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All Journal ComEngApp : Computer Engineering and Applications Journal JTEV (Jurnal Teknik Elektro dan Vokasional Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Emitor: Jurnal Teknik Elektro Annual Research Seminar JURNAL NASIONAL TEKNIK ELEKTRO Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jusikom : Jurnal Sistem Komputer Musirawas Dinamisia: Jurnal Pengabdian Kepada Masyarakat Journal of Information Technology and Computer Engineering KOMPUTIKA - Jurnal Sistem Komputer GERVASI: Jurnal Pengabdian kepada Masyarakat JTT (Jurnal Teknologi Terapan) Jurnal Teknologi Elekterika Jurnal Generic REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat J-Innovation Jurnal Fokus Elektroda (Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) Jurnal Rekayasa elektrika ABDIKOM Emitor: Jurnal Teknik Elektro
Kemahyanto Exaudi
Fakultas Ilmu Komputer Universitas Sriwijaya
Aerospace Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Implementation of Fuzzy Method towards Hydroponic Smart Showcase Innovation Sembiring, Sarmayanta; Exaudi, Kemahyanto; Prasetyo, Aditya PP; Rendyansyah, Rendyansyah; Nadhira, Wardha
Emitor: Jurnal Teknik Elektro Vol 24, No 3: November 2024
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v24i3.4043

Abstract

Hydroponics is a technique that allows easy cultivation of fresh and hygienic vegetables, even with limited space. Recent innovations in hydroponic development have resulted in a smart showcase prototype, which is controlled using Sugeno fuzzy techniques. This prototype uses a DC fan to maintain a stable temperature and humidity level. This invention is both ecologically friendly and portable, making it suitable for a wide range of users, including apartment residents. Experimental results using the fuzzy method show that this prototype can effectively support indoor hydroponic techniques, with fan rotation ranging from 180 to 255 rpm based on variations in room temperature and humidity. The showcase successfully maintained a stable temperature range of 28–30 °C and a humidity of 60–70% RH. In addition, out of 12 vegetable samples tested for 14 days, 7 kale stems showed significant growth. Overall, this smart showcase prototype offers the potential to bring hydroponics indoors and promote fresh vegetable cultivation.
Implementation of Fisherface Algorithm for Eye and Mouth Recognition in Face-Tracking Mobile Robot Ahmad Zarkasi; Huda Ubaya; Kemahyanto Exaudi; Ades Harafi Duri
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 3 (2024): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i3.29266

Abstract

Facial recognition is an artificial intelligence algorithm that distinguishes one face from another by capturing facial patterns visually. This recognition specifically detects and identifies individuals based on facial features by scanning the entire face. Several methods are used for facial detection, including facial landmarks points, Local Binary Patterns Histograms (LBPH), and Fisherface. In the context of this research, Fisherface is used to reduce the dimensionality of facial space in order to obtain image features. The method is insensitive to changes in expression and lighting, leading to better pattern classification and making it suitable for implementation on mobile devices such as robot vision. Therefore, this research aimed to measure the response time speed and accuracy level of pattern recognition when implemented on mobile robot devices. The results obtained from the accuracy testing showed that the highest accuracy for face detection process was 90%, while the lowest was 78.3%. In addition, the average execution time (AET) for the fastest process was 1.63 seconds and the slowest was 1.72 seconds. For pattern recognition, the statistics showed 90% accuracy, 100% precision, 81.81% recall, and F-1 score of 89.5%. Meanwhile, the longest execution time was 0.084 seconds and the fastest was 0.064 seconds. In face tracking process, the mobile robot movement was based on real-time pixel sizes, determining x and y values to produce the center of face region.
Control System for U-Arm Robot Arm Movement with Linear Gripper Based on Inverse Kinematic Method Prasetyo, Aditya Putra Perdana; Rahmatullah, Ikang; Exaudi, Kemahyanto; Rendyansyah, Rendyansyah
JITCE (Journal of Information Technology and Computer Engineering) Vol. 8 No. 2 (2024)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.8.2.97-103.2024

