Advances in technology have increased the use and complexity of software. The complexity of the software can increase the possibility of defects. Defective software can cause high losses. Fixing defective software req...
Advances in technology have increased the use and complexity of software. The complexity of the software can increase the possibility of defects. Defective software can cause high losses. Fixing defective software requires a high cost because it can spend up 50% of the project schedule. Most software developers don't document their work properly so that making it difficult to analyse software development history data. Software metrics which use in cross-project software defects prediction have many features. Software metrics usually consist of various measurement techniques, so there are possibilities for their features to be similar. It is possible that these features are similar or irrelevant so that they can cause a decrease in the performance of classifiers. In this study, several feature selection techniques were proposed to select the relevant features. The classification algorithm used is Naive Bayes. Based on the analysis using ANOVA, the SBS and SBFS models can significantly improve the performance of the Naïve Bayes model.
The Internet of Things (IoT) is a concept where internet connectivity can exchange information with each other with objects around it. The essence of IoT is interconnected devices that produce and exchange observation...
The Internet of Things (IoT) is a concept where internet connectivity can exchange information with each other with objects around it. The essence of IoT is interconnected devices that produce and exchange observation data, facts, and other data, so that it is available to anyone. In this paper we present how the smart room model is designed using sensors and micro-controllers to automate the use of electronic devices and the security of a room using the concept of the Internet of Things. Implementation of the smart room concept from the results of this study, we hope that the concept in this smart room can be implemented and the automation process in this smart room can have a major impact on the efficiency of operational costs, especially electricity payments and improve home security because there is automatic control.
The transfer of land has an impact on the decreasing of the agricultural land area, so it is necessary to plan the right cropping pattern as an effort to increase the productivity of agricultural cultivation. Also, Cl...
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In this millennial era, a large amount of digital data traffic going through communication media on digital technology every day. Most of the data are documents and other essential information. The existing rapid deve...
In this millennial era, a large amount of digital data traffic going through communication media on digital technology every day. Most of the data are documents and other essential information. The existing rapid development of technology nowadays, information can be easily faked. To make sure the validity of a digital document, a digital signature is required to verify the originality of the document. The purpose of this research is to design software which implemented the group signature algorithm to apply and verify digital signatures. The Signature Group algorithm used in this research is the Tseng-Jan scheme. The Tseng-Jan scheme consists of 5 stages: setup, join, sign, verify, and open. After applying the algorithm using 2 digits key and 3 digits key on the samples, 80% of the verification experiment on 2 digits key was succeeded 70% of the verification experiment on 3 digits key was succeeded.
The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 led to increased sampling of sarbecoviruses circulating in horseshoe bats. Employing phylogenetic inference while accounting for recombination of bat sarbecovir...
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In this work we address the automatic music genre classification as a pattern recognition task. The content of the music pieces were handled in the visual domain, using spectrograms created from the audio signal. This...
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In this work we address the automatic music genre classification as a pattern recognition task. The content of the music pieces were handled in the visual domain, using spectrograms created from the audio signal. This kind of image has been successfully used in this task since 2011 by extracting handcrafted features based on texture, since it is the main visual attribute found in spectrograms. In this work, the patterns were described by representation learning obtained with the use of convolutional neural network (CNN). CNN is a deep learning architecture and it has been widely used in the pattern recognition literature. Overfitting is a recurrent problem when a classification task is addressed by using CNN, it may occur due to the lack of training samples and/or due to the high dimensionality of the space. To increase the generalization capability we propose to explore data augmentation techniques. In this work, we have carefully selected strategies of data augmentation that are suitable for this kind of application, which are: adding noise, pitch shifting, loudness variation and time stretching. Experiments were conducted on the Latin Music Database (LMD), and the best obtained accuracy overcame the state of the art considering approaches based only in CNN.
There are several ways to deal with security issues of confidential data sent via the internet, including using cryptographic techniques and steganography. Steganography is the science and art of concealing informatio...
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Raspberry Pi is a mini-computer that is provided to carry out activities quickly and precisely, but Raspberry Pi was created to not be able to do the real-time system with the support of Windows 10 IoT operating syste...
Raspberry Pi is a mini-computer that is provided to carry out activities quickly and precisely, but Raspberry Pi was created to not be able to do the real-time system with the support of Windows 10 IoT operating system, so the real-time system can be done on Raspberry Pi. The real-time applied in the application needs to be tested with the Nyquist theory. The purpose of this study was to get real-time system measurements available on Windows 10 IoT. This test is done using the Nyquist theory by calculating the results of measurements on mp3 streaming performed on Windows 10 IoT.
This article aims to proposed framework an Intelligent Recommender System (IRS) for students in higher education institutions. This conceptual framework includes problems in predicting student performance, the possibi...
This article aims to proposed framework an Intelligent Recommender System (IRS) for students in higher education institutions. This conceptual framework includes problems in predicting student performance, the possibility of graduating on time, and recommends choosing subjects according to performance, and career interests, which are useful for assisting pedagogical interventions in future student development. The success in the development and implementation of the proposed IRS framework is inseparable from using data mining and machine learning techniques in predicting and providing recommendations. Data analysis consisted of clustering techniques, association rules, and classification using Support Vector Machine (SVM), Naïve Bayes, and k-Nearest Neighbour (k-NN). These techniques are used to solve problems related to students and to provide appropriate recommendations. The result is an IRS conceptual framework for the college student that can be used as smart agents to provide student guidance and suggestions to support the process of education in higher education.
Congestion in Jakarta is a chronic problem and is still being sought. The growing city of Jakarta is facing various international events, increasing the complexity of these congestion problems. This research is aimed ...
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