Proceeding of the Electrical Engineering Computer Science and Informatics
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Comparative Performance Analysis of Linear Precoding in Downlink Multi-user MIMO
Get PDFThis paper investigates the comparative performance of linear precoding schemes. The linear precoding schemes are including block diagonalization (BD), zero forcing (ZF), and maximum ratio transmission (MRT) in downlink multi-user MIMO. This work delivers the performance of linear precoding in term of achievable sum rate and bit error rate (BER) with a variation of the signal to noise ratio (SNR) and the number of transmitter-receiver antennas. We suppose that the transmitters have a complete channel state information. The results show that the MRT precoding yields better bit error rate than both the BD and ZF precoding schemes. However, the ZF precoding generates better achievable sum rate than the MRT precoding. In the other side, the MRT precoding also outperforms when the number of active users is bigger than Kcross while the number of active users is less than Kcross the ZF precoding is still dominant
Automatic Switching Algorithm for Photovoltaic Power Generation System
Get PDFwithin remote area worldwide, solar panel is still considered as an alternative with lower efficiency rate and a complex system needing backup source and storage such as battery. PI MPPT controller then used to remarkably improve the efficiency rate of the solar panel by maintaining it on its Maximum Power Point (MPP) reference. However, tackling the complexity of photovoltaic generator for remote area require another solution. This paper provide a simple yet applicable solution by presenting an algorithm to automatically control the photovoltaic generator system for remote area. The algorithm logic is determined by the key parameters from each systems inside, which are solar panel, PI Boost Converter, Battery, and Load. The simulation result proves that the algorithm is able to provide an appropriate result with all condition working properly. Thus, the algorithm is eligible to be applied and to be developed furthe
Object Detection of Omnidirectional Vision Using PSO-Neural Network for Soccer Robot
Get PDFThe vision system in soccer robot is needed to recognize the object around the robot environment. Omnidirectional vision system has been widely developed to find the object such as a ball, goalpost, and the white line in a field and recognized the distance and an angle between the object and robot. The most challenging in develop Omni-vision system is image distortion resulting from spherical mirror or lenses. This paper presents an efficient Omni-vision system using spherical lenses for real-time object detection. Aiming to overcome the image distortion and computation complexity, the distance calculation between object and robot from the spherical image is modeled using the neural network with optimized by particle swarm optimization. The experimental result shows the effectiveness of our development in the term of accuracy and processing time
Decision Support System Scheme Using Forward Chaining And Simple Multi Attribute Rating Technique For Best Quality Cocoa Beans Selection
Get PDFCocoa is a crop plantation originating from the tropical forests of Central America and northern part of South America. In general, cocoa grouped into three types namely Forastero, Criollo, and Trinitario which is the result of a cross between Forastero with Criollo. Cocoa (Theobroma cacao L.) is one of the comodity that has an important role in the Indonesian economy. The Indonesian's processing directorate, and the programs related to the 2015-2019 development are the Increased Production and Productivity of Sustainable Plantation Crops. This program is conducted to increase the production, productivity of cocoa and other plantation crops. One of the focus activities is Inventory of postharvest data of plantation. In the selection of cocoa beans based on the best quality, Indonesian Coffee and Cocoa Research Center is often missed so that there are some cocoa beans that should not pass the quality but still processed into processed products. In that case we proposed a new scheme for Decision Support System by using Forward Chaining method and Simple Multi Attribute Rating Technique (SMART). The combination of these two methods proved to be able to do a very good selection of cocoa beans. Where the selection is done with two stages proven can really filter the cocoa beans are good for health
Sentiment Analysis Based on Appraisal Theory for Assessing Incumbent Electability
Get PDFSentiment analysis is a useful study for determining opinions by classifying text. The document used in the research comes from Twitter about public opinion about community satisfaction related to performance of incumbent. The method used is Appraisal Theory. The data used are 1587 for Jokowi related data, 1774 for Ministry related data, and 1337 government related data. The result of data analysis from this research is that people have positive sentiments for incumbent. Innovation is a term that has the highest positive sentiment, whereas imaging is the term that has the lowest negative sentiment
Design of Hybrid System Power Management Based Operational Control System to Meet Load Demand
