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Comparing the Immersive Levels of Trivia Hidden Object Game Paper-based and Game Applications Jahsy, Ibnu; Ilyas Nuryasin; Hardianto Wibowo
Journal of Games, Game Art, and Gamification Vol. 10 No. 1 (2025)
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/jggag.v9i2.11415

Abstract

The widespread development of the digital gaming industry in Indonesia began in 2000. The growth in interest in gaming has led to various objectives and encouraged research into several aspects and concepts of digital games. The aim of this research is to examine how significant the immersive differences are between paper-based game versions and applications/games among participants over 40 years old. The total average immersion obtained from the paper version is 4.43, while the application/game version is 5.85. For the average immersion per scale, the results of testing per scale show that the lowest average for the paper version is found in the Presence scale with 4.15, and the highest in Usability with 4.81. In the application/game version, the lowest average is found in the Focus Of Attention scale with a total of 5.55. The Usability scale scored 6.11, which is the highest result in the application/game version. The Interest scale is a category that has a significant difference between the paper and application/game versions with a margin of 1.6.
Analysis of the Combination of Naïve Bayes and MHR (Mean of Horner’s Rule) for Classification of Keystroke Dynamic Authentication Sari, Zamah; Chandranegara, Didih Rizki; Khasanah, Rahayu Nurul; Wibowo, Hardianto; Suharso, Wildan
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.839

Abstract

Keystroke Dynamics Authentication (KDA) is a technique used to recognize somebody dependent on typing pattern or typing rhythm in a system. Everyone's typing behavior is considered unique. One of the numerous approaches to secure private information is by utilizing a password. The development of technology is trailed by the human requirement for security concerning information and protection since hacker ability of information burglary has gotten further developed (hack the password). So that hackers can use this information for their benefit and can disadvantage others. Hence, for better security, for example, fingerprint, retina scan, et cetera are enthusiastically suggested. But these techniques are considered costly. The advantage of KDA is the user would not realize that the system is using KDA. Accordingly, we proposed the combination of Naïve Bayes and MHR (Mean of Horner’s Rule) to classify the individual as an attacker or a nonattacker. We use Naïve Bayes because it is better for classification and simple to implement than another. Furthermore, MHR is better for KDA if combined with the classification method which is based on previous research. This research showed that False Acceptance Rate (FAR) and Accuracy are improving than the previous research.
The Relationship Between Sitting Duration And Flexibility Hamstring Muscle In Employees At RSUD Ngimbang Wibowo, Hardianto; Rahmanto, Safun; Lubis, Zidni
JURNAL KEPERAWATAN DAN FISIOTERAPI (JKF) Vol. 6 No. 1 (2023): Jurnal Keperawatan dan Fisioterapi (JKF)
Publisher : Fakultas Keperawatan dan Fisioterapi Institut Kesehatan Medistra Lubuk Pakam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35451/jkf.v6i1.1712

Abstract

Some employees at Ngimbang Hospital work activities are carried out in a sitting position for a long duration and almost done every day, especially for office administration employees. This will pose a risk of musculoskeletal disorders, especially hamstring muscle flexibility. A decrease in muscle flexibility will affect body fitness which can affect the work productivity of these employees. This study aims to determine the relationship between sitting duration and hamstring muscle flexibility. This study used a Cross Sectional Study research design involving 32 employee samples. Sitting duration is the independent variable while the dependent variable is hamstring muscle flexibility. The results of the normality test using the Shapiro-wilk test showed that the sitting duration variable was worth 0.000 and the hamstring muscle flexibility variable was worth 0.799, meaning that there was one variable that was not normally distributed, while the correlation test using Spearman obtained a value of 0.000 (<0.05). It is concluded that there is a relationship between sitting duration and hamstring muscle flexibility in employees at Ngimbang Hospital. The longer the duration of sitting, the more hamstring muscle flexibility decreases.
Designing a QR Code Attendance System Using BYOD (Bring Your Own Device) Djamarullah, Ahmad Raihan; Nuryasin, Ilyas; Wibowo, Hardianto
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3522

Abstract

Attendance is an activity of collecting attendance data from each individual who attends events, work, and learning. The current application of attendance in certain companies, schools, or universities is still done manually using paper so it is considered less efficient and effective. Digitizing attendance activities can provide many benefits, such as making managing large amounts of attendance data easier. This is usually used in companies or schools. To reduce additional costs, this can be done by using a personal device as a medium for taking attendance, this can be called BYOD or Bring Your Own Device. The attendance that will be designed will use the user's smartphone or mobile device as a medium for taking attendance by scanning the QR code. The results of tests carried out using black box testing on mobile and web applications, shows that all the features contained in both applications are running according to their function. The use of QR Codes and also the implementation of BYOD can make it easier for users to take attendance. Apart from this, it is also easier for admins to manage user attendance data.
User Classification Based On Mouse Dynamic Authentication Using K-Nearest Neighbor Chandranegara, Didih Rizki; Ashari, Anzilludin; Sari, Zamah; Wibowo, Hardianto; Suharso, Wildan
Makara Journal of Technology Vol. 27, No. 1
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Mouse dynamics authentication is a method for identifying a person by analyzing the unique pattern or rhythm of their mouse movement. Owing to its distinctive properties, such mouse movements can be used as the basis for security. The development of technology is followed by the urge to keep private data safe from hackers. Therefore, increasing the accuracy of user classification and reducing the false acceptance rate (FAR) are necessary to improve data security. In this study, we propose to combine the K-nearest neighbor method and simple random sampling and obtain a sample from a dataset to improve the classification of users and attackers. The results show that our proposed method has high accuracy for implement to practical system and reports the best results than previous research with a FAR of 0.037. Therefore, this method can be implemented in a real login system. The high false rejection rate of our proposed method will not be a problem because the most important thing in the login system is denying the attacker system access.
Analysis of Pneumonia on Chest X-Ray Images Using Convolutional Neural Network Model iResNet-RS Chandranegara, Didih Rizki; Vitanti, Vizza Dwi; Suharso, Wildan; Wibowo, Hardianto; Arifianto, Sofyan
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.1728

Abstract

Pneumonia, a prevalent inflammatory condition affecting lung tissue, poses a significant health threat across all age groups and remains a leading cause of infectious mortality among children worldwide. Early diagnosis is critical in preventing severe complications and potential fatality. Chest X-rays are a valuable diagnostic tool for pneumonia; however, their interpretation can be challenging due to unclear images, overlapping diagnoses, and various abnormalities. Consequently, expedient, and accurate analysis of medical images using computer-aided methods has become crucial. This research proposes a Convolutional Neural Network (CNN) model, specifically the ResNet-RS Model, to automate pneumonia identification. The Contrast Limited Adaptive Histogram Equalization (CLAHE) technique enhances image contrast and highlights abnormalities in pneumonia images. Additionally, data augmentation techniques are applied to expand the image dataset while preserving the intrinsic characteristics of the original images. The proposed methodology is evaluated through three testing scenarios, employing chest X-ray images and pneumonia dataset. The third testing scenario, which incorporates the ResNet-RS model, CLAHE preprocessing, and data augmentation, achieves superior performance among these scenarios. The results show an accuracy of 92% and a training loss of 0.0526. Moreover, this approach effectively mitigates overfitting, a common challenge in deep learning models. By leveraging the power of the ResNet-RS model, along with CLAHE preprocessing and data augmentation techniques, this research demonstrates a promising methodology for accurately detecting pneumonia in chest X-ray images. Such advancements contribute to the early diagnosis and timely treatment of pneumonia, ultimately improving patient outcomes and reducing mortality rates.