 Subjects -> ELECTRONICS (Total: 207 journals)
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- Water Level Detection for Flood Disaster Management Based on Real-time
Color Object Detection
Authors: Khairun Saddami; Yudha Nurdin, Fina Noviantika, Maulisa Oktiana, Sayed Muchallil
Abstract: Currently, the water level monitoring system for a river uses instruments installed on the banks of the river and must be checked continuously and manually. This study proposes a real-time water level detection system based on a computer vision algorithm. In the proposed system, we use color object tracking technique with a bar indicator as a reference’s level. We set three bar indicators to determine the status of the water level, namely NORMAL, ALERT and DANGER. A camera was installed across the bar level indicators to capture bar indicator and monitoring the water level. In the simulation, the monitoring system was installed in 5-100 lux lighting conditions. For experimental purposes, we set various distances of the camera, which is set of 40-80 centimeters and the camera angle is set of 30-60 degrees. The experiment results showed that this system has an accuracy of 94% at camera distance is in range 50-80 centimeters and camera angle is 60o. Based on these results, it can be concluded that this proposed system can determine the water level well in varying lighting conditions.
PubDate: Fri, 17 Mar 2023 00:00:00 +000
- The Implementation of Pretrained VGG16 Model for Rice Leaf Disease
Classification using Image Segmentation
Authors: Jody Ririt Krido Suseno; Agus Eko Minarno, Yufis Azhar
Abstract: Rice is an agricultural sector that produces rice which is one of the staple foods for the majority of the population in Indonesia. In the cultivation of rice plants there are also factors that affect rice production and are not realized by farmers causing that they are late in handling and diagnosing symptoms and making rice production decline. Therefore, it is necessary to have an early diagnosis of rice plants to identify them correctly, quickly and accurately. Machine learning is one of the classification techniques to detect various plant diseases such as rice plants. There are several studies on machine learning using the Convolutional Neural Network with the VGG16 model to classify rice leaf diseases and using Image Segmentation techniques on rice leaf datasets for make the image becomes a form that is not too complicated to analyze. The data used in this research is Rice Leaf Disease which consists of 3 classes including Bacterial leaf blight, Brown spot, and Leaf smut. Then segmentation is carried out using two techniques, namely threshold and k means. Then data augmentation for make dataset used has a large and varied number and training using VGG16 model with hyperparameter tuning and obtained 91.66% accuracy results for scenarios with the k-means dataset.
PubDate: Wed, 01 Mar 2023 00:00:00 +000
- Object Detection and Monitor System for Building Security Based on
Internet of Things (IoT) Using Illumination Invariant Face Recognition
Authors: Ivan Chatisa; Yoanda Alim Syahbana, Agus Urip Ari Wibowo
Abstract: Theft and intrusion are crimes that often occur in neighborhoods when there is opportunity or negligence by owners and security personnel. Many studies have been carried out to improve environmental security by applying cameras as a surveillance medium. However, the camera is not optimal in detecting objects when the lighting conditions are lacking. Therefore, in this study, a monitoring and object detection system was built by applying the Illumination Invariant model. This model is used to improve the appearance of the image from light and shadow reflections. The process of detecting and identifying objects is done by using human facial features (face detection) captured by the camera. The camera used is a Logitec C270 Webcam 720p which is connected via a USB port on the Raspberry Pi 4. The Raspberry Pi 4 processes human face image data and sends the processing results to a MySQL database using the HTTP protocol. Data transmission is done using the Python Flask web framework. The system was successfully run 100% by using black box testing of all functional requirements. Tests on the object detection feature were carried out based on different lighting conditions 15 times by comparing the original image and the results of the Illumination Invariant implementation. Based on the test results obtained object detection accuracy of 86.7%.