Abstract

This research presents the development of a U-Arm model robot with three degrees of freedom, utilizing Inverse Kinematic calculations. The novelty of this project lies in its precise control of the robot arm's movements through advanced kinematic algorithms. Inverse Kinematics is a mathematical process used to determine the joint angles of the robot arm from known (x, y, z) coordinates of the end-effector and the lengths of each link. The robotic arm consists of four links with lengths of 8.2 cm, 15 cm, 16 cm, and 18.4 cm, respectively, and is equipped with a gripping module for object manipulation. The methodology involves calculating the joint angles required for the desired end-effector position, ensuring accurate and efficient movement. Testing results indicate an average coordinate error of 7.13%, demonstrating the system's precision and reliability. This error rate provides valuable insights into the performance and potential areas for improvement in the kinematic model. Additionally, this research includes the development of a program to control the servo motor speed using For and delay functions. This program enhances the robot's operational efficiency by allowing precise speed adjustments, which are crucial for various applications. Overall, this study contributes to the field of robotics by offering a detailed analysis of kinematic control and program development for a multi-link robotic arm, highlighting its potential for practical applications.
IDENTIFICATION TYPE OF GAS BASED ON DISCHARGE TIME MEASURING IN LIGHT EMITTING DIODE SERIES Prasetiyo, Bagus; Exaudi, Kemahyanto; Mahjud, Ichsan
Jurnal Teknologi Elekterika Vol. 22 No. 1 (2025)
Publisher : Jurusan Teknik Elektro Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/elekterika.v22i1.5494

Abstract

Nowadays, gas or vapor detection to observe environment situation is very required in many fields. Spectrophotometer method is always used to analyze contain and gas concentrate based on the absorption intensity of light by the gas sample. This research used Light Emitting Diode (LED) series act as a transmitter and light receiver (detector). Above detector surface is layered by a chemical membrane that selective in to the type of gas according the polarization level. This vapor absorption in chemical membrane can cause shrinking the intensity of light that hit the detector. This light will be discarding the load in internal capacitor of the detector. Duration internal sudden discharge of the LED depends on light intensity that hit it. Detector LED series that layered by different chemical membrane is produce different an absorption phase that patterning different discharge time. In this experiment, alcoholic solution and gasoline are used as vapor samples. Identify types of gas using imitation nerve connection method to finding out every type of gas with 80% success.
The Role of Image Generative Artificial Intelligence in Optimizing Digital Visual Assets for Animation and Motion Graphics Content B Azhar, Iman Saladin; Sari, Winda Kurnia; Exaudi, Kemahyanto; Prasetyo, Aditya Putra Perdana
REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Vol 6, No 2 (2025): Reka Elkomika
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/rekaelkomika.v6i2.162-172

Abstract

This Community Service Program (PKM) was conducted to introduce and promote the use of Motion Graphics and Image Generative AI technologies as innovative tools to support digital content creation, particularly in the context of industry and government institutions. Through a workshop format, participants were provided with an overview of how these technologies can improve the quality, clarity, and appeal of visual communication. The session included a conceptual explanation of Image Generative AI, such as Adobe Firefly, which allows users to generate visual assets through text prompts, and Adobe After Effects, a powerful tool for producing dynamic animations and motion graphics. Participants actively followed the material presented and showed interest in how these tools can be applied in real-world promotional or branding efforts. The workshop concluded that integrating these technologies holds great potential for enhancing institutional communication strategies. Future programs are expected to include more hands-on and practice-oriented sessions to further develop participants’ digital production skills.
Robot Vision Pattern Recognition of the Eye and Nose Using the Local Binary Pattern Histogram Method Zarkasi, Ahmad; Ubaya, Huda; Exaudi, Kemahyanto; Almuqsit, Alif; Arsalan, Osvari
Computer Engineering and Applications Journal (ComEngApp) Vol. 12 No. 3 (2023)
Publisher : Universitas Sriwijaya

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

Abstract

The local binary pattern histogram (LBPH) algorithm is a computer technique that can detect a person's face based on information stored in a database (trained model). In this research, the LBPH approach is applied for face recognition combined with the embedded platform on the actuator system. This application will be incorporated into the robot's control and processing center, which consists of a Raspberry Pi and Arduino board. The robot will be equipped with a program that can identify and recognize a human's face based on information from the person's eyes and nose. Based on the results of facial feature identification testing, the eyes were recognized 131 times (87.33%), and the nose 133 times (88.67%) out of 150 image data samples. From the test results, an accuracy rate of 88%, the partition rate of 95.23%, the recall of 30%, the specificity of 99%, and the F1-Score of 57.5% were obtained.
Implementation of Weightless Neural Network in Embedded Face Recognition for Eye and Nose Pattern Mobile Identification Zarkasi, Ahmad; Exaudi, Kemahyanto; Sazaki, Yoppy; Romadhona, Londa Arrahmando
Computer Engineering and Applications Journal (ComEngApp) Vol. 14 No. 2 (2025)
Publisher : Universitas Sriwijaya

