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JOIV : International Journal on Informatics Visualization

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Published by Politeknik Negeri Padang

ISSN : 25499610 EISSN : 25499904 DOI : -

Core Subject : Science,

Computer Science & IT

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 8 Documents

Search results for , issue "Vol 1, No 3 (2017)" : 8 Documents clear

A MMSE-based Beamforming Algorithm for MIMO Point-to-Point Full-Duplex Communication Systems Tu Bui-Thi-Minh; Xung Le; Vien Nguyen-Duy-Nhat
JOIV : International Journal on Informatics Visualization Vol 1, No 3 (2017)
Publisher : Politeknik Negeri Padang

In this paper, we focus on the precoding design for sum rate maximization while considering the effects of residual SI for point – to-point multiple input/multiple output (MIMO) Full-Duplex systems. The MMSE-based beamforming algorithm was proposed to cancel the SI. The results shown that, the self-interference cancellation is done by matrix precoding at the transmitter if the total number of transmitting antenna of two nodes is greater than the number of receiving antenna of one node. The Bit Error Rate (BER) was also evaluated in the simulation.

A Survey on Data Mining Algorithms and Techniques in Medicine Kasra Madadipouya
JOIV : International Journal on Informatics Visualization Vol 1, No 3 (2017)
Publisher : Politeknik Negeri Padang

Medical Decision Support Systems (MDSS) industry collects a huge amount of data, which is not properly mined and not put to the optimum use. This data may contain valuable information that awaits extraction. The knowledge may be encapsulated in various patterns and regularities that may be hidden in the data. Such knowledge may prove to be priceless in future medical decision making. Available medical decision support systems are based on static data, which may be out of date. Thus, a medical decision support system that can learn the relationships between patient histories, diseases in the population, symptoms, pathology of a disease, family history, and test results, would be useful to physicians and hospitals. This paper provides an in-depth review of available data mining algorithms and techniques. In addition to that, data mining applications in medicine are discussed as well as techniques for evaluating them and available applications of performance metrics.

Bike Sharing Prediction using Deep Neural Networks Chandrasegar Thirumalai; Ravisankar Koppuravuri
JOIV : International Journal on Informatics Visualization Vol 1, No 3 (2017)
Publisher : Politeknik Negeri Padang

In this paper, we will use deep neural networks for predicting the bike sharing usage based on previous years usage data. We will use because deep neural nets for getting higher accuracy. Deep neural nets are quite different from other machine learning techniques; here we can add many numbers of hidden layers to improve the accuracy of our prediction and the model can be trained in the way we want such that we can achieve the results we want. Nowadays many AI experts will say that deep learning is the best AI technique available now and we can achieve some unbelievable results using this technique. Now we will use that technique to predict bike sharing usage of a rental company to make sure they can take good business decisions based on previous years data.

Smart Pump Operation Monitoring And Notification (PuMa) Via Telegram Social Messaging Application Mohamad Hanif Md Saad; Rabiah Adawiyah Shahad; Mohamad Zaki Sarnon; Muhammad Faiz Mohd Shukri; Aini Hussain
JOIV : International Journal on Informatics Visualization Vol 1, No 3 (2017)
Publisher : Politeknik Negeri Padang

Water supply system contains hydraulic components to supply water. The pumps are an important part in water distribution system and need to be well maintained for most of the time. The failure of pump operating system will result in the water shortage inside water tank. This phenomenon might occur due to the tripped pump and power. This paper proposed a remote monitoring and notification system applied in the pump house with the used of Complex Event Processing tools. Whereas, the notification system that act as an output adapter uses a Telegram Social Messaging application. The study is about how fast the notification system between using SMS and Telegram as an output adapter in the pump operation.

Blocking probability analysis of wireless sensors that employ opportunistic spectrum access L. Anusha; B Seetha ramanjaneyulu; K. Annapurna
JOIV : International Journal on Informatics Visualization Vol 1, No 3 (2017)
Publisher : Politeknik Negeri Padang

Opportunistic accessing of vacant channels of licensed spectrum by non-licensed wireless devices offers a convenient solution to the spectrum scarcity problems experienced by many wireless communication systems. Due to the fixed assignment policy of spectrum, some of the licensed frequencies are not in full utilization by their licensed users. On the other hand, there exists a severe scarcity of bandwidth for new wireless services. In this context, opportunistic access is found to be a boon, to overcome the spectrum scarcity problems. In this paper, opportunistic accessing of vacant channels by the wireless sensors is analysed. Finding the number of devices that can be supported for the available vacant bandwidth is the main focus of the work. Assessing the blocking probabilities experienced by the devices is found to offer an approximation of the number of devices that can be accommodated in a given scenario, for permissible blocking rates. This kind of analysis can help in proper planning of such wireless sensor networks, to deploy them in a way that they can make use of the white space bandwidths efficiently.