PubDate: Tue, 28 Feb 2023 00:00:00 +000
- PID Controller for DC-DC Converter under Dynamic Load Change in
Photovoltaics based Low-Voltage DC Microgrid
Authors: Made Andik Setiawan; Fahmi Hidayat, Ela Sari
Abstract: Today, DC Microgrid gain more attraction due to increasing electronic digital devices application such smart-phones, smart-tvs, and other digital apparatus which are operated in DC form. In the common grid, the electric power from AC source is converted to DC voltage for powering the digital devices as load. Hence, there are power conversions from AC-DC and potentially loss energy during conversions. DC Microgrid consisted of sources, loads, distribution lines and energy storages. In small capacity DC Microgrid, the stability of the system is vulnerable by dynamic load change. During load demands fluctuations, the DC Microgrid voltage is also dynamically fluctuated and can reach over the designated rate. To solve this problem, the PID controller is introduced in the DC-DC converter for maintaining the voltage rate at designated value regardless the load demands. In this paper, the DC Microgrid is consisted of photovoltaics as DC sources, XL-6019 as DC-DC converter, Arduino as controller, voltage and current sensors, distribution lines and loads. The proposed method is evaluated via experimental results. The responses of the proposed method in the DC Microgrid system are presented, evaluated, discussed, and compared between with and without applied method. The experimental results indicate that the proposed method has ability to reduce the voltage profile fluctuations during load demands changes and in short time.
PubDate: Wed, 15 Feb 2023 00:00:00 +000
- Utilization of AR Technology for The Development of Speech Therapy
Applications by Optimizing Marked-Based Tracking Method
Authors: Linda Perdana Wanti; Oman Somantri, Titin Karyati
Abstract: Autism is a developmental disorder that attacks children mentally and causes difficulties in interacting with the social environment. Therapy that can be done to people with autism to deal with communication disorders is speech therapy. Application usage health or better known as mobile health is easy and fast to help users in accessing information about various health problems, one of which is child development or better known as an autism spectrum disorder (ASD) which was developed using augmented reality (AR) technology. The purpose of the study is to optimizing the marked-based tracking method to augmented reality technology for speech therapy tutorials for children with autism. The results obtained from this study are the SELPY application (Self Autism Therapy) mobile-based speech therapy for people with autism which is a product of the application of appropriate technology in the field of information technology, especially in the health sector. The marked-based tracking method has been successfully implemented in the development of speech therapy AR applications for children with autism spectrum disorder (ASD). This is by the results of the tests that have been carried out, namely distance testing and angle testing. The most ideal distance to detect marker/image targets is 40cm to 50cm with a smartphone tilt angle of 200 to 300.
PubDate: Wed, 15 Feb 2023 00:00:00 +000
- Risk Management using COBIT 5 for Risk : A Case Study on Local Government
in Indonesia
Authors: Beny Prasetyo; Lailatul Qomariah Toha, Windi Eka Yulia Retnani
Abstract: BP4D (Regional Development Planning, Research and Development Agency) Bondowoso utilizes information technology to support its duties and functions, one of which is SIPD (Sistem Informasi Pemerintah Daerah). SIPD provides many benefits and conveniences such as improving the quality of public services, transparency, improving bureaucratic accountability, but in its implementation SIPD can also pose dangerous risks both from processes involving the system and the system itself. These risks can disrupt BP4D Bondowoso's business processes and cause various losses. To protect BP4D Bondowoso from losses caused by risk, risk management is carried out using the relevant framework, namely COBIT 5 Enabling Process and COBIT 5 for Risk with the APO12 risk management process. Data were collected by interview and distributing questionnaires. Fifty-one risks were identified in the implementation of SIPD at BP4D Bondowoso consisting of 48 negative risks and 3 positive risks. The risks found dominate the type of IT Benefit / Value Enablement and the category of regulatory compliance. Identified 3 very high risks in the category of regulatory compliance and software. Overall risk dominates the medium rating, which is 28 risks and the high risk consists of 20 risks. The negative risk response is dominated by mitigate, which is 33 risks.
PubDate: Wed, 15 Feb 2023 00:00:00 +000
- Expert System for Predictive Maintenance Transformer using J48 Algorithm
Authors: Erna Alimudin; Arif Sumardiono, Nur Budi Nugraha
Abstract: Predictive maintenance can reduce the risk of sudden transformer failure which causes the risk of plant to stop operating. One of transformer predictive maintenance technique is the Dissolved Gas Analysis (DGA) Test Oil Transformer. The gas is interpreted and analyzed to find out and get conclusions about the health condition and also possible problems in the transformer based on IEEE Standards and IEC Standards. To facilitate monitoring, a Decision Support System for Interpretation of Test Results of DGA Oil Immersed Transformer was created to form a database containing transformer data with the amount of main gas from the DGA test results. Next, decision tree was made using the J48 algorithm. The decision tree simplifying and speed up the decision-making process for recommended actions that are displayed on the system. The system also displays a trending graph of the last transformer test and quickly displays a dashboard of transformer status, i.e. normal, alarm, or danger. Engineer will get notification email if any transformer is in danger status. In addition, the system is able to provide information on possible fault types for each transformer. The benefits of this system are that the health condition of the transformer can be monitored properly and corrective action can be taken immediately on a problem based on the results of the decision support system. This will reduce the risk of shutdown and support the reliability of plant operations.
