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Contact Name
Rahmat Hidayat
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INDONESIA
JOIV : International Journal on Informatics Visualization
ISSN : 25499610     EISSN : 25499904     DOI : -
Core Subject : Science,
JOIV : International Journal on Informatics Visualization is an international peer-reviewed journal dedicated to interchange for the results of high quality research in all aspect of Computer Science, Computer Engineering, Information Technology and Visualization. The journal publishes state-of-art papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the advancement of science and technology, the JOIV follows the open access policy that allows the published articles freely available online without any subscription.
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Articles 10 Documents
Search results for , issue "Vol 4, No 2 (2020)" : 10 Documents clear
Speech Command Recognition using Artificial Neural Networks Sushan Poudel; Dr. R Anuradha
JOIV : International Journal on Informatics Visualization Vol 4, No 2 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.2.358

Abstract

Speech is one of the most effective way for human and machine to interact. This project aims to build Speech Command Recognition System that is capable of predicting the predefined speech commands. Dataset provided by Google’s TensorFlow and AIY teams is used to implement different Neural Network models which include Convolutional Neural Network and Recurrent Neural Network combined with Convolutional Neural Network. The combination of Convolutional and Recurrent Neural Network outperforms Convolutional Neural Network alone by 8% and achieved 96.66% accuracy for 20 labels.
Forecasting Bitcoin using Double Exponential Smoothing Method Based on Mean Absolute Percentage Error Febri Liantoni; Arif Agusti
JOIV : International Journal on Informatics Visualization Vol 4, No 2 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (88.161 KB) | DOI: 10.30630/joiv.4.2.335

Abstract

Abstract— After being introduced in 2008, the rise in the price of bitcoin and the popularity of other cryptocurrencies triggered a growing discussion about how much energy was consumed during the production of this currency. Making cryptocurrency the most expensive and most popular, both the business world and the research community have begun to study the devel-opment of bitcoin. In this study bitcoin price predictions are performed using the double exponential smoothing method based on the mean absolute percentage error (MAPE). The MAPE value is used to find the best alpha (α) parameter as the basis for bitcoin price forecasting. The dataset used is the price of bitcoin from 2017 to 2019. The dataset was obtained from www.cryptocompare.com. As for the value of the alpha parameter (α), using a value of 0.1 to 0.9. Based on the test results using the double exponential smoothing method obtained the smallest MAPE value of 2.89%, with the best alpha (α) at 0.9. The prediction is done to see the price of bitcoin on January 1, 2020. The error rate generated on the predicted price of bitcoin uses an amount of 0.0373%. This shows that the system built can be used as a support for decision making when trading bitcoin.
Concerns-Based Reverse Engineering for Partial Software Architecture Visualization Hind Alamin M; Hany H Ammar
JOIV : International Journal on Informatics Visualization Vol 4, No 2 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.2.357

Abstract

Recently, reverse engineering (RE) is becoming one of the essential engineering trends for software evolution and maintenance. RE is used to support the process of analyzing and recapturing the design information in legacy systems or complex systems during the maintenance phase. The major problem stakeholders might face in understanding the architecture of existing software systems is that the knowledge of software architecture information is difficult to obtain because of the size of the system, and the existing architecture document often is missing or does not match the current implementation of the source code. Therefore, much more effort and time are needed from multiple stakeholders such as developers, maintainers and architects for obtaining and re-documenting and visualizing the architecture of a target system from its source code files. The current works is mainly focused on the developer viewpoint. In this paper, we present a RE methodology for visualizing architectural information for multiple stakeholders and viewpoints based on applying the RE process on specific parts of the source code. The process is driven by eliciting stakeholders’ concerns on specific architectural viewpoints to obtain and visualize architectural information related these concerns. Our contributions are three fold: 1- The RE methodology is based on the IEEE 1471 standard for architectural description and supports concerns of stakeholder including the end-user and maintainer; 2- It supports the visualization of a particular part of the target system by providing a visual model of the architectural representation which highlights the main components needed to execute specific functionality of the target system, 3- The methodology also uses architecture styles to organize the visual architecture information. We illustrate the methodology using a case study of a legacy web application system.
Integrating Cognitive Antecedents to UTAUT Model to Explain Adoption of Blockchain Technology Among Malaysian SMEs Hamed Khazaei
JOIV : International Journal on Informatics Visualization Vol 4, No 2 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.2.362

Abstract

Blockchain technology is gaining consideration more and more and will potentially revolutionize most of the industries. Bitcoin cryptocurrency which uses Blockchain platform, has even promoted this technology more. Blockchain is a decentralized source and encrypted database for storing transaction information. Instead of being dependent on a centralised mediator like bank, by using blockchain, parties can transfer fund promptly trough connected ledgers called blocks. Using this method transactions will significantly be more transparent for both parties. Consequently, transactions are performed based on the distributed trust among other blockchain users in the network. Blockchain will promote transparency in every industry, yet implementation of blockchain technology is still limited. This study focuses to study the possible factors affecting adoption of blockchain technology by focusing on literature review and using Unified Theory of Acceptance and Use of Technology as a theoretical basis.
M-Learning: Positioning the Academics to the Smart devices in the Connected Future Tanweer Alam; Mohammed Aljohani
JOIV : International Journal on Informatics Visualization Vol 4, No 2 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.2.347

