Jurnal Ilmu Komputer dan Informasi
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SIMILARITY BASED ENTROPY ON FEATURE SELECTION FOR HIGH DIMENSIONAL DATA CLASSIFICATION
Get PDFAbstract Curse of dimensionality is a major problem in most classification tasks. Feature transformation and feature selection as a feature reduction method can be applied to overcome this problem. Despite of its good performance, feature transformation is not easily interpretable because the physical meaning of the original features cannot be retrieved. On the other side, feature selection with its simple computational process is able to reduce unwanted features and visualize the data to facilitate data understanding. We propose a new feature selection method using similarity based entropy to overcome the high dimensional data problem. Using 6 datasets with high dimensional feature, we have computed the similarity between feature vector and class vector. Then we find the maximum similarity that can be used for calculating the entropy values of each feature. The selected features are features that having higher entropy than mean entropy of overall features. The fuzzy k-NN classifier was implemented to evaluate the selected features. The experiment result shows that proposed method is able to deal with high dimensional data problem with average accuracy of 80.5%
LOCATION ANALYSIS ON SMART HOUSE USING PROJECTIVE TRANSFORMATION
Get PDFIn this paper, a method of location analysis for smart house is proposed. The proposed method uses projective transformation to process the input from visual sensor for determining coordinate of resident and also the entire device inside the smart house. With a good calculated coordinate, each device function in the smart house can be optimized for the good of the resident. From the experiment results, the proposed method successfully maps all coordinates of any device in the smart house up to 81% accuracy
EARLY DETECTION AND MONITORING SYSTEM OF HEART DISEASE BASED ON ELECTROCARDIOGRAM SIGNAL
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Heart disease is the number one deadly disease in Indonesia. One of the main causes of fatality is the late detection of the disease. To avoid escalation of mortality caused by heart disease, we need early detection and monitoring system of heart disease. Therefore, in this research we propose an early detection and monitoring system of heart disease based on ECG signal. The proposed system has three main components: ECG hardware, smartphone, and server. Since the proposed system is designed to classify heartbeat signal, heart disease symptom can be detected as early as possible. We use FLVQ-PSO algorithm to classify heartbeat signal. Experiment result shows that classification accuracy of the system can reach 91.63%. Moreover, the proposed system can be used to verify patients heartbeat by cardiologists from distant area (telehealth). Experiment result shows that responsiveness of the system for the telehealth system is less than 0.6 seconds
ADAPTIVE ANT COLONY OPTIMIZATION BASED GRADIENT FOR EDGE DETECTION
Get PDFAnt Colony Optimization (ACO) is a nature-inspired optimization algorithm which is motivated by ants foraging behavior. Due to its favorable advantages, ACO has been widely used to solve several NP-hard problems, including edge detection. Since ACO initially distributes ants at random, it may cause imbalance ant distribution which later affects path discovery process. In this paper an adaptive ACO is proposed to optimize edge detection by adaptively distributing ant according to gradient analysis. Ants are adaptively distributed according to gradient ratio of each image regions. Region which has bigger gradient ratio, will have bigger number of ant distribution. Experiments are conducted using images from various datasets. Precision and recall are used to quantitatively evaluate performance of the proposed algorithm. Precision and recall of adaptive ACO reaches 76.98 % and 96.8 %. Whereas highest precision and recall for standard ACO are 69.74 % and 74.85 %. Experimental results show that the adaptive ACO outperforms standard ACO which randomly distributes ants
MULTITHRESHOLDING IN GRAYSCALE IMAGE USING PEA FINDING APPROACH AND HIERARCHICAL CLUSTER ANALYSIS
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Image segmentation is typically used to distinguish objects that exist in an image. However, it remains difficult to accommodate favourable thresholding in multimodal image histogram problem with specifically desired number of thresholds. This research proposes a novel approach to find thresholds in multimodal grayscale image histogram. This method consists of histogram smoothing, identification of peak(s) and valley(s), and merging process using hierarchical cluster analysis. Using five images that consisted of grayscale and converted-to-grayscale images. This method yields maximum value of accuracy, precision, and recall of 99.93%, 99.75%, and 99.75% respectively. These results are better than the similar peak finding method in multimodal grayscale image segmentation
AUTOMATIC ARRHYTHMIAS DETECTION USING VARIOUS TYPES OF ARTIFICIAL NEURAL NETWORK BASED LEARNING VECTOR QUANTIZATION (LVQ)
