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All Journal Gorga : Jurnal Seni Rupa Jurnal Ilmiah Poli Rekayasa JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Ilmiah Matrik JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Wimba: Jurnal Komunikasi Visual Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat International Journal of Advanced Science Computing and Engineering
Gusman, Taufik
Politeknik Negeri Padang
Arts Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences

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Journal : JOIV : International Journal on Informatics Visualization

 1 
Classifying Vehicle Types from Video Streams for Traffic Flow Analysis Systems Imran B. Mu’azam; Nor Fatihah Ismail; Salama A. Mostafa; Zirawani Baharum; Taufik Gusman; Dewi Nasien
JOIV : International Journal on Informatics Visualization Vol 6, No 1 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.1.739

Abstract

This paper proposes a vehicle types classification modelfrom video streams for improving Traffic Flow Analysis (TFA) systems. A Video Content-based Vehicles Classification (VC-VC) model is used to support optimization for traffic signal control via online identification of vehicle types.The VC-VC model extends several methods to extract TFA parameters, including the background image processing, object detection, size of the object measurement, attention to the area of interest, objects clash or overlap handling, and tracking objects. The VC-VC model undergoes the main processing phases: preprocessing, segmentation, classification, and tracks. The main video and image processing methods are the Gaussian function, active contour, bilateral filter, and Kalman filter. The model is evaluated based on a comparison between the actual classification by the model and ground truth. Four formulas are applied in this project to evaluate the VC-VC model’s performance: error, average error, accuracy, and precision. The valid classification is counted to show the overall results. The VC-VC model detects and classifies vehicles accurately. For three tested videos, it achieves a high classification accuracy of 85.94% on average. The precession for the classification of the three tested videos is 92.87%. The results show that video 1 and video 3 have the most accurate vehicle classification results compared to video 2. It is because video 2 has more difficult camera positioning and recording angle and more challenging scenarios than the other two. The results show that it is difficult to classify vehicles based on objects size measures. The object's size is adjustable based on the camera altitude and zoom setting. This adjustment is affecting the accuracy of vehicles classification.
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.
Modified Alexnet Architecture for Classification of Cassava Based on Leaf Images Sholihin, Miftahus; Md Fudzee, Mohd Farhan; Ismail, Mohd Norasri; Wati, Efi Neo; Arshad, Mohamad Syafwan; Gusman, Taufik
JOIV : International Journal on Informatics Visualization Vol 8, No 3 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3.2966

Abstract

The objective of this study is to address the drawbacks of conventional classification approaches through the implementation of deep learning, specifically a modified AlexNet. The primary aim of this study is to precisely categorize the four distinct varieties of cassava, namely Manggu, Gajah, Beracun, and Kapok. The cassava dataset was obtained from farmers in Lamongan, Indonesia, and was used as a source of information. Data collection on cassava leaves was carried out with agricultural research specialists. A total of 1,400 images are included in the dataset, with 350 images corresponding to each variety of cassava produced. The central focus of this research lies in a comprehensive evaluation of the modified AlexNet architecture's performance compared to the original AlexNet architecture for cassava classification. Multiple scenarios were examined, involving diverse combinations of learning rates and epochs, to thoroughly assess the robustness and adaptability of the proposed approach. Among the evaluation criteria that were rigorously examined were accuracy, recall, F1 score, and precision. These metrics were used to determine the predictive capabilities of the model as well as its potential utilization in the actual world. The results show that the modified AlexNet design has better performance than the original AlexNet for recall, accuracy, precision, and F-1 score, all achieving a rate of 87%. In situations where a learning rate of 0.0001 and an epoch count of 150 are utilized, the performance of the approach stands out significantly, displaying an excellent level of competency. Nevertheless, it is crucial to recognize that distinct fluctuations in performance were noted within particular contexts and with diverse learning rates.
Systematic Literature Review of Gender Bias within Video Games Character Design Ibrahim, Najwa Sabirah; Senan, Norhalina; Othman, Muhammad Fakri; Azmi, Shahdatunnaim; Erianda, Aldo; Gusman, Taufik
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.3297

