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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electronics and Instrumentation Systems Jurnal Ilmu Dasar TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Journal of Engineering and Technological Sciences Proceeding of the Electrical Engineering Computer Science and Informatics Journal of Mechanical Engineering Science and Technology Jurnal Elektronika dan Telekomunikasi JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Jurnal Rekayasa elektrika
Anam, Khairul
Department Of Electrical Engineering, Universitas Jember
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering

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Robot Beroda Pendeteksi Gas Karbon Monoksida dan Metana Berbasis IoT Menggunakan Metode Finite State Machine dan Fuzzy Logic Wira Adi Winata; Khairul Anam; Ali Rizal Chaidir
Jurnal Rekayasa Elektrika Vol 18, No 1 (2022)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v18i1.24485

Abstract

Occupational Safety and Health (K3) is an important requirement needed in mining. This is because activities in mining have great risks and are associated with unpredictable natural conditions. One of them is the leakage of hazardous gas at the mine site caused by mining activities. This article proposes a wheeled robot to detect carbon monoxide gas and methane gas based on the Internet of Things (IoT) using Finite State Machine (FSM) and Fuzzy Logic. The finite state machine (FSM) in this study is used as a control of the robot’s movement, while fuzzy logic is used as a safety classification of the readable state of dangerous gases. The results showed that the system was capable of detecting gas and the information is successfully sent to a web server. In addition, the use of lidar can detect obstacles around the robot.  
Rancang Bangun Sistem Navigasi Robot Beroda Pemandu Disabilitas Netra Menggunakan Metode Waypoint Ahmad Rausan Fikri; Khairul Anam; Widya Cahyadi
Jurnal Rekayasa Elektrika Vol 16, No 3 (2020)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v16i3.15711

Abstract

Robotics has become a popular field of research for developing medical and human aids, including visually impaired people. This paper presents problem-solving of creating a robot that can guide visually impaired people outdoor using a Global Positioning System (GPS)-based navigation system with a waypoint method. This study uses Linkit ONE, which is equipped with a GPS as a determinant of the earth’s ordinate position, added with a compass module to determine the robot’s direction and a rotary encoder sensor to minimize the error of the robot’s position. There are two tests with four waypoints. Firstly, it is a test with no obstacles and holes. Secondly, it is the test with obstacles and holes. The first test results obtained an average error of waypoint-1 0.54 m(meters), waypoint-2 1.2 m, waypoint-3 1,9 m, and waypoint-4 1.7 m. Meanwhile, the second test results yielded an average error of waypoint-1 1.26 m, waypoint-2 2.18 m, waypoint-3 2.52 m, and waypoint-4 2,44 m. Therefore, the visual disability guidance robot with this waypoint method has good accuracy because the average error value of the robot is under a radius of 2 m when there are no obstacles and holes and under a radius of 3 m when there are obstacles and holes. 
Evaluation Of Inverse Kinematics For Quadruped Robot With Accelerometer Sensor Ahmad Iqbal Nasrudin; Khairul Anam; M. Agung Prawira N
Jurnal Rekayasa Elektrika Vol 15, No 3 (2019)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v15i3.14079

Abstract

Quadruped robot is one of the types of robots that move using legs 4 compiled by some of the servo motor as a driving force on each foot ft the DOF is used. However, problems arise when this robot is confronted on the inclined plane, because the burden is borne out every servo motor on the feet will be different, so can make a fast servo motor damaged. This research was conducted on the design of the quadruped robot system for stability on the inclined plane using the accelerometer sensor and the application of the inverse kinematics method with PID control of Ziegler-Nichols. The results of tests obtained response robots in stabilizing the body when faced with the inclined plane with some degree of slope of the pitch and roll. In this research was conducted some test for quadruped robot: static Testing robot against the angel of the pitch in the standby retrieved response average robot in stabilizing the body is 245 ms, static Testing robot against the angle of roll in standby retrieved response average robot in stabilizing the body is 280 ms, dynamic Testing robot against the roll and pitch in standby retrieved response average robot in stabilizing the body is 8 seconds, Static Testing robot to stabilizing the body against the angel of roll in running the largest robot oscillations obtained 10 degrees, dynamic Testing robot to stabilizing the body against the angle of roll in run retrieved response average robot in stabilizing the body is 490 ms.
Sistem Navigasi Kursi Roda Elektrik untuk Pasien Penyandang Cacat Fisik Menggunakan Metode Convolutional Neural Network Sutikno Sutikno; Khairul Anam; Azmi Shaleh
Jurnal Rekayasa Elektrika Vol 17, No 1 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v17i1.16376

