IJARAI Volume 4 Issue 12

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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Paper 1: Effect of Sensitivity Improvement of Visible to NIR Digital Cameras on NDVI Measurements in Particular for Agricultural Field Monitoring

Abstract: Effect of sensitivity improvement of Near Infrared: NIR digital cameras on Normalized Difference Vegetation Index: NDVI measurements in particular for agricultural field monitoring is clarified. Comparative study is conducted between sensitivity improved visible to near infrared camera of CuInGaSe: CIGS and the conventional camera. Signal to Noise: S/N ratio and sensitivity are evaluated with NIR camera data which are acquired in tea farm areas and rice paddy fields. From the experimental results, it is found that S/N ratio of the conventional digital camera with NIR wavelength coverage is better than CIGS utilized image sensor while the sensitivity of the CIGS image sensor is much superior to that of the conventional camera. Also, it is found that NDVI derived from the CIGS image sensor is much better than that from the conventional camera due to the fact that the sensitivity of the CIGS image sensor in red color wavelength region is much better than that of the conventional camera.

Author 1: Kohei Arai
Author 2: Takuji Maekawa
Author 3: Toshihisa Maeda
Author 4: Hiroshi Sekiguchi
Author 5: Noriyuki Masago

Keywords: CuInGaSe; SiCMOS; NDVI; Rice crop; Tealeaves; S/N ratio; Sensivity

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Paper 2: An Implementation of Outpatient Online Registration Information System of Mutiara Bunda Hospital

Abstract: Outpatient care is one of the medical services in Mutiara Bunda hospital. The management of outpatient registration of Mutiara Bunda Hospital used conventional way. Within 1 hour serving, 5 patients were enrolled with an average time of 13 minutes per patient. This caused the registration queue to get outpatient services. The study was conducted with the aim to produce outpatient online registration information system design of Mutiara Bunda Hospital in order to increase outpatient registration service and to manage data in getting medical care. The patients register on Outpatient Online Registration Information System without having to come first to the hospital and get a queue number, so they can estimate the waiting time in the hospital to get medical care at Mutiara Bunda Hospital; while the patients who come to the hospital are served directly by the registrar. From the results of the research, it can be concluded that the application of Outpatient Online Registration Information System help in managing and processing data of patient registration to be able to get medical care immediately at Mutiara Bunda Hospital.

Author 1: Masniah

Keywords: Online Registration; Outpatient; Information System

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Paper 3: An Expert System-Based Evaluation of Civics Education as a Means of Character Education Based on Local Culture in the Universities in Buleleng

Abstract: Civics education as a means of character education based on local culture has the mission to develop values and attitudes. In the educational process, various strategies and methods of value education can be used. In Civics Education characters are developed as the impact of education and also as its nurturing effect. Meanwhile, other subjects, which formally have the major mission other than character development have to develop activities that have the nurturing effect of character development in the students. However, in the educational process this has not run well. Hence there is a need to evaluate educational programs at public as well as private universities in Buleleng regency. One of the evaluation techniques that can be used is the CIPP model combined with certainty factor method in expert system. The CIPP Model can evaluated the Civics education processes at all the public and private universities in Buleleng regency objectively, especially in probing local culture in character educational development. Meanwhile, the certainty factor method is used to determine the extent or degree of certainty of a component being evaluated in Civics educational processes.

Author 1: Dewa Bagus Sanjaya
Author 2: Dewa Gede Hendra Divayana

Keywords: Evaluation of Civics Education; Character; Local culture; Expert System; Certainty Factor

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Paper 4: Blurring and Deblurring Digital Images Using the Dihedral Group

Abstract: A new method of blurring and deblurring digital images is presented. The approach is based on using new filters generating from average filter and H-filters using the action of the dihedral group. These filters are called HB-filters; used to cause a motion blur and then deblurring affected images. Also, enhancing images using HB-filters is presented as compared to other methods like Average, Gaussian, and Motion. Results and analysis show that the HB-filters are better in peak signal to noise ratio (PSNR) and RMSE.

