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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Informatics (IJEEI) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JURNAL NASIONAL TEKNIK ELEKTRO JURNAL INTEGRASI Journal of Community Service and Empowerment Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam Engagement: Jurnal Pengabdian Kepada Masyarakat
Eko Rudiawan Jamzuri
Department Of Electrical Engineering, Politeknik Negeri Batam, Indonesia
Religion Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Mechanical Engineering Social Sciences Other

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Desain Sistem Pengatur Lampu Lalu Lintas dengan Identifikasi Kepadatan Kendaraan Menggunakan Metode Subtraction Djavendra, Geminiesty Lathifasari; Aisyah, Siti; Jamzuri, Eko Rudiawan
JURNAL NASIONAL TEKNIK ELEKTRO Vol 7, No 2: July 2018
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (486.647 KB) | DOI: 10.25077/jnte.v7n2.541.2018

Abstract

The increasing number of vehicle causes the increasing of traffic density in which one of the main factors of congestion. Traffic density is usually alocated at certain points of roads, one at the instersection. In the novel technology, traffic in the crossroads had been controlled by traffic light using a traffic density prediction system. This prediction system would determine the duration of  active green lights and red lights at each intersection. One of the most common prediction systems is a statistical estimation of vehicle density. Other method at controlling traffic density such as visually monitoring system might be implemented to increase system performance. Therefore, this research proposes an automatically traffic control system by predicting traffic density using image processing techniques. The proposed system is using a camera to visually monitor traffic condition. The image data obtained from the camera would be processed using an image processing and background subtraction techniques. This technique compared an the captured-image with a reference image to result a subtracted-image depicted the traffic density which is represented by the number of white pixels. Based on the number of white pixels that have been obtained, the percentage of vehicle queue length and vehicle density can be determine. The percentage then sent to the microcontroller in order to control the duration of the active green light. The traffic light control system using traffic density calculation has an accuracy of up to 77.03% while using the calculation of vehicle queue length reached 91.18%.Keywords : Image processing, image subtraction, light control system, traffic density, dilation, erosionAbstrakBertambahnya jumlah kendaraan menyebabkan meningkatnya kepadatan lalu lintas yang menjadi salah satu faktor utama penyebab kemacetan. Kepadatan lalu lintas biasanya teralokasi di beberapa titik-titik tertentu di ruas jalan, salah satunya di persimpangan. Saat ini lalu lintas di persimpangan jalan diatur oleh lampu lalu lintas menggunakan sistem prediksi kepadatan lalu lintas. Sistem prediksi ini nantinya akan menentukan lama aktifnya lampu hijau dan lampu merah di setiap persimpangan. Salah satu sistem prediksi yang banyak digunakan adalah metode estimasi stastistik kepadatan kendaraan. Metode lain pengontrolan kepadatan lalu lintas seperti sistem pemantauan secara visual memungkinkan untuk diterapkan guna menambah performansi sistem. Untuk itu penelitian ini mengusulkan pembuatan sebuah sistem pengontrolan lampu lalu lintas secara otomatis dengan prediksi kepadatan kendaraan menggunakan teknik pengolahan citra. Sistem yang dibangun menggunakan kamera untuk memantau kondisi kendaraan di jalan raya. Data gambar yang didapat dari kamera kemudian diolah menggunakan teknik pengolahan citra dan teknik pengurangan citra. Teknik ini membandingkan citra objek dengan citra referensi sehingga dapat diketahui jumlah piksel putih pada citra hasil pengurangan citra. Berdasarkan jumlah piksel putih yang telah diperoleh tersebut dapat diketahui persentase panjang antrian kendaraan dan kepadatan kendaraan. Data persentase yang diperoleh kemudian dikirim ke mikrokontroler untuk mengontrol durasi nyala lampu hijau. Pengontrolan lampu lalu lintas dengan perhitungan kepadatan kendaraan memiliki akurasi hingga 77.03% sedangkan dengan perhitungan panjang antrian kendaraan mencapai 91.18%. Kata Kunci : Pengolahan citra, pengurangan citra, sistem kontrol lampu, kepadatan kendaraan, dilation, erosion
A Fast and Accurate Object Detection Algorithm on Humanoid Marathon Robot Eko Rudiawan Jamzuri; Hanjaya Mandala; Jacky Baltes
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (957.107 KB) | DOI: 10.52549/ijeei.v8i1.1960