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Abstract

The pattern of the human face is a form of self-identity and also a form of originality for each individual. The development of facial recognition technology impacts its application in various computing devices, both in computer vision and on single-chip processors. One of the continuously developed implementations is in the form of robot vision by identifying facial features. This research aims to develop a facial recognition system focusing on the identification of the eye and nose areas. This research utilizes the Weightless Neural Network (WNN) method with the Immediate Scan technique. The combination of methods allows for rapid and accurate pattern recognition, even when the face changes position. The detection process is carried out using the Haar Cascade Classifier algorithm, which functions to recognize faces and divides the area into nine different zones to ensure accurate identification. The hardware implementation was carried out on a Raspberry Pi for face detection and facial pattern recognition, as well as the data processor for the robot vision sensor and actuator on the microcontroller. The results of the robot's movement testing have worked well according to the calculation of GPS data values to determine the robot's last position. Then, in the face pattern recognition process, it shows that the proposed method can achieve a maximum accuracy level of up to 98.87% in testing with the internal data set, while testing under different conditions experiences a slight decrease in accuracy to 91.38%. The highest similarity percentage to the faces of other individuals reached 75.69%, indicating that this method is quite adaptive to various facial variations. The execution time of the identification process ranges from 11 ms to 17 ms, depending on the amount of data compared during the scanning. This research is expected to serve as a foundation for further development in robotics systems and embedded system-based facial recognition.
Implementation of Feature Selection for Optimizing Voice Detection Based on Gender using Random Forest Abdurahman; Vindriani, Marsella; Prasetyo, Aditya Putra Perdana; Sukemi; Buchari, M. Ali; Sembiring, Sarmayanta; Firnando, Ricy; Isnanto, Rahmat Fadli; Exaudi, Kemahyanto; Dudifa, Aldi; Riyuda, Rafki Sahasika
Computer Engineering and Applications Journal (ComEngApp) Vol. 14 No. 2 (2025)
Publisher : Universitas Sriwijaya

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

Abstract

Gender-based voice detection is one of the machine learning applications that has various benefits in technology and services, such as virtual assistants, human-machine interaction systems, and voice data analysis. However, the use of too many features, including irrelevant features, can cause a decrease in accuracy and model performance. This research aims to optimize voice-based gender detection by applying a feature selection method to select significant features based on their correlation value to the target. Experimental results show that by using only the significant features selected through correlation analysis, the accuracy of the model is significantly improved compared to using all available features. This research confirms the importance of feature optimization to support the development of more efficient and accurate gender-based speech detection models.
The Eye and Nose Identification Chip Controller-Based on Robot Vision Using Weightless Neural Network Method Zarkasi, Ahmad; Ubaya, Huda; Exaudi, Kemahyanto; Fitriyanto, Megi
Computer Engineering and Applications Journal (ComEngApp) Vol. 13 No. 3 (2024)
Publisher : Universitas Sriwijaya

