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JOIV : International Journal on Informatics Visualization

joiv
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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.

Arjuna Subject : -

Articles 1,172 Documents

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

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.

Analysis of Network Function Virtualization and Software Defined Virtualization M. Sandeep Kumar; Prabhu j
JOIV : International Journal on Informatics Visualization Vol 1, No 4 (2017)
Publisher : Society of Visual Informatics

Network function virtualization (NFV) has played important role in both industry and academic change in telecommunication services. NFV has the ability to handle reduction on OPEX and CAPEX; it provides new service and also increases quickly in getting a time value. NFV has an opportunity in doing research in developing new innovation in architecture, framework, and measures some of the technology used in deploying in NVF. In this paper, the author describes the relation between NFV, SDV and cloud computing. Â The architecture of NVF its advantage in using network function virtualization and some activity used in NFV and adoption of NVF and future direction of NFV, issues, and difference in NFV and SDV.

Specific Language for Robot Trajectory Generation Kaloyan Yankov
JOIV : International Journal on Informatics Visualization Vol 1, No 4 (2017)
Publisher : Politeknik Negeri Padang

In this paper, a programming language for describing trajectories of the Mover 4 educational robot is discussed. The goal is to overcome the limitations of the programming tools provided by the manufacturer. Object-oriented structures of trajectories in the joint space and three-dimensional space are formulated. The model of the trajectory in the joint space is represented by the value of the joint, its velocity and acceleration, and the inertial tensor of the configuration from the respective joint to the end-effector. The inertia tensor is necessary to calculate joint forces and moments. A point from the trajectory in three-dimensional space is defined by the Cartesian coordinates of the end-effector, its orientation with the Euler angles and its velocity. Language offers spatial primitives to describe trajectories formed by segments, circle arcs, and cubic splines. Each primitive has a method of generating intermediate points. The language will allow the study of kinematic and dynamic capabilities in tracking trajectories.

Customer Profiling using Classification Approach for Bank Telemarketing Shamala Palaniappan; Aida Mustapha; Cik Feresa Mohd Foozy; Rodziah Atan
JOIV : International Journal on Informatics Visualization Vol 1, No 4-2 (2017): The Advancement of System and Applications
Publisher : Society of Visual Informatics

Telemarketing is a type of direct marketing where a salesperson contacts the customers to sell products or services over the phone. The database of prospective customers comes from direct marketing database. It is important for the company to predict the set of customers with highest probability to accept the sales or offer based on their personal characteristics or behavior during shopping. Recently, companies have started to resort to data mining approaches for customer profiling. This project focuses on helping banks to increase the accuracy of their customer profiling through classification as well as identifying a group of customers who have a high probability to subscribe to a long term deposit. In the experiments, three classification algorithms are used, which are NaÃ¯ve Bayes, Random Forest, and Decision Tree. The experiments measured accuracy percentage, precision and recall rates and showed that classification is useful for predicting customer profiles and increasing telemarketing sales.

Multilayered Framework to Enhance Management Information Systems Decision on Sensitive Data in Cloud Computing Environment Haifaa Jassim Muhasin; Rodziah Atan; Marzanah A.Jabar; Salfarina Abdullah; Shahreen Kasim
JOIV : International Journal on Informatics Visualization Vol 1, No 4-2 (2017): The Advancement of System and Applications
Publisher : Politeknik Negeri Padang

The purpose of this research is defining the main factors influencing on decision of management system on sensitive data in cloud. The framework is proposed to enhance management information systems decision on sensitive information in cloud environment. The structured interview with several security experts working on cloud computing security to investigate the main objective of framework and suitability of instrument, a pilot study conducts to test the instrument. The validity and reliability test results expose that study can be expanded and lead to final framework validation. This framework using multilevel related to Authorization, Authentication, Classification and identity anonymity, and save and verify, to enhance management information system decision on sensitive data in cloud.

A Digital Image Watermarking System: An Application of Dual Layer Watermarking Technique Châ€™ng Chen Phin; Nurul Hidayah Ab Rahman; Noraini Che Pa
JOIV : International Journal on Informatics Visualization Vol 1, No 4-2 (2017): The Advancement of System and Applications
Publisher : Society of Visual Informatics

Watermarking is a method to digitally sign a product to provide authentication and prevent copyright infringement to proving the ownership of a product and provides integrity for companies to protect their product. In this study, dual layer watermark that applies two different watermarking techniques at each layer is presented. The first layer applies the LSB Substitution technique while the second layer uses the Discrete Wavelet Transform (DWT) technique. This implies greater integrity as it contains of two signatures in providing authentication.