Abstract

Patients with physical disabilities, such as losing a leg or experiencing paralysis, will have difficulty moving from one place to another. As a result, they need someone or a device that can help them to move. One that is often used by patients is a wheelchair. This study proposes an electric wheelchair navigation system that can be controlled by voice commands using the Convolutional Neural Network (CNN) method. CNN is used as the main method for identifying commands embedded on the Raspberry Pi microcontroller. The recorded voice data is then converted to spectrogram images before being fed to CNN. This method is proven to be better in voice command recognition with an accuracy of above 90%. There are five different voice commands: forward, backward, left, right, and stop. Preliminary experimental results indicate that the electric wheelchair is able to move according to the commands given.
Pengendali Wireless Mobile Robot Arm (WMRA) Berdasarkan Gestur Lengan Menggunakan Sensor Accelerometer dan Logika Fuzzy Widya Cahyadi; Ali Rizal Chaidir; Azmy Akhyar Al Insani; Khairul Anam; Andrita Ceriana Eska
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 13, No 2 (2023): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.77125

Abstract

Telerobotik adalah sistem pengendali robot dalam jarak jauh yang membutuhkan campur tangan manusia sebagai operator (Human-in-the-Loop). Pada penelitian sebelumnya, mobile robot manipulator dikendalikan berdasarkan gestur jari operator melalui image processing menggunakan metode template matching dengan komunikasi melalui kabel. Sehingga pada penelitian selanjutnya, dibuat sistem kendali robot berdasarkan gestur lengan menggunakan sensor accelerometer dan logika fuzzy dengan komunikasi nirkabel melalui jaringan internet. Robot yang dikendalikan terdiri dari robot arm 2 dof dan robot non-holonomic dengan 4 roda. Sistem kendali robot terdiri dari 2 sensor accelerometer yang terpasang pada lengan operator. Juga terdapat sensor hall-effect sebagai kendali gerak gripper. Metode fuzzy sugeno diterapkan pada sistem kendali gerak mobile robot agar didapatkan respon robot yang dapat bergerak secara bebas berdasarkan gestur lengan operator. Berdasarkan analisa dan data pengujian didapatkan hasil bahwa robot dapat dikendalikan dengan cukup baik.
Feature Extraction Evaluation of Various Machine Learning Methods for Finger Movement Classification using Double Myo Armband Khairul Anam; Harun Ismail; Faruq Sandi Hanggara; Cries Avian; Safri Nahela; Muchamad Arif Hana Sasono
Journal of Engineering and Technological Sciences Vol. 55 No. 5 (2023)
Publisher : Directorate for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2023.55.5.8

Abstract

The deployment of electromyography (EMG) signals attracts many researchers since it can be used in decoding finger movements for exoskeleton robotics, prosthetics hand, and powered wheelchair. However, decoding any movement is a challenging task. The success of EMG signals' use lies in the appropriate choice of feature extraction and classification model, especially in the feature extraction process. Therefore, this study evaluates an eight-feature extraction evaluation on various machine learnings such as the Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Decision Tree (DT), Naïve Bayes (NB), and Quadratic Discriminant Analysis (QDA). The dataset from four intact subjects is used to classify twelve finger movements. Through 5 cross-validations, the result shows that almost all feature extractions combined with SVM outperform other combinations of features and classifiers. Mean Absolute Value (MAV) as a feature and SVM as a classifier highlight the best combination with an accuracy of 94.01%.
Navigation System of Electric Car with Faster R-CNN for Pediatric Patient Transportation Qoyima, Rosida Amalia Nurul; Kaloko, Bambang Sri; Anam, Khairul; Sasono, Muchamad Arif Hana; Efendi, Dicky Yusril
Jurnal ILMU DASAR Vol 26 No 1 (2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jid.v26i1.50186

Abstract

The use of electric cars as a means of transportation for pediatric patients has the main purpose of having a positive effect on the psychology of pediatric patients before surgery. Therefore, it is expected to accelerate the healing process. An electric car navigation system that can recognize the environment is needed. This article aims to develop a camera-based semi-autonomous navigation system using the faster R-CNN method to detect markers as electric car direction. This method optimizes the range of interest (RoI) layer to produce optimal features. Faster R-CNN is faster in generating accurate region proposals compared to R-CNN and Fast R-CNN. Various Faster R-CNN models were tested in image data processing for marker detection as the electric car steering system. Test results on FPS variations show that the best results were obtained when using the Faster R-CNN MobileNet V3 Large 320 FPN model with a value of 11.3f ps for the forward marker, 18.9 fps for the stop marker, 22.6 fps for the left turn marker and 11.1 fps for the right turn marker. With this model, the results obtained are quite good in testing the performance of the car navigation system. The results obtained in the success of the test are 70% for the forward marker test, 100% for the stop marker test, 90% for the left turn marker and 100% for the right turn marker.
Analysis of Titanium Mesh Ti6Al4V Formation Using Die Press Forming Machine for Cranioplasty Rizal, Ahmad Ayyub Syaiful; Darsin, Mahros; Wibowo, Robertoes Koekoeh K.; Anam, Khairul
Journal of Mechanical Engineering Science and Technology (JMEST) Vol 8, No 2 (2024)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um016v8i22024p445