Abstract

This paper introduces a fast and accurate object detection algorithm based on a convolutional neural network for humanoid marathon robot applications. The algorithm is capable of operating on a low-performance CPU without relying on the GPU or hardware accelerator. A new region proposal algorithm, based on color segmentation, is proposed to extract a region containing a potential object. As a classifier, the convolution neural network is used to predict object classes from the proposed region. In the training phase, the classifier is trained with an Adam optimizer to minimize the loss function, using datasets collected from humanoid marathon competitions and diversified using image augmentation. An NVIDIA GTX 1070 training machine, with 500 batch images per epoch and a learning rate of 0.001, required 12 seconds to minimize the loss value below 0.0374. In the accuracy evaluation, the proposed method successfully recognizes and localizes three classes of marker with a training accuracy of 99.929%, validation accuracy of 99.924%, and test accuracy of 98.821%. As a real-time benchmark, the algorithm achieves 41.13 FPS while running on a robot computer with Intel i3-5010U CPU @ 2.10GHz.
Desain Sistem Pengatur Lampu Lalu Lintas dengan Identifikasi Kepadatan Kendaraan Menggunakan Metode Subtraction Geminiesty Lathifasari Djavendra; Siti Aisyah; Eko Rudiawan Jamzuri
JURNAL NASIONAL TEKNIK ELEKTRO Vol 7, No 2: July 2018
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (486.647 KB) | DOI: 10.25077/jnte.v7n2.541.2018

Abstract

The increasing number of vehicle causes the increasing of traffic density in which one of the main factors of congestion. Traffic density is usually alocated at certain points of roads, one at the instersection. In the novel technology, traffic in the crossroads had been controlled by traffic light using a traffic density prediction system. This prediction system would determine the duration of  active green lights and red lights at each intersection. One of the most common prediction systems is a statistical estimation of vehicle density. Other method at controlling traffic density such as visually monitoring system might be implemented to increase system performance. Therefore, this research proposes an automatically traffic control system by predicting traffic density using image processing techniques. The proposed system is using a camera to visually monitor traffic condition. The image data obtained from the camera would be processed using an image processing and background subtraction techniques. This technique compared an the captured-image with a reference image to result a subtracted-image depicted the traffic density which is represented by the number of white pixels. Based on the number of white pixels that have been obtained, the percentage of vehicle queue length and vehicle density can be determine. The percentage then sent to the microcontroller in order to control the duration of the active green light. The traffic light control system using traffic density calculation has an accuracy of up to 77.03% while using the calculation of vehicle queue length reached 91.18%.Keywords : Image processing, image subtraction, light control system, traffic density, dilation, erosionAbstrakBertambahnya jumlah kendaraan menyebabkan meningkatnya kepadatan lalu lintas yang menjadi salah satu faktor utama penyebab kemacetan. Kepadatan lalu lintas biasanya teralokasi di beberapa titik-titik tertentu di ruas jalan, salah satunya di persimpangan. Saat ini lalu lintas di persimpangan jalan diatur oleh lampu lalu lintas menggunakan sistem prediksi kepadatan lalu lintas. Sistem prediksi ini nantinya akan menentukan lama aktifnya lampu hijau dan lampu merah di setiap persimpangan. Salah satu sistem prediksi yang banyak digunakan adalah metode estimasi stastistik kepadatan kendaraan. Metode lain pengontrolan kepadatan lalu lintas seperti sistem pemantauan secara visual memungkinkan untuk diterapkan guna menambah performansi sistem. Untuk itu penelitian ini mengusulkan pembuatan sebuah sistem pengontrolan lampu lalu lintas secara otomatis dengan prediksi kepadatan kendaraan menggunakan teknik pengolahan citra. Sistem yang dibangun menggunakan kamera untuk memantau kondisi kendaraan di jalan raya. Data gambar yang didapat dari kamera kemudian diolah menggunakan teknik pengolahan citra dan teknik pengurangan citra. Teknik ini membandingkan citra objek dengan citra referensi sehingga dapat diketahui jumlah piksel putih pada citra hasil pengurangan citra. Berdasarkan jumlah piksel putih yang telah diperoleh tersebut dapat diketahui persentase panjang antrian kendaraan dan kepadatan kendaraan. Data persentase yang diperoleh kemudian dikirim ke mikrokontroler untuk mengontrol durasi nyala lampu hijau. Pengontrolan lampu lalu lintas dengan perhitungan kepadatan kendaraan memiliki akurasi hingga 77.03% sedangkan dengan perhitungan panjang antrian kendaraan mencapai 91.18%. Kata Kunci : Pengolahan citra, pengurangan citra, sistem kontrol lampu, kepadatan kendaraan, dilation, erosion
Plant Integrity Monitoring Menggunakan Ultrasonic dengan Metode Fuzzy Decision Support Berbasis Wireless Sumantri Kurniawan Risandriya; Eko Rudiawan; Wahyu Wibowo
JURNAL INTEGRASI Vol 7 No 1 (2015): Jurnal Integrasi - April 2015
Publisher : Politeknik Negeri Batam