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An automatic Arrythmias detection system is urgently required due to small number of cardiologits in Indonesia. This paper discusses only about the study and implementation of the system. We use several kinds of signal processing methods to recognize arrythmias from ecg signal. The core of the system is classification. Our LVQ based artificial neural network classifiers based on LVQ, which includes LVQ1, LVQ2, LVQ2.1, FNLVQ, FNLVQ MSA, FNLVQ-PSO, GLVQ and FNGLVQ. Experiment result show that for non round robin dataset, the system could reach accuracy of 94.07%, 92.54%, 88.09% , 86.55% , 83.66%, 82.29 %, 82.25%, and 74.62% respectively for FNGLVQ, FNLVQ-PSO, GLVQ, LVQ2.1, FNLVQ-MSA, LVQ2, FNLVQ and LVQ1. Whereas for round robin dataset, system reached accuracy of 98.12%, 98.04%, 94.31%, 90.43%, 86.75%, 86.12 %, 84.50%, and 74.78% respectively for GLVQ, LVQ2.1, FNGLVQ, FNLVQ-PSO, LVQ2, FNLVQ-MSA, FNLVQ and LVQ1
TERRAIN: FETAL GROWTH TELEHEALTH SYSTEM BASED ON 2D FETAL HEAD IMAGE USING RANDOMIZED HOUGH TRANSFORM
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Intrauterine growth restriction (IUGR) is one of many fetal abnormalities, which has high contribution on maternal mortality rate and perinatal mortality rate in Indonesia. Apparently, IUGR impact can be reduced if only the symptoms are detected earlier and the correct treatment is applied. However, fetal growth detection and monitoring process in Indonesia is obstructed because the number of physicians is very limited and ultrasonography (USG) devices are expensive. Moreover, both the physicians and USG devices are only available in big cities. To answer those problems, this research proposed an intelligent system that can provide fetal growth telemonitoring in rural areas. This system consists of three components: portable USG device, mobile application which is developed using Android operating system, and server application which is developed using Django. The main feature of this system is automatic fetal head parameter detection and its ability to operate in the limited internet access environment. In this system, automatic fetal head parameter detection uses RHT method to approximate fetal head’s ellipse shape. Experiment result shows that RHT detection ability with ∆ellipse average of 79.564 and running time average of 0.373 second
DECENTRALIZED SOCIAL NETWORK SERVICE USING THE WEB HOSTING SERVER FOR PRIVACY PRESERVATION
Get PDFIn recent years, the number of subscribers of the social network services such as Facebook and Twitter has increased rapidly. In accordance with the increasing popularity of social network services, concerns about user privacy are also growing. Existing social network services have a centralized structure that a service provider collects all the user’s profile and logs until the end of the connection. The information collected typically useful for commercial purposes, but may lead to a serious user privacy violation. The user’s profile can be compromised for malicious purposes, and even may be a tool of surveillance extremely. In this paper, we remove a centralized structure to prevent the service provider from collecting all users’ information indiscriminately, and present a decentralized structure using the web hosting server. The service provider provides only the service applications to web hosting companies, and the user should select a web hosting company that he trusts. Thus, the user’s information is distributed, and the user’s privacy is guaranteed from the service provider
INFORMATION RETRIEVAL OF TEXT DOCUMENT WITH WEIGHTING TF-IDF AND LCS
Get PDFInformation retrieval of text document requires a method that is able to restore a number of documents that have high relevance according to the user's request. One important step in the process is a text representation of the weighting process. The use of LCS in Tf-Idf weighting adjustments considers the appearance of the same order of words between the query and the text in the document. There is a very long document but irrelevant cause weight produced is not able to represent the value relevance of documents. This research proposes the use of LCS which gives weight to the word order by considering long documents related to the average length of documents in the corpus. This method is able to return a text document effectively. Additional features of word order by normalizing the ratio of the overall length of the document to the documents in the corpus generate values of precision and recall as well as the method of Tasi et al
PROPOSED ARCHITECTURE AND THE DEVELOPMENT OF NFCAFE: AN NFC-BASED ANDROID MOBILE APPLICATIONS FOR TRADING TRANSACTION SYSTEM IN CAFETARIA
Get PDFThe development of mobile technology and RFID leads to an innovative mobile payment technology by using NFC. One of the popular mobile device platforms today is Android. This research proposes an architecture of NFC-based payment system in cafeteria – which is called NFCafe – and the implementation of it in Android applications. It is a closed payment systems – without involving third parties such as banks. The security issue is handled by using symmetric and asymmetric encryptions, they are RSA and AES. The application has been developed and successfully passed the testing conducted by several respondents