Author 1: Husein Hadi Abbas Jassim
Author 2: Zahir M. Hussain
Author 3: Hind R.M Shaaban
Author 4: Kawther B.R. Al-dbag

Keywords: Dihedral group; Kronecker Product; motion blur and deblur; digital image

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Paper 5: Naive Bayes Classifier Algorithm Approach for Mapping Poor Families Potential

Abstract: The poverty rate that was recorded high in Indonesia becomes main priority the government to find a solution to poverty rate was below 10%. Initial identification the potential poverty becomes a very important thing to anticipate the amount of the poverty rate. Naive Bayes Classifier (NBC) algorithm was one of data mining algorithms that can be used to perform classifications the family poor with 11 indicators with three classifications. This study using sample data of poor families a total of 219 data. A system that built use Java programming compared to the result of Weka software with accuracy the results of classification of 93%. The results of classification data of poor families mapped by adding latitude-longitude data and a photograph of the house of the condition of poor families. Based on the results of mapping classifications using NBC can help the government in Kabupaten Bantul in examining the potential of poor people.

Author 1: Sri Redjeki
Author 2: M. Guntara
Author 3: Pius Anggoro

Keywords: Data Mining; Naive Bayes; Poverty Potential; Mapping

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Paper 6: Language Identification by Using SIFT Features

Abstract: Two novel techniques for language identification of both, machine printed and handwritten document images, are presented. Language identification is the procedure where the language of a given document image is recognized and the appropriate language label is returned. In the proposed approaches, the main body size of the characters for each document image is determined, and accordingly, a sliding window is used, in order to extract the SIFT local features. Once a large number of features have been extracted from the training set, a visual vocabulary is created, by clustering the feature space. Data clustering is performed using K-means or Gaussian Mixture Models and the Expectation - Maximization algorithm. For each document image, a Bag of Visual Words or Fisher Vector representation is constructed, using the visual vocabulary and the extracted features of the document image. Finally, a multi class Support Vector Machine classification scheme is used, to score the system. Experiments are performed on well-known databases and comparative results with another established technique, are also given.

Author 1: Nikos Tatarakis
Author 2: Ergina Kavallieratou

Keywords: Document image processing; language identification; SIFT features; bag of Visual Words; Fisher Vector

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Paper 7: Analytical Study of Some Selected Classification Algorithms in WEKA Using Real Crime Data

Abstract: Data mining in the field of computer science is an answered prayer to the demand of this digital age. It is used to unravel hidden information from large volumes of data usually kept in data repositories to help improve management decision making. Classification is an essential task in data mining which is used to predict unknown class labels. It has been applied in the classification of different types of data. There are different techniques that can be applied in building a classification model. In this study the performance of these techniques such as J48 which is a type of decision tree classifier, Naïve Bayesian is a classifier that applies probability functions and ZeroR is a rule induction classifier are used. These classifiers are tested using real crime data collected from Nigeria Prisons Service. The metrics used to measure the performance of each classifier include accuracy, time, True Positive Rate (TP) Rate, False Positive (FP) Rate, Kappa Statistic, Precision and Recall. The study showed that the J48 classifier has the highest accuracy compared to other two classifiers in consideration. Choosing the right classifier for data mining task will help increase the mining accuracy.

Author 1: Obuandike Georgina N.
Author 2: Audu Isah
Author 3: John Alhasan

Keywords: Data Mining; Classification; Decision Tree; Naïve Bayesian; Tp Rate; component; formatting

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Paper 8: Differential Evolution Enhanced with Eager Random Search for Solving Real-Parameter Optimization Problems

Abstract: Differential evolution (DE) presents a class of evo-lutionary computing techniques that appear effective to handle real parameter optimization tasks in many practical applications. However, the performance of DE is not always perfect to ensure fast convergence to the global optimum. It can easily get stagnation resulting in low precision of acquired results or even failure. This paper proposes a new memetic DE algorithm by incorporating Eager Random Search (ERS) to enhance the performance of a basic DE algorithm. ERS is a local search method that is eager to replace the current solution by a better candidate in the neighborhood. Three concrete local search strategies for ERS are further introduced and discussed, leading to variants of the proposed memetic DE algorithm. In addition, only a small subset of randomly selected variables is used in each step of the local search for randomly deciding the next trial solution. The results of tests on a set of benchmark problems have demonstrated that the hybridization of DE with Eager Random Search can substantially augment DE algorithms to find better or more precise solutions while not requiring extra computing resources.

Author 1: Miguel Leon
Author 2: Ning Xiong

Keywords: Evolutionary Algorithm, Differential Evolution, Ea-ger Random Search, Memetic Algorithm, Optimization

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