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

Abstract

Melakukan pengukuran ketebalan pipa dengan ultrasonic thickness gauging biasanya dilakukan dengan cara manual dengan bantuan operator produksi atau teknisi. Dalam hal ini jika terdapat area yang berbahaya misalnya tegangan tinggi, tempat terbatas, kandungan bahan kimia, udara berpolusi, dan bahaya lainnya, maka akan mengalami kesulitan terhadap operator atau teknisi tersebut untuk melakukan monitoring secara manual. Maka untuk itu diperlukan sistem yang dapat melakukan monitoring terhadap benda kerja yang diukur dan dilakukan peletakkan secara tetap atau permanen. Untuk pengambilan data bisa dilakukan dengan cara nirkabel atau wireless dengan menggunakan sinyal wifi yang telah dihubungkan dengan microcontroller arduino. Sehingga operator atau teknisi akan mudah dalam pengambilan dan analisa data. Untuk analisa data dari pembacaan sensor ultrasonik, sensor suhu, dan sensor kelembaban yang telah diambil datanya melalui jaringan nirkabel, maka diperlukan analisa lebih lanjut. Untuk analisa tersebut maka digunakan metode RBI (Risk Based Inspection) sebagai parameter acuan range kriteria. Dan kemudian menggunakan logika fuzzy dengan decision support system atau sistem penunjang keputusan.Dari hasil analisa tersebut maka kita bisa mendapatkan tingkat laju korosi, remaining life (tingkat ketahaan material), kapan melakukan inspeksi atau maintenance, tingkat keringanan atau beratnya bahaya, dan lain lainnya.
Workshop Teknologi Robotika untuk Anak Usia 8-15 Tahun di Kota Batam Indra Hardian Mulyadi; Senanjung Prayoga; Rifqi Amalya Fatekha; Hendawan Soebhakti; Eko Rudiawan Jamzuri; Lindawani Siregar; Heru Wijanarko; Eka Mutia Lubis; Ika Karlina Laila Nur Suciningtyas; Vivin Oktowinandi; Ridwan Ridwan; Fitriyanti Nakul; Budi Sugandi
Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam Vol 4 No 2 (2022): Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/abdimaspolibatam.v4i2.4807

Abstract

The Covid-19 pandemic requires elementary and junior high school students to do online learning activities at home. In practice, children interact more often with their gadget during online school hours and outside these hours. Its a concern for most Graha Nusa Batam community residents because the children there are already starting to have symptoms of gadget addiction. Against this background, Batam State Polytechnic (Polibatam) held a robotics technology workshop program for children aged 8-15 years. This activity aims to increase children's understanding of robotics technology, which includes electronics and mechanics. In addition, this activity provides several benefits, namely: being an attractive alternative for children to reduce playing with their gadgets; provide children's experiences in problem solving, creativity and collaboration; and include field experience for Polibatam students by applying the knowledge gained through Project Based Learning (PBL) for the benefit of the community.This workshop held four meetings (March to April 2021) at the At-Taqwa Al-Qur'an Education Park (TPA) building, Graha Nusa Batam housing. The robot used is an analog line follower. Pre-test and post-test were conducted to measure the increase in participants' understanding of the material. This test shows that participants' knowledge of robotics technology can increase up to 25% for participants aged 8-11 years and 22% for 12-15 years.
Automatic optical inspection for detecting keycaps misplacement using Tesseract optical character recognition Anisatul Munawaroh; Eko Rudiawan Jamzuri
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5147-5155

