclassified students is reduced to 24 students. However, there is no improvement in Random Forest method by using this adaptive boosting.
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.
Analisis Kinerja Protokol Routing AODV, DSR, dan OLSR pada Mobile Ad hoc Network Berdasarkan Parameter Quality of Service Alamsyah Zakaria; Eko Setijadi; I Ketut Eddy Purnama; Mauridhi Hery Purnomo
Jurnal Rekayasa Elektrika Vol 14, No 3 (2018)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v14i3.9798

Abstract

MANET is autonomous, self-configured, and applicable to emergency locations such as forest fires, earthquakes, floods, and health monitoring. However, challenges and difficulties faced by the mobile ad-hoc network (MANET) is a dynamically built network system, without the support of infrastructure in communicating between one node and other nodes, and limited energy sources. To overcome MANET problems and to obtain optimal network quality, the selections of routing protocols and quality of service (QoS) are significant in MANET design. This study aims to analyze the performance of routing protocols: dynamic source routing (DSR), ad-hoc on demand distance vector (AODV) and optimized link state routing (OLSR) based on QoS. The analyzed QoS parameters include packet delivery ratio (PDR), packet loss, throughput, and delay. Simulation results using network simulator version based on the number of node densities indicate that OLSR has better performance compared to AODV and DSR regarding PDR, packet loss, throughput, and delay.
Potential Usage of Solar Energy as a Renewable Energy Source in Petukangan Utara, South Jakarta Eka Purwa Laksana; Yani Prabowo; Sujono Sujono; Rummi Sirait; Nifty Fath; Ardyono Priyadi; Mauridhi Hery Purnomo
Jurnal Rekayasa Elektrika Vol 17, No 4 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v17i4.22538

Abstract

Indonesia is a tropical country located on the equator. The average intensity of solar radiation in Indonesia is 4.8 kWh/m2. This makes Indonesia a country with new and ren ewable energy potential, one of which is solar panel technology. The first step that must be done in the process of installing solar panels in a place is to analyze the potential of solar energy. In this study, an analysis of the potential of solar energy as a new renewable energy source has been carried out at Budi Luhur University, North Petukangan, South Jakarta. Based on the research results, the maximum photovoltaic efficiency that can be achieved is 21.45%. During the day, the efficiency of the solar panels increases along with the ncrease in the value of the voltage obtained. However, the higher the panel temperature, the lower the efficiency of the solar panel. Therefore, a cooling system is needed to anticipate this.
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.
HiroPoseEstimation: A Dataset of Pose Estimation for Kid-Size Humanoid Robot Rafly Azmi Ulya, Amik; Hutama Harsono, Nathanael; Mulyanto Yuniarno, Eko; Hery Purnomo, Mauridhi
Journal of Information Technology and Computer Science Vol. 8 No. 3: December 2023
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202383568

Abstract

Pose estimation is a field of computer vision research that involves detecting, associating, and tracking data points on body parts. It is used for health monitoring, sign language understanding, human gesture control, elderly activities, sports, and humanoid robot pose estimation. The anatomy of a humanoid robot is similar to a human, which forms the basis for utilizing humanoid robot pose estimation. The Humanoid League is a major domain of the RoboCup competition, featuring soccer matches between humanoid robots. Pose estimation is used to measure the robot’s performance. Nevertheless, there have not been many research done on this subject. A new dataset model needs to be developed to solve the proposed problem. This work introduces HiroPoseEstimation, a kid-size humanoid robot dataset with several types of robots used in various poses based on movements in a soccer game. It is evaluated with both bottomup and top-down approaches using keypoint mask R-CNN and single-stage encoder-decoder model. Both methods demonstrate good performance on the proposed dataset.
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 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 Rokhana, Rika Rumaisah Hidayatillah Ruri Suko Basuki Rusmono Yulianto Saidah Saidah Saputra, Daniel Gamaliel Sartana, Bruri Trya SATO Yukihiko Setiawan, Esther Setijadi, Eko 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