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

Abstract

Increasingly advanced image analysis in computer vision, allowing computers to interpret, identify, and analyze pictures with accuracy comparable to humans. The availability of data sources in decimal, hexadecimal, or binary forms enables researchers to take the initiative in applying their study findings. Decimal formats are typically used on traditional computers like desktops and minicomputers, whereas hexadecimal and binary formats were utilized on single-chip controllers. Weightless Neural Network is a method that can be implemented in a single chip controller. The aim of this research is to develop a facial recognition system, for eye and mouth identification, that works in a single chip controller or also called a microcontroller. The suggested method is a Weightless Neural Network with Immediate Scan approach for processing and identifying eye and nose patterns. The data will be handled in many memory locations that are specifically designed to handle massive volumes of data. The data is made up of primary face data sheets and face input data. The data sets utilized are (x,y) pixels, and frame sizes range from 90x90 pixels to 110x110 pixels. Each face shot will be processed by selecting the region of the eyes and nose and saving it as an image file. The eye and nose will identify the face frame. Next, the photos will be converted to binary format. A magazine matrix will be used to transmit binary data from a minicomputer to a microcontroller via serial connection. Based on a known pattern, the resultant similarity accuracy is 83,08% for the eye and 84,09% for the sternum. In contrast, the similarity percentage for an eye ranges from 70% to 85% for an undefined pattern.
Innovative smart showcase design for indoors and eco-friendly hydroponics Exaudi, Kemahyanto; Sembiring, Sarmayanta; Putra Perdana Prasetyo, Aditya; Stiawan, Deris; Fakhrurroja, Hanif; Budiarto, Rahmat
Bulletin of Electrical Engineering and Informatics Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i4.8353

Abstract

Hydroponics is a unique and fascinating farming technique for producing plants and vegetables. Without having to use a large area of land, people can easily apply the technique to produce fresh and hygienic vegetables. However, the technique cannot be used in apartment environment due to the limited sunlight. Thus, this study introduces an innovative hydroponic system, called as hydroponics smart showcase system that can be implemented indoors, even in the presence of minimal sunlight, and can be monitored online by users. The proposed system consists of a net pot of 4-5 hydroponics cups with a diameter of 50 mm, air temperature and humidity sensors, water level sensors, ultraviolet (UV) lights, indicator displays, and DC fans. Experimental results show that the development of innovative hydroponics using smart showcase has succeeded in stabilizing the air in the showcase according to the specified references. Moreover, UV light intensity settings for photosynthesis can be applied remotely with duration of 24 hours.
Co-Authors Abdul Wahid Sempurna Abdul Wahid Sempurna Abdul Wahid Sempurna Abdurahman Abdurahman Ades Harafi Duri Adi Hermansyah Aditya P.P Prasetyo Aditya P.P. Prasetyo Aditya PPP Aditya Putra Perdana Prasetyo Ahmad Fali Oklilas Ahmad Fali Oklilas Ahmad Rifai Ahmad Zarkasi Ahmad Zarkasi Alif Almuqsit Almuqsit, Alif B Azhar, Iman Saladin Bagus Prasetyo Bangun Sudrajat Bangun Sudrajat Barzan Trio Putra Brema Alfaretz Tarigan Buchari, M. Ali Dedy Kurniawan Deris Stiawan Desyandri Desyandri Dody Firmansyah Dudifa, Aldi Fakhrurroja, Hanif Fatimah, Sayyidatina Fitriyanto, Megi Hadir Kaban Huda Ubaya Huda Ubaya Huda Ubaya Ichsan Mahjud Izzati Millah Hanifah Jorena Jorena M. Dimas Firmansyah Mileandira, Leviarta Monica Ayu Amaria Muhammad Ajran Saputra Muhammad Furqon Rabbani Nabillah Selva Setiawan Nadhira, Wardha Osvari Arsalan Pingki Pingki Prasetiyo, Bagus Prasetyo, Aditya P P Prasetyo, Aditya P.P. Prasetyo, Aditya PP Prasetyo, Aditya Putra Perdana Purwita Sari Purwita Sari Purwita Sari Purwoko, Agus Putra Perdana Prasetyo, Aditya R Rendyansyah Rahmad Fadli Isnanto Rahmat Budiarto Rahmat Fadli Isnanto Rahmatullah, Ikang Rendyansyah Rendyansyah Rendyansyah Rendyansyah Rendyansyah Ricy Firnando Rido Zulfahmi Riyuda, Rafki Sahasika Romadhona, Londa Arrahmando Rony, Zahara Tussoleha Rossi Passarella Roswitha Yemima Tiur Mediswati Sari, Komang Mita Sarmayanta Sembiring Sarmayanta Sembiring Sarmayanta Sembiring Sayyidatina Fatimah Sri Desy Siswanti Sri Desy Siswanti Sry Desy Siswanti Sukemi Sutarno Sutarno Tharisa Antya Perdani Tri Wanda Septian Tri Wanda Septian, Tri Wanda Vindriani, Marsella Wahyu Gunawan Winda Kurnia Sari