Abstract

Gender bias in video games refers to the unequal treatment and discrimination that players experience based on gender, which is often normalized within the gaming community. Gender bias is widespread in Multiplayer Online Battle Arena (MOBA) games, where it can take many different forms. Common examples include assumptions made about players' abilities, character design in games, and the roles given to characters according to gender. This situation has created an unwelcoming environment, especially for female players, leading to feelings of exclusion. This study conducts a systematic literature review to examine gender bias in MOBA games, explicitly focusing on character representation, hypersexualized character models, and gameplay mechanics. By analyzing data from peer-reviewed articles, theses, and research papers, the study highlights the recurring patterns of bias and identifies gaps in current approaches. Although prior studies have explored the elements that contribute to gender bias, few studies have offered practical solutions to mitigate this bias. However, there is still a lack of research proposing a practical game design framework that integrates strategies to reduce this bias. In conclusion, efforts to address gender bias are not only significant in terms of design ethics, but also a good strategy in expanding the game's audience. This study identifies possible solutions that might help future research and be developed into a conceptual framework model that developers can understand to create a more inclusive, fair, and profitable gaming environment in the long term.
Virtual Campus Tour Application through Markerless Augmented Reality Approach Liang, Ang Wei; Wahid, Noorhaniza; Gusman, Taufik
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.743

Abstract

Augmented Reality (AR) technology has been widely used on campus tours by universities all around the world. However, the students that stay very far away do not have a chance to visit around the campus. Also, the information that is available on the official website is static, resulting in the visitors feeling less engaged with the information. Hence, the virtual campus tour application using the markerless AR technology, namely AR-UTHM Tour is proposed to be developed on the Android mobile-based platform to visualize the buildings and facilities that are available in the university, specifically Universiti Tun Hussein Onn Malaysia (UTHM). This approach allows the users to visualize the 3D models by pointing the camera at any flat surface. Then, the feature point will be generated to generate a virtual plane. The information about the facilities was obtained from the UTHM official website and the 3D models of the buildings were referred to the floor plan and the actual images. The user acceptance test has been conducted on 30 students of UTHM using Technology Acceptance Model (TAM). The result shows that more than 50% of the respondents have successfully executed the AR session without any error. Overall results show that the users are satisfied with the AR-UTHM Tour application. In conclusion, this application is suitable to be used as a medium to introduce and promote UTHM virtually. Future improvements in terms of detailing the aesthetic of the 3D model will be taken into consideration.
Vehicles Speed Estimation Model from Video Streams for Automatic Traffic Flow Analysis Systems Arriffin, Maizatul Najihah; Mostafa, Salama A.; Khattak, Umar Farooq; Jaber, Mustafa Musa; Baharum, Zirawani; Defni, -; Gusman, Taufik
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1820

Abstract

Image and video processing have been widely used to provide traffic parameters, which will be used to improve certain areas of traffic operations. This research aims to develop a model for estimating vehicle speed from video streams to support traffic flow analysis (TFA) systems. Subsequently, this paper proposes a vehicle speed estimation model with three main stages of achieving speed estimation: (1) pre-processing, (2) segmentation, and (3) speed detection. The model uses a bilateral filter in the pre-processing strategy to provide free-shadow image quality and sharpen the image. Gaussian filter and active contour are used to detect and track objects of interest in the image. The Pinhole model is used to assess the real distance of the item within the image sequence for speed estimation. Kalman filter and optical flow are used to flatten vehicle speed and acceleration uncertainties. This model is evaluated with a dataset that consists of video recordings of moving vehicles at traffic light junctions on the urban roadway. The average percentage for speed estimation error is 20.86%. The average percentage for accuracy obtained is 79.14%, and the overall average precision of 0.08.
Intervention Strategies through Interactive Gamification E-Learning Web-Based Application to Increase Computing Course Achievement Mohd Safar, Noor Zuraidin; Kamaludin, Hazalila; Ahmad, Masitah; Jofri, Muhammad Hanif; Wahid, Norfaradilla; Gusman, Taufik
JOIV : International Journal on Informatics Visualization Vol 6, No 2 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2.1001

