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JOIV : International Journal on Informatics Visualization
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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Implementation 2D Lidar and Camera for detection object and distance based on RoS Mulyanto, Agus; Borman, Rohmat Indra; Prasetyawan, Purwono; Sumarudin, A
JOIV : International Journal on Informatics Visualization Vol 4, No 4 (2020)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.4.466

Abstract

The advanced driver assistance systems (ADAS) are one of the issues to protecting people from vehicle collision. Collision warning system is a very important part of ADAS to protect people from the dangers of accidents caused by fatigue, drowsiness and other human errors. Multi-sensors has been widely used in ADAS for environment perception such as cameras, radar, and light detection and ranging (LiDAR). We propose the relative orientation and translation between the two sensors are things that must be considered in performing fusion. we discuss the real-time collision warning system using 2D LiDAR and Camera sensors for environment perception and estimate the distance (depth) and angle of obstacles. In this paper, we propose a fusion of two sensors that is camera and 2D LiDAR to get the distance and angle of an obstacle in front of the vehicle that implemented on Nvidia Jetson Nano using Robot Operating System (ROS). Hence, a calibration process between the camera and 2D LiDAR is required which will be presented in session III. After that, the integration and testing will be carried out using static and dynamic scenarios in the relevant environment. For fusion, we use the implementation of the conversion from degree to coordinate. Based on the experiment, we result obtained an average of 0.197 meters
Feature Selection Techniques for Selecting Proteins that Influence Mouse Down Syndrome Using Genetic Algorithms and Random Forests Fiqhri Mulianda Putra; Fadhlal Khaliq Surado; Global Ilham Sampurno
JOIV : International Journal on Informatics Visualization Vol 4, No 3 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.3.375

Abstract

Feature selection technique is a technique to reduce data dimensions which are widely used to find the set of features that best represent data. One area of science that often applies this technique is bioinformatics. An example of its application is the selection of significant proteins in the case of Down syndrome. To find out the most influential protein, experiments were carried out on normal mice with trisomy rats (down syndrome mice) totaling 1080 sample and obtained 77 levels of protein expression. The analysis carried out was divided into three groups. Each group was searched for the most influential proteins using genetic algorithms with fitness calculations using random forest algorithms. The results of the protein selection of the three data groups indicate the relationship of the selected proteins to the improvement of learning ability and memory. The results of evaluating selected protein models show a high degree of accuracy, which is above 98.7% for each data group.
Teler Real-time HTTP Intrusion Detection at Website with Nginx Web Server Tedyyana, Agus; Ghazali, Osman
JOIV : International Journal on Informatics Visualization Vol 5, No 3 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.3.510

Abstract

Web servers and web-based applications are now widely used, but in this case, the crime rate in cyberspace has also increased. Crime in cyberspace can occur due to the exploitation of how a system works. For example, the way HTTP works are exploited to weaken the webserver. Various tools for attacking the internet are also starting to be easy to find, but so are the tools to detect these attacks. One of the useful tools for detecting attacks and sending warnings against threats is based on the weblogs on the webserver. Many have not reviewed Teler as an intrusion detection system on HTTP on web servers because the existing tools are relatively new. Teler detecting the weblog and run on the terminal with rule resources collected from the community. So here, the researcher tries to implement the use of Teler in detecting HTTP intrusions on a Nginx-based web server. Intrusion is carried out in attacks commonly used by attackers, for example, port scanning and directory brute force using the Nmap and OWASP ZAP tools. Then the detection results will be sent via the Telegram bot to the server admin. From the results of the experiments conducted, it has been found that Teler is still classified as being able to send warning notifications with a delay between the time of detection and the time when the alert is received, no more than 3 seconds.
Autonomous Agents in 3D Crowd Simulation Through BDI Architecture Sim Keng Wai; Cheah WaiShiang; Muhammad Asyraf bin Khairuddin; Yanti Rosmunie Binti Bujang; Rahmat Hidayat; Celine Haren Paschal
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.371

