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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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Virtual Reality (VR) in Superior Education Distance Learning: A Systematic Literature Review Christian, Bernuy; Salvador, Chumbe; Christian, Garcia
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.5.3.632

Abstract

Virtual Reality (VR) is one of the most popular contemporary technologies and it is widely used in the videogame industry, nonetheless, this does not restrict its use in other areas of science, such as medicine or education. Due to the large commotion caused by the appearance of Covid-19, long distance virtual education technologies (e-learning) are being used. With this context, virtual reality is the focus of this study, which had the objective of understanding the work done in superior education at a distance, through the use of VR, by doing a systematic literature review (SLR; LSR in Spanish). The results reveal that the use of VR in education can improve the experience, motivation and the comprehension of abstract concepts for the students, offering them an immersive environment in which they can interact and achieve effective learning. It was concluded that the works that were reviewed regarding the topic evidence a strong growth in the application of VR in education, which in their majority, employ experimental comparative methods between groups of students which use VR when compared to others who use the traditional method.
Real-time Estimation of Road Surfaces using Fast Monocular Depth Estimation and Normal Vector Clustering Yi, Chuho; Cho, Jungwon
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.5.3.641

Abstract

Estimating a road surface or planes for applying AR(Augmented Reality) or an autonomous vehicle using a camera requires significant computation. Vision sensors have lower accuracy in distance measurement than other types of sensor, and have the difficulty that additional algorithms for estimating data must be included. However, using a camera has the advantage of being able to extract various information such as weather conditions, sign information, and road markings that are difficult to measure with other sensors. Various methods differing in sensor type and configuration have been applied. Many of the existing studies had generally researched by performing the depth estimation after the feature extraction. However, recent studies have suggested using deep learning to skip multiple processes and use a single DNN(Deep Neural Network). Also, a method using a limited single camera instead of a method using a plurality of sensors has been proposed. This paper presents a single-camera method that performs quickly and efficiently by employing a DNN to extract distance information using a single camera, and proposes a modified method for using a depth map to obtain real-time surface characteristics. First, a DNN is used to estimate the depth map, and then for quick operation, normal vector that can connect similar planes to depth is calculated, and a clustering method that can be connected is provided. An experiment is used to show the validity of our method, and to evaluate the calculation time.
Analysis of Web-based Learning Interface Design based on Experts’ Verification for Higher Education Bakar, Zuriana Abu; Salim, Fatin Sarah; Zainuddin, Nor Fatin Farzana; Noor, Noor Maizura Mohamad; Mohemad, Rosmayati
JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.2.410

Abstract

Recently, the Web-based learning (WBL) platform, particularly for higher education, has become more crucial due to the Covid-19 pandemic. Thus, due to the increased use of WBL   in higher education, an effective WBL interface design for higher education is truly important in order to attract students to use WBL and to further keep them engaged during learning via the Web-based platform. Therefore, the aim of this study was to determine the aesthetics of web interfaces based on experts’ opinions. This study adopted a quantitative research approach involving a data-gathering survey. Fifteen (15) WBL interfaces were designed based on nine (9) design principles which were balance, proportion, simplicity, alignment, movement, hierarchy, consistency, contrast, and proximity. The results of this study discovered that nine (9) WBL interfaces were determined by the experts as aesthetic interfaces, five (5) WBL interfaces as non-aesthetic and 1 (one) WBL interface was considered neither aesthetic nor non-aesthetic. This finding revealed that six (6) out of nine (9) interfaces had the balance design principle. However, balance was also in most non-aesthetic interfaces. A possible reason that balance was the most design principle in both the aesthetic and the non-aesthetic interfaces is that when designing WBL interfaces, there is a need to consider the combination of the design principles as a whole, and not count the design principles individually. In conclusion, this study's findings could contribute to the knowledge in the Human Computer Interaction domain, specifically in the interface design area.
Hierarchical and K-means Clustering in the Line Drawing Data Shape Using Procrustes Analysis Ridho Ananda; Agi Prasetiadi
JOIV : International Journal on Informatics Visualization Vol 5, No 3 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.3.532