ExSIDE: Component Based Object Oriented Expert System’s Integrated Development Environment Mohamad Hanif Md Saad; Rabiah Adawiyah Shahad; Kong Win; Aini Hussain
JOIV : International Journal on Informatics Visualization Vol 1, No 3 (2017)
Publisher : Politeknik Negeri Padang

This paper describes the design and development of a component-based object oriented Expert System's Integrated Development Environment (ExSIDE). It is integrated with (i) a user-friendly manual and automated knowledge acquisition and management tool (ExSIDE_KAMT);(ii) an independent and customizable runtime module (ExSIDE_RTM); (iii) an object-oriented in-process Component Object Model (COM)-based inference engine (ExSIDE_IE); (iv) an object-oriented out-of-process COM-based inference engine (ExSIDE_IESvr); (v) and a PHP based inference engine (ExSIDE_PHP). ExSIDE_RTM can function independently as an Expert System Shell (ESS) and helps user to develop Expert Systems rapidly. ExSIDE_IE and ExSIDE_IES can be integrated with COM-supporting general purpose and scientific application development tools such as variants of C/C++/C#, BASIC (Visual BASIC®, REALbasic®), Java, MATLAB®, LabVIEW®, and Mathematica® to develop more advanced Expert Systems. Finally, ExSIDE_IE and ExSIDE_PHP can be used with Active Server Pages (ASP) and PHP technologies to generate web based Expert Systems. The unique framework of the ExSIDE enables rapid development of Expert Systems' on PC and web for technical and non-technical users. The overall system was developed successfully, and its usability was demonstrated via five unique Expert Systems case studies discussed in this paper.

Model-Based Resource Utilization and Performance Risk Prediction using Machine Learning Techniques Haitham A.M Salih; Hany H Ammar
JOIV : International Journal on Informatics Visualization Vol 1, No 3 (2017)
Publisher : Politeknik Negeri Padang

The growing complexity of modern software systems makes the performance prediction a challenging activity. Many drawbacks incurred by using the traditional performance prediction techniques such as time consuming and inability to surround all software system when large scaled. To contribute to solving these problems, we adopt a model-based approach for resource utilization and performance risk prediction. Firstly, we model the software system into annotated UML diagrams. Secondly, performance model is derived from UML diagrams in order to be evaluated. Thirdly, we generate performance and resource utilization training dataset by changing workload. Finally, when new instances are applied we can predict resource utilization and performance risk by using machine learning techniques. The approach will be used to enhance work of human experts and improve efficiency of software system performance prediction. In this paper, we illustrate the approach on a case study. A performance training dataset has been generated, and three machine learning techniques are applied to predict resource utilization and performance risk level. Our approach shows prediction accuracy within 68.9 % to 93.1 %.

Study on Blockchain Visualization Tri Sundara; Ideva Gaputra; Siska Aulia
JOIV : International Journal on Informatics Visualization Vol 1, No 3 (2017)
Publisher : Politeknik Negeri Padang

Blockchain as a distributed ledger system which provide underlying technology behind Bitcoin. Blockchain paradigm can be extended to provide a generalized framework for implementing decentralized compute resources. Some attempts has been made to visualize Blockchain transaction flow. This research aims to assess those attempts through systematic review.

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Contact Name
Rahmat Hidayat

Contact Email
mr.rahmat@gmail.com

Phone
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Journal Mail Official
rahmat@pnp.ac.id

Editorial Address
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Location
Kota padang,

Sumatera barat

INDONESIA

Abstract

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Abstract

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Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Rahmat Hidayat

Contact Email mr.rahmat@gmail.com

Phone -

Journal Mail Official rahmat@pnp.ac.id

Editorial Address -

Location Kota padang, Sumatera barat INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Rahmat Hidayat

Contact Email
mr.rahmat@gmail.com

Phone
-

Journal Mail Official
rahmat@pnp.ac.id

Editorial Address
-

Location
Kota padang,

Sumatera barat

INDONESIA