Abstract

M-learning is about using the massive growth of mobile technologies to benefit learners and learning. As computers and the internet become essential educational tools, the technologies become more portable, affordable, effective and easy to use. Using portable computing devices (such as laptops, tablet PCs, PDAs, and smartphones) with wireless networks enables mobility and mobile learning, allowing college teaching and learning to extend to spaces beyond the traditional classroom. Within the classroom, mobile learning gives university instructors and learners increased flexibility and new opportunities for interaction. Decision support systems can play an important role in decision making for the interaction of instructors and students. Mobile technologies can support learning experiences at the university level that are collaborative, accessible, and integrated with the world beyond the classroom educative learning initiative. In the proposed framework we will use a decision support system for taking some decisions using the system. The system will notify students when they need alert of lecture time, low attendance, meeting time, exam schedule notification, result etc. Also, the Framework will take quizzes periodically for improving the quality of learning of each class and send the result to the student as well as faculty and add this result in the record of the student in university. Students can ask general and technical questions from the system, system reply answer of general questions and send technical questions to the faculty, faculty reply through the system. The student also votes at the end of every lecture, if the system found against vote then send the message to the concerned faculty for improvement in the lecture.  My research will be more helpful for students and university teachers to increase flexibility and interaction with students more effectively.
Security Improvement Mechanisms in Software-Defined Internet of Things Seyedakbar Mostafavi; Hussaindad Saadat; Razieh Allamehzadeh
JOIV : International Journal on Informatics Visualization Vol 4, No 2 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.2.363

Abstract

The IoT contains millions of heterogeneous smart objects that are connected together through the Internet platform. These heterogeneous smart objects deal with different protocols, technologies and resources, therefore each of them requires diverse security services in heterogeneous environments. Therefore, providing security services in heterogeneous environments is a daunting task for network providers that cannot be guaranteed through the traditional network architecture. Wide distribution and openness of IoT smart objects makes them very vulnerable to attacks and it can be easily targeted by cyber-attacks. Software-Defined Networking (SDN) is a new paradigm that separates the control plane from data plane t a global network view by centralized controller. Integrating the software-defined network with the Internet of Things can provide better access control and security mechanisms. Software-defined networking provides better control and management possibilities to manage and secure Internet of Things in a good manner. In this paper, we discuss about IoT architecture, security challenges in IoT, SDN architecture, security challenges in each layers of the SDN and software-defined IoT. In addition, we provide solutions to security problems in IoT through software-defined networking approach.
Decompositions of Complete Multigraphs into Cyclic Designs Mowafaq Alqadri; Haslinda Ibrahim; Sharmila Karim
JOIV : International Journal on Informatics Visualization Vol 4, No 2 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (58.815 KB) | DOI: 10.30630/joiv.4.2.349

Abstract

Let  and  be positive integer,  denote a complete multigraph. A decomposition of a graph  is a set of subgraphs of  whose edge sets partition the edge set of . The aim of this paper, is to decompose a complete multigraph  into cyclic -cycle system according to specified conditions. As the main consequence, construction of decomposition of  into cyclic Hamiltonian wheel system, where , is also given. The difference set method is used to construct the desired designs.
An Automated Obstacle Detector and Path Finder Robotic Car Mohammad Shamiur Rahman Al Nahian; Arnab Piush Biswas
JOIV : International Journal on Informatics Visualization Vol 4, No 2 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1704.87 KB) | DOI: 10.30630/joiv.4.2.366

Abstract

This is to present you a simple and cost-efficient obstacle detecting mobile robot. Here a controlled rotating sonar sensor has been used to measure distance.  With this robot the angular and distance values are being sampled with the system support and being simplified to get a correct way through the given algorithm. The system was implemented in C++ type Arduino coding Software. Inputting the data and processing it in Arduino; all were digitally maintained; the digital pins of Arduino were used. And the outputs were controlled by the Arduino which were pre-given. This simple, cost efficient and mostly accurate project can be used in farming as well as defense and security sector of any country.
Image Processing Techniques on Radiological Images of Human Lungs Effected by COVID-19 A.M. Sirisha; P. Venkateswararao
JOIV : International Journal on Informatics Visualization Vol 4, No 2 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (102.272 KB) | DOI: 10.30630/joiv.4.2.359

Abstract

The wide spread of COVID-19 all over the world inspires every human to know and visualize its effect on human body. As   COVID-19 effects the human lungs here a number of radiological images of human lungs are analysed using an image processing technique called Threshold Segmentation. A significant difference is observed between healthy lung images and COVID-19 effected lung images.
A Survey of Predicting Heart Disease M Preethi; J Selvakumar
JOIV : International Journal on Informatics Visualization Vol 4, No 2 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (935.672 KB) | DOI: 10.30630/joiv.4.2.365

Abstract

This paper describes various methods of data mining, big data and machine learning models for predicting the heart disease. Data mining and machine learning plays an important role in building an important model for medical system to predict heart disease or cardiovascular disease. Medical experts can help the patients by detecting the cardiovascular disease before occurring. Now-a-days heart disease is one of the most significant causes of fatality. The prediction of heart disease is a critical challenge in the clinical area. But time to time, several techniques are discovered to predict the heart disease in data mining. In this survey paper, many techniques were described for predicting the heart disease.

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