Abstract

Agent based simulation (ABS) is a paradigm to modelling systems included of autonomous and interacting agents. ABS has been tremendous growth and used by researchers in the social sciences to study socio-environmental complex systems. To date, various platforms have been introduced for agent-based social simulation. They are rule based in any logic, python based in SPADE and etc. Although those platforms have been introduced, there is still an insufficient to develop a crowd simulation in 3D platform. Having a 3D platform is needed to enabling the crowd simulation for training purposes. However, the current tools and platform still lack features to develop and simulate autonomous agents in the 3D world. This paper introduced a BDI plug in at Unity3D for crowd simulation. BDI is an intelligent agent architecture and it is able to develop autonomous agents in crowd environment. In this paper, we present the BDI plug with a case study of Australia bush fire and discuss a method to support autonomous agents' development in 3D crowd simulation. The tool allows the modeller to develop autonomous agents in 3D world by taking the advantages of Unity3D.
Large Dataset Classification Using Parallel Processing Concept Mohammad Aljanabi; Hind Ra'ad Ebraheem; Zahraa Faiz Hussain; Mohd Farhan Md Fudzee; Shahreen Kasim; Mohd Arfian Ismail; Dwiny Meidelfi; Aldo Erianda
JOIV : International Journal on Informatics Visualization Vol 4, No 4 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.4.361

Abstract

Much attention has been paid to large data technologies in the past few years mainly due to its capability to impact business analytics and data mining practices, as well as the possibility of influencing an ambit of a highly effective decision-making tools. With the current increase in the number of modern applications (including social media and other web-based and healthcare applications) which generates high data in different forms and volume, the processing of such huge data volume is becoming a challenge with the conventional data processing tools. This has resulted in the emergence of big data analytics which also comes with many challenges. This paper introduced the use of principal components analysis (PCA) for data size reduction, followed by SVM parallelization. The proposed scheme in this study was executed on the Spark platform and the experimental findings revealed the capability of the proposed scheme to reduce the classifiers’ classification time without much influence on the classification accuracy of the classifier.
Laying Chicken Algorithm (LCA) Based For Clustering Yanto, Iwan Tri Riyadi; Setiyowati, Ririn; Irsalinda, Nursyiva; Rasyidah, -; Lestari, Tri
JOIV : International Journal on Informatics Visualization Vol 4, No 4 (2020)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.4.467

Abstract

Numerous research and related applications of fuzzy clustering are still interesting and important. In this paper, Fuzzy C-Means (FCM) and Laying Chicken Algorithm (LCA) were modified to improve local optimum of Fuzzy Clustering presented by using UCI dataset. In this study, the proposed FCMLCA performance was also compared to baseline technique based on CSO methods. The simulation results indicate that the FCMLCA method have better performance than the compared methods.
Single Image Dehazing Using Deep Learning Hartanto, Cahyo Adhi; Rahadianti, Laksmita
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.431

Abstract

Many real-world situations such as bad weather may result in hazy environments. Images captured in these hazy conditions will have low image quality due to microparticles in the air. The microparticles light to scatter and absorb, resulting in hazy images with various effects. In recent years, image dehazing has been researched in depth to handle images captured in these conditions. Various methods were developed, from traditional methods to deep learning methods. Traditional methods focus more on the use of statistical prior. These statistical prior have weaknesses in certain conditions. This paper proposes a novel architecture based on PDR-Net by using a pyramid dilated convolution and pre-processing modules, processing modules, post-processing modules, and attention applications. The proposed network is trained to minimize L1 loss and perceptual loss with the O-Haze dataset. To evaluate our architecture's result, we used structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), and color difference as an objective assessment and psychovisual experiment as a subjective assessment. Our architecture obtained better results than the previous method using the O-Haze dataset with an SSIM of 0.798, a PSNR of 25.39, but not better on the color difference. The SSIM and PSNR results were strengthened by using subjective assessments and 65 respondents, most of whom chose the results of the restoration of the image produced by our architecture.
GDSS Prototype Model for Supplier Selection at MDM Cooperative Azmi, Meri; Sonatha, Yance; Rahmayuni, Indri; Paboreal Dunque, Kristine Mae; Putra, Dwi Sudarno
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.473

