JOIV : International Journal on Informatics Visualization
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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<![CDATA[Design of Personal Mobility Safety System Using AI ]]>
<![CDATA[Hyun Joo Park]]>;
<![CDATA[Kang-Hyeon Choi]]>;
<![CDATA[Jong-Won Yu]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021) ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.5.2.558
<![CDATA[In this paper, we propose the implementation of a safety device that generates an alarm sound or braking operation to reduce the risk of accidents. It reduces the exposure of risks due to non-wearing by supplementing the function of the helmet for safety. For machine learning, the safety state is learned by using two types of sensing data, and when an abnormal helmet use or speed or drinking driving is detected, an alarm sound is generated and motion is broken to maintain the safe state. By measuring data using a gas sensor, alcohol is checked and this is used as abnormal data. Users form a habit of wearing safety equipment with continuous safety alarm sound and speed braking and proper driving habit by driving in a normal state without drinking alcohol. In addition, the proposed system enables real-time monitoring, thereby reducing risks by continuously maintaining safe driving and wearing protective equipment. The proposed system uses artificial intelligence to discriminate data related to helmet wearing, speed, and drinking in making an electric kickboard for safety, and triggers an alarm or operates the brake to prevent abnormal driving. If the design and function are supplemented, it will become a basic function that can be applied to various equipment of transportation.]]>
<![CDATA[Data Mining Techniques for Pandemic Outbreak in Healthcare ]]>
<![CDATA[Nur Izyan Suraya Abdul Satar]]>;
<![CDATA[Azlinah Mohamed]]>;
<![CDATA[Azliza Mohd Ali]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021) ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.5.2.548
<![CDATA[Pandemic outbreaks such as SARS-CoV, MERS-CoV and Covid-19 have attracted worldwide attention since these viruses have affected many countries and become a global public health issue. In 2019, Covid-19 was announced as a pandemic disease and categorized as a public health emergency globally. It is ranked as the sixth most serious pandemic internationally. This pandemic tracking and analysis require an appropriate method that gives better performance in terms of accuracy, precision and recall that defines its pattern since it involves huge and complicated datasets from the pandemic. Pattern identification is currently applied in many instances due to the rapid growth of data besides having the potential to generate a knowledge-rich environment which can help to significantly improve the quality of clinical decisions and identify the relationships between data items. Therefore, there is a need to review the techniques in data mining on the pandemic outbreak that focuses on healthcare. The goal of this study was to analyze the algorithms from the data mining method that had been implemented for pandemic outbreaks in past research such as SARS-CoV, MERS-CoV and Covid-19. The result shows that 2 main algorithms, namely Naïve Bayes and Decision Tree, from the classification method, are appropriate algorithms and give more than 90% accuracy in both the pandemic and healthcare. This will be further considered and investigated for future analysis on large datasets of Covid-19 which can help researchers and healthcare practitioners in controlling the infection of the coronavirus using the data mining technique discussed.]]>
<![CDATA[Internet of Things-Based Energy Efficiency Optimization Model in Fog Smart Cities ]]>
<![CDATA[Wasswa Shafik]]>;
<![CDATA[S. Mojtaba Matinkhah]]>;
<![CDATA[Mamman Nur Sanda]]>;
<![CDATA[Fawad Shokoor]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021) ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.5.2.373
<![CDATA[In recent years, the IoT) Internet of Things (IoT) allows devices to connect to the Internet that has become a promising research area mainly due to the constant emerging of the dynamic improvement of technologies and their associated challenges. In an approach to solve these challenges, fog computing came to play since it closely manages IoT connectivity. Fog-Enabled Smart Cities (IoT-ESC) portrays equitable energy consumption of a 7% reduction from 18.2% renewable energy contribution, which extends resource computation as a great advantage. The initialization of IoT-Enabled Smart Grids including (FESC) like fog nodes in fog computing, reduced workload in Terminal Nodes services (TNs) that are the sensors and actuators of the Internet of Things (IoT) set up. This paper proposes an integrated energy-efficiency model computation about the response time and delays service minimization delay in FESC. The FESC gives an impression of an auspicious computing model for location, time, and delay-sensitive applications supporting vertically -isolated, service delay, sensitive solicitations by providing abundant, ascendable, and scattered figuring stowage and system associativity. We first reviewed the persisting challenges in the proposed state-of-the models and based on them. We introduce a new model to address mainly energy efficiency about response time and the service delays in IoT-ESC. The iFogsim simulated results demonstrated that the proposed model minimized service delay and reduced energy consumption during computation. We employed IoT-ESC to decide autonomously or semi-autonomously whether the computation is to be made on Fog nodes or its transfer to the cloud.]]>
<![CDATA[Identifying the Requirements of Visually Impaired Users for Accessible Mobile E-book Applications ]]>
<![CDATA[Nor Laily Hashim]]>;
<![CDATA[Munya Saleh Ba Matraf]]>;
<![CDATA[Azham Hussain]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021) ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.5.2.398