PubDate: Wed, 15 Feb 2023 00:00:00 +000
- Analyzing the Quality of Game-based Assessment Design in Basic Arithmetic
Operations
Authors: M. Naufal Azzmi. H; Umi Laili Yuhana, Nawang Sulistyani, Lailatul Husniah
Abstract: The use of Serious Games in education has experienced rapid development. However, not all studies have been able to show evidence that game-based methods are superior to other methods. It is important to analyze the quality of game designs used in learning and assessment used to assess students. This study focuses on how to design a serious game called B-block used in the assessment. The researcher validates the quality of the serious game first before conducting a pilot study regarding the feasibility of the Serious Game given for assessment. The game focuses on basic arithmetic, including addition, subtraction, division, and multiplication, and involves positive and negative numbers. The study was conducted in one of the schools in Indonesia and given to 35 students with an age range of 11-12 years with different student backgrounds in their experience with game-based exams. Based on these results, 85.7% of respondents agreed that this game could be used as a substitute for paper-based exams, with the analysis of game design quality having an average value of 78% pedagogic specifications and 73% playful and 80% technical specifications. Thus, the average value of this game quality analysis is considered superior and meets almost all the specifications needed for assessment. We also argue that serious game is closely related to how game design meets specifications for use as educational tools.
PubDate: Wed, 15 Feb 2023 00:00:00 +000
- Sensor Fusion using Model Predictive Control for Differential Dual Wheeled
Robot
Authors: Achmad Imam Sudianto; Muhammad Aziz Muslim, Moch Rusli
Abstract: Every mobile robot mission starts with the robot being moved to the task site. From there, the robot executes its tasks. A control system is required to move the mobile robot's actuator (which may be in the shape of wheels or legs) and comprehend the environment around the robot to perform these movements (perception). This research aims to develop a technique to control a robot’s movement while detecting obstacles and distances toward an object. The robot is equipped with LIDAR and a camera to perform these tasks. The control is divided into two major parts, low-level and high-level controller. As part of a low-level controller robot, the Model Predictive Control (MPC) method is proposed to help with the control of the wheel while the Artificial Neural Network (ANN) approach to use in this study to identify obstacles and the Convolutional Neural Network (CNN) method for detecting objects, both ANN and CNN as a control for high-level part of the robot. The results of this study can prove that CNN can help detect existing objects with a value of 45% for detecting some objects. The obtained result from the MPC method, which has been combined with an ANN as an obstacle detector, is that the smaller the horizon value, the shorter the time needed to reach the desired coordinates with the result being 45 seconds.
PubDate: Wed, 15 Feb 2023 00:00:00 +000
- Design MPPT with Anfis Method on Zeta Converter With DC Load
Authors: Epyk Sunarno; Indhana Sudiharto, Dian Yolanita
Abstract: Maximum power point tracking (MPPT) for PV (Photovoltaic) systems is provided in this research using artificial intelligence-based control. The design of MPPT system with Anfis Method on the Zeta Converter with DC Load is used to optimize the work of the Photovoltaic which will be used for DC load sources. The MPPT process consists of four main stages, namely module training data, determining input and output data, determining the number and type of membership functions and ANFIS training data. Zeta converter works like a buck boost, which can increase or decrease the voltage which is an advantage in designing systems with very volatile Photovoltaic sources. Zeta Converter is used to get higher efficiency, smaller input and output current ripple values and smaller core losses in the inductor. To improve the efficiency of system performance, An MPPT algorithm for the adaptive neuro fuzzy inference system (ANFIS) that is programmed into a microcontroller controls the zeta converter. ANFIS control is used because the response is faster and more effective. The combined simulation's findings demonstrate that the ANFIS control was successful, and the system can now produce the best possible power from Photovoltaic ipanelsiiniMPPT mode by boosting efficiency by up to 19.96%.
PubDate: Wed, 15 Feb 2023 00:00:00 +000
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