EMITTER International Journal of Engineering Technology
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160 research outputs found
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Improvement of Segmentation Performance for Feature Extraction on Whirlwind Cloud-based Satellite Image using DBSCAN Clustering Algorithm
No full textImages contain a lot of information that can be used in a variety of areas. One of the images that have much information inside is satellite image. In order to extract the information properly, the image processing step should be performed properly. The segmentation process plays an important role in image processing, especially for feature extraction. Many ways were developed to perform the segmentation image. In this study, we apply DBSCAN clustering to segment images on whirlwind cloud feature extraction problems. DBSCAN is a density-based classifier method which means it is suitable to group a density-based data. While the image used in the segmentation process is the Himawari 8 satellite image which also contains density-based data. It contains various information about clouds condition like cloud type, cloud temperature, cloud humidity, rainfall potential based on cloud temperature, etc. This study uses Himawari 8 satellite images as input where the images taken are images several hours before a wirlwind event in an area, while the cluster method used is the DBSCAN algorithm. Clustering is done to get the extraction features of a wirlwind in the form of centroid points that characterize the movement of a cloud. Segmentation performance was observed based on the number of centroid points as a result of clustering several types of clouds in an area before a wirlwind occurred. Based on segmentation testing using the DBSCAN algorithm for cloud data in an area for several hours before a wirlwind, better segmentation performance was obtained compared to the segmentation results of the Meng hee heng k-means algorithm for the same test data specifications. DBSCAN separates a type of cloud in more detail that makes it easier to record each centroid of each cluster around the scene. It is even able to cluster small groups of clouds independently so that these small groups of clouds can also be detected as features
Augmented Reality as Learning Medium for Preservation of Traditional Musical Instruments in Bangka
No full textNowadays the use of technology is something that can be found anywhere. This condition has an impact on the loss of awareness of the Indonesian cultural treasures value in the form of traditional tools. No exception to traditional musical instruments on Bangka Island which began to lose its popularity. At present, most teenagers on Bangka Island cannot play traditional musical instruments. Likewise with the children who do not know and not even know their own regional musical instruments. With the continuation of this condition, it is feared that the existence of traditional Bangka musical instruments will disappear, as well as human resources that can play it. Augmented Reality (AR) is a visual technology that can display objects in 3D. The advantage of this technology is being able to give a display of real-time musical instrument in the form of dynamic 3D visualization of objects and it is in accordance with the movements of the user's smartphone camera. AR has also been applied in various cases as a solution to problem-solving. Therefore, to overcome this problem, an application to preserve the traditional Bangka musical instruments using Augmented Reality (AR) is forming. The 3D objects of musical instruments are made using Maya. Unity is also used as an engine for the application of 3D modeling on the Android system, and Vuforia SDK as it’s augmented reality engine. The results of performance testing obtained 100% running well. From the results of testing the user experience with the HARUS method, it is proven that the system has comprehensibility aspects of 75.98% and manipulability aspects of 80.74% so that the total value HARUS be 78.36%
A Simplified Sounding System for Finding NVIS Channel Availability to Support Government Radio Networks in Indonesia
No full textMostly natural disasters in Java Island such as landslides are within the vicinity of not more than 200 Km from the district capital. Cellular communications require complex systems and rather vulnerable  to cope with disasters. NVIS mode is considered as a simple radio link during disaster mitigation initiation process. It needs a valid estimation to figure out the condition of the ionosphere. There are two purposes of this study, the first of which is an attempt to find out a fact the existences of authorized HF users who still work in the band of 3 MHz – 10 MHz. The second is to integrate low cost HF radio communication, commonly available small single board computer hardware, and opensource software, to build a sounding system to evaluate the quality of NVIS channels. Prediction system such VOACAP give hourly prediction data, however it has an inherent limitation because of  nature the underlying databases is monthly average based, therefore, the estimation could not be made in a daily bases. However, a real-time channel evaluation (RTCE) able to purify maximum observed frequency (MOF) estimation, and consequently, its able to select the best available frequency for short term and real time operation. In this study, we used WSPR to perform a simple RTCE technique. Furthermore, we also reviewed the current regulatory status regarding the availability of sub-10 MHz band for NVIS radio operation. The results show that discrepancies between simulation and measurement are occurred mainly because of sporadic data in the band of 60m and 80m. However, all of the measurement results and simulations almost have the same agreement regarding the quiet period between local midnight and local sunrise. The results of measurements show that 60m band is the most reliable NVIS channel between local sunrise and local midnight. Furthermore, 100 watts is a proper transmitter power to reach the required SNR for reliable voice communication.Â
Load Identification Using Harmonic Based on Probabilistic Neural Network
No full textDue to increase power quality which are caused by harmonic distortion it could be affected malfunction electrical equipment. Therefore, identification of harmonic loads become important attention in the power system. According to those problems, this paper proposes a Load Identification using harmonic based on probabilistic neural network (PNN). Harmonic is obtained by experiment using prototype, which it consists of microcontroller and current sensor. Fast Fourier Transform (FFT) method to analyze of current waveform on loads become harmonic load data. PNN is used to identify the type of load. To load identification, PNN is trained to get the new weight. Testing is conducted To evaluate of the accuracy of the PNN from combination of four loads. The results demonstrate that this method has high accuracy to determine type of loads based on harmonic loa
Design, Analysis and Performance Evaluation of Electrical Power Subsystem based on Triple-Junctions Solar PV Cells and SEPIC for a Conceptual 1u Cubesat Mission