Abstract

This study aims to help students improve their knowledge capability based on their active participation through gamification. Gamification is one of the newer methods of education that has the potential to improve student learning. This research looked into gamification's efficacy in student engagement and learning retention during teaching and learning sessions for computer science or information technology courses. The assessment involved in this study is through Pre-Test and Post-Test through instructional intervention by adapting interactive Quizizz gamification e-learning web-based application. The flow of research works begins with a survey of the problem, pre-intervention analysis, and action was taken during the intervention, ending with the implementation and observation phase. The pre and post-analysis of test results and questionnaires were accomplished and discussed. Fifty-six respondents participate in this study. Results show that 87% of the respondents have increased their percentage of marks. In the pre-test result, 56% of the respondents achieved below the 55 marks, while in the post-test, it reduced to 14%. Adoption of other gamification applications, a larger target demographic, and the addition of computer science or information technology courses will help improve the study in the future.
Study the Field of View Influence on the Monchromatic and Polychromatic Image Quality of a Human Eye Qasim, Adeeb Mansoor; Aljanabi, Mohammad; Kasim, Shahreen; Ismail, Mohd Arfian; Gusman, Taufik
JOIV : International Journal on Informatics Visualization Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.1-2.931

Abstract

In this paper, the effect of the eye field of view (known as F.O.V.) on the performance and quality of the image of the human eye is studied, analyzed, and presented in detail. The image quality of the retinal is numerically analyzed using the eye model of Liou and Brennan with this polymer contact lens. The image, which is in digital form were collected from various sources such as from photos, text structure, manuscripts, and graphics. These images were obtained from scanned documents or from a scene. The color fringing which is chromatic aberration addition to polychromatic effect was studied and analyzed. The Point Spreads Function or (known as PSF) as well as The Modulation Transfers Function (known as MTF) were measured as the most appropriate measure of image quality. The calculations of the image quality were made by using Zemax software. Then, the result of the calculation demonstrates the value of correcting the chromatic aberration. The results presented in this paper had shown that the form of image is so precise to the eye (F.O.V.). The image quality is degraded as (F.O.V.) increase due to the increment in spherical aberration and distortion aberration respectively. In conclusion, then Zemax software that was used in this study assist the researcher potential to design human eye and correct the aberration by using external optics.
Co-Authors Ahmad, Masitah Aldo Erianda, Aldo Aljanabi, Mohammad Ardian Firosha Arriffin, Maizatul Najihah Arshad, Mohamad Syafwan Asrinaldi Asrinaldi Asrinaldi Asrinaldi Azmi, Shahdatunnaim Baharum, Zirawani Danakorn Nincarean Eh Phon Deddy Prayama Defni, - Dewi Nasien Fhadel Wedi Pratama Firosha, Ardian Fitri Nova Nova Friadi, John Hendra Rotama Hidra Amnur Ibrahim, Najwa Sabirah Imran B. Mu’azam Ismail, Mohd Arfian Ismail, Mohd Norasri Jaber, Mustafa Musa Jofri, Muhammad Hanif Kamaludin, Hazalila Khattak, Umar Farooq Liang, Ang Wei Meri Azmi Meri Azmi Miftahus Sholihin Mohd Farhan MD Fudzee, Mohd Farhan Mohd Rustam Mohd Rameli Mohd Safar, Noor Zuraidin Mostafa, Salama A. Muhammad Umar Huzein Muhammad Yosazikri Ikhsan Najua Syuhada Ahmad Alhassora Nissa, Wirda Nor Fatihah Ismail Nurhatisyah Nurhatisyah Nurul Aswa Omar Othman, Muhammad Fakri PUTRI WAHYUNI Qasim, Adeeb Mansoor Rasyidah, - Rita Afyenni Ronal Hadi Roni Putra Safiani Osman Salama A. Mostafa Sean Rayhan Senan, Norhalina Shahreen Kasim, Shahreen Suci Ramadhani Sumema Sumema Sumema Sumema, Sumema Tri Lestari Wahid, Noorhaniza Wahid, Norfaradilla Wati, Efi Neo Windayati, Diana Titik Yance Sonatha Zirawani Baharum