Abstract

This research study aims to develop automatic optical inspection (AOI) for detecting keycaps misplacement on the keyboard. The AOI hardware has been designed using an industrial camera with an additional mechanical jig and lighting system. Optical character recognition (OCR) using the Tesseract OCR engine is the proposed method to detect keycaps misplacement. In addition, captured images were cropped using a predefined region of interest (ROI) during the setup. Subsequently, the cropped ROIs were processed to acquire binary images. Furthermore, Tesseract processed these binary images to recognize the text on the keycaps. Keycaps misplacement could be identified by comparing the predicted text with the actual text on the golden sample. Experiments on 25 defects and 25 non-defected samples provided a classification accuracy of 97.34%, a precision of 100%, and a recall of 90.70%. Meanwhile, the character error rate (CER) obtained from the test on a total of 57 characters provided a performance of 10.53%. This outcome has implications for developing AOI for various keyboard products. In addition, the precision level of 100% signifies that the proposed method always offers correct results in detecting product defects. Such outcomes are critical in industrial applications to prevent defective products from circulating in the market.
Tiny-YOLO distance measurement and object detection coordination system for the BarelangFC robot Susanto Susanto; Jony Arif Ricardo Silitonga; Riska Analia; Eko Rudiawan Jamzuri; Daniel Sutopo Pamungkas
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i6.pp6926-6939

Abstract

A humanoid robot called BarelangFC was designed to take part in the Kontes Robot Indonesia (KRI) competition, in the robot coordination division. In this division, each robot is expected to recognize its opponents and to pass the ball towards a team member to establish coordination between the robots. In order to achieve this team coordination, a fast and accurate system is needed to detect and estimate the other robot’s position in real time. Moreover, each robot has to estimate its team members’ locations based on its camera reading, so that the ball can be passed without error. This research proposes a Tiny-YOLO deep learning method to detect the location of a team member robot and presents a real-time coordination system using a ZED camera. To establish the coordinate system, the distance between the robots was estimated using a trigonometric equation to ensure that the robot was able to pass the ball towards another robot. To verify our method, real-time experiments was carried out using an NVDIA Jetson NX Xavier, and the results showed that the robot could estimate the distance correctly before passing the ball toward another robot.
Robotics training to improve STEM skills of Islamic boarding school students in Batam Eko Rudiawan Jamzuri; Hendawan Soebhakti; Senanjung Prayoga; Rifqi Amalya Fatekha; Anugerah Wibisana; Fitriyanti Nakul; H. Hasnira; Riska Analia; S. Susanto; Ryan Satria Wijaya; Ika Karlina Laila Nur Suciningtyas; Widya Rika Puspita; Eka Mutia Lubis; Adlian Jefiza; B. Budiana; Ahmad Riyad Firdaus
Journal of Community Service and Empowerment Vol. 5 No. 1 (2024): April
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/jcse.v5i1.26895

Abstract

One potential approach to addressing the challenges posed by the advent of Industry 4.0 and Society 5.0 is to offer robotics training. This endeavor aims to enhance students' foundational understanding of STEM (Science, Technology, Engineering, and Mathematics) disciplines. The study involved collaborating with the Pondok Pesantren Granada, an Islamic Boarding School located in Batam, to provide robotics training as community service activities. The study included 29 trainees: 15 from class XI and 7 from classes X and XII. The teaching was conducted using a combination of didactic instruction, interactive discourse, and hands-on exercises. Trainees are administered a written examination to assess their proficiency level before and after the training program. The training outcomes exhibited a significant improvement in the mean STEM proficiency of trainees, with an increase of 38.15%. Furthermore, a series of activities have been effectively implemented, resulting in trainee satisfaction ratings exceeding 50% concerning course materials, trainer, and teaching equipment. A mere 17% of the individuals undergoing training expressed dissatisfaction with the allocated time, particularly the hands-on component's duration.
Improving STEM Capability of Islamic Boarding School Students in Batam Through Robotics Training Hendawan Soebhakti; Eko Rudiawan Jamzuri; Senanjung Prayoga; Rifqi Amalya Fatekha; Anugerah Wibisana; Susanto Susanto; Riska Analia; Fitriyanti Nakul; Adlian Jefiza; Eka Mutia Lubis; Budiana Budiana; Ika Karlina Laila Nur Suciningtyas; Ahmad Riyad Firdaus
Engagement: Jurnal Pengabdian Kepada Masyarakat Vol 7 No 2 (2023): November 2023
Publisher : Asosiasi Dosen Pengembang Masyarajat (ADPEMAS) Forum Komunikasi Dosen Peneliti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/engagement.v7i1.1350