Abstract

MDM is a trade cooperative business unit that supplies healthy food options for consumers around the Andalas University campus. So far, the selection of suppliers that provide supply goods to the stores is only based on the trust between both parties, which is the principle of mutual acquaintance and kinship. The problems that may arise from a process like this are the lack of the right supplier, unavailability of goods, relatively higher product prices, late delivery, and low-quality goods. Therefore, we need a GDSS that is capable of overcoming these problems. This GDSS helps in decision-making by determining the right supplier for each of the stores owned by the MDM Cooperative. The methods used are AHP, TOPSIS, and BORDA, involving six criteria and five tested alternatives. The AHP method is used to obtain the weight of each criterion taken from the pairwise comparison matrix. The TOPSIS method is used to determine which suppliers get priority for supply goods. Combining the AHP and TOPSIS methods can reduce the weaknesses of the TOPSIS itself by giving subjective weights. The use of the BORDA method can provide maximum results in selecting this supplier. This GDSS also involves three decision-making bodies: the head of the cooperative, the deputy, and the treasurer. The results of this prototype can show the best alternative selected based on the ranking method.
Cloud Computing Adoption Using TOE Framework for Indonesia’s Micro Small Medium Enterprises Gui, Anderes; Fernando, Yudi; Shaharudin, Muhammad Shabir; Mokhtar, Mazita; Karmawan, I Gusti Made; Suryanto, -
JOIV : International Journal on Informatics Visualization Vol 4, No 4 (2020)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.4.458

Abstract

Cloud computing is one of the pillars of the Industrial Revolution 4.0. Cloud computing provides ample benefits to companies such as mobility, ease of access, and enable collaboration. Nevertheless, the impact of cloud computing on the micro, small and medium enterprises (MSMEs) is not well established. This research aims to classify the factors affecting the acceptance of cloud computing in Indonesian MSMEs. A total of 135 participants participated in this analysis. The TOE Structure is used in this analysis. Methods of data collection using Google form. The details have been analysed with SPSS and SmartPLS. The findings demonstrated that top management encouragement and relative advantages have a positive impact on the adoption of cloud computing in MSMEs in Indonesia. In order to increase the adoption of cloud-based computing in Indonesia, cloud-based businesses need to concentrate on these two reasons so that MSMEs in Indonesia can embrace more cloud computing. Furthermore, the improvement of cloud computing adoption should come from government policy and incentives. Theoretically, this research helps to establish the TOE framework by providing empirical evidence. This research also explains that the TOE framework can help companies to understand critical domains that impact their businesses and which domain companies should focus.
Using Augmented Reality Application to Reduce Time Completion and Error Rate in PC Assembly Safiani Osman; Danakorn Nincarean Eh Phon; Nurul Aswa Omar; Mohd Rustam Mohd Rameli; Najua Syuhada Ahmad Alhassora; Taufik Gusman
JOIV : International Journal on Informatics Visualization Vol 4, No 3 (2020)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.3.245

Abstract

In the present context of globalization, the demand for assembly skill has increased and play an essential role in today’s industry. The traditional assembly instruction, face-to-face and manual instruction, may contain unimportant information that can result in misinterpretation, which in turn may increase the number of error and takes longer time to complete the task. A new technology (AR) claims to increase the efficiency of assembly task by directly visualizing computer generated 3D information in the real environment. Therefore, this study aims to determine the impact of AR on the time of task completion and the number of error made during the assembly task. The comparative user study was quantitative involving 18 users divided into either AR group or traditional group performing a pc assembly task. Statistical analysis revealed that the time of completion and error rate for two different group is statistically significant. The findings showed that the use of AR application has resulted in decreasing the number of error made and shorten the time to complete the task than the traditional instructional manual in assemble a pc. Considering these result, it can conclude that augmented reality application is an effective and beneficial tool to be applied in assembly and education.

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