Abstract

One of the problems in the clustering process is that the objects under inquiry are multivariate measures containing geometrical information that requires shape clustering. Because Procrustes is a technique to obtaining the similarity measure of two shapes, it can become the solution. Therefore, this paper tried to use Procrustes as the main process in the clustering method. Several algorithms proposed for the shape clustering process using Procrustes were namely hierarchical the goodness-of-fit of Procrustes (HGoFP), k-means the goodness-of-fit of Procrustes (KMGoFP), hierarchical ordinary Procrustes analysis (HOPA), and k-means ordinary Procrustes analysis (KMOPA). Those algorithms were evaluated using Rand index, Jaccard index, F-measure, and Purity. Data used was the line drawing dataset that consisted of 180 drawings classified into six clusters. The results showed that the HGoFP, KMGoFP, HOPA and KMOPA algorithms were good enough in Rand index, F-measure, and Purity with 0.697 as a minimum value. Meanwhile, the good clustering results in the Jaccard index were only the HGoFP, KMGoFP, and HOPA algorithms with 0.561 as a minimum value. KMGoFP has the worst result in the Jaccard index that is about 0.300. In the time complexity, the fastest algorithm is the HGoFP algorithm; the time complexity is 4.733. Based on the results, the algorithms proposed in this paper particularly deserve to be proposed as new algorithms to cluster the objects in the line drawing dataset. Then, the HGoFP is suggested clustering the objects in the dataset used.
A Study on Analysis of Satisfaction for Engineering Convergence Subject Jaechoon Jo; Seungdo Jeong; Sunhee Kim; Kwangjae Lee; Hyunjoo Park
JOIV : International Journal on Informatics Visualization Vol 5, No 3 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.3.674

Abstract

Our world is quickly moving towards the fourth industrial revolution including mobile, big data, AI, IoT, cloud computing, VR, etc. Recently, South Korea has been emphasizing convergence education to university. Thus, university has begun doing convergence education on their own by linking major subjects and liberal arts courses or linking different departments. In this paper, we analyzed learners’ satisfaction for operating convergence education effectively to increase education satisfaction and developed convergence curriculum and convergence skills required by society. for this study, a satisfaction survey is conducted for students majoring in engineering colleges. And the students’ experiences are collected through interviews and questionnaires for suggesting improved the convergence curriculum operation. We also did interviews and asked students about the meaning convergence education had for them, the impressions they had after taking the classes, and any opinions for further improvements. As a result of the analysis of student's satisfaction and satisfaction of convergence curriculum, it was analyzed as “approximately satisfied” with 3.6. Additionally, the correlation between student satisfaction and convergence curriculum satisfaction was analyzed, and the correlation coefficient showed a significant correlation with 0.732. In other words, it can be seen that students with high-student satisfaction are also highly satisfied with the convergence curriculum. Based on the result of the research and the student’s opinions, we would like to suggest that there should be subject development that is connected to careers or job searching for senior students, and additional research of practical educational methods are also needed.
Development of an Artificial Intelligence Education Model of Classification Techniques for Non-computer Majors Youngseok Lee; Jungwon Cho
JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.2.552

Abstract

In the near future, as artificial intelligence and computing network technology develop, collaboration with artificial intelligence (AI) will become important. In an AI society, the ability to communicate and collaborate among people is an important element of talent. To do this, it is necessary to understand how artificial intelligence based on computer science works. AI is being rapidly applied across industries and is developing as a core technology to enable a society led by knowledge and information. An AI education focused on problem solving and learning is efficient for computer science education. Thus, the time has come to prepare for AI education along with existing software education so that they can adapt to the social and job changes enabled by AI. In this paper, we explain a classification method for AI machine learning models and propose an AI education model using teachable machines. Non-computer majors can understand the importance of data and the AI model concept based on specific cases using AI education tools to understand and experiment with AI even without the knowledge of mathematics, and use languages such as Python, if necessary. Through the application of the machine learning model, AI can be smoothly utilized in their field of interest. If such an AI education model is activated, it will be possible to suggest the direction of AI education for collaboration with AI experts through the application of AI technology.
Role Comparison between Deep Belief Neural Network and NeuroEvolution of Augmenting Topologies to Detect Diabetes A.B.M. Wijaya; D.S. Ikawahyuni; Rospita Gea; Febe Maedjaja
JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.2.448