Abstract

Conducting robotics training as a community service to improve basic knowledge of Science, Technology, Engineering, and Mathematics (STEM) for students is one of the ways to improve their basic knowledge of Science, Technology, Engineering, and Mathematics (STEM) for students is one of the most important aspects of the facing the industrial era 4.0 and society 5.0. Through the Service-Learning approach, this community service by collaborating with Granada International in Batam by involving 29 students, consisting of 7 students from class X, 15 students from class XI, and the rest from class XII, class XI students, and the rest from class XII. The results of mentoring through robotics training were able to increase the average STEM skills of students by 38.15%. In addition, the activity was successfully implemented with participant satisfaction levels above 50% for the subject matter, instructor, and training equipment. Only 17% of the trainees stated that the training time was insufficient, especially for practicum.
Object Detection and Pose Estimation with RGB-D Camera for Supporting Robotic Bin-Picking EKO RUDIAWAN JAMZURI; RISKA ANALIA; SUSANTO SUSANTO
Jurnal Elkomika Vol 11, No 1 (2023): ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektr
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v11i1.128

Abstract

ABSTRAKTujuan dari penelitian ini adalah untuk mendeteksi objek dan mengestimasi pose objek menggunakan kamera RGB-D. Dalam penelitian ini, kami mengusulkan pemrosesan data pada citra RGB dan citra depth saja, tanpa menggunakan point cloud, seperti pada umumnya. Metode yang diusulkan mendeteksi posisi dan orientasi objek menggunakan DRBox-v2 dari Region of Interest (ROI), yang sebelumnya diperoleh dari pendeteksian pada penanda ArUco. Hasil deteksi objek kemudian diskalakan dan digunakan pada citra depth untuk mendapatkan perkiraan posisi dan orientasi objek. Dari sisi pendeteksi objek, usulan metode memperoleh nilai Average Precision (AP) sebesar 0,740. Sedangkan untuk estimator pose, usulan metode menghasilkan kesalahan posisi rata-rata 13,36 mm dan kesalahan orientasi rata-rata 0,75 derajat. Metode yang diusulkan berpotensi menjadi alternatif sistem deteksi objek dan estimasi pose pada kamera RGB-D yang tidak memerlukan pemrosesan point cloud dan tidak memerlukan model referensi objek.Kata kunci: deteksi objek, estimasi pose, DRBox, ArUco, bin-picking ABSTRACTThis study aims to detect objects and estimate the object's pose using an RGB-D camera. In this study, we proposed data processing on RGB images and depth images only, without using point clouds, as in general. The proposed method detected the object's position and orientation using the DRBox-v2 from the Region of Interest (ROI), which was previously obtained from detecting ArUco markers. The object detection results were then scaled and used in the depth image to get the object's approximate position and orientation. In object detection, the proposed method obtained an Average Precision (AP) value of 0.740. As for the pose estimator, our method generated an average position error of 13.36 mm and an average orientation error of 0.75 degrees. Therefore, this method can be an alternative object detection and pose estimation system on an RGB-D camera that does not require point cloud processing and an object reference model.Keywords: object detection, pose estimation, DRBox, ArUco, bin-picking
Co-Authors Adlian Jefiza Adlian Jefiza Ahmad Riyad Firdaus Ahmad Riyad Firdaus Anisatul Munawaroh Anugerah Wibisana Anugerah Wibisana B. Budiana Budi Sugandi Budiana Budiana Daniel Sutopo Pamungkas Eka Mutia Lubis Eka Mutia Lubis Eka Mutia Lubis Fatekha, Rifqi Amalya Fitriyanti Nakul Fitriyanti Nakul Fitriyanti Nakul Geminiesty Lathifasari Djavendra H. Hasnira Hanjaya Mandala Hendawan Soebhakti Hendawan Soebhakti Hendawan Soebhakti Heru Wijanarko Ika Karlina Laila Nur Suciningtyas Ika Karlina Laila Nur Suciningtyas Jacky Baltes Jony Arif Ricardo Silitonga Lindawani Siregar Mulyadi, Indra Hardian Prayoga, Senanjung Ridwan Ridwan Rifqi Amalya Fatekha Rifqi Amalya Fatekha Riska Analia Riska Analia Ryan Satria Wijaya S. Susanto Senanjung Prayoga Siti Aisyah Sumantri Kurniawan Risandriya Susanto Susanto Vivin Oktowinandi Wahyu Wibowo Widya Rika Puspita