No full textThis study aims to popularize low voltage power supply design especially for space satellite Cubesat mission and other portable consumer electronic devices. In this context, a preliminary design of an electrical power subsystem (EPS) is carried out for a conceptual 1u Cubesat mission in this paper. Mathematical modeling of the basic elements of the EPS is presented. Photovoltaic (PV) power generation system that is selected is made up of triple-junction solar cells, and the battery charging system based on lithium technology as well as the power conditioning converters are selected based on single ended primary inductance converter topology popularly abbreviated as SEPIC. Triple-junction solar PV cell results are verified by comparing with the datasheet values. A maximum power point tracking algorithm which is known as perturb and observe is implemented and proportional-integral controller is used for the SEPIC. All of these are well analyzed, mathematically modeled and simulated. Feasibility of the designed EPS is verified by comparing with similar devices from different manufacturers
Position Control of 1-DOF High-Precision Rotary Table using Adaptive Neuro-Fuzzy Inference System (ANFIS) Controller
No full textResearch of position control of 1-DOF high-precision rotary table using adaptive Neuro-Fuzzy inference system (ANFIS) controller has been done. In the closed-loop system without a controller, the response was oscillating and pounding caused by inertial torque. It because a rotary table receives a considerable load. Based on this, the ANFIS controller is needed to eliminate oscillations and compensate for the inertia. The result shows that there was no oscillation or overshoot with the steady-state error value of 2.27% for the reference angle of 45°, valued at 0.10% reference angle of 180°, and valued at 0% reference angle of 360°. The result proves that ANFIS controllers can eliminate oscillations with and compensate for inertia
Collaboration FMADM And K-Means Clustering To Determine The Activity Proposal In Operational Management Activity
No full textIndonesian government agencies under the Ministry of Energy and Mineral Resources still use manual methods in determining and selecting proposals for operational activities to be carried out. This study uses the Decision Support System (DSS) method, namely Fuzzy Multiple Attribute Decision Decision (Fmadm) and K-Means Clustering method in managing Operational Plan activities. Fmadm to select the best alternative from a number of alternatives, alternatives from this study proposed activity proposals, then ranking to determine the optimal alternative. The K-Means Clustering Method to obtain cluster values for alternatives on the criteria for activity dates, types of activities, and activity ceilings. The last iteration of the Euclidian distance calculation data on k-means shows that alternatives that have the smallest centroid value are important proposal criteria and the largest centroid value is an insignificant proposal criteria. The results of the collaboration of the Fmadm and K-Means Clustering methods show the optimal ranking of activities (proposal activities) and the centroid value of each alternative
Performance Analysis of Specification Computer and Mobile with Implementation Tawaf Virtual Reality using A* Algorithm and RVO System
No full textHigh-Performance Computer (HPC) is computer systems that are built to be able to solve computational loads. HPC can provide a high-performance technology and short the computing processes timing. This technology was often used in large-scale industries and several activities that require high-level computing, such as rendering virtual reality technology. In this research, we provide Tawaf’s Virtual Reality with 1000 of Pilgrims and realistic surroundings of Masjidil-Haram as the interactive and immersive simulation technology by imitating them with 3D models. Thus, the main purpose of this study is to calculate and to understand the processing time of its Virtual Reality with the implementation of tawaf activities using various platforms; such as computer and Android smartphone. The results showed that the outer-line or outer rotation of Kaa’bah mostly consumes minimum times although he must pass the longer distance than the closer one.  It happened because the agent with the closer area to Kaabah is facing the crowded peoples. It means an obstacle has the more impact than the distances in this case
GURILEM : A Novel Design of Customer Rating Model using K-Means and RFM
No full textA rating system or reviews are generally used to assist in making decisions. Rating system widely used as a technique in the recommendation of one of them used by the customer, as in determining the resort to be used. However, the credibility of the rating looks vague because the rating could only represent some points of service. So that customer preference with each other is very different. Personalized recommendation systems offer more personalized advice, precisely knowing the preferences or tastes of the customers. Especially for customers who have a transaction history or reservation as at their resorts provide good information used by managers to design a recommendation model for their customers. In this study aims to create a model of resort recommendations based on a rating of frequency. This frequency is the number of resort use by the customer within the specified time frame. With the frequency can represent the preferences of customers. The RFM method is used to measure the reservation frequency value of the customer. The K-Means method is used to categorize customer data with its frequency and classify the type of resort. Recommendation resort to the customer based on the dominant use in one of the resort types. The recommended type of resort based on the similarity between the types of resorts used with other types of resorts
AGC of a multi sources power system with natural choice of power plants
No full textThis paper presents an application of optimal control theory in multi sources power system by considering natural choice of power plants participating in automatic generation control (AGC) scheme. However, for successful operation of large power system, the natural choices of generation suitable for AGC system are hydro and thermal power plants since gas and nuclear power plants are rarely participates in the AGC scheme. Therefore, this work presents design and implementation of proportional integral (PI) structured optimal AGC controller in the presence of hydro and thermal power plants by using state vector feedback control theory. Moreover, various case studies are identified to obtain: (i) Cost aspects of physical realization of optimal AGC controller, (ii) Closed loop system stability margin through patterns of eigenvalues and (iii) System dynamic performance. Further, results have shown that when optimal AGC scheme is implemented in power system, the dynamic performance of power system is outstanding over those obtained with genetic algorithms (GAs) tuned PI structured AGC controller. Besides, with optimal AGC controller, cheaper cost of control structure, increased in system closed loop stability margin and outstanding dynamic performance of power system have been found when lessening in hydro generation is replaced by generation from thermal power plants for various case studies under investigation