Classification of Alcohol Consumption among Secondary School Students Shamala Palaniappan; Norhamreeza A Hameed; Aida Mustapha; Noor Azah Samsudin
JOIV : International Journal on Informatics Visualization Vol 1, No 4-2 (2017): The Advancement of System and Applications
Publisher : Politeknik Negeri Padang

In 2016, the National Institute of Health reported that 26% of 8th graders, 47% of 10th graders, and 64% of 12th graders have all had experience in consuming alcoholic drinks. This finding indicates an accelerating trend in alcohol use among school students, hence a growing concerns among the public. To address this issue, this paper is set to model the alcohol consumption data among the secondary school students and attempt to predict the alcohol consumption behaviors among them. A set of classification experiments are carried out and the classification accuracies are compared between two variations of neural network algorithms; a self-tuning multilayer perceptron classifier (AutoMLP) against the standard MLP using the student alcohol consumption dataset. It is found that AutoMLP produced better accuracy of 64.54% than neural network with 61.78%.

Accuracy of Panoramic Dental X-Ray Imaging in Detection of Proximal Caries with Multiple Morpological Gradient (mMG) Method Jufriadif Na`am
JOIV : International Journal on Informatics Visualization Vol 1, No 1 (2017)
Publisher : Society of Visual Informatics

Dental caries is tooth decay caused by bacterial infection. This is commonly known as tooth decay. Classification of caries by location consists of; occlusal caries, proximal caries, root caries and caries enamel. Diagnosis of dental caries in general carried out with the help of radiographic images is called Dental X-Ray. Dental X-Ray consists of bitewing, Periapical and Panoramic. Identification of proximal caries using Dental Panoramic X-Ray lowest precision was compared with both other Dental X-Ray. This study aims to perform sharpening and improving the quality of information contained in the image of Panoramic Dental X-Ray to clarify the edges of the objects contained in the image, making it easier to identify and proximal caries severity. The methods and algorithms used are multiple Morphology Gradient (mMG). The results obtained are increased accuracy in identifying proximal caries 47.5%. Based on the severity of it, that level of enamel = 47.37%; dentin rate = 42.1% and the rate of dentin = 1.3%. Accuracy level of accuracy in identifying proximal caries a higher level of email, so that patients with proximal caries early levels can be tackled early handling by the dentist

An Application of Artificial Neural Networks and Fuzzy Logic on the Stock Price Prediction Problem Thanh Tung Khuat; My Hanh Le
JOIV : International Journal on Informatics Visualization Vol 1, No 2 (2017)
Publisher : Society of Visual Informatics

The financial industry has been becoming more and more dependent on advanced computing technologies in order to maintain competitiveness in a global economy. Hence, the stock price prediction problem using data mining techniques is one of the most important issues in finance. This field has attracted great scientific interest and has become a crucial research area to provide a more precise prediction process. Fuzzy logic (FL) and Artificial Neural Network (ANN) present an exciting and promising technique with a wide scope for the applications of prediction. There is a growing interest in both fields of fuzzy logic computing and the financial world in the use of fuzzy logic to predict future changes in prices of stocks, exchange rates, commodities, and other financial time series. Fuzzy logic provides a way to draw definite conclusions from vague, ambiguous or imprecise information. Artificial Neural Network is one of data mining techniques being widely accepted in the business area due to its ability to learn and detect relationships among nonlinear variables. The ANN outperforms statistical regression models and also allows deeper analysis of large data sets, especially those that have the tendency to fluctuate within a short of time period. In this paper, we investigate the ability of Fuzzy logic and multilayer perceptron (MLP), which is a kind of the ANN, to tackle the financial time series stock forecasting problem. The proposed approaches were tested on the historical price data collected from Yahoo Finance with different companies. Furthermore, the comparison between those techniques is performed to examine their effectiveness.

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 : Society of Visual Informatics

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.

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Home Page

OAI Link

Editorial Team

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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

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Abstract

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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

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