No full textRenewable energy is an energy of unlimited sources that covering wind, sunshine and water, which can be used as sources of renewable power plants. These power plants give several advantages, but also some disadvantages, such as expensive generation costs, etc. The difficulty of being raised, due instability of renewable energy resources (RER). Aim of this study is to design power management of a hybrid system based on operational control system due to load demand. In this study, Power Management of Hybrid System used 3 power plants: Photovoltaic (PV), Wind Power, and Micro Hydro Power Plant (PLTmH), while Battery was employed as storage system. Main focus of the work was to determine the activation of each plant using Artificial Neural Network (ANN) method to fulfill the load demand. Matlab Simulink was employed to developed and simulate the ANN on the system. From results of simulation can be concluded that ANN can reach target accuracy level in 80%. When interconnecting the entire plant, the ANN experienced a misreading due to the voltage drop in each generator that affected the ANN input
Sarcasm Detection on Indonesian Twitter Feeds
Get PDFIn social media, some people use positive words to express negative opinion on a topic which is known as sarcasm. The existence of sarcasm becomes special because it is hard to be detected using simple sentiment analysis technique. Research on sarcasm detection in Indonesia is still very limited. Therefore, this research proposes a technique in detecting sarcasm in Indonesian Twitter feeds particularly on several critical issues such as politics, public figure and tourism. Our proposed technique uses two feature extraction methods namely interjection and punctuation. These methods are later used in two different weighting and classification algorithms. The empirical results demonstrate that combination of feature extraction methods, tf-idf, k-Nearest Neighbor yields the best performance in detecting sarcasm
Diagnosis of Smear-Negative Pulmonary Tuberculosis using Ensemble Method: A Preliminary Research
Get PDFIndonesia is one of 22 countries with the highest burden of Tuberculosis in the world. According to WHO’s 2015 report, Indonesia was estimated to have one million new tuberculosis (TB) cases per year. Unfortunately, only one-third of new TB cases are detected. Diagnosis of TB is difficult, especially in the case of smear-negative pulmonary tuberculosis (SNPT). The SNPT is diagnosed by TB trained doctors based on physical and laboratory examinations. This study is preliminary research that aims to determine the ensemble method with the highest level of accuracy in the diagnosis model of SNPT. This model is expected to be a reference in the development of the diagnosis of new pulmonary tuberculosis cases using input in the form of symptoms and physical examination in accordance with the guidelines for tuberculosis management in Indonesia. The proposed SNPT diagnosis model can be used as a cost-effective tool in conditions of limited resources. Data were obtained from medical records of tuberculosis patients from the Jakarta Respiratory Center. The results show that the Random Forest has the best accuracy, which is 90.59%, then Adaboost of 90.54% and Bagging of 86.91%
Prediction Of Students Academic Success Using Case Based Reasoning
Get PDFAcademic success for a student is influenced by many factors during their study period. Factors such as student gender, student absenteeism, parental satisfaction with schools, relations and parents who are responsible for students can influence student success in the academic field. Researchers try to find out what are the most dominant factors in determining academic success for a student at different levels of education such as elementary, middle and high school level. Previous research grouped the level of student academic success into three levels, namely low, medium, high and obtained 15 Association Rules Generated By Apriori Algorithm. This study tried to find out and predict the possible level of academic success of students by using 9 Association Rules Generated By Apriori Algorithm from previous research. The method used to predict the level of student academic success is case based reasoning with the nearest neighbor algorithm. By using the Association Rules Generated By Image Algorithm and with the data set from the xAPIEducational Mining Dataset the case similarity value was obtained with knowledge data that is 1 with a percentage of 81%, and data that had a similarity value of less than 1 was 19%. While in the previous study the best classification accuracy was 80.6% by the Voting classifier. And the grouping of success data is divided into two, namely low and high
Speaker and Speech Recognition Using Hierarchy Support Vector Machine and Backpropagation
Get PDFVoice signal processing has been proposed to improve effectiveness and facilitate the public, such as Smart Home. This study aims a smart home simulation model to move doors, TVs, and lights from voice instructions. Sound signals are processed using Mel-frequency Cepstrum Coefficients (MFCC) to perform feature extraction. Then, the voice is recognized by the speaker using a hierarchy Support Vector Machine (SVM). So that unregistered speakers are not processed or are declared not having access rights. For the process of recognizing spoken words such as "Open the Door”,"Close the Door","Turn on the TV","Turn off the TV","Turn on the Lights" and "Turn Offthe Lights" are done using Backpropagation. The results showed that hierarchy SVM provided an accuracy of 71% compared to the single SVM of 45%