Abstract

Diabetes in Indonesia has been perceived as a grave health problem and has been a concern since the early 1980’s [2]. The prevalence of diabetes in adults in Indonesia, as stated by IDF, was 6.2% with the total case amounting to 10.681.400. Moreover, Indonesia is also in the top ten global countries with the highest diabetes case in 2013. This research will investigate the role of Deep Belief Network (DBN) and NeuroEvolution of Augmenting Topology (NEAT) in solving regression problems in detecting diabetes. DBN works by processing the data in unsupervised network architectures. The algorithm puts Restricted Boltzmann Machines (RBM) into a stacked process. The output of the first RBM will be the input for the next RBM. On the other hand, the NEAT algorithm works by investigating the neural network architecture and evaluating the architecture using a multi-layer perceptron algorithm. Collaboration with a Genetic Algorithm in NEAT is the key process in architecture development. The research results showed that DBN could be utilized as the initial weight for Backpropagation Neural Network at 22.61% on average. On the other hand, the NEAT algorithm could be used by collaborating with a multi-layer perceptron to solve this regression problem by providing 74.5% confidence. This work also reveals potential works in the future by combining the Backpropagation algorithm with NEAT as an evaluation function and by combining it with DBN algorithms to process the produced initial weight.
Evaluation of Lossy Compressed Mosaic for SPOT-6/7 Remote Sensing Data in SPACeMAP Agnes S Payani; Siti D Wahyuningsih; Gusti D Yudha; Nico Cendiana; Hanna Afida; Steward Augusto
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.5.3.507

Abstract

SPACeMAP is a remote-sensing data portal system owned by LAPAN used to distribute mosaic data of Medium-Resolution to Very-High-Resolution for Provincial Governments. The frequently arising problem is that mosaic images have very large data size, especially for SPOT-6/7 mosaic images. The increasing number of data and users may affect the data loading process on the portal so that mosaic data compression can be considered. SPACeMAP has the Image Compressor feature using the Tile and Line algorithms with a compression ratio (target rate) recommended for optics (15 to 20). This study aims to determine the best algorithm and target rate to get compressed mosaic SPOT-6/7 imagery. The comparison method was done qualitatively through visual comparison and quantitatively by using Compression Ratio (CR), Bit per Pixel (BPP), and Peak Signal to Noise Ratio (PSNR).  Results of the experiment show that, quantitatively, both Tile and Line algorithms give a different performance, depends on the zoom level and land cover characteristics. In terms of the qualitative result, the Tile algorithm gives better overall results compare to the Line algorithm. Quantitatively, both algorithms show good performance in the homogenous area. The target rate difference on the testing range does not affect process duration, nevertheless, the Line algorithm has a long process duration compare to the Tile algorithm. However, compression mosaics with lower or higher resolution remote sensing data may provide different results. Hence, this need be addressed on further studies.
IT-Architecture Study Literature Research Collaboration: Malay Architecture Context Gun Faisal; Nina Fadilah Najwa; Muhammad Ariful Furqon; Fazrol Rozi
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.5.3.479

Abstract

Talking about architecture culture means talking about buildings and architecture. Architecture is a field of research that is always related to space and form. One of the exciting research topics on architecture is research on Malay architecture. Preserving Malay architecture is an important thing that must be done physically and meaningfully, positively impacting the community's development. The rapid development of information technology (IT) should be part of conservation efforts. IT supports various activities that significantly help conservation efforts. The role of IT in architecture is a significant research opportunity because of still little research on this topic. Thus, we conduct a study and analysis using a systematic literature review methodology to review IT-Architecture research, especially Malay architecture. The systematic literature review methodology consists of six stages, namely: (1) research question definition; (2) literature searching by keywords on literature sources; (3) literature assessment; (4) literature quality measurement; (5) data extraction and synthesis; and (6) research recommendation and suggestion. After going through the quality assessment process, only 37 papers were obtained that were relevant to the topic of IT-Architecture. The most discussed research themes in this literature review search were: (1) building information modeling (BIM) and augmented reality (AR) / virtual reality (VR); (2) BIM and geographic information system (GIS); and (3) BIM application and technology. However, based on literature searches, IT, and Malay architecture are still insufficient. Therefore, the topic of IT and Malay architecture still needs to be studied further in the future.
Data Analysis from Two-choice Decision Tasks in Visual Information Processing Kraleva, Radoslava; Kralev, Velin; Koprinkova-Hristova, Petia
JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.2.413

Abstract

Data analysis are important tasks in research. The present study focuses on the analysis of data sets from human eye movement experiments. The results of the experiments were analyzed according to two criteria – gender and age of the participants. The participants were divided into 3 groups, respectively group 1: between 20 and 35 years, group 2: between 36 and 55 years and group 3: between 56 and 85 years. The results showed that 75% of the two-choice decision tasks were solved correctly. This trend was maintained among the participants from group 1 – respectively 75.4%. The participants from group 2 gave more correct answers – respectively 82.2%, but the participants from group 3 gave fewer correct answers – respectively 70.2%. The average value of the response time indicator (of all participants) was 1455 ms. The response time of the participants from groups 1 and 2 was shorter than the average (respectively with 483 ms and 235 ms). The response time of the participants from group 3 was longer than the average (respectively with 626 ms).

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