Abstract

Cranioplasty is required for patients with head defects, where the deformed part of the head is replaced with Ti6Al4V titanium wire implants. The titanium wire forming process is usually done manually, which can take a long time and give results that do not match the anatomical shape of the head. Therefore, it is important to develop domestic technology that can produce titanium wire automatically. This study aims to analyze the frame and mold of the automatic wire mesh molding machine before production. The tool is made using press forming method and finite element analysis with ANSYS software. The machine frame is made of 304 stainless steel material, while the mold uses ABS material. The analysis was performed with a constant load force of 100 N, corresponding to the maximum reading on the load cell. The simulation results show the deformation, strain, and von Mises stress of the machine frame and punch model, which are still far below the plastic deformation and UTS values of the material. However, the analysis results on the Ti6Al4V titanium die and mesh exceeded the UTS of the material in the cutting edge area of the die. Nevertheless, the die model can still be used because the maximum stress point is located at the edge of the die design area, where the titanium mesh will be cut when applied to the patient's skull implant. The results of this study are expected to help medical personnel in skull implant surgery and analysis of press machine manufacturing.
The Implementation of Mamdani Fuzzy Logic Control on a Hexapod Robot as a Guide for Visually Impaired People Prawira Negara, Mohamad Agung; Mulyadi, Fikri; Chaidir, Ali Rizal; Anam, Khairul
Jurnal Elektronika dan Telekomunikasi Vol 24, No 2 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.638

Abstract

The constraints faced by visually impaired individuals have spurred various human-created innovations to aid them. One such innovation is employing robots as guides for the blind. Numerous studies have delved into utilizing robots as guides for visually impaired individuals. Nevertheless, these robots still encounter limitations, particularly in navigating rough and uneven terrain. To tackle this issue, there's a necessity for a hexapod robot capable of traversing uneven surfaces more effectively than wheeled robots. The hexapod robot developed in this research is an autonomous robot that employs fuzzy logic as its control method. The resultant hexapod robot has showcased outstanding performance, attaining a 100% success rate in navigating the specified path and demonstrating a reliability of 79.78%.
Desain Algoritma Autonomous Deep Learning (ADL) untuk Sistem Kontrol Tangan Prostetis pada Disabilitas Widhi Winata Sakti; Siti Tsaniyatul Miratis Sulthoniyah; Donny Setiawan; Adi Mulyadi; Khairul Anam
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 6 No. 2 (2024): Desember 2024
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i2.14184

Abstract

Penyandang Disabilitas (ODD) memiliki risiko kemiskinan yang tinggi di Indonesia dan dianggap tidak produktif. Menurut data Badan Pusat Statistik (BPS), pada tahun 2019-2020, jumlah penyandang disabilitas di Indonesia mencapai lebih dari 28 juta orang. Tangan palsu telah menjadi solusi untuk membantu individu penyandang disabilitas meningkatkan kualitas hidupnya. Pemrosesan sinyal EEG untuk kontrol prostetik masih tergolong baru, dan diperlukan penelitian lebih lanjut untuk mengoptimalkan kinerja algoritma. diusulkan menggunakan desain algoritma Autonomous Deep Learning (ADL). Struktur jaringan dapat dibangun dari awal tanpa adanya pengaturan manual, mengingat kompleksitas jaringan saraf yang sering mengalami overfitting, model tidak efektif dalam klasifikasi. Hasil percobaan dari 6 subjek dengan rata-rata 96% dengan error 10% pada subjek mandiri
Co-Authors Adel Al-Jumaily Adel Al-Jumaily Adi Mulyadi Ahmad Adib Rosyadi Ahmad Iqbal Nasrudin Ahmad Rausan Fikri AHMADI, SOFYAN Al-Jumaily, Adel Ali Rizal Chaidir Andrita Ceriana Eska Azmi Saleh Azmi Shaleh Azmy Akhyar Al Insani Bambang Sri Kaloko Bambang Sujanarko Cries Avian Cries Avian Donny Setiawan Efendi, Dicky Yusril Faruq Sandi Hanggara Harun Ismail Ihsanul Azmi Kartika Senjarini M. Agung Prawira N Mahros Darsin Mohamad Agung Prawira Negara, Mohamad Agung Muchamad Arif Hana Sasono Muhammad Nuh Mulyadi, Fikri Qoyima, Rosida Amalia Nurul Rike Oktarianti Rizal, Ahmad Ayyub Syaiful Safri Nahela Sasono, Muchamad Arif Hana Siti Tsaniyatul Miratis Sulthoniyah Sutikno Sutikno Sutikno Sutikno Wibowo, Robertoes Koekoeh K. Widhi Winata Sakti Widya Cahyadi Wira Adi Winata