<![CDATA[Books are a medium for communicating information and in recent years have taken the electronic form called e-books. This shift has opened new opportunities for the visually impaired in overcoming their struggles with books in the traditional paper format. Yet, the National Federation of the Blind (NFB) claimed that many e-book applications do not meet needs of the visually impaired. Very few studies had investigated this subject matter hence paving the way for this current study to address the above research gap. As a result, equitable access to e-books for the visually impaired is still limited. Hence, there is now a necessity to design usable and accessible e-book interfaces for the visually impaired. To achieve this goal, it is important to identify the e-book requirements of the visually impaired into their e-book applications. An online survey was conducted involving seven visually impaired students at a local Malaysian university. The target participants’ ages are between 21 and 27 years old. The outcomes of this study identified ten requirements for accessible e-book applications for the visually impaired. Among these requirements are features that enable users to zoom, read aloud, and search for book contents. Besides that, screen reader strategy and text-to-speech are also mandatory. Other requirements include clear text and sound, ease of navigation, high contrast, and high brightness. These requirements will involve the field of Human-Computer Interaction design which is applied particularly in the development of usable and accessible mobile e-book applications for the visually impaired.]]>
<![CDATA[AP-based CW Synchronization Scheme in IEEE 802.11 WLANs ]]>
<![CDATA[Jin-Lee Lee]]>;
<![CDATA[Yeunwoong Kyung]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021) ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.5.2.553
<![CDATA[In this paper, an optimal CW (Contention Window) synchronization scheme is proposed in IEEE 802.11 WLANs. IEEE 802.11 WLANs operates with DCF (Distributed Coordination Function) mode for the MAC (Medium Access Control). In DCF, CW becomes the minimum CW according to the success of data transmissions and increases exponentially due to the collisions. In this situation, the smaller value of the minimum CW can increase the collision probability because stations have higher opportunity to access the medium. On the other hand, the higher value of the minimum CW will delay the transmission, which can result in the network performance degradation. In IEEE 802.11, since the base minimum CW value is a fixed value depending on the hardware or standard, it is difficult to provide the optimal network performance that can be determined by the flexible CW value according to the number of active stations. In addition, the synchronization of optimal CW is required among mobile stations to adapt the network parameters. Especially for the newly joined stations such as moving or turning on stations, they need to adapt the minimum CW value to get the optimal network performance. The shorter the adaptation time is, the better the network performance can maintain. Therefore, in this paper, AP (Access Point) calculates the optimal CW and shares it with mobile stations using beacon and probe response messages for the fast CW synchronization. Extensive simulation results show that the proposed scheme outperforms the previous schemes in terms of the network throughput and adaptation time. ]]>
<![CDATA[Real-time Triplet Loss Embedding Face Recognition for Authentication Student Attendance Records System Framework ]]>
<![CDATA[Hady Pranoto]]>;
<![CDATA[Oktaria Kusumawardani]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021) ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.5.2.480
<![CDATA[The number of times students attend lectures has been identified as one of many success factors in the learning process in many studies. We proposed a framework of the student attendance system by using face recognition as authentication. Triplet loss embedding in FaceNet is suitable for face recognition systems because the architecture has high accuracy, quite lightweight, and easy to implement in the real-time face recognition system. In our research, triplet loss embedding shows good performance in terms of the ability to recognize faces. It can also be used for real-time face recognition for the authentication process in the attendance recording system that uses RFID. In our study, the performance for face recognition using k-NN and SVM classification methods achieved results of 96.2 +/- 0.1% and 95.2 +/- 0.1% accordingly. Attendance recording systems using face recognition as an authentication process will increase student attendance in lectures. The system should be difficult to be faked; the system will validate the user or student using RFID cards using facial biometric marks. Finally, students will always be present in lectures, which in turn will improve the quality of the existing education process. The outcome can be changed in the future by using a high-resolution camera. A face recognition system with facial expression recognition can be added to improve the authentication process. For better results, users are required to perform an expression instructed by face recognition using a database and the YOLO process.]]>
<![CDATA[The Implementation of SAW and BORDA Method to Determine the Eligibility of Students’ Final Project Topic ]]>
<![CDATA[Dwiny Meidelfi]]>;
<![CDATA[- Yulherniwati]]>;
<![CDATA[Fanni Sukma]]>;
<![CDATA[Dikky Chandra]]>;
<![CDATA[Anna Hendri Soleliza Jonas]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021) ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.5.1.447
<![CDATA[The fourth-year students of Bachelor of Applied Studies (BAS) Software Engineering Technology Department of Information Technology (IT) Politeknik Negeri Padang (PNP) are required to work on the Final Project Proposal to the Coordinator, to deliver to the expertise group team to assess the eligibility of the topic. The expertise teams consist of the same skill family. The assessment criteria include originality, novelty, target and topic contribution, methodology, and similarity. Therefore, a system to support group decisions is highly needed to get eligibility for the topic. In a pandemic like today, indoor gatherings are severely restricted. The work from home policy also limits the movement of the team to gather together so that the expert team who would judge cannot conduct a meeting to determine the feasibility of the final project topic optimally. The existence of a subjective assessment of a particular topic requires discussion from the team. The simple Additive Weighting (SAW) method was used to rank the final project proposal, and BORDA method was used to Accumulate the assessment score of the expert team. The research revealed the recommendation on students’ final topics. Testing is done by testing the sensitivity of the criteria used in a decision maker's preference. The final result of this research is a recommendation of a final project that is feasible to be implemented by students and recommendation for sensitive assessment criteria. From the ten topics of the final project that were assessed, seven topics could be accepted. The sensitivity test results showed that the weight with criterion 1 and criterion 4 significantly affect the assessment results.]]>
<![CDATA[The Comprehensive Mamdani Inference to Support Scholarship Grantee Decision ]]>
<![CDATA[- Humaira]]>;
<![CDATA[- Rasyidah]]>;
<![CDATA[- Junaldi]]>;
<![CDATA[Indri Rahmayuni]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021) ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.5.2.449
<![CDATA[Fuzzy Mamdani has been mostly used in various disciplines of science. Its ability to map the input-output in the form of a surface becomes an interesting thing. This research took DSS case of a scholarship grantee. Many criteria in taking a decision need to be simplified so that the result obtained remains intuitive. The model completion by conducting two stages consisted of two phases. The first phase consists of four FIS blocks. The second phase consists of one FIS block. The FIS design in the first phase was designed in such a way so that the output obtained has a big score interval. FIS output at the first phase will become FIS input at the second phase. This big value range becomes good input at FIS in the second phase. Each FIS block has different total input. Until the surface formed must be seen from various dimensions to assure trend surface increasing or decreasing softly. This kind of thing is conducted by observing the movement of output dots kept for its soft surface form. The output dots change influenced by the membership function, the regulations used, total fuzzy set, and parameter value of membership function. This research used the Gaussian membership function. The Gaussian membership function is highly suitable for this DSS case. This article also explains the usage of a fuzzy set in each input, the parameter from the membership function, and the input value range. After observing the surface form with an intuitive approach, then this model needs to be evaluated. The evaluation was done to measure the model performance using Confusion Matrix. The result of model performance obtained accuracy in the amount of 85%.]]>
<![CDATA[3D CNN based Alzheimer’s diseases classification using segmented Grey matter extracted from whole-brain MRI ]]>
<![CDATA[Bijen Khagi]]>;
<![CDATA[Goo-Rak Kwon]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021) ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.5.2.572
<![CDATA[A recent study from MRI has revealed that there is a minor increase in cerebral-spinal fluid (CSF) content in brain ventricles and sulci, along with a substantial decrease in grey matter (GM) content and brain volume among Alzheimer's disease (AD) patients. It has been discovered that the grey matter volume shrinkage may indicate the possible case of dementia and related diseases like AD. Clinicians and radiologists use imaging techniques like Magnetic Resonance Imaging (MRI), Computed Tomography (CT) scan, and Positron Emission Tomography (PET) to diagnose and visualize the tissue contents of the brain. Using the whole brain MRI as the feature is an on-going approach among machine learning researchers, however, we are interested only in grey matter content. First, we segment the MRI using the SPM (Statistical parameter mapping) tool and then apply the smoothing technique to get a 3D image of grey matter (later called as grey version) from each MRI. This image file is then fed into 3D convolutional neural network (CNN) with necessary pre-processing so that it can train the network, to produce a classifying model. Once trained, an untested MRI (i.e. its grey version) can be passed through the CNN to determine whether it is a healthy control (HC), or Mild Cognitive Impairment (MCI) due to AD (mAD) or AD dementia (ADD). Our validation and testing accuracy are reported here and compared with normal MRI and its grey version.]]>
<![CDATA[Conceptual Model on Internet Banking Acceptance in China with Social Network Influence ]]>
<![CDATA[Guo Yi]]>;
<![CDATA[Norziha Megat Mohd. Zainuddin]]>;
<![CDATA[Nur Azaliah Bt Abu Bakar]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021) ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.5.2.403
<![CDATA[The Internet of Things and Industry 4.0 is changing the way we live including Internet Banking. Although, the government has been encouraging, the acceptance of internet banking is still not well received by Chinese customers. The reason is because they are more concerned about the economic development on the banking industry, and less concerned about technology acceptance and its development. This lack of acceptance is also attributed to the current lack of social network influence to internet banking which including its weak compliance, lack of identification, and lack of internalization. This paper aims to identify the factors that may be influencing IB acceptance by proposing a model which can determine customer’s behavioural intention based on social network influence. The TAM, UTAUT and the Social Influence Theory (SIT) were simultaneously adopted for this study. It is to use the TAM model’s perceived ease of use and perceived usefulness, the UTAUT model’s social influence, and the SIT’s compliance, identification and internalization factor for the analysis. For this purpose, a preliminary study was first administered so as to identify customers’ attitude of the IB acceptance. Thirty respondents were recruited for a structured interview. The behavioural intention and social network influence on internet banking in China was then examined with the proposed model. It appears that the model can be used to forecast Chinese customers’ acceptance of internet banking. It will give benefits to bank and society on paying attention to the influence of